Medication Development

for the Treatment of Cocaine

Dependence: Issues in

Clinical Efficacy Trials

Editors:

Betty Tai, Ph.D.

Nora Chiang, Ph.D.

Peter Bridge, M.D.

NIDA Research Monograph 175

1997

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

National Institutes of Health

National Institute on Drug Abuse

Office of Science Policy and Communications

5600 Fishers Lane

Rockville, MD 20857
ii

ACKNOWLEDGMENT

This monograph is based on the papers from a technical review

“Medication Development for the Treatment of Cocaine Dependence:

Issues in Clinical Efficacy Trials” held on October 20-21, 1994. The

review meeting was sponsored by the National Institute on Drug

Abuse.

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reproduced without permission from the Institute or the

authors. Citation of the source is appreciated.

Opinions expressed in this volume are those of the authors and

do not necessarily reflect the opinions or official policy of the

National Institute on Drug Abuse or any other part of the U.S.

Department of Health and Human Services.

The U.S. Government does not endorse or favor any specific

commercial product or company. Trade, proprietary, or

company names appearing in this publication are used only

because they are considered essential in the context of the

studies reported herein.

National Institute on Drug Abuse

NIH Publication No. 97-4125

Printed 1997

NIDA Research Monographs are indexed in the Index

Medicus. They are selectively included in the

coverage of American Statistics Index,

BioSciences Information Service, Chemical

Abstracts, Current Contents, Psychological

Abstracts, and Psychopharmacology Abstracts.
iii

Table of Contents

Click on title or page number to go to section

Preface..............................................................................................1

Betty Tai, Charles V. Grudzinskas, Nora Chiang, and

Peter Bridge

Goals and Rationale for Pharmacotherapeutic Approach

in Treating Cocaine Dependence: Insights From Basic and

Clinical Research...............................................................................5

Mary Jeanne Kreek

Overview of Potential Treatment Medications for Cocaine

Dependence.....................................................................................36

Elinore F. McCance

Methodologic Recommendations for Cocaine Abuse Clinical

Trials: A Clinician-Researcher’s Perspective....................................73

Edward V. Nunes

Management of Clinical Trials With New Medications for

Cocaine Dependence and Abuse......................................................96

Ari Kiev

Outcome Measurement Considerations: Pharmacological

Treatments for Substance Abuse....................................................118

Karla Moras

Variability in Treatment-Seeking Cocaine Abusers: Implications

for Clinical Pharmacotherapy Trials...............................................137

Kathleen M. Carroll, Charla Nich, and Bruce J. Rounsaville

Baseline Assessment, Study Entry, and Stabilization:

Double-Blind Clinical Trials in Drug Dependence.........................158

John Grabowski, Gila Arnoni, Ronith Elk, Howard Rhoades,

and Joy Schmitz

The Addiction Severity Index in Clinical Efficacy Trials of

Medications for Cocaine Dependence............................................182

John S. Cacciola, Arthur I. Alterman, Charles P. O’Brien,

and A. Thomas McLellan
iv

Cognitive-Neuromotor Assessment of Substance Abuse:

Focus on Issues Related to Cocaine Abuse Treatment.....................192

E.H. Ellinwood, Jr. and T.H. Lee

Treatment Effectiveness Score as an Outcome Measure in

Clinical Trials................................................................................208

Walter Ling, Steven Shoptaw, Donald Wesson, Richard A.

Rawson, Margaret Compton, and C. James Klett

Pharmacokinetics of Cocaine: Considerations When Assessing

Cocaine Use by Urinalysis.............................................................221

Reese T. Jones

Quantitative Urine Levels of Cocaine and Other Substances

of Abuse........................................................................................235

Jeffery N. Wilkins

Use of Quantitative Urinalysis in Monitoring Cocaine Use.............253

Kenzie L. Preston, Kenneth Silverman, Charles R. Schuster,

and Edward J. Cone

Is Quantitative Urinalysis More Sensitive?......................................265

Shou-Hua Li, Nora Chiang, Betty Tai, Charles K.

Marschke, and Richard L. Hawks

Comparison of Immunoassays for Semiquantitative Measurement

of Benzoylecgonine in Urine.........................................................287

Rodger L. Foltz, Christine Botelho, Scott A. Reuschel,

David J. Kuntz, David E. Moody, and Gloria M. Bristow

Appendix I: Workshop Summary Outcome Measures and

Success Criteria..............................................................................303

Betty Tai

Appendix II: Workshop Summary Clinical Decision Tree for

Cocaine Addiction Pharmacotherapy.............................................312

Betty Tai, Charles V. Grudzinskas, Peter Bridge, and

Nora Chiang
1

PREFACE

Betty Tai, Charles V. Grudzinskas, Nora Chiang, and

Peter Bridge

More than 23 million Americans have used cocaine at some time in

their lives, and more than 1.3 million are current cocaine users.

Cocaine abuse and dependence affect all segments of society with

devastating personal, social, and public health consequences.

Unfortunately, effective cocaine pharmacotherapies are lacking.

Accordingly, the National Institute on Drug Abuse (NIDA) has made

the development of an anticocaine medication its number one

priority.

More than 30 marketed medications have been tested in the last

decade for their effectiveness to treat cocaine addiction. Several

review articles (see Elinore F. McCance's chapter, this volume) were

published and general conclusions are: (1) most of the open trials

had positive results; however, when the studies were repeated in a

blinded manner, the results became negative, which leaves the

development potential of these medications unclear; (2) the clinical

research efforts were primarily focused on the evaluation of a broad

range of the marketed medications in the absence of reliable animal

and/or clinical models to predict clinical utility; and (3) the

heterogeneity across study design coupled with the lack of

standardization of methodology used by the researchers in

conducting these clinical studies made it impossible to evaluate and

compare results for different studies to determine which medications

should be advanced for further clinical evaluation.

One classical example of the lack of methodology standards can be

illustrated with the review of studies of desipramine, a tricyclic

antidepressant that has been widely prescribed to treat cocaine

dependence (Halikas et al. 1991). More than a dozen clinical studies

have been conducted and published since 1982. A meta-analysis of

the published trials was attempted (Levine and Lehman 1991). This

task proved to be extremely difficult because of the heterogeneity in

the design of the various studies. Some of the subjects who were

studied were primarily cocaine abusers, some were methadone

maintained, and others were dually diagnosed. The

inclusion/exclusion criteria were very different for each study.

Regarding dose regimens, the more recent studies provided blood

levels instead of doses. The protocol designs included

random/nonrandom, open/blind, and controlled/uncontrolled study

designs. In general, five categories of outcome measures have been

commonly used: psychiatric outcome measures, craving, subjective

drug effects, pattern of drug use, and retention in treatment. However,

in these published studies, the definitions of outcome measures varied;

the instruments and methods used in collecting the outcome measures

varied; the questions asked, the adjectives used in forming these

questions, and the scales used to assess the subjective effects varied;

the sources and frequency for monitoring drug use patterns varied;
2

and the ways the data were analyzed and expressed also varied. These

factors made it very difficult to interpret the study results and reach

conclusions about whether desipramine is or is not efficacious in

treating cocaine addiction.

In light of this, in 1992 the Medications Development Division

(MDD) of NIDA proposed the establishment of a Clinical Decision

Network, the objective of which was to create an alignment of opinion

leaders in academia, government, and the pharmaceutical industry to

address issues pertinent to conducting successful anticocaine clinical

efficacy trials. The specific goals for this Network were to: (1) ensure

that initial pharmacologic activity studies generated information that

would be useful in predicting future clinical efficacy, (2) develop

common outcome measures and consistent definitions of trial success

so that comparison across studies could be made, and (3) create a

Clinical Decision Tree to accelerate the development of treatment

medications for cocaine addiction.

A series of workshops have been conducted since 1992 to identify

and resolve the practical problems confronting researchers in

conducting cocaine medication efficacy trials.

• MDD Workshop I (4/20/92)

Identified the elements missing in the current clinical trial

paradigm and Task Forces appointed. Summary was reported in

the College on Problems of Drug Dependence (CPDD) (Tai

1992).

• MDD Workshop II (10/18/92)

Reviewed Task Force Proposals on outcome measures and success

criteria. Summary report published by MDD. (See appendix I.)
3

• MDD Workshop III (11/13/92)

Reviewed Task Force Proposals on Clinical Decision Tree.

Summary report presented at CPDD in 1993. (See appendix II.)

Workshop results were summarized and disseminated at 1992 and

1993 CPDD annual meetings and at the 1992 American College of

Clinical Pharmacology (ACCP) annual meeting. The culmination of

the effort of these workshops resulted in a NIDA Technical Review

meeting "Medications Development for the Treatment of Cocaine

Dependence: Issues in Clinical Efficacy Trials," which was held in

October 1994 at NIDA. The presentations at this Technical Review

were arranged into three sessions. The first session provided an

overview of the rationale for pharmacotherapeutical approaches and a

comprehensive review of the compounds tested in the past 5 years.

The second session targeted issues critical to the design,

implementation, analysis, and interpretation of clinical efficacy trials

for anticocaine addiction medications. The third and final session

focused on a thorough investigation of the limitations and

effectiveness of using qualitative and quantitative urinalysis, which is

one of the core outcome measures to assess cocaine use in the clinical

trials.

This monograph presents the proceedings of the October 1994

Technical Review. It is the editors’ hope that this monograph will

stimulate further research in the area of development and application

of more sensitive clinical trial methodologies for drug abuse research,

i.e.: (a) sensitive outcome measures (surrogate or direct) that

effectively measure medical improvement in short treatment periods,

(b) valid and reliable instruments to measure the above-mentioned

outcome measures, (c) animal and/or human pharmacological models

that are sensitive for predicting clinical relevance of testing

compounds, (d) impact of interaction with levels of psychosocial

support, and (e) the inclusion and exclusion criteria of subpatient

populations with comorbidity and polysubstance abuse and how they

affect the trial designs.

With sensitive methods and standardized processes, future trials may

be compared meaningfully and allow valid, critical development

decisions to be made to accelerate the identification, evaluation, and

development of anticocaine addiction medications.
4

REFERENCES

Halikas, J.A.; Crosby, R.D.; and Carlson, G.A. Current pharmacotherapy

practices for cocaine abuse. Ann Clin Psychiatry 3:167-

168, 1991.

Levine, F., and Lehman, A. Meta analysis of desipramine as an adjunct in

the treatment of cocaine addiction. J Clin

Psychopharmacology 116:374-378, 1991.

Tai, B. The role of clinical pharmacology in predicting clinical efficacy.

In: Harris, L.H., ed. Problems of Drug Dependence, 1992:

Proceedings of the 54th Annual Scientific Meeting of the

College on Problems of Drug Dependence. National

Institute on Drug Abuse Research Monograph 132. NIH

Pub. No. 93-3505. Washington, DC: Supt. of Docs., U.S.

Govt. Print. Off., 1992. p. 42.

AUTHORS

Betty Tai, Ph.D.

Chief, Regulatory Affairs Branch

Medications Development Division

Charles V. Grudzinskas, Ph.D.

Director, Medications Development Division

Nora Chiang, Ph.D.

Chemistry and Pharmaceutics Branch

Medications Development Division

Peter Bridge, M.D.

Chief, Clinical Trials Branch

Medications Development Division

National Institute on Drug Abuse

Parklawn Building, Room 11A-55

5600 Fishers Lane

Rockville, MD 20857
5

Goals and Rationale for

Pharmacotherapeutic Approach in

Treating Cocaine Dependence: Insights

From Basic and Clinical Research

Mary Jeanne Kreek

The early research conducted in the author’s laboratory from 1975

onward stemmed from the even earlier work, beginning in 1964 when the

author was a member of the laboratory of Professor Vincent P. Dole at the

Rockefeller Institute for Biomedical Research (now the Rockefeller

University) (Dole et al. 1966; Kreek 1972, 1973a; Kreek et al. 1972). At

that time, scientists were challenged to develop a treatment for opiate

dependency, a problem that is still being addressed, but for which there

are now three different pharmacotherapeutic approaches approved by the

Food and Drug Administration (FDA), and a fourth under investigation.

This chapter will review briefly some of the early concepts because they

are relevant for the current major problem: developing a new medication

(and possibly a variety of medications) for treating cocaine dependency.

In 1964, researchers had recognized the need to develop a pharmacotherapy for the treatment of opiate dependency, because the most humane

and excellent drug-free approaches were not effective for the majority of

patients. It must be emphasized from the outset that any

pharmacotherapy for managing any addictive disease must be carried out

in concert with excellent psychosocial interventions, with counseling and

rehabilitation efforts. The very complex disorders of any one of the

addictive diseases can only infrequently be managed with chemotherapy

alone. Researchers have to be as realistic with respect to cocaine

dependency, as they were 30 years ago with respect to opiate dependency.

It should be remembered that even the very best “drug free”

psychosocial and rehabilitation approaches alone have been successful for

extended periods of time in only a limited number of persons, and have

been far too limited to accept these as the only approaches available for

treatment. Ultimately, what is needed in most cases of both opiate and

cocaine addiction is combination therapy. This chapter, however, will be

limited to pharmacotherapy.

Several recent studies, including the high school student and household

surveys, have elucidated the current magnitude of the cocaine problem. It

is estimated that around 24 million people in the United States have used

cocaine at some time; over 3 million are occasional cocaine users; about
6

1.3 million are current cocaine users, and at least 600,000, and maybe

many more, are very frequent users, defined as multiple uses each week,

either by “binge” pattern or a regular daily use pattern (Kreek 1996). It

should be asked, “For which one of these groups are researchers seeking

to develop pharmacotherapy?” This is a question that has not been

addressed as potential medications for treatment have been identified and

clinical trials for treatment of cocaine addiction have been conducted.

Researchers have failed to ask, “For whom is this particular medication

targeted?” or more generally, “For what group of persons afflicted with

chemical dependency problems, of what type, severity and duration?”

These questions are critical. If a nicotine patch is used on someone who

smokes only 1 cigarette a day, the investigator or clinician may be dealing

with a very different situation, and thus outcome, than when investigating,

or attempting to treat someone who smokes 10 cigarettes or 3 packs of

cigarettes a day. Results may be different because the neurobiology, as

well as the behaviors, are different. Researchers need to develop

operational definitions and guidelines, such as in 1964 when the author

and her colleagues were forced, over a brief period of time, to define

opiate addiction. The original operational definition was multiple daily

doses of opiate use, usually heroin, with the development of tolerance,

physical dependence, and drug-seeking behavior, and a duration of that

pattern of behavior for 3 years or more. In a stepwise manner, with the

advice of the author’s group and many others, the official definition of

“3 years” has been, as of 1983, reduced to 1 year of that pattern of

behavior, and thus defined the duration of addiction. The Institute of

Medicine has published recommendations on the regulations governing

methadone treatment (Rettig and Yarmolinsky 1994); the FDA and the

Drug Enforcement Agency (DEA) may be considering the available

information supporting the concept that even 1 year of daily illicit opiate

use may be too long to demand for entry into a pharmacotherapy using

an opioid agonist or, alternatively, partial agonist, such as methadone, lalpha-acetylmethadyl (LAAM), or in the future, possibly buprenorphine

(Rettig and Yarmolinsky 1994). The 3-, then 2-, and now 1-year length

of addiction requirement is based on the operational definition first

formulated in 1964. It still is an operational, not a medical or

neurobiological definition, but it has served clinical scientists, clinicians,

and policymakers very well because groups of subjects can be compared

with respect to their response to treatment, as well as their neurobiology

status. There is a definite need now to define different levels of cocaine

dependency at an operational level, which will understandably be

imperfect biologically, but at least will allow for more effective

comparison of clinical and fundamental studies.
7

If researchers believed that cocaine dependency was solely a behavior that

occurs in a social and environmental context, with no neurobiological

ramifications, that is, with both no possible predisposition on a genetic

basis, and/or with no persistent or permanent alterations of physiology as a

result of its use, then no one would discuss the need for development of a

pharmacotherapeutic agent. However, irrespective of the hypotheses that

may be formulated and addressed, most agree that there are probably

either genetic factors that confer or augment vulnerability to develop each

of the specific addictions, and/or persistent or permanent changes effected

by the drug of abuse, which may contribute to, or cause, the acquisition

and perpetuation of the drug-seeking behavior and also the persistence of

“drug hunger” or craving, with the proclivity for relapse. Especially

important for cocaine addiction is the profound craving associated with

the cocaine-abstinent state. However, any genetic or neurobiological

factors must be considered in a contextual setting, including: the

individual’s stage of development, what other kinds of exposures there

have been (including both diseases and drugs), and the individual’s

response to stressors. Also important is the overall environment, and

especially the set and setting of drug exposures and related economic

factors.

The goals and rationale for the development of a pharmacotherapy for

addictions have evolved in the author’s laboratory over the past 20 years,

based in part on early conceptualizations 30 years ago with respect to

opiate dependency and, more recently, with respect to both cocaine

dependency and alcoholism (Dole et al. 1966; Kreek 1972, 1973a, 1973c,

1978, 1991, 1992a, 1992b, 1992c; Kreek and Hartman 1982).

First, an agent must prevent any physiologically based withdrawal

symptoms (Kreek 1992c). This is especially important with opiate

dependency, though possibly of lesser importance with respect to cocaine

dependency. However, there are dramatic histories and presentations in

the literature of cocaine withdrawal symptoms, especially in the outpatient

setting, where cues and other conditioned factors may play a dominant

role. In a quiet, stress-minimized inpatient setting, such as that of the

clinical research group at the Addiction Research Center, which is the

intramural program of the National Institute on Drug Abuse (NIDA) and

the author’s laboratory at the Rockefeller University resource at the NIHsupported General Clinical Research Center (GCRC) of the Rockefeller

University Hospital, as well as in other clinical investigators’ settings, only

modest to absent withdrawal symptoms have been described in recently

abstinent cocaine addicts (Cambor et al. 1992; Ho et al. 1992).
8

Secondly, a pharmacotherapeutic agonist needs to reduce drug craving or

“hunger.” For cocaine dependency, this goal has to be at the top of the

list. Long after the cocaine “binge” is over and the cocaine has cleared

the body and the major benzoylecgonine (BE) and the other metabolites

are gone, craving still persists (Kreek 1992c). In fact, relapse may be seen

at very distant timepoints and, although cues and conditioning play a role,

cravings have arisen in very sterile settings such as a clinical inpatient

research unit.

The third goal of any specific pharmacotherapy is normalization of

physiological functions disrupted by drug use. Functions that have been

disrupted may be epiphenomena. However, it is important to note that

some of the disruptions are of the stress-responsive axis, which has been

hypothesized to contribute to the perpetuation of drug-seeking behavior.

Finally, any medication ideally should be targeted to a specific site of

action, a receptor, or a physiological system, which has been affected or

deranged by the drug of abuse in a very specific manner. Therefore, it is

imperative that it is clear what the drugs of abuse do, where they act, what

the actions are, and what the immediate as well as distant ramifications are,

on a biological and neurobiological basis.

After recruitment as a resident in internal medicine at New York Hospital

Cornell Medical Center in the autumn of 1963 by Professor Vincent P.

Dole, the author had the opportunity to do a research elective at the

Rockefeller Institute for Biomedical Research and in early 1964, to join

Professor Dole and the late Dr. Marie Nyswander, who also arrived at that

time, in the initial research efforts to address the following question:

Could a pharmacotherapy for opiate dependency be developed? Some of

the criteria for a research pharmacotherapeutic agent then and now are:

(1) ideally, the medication should be orally effective; (2) there should be

a slow onset of action of that medication to eliminate any reinforcing

effects of the agent, so it would not become a primary drug of abuse; and

(3) the drug should be long-acting with a gradual offset, as well as onset,

of action.

Methadone, which at that time had been studied to a very limited extent,

and used in few resources for the “detoxification” of heroin addicts, met

all three of these criteria. In 1964, there were no analytical techniques to

measure sensitively and specifically any opiate in blood or even in urine;

thus clinical observations had to be used to assess the pharmacology of a

potential research treatment agent, based on the observed pharmacodynamics. In addition, at that time, a medication was sought that could be

given in doses that would not cause euphoria or any other kind of opiate

effect. This was achieved with methadone. However, in some early
9

research studies, when doses of methadone were given that exceeded the

degree of tolerance developed by the individuals, although true euphoria

was not observed, somnolence and sleepiness occurred. If a dose of

methadone was selected initially to be less than that for which tolerance

has been developed by the individual, no euphoria, no sleepiness, and no

other narcotic-like effects would be detected. The dose then could be

ascended slowly to achieve ultimately a dose that provides not only

tolerance, but cross-tolerance to other opiate drugs. Through the

mechanism of cross-tolerance the effects of any super-imposed shortacting opiates are “blockaded” (Dole et al. 1966). Finally, a medication

should prevent withdrawal symptoms. This may be of lesser importance

with respect to the management of cocaine dependency since in a

controlled, stress-minimized environment such as a hospital or clinical

research unit, withdrawal symptoms following cessation of cocaine use are

minimal (Cambor et al. 1992; Ho et al. 1992). However, each one of

these characteristics must be sought in the development of

pharmacotherapeutic agents for the management of cocaine dependency.

Also, for cocaine dependency, like the case of opiate dependency, where it

has been clearly desirable to have more than one therapeutic agent, it

would be desirable to have several pharmacotherapeutic agents with

different actions and mechanisms of action to manage the diverse

populations needing treatment.

By 1972, two groups then working independently (now both part of the

NIH-NIDA Research Center) developed techniques for measuring plasma

levels of methadone, using gas-liquid chromatography (Dole and Kreek

1973; Inturrisi and Verebely 1972, 1973; Kreek 1973b, Kreek et al.

1976). Researchers found precisely what was observed clinically, that is,

after a single oral dose of methadone during chronic steady-dose

treatment, there is a sustained plasma level over a 24-hour dosing interval

(Inturrisi and Verebely 1973; Kreek 1973b). Secondly, the rise to peak

level is gradual, with a resultant gradual onset of action; the peak levels do

not occur until 2 to 4 hours after the oral dose is given. The peak plasma

levels are very modest, barely a doubling of the nadir. With this slow rate

of rise and low peak levels, thus the very slow onset of action, no

reinforcing effects or narcotic-like effects are expected, if the proper dose

has been administered. From a kinetic standpoint, whereas heroin has a

half-life in humans of 1 to 2 hours, and the major morphine metabolite of

heroin is 4 to 6 hours, methadone has a half-life of 24 hours in man

(Inturrisi and Verebely 1972, 1973; Kreek 1973b). Using stable isotope

techniques to label both the active and inactive enantiomer of methadone

with different amounts of deuterium at specific nonmetabolically reactive

sites, the author and her colleagues were able to define, using chemical

ionization mass spectrometry, that the half-life of the active l-enantiomer
10

was 48 hours (Hachey et al. 1977; Kreek et al. 1979; Nakamura et al.

1982). This long-acting profile of methadone occurs uniquely in

humans. In rodents, methadone has a half-life of about 60 to 90 minutes,

similar to that of morphine (Kreek 1979). Thus, the pharmacokinetic

profile would have been able to be elucidated only in humans, where it

would be ultimately determined.

In good treatment programs, steady and adequate doses of methadone are

used, 60 to 120 mg/d for the average patient, after slow escalation from

initial lower doses, followed by stabilization of dose (Dole et al. 1966;

Kreek 1991, 1992a, 1992b, 1992c). Use of stabilized doses in treatment

is critical. One should never use changes in methadone dosage to effect a

behavioral change, or use dose changes in a contingency contract for

behavior modification. Doses must be kept constant. Otherwise, the

rationale and proven mechanism of methadone action as used in

appropriate pharmacotherapy is impaired and the desired normalization

of disrupted physiology is not achieved. In good programs, there should

also be concomitant rehabilitation efforts, psychosocial support systems,

and access to medical and psychiatric care. Also, in good programs that

combine adequate and stable doses of methadone combined with other

psychosocial, counseling, and medical services, retention in 1964 and

retention in 1994 (as in the two clinics connected with the NIDA Research

Center) ranges from 70 percent to 85 percent, and, after the first 6 months

of stabilization in treatment, continuing use of heroin drops to below 15

percent. The actions of methadone prevent withdrawal symptoms and

also prevent “drug hunger” or craving, that is, the desire to use other

illicit opiates (Dole et al. 1966; Kreek 1991, 1992a, 1992b, 1992c; Rettig

and Yarmolinsky 1994). However, the blockade of the euphorogenic or

other narcotic-like effects of any superimposed short-acting opiates that is

achieved by adequate steady-dose methadone treatment also means that,

when on methadone, a patient who tries to get a euphoric or “high”

sensation from illicit heroin cannot do so unless extraordinarily large and

expensive amounts of heroin are used. In the author’s original titration

studies, over $200 equivalent of illicit heroin purchased on the streets of

New York administered intravenously in a single dose was needed to

override the cross-tolerance developed by a full blockading treatment

dose, i.e., 60 to 120 mg/day of methadone (Dole et al. 1966).

For any pharmacotherapy to be developed for treatment of cocaine

addiction, it may be essential both to block the acute reinforcing and

euphorogenic effects of cocaine, and also reduce or eliminate the chronic

and persistent craving for cocaine which leads to relapse. It may or may

not be found that a single pharmacotherapeutic agent can effect both of

these desired effects, since there is evidence from the author’s laboratory
11

that more than one neurobiological mechanism may be involved (Branch

et al. 1992; Kreek 1987; Maggos et al. 1995; Maisonneuve and Kreek

1994; Maisonneuve et al. 1995; Spangler et al. 1993a, 1993b, 1994,

1995; Unterwald et al. 1992, 1993, 1994a, 1994b).

It was also seen that during chronic long-term methadone maintenance

treatment, when a stable moderate to high dose of methadone was used,

there was normalization of several physiological functions that were

critical for normal survival functions as well as for generalized well-being,

including behavioral and emotional status, which were functions that were

disrupted by chronic use of heroin. Normalization of the stressresponsive hypothalamic-pituitary-gonadal axis, and also normalization of

the hypothalamic-pituitary-adrenal axis involved in reproductive

behaviors and biology, occur during chronic steady-dose treatment

(Cushman and Kreek 1974a; Kennedy et al. 1990; Kosten et al. 1987,

1992; Kreek 1972, 1973a, 1978, 1992c; Kreek and Hartman 1982; Kreek

et al. 1981, 1983, 1984a, 1984b). A moderate extent of normalization to

prolactin responsivity occurs, although there is still responsivity of

prolactin release as reflected by peak levels of prolactin at the time of

peak plasma levels of methadone. However, prolactin levels above normal

are not reached (Kreek 1978).

Linked in part to normalization of neuroendocrine function, normalization of immune function indices also occurs during chronic long-term

methadone treatment, including normalization of natural killer cell

activity, absolute numbers of T cells, T-cell subsets, B cells, and NK cells

and, when studied after stabilization for 10 years or more, near

normalization of levels of immunoglobulins IgG and IgM, which are

profoundly elevated in untreated street heroin addicts (Kreek 1973a,

1978, 1994; Kreek et al. 1972; Novick et al. 1989; Ochshorn-Adelson et

al. 1994; Ochshorn et al. 1990). Natural killer-cell activity is reduced to a

potentially clinically significant level in untreated heroin addicts. This is

probably due to multiple factors, including injection of multiple foreign

substances and other diseases, but also possibly to indirect or direct opiate

effects. It is less clear why there are increased absolute numbers of T cells

and B cells in untreated heroin addicts when HIV infection is not present,

but that has been a reproducible finding from many studies (Novick et al.

1989; Ochshorn et al. 1990; Ochshorn- Adelson et al. 1994).

By using appropriate doses of methadone, an effective methadone

program also prevents drug craving and thus prevents use of dirty needles

to inject illicit drugs. When the author carried out a study in which sera

that were prospectively banked from 1969 onward from all research

subjects entering basic and clinical research in the laboratory were
12

unbanked and studied in 1983-84, HIV was detectable when the AIDS

epidemic appeared in the parenteral-drug-abusing population in New

York City (DesJarlais et al. 1984, 1989; Kreek et al. 1990; Novick et al.

1986a, 1986b). This also allowed the author’s group to ask about the

impact of effective methadone treatment on acquisition of HIV-1

infection. In the Centers for Disease Control (CDC) Bulletin published in

the summer of 1984, the author and her colleagues reported that effective

methadone treatment prevents HIV-1 infection by reducing or eliminating

use of unsterile needles (DesJarlais et al. 1984). Ten years later, there are

still waiting lists for entry into methadone maintenance treatment in many

regions, and no access to treatment in many other areas. Also over the

past 10 years, the unit funding for each treatment resource has gone

down, resulting in too few effective or “good” programs, which by

definition, use adequate and stable doses of methadone, and also provide

ready access to onsite counseling, medical, and psychiatric care. Whatever

efficacious medication for treatment of cocaine dependency might be

developed, if there are no appropriate treatment resources in which to

deliver it, that is, programs that can combine pharmacotherapy with

support services in a proper environment, there will never be a therapy

that will be effective and generally accepted by patients and by the

community. Researchers must address the need for proper access to

treatment and form appropriate, effective programs, while developing new

medications and conducting exciting and potentially important

neurobiological studies.

In addition to methadone, other medications have been developed for

treatment of chronic opiate addiction. A longer-acting congener of

methadone, which like methadone is a pure opioid agonist directed at the

mu opioid receptor LAAM (for which NIDA is to be credited for gaining

prompt FDA approval) is now available for maintenance treatment.

Buprenorphine, a partial agonist, or mixed antagonist, is currently under

study. Naltrexone, a pure opioid antagonist, was approved by the FDA

several years ago. Each medication may be beneficial for some heroin

addicts, yet each will require administration by appropriately trained staff

and with appropriate monitoring of all patients in treatment, as well as

initial administration in a treatment modality that will also provide

counseling, rehabilitation efforts, AIDS risk reduction, education, and

access to medical and psychiatric care, especially for addicts first entering

treatment.

In the “worst” or most limited in terms of ancillary services, of all

programs reported, in a controlled study that administered an adequate

dose of methadone (often not done in minimal services clinics), as

reported by McLellan and O’Brien in their “three levels of treatment
13

study,” it was found that giving out methadone alone has a 45 to 55

percent success rate in terms of stopping illicit opiate use in unselected

heroin addicts (McLellan et al. 1993). In contrast, naltrexone, in

unselected heroin addicts (not small groups of physicians or nurse addicts

or special groups such as those on probation with a 6-month contract), in

the best of studies, including the pivotal multicenter trial planned by the

National Academy of Sciences group, has been shown to have

effectiveness only in 15 percent to 20 percent of patients and then only

for a very short time. This low level of effectiveness resulted in stopping

this multicenter trial much earlier than planned (National Research

Council Committee on Clinical Evaluation of Narcotic Antagonists 1978).

Also, drug-free treatment, in the best of approaches and the worst of

approaches, results in only 15 to 30 percent success, measured by

retention and remaining in an abstinent state for 1 year or more (Cooper

et al. 1983).

Clearly, a pharmacotherapy for cocaine as well as for opiate and alcohol

addiction is needed, but it should be appropriately delivered in wellstaffed and broad services programs, as discussed earlier. Also needed is a

definition of cocaine dependency in terms of different stages of duration

and severity so that data analogous to the abundant data on treatment of

opiate addiction can be presented. Opiate addiction as defined for criteria

for entry into methadone maintenance and LAAM treatment, and thus for

all studies discussed here is, is at least 1 year of multiple daily dose uses of

heroin, with the development of tolerance, physical dependence, and

drug-seeking behavior. Studies have yet to be performed on drug abusers

with less than 1 year of daily or intermittent heroin use, of the efficacy of

naltrexone, for whom naltrexone is the only pharmacotherapy, by law,

that can be used. Also necessary are natural history studies on early drug

abusers with opiate dependency for less than 1 year, i.e., short-term

addicts. Similarly, 1 year of daily or at least weekly “binge pattern”

cocaine use might provide a satisfactory definition for long term or

“hard-core” cocaine addicts. Researchers could then target a

pharmacotherapy for such a long-term or “hard-core” group and

correlate data from treatment outcome studies across centers. At the same

time, researchers could develop an intervention for cocaine abusers with a

shorter history of use.

The author’s laboratory has worked on the hypothesis that the

endogenous opioid system may be involved to some extent, and possibly

to a considerable extent, in each of three major addictive diseases: opiate,

cocaine, and alcohol addictions. The endogenous opioid system has three

classes of endogenous opioid peptides: the endorphins, the enkephalins,

and the dynorphins. Single genes code for each of these three classes of
14

endogenous peptides. These genes have been cloned, and the

biochemical characterization of the several opioid and nonopioid peptides

from the single precursor peptide, as well as some of the mechanisms for

processing and biotransforming the parent peptides to those various

peptides, has been defined. In December 1992, the first opioid receptor

gene, the delta opioid receptor gene, was cloned independently by Evans

and by Kieffer (Evans et al. 1992; Kieffer et al. 1992). This was soon

followed by cloning of both the mu and kappa receptors by Yu, and the

mu receptor gene by Uhl, Akil, and Watson, and others (Chen et al.

1993a, 1993b; Thompson et al. 1993; Wang et al. 1993, 1994a, 1994b).

At this time it seems that there are indeed three genes coding for three

types of opioid receptors, as had been predicted through many cell

biological and medicinal chemistry studies using primarily selectively

synthetic ligands. To date, no separate genes to explain subtypes of each

of these three types of opioid receptors, as defined by use of selective

chemical ligands, have been found. There is a fourth (or more)

“orphan” opioid receptor-like gene(s), with significant homology to the

opioid receptor gene, the natural ligand(s), which is still to be determined.

Cocaine acts primarily by inhibiting the synaptic reuptake of dopamine

(DA) into presynaptic sites and also inhibits the receptors of serotonin and

norepinephrine by acting at their transporters. Of those three

neurotransmitters, most studies have focused primarily on DA, since DA

has been so closely linked, by many studies in animal models and at the

human level, with the reinforcing or the pleasurable effects of drugs of

abuse (Koob 1992). DA, normally released into the synapse, primarily

acts at postsynaptic DA receptors, now defined as existing in five distinct

types with different and opposing effects. DA thereby activates one or

more signal transduction systems, including receptor-specific stimulating

or inhibiting effects on adenylyl cyclase activity. Similarly, serotonin and

norepinephrine released from presynaptic sites may act at many specific

receptors with subsequent signal transduction. These neurotransmitters

are subsequently transported first back into presynaptic areas by their

specific transporter proteins and then back into presynaptic vesicles.

There are also presynaptic DA autoreceptors, where DA may act to

regulate DA release.

Although the major effect of cocaine that is known is the direct effect of

blocking reuptake of the three neurotransmitters at the site of their

specific transporters, this effect is transient (Maisonneuve and Kreek

1994; Maisonneuve et al. 1995). Researchers have raised the question of

what may be the indirect effects of cocaine on the endogenous opioid

peptides and their receptor systems. These may be longer lasting effects,

and/or may provide memory that leads to continual self-administration or
15

relapse to drug use. The reinforcing or reward effects of drugs of abuse,

the “pleasurable” or “desirable” effects, are thought to be those that

lead to “craving” or “drug hunger,” resulting ultimately with

spontaneous activity, or work, for drug acquisition and drug selfadministration. The primary sites of action of drugs of abuse with respect

to their “reward” or reinforcing effects have been identified by many

groups as being in specific brain regions, all rich in dopaminergic

(DArgic) nerve terminals or alternative cell bodies, including primarily the

mesolimbic and mesocortical dopaminergic systems, especially the

nucleus accumbens, which receives terminals from the ventral tegmental

area. Also, some of the locomotor activity effects of cocaine and other

drugs of abuse derive from effects on DA projections from the substantia

nigra to the caudate putamen region as well as the mesolimbicmesocortical system effects. In addition, it has been hypothesized that the

hypothalamus may be important with respect to modulating, in part

possibly through different DArgic pathways located therein that may, in

turn, affect the responsivity of related hormone systems (Kreek 1996). At

these sites, altered stress responsivity may be localized which, since 1972,

the author had hypothesized may be part of the neurobiological basis of

addictive disorders (Kreek 1972, 1992c). The question is what are the

linkages between the DArgic system and the opioid system within these

single brain regions, and what are the feedback loops between these

regions. Specifically one of the questions the author has been addressing

is whether or not dynorphin plays a significant role in the feedback

control of DArgic tone (Chou et al. 1994a, 1994b; Kreek et al. 1994;

Spangler et al. 1993a, 1993b, 1994, 1995, 1996).

Also especially interesting is the role of the stress-responsive axis in the

addictive diseases. A single gene and gene product, pro-opiomelanocortin (POMC), yields beta-endorphin, an endogenous opioid, in

equimolar concentrations with ACTH, long appreciated as the major

stress-responsive peptide in mammals, which causes release from the

adrenal cortex of glucocorticoids (cortisol in man, corticosterone in rats).

Glucocorticoids, in turn, are critical hormones modulating many

metabolic and immune functions. Corticotropin-releasing factor (CRF) is

released from the hypothalamus and acts on the anterior pituitary to cause

production and release of beta-endorphin and ACTH from POMC.

Glucocorticoid released from the adrenal cortex act at glucocorticoid

receptors both in the hypothalamus and in the anterior pituitary to affect

the negative feedback control of CRF and POMC release was reconfirmed

as also regulating these hormones encoding mRNA of rat POMC (Zhou et

al. 1996a, 1996b).
16

The author’s work on opiate dependency has shown in humans that

opiates will suppress this hypothalamic pituitary adrenal (HPA) axis

acutely; in rodents, however, opiates apparently acutely activate hormones

of the HPA axis. When used on a chronic basis in man, short-acting

opiates, such as heroin, continue to cause suppression of this HPA axis.

However, in an opioid-tolerant and opioid-dependent human being who

stops all opiate use and thus goes into opiate withdrawal, the opposite is

seen—profound activation of this HPA axis (Kreek 1972, 1973a, 1973c;

1978, 1992c). Some data from the author’s group, and from ongoing

collaborative work with a group at Yale, support that this opioid activation

of the HPA axis may actually precede the first measurable or significant

signs and symptoms of opiate withdrawal (Culpepper-Morgan and Kreek,

in press; Culpepper-Morgan et al. 1992; Rosen et al. 1995, 1996). Opioid

antagonists given to opioid-naive individuals, or to former heroin addicts

for management of addiction, exert effects on the HPA axis similar to

those found in opiate withdrawal (Kosten et al. 1986a, 1986b;Kreek et al.

1984b). They cause activation of the HPA axis with release of ACTH,

beta-endorphin, and cortisol. During chronic steady-dose treatment with

the long-acting opioid agonist methadone, normalization of this axis

occurs with normal plasma levels of hormones and normal release, as well

as circadian patterns of release of the HPA axis hormones and normal

negative feedback control of that release (Kennedy et al. 1990; Kreek

1972, 1973a, 1973c, 1978, 1992c; Kreek and Hartman 1982; Kreek et al.

1981, 1983, 1984a).

A provocative test of chemically induced stress using metyrapone, which

blocks the last step of cortisol production in the adrenal cortex, blocks the

negative feedback control mechanisms by cortisol at the hypothalamic

and anterior pituitary sites and thereby normally yields a twofold to

fourfold increase in plasma levels of ACTH and beta-endorphin. It has

been used by the author’s laboratory to study the responsiveness of the

HPA axes in former addicts and addicts in treatment. In active heroin

addicts taking heroin, a hyporesponsivity to this blockade of cortisol

synthesis is seen; in drug-free former heroin addicts, hyperresponsivity to

this chemically induced stress is frequently seen (Cushman and Kreek

1974b; Kreek 1972, 1973a, 1973c, 1978, 1987, 1992c; Kreek and

Hartman 1982; Kreek et al. 1984a). In long-term methadone maintained

patients, euresponsivity is seen (Kennedy et al. 1990; Kreek 1973a,

1973c), 1978, 1992c; Kreek et al. 1984a).

Cocaine has been shown by several laboratories to activate the HPA axis

when cocaine is present, both in animal studies and in humans. Very

intriguingly, a hyperresponsivity to this chemically induced stress has

been found in some, but not all, recently abstinent cocaine addicts. The
17

author has recently studied cocaine addicts with long-term and very heavy

usage, using the Addiction Severity Index (ASI) to assess the degree of

severity, those who have been cocaine addicts for more than 1 year and

have a “binge” and/or daily pattern of cocaine use with sustained social

disruption, as well as profound weight loss. When such deeply impaired

cocaine addicts were admitted to a research unit following continued

“refeeding,” very rapid weight gain was observed not unexpectedly

(Cambor et al. 1992; Ho et al. 1992). However, no dramatic changes in

heart rate or blood pressure were found. In ongoing studies of such

patients in an NIH-GCRC unit, hyperresponsivity to metyrapone-induced

stress in some subjects was seen. The author is continuing to study this

phenomenon in such subjects and also has looked at craving in these

subjects using two different visual analog scales, “craving now” and

“craving sometime during the last 24 hours.” Three different patterns of

responses have been observed: those who have craving at admission and

persisting through 21 days in the hospital; those who had craving when

they were first admitted but with the craving gradually decreasing and in

some cases disappearing; and those with no craving in the stressminimized environment with no “cues” until, with no apparent

provocation, it suddenly emerges again (Cambor et al. 1992; Ho et al.

1992).

A much less expensive and more easily performed technique for

quantitatively measuring BE in urine using a commercialized type of

immune assay that can be performed quantitatively has been modified

from the vigorous work of Batki, Jones, and colleagues, using gas

chromatography (Batki et al. 1993; Peters et al., in press; Reid et al.

1995). This method provides much more pertinent information than

simply getting a “positive-negative” result from such testing by immune

assays, which only indicate that more or less than 300 ng/mL of BE is

present in urine. Studies have been conducted in cocaine addicts admitted

to the author’s Rockefeller University clinical research ward and studied

in the early abstinent state for more than 40 days as inpatients, with no

passes allowed. After patients have been in the research unit for an

extended time, usually more than 40 days, a limited number of authorized

passes are allowed. There are twenty 24-hour urines collected in the

hospital daily on all study subjects at all times for a variety of

measurements. In a 24-hour urine collection, the authors were able to

measure and calculate the total BE metabolite excreted each day as well as

the absolute concentration per milliliter. Also, both creatinine

concentration and the total amounts of creatinine excreted each 24-hour

period were determined. During the first few days of hospitalization, the

levels of benzoylcognine slowly declined, but remained above 300 ng/mL

for several days (Peters et al., in press; Reid et al. 1995). Thus if the
18

standard method of designating urine “positive” or “negative” were

used, a specimen collected for monitoring purposes could be incorrectly

evaluated as “positive.” A steady decline in levels of BE (or the ratio to

creatinine) documents no further, or more recent, cocaine use.

Conversely, an increase in metabolite levels shows recent further use, thus

“relapse,” with the implied interpretation being continuing or relapse to

cocaine use. Like the Batki and Jones group, the author’s group has

proposed and demonstrated that expressing quantitative data, from both

spot urine collections made in the clinic, as well as 24-hour urine

collections made in an inpatient research setting, as a ratio of BE to

creatinine, may rectify any false-negative data that could result from

purposeful or accidental dilution of urine (Batki et al. 1993; Peters et al.,

in press). Any illicit use of cocaine while out on pass in this group study,

which occurred in three study subjects only, was found by the

reappearance of BE in the urine after the initial steady decrease and then

disappearance of metabolite. The magnitude of the levels of

benzylecgonine would reflect the amount of cocaine used.

Several years ago, in the author’s laboratory, a rat model was developed to

mimic human patterns of cocaine use. Whether daily or weekly, cocaine

is most often self-administered in a “binge” pattern, with multiple doses

given over a usually 1- to 24-hour timeframe, although sometimes much

longer, and then with no cocaine used for a period of time. In animal

models, cocaine was administered just before what would be the sleep time

in rats, again parallel to the frequent time of human “binge” use by the

cocaine addict. In this model, repeated doses of cocaine are given at 9:30,

10:30, and 11:30 in the morning (Branch et al. 1992). Then no cocaine

is administered for the next 22 hours. A variety of behavioral,

neurochemical, cellular, and molecular biological measurements are

made. Food intake was found to be similar in both low dose (2.5 mg/kg,

three times per day) and high dose (10 mg/kg, three times per day)

cocaine-treated and saline-treated animals. Weight gain, however, was

different. An initial slowing of weight gain was found in the late

adolescent/early adult rats; the weight gain then became equivalent after 7

to 10 days of cocaine administration.

Locomotor activity monitoring is conducted in the author’s laboratory on

individual animals in homecages on a 24-hour basis. On day 1 of

“binge” pattern cocaine administration, locomotor activity is increased

after each of the three administrations of cocaine (15 mg/kg three times

per day) (Unterwald et al. 1994b). By the last days of 14 days of

“binge” pattern cocaine administration, a profound difference is seen in

locomotor activity in cocaine-treated versus saline-treated animals. This is

“sensitization” described and studied by many other workers, but using
19

very different experimental protocols. In this study, a regular, although

intermittent, “binge” pattern of chronic cocaine administration with a 22-

hour interval between cocaine doses caused a hypersensitivity to cocaine

with respect to its effects on locomotor activity (Unterwald et al. 1994b).

Since in this study, 24-hour activity in homecage was measured with no

removal of animals for cocaine/saline injections, and no removal for

behavioral measurement, the timecourse of development of sensitization

has been determined, which seems to be an extraordinarily robust

phenomena in rat models. Both acutely and when studied in a chronic

basis, this locomotor activation exactly parallels the increases in

extracellular fluid concentrations of DA measured directly in

microdialysis studies conducted using the same treatment protocol

(Maisonneuve and Kreek 1994; Maisonneuve et al. 1995; Unterwald et al.

1994b).

Microdialysis studies were performed with probes in the nucleus

accumbens (ventromedial striatum) and in the caudate putamen

(dorsolateral striatum) (Maisonneuve and Kreek 1994; Maisonneuve et al.

1995). It was found that following each dose of cocaine, levels of DA in

the extracellular fluid are elevated. However, following the second and

third dose of cocaine on the first day of cocaine administration, a plateau

of the rises in DA concentration in extracellular fluid is seen. In contrast,

when actual levels of cocaine in the caudate putamen are measured, it was

found that the half-life of cocaine in this brain region is around 30

minutes; thus the amounts of cocaine accumulate, with further increases in

cocaine levels in the brain regions after each of these three “binge

pattern” cocaine administrations (Maisonneuve and Kreek 1994). Thus

there is evidence for acute adaptation or tolerance to this particular effect

of cocaine on extracellular DA concentrations on this first day of cocaine

administration.

After 14 days, there is again a rise in DA levels in the extracellular fluid

after each dose of cocaine, paralleling the behavioral data on locomotor

activity (Maisonneuve et al. 1995). However, two interesting issues were

noted. At every timepoint the actual concentrations of DA in the

extracellular fluid in both the caudate putamen and nucleus accumbens

regions are lower in the animals that had been receiving the “binge”

pattern cocaine administered on a chronic basis, as contrasted to salinetreated animals receiving cocaine for the first time on the last day of the

study. Much of the microdialysis study data published by various

research groups are presented as percent changes from baseline values. In

the author’s studies, in which all probes used are precalibrated, the data

could also be measured in actual amounts of DA. Significant reductions

of extracellular fluid concentrations of DA, both prior to and following
20

each injection of cocaine, were found on the final 14th day of “binge

pattern” cocaine administration. If these data were then expressed in the

more conventional units of percent change from baseline, essentially the

same responses were observed after the first doses of cocaine in both

cocaine and saline-pretreated animals. However, no plateau in DA levels

was observed after the second and third cocaine doses in the chronic

cocaine-treated rats. This relatively greater rise in extracellular fluid DA

after chronic cocaine administration would parallel what was seen with the

cocaine-induced activity, which is an enhanced response to the chronic

intermittent cocaine administration or sensitization (Maisonneuve et al.

1995).

In related studies using the technique of quantitative autoradiography, the

effects of this “binge” pattern cocaine administration on altering D1 and

D2 DA receptor densities were demonstrated (Unterwald et al. 1994b).

The D2 type DA receptors were increased in density significantly at 7 days

after “binge” cocaine administration in three areas of the mesolimbicmesocortical system, including the nucleus accumbens, the caudate

putamen, and olfactory tubercle. These changes, however, were transient.

By 14 days, no alterations in the density of D2 DA receptors were found in

any brain region (Unterwald et al. 1994b). However,

D1-type DA receptors were found to be significantly increased after 14

days in both the nucleus accumbens and the olfactory tubercle. This

enhanced density of D1 DA receptors following chronic “binge pattern”

cocaine administration occurred specifically in areas of the brain known

to be involved in the rewarding effects of cocaine and other drugs of

abuse. These findings are provocative, especially with known linkage

between the D1 DA receptors and dynorphinergic neurons.

What is the answer to the question, “What other changes are present after

DA levels have returned to normal in the extracellular fluid or, in fact, to

modestly suppressed levels, and if there are enhanced D1 DA but not D2

DA receptor densities, what happens to the endogenous opioid system?”

What has been found is that the mu opioid receptors are significantly

increased in density, as measured by quantitative autoradiography using

mu selective opioid ligands in the caudate putamen, the nucleus

accumbens, the cingulate cortex, and also in the basolateral amygdala

after 14 days of “binge pattern” cocaine administration (Unterwald et al.

1992, 1994a).

The effects of “binge” pattern cocaine administration on kappa type

opioid receptors have also been studied (Unterwald et al. 1994a). Again,

when using selective ligands, significant increase in binding capacity in

the caudate putamen, the nucleus accumbens, the cingulate cortex and
21

also in the olfactory tubercle, again all brain regions that are part of the

mesolimbic, mesocortical, or nigrostriatal DArgic system, where DArgic

terminals are abundant as projections from the substantia nigra and the

ventral tegmental area, have been found. No significant changes in mu or

kappa opioid receptors were found within other brain regions where they

are equally or more dense in the basal state. It is of special interest that

the significant changes in D1 DA receptor density and in kappa receptor

density were both found in two areas of central importance for reward

mechanisms: the nucleus accumbens and the olfactory tubercle, both

important regions of the mesolimbic-mesocortical DArgic system. These

findings are of special importance since dynorphinergic activity is known

to be linked to activation of the D1 type DA receptors (Spangler et al., in

press-a, -b, -c; Unterwald et al. 1994b) and since full-length dynorphin

peptides are the natural ligands of the kappa opioid receptors. It has been

hypothesized that dynorphin acts to lower DArgic tone, with negative

feedback control from the caudate putamen to the substantia nigral site of

DArgic neurons, which project to the caudate putamen and which are part

of the nigrostriatal DArgic system, and also possibly from the nucleus

accumbens to the ventral tegmental area site of DArgic neurons, which

project to the nucleus accumbens, amygdala, olfactory tubercle, cingulate

cortex, and other brain regions of the mesolimbic-mesocortical-DArgic

system. The authors also have hypothesized that there may be action of

dynorphinergic peptides to decrease DArgic tone directly within the

caudate putamen and within the nucleus accumbens. This hypothesis is

supported by the recent finding of DAT (DA transporter) gene message

expression within both the caudate putamen and the nucleus accumbens

(Maggos et al. 1995, in press).

Several scientists at the NIH-NIDA Research Center have developed a

modified technique of solution hybridization RNase protection assay, in

which 18S ribosomal RNA is used as an internal standard, and both sense

and antisense riboprobes are used to construct calibration curves of

internal standards and gene of interest (Branch et al. 1992; Inturrisi et al.

1988). Following gel analysis of hybridization with the use of each new

probe or experimental perturbation, the routine procedure for quantitative

measurements of the levels of mRNA of genes of interest in specific brain

regions of individual animals includes precipitation with trichloracetic

acid of hybridized species, followed by filtration and counting. This

modified procedure has allowed the study of specific brain regions from

individual animals with precise measurements that allow detection of the

small, but potentially very significant, changes that impact or perturb

integrated physiology in mammalian physiology (Spangler et al. 1993a,

1993b, 1994, 1995, 1996; in press-a, -b, -c). Using this technique,

researchers use ribosomes, usually subcloned from probes provided by
22

various colleagues for studies of specific genes from specific species. The

author prefers using riboprobes that are over 500 bases in length to

increase stringency of the solution hybridization RNase, protection assays,

a sharp contrast to the very short probes that must be used for in situ

hybridization, which usually are 150 to 250 bases in length.

It has been seen that at the end of 14 days of “binge pattern” cocaine

administration, there is no change in gene expression, measured as

quantities of mRNA levels of the DA transporter gene expression in the

substantia nigra or in the ventral tegmental areas, the two areas where this

gene is the most highly expressed (Maggos et al. 1995, in press).

Recently, the author used probes for rat genes cloned by Yu and Uhl, and

others, following the initial identification of cDNAs of the mouse delta

opioid receptor by expression cloning, achieved by Evans and by Kieffer

and colleagues, to study the quantitative levels of gene expression of the

kappa and mu opioid receptor in specific brain areas (Chen et al. 1993a,

1993b; Evans et al. 1992; Kieffer et al. 1992; Wang et al. 1993).

Researchers are continuing studies to look at the impact that drugs of

abuse and treatment agents on these opioid receptors, as well as on signal

transduction systems related to these receptors. High levels of abundance

of gene expression for both the mu and kappa receptors have been found

in the caudate putamen and the nucleus accumbens, and also in the

hypothalamus as well as in the substantia nigra, the olfactory tubercle, and

the amygdala (Spangler et al. 1994, 1995). The author also has

remapped, using this very sensitive technique, the levels of gene

expression of opioid peptide genes in various regions (Branch et al. 1992;

Spangler et al. 1993a, 1993b, 1996, in press-a, -b). Again, the two

regions of great abundance of proenkephalin and prodynorphin gene

expression are the nucleus accumbens and the caudate putamen, and to a

lesser extent the hypothalamus.

The author then studied the effects of binge pattern cocaine administration on opioid peptide gene expression. After 14 days of “binge”

cocaine administration, no changes in proenkephalin gene expression

were observed in any brain region (Branch et al. 1992). However,

following that pattern of chronic cocaine administration in the rat,

significant upregulation of prodynorphin mRNA levels in caudate

putamen were found (Spangler et al. 1993a, 1993b).

It has been hypothesized that dynorphin A, one of the major opioid

peptides processed from the initial single gene product of prodynorphin

gene expression, may act directly or indirectly to lower DArgic tone

(Kreek et al. 1994). In humans, DA plays a dominant role in tonically

inhibiting prolactin release, acting on the tuberoinfundibular DArgic
23

system. Such an effect may parallel the effect of dynorphin on the

mesolimbic, mesocortical, and nigrostriatal DArgic systems. Thus, an

elevation in prolactin levels may reflect a selective or general reduction in

DArgic tone on the brain. The question is whether dynorphin A will

effect an increase in prolactin levels in humans. Dynorphin A normally

has 17 amino acids; the truncated form of dynorphin A (1-13) of natural

sequence has been made available to the author for independent clinical

research in humans by Neurobiological Technologies, Inc., in Richmond,

California. With Dr. B. Chait, Head of the Laboratory of Extended Range

Mass Spectrometry, at Rockefeller University, a matrix-assisted, laser

desorption mass spectrometry method has been developed to study

neuropeptide processing and biotransformation (Chou et al. 1993a,

1993b, 1993c, 1994a, 1994b, in press; Yu et al., in press). Using this

technique, all of the specific products of neuropeptide biotransformation

ex vivo can be analyzed simultaneously. By this technique, it has been

determined that the most abundant active opioid component of dynorphin

A (1-13) is dynorphin A (1-12), along with the nonopioid peptides

dynorphin A (2-12), which may have some different activities, and

dynorphin A (4-12) (Chou et al. 1993a, 1993b, 1994a, 1994b, in press).

It has been found that both the opioid peptides dynorphin A (1-13),

dynorphin A (1-17), and dynorphin A (1-6), and also the major

nonopioid biotransformation products dynorphin A (2-17) and

dynorphin A (2-12), inhibit adenylyl cyclase in rat caudate putamen

membranes (Claye et al. 1996). In pilot studies, when dynorphin A (1-

13) is given to normal volunteers, it causes a significant rise in serum

prolactin levels, which persists for around 90 minutes when 120 &g/kg of

dynorphin A (1-13) is given intravenously (Kreek et al. 1994). This is

dose-responsive effect, with further increases and more prolonged

elevations in serum prolactin levels when 500 &g/kg of dynorphin A (1-

13) is administered intravenously. Controlled studies in patients with

defined addictive diseases are continuing.

In summary, there are at least two medications, methadone and LAAM,

both specific opioid agonists, an additional partial agonist under study,

buprenorphine, that are highly efficacious in the treatment of opiate

addiction, and also, an antagonist, naltrexone, effective in small, welldefined subpopulations. All of these are directed at the opiate system, not

surprisingly. But much more surprising, and now well elucidated by the

author’s group and supported by findings from other groups, is that

cocaine disrupts specific aspects of the endogenous opioid system in

humans as well as in animal models. Thus, in theory, there may be some

pharmacotherapeutic benefit from targeting an opioid agonist or partial

agonist in cocaine dependency, at least in the setting of codependency

with an opiate such as heroin. Several studies, most recently by Borg and
24

colleagues (1995), have shown that although some 70 to 90 percent of

former heroin addicts have used cocaine heavily prior to admission to

methadone maintenance, over 40 to 50 percent stop using cocaine during

effective methadone maintenance treatment, and only 20 to 30 percent

continue with regular cocaine (Borg et al. 1995). This is an effect that

can be attributed primarily to the positive psychosocial intervention;

however, it may, in part, be attributable to pharmacological actions of

methadone or LAAM or buprenorphine (Borg et al. 1995).

Several groups including that of Volpicelli and O’Brien at the University

of Pennsylvania and O’Malley and colleagues at Yale, as well as B. Mason

at the University of Miami have shown that specific opiate antagonists

such as naltrexone or nalmefene may be useful in the treatment of

alcoholism (Mason et al. 1994; O’Malley et al. 1992; Volpicelli et al.

1992). Thus there is increasing evidence that the endogenous opiate

systems, as well as the DArgic system, and possibly also the serotonergic

system, may be intrinsically involved in each of these three major

addictions: heroin, cocaine and alcohol. All of these neurobiological and

clinical findings should guide researchers in the exploration for a

pharmacotherapy for cocaine addicts.

REFERENCES

Batki, S.L.; Manfredi, L.B.; Jacob, P.; and Jones, R.T. Fluoxetine for cocaine

dependence in methadone maintenance: Quantitative plasma

and urine cocaine/benzoylecgonine concentrations. J Clin

Psychopharmacol 13:243-250, 1993.

Borg, L.; Broe, D.M.; Ho, A.; and Kreek, M.J. Cocaine abuse is decreased with

effective methadone maintenance treatment at an urban

Department of Veterans Affairs (DVA) Program. In: Harris,

L.S., ed. Problems of Drug Dependence, 1994: Proceedings

of the 56th Annual Scientific Meeting of the College on

Problems of Drug Dependence, Inc. Vol. II. National Institute

on Drug Abuse Research Monograph 153. NIH Pub. No.

(ADM)95-3883. Washington, DC: Supt. of Docs., U.S. Govt.

Print. Off., 1995. p. 17.

Branch, A.D.; Unterwald, E.M.; Lee, S.E.; and Kreek, M.J. Quantitation of

preproenkephalin mRNA levels in brain regions from male

Fischer rats following chronic cocaine treatment using a

recently developed solution hybridization procedure. Mol

Brain Res 14:231-238, 1992.
25

Cambor, R.; Ho, A.; Bodner, G.; Lampert, S.; Kennedy, J.; and Kreek, M.J.

Changes in clinical status of newly abstinent hospitalized

cocaine users. In: Harris, L.S., ed. Problems of Drug

Dependence, 1991: Proceedings of the 53rd Annual Scientific

Meeting of the College on Problems of Drug Dependence.

National Institute on Drug Abuse Research Monograph 119.

NIH Pub. No. (ADM)92-1888. Washington, DC: Supt. of

Docs.,U.S. Govt. Print. Off., 1992. p. 440.

Chen, Y.; Mestek, A.; Liu, J.; Hurley, J.A.; and Yu, L. Molecular cloning and

functional expression of a mu opioid receptor from rat brain.

Mol Pharmacol 44:8-12, 1993a.

Chen, Y.; Mestek, A.; Liu, J.; and Yu, L. Molecular cloning of a rat kappa

opioid receptor reveals sequence similarities to the mu and

delta opioid receptors. Biochem J 295:625-628, 1993b.

Chou, J.Z.; Chait, B.T.; and Kreek, M.J. Study of dynorphin A peptides in vitro

processing in human blood by matrix-assisted laser desorption

mass spectrometry. In: Harris, L.S., ed. Problems of Drug

Dependence, 1992: Proceedings of the 54th Annual Scientific

Meeting of the College on Problems of Drug Dependence.

National Institute on Drug Abuse Research Monograph 132.

NIH Pub. No. (ADM)93-3505. Washington, DC: Supt. of

Docs., U.S. Govt. Print. Off., 1993a. p. 380.

Chou, J.Z.; Chait, B.T.; Wang, R.; and Kreek, M.J. Differential

biotransformation of dynorphin A 1-17 and dynorphin A1-13

peptides in human blood, ex vivo. Peptides, in press.

Chou, J.Z.; Kreek, M.J.; and Chait, B.T. Study of opioid peptides by laser

desorption mass spectrometry. In: Harris, L.S., ed. Problems of

Drug Dependence, 1992: Proceedings of the 54th Annual

Scientific Meeting of the College on Problems of Drug

Dependence. National Institute on Drug Abuse Research

Monograph 132. NIH Pub. No.

93-3505. Washington, DC: Supt. of Docs., U.S. Govt. Print.

Off., 1993c.

Chou, J.Z.; Kreek, M.J.; and Chait, B.T. Matrix-assisted laser desorption mass

spectrometry of biotransformation products of dynorphin A

in vitro. J Am Soc Mass Spectrom 5:10-16, 1994a.

Chou, J.Z.; Maisonneuve, I.M.; Chait, B.T.; and Kreek, M.J. Study of

dynorphin A(1-17) in vivo processing in rat brain by

microdialysis and matrix-assisted laser desorption mass

spectrometry. In: Harris, L.S., ed. Problems of Drug

Dependence, 1993: Proceedings of the 55th Annual Scientific

Meeting, the College on Problems of Drug Dependence, Inc.

Vol. II. Abstracts. National Institute on Drug Abuse Research
26

Monograph 141. NIH Pub. No. (ADM)94-3749, 1994b. p.

240.
27

Chou, J.Z.; Maisonneuve, I.M.; Kreek, M.J.; and Chait, B.T. Matrix-assisted

laser desorption mass spectrometry of dynorphin A(1-17)

processing in human plasma and rat brain. Abstracts of the

41st ASMS Conference on Mass Spectrometry & Allied

Topics, San Francisco, CA, 1993b.

Claye, L.H.; Unterwald, E.M.; Ho, A.; and Kreek, M.J. Inhibition of adenylyl

cyclase activity by opioid and non-opioid dynorphin A

peptides in rat caudate putamen. In: Harris, L.S., ed. Problems

of Drug Dependence, 1995: Proceedings of the 57th Annual

Scientific Meeting of the College on Problems of Drug

Dependence. National Institute on Drug Abuse Research

Monograph 162. NIH Pub. No. (ADM)96-4116. Washington,

DC: Supt. of Docs., U.S. Govt. Print. Off., 1996. p. 132.

Cooper, J.R.; Altman, F.; Brown, B.S.; and Czechowicz, D., eds. Research in the

Treatment of Narcotic Addiction: State of the Art. National

Institute on Drug Abuse Research Monograph. DHHS Pub.

No. (ADM)83-1281. Washington, DC: Supt. of Docs., U.S.

Govt. Print. Off., 1983.

Culpepper-Morgan, J.A.; Inturrisi, C.E.; Portenoy, R.K.; Foley, K.; Houde,

R.W.; Marsh, F.; and Kreek, M.J. Treatment of opioid induced

constipation with oral naloxone: A pilot study. Clin

Pharmacol Ther 23:90-95, 1992.

Cushman, P., and Kreek, M.J. Methadone-maintained patients. Effects of

methadone on plasma testosterone, FSH, LH and prolactin. N

Y State J Med 74:1970-1973, 1974a.

Cushman, P., and Kreek, M.J. Some endocrinologic observations in narcotic

addicts. In: Zimmerman, E., and George, R., eds. Narcotic and

the Hypothalamus. New York: Raven Press, 1974b. pp. 161-

173.

DesJarlais, D.C.; Friedman, S.R.; Novick, D.M.; Sotheran, J.L.; Thomas, P.;

Yancovitz, S.R.; Mildvan, D.; Weber, J.; Kreek, M.J.;

Maslansky, R.; Bartelme, S.; Spira, T.; and Marmor, M. HIV I

infection among intravenous drug users in Manhattan, New

York City 1977 to 1987. JAMA 261:1008-1012, 1989.

DesJarlais, D.C.; Marmor, M.; Cohen, H.; Yancovitz, S.; Garber, J.; Friedman,

S.; Kreek, M.J.; Miescher, A.; Khuri, E.; Friedman, S.M.;

Rothenberg, R.; Echenberg, D.; O’Malley, P.O.; Braff, E.;

Chin, J.; Burtenol, P.; and Sikes, R.K. Antibodies to a

retrovirus etiologically associated with Acquired

Immunodeficiency Syndrome (AIDS) in populations with

increased incidences of the syndrome. MMWR 33:377-379,

1984.

Dole, V.P., and Kreek, M.J. Methadone plasma level: Sustained by a reservoir

of drug in tissue. Proc Natl Acad Sci U S A 70:10, 1973.
28

Dole, V.P.; Nyswander, M.E.; and Kreek, M.J. Narcotic blockade. Arch Intern

Med 118:304-309, 1966.

Evans, C.J.; Keith, D.E., Jr.; Morrison, H.; Magendzo, K.; and Edwards, R.H.

Cloning of a delta opioid receptor by functional expression.

Science 258:1952-1955, 1992.

Hachey, D.L.; Kreek, M.J.; and Mattson, D.H. Quantitative analysis of

methadone in biological fluids using deuterium-labeled

methadone and GLC-chemical-ionization mass spectrometry.

J Pharm Sci 66:1579-1582, 1977.

Ho, A.; Cambor, R.; Bodner, G.; and Kreek, M.J. Intensity of craving is

independent of depression in newly abstinent chronic cocaine

users. In: Harris, L.S., ed. Problems of Drug Dependence,

1991: Proceedings of the 53rd Annual Scientific Meeting of

the College on Problems of Drug Dependence. National

Institute on Drug Abuse Research Monograph 119. NIH Pub.

No. (ADM)92-1888. Washington, DC: Supt. of Docs., U.S.

Govt. Print. Off., 1992. p. 441.

Inturrisi, C.E., and Verebely, K. A gas-liquid chromatographic method for the

quantitative determination of methadone in human plasma

and urine. J Chromatogr 65:361-369, 1972.

Inturrisi, C.E., and Verebely, K. The levels of methadone in the plasma in

methadone maintenance. Clin Pharmacol Ther 13:633-637,

1973.

Inturrisi, C.E.; Branch, A.D.; Robertson, H.D.; Howells, R.D.; Franklin, S.O.;

Shapiro, J.R.; Clavano, S.E.; and Yoburn, B.C. Glucocorticoid

regulation of enkephalins in cultured rat adrenal medulla. Mol

Endocrinol 2:663-640, 1988.

Kennedy, J.A.; Hartman, N.; Sbriglio, R.; Khuri, E.; and Kreek, M.J.

Metyrapone-induced withdrawal symptoms. Br J Addict

85:1133- 1140, 1990.

Kieffer, B.L.; Befort, K.; Gaveriaux-Ruff, C.; and Hirth, C.G. The delta-opioid

receptor: Isolation of a cDNA by expression cloning and

pharmacological characterization. Proc Natl Acad Sci U S A

89:12048-12052, 1992.

Koob, G.F. Drugs of abuse: Anatomy, pharmacology and function of reward

pathways. Trends Pharmacol Sci 13:177-184, 1992.

Kosten, T.R.; Kreek, M.J.; Raghunath, J.; and Kleber, H.D. Cortisol levels

during chronic naltrexone maintenance treatment in ex-opiate

addicts. Biol Psychiatry 2l:2l7-220, 1986a.

Kosten, T.R.; Kreek, M.J.; Raghunath, J.; and Kleber, H.D. A preliminary study

of beta-endorphin during chronic naltrexone maintenance

treatment in ex-opiate addicts. Life Sci 39:55-59, 1986b.
29

Kosten, T.R.; Kreek, M.J.; Swift, C.; Carney, M.K.; and Ferdinands, L. Betaendorphin levels in CSF during methadone maintenance. Life

Sci 41:1071-1076, 1987.

Kosten, T.R.; Morgan, C.; and Kreek, M.J. Beta-endorphin levels during

heroin, methadone, buprenorphine and naloxone challenges:

Preliminary findings. Biol Psychiatry 32:523-528, 1992.

Kreek, M.J. Medical safety, side effects and toxicity of methadone.

Proceedings of the Fourth National Conference on Methadone

Treatment, NAPAN-NIMH 171-174, 1972.

Kreek, M.J. Medical safety and side effects of methadone in tolerant

individuals. JAMA 223:665-668, 1973a.

Kreek, M.J. Plasma and urine levels of methadone. N Y State J Med 73:2773-

2777, 1973b.

Kreek, M.J. Physiological implications of methadone treatment. Proceedings

of the Fifth National Conference of Methadone Treatment,

NAPAN II-NIMH 85-91, 1973c.

Kreek, M.J. Medical complications in methadone patients. Ann N Y Acad Sci

311:110-134, 1978.

Kreek, M.J. Methadone disposition during the perinatal period in humans.

Pharmacol Biochem Behav Suppl 11:1-7, 1979.

Kreek, M.J. Multiple drug abuse patterns and medical consequences. In:

Meltzer, H.Y., ed. Psychopharmacology: The Third

Generation of Progress. New York: Raven Press, 1987. pp.

1597-1604.

Kreek, M.J. Using methadone effectively: Achieving goals by application of

laboratory, clinical, and evaluation research and by

development of innovative programs. In: Pickens, R.;

Leukefeld, C.; and Schuster, C.R., eds. Improving Drug Abuse

Treatment. National Institute on Drug Abuse Research

Monograph 106. DHHS Pub. No. (ADM)91-1754.

Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1991.

pp. 245-266.

Kreek, M.J. The addict as a patient. In: Lowinson, J.H.; Ruiz, P.; Millman, R.B.;

and Langrod, J.G., eds. Substance Abuse: A Comprehensive

Textbook. Baltimore, MD: Williams and Wilkins, 1992a. pp.

997-1009.

Kreek, M.J. Epilogue: Medical maintenance treatment for heroin addiction,

from a retrospective and prospective viewpoint. In: State

Methadone Maintenance Treatment Guidelines. Office for

Treatment Improvement, Division for State Assistance.

Washington, DC: Supt. of Docs., U.S. Govt. Print. Off.,

November 1992b. pp. 255-272.
30

Kreek, M.J. Rationale for maintenance pharmacotherapy of opiate

dependence. In: O’Brien, C.P., and Jaffe, J.H., eds. Addictive

States. New York: Raven Press, 1992c. pp. 205-230.

Kreek, M.J. Pharmacology and medical aspects of methadone treatment. In:

Rettig, R.A., and Yarmolinsky, A., eds. Federal Regulation of

Methadone Treatment. Washington, DC: National Academy of

Sciences, National Academy Press, 1994.

Kreek, M.J. Opiates, opioids and addiction. Mol Psychol 1:232-254, 1996.

Kreek, M.J., and Hartman, N. Chronic use of opioids and antipsychotic drugs:

Side effects, effects on endogenous opioids and toxicity. Ann

N Y Acad Sci 398:151-172, 1982.

Kreek, M.J.; DesJarlais, D.C.; Trepo, C.L.; Novick, D.M.; Abdul-Quader, A.;

and Raghunath, J. Contrasting prevalence of delta hepatitis

markers in parenteral drug abusers with and without AIDS. J

Infect Dis 162:538-541, 1990.

Kreek, M.J.; Dodes, L.; Kane, S.; Knobler, J.; and Martin, R. Long-term

methadone maintenance therapy: Effects on liver function.

Ann Intern Med 77:598-602, 1972.

Kreek, M.J.; Gutjahr, C.L.; Garfield, J.W.; Bowen, D.V.; and Field, F.H. Drug

interactions with methadone. Ann N Y Acad Sci 281:350-370,

1976.

Kreek, M.J.; Hachey, D.L.; and Klein, P.D. Stereoselective disposition of

methadone in man. Life Sci 24:925-932, 1979.

Kreek, M.J.; Ho, A.; and Borg, L. Dynorphin A1-13 causes elevation of serum

levels of prolactin in human subjects. In: Harris, L.S., ed.

Problems of Drug Dependence, 1993: Proceedings of the

55th Annual Scientific Meeting of the College on Problems of

Drug Dependence, Inc. Vol. II. Abstracts. National Institute

on Drug Abuse Research Monograph 141. NIH Pub. No.

(ADM)94-3749. Washington, DC: Supt. of Docs., U.S. Govt.

Print. Off., 1994. p. 108.

Kreek, M.J.; Raghunath, J.; Plevy, S.; Hamer, D.; Schneider, B.; and Hartman,

N. ACTH, cortisol and beta-endorphin response to

metyrapone testing during chronic methadone maintenance

treatment in humans. Neuropeptides 5:277-278, 1984a.

Kreek, M.J.; Schneider, B.S.; Raghunath, J.; and Plevy, S. “Prolonged (24

hour) Infusion of the Opioid Antagonist Naloxone Does Not

Significantly Alter Plasma Levels of Cortisol and ACTH in

Humans.” Abstracts of the Seventh International Congress of

Endocrinology, Excerpta Medica, International Congress

Series 652, Amsterdam Oxford-Princeton, July 845, 1984b.
31

Kreek, M.J.; Wardlaw, S.L.; Friedman, J.; Schneider, B.; and Frantz, A.G.

Effects of chronic exogenous opioid administration on levels

of one endogenous opioid (beta-endorphin) in man. In:

Simon, E., and Takagi, H., eds. Advances in Endogenous and

Exogenous Opioids. Tokyo, Japan: Kodansha Ltd., Publishers,

1981. pp. 364-366.

Kreek, M.J.; Wardlaw, S.L.; Hartman, N.; Raghunath, J.; Friedman, J.;

Schneider, B.; and Frantz, A.G. Circadian rhythms and levels

of beta- endorphin, ACTH, and cortisol during chronic

methadone maintenance treatment in humans. Life Sci

33(Suppl. I):409-411, 1983.

Maggos, C.E.; Spangler, R.; Zhou, Y.; and Kreek, M.J. Dopamine transporter

mRNA levels in the rat substantia nigra and ventral tegmental

area immediately following and at two days and ten days after

‘binge’ cocaine administration. In: Harris, L.S., ed. Problems

of Drug Dependence, 1994: Proceedings of the 56th Annual

Scientific Meeting of the College on Problems of Drug

Dependence, Inc. Vol. II. National Institute on Drug Abuse

Research Monograph 153. NIH Pub. No. (ADM)95-3883.

Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1995.

p. 508.

Maggos, C.E.; Spangler, R.; Zhou, Y.; Schlussman, S.D.; Ho, A.; and Kreek,

M.J. Quantitation of dopamine transporter mRNA in the rat

brain: Mapping, effects of “binge” cocaine administration

and withdrawal. Synapse, in press.

Maisonneuve, I.M., and Kreek, M.J. Acute tolerance to the dopamine response

induced by a binge pattern of cocaine administration in male

rats: An in vivo microdialysis study. J Pharmacol Exp Ther

268(2):916-921, 1994.

Maisonneuve, I.M.; Ho, A.; and Kreek, M.J. Chronic administration of a

cocaine “binge” alters basal extracellular levels in male rats:

An in vivo microdialysis study. J Pharmacol Exp Ther

272:652-657, 1995.

Mason, B.J.; Ritvo, E.C.; Morgan, R.O.; Salvato, F.R.; Goldberg, G.; Welch, B.;

and Mantero-Atienza, E. A double-blind, placebo-controlled

pilot study to evaluate the efficacy and safety of oral

nalmefene HCl for alcohol dependence. Alcohol Clin Exp Res

18:1162-1167, 1994.

McLellan, A.T.; Arndt, I.O.; Metzger, D.S.; Woody, G.E.; and O’Brien, C.P.

The effects of psychosocial services in substance abuse

treatment. JAMA 269(15):1953-1959, 1993.

Nakamura, K.; Hachey, D.L.; Kreek, M.J.; Irving, C.S.; and Klein, P.D.

Quantitation of methadone enantiomers in humans using
32

stable isotope-labeled 2H3, 

2H5

, 

2H8

 methadone. J Pharm Sci

71:39-43, 1982.

National Research Council Committee on Clinical Evaluation of Narcotic

Antagonists. Clinical evaluation of naltrexone treatment of

opiate-dependent individuals. Arch Gen Psychiatry 35:335-

340, 1978.

Novick, D.; Kreek, M.J.; DesJarlais, D.; Spira, T.J.; Khuri, E.T.; Raghunath, J.;

Kalyanaraman, V.S.; Gelb, A.M.; and Miescher, A. Antibody

to LAV, the putative agent of AIDS, in parenteral drug abusers

and methadone-maintained patients: Abstract of clinical

research findings: Therapeutic, historical, and ethical aspects.

In: Harris, L.S., ed. Problems of Drug Dependence, 1985:

Proceedings of the 47th Annual Scientific Meeting of the

College on Problems of Drug Dependence. National Institute

on Drug Abuse Research Monograph 67. NIH Pub. No.

(ADM)86-1448. Washington, DC: Supt. of Docs., U.S. Govt.

Print. Off., 1986a. pp. 318-320.

Novick, D.M.; Khan, I.; and Kreek, M.J. Acquired immunodeficiency

syndrome and infection with hepatitis viruses in individuals

abusing drugs by injection. United Nations Bulletin on

Narcotics 38:15-25, 1986b.

Novick, D.M.; Ochshorn, M.; Ghali, V.; Croxson, T.S.; Mercer, W.D.;

Chiorazzi, N.; and Kreek, M.J. Natural killer cell activity and

lymphocyte subsets in parenteral heroin abusers and longterm methadone maintenance patients. J Pharmacol Exp Ther

250:606- 610, 1989.

Ochshorn, M.; Novick, D.; and Kreek, M.J. In vitro studies of methadone effect

on natural killer (NK) cell activity. Isr J Med Sci 26:421-425,

1990.

Ochshorn-Adelson, M.O.; Novick, D.M.; Khuri, E.; Albeck, H.; Hahn, E.F.;

and Kreek, M.J. Effects of the opioid antagonist naloxone on

human natural killer cell activity: In vitro and acute, low-dose

in vivo studies. Alcohol Clin Exp Res 18(6):1361-1367, 1994.

O’Malley, S.S.; Jaffe, A.J.; Change, G.; Schottenfeld, R.S.; Meyer, R.E.; and

Rounsaville, B.J. Naltrexone and coping skills therapy for

alcohol dependence. Arch Gen Psychiatry 49:881-887, 1992.

Peters, J.; Chou, J.; Ho, A.; Reid, K.; Borg, L.; and Kreek, M.J. Simplified

quantitation of urinary benzoylecgonine in cocaine addicion

research and for related pharmacotherapeutic trials. Addiction,

in press.

Reid, K.; Peters, J.; Chou, J.; Ho, A.; Borg, L.; and Kreek, M.J. Quantitative

measurement of benzoylecgonine as a marker for relapse to

cocaine abuse. In: Harris, L.S., ed. Problems of Drug

Dependence, 1994: Proceedings of the 56th Annual Scientific
33

Meeting of the College on Problems of Drug Dependence, Inc.

Vol. II. National Institute on Drug Abuse Research

Monograph 153. NIH Pub. No. (ADM)95-3883. Washington,

DC: Supt. of Docs., U.S. Govt. Print. Off., 1995. p. 331.

Rettig, R.A., and Yarmolinsky, A., eds. Federal Regulation of Methadone

Treatment. Washington, DC: National Academy Press, National

Academy of Sciences, 1994.

Rosen, M.I.; McMahon, T.J.; Margolin, A.; Gill, T.S.; Woods, S.W.; Pearsall,

H.R.; Kreek, M.J.; and Kosten, T.R. Reliability of sequential

naloxone challenge tests. Am J Drug Alcohol Abuse

21(4):453-467, 1995.

Rosen, M.I.; McMahon, T.J.; Pearsall, H.R.; Hameedi, F.A.; Woods, S.W.;

Kosten, T.R.; and Kreek, M.J. Correlations among measures of

naloxone-precipated opiate withdrawal. In: Harris, L.S., ed.

Problems of Drug Dependence 1995, Proceedings of the 57th

Annual Scientific Meeting of the College on Problems of Drug

Dependence. National Institute on Drug Abuse Research

Monograph 162. NIH Pub. No. (ADM)96-4116. Washington,

DC: Supt. of Docs., U.S. Govt. Print. Off., 1996. p. 120.

Spangler, R.; Ho, A.; Zhou, Y.; Maggos, C.; Yuferov, V.; and Kreek, M.J.

Regulation of kappa opioid receptor mRNA in the rat brain

by “binge” pattern cocaine administration and correlation

with preprodynorphin mRNA. Mol Brain Res 38:71-76, 1996.

Spangler, R.; Unterwald, E.M.; Branch, A.; Ho, A.; and Kreek, M.J. Chronic

cocaine administration increases prodynorphin mRNA levels

in the caudate putamen of rats. In: Harris, L.S., ed. Problems

of Drug Dependence, 1992: Proceedings of the 54rd Annual

Scientific Meeting of the College on Problems of Drug

Dependence. National Institute on Drug Abuse Research

Monograph 132. NIH Pub. No. (ADM)93-3505. Washington,

DC: Supt. of Docs., U.S. Govt. Print. Off., 1993a. p. 142.

Spangler, R.; Unterwald, E.M.; and Kreek, M.J. ‘Binge’ cocaine administration

induces a sustained increase of prodynorphin mRNA in rat

caudate-putamen. Mol Brain Res 19:323-327, 1993b.

Spangler, R.; Zhou, Y.; Maggos, C.E.; Schlussman, S.D.; Ho, A.; and Kreek,

M.J. Prodynorphin, proenkephalin and kappa opioid receptor

mRNA responses to acute “binge” cocaine. Mol Brain Res, in

press-a.

Spangler, R.; Zhou, Y.; Maggos, C.E.; Zlobin, A.; Ho, A.; and Kreek, M.J.

Dopamine antagonist and “binge” cocaine effects on rat

opioid and dopamine transporter mRNAs. Neuroreport, in

press-b.

Spangler, R.; Zhou, Y.; Schlussman, S.D.; Ho, A.; and Kreek, M.J. Behavioral

stereotypes induced by “binge” cocaine administration are
34

independent of drug-induced increases in corticosterone

levels. Behav Brain Res, in press-c.

Spangler, R.; Zhou, Y.; Unterwald, E.; Yuferov, V.; Ho, A.; and Kreek, M.J.

Kappa opioid receptor mRNA levels in the rat brain: Effects

of dopamine antagonists and cocaine. Proceedings of the 25th

International Narcotics Research Conference (INRC). Regul

Pept 54:283, 1994.

Spangler, R.; Zhou, Y.; Unterwald, E.M.; and Kreek, M.J. Opioid peptide and

receptor mRNA levels in the rat brain determined by TCA

precipitation of mRNA: cRNA hybrids. In: Harris, L.S., ed.

Problems of Drug Dependence, 1994: Proceedings of the

56th Annual Scientific Meeting of the College on Problems of

Drug Dependence, Inc. Vol. II. National Institute on Drug

Abuse Research Monograph 153. NIH Pub. No. (ADM)95-

3883. Washington, DC: Supt. of Docs., U.S. Govt. Print. Off.,

1995. p. 484.

Thompson, R.C.; Mansour, A.; Akil, H.; and Watson, S.J. Cloning and

pharmacological characterization of a rat mu opioid receptor.

Neuron 11:903-913, 1993.

Unterwald, E.M.; Cox, B.M.; Kreek, M.J.; Cote, T.E.; and Izenwasser, S.

Chronic repeated cocaine administration alters basal and

opioid-regulated adenylyl cyclase activity. Synapse 15:33-38,

1993.

Unterwald, E.M.; Ho, A.; Rubenfeld, J.M.; and Kreek, M.J. Time course of the

development of behavioral sensitization and dopamine

receptor upregulation during binge cocaine administration. J

Pharmacol Exp Ther 270(3):1387-1397, 1994b.

Unterwald, E.M.; Horne-King, J.; and Kreek, M.J. Chronic cocaine alters brain

mu opioid receptors. Brain Res 584:314-318, 1992.

Unterwald, E.M.; Rubenfeld, J.M.; and Kreek, M.J. Repeated cocaine

administration upregulates and , but not , opioid

receptors. NeuroReport 5:1613-1616, 1994a.

Volpicelli, J.R.; Alterman, A.I.; Hayashida, M.; and O’Brien, C.P. Naltrexone

in the treatment of alcohol dependence. Arch Gen Psychiatry

49:876-880, 1992.

Wang, J.B.; Imai, Y.; Eppler, C.M.; Gregor, P.; Spivak, C.; and Uhl, G.R. Muopiate receptor: cDNA cloning and expression. Proc Natl

Acad Sci U S A 90:10230-10234, 1993.

Wang, J.B.; Johnson, P.S.; Persicl, A.M.; Hawkins, A.L.; Griffen, C.A.; and Uhl,

G.R. Human opiate receptor, cDNA and genomic clones,

pharmacologic characterization and chromosomal assignment.

FEBS Lett 338:217-222, 1994a.

Wang, J.B.; Johnson, P.S.; Wu, J.M.; Wang, W.F.; and Uhl, G.R. Human 

opiate receptor second extracellular loop elevates dynorphin’s
35

affinity for / chimeras. J Biol Chem 269:25966-25969,

1994b.

Yu, J.; Butelman, E.R.; Woods, J.H.; Chait, B.T.; and Kreek, M.J. In vitro

biotransformation of dynorphin A1-17 is similar in human and

rhesus monkey blood as studied by matrix-assisted laser

desorption/ionization mass spectrometry. J Pharmacol Exp

Ther, in press.

Zhou, Y.; Spangler, R.; LaForge, K.S.; Maggos, C.E.; and Kreek, M.J.

Modulation of CRF-R1 mRNA in rat anterior pituitary by

dexamethasone: Correlation with POMC mRNA. Peptides

17:435- 441, 1996a.

Zhou, Y.; Spangler, R.; LaForge, K.S.; Maggos, C.E.; Unterwald, E.M.; Ho, A.;

and Kreek, M.J. Regulation of POMC gene expression in rat

pituitary, hypothalamus and amygdala by chronic

administration of CRH, dex, and methadone. In: Harris, L.S.,

ed. Problems of Drug Dependence, 1995: Proceedings of the

57th Annual Scientific Meeting of the College on Problems of

Drug Dependence. National Institute on Drug Abuse Research

Monograph 162. NIH Pub. No. (ADM)96-4116. Washington,

DC: Supt. of Docs., U.S. Govt. Print. Off., 1996b. p. 183.

AUTHOR

Mary Jeanne Kreek, M.D.

Professor and Senior Physician

Rockefeller University

1230 York Avenue

New York, NY 10021
36

Overview of Potential Treatment

Medications for Cocaine

Dependence

Elinore F. McCance

INTRODUCTION

The search for a pharmacotherapeutic agent for the treatment of

cocaine dependence began in the early 1980s as clinicians and

researchers realized that the cocaine epidemic was growing rapidly and

that standard drug counseling and self-help groups made little impact

on the addiction for many cocaine abusers. Cocaine was initially

viewed as a recreational drug for the wealthy with limited negative

consequences for the majority of users (Grinspoon and Bakalar 1980).

The widespread availability of cocaine and increased prevalence of

more addictive routes of administration (intravenous (IV) and

smoked) have resulted in cocaine abuse and dependence becoming one

of the most serious public health problems in the United States. The

National Institute on Drug Abuse (NIDA) estimates that at least 2

million persons are cocaine abusers and that 1 to 3 million persons are

in need of treatment (Kozel and Adams 1985).

Cocaine dependence is different from other major mental and

substance use disorders in that intensive research efforts have only

been underway for about 15 years. Truly elegant work has provided at

least a partial explanation for cocaine-induced behavioral and

physiological effects, and epidemiological and treatment research to

date has elucidated many of the clinical challenges yet to be met. The

lag between an understanding of molecular, cellular, and

neurobiological effects of cocaine and their relationship to behavioral

responses induced by cocaine has resulted in the testing of

pharmacological agents aimed at impacting cocaine abuse based on

rationales limited by the scientific and clinical understanding of the

disease at that time. The evolution of clinical trials methodologies

that will yield more useful clinical information and effectively test

underlying hypotheses continues. The gaps in scientists’ knowledge

and limits in clinical methodology to date have restricted the clinical

application of many studies. Given these limitations, it is not

surprising that no widely efficacious pharmacotherapy for the

treatment of cocaine dependence has emerged thus far.
37

This chapter will summarize the most recent efforts to identify an

effective medication for the treatment of cocaine dependence with a

focus on work reported over the last 5 years. Some of the clinical

attributes for development of an ideal pharmacotherapy will be

discussed, as well as rationales utilized for selecting potential

pharmacotherapies. New possibilities for medication treatment of

cocaine dependence will be briefly reviewed. These may constitute

the rudiments of hypotheses and rationales for effective treatments in

the future for this most difficult and challenging disorder.

RATIONALE FOR PHARMACOTHERAPY OF COCAINE

DEPENDENCE

Pharmacotherapy of any substance use disorder should be undertaken

to address specific problems arising in the course of treatment. For

example, the use of medication is often necessary to treat withdrawal

syndromes, particularly those in which patients are physiologically

addicted to the substance. The choice of a pharmacotherapy for

withdrawal should be based on a medical assessment that considers the

patient’s past and present medical history, as well as consideration of

the past history of detoxification and the level(s) of care available.

Medication is also considered as a means of relieving craving,

especially early in abstinence when such urges put the patient at

significant risk for relapse. Effective anticraving medications for

most substances of abuse are not available at this time, with the one

major exception of methadone maintenance for opiate dependence.

Medication treatment may be considered for the initiation and

maintenance of abstinence from the substance of abuse. There are

limited examples of such medications for the treatment of addictive

diseases at this time, including methadone and other long- acting

opiates such as buprenorphine or l-alpha-acetylmethadyl (LAAM),

which induce tolerance to the effects of opiates. Naltrexone is useful

for the treatment of opiate dependence by preventing euphoria when

opiates are self-administered. Disulfiram (Antabuse), a drug that

results in an aversive physical reaction when alcohol is taken, is a

useful adjunct in the treatment of alcohol dependence for selected

patients.

Cocaine does not cause physiological dependence, but the

psychological addiction in patients with cocaine use disorders can be

disabling (Gawin and Ellinwood 1988, 1989). An abstinence

syndrome has been described for cocaine dependence and consists of

three phases: the “crash,” withdrawal, and extinction (Gawin and
38

Kleber 1986, 1988). Medication management of these phases could

be useful for the treatment of cocaine use disorders.

The “crash” is associated with exhaustion following a binge, but other

symptoms may occur including agitation, anxiety, depression, and

psychosis. These symptoms may require emergent medical and

psychiatric evaluation and treatment. An important part of the

management of patients with such symptoms is a thorough

psychiatric evaluation. Patients in whom symptoms of agitation,

psychosis, or depression do not abate over the first few days of

treatment, or those in whom such symptoms worsen, may have a

comorbid psychiatric disorder that requires psychiatric care. This

distinction is critically important in cocaine abusers. Several

investigators have shown that comorbid psychiatric disorders occur at

high frequency in cocaine abusers (Rounsaville et al. 1991; Weiss and

Mirin 1986; Weiss et al. 1988). Further, the lack of appropriate

psychiatric care will have a significant negative impact on the

patient’s ability to initiate and maintain abstinence. Finally, these

patients have needs that are not adequately addressed in standard

cocaine abuse treatment, which decreases the likelihood that

treatment outcome in these patients will be positive. Such individuals

require dual diagnosis treatment, which can address both the cocaine

abuse and the psychiatric disorder (Hellerstein and Meehan 1987;

Martino et al. 1995; Roberts et al. 1992).

The cocaine withdrawal syndrome is a constellation of affective and

psychological symptoms lasting from 2 to 10 weeks and is marked by

decreased energy, lack of interest, and anhedonia. These symptoms

fluctuate and are not severe enough to meet diagnostic criteria for an

affective disorder. Symptoms do not occur uniformly in newly

abstinent cocaine abusers and, in particular, patients who are

hospitalized following cessation of cocaine use may not experience

substantial withdrawal symptoms (Brower et al. 1988; Weddington et

al. 1990). The cocaine withdrawal syndrome does not generally

require medical treatment or pharmacotherapy. However, it is during

this time that relapse risk is greatest, so that development of a

pharmacotherapy that could assist the patient in initiating and

maintaining abstinence would be of great utility in the treatment of

cocaine dependence.
39

DEVELOPMENT OF A PHARMACOTHERAPY FOR COCAINE

DEPENDENCE

In developing an effective pharmacotherapy for substance

dependence, the various actions of the drug must be identified. Those

effects that will decrease substance abuse should be targeted for

pharmacotherapy development. In the case of cocaine, there are

several effects that may be points for pharmacotherapy intervention.

Cocaine dependence is characterized by either daily or binge use of the

drug, perpetuated by intense craving that use of the drug induces (Jaffe

et al. 1989). An agent that decreases cocaine craving would be useful

for treatment of cocaine dependence. Craving is stimulated by the

euphoria induced by the drug (the cocaine “high”). A drug that also

could diminish cocaine “high” might assist patients in maintaining

sobriety. Finally, repeated use of cocaine is associated with dysphoria,

paranoia, and agitation. Development of a medication treatment that

could accentuate these adverse psychological effects after a single use

might also dissuade the cocaine abuser from using subsequent doses of

cocaine.

The development of a medication for treatment of cocaine

dependence should include consideration of what the “ideal”

properties of such a pharmacotherapeutic agent might be. These

attributes are summarized in table 1. A medication should be available

by a convenient route of administration. Oral preparations are most

frequently used and are accepted by patients and clinicians. A

preparation that provides for a long-acting medication treatment,

such as an intramuscular (depot) formulation, or a transdermal

preparation, would offer certain advantages, including a decrease in

medication noncompliance and less frequent medication doses. While

frequent clinic visits are desirable early in treatment when it is

important to engage the patient and assist in the induction of

abstinence, frequent visits are less important in later stages of

treatment when the patient has been able to utilize treatment

effectively and could, in some cases, impede the patient’s ability to

engage in employment and other activities important to the recovery

process.

Medications must be medically safe and have few side effects. Patients

must be willing to accept the medication as an important and useful

part of treatment for their cocaine dependence. It is important to

match patients to treatments. There will be patients who will embrace

philosophies of drug abuse treatment that discourage the use of
40

TABLE 1. Properties of an ideal pharmacotherapy for cocaine

dependence.

• Convenient route of administration: oral, intramuscular (depot

formulation), or transdermal.

• Long acting.

• Medically safe with few side effects.

• Acceptable to patients presenting for treatment.

• Ideally, little abuse liability.

• Useful for more than one class of drug since many cocaine

abusers are polysubstance abusers.

• Used in conjunction with behavioral treatments that target the

drug abuse and psychosocial problems related to the drug abuse.

medication treatments and rely on group support and internal motivation

(such as self-help organizations). Other patients may have comorbid

psychiatric disorders that would be more appropriately treated with

standard psychotropic medications indicated for the psychiatric disorder.

Some patients will have medical disorders that would make them poor

candidates for a medication treatment of their drug abuse (e.g., disulfiram

would be contraindicated in the alcoholic patient with esophageal varices,

and caution must be used in naltrexone treatment of an opiate-dependent

individual with hepatic impairment). Finally, stage of treatment for the

cocaine addiction must be considered. Pharmacotherapies will be most

useful in the withdrawal phase when relapse risk is greatest. It would be

unusual to initiate medication for cocaine dependence after several

months of sustained abstinence.

An ideal medication treatment for cocaine dependence would have little

abuse liability and would be useful for treatment of other addictions in

addition to cocaine. Cocaine abusers are often polysubstance abusers and

frequently require treatment for alcoholism or opiate abuse/dependence.

Marijuana is also a frequently abused drug. At this time, no drug has been

shown to be efficacious for treatment of polysubstance abuse, though

some promising results have been shown for naltrexone for opiates

(Fraser 1990; Ling and Wesson 1990), alcohol (O’Malley et al. 1992;

Volpicelli et al. 1992), and disulfiram (for cocaine and alcohol) (Carroll et

al. 1993; Van Etten et al. 1994). Finally, any medication treatment must
41

be utilized in conjunction with psychosocial therapies to maximize

clinical benefit to the cocaine-dependent patient.

Pharmacotherapy Approaches

Medications development for cocaine dependence has followed two basic

approaches. The first has been an attempt to identify drugs that function

as cocaine antagonists, and the second has been to develop drugs with

properties similar to cocaine but with a longer duration of action, e.g.,

cocaine analogs. Cocaine antagonists include drugs that attenuate the

acute reinforcement and other effects that have become associated with

cocaine use. Advantages to the use of cocaine antagonists are that

decreasing euphoric effects of cocaine may be helpful in terminating the

abuse of the drug and in enhancing compliance with treatment. Another

advantage would be the low abuse liability of these drugs. A problem with

the use of cocaine antagonists is that such drugs might produce dysphoria

in patients, since the hedonic (and reinforcing) effects of cocaine are

thought to be mediated through dopaminergic systems (Fibiger et al.

1992; Koob 1992). Drugs that block the hedonic effects of cocaine could

block hedonic effects in general, resulting in dysphoria. Cocaine analogs

include drugs that would indirectly block acute cocaine effects by inducing

cross-tolerance. Advantages of such drugs include a reduction in cocaine

abstinence or withdrawal symptoms and enhanced compliance due to the

mood-enhancing effects of the drug. This might assist the patient in

breaking the cycle of cocaine use and could be helpful in the treatment

engagement process. A problem with this approach could be that cocaine

analogs would be stimulant drugs with abuse liability and street value.

Stimulant drugs may increase craving for cocaine or possibly increase

cocaine use. The use of such drugs would require careful monitoring in an

outpatient setting.

PHARMACOTHERAPY FOR COCAINE DEPENDENCE—RECENT

RESEARCH

The epidemic of cocaine abuse has resulted in intensive efforts to develop

effective treatments. These efforts include development of both

psychosocial interventions and medication treatments for cocaine

dependence. The purpose of this chapter is to review developments in

the search for an effective pharmacotherapy for cocaine dependence.

This chapter will also briefly consider additional agents that have yet to

be examined, but serve as examples of approaches that represent the

rationale of the use of cocaine agonists (medications that share some

pharmacological properties of cocaine) and the use of cocaine antagonists
42

(drugs that, based on pharmacological properties, might antagonize

cocaine effects) for the treatment of cocaine addiction.

A large number of medications have been used for treatment of cocaine

dependence (table 2). These medications have been utilized for a variety

of cocaine-related effects, including treatment of cocaine withdrawal,

treatment for cocaine craving, and initiation and maintenance of

abstinence. Many of these medications have appeared to be promising in

open trials. However, once studied in randomized, placebo-controlled

clinical trials, no medications to date have been shown to have substantial

efficacy for the treatment of cocaine dependence.

In addition to the lack of strong evidence for efficacy, there have been

numerous problems in the interpretation of results from many studies.

These difficulties are summarized in table 3. Studies to date have often

included small sample sizes and have been hampered by large dropout

rates. Diagnostic criteria have varied across clinical trials (some studies

enroll patients meeting diagnostic criteria for cocaine dependence, others

cocaine abuse, and others do not specify patient diagnosis). It is difficult

to know whether the results of a study are generalizable to the population

of treatment-seeking, cocaine-addicted individuals. Many of the larger

studies have looked at pharmacotherapies for cocaine dependence in

patients with primary opiate dependence and who receive methadone

maintenance. While this population tends to be more available for

followup because of the need to report to a clinic daily for methadone

treatment, it is likely that these patients are different from patients with

primary cocaine use disorders. Therefore, results obtained in studies

enrolling methadone-maintained cocaine abusers may not be

generalizable, though certainly such studies are important given the

prevalence of cocaine abuse in this group. Outcome variables differ

among clinical trials making it difficult to determine a drug’s

effectiveness. Studies that have utilized self-reports without confirmation

by urine toxicology screen may not be reflective of cocaine use by study

participants.

Future studies should be double blind and placebo controlled, and include

large, diagnostically well-defined samples. Standardized outcome

variables to assess the efficacy of the medication treatment
43

TABLE 2. Medications that hav

Dopaminergic agents Miscellaneous agents

bromocriptine buprenorphine

L-dopa carbamazepine

methylphenidate nimodipine

mazindol mazindol

pergolide nifedipine

amantadine disulfiram

flupenthixol clozapine

haloperidol tyrosine

bupropion naltrexone

selegiline gepirone

AMPT tryptophan

benztropine placebo

ritanserin

Antidepressants

desipramine (DMI)

fluoxetine

sertraline

imipramine

maprotilene

phenelzine

trazodone

lithium

should be utilized. Regular urine toxicology confirmation of drug use

needs to be included in all efficacy trials.

The following sections will summarize recently (primarily the last 3

years, but in some instances up to 5 years) reported studies

of pharmacotherapies for cocaine dependence. The

summary will include only studies that have been

conducted in humans with primary cocaine use disorders

(i.e., cocaine abuse or cocaine dependence). Although

many studies have been conducted in methadonemaintained, cocaine-abusing patients (i.e., patients with

primary opiate dependence), these patients are

sufficiently different from primary cocaine-abusing

patients both in terms of the neurobiological and

physiological effects of the primary drug of abuse and in
44

terms of the clinical treatment that results reported for

them may not be generalizable to those with primary
45

TABLE 3. Difficulties with inter

• Outcome variables differ:

Cocaine self-reports.

Urine toxicology screens.

Retention in treatment.

Craving assessments.

Length of abstinence.

Depression.

Cocaine withdrawal symptoms.

• Open-label studies.

• Small sample size.

• High dropout rate.

• Diagnosis at entry: Cocaine abuse versus cocaine dependence.

• Severity of cocaine use is usually not considered.

• Many studies report on opiate-dependent cocaine abusers.

cocaine use disorders. Summaries of the results of preclinical studies will

be limited to one very recent report that may have important

implications for chronic treatment of humans with the specified agent

(haloperidol) and recent preclinical reports that may lead the field in new

directions for medication development for cocaine dependence. Finally,

the studies reported will include both outpatient clinical trials and

inpatient studies that examine the effects of a particular agent on cocaine

responses in human volunteers.

Desipramine

Desipramine (DMI), a tricyclic antidepressant agent, was one of the first

medications to be studied as a treatment for cocaine dependence and, as

such, is one of the most extensively studied pharmacotherapies for
46

cocaine dependence to date. DMI may act as a specific antianhedonic

agent in cocaine-dependent patients (Gawin and Kleber 1986). Several

recent controlled clinical trials in cocaine abusers have been reported and

are summarized (table 4). One double-blind, placebo-controlled,

randomized trial included 29 subjects. In this trial, 14 subjects were

randomized to treatment with 40 mg of DMI daily. Outcome variables

included cocaine use self-reports, urine toxicology screens, and cocaine

craving measures. No significant difference was observed between DMI

and placebo treatment in this study (Covi et al. 1993, 1994). A large

clinical trial that examined the efficacy of DMI and psychotherapy, alone

and in combination, as a treatment for ambulatory cocaine abusers has

been reported (Carroll et al. 1994). In this 12-week, double-blind,

placebo-controlled trial, 139 subjects were assigned to one of four

conditions. These conditions included relapse prevention therapy plus

DMI, clinical management plus DMI, relapse prevention plus placebo, and

clinical management plus placebo. The mean dose of DMI was 200 mg

daily and was adjusted by a nonblinded psychiatrist in response to plasma

concentration (target ranges 300 to 750 ng/mL) and side effects. All

groups showed significant improvement in treatment retention and a

reduction in cocaine use at 12 weeks, but there were no significant main

effects for psychotherapy, pharmacotherapy, or the combination. Lower

severity patients (cocaine use 1 to 2.5 g/week) had improved abstinence

initiation when treated with DMI. DMI was significantly more effective

than placebo in reducing cocaine use during the first 6 weeks of treatment.

Depressed subjects had a greater reduction in cocaine use than

nondepressed subjects and had a better response to relapse prevention

therapy. The findings of this study underscore the heterogeneity among

cocaine abusers and the need to develop specialized treatments for distinct

subgroups of cocaine abusers.

Dopaminergic Agents

The most widely accepted explanation of cocaine-induced euphoria is that

dopamine (DA) reuptake inhibition results in increased

extracellular DA concentration in the mesolimbic and

mesocortical reward pathways in the brain. Numerous studies

have provided evidence for the importance of DA in the

reinforcing properties of cocaine. Low doses of DA
47

TABLE 4. Desipramine (DMI)

Desipramine (DMI)

Rationale: Blocks reuptake of norepinephrine and to a lesser extent

dopamine; postulated to act as a specific antianhedonic agent in

cocaine-dependent patients.

Controlled studies:

• (Covi et al. 1993, 1994): DMI was not significantly better than

placebo.

• (Carroll et al. 1994): DMI may be useful for selected patients:

Lower severity patients (cocaine use: 1 to 2.5 g/wk) had

significantly longer periods of abstinence.

DMI was associated with improved abstinence initiation weeks 2

through 6 only.

receptor antagonists, when injected systemically, consistently increase

cocaine self-administration in animals, indicating a of blockade of cocaine

effects (Koob 1992). In addition, 6-hydroxydopamine (6-OHDA) lesions

of dopaminergic terminals in the nucleus accumbens produce extinctionlike responding and a reduction in cocaine self-administration (Lyness et

al. 1979; Roberts et al. 1977, 1980). Similar lesions in other areas of the

brain (frontal cortex and caudate nucleus) do not alter cocaine selfadministration (Koob et al. 1987; Martin-Iverson et al. 1986). In vivo

brain microdialysis has also provided additional experimental data that

indicate that mesolimbic DA levels are associated with cocaine reward

(Fibiger et al. 1992). Conversely, cocaine abstinence that is characterized

by depression, irritability, and anxiety (the “crash”) has been

hypothesized to result from dopaminergic hypoactivity (Dackis and Gold

1985). Support for this hypothesis is derived from studies of in vivo

microdialysis during cocaine withdrawal (Weiss et al. 1992). These

experimental findings support the rationale for use of dopaminergic

agents in the treatment of cocaine dependence described below.

Dopamine Antagonists

DA antagonists, of which two have been examined (haloperidol and

flupenthixol), have been postulated to have potential as treatment agents
48

for cocaine dependence. This is due to their ability to block specific DA

receptors that might alter cocaine acute effects thought to be mediated by

a rapid increase in DA in the nucleus accumbens. The effects of

haloperidol on subjective and physiologic responses to cocaine was

examined in five cocaine-abusing volunteers (Sherer et al. 1989). In a

randomized, double-blind study design each subject received either

haloperidol 8 mg or placebo followed 20 minutes later by IV cocaine (40

mg) administration. Haloperidol attenuated expected increases in blood

pressure, but not heart rate. Haloperidol reduced subject ratings of

pleasant sensation following cocaine administration, but had no effect on

cocaine euphoria as measured by the variable “rush” (table 5).

Flupenthixol is a thioxanthene with DA antagonist properties. It is being

examined in controlled, outpatient trials for efficacy in the treatment of

cocaine dependence. In a 6-week, double-blind, placebo-controlled study

comparing DMI and flupenthixol, an interim data analysis showed a trend

toward better engagement in treatment for patients randomized to

flupenthixol treatment (Gawin et al. 1993; Khalsa et al. 1994) (table 5).

TABLE 5. Dopamine (DA) antagonists.

Rationale: Cocaine euphoria appears to be mediated by a rapid

increase in DA in nucleus accumbens; blockade of specific DA

receptors may change acute cocaine effects.

Haloperidol

• (Sherer et al. 1989): Pretreatment with haloperidol 8 mg

followed by IV cocaine (40 mg) showed decrease in pleasant

effects of cocaine, but no effect on cocaine euphoria as measured

by “rush.”

• (Kosten et al. 1994): Chronic haloperidol treatment enhanced

cocaine-induced conditioned place preference (CPP), while acute

treatment blocks CPP.

Flupenthixol

• (Gawin et al. 1993; Khalsa et al. 1994): A 6-week, double-blind,

placebo-controlled study comparing DMI and flupenthixol in

cocaine-dependent outpatients showed a trend toward better

engagement in treatment in group assigned to flupenthixol.

The effect of both acute and chronic haloperidol treatment on cocaineconditioned place preference in rats has been recently studied (Kosten et

al. 1994). Using a full cocaine dose-response function, acute haloperidol
49

was shown to block cocaine-conditioned place preference. In contrast,

chronic haloperidol treatment resulted in behavioral supersensitivity,

lowering the dose of cocaine that supports conditioned place preference.

This finding supports those of other studies that show that chronic

haloperidol treatment leads to receptor supersensitivity and enhanced

locomotor responses to cocaine (LeDuc and Mittleman 1993). This

study indicated that haloperidol and similar DA antagonists might be

contraindicated for long-term treatment of cocaine abuse. It appears that

one possibility is that such agents could contribute to enhanced cocaine

effects. These findings may also help to partially explain the high

prevalence of cocaine abuse in neuroleptic-maintained schizophrenics

(Schneier and Siris 1987).

Dopamine Agonists

It has been postulated that chronic cocaine use may deplete central DA,

which could result in supersensitivity of dopaminergic receptors. DA

hypofunction induced by cocaine abuse may underlie craving and

withdrawal symptoms often observed in recently abstinent cocainedependent patients. The following section includes a review of recent

studies that have used agents with DA agonist properties in the treatment

of cocaine use disorders.

Bromocriptine is an agonist with high affinity for the D2 receptor.

Treatment with bromocriptine might reverse dopaminergic deficits

induced by cocaine and ameliorate craving and withdrawal. Two studies

have addressed the utility of bromocriptine in the treatment of cocaine

dependence by examining effects of pretreatment with bromocriptine on

cocaine administration (table 6). Pretreatment with either bromocriptine

2.5 mg or 5 mg 2 hours prior to cocaine administration had no effect on

cocaine euphoria; however, heart rate following bromocriptine

pretreatment was augmented (Kumor et al. 1989). Another study

examined the effects of bromocriptine pretreatment (0, 1.2, or 2.5 mg)

on IV cocaine (0, 12.5, 25, or 50 mg) administration. While

bromocriptine did not alter the subjective effects of cocaine, significant

increases in heart rate were again observed with the combination (Preston

et al. 1992).

Controlled outpatient clinical trials have been limited with bromocriptine.

Early open studies using doses of 1.25 mg to 2.5 mg daily have yielded
50

TABLE 6. Dopamine (DA) agonists.

Rationale: Cocaine may deplete central DA, which may result in DA

receptor supersensitivity and DA hypofunction, which may

underlie craving, withdrawal.

Bromocriptine (D2 agonist)

• (Sherer et al. 1989): Bromocriptine pretreatment (2.5 mg or 5

mg) 2 hours prior to cocaine administration; no effect on cocaine

euphoria, increase in heart rate.

• (Preston et al. 1992): Pretreatment with bromocriptine (0, 1.2,

2.5 mg) did not alter subjective effects of cocaine (0, 12.5, 25, 50

mg IV); significant increase in heart rate was observed with the

combination.

• Few controlled clinical trials.

• Reports of difficulty with adverse event profile (headache,

vertigo, syncope).

Amantadine (DA release)

• (Sholar et al. 1994): Acute effects of amantadine (0, 200 mg, or

400 mg) on intranasal (IN) cocaine administration; attenuation of

heart rate increases following cocaine administration for both

doses of amantadine; the 200 mg dose was associated with

decreased cocaine “high,” chronic amantadine administration

(100 mg twice daily) enhanced euphoric effects of cocaine in male

subjects.

• (Weddington et al. 1991): 12-week, single-blind study (N = 54),

all treatment groups showed decrease in cocaine use and craving;

no evidence for efficacy of amantadine (400 mg/d).

• (Alterman et al. 1992): Amantadine 100 mg twice daily (N =

42) associated with significantly less cocaine-positive urines than

placebo-treated patients, though there was no difference in selfreport of cocaine or other substance use.
51

TABLE 6. Dopamine (DA) agonists (continued).

Bupropion (inhibits DA uptake)-Bromocriptine (D2 agonist)

• (Montoya et al. 1994): 8-week open-label trial using

combination of bupropion < 300 mg/d and bromocriptine < 7.5

mg/d; no decrease in cocaine-positive urines.

L-deprenyl (inhibits DA metabolism)

• (Haberny et al. 1994): Five subjects with history of IV cocaine

abuse, 2-day pretreatment with L-deprenyl 10 mg or placebo

followed by cocaine (0, 20, 40 mg IV); no alteration of

physiological or subjective effects of cocaine by L-deprenyl.

Methylphenidate (DA release)

• (Grabowski et al. 1994): Methylphenidate 20 mg SR twice daily

+ 5 mg standard versus placebo (N = 7) for 8 weeks; decreased

craving in methylphenidate group, no decrease in cocaine use.

conflicting results and suffered from high dropout rates (Dackis et al.

1987; Giannini and Baumgartel 1987). In a double-blind clinical trial

using bromocriptine 5 mg to 7.5 mg daily, the study drug was poorly

tolerated with frequently reported side effects of headaches, vertigo,

and/or syncope resulting in high dropout rates (Tennant and Sagherian

1987). The use of bromocriptine to treat acute cocaine abstinence has

recently been revisited in a small, double-blind, placebo-controlled trial

(Moscovitz et al. 1993). Bromocriptine 1.25 mg three times daily or

placebo was given to patients presenting to an emergency room for minor

medical complaints, but who were found to be abusing cocaine by urine

toxicology screen. Subjects were given followup appointments four times

over a 15-day period. Although the small sample size lacked statistical

power to make inference, the investigators found that bromocriptine was

generally well tolerated. Five of 14 subjects randomized to bromocriptine

returned for all visits and three of these subjects had negative urine

toxicology screens on all visits. Subjects randomized to bromocriptine

and placebo showed no difference in retention (bromocriptine group 43

percent, placebo group 31 percent). Those randomized to bromocriptine

had more urine toxicology screens negative for cocaine (67 percent) than

those randomized to placebo (31 percent). Drawbacks to this study

include the small sample size and its atypical quality, since these were not

subjects seeking treatment for perceived problems with cocaine use.

Additionally, there was no monitoring to determine compliance with the

study medication. Novel treatments with bromocriptine are being
52

explored and could include the use of bromocriptine in combination with

other agents. For example, an open-label study of the combination of

bromocriptine (œ 7.5 mg daily) and bupropion (œ 300 mg daily) was

conducted over an 8-week study period (Montoya et al. 1994a, 1994b).

There was a significant reduction in pre- and posttreatment self-reports

of cocaine use (p < 0.01), but no significant change in urine toxicology

screens (both qualitative and quantitative). This study provides evidence

for the safety of this combination, but does not support efficacy for the

treatment of cocaine dependence. However, these studies indicate that

bromocriptine may have some utility in the treatment of cocaine

dependence and should be considered in future, well-controlled studies.

Amantadine increases dopaminergic transmission, but whether the

mechanism is DA release, direct effects on DA receptors, or DA reuptake

blockade is unclear. There have been few recent controlled studies of

amantadine for treatment of cocaine dependence. These are summarized

in table 6. One study examined the effects of acute amantadine (200 mg

or 400 mg) and chronic amantadine (100 mg twice daily for 4 days)

followed by insufflation of cocaine 0.9 mg/kg (Sholar et al. 1994). Acute

effects of both amantadine doses on cocaine responses included

attenuation of heart rate increases, while the amantadine 200 mg dose was

associated with a decrease in cocaine “high.” Chronic administration of

amantadine 100 mg twice daily was associated with increased “high” in

male subjects after cocaine administration as compared to female subjects.

A 12-week, single-blind comparison of DMI (200 mg daily), amantadine

(400 mg daily), or placebo as adjunctive treatments to counseling for

cocaine dependence has been reported (Weddington et al. 1991). All

treatment groups demonstrated decreased cocaine use, craving, and

psychiatric symptoms, indicating no specific treatment effect of the

active medication treatments. The effectiveness of amantadine was

evaluated in a double-blind, placebo-controlled trial in which 42 patients

in a day treatment program were randomized to amantadine 100 mg twice

daily (N = 21) to be taken over 10 days or placebo (N = 21). Urine

toxicology screens showed that those who had received amantadine were

significantly more likely to be free of cocaine (p < 0.05) at the 2-week

and 1-month followup visits, though self-reports for the two treatment

groups did not differ. This study indicated that amantadine may have

some efficacy in early treatment of cocaine dependence (Alterman et al.

1992).

Bupropion is a second-generation antidepressant that enhances

dopaminergic transmission, but has little effect on serotonergic

neurotransmission. To date, experience with bupropion in clinical trials

has been limited. In an open pilot study, six methadone-maintained

cocaine abusers participated in an 8-week outpatient study in which they
53

received bupropion 100 mg three times daily (the usual dose used for

treatment of depression). At the 8-week followup, only one of the study

participants was still using cocaine. At the 3-month followup, the four

patients who achieved abstinence from cocaine during bupropion

treatment remained free of cocaine use as indicated by self-report and

urine analysis (Margolin et al. 1991). The results of a large multicenter

study designed to assess the effectiveness of bupropion for treatment of

cocaine addiction in methadone-maintained patients showed little

evidence for efficacy in this group (Vocci et al. 1994). Another study

explored the use of bupropion in conjunction with bromocriptine

treatment in primary cocaine abusers (table 6) (Montoya et al. 1994a,

1994b). Given its DA agonist properties, this drug should be considered

for further clinical trials to assess its efficacy for treatment of primary

cocaine dependence.

L-deprenyl is a monoamine oxidase type B inhibitor that specifically

inhibits the metabolism of DA. Its present indication is for the treatment

of Parkinson’s disease. The ability of L-deprenyl to potentiate DA has

led to consideration of its use in the treatment of cocaine dependence. A

study in five human volunteers examined the effects of L-deprenyl alone

and in combination with cocaine (Haberny et al. 1994) (table 6). Subjects

were treated with L-deprenyl 10 mg or placebo for 2 days. Each subject

participated in cocaine administration sessions following treatment with

L-deprenyl and following placebo treatment. Cocaine doses of 0, 20, and

40 mg were administered intravenously at 60-minute intervals. No

differences in physiological (cardiovascular) parameters or drug liking

were observed for sessions that included cocaine-alone administration or

the L-deprenyl-cocaine combination.

Methylphenidate (MP) is a stimulant drug primarily used in the treatment

of childhood attention deficit hyperactivity disorder. MP is a DA agonist

with pharmacological properties that include DA release and reuptake

inhibition. It is being studied as an initial treatment for cocaine

dependence (Grabowski et al. 1994) (table 6). This study represents a

unique approach to drug development for cocaine dependence. Subjects

were cocaine-dependent volunteers who were admitted to an inpatient

unit for a 2-day period during which pretreatment safety, physiological,

behavioral, and cognitive assessments were made. Subjects were

monitored and stabilized for 2 weeks in an outpatient clinic. Subjects (N =

7) were then randomly assigned either to placebo or to MP 20 mg

(sustained-release preparation) twice daily and 5 mg of standard MP daily

in an 8-week trial. Quantitative urine benzoylecgonine (BE)

determinations were conducted on urine samples obtained twice a week

and patient self-reports were also elicited. A preliminary report from this
54

ongoing study has indicated that retention is good, with only one dropout

from the MP group thus far. Reported desire to use cocaine and

“preoccupation with use” are decreased in the MP group. Nonsignificant

increases in blood pressure and pulse were observed in the MP group. No

significant difference in abstinence or cocaine use as determined by

quantitative urine BE were observed in this small sample. This study

demonstrated a novel approach to drug development and showed that this

class of medications may be useful in the treatment of cocaine

dependence.

Cocaine Antagonists

A variety of medications have been examined for their effectiveness in

blocking the reinforcing effects of cocaine. These drugs, including

mazindol, fluoxetine, carbamazepine, naltrexone, and disulfiram, which

have been the subject of study over the past several years, have a broad

range of pharmacological properties, and all differ greatly in primary

indication. However, all have been postulated to antagonize the effects

of cocaine through pharmacological properties specific to each drug,

which might alter neurobiological and reinforcing effects of cocaine.

Mazindol. The euphorigenic and reinforcing effects of cocaine are

thought to be related to the effect of cocaine on DA reuptake

inhibition. Although the potency of cocaine-like drugs as

inhibitors of DA uptake is highly correlated with reinforcement in

animal studies, several potent DA uptake blockers do not produce

addiction and are not associated with euphoric effects in humans

(Rothman 1990). Mazindol is a DA reuptake inhibitor without

abuse liability. As such, mazindol may antagonize the effects of

cocaine and be useful in the treatment of cocaine dependence.

One study has reported on the effects of cocaine alone and in

combination with mazindol in cocaine-abusing volunteers

(Preston et al. 1993) (table 7). Subjects participated in a

crossover study that included 12 acute drug conditions. Subjects

were randomized to treatment with mazindol 0, 1, or 2 mg orally

2 hours prior to administration of IV cocaine (0, 12.5, 25, or 50

mg). Cocaine and mazindol alone were found to significantly
55

TABLE 7. Cocaine antagonists

Mazindol

Rationale: Blocks DA reuptake, may substitute for cocaine, but with weaker

effects, less abuse liability, cocaine use during treatment may be less

reinforcing.

• (Stine et al. 1992): Mazindol 2 mg daily or placebo (N = 33); no effect on

cocaine use, no significant adverse events.

• (Preston et al. 1993): Mazindol pretreatment (0, 1, and 2 mg) followed by

cocaine administration (0, 12.5, 25, 50 mg IV), no evidence that mazindol

altered subjective effects of cocaine, but the combination significantly

increased heart rate and blood pressure.

Fluoxetine (FLX)

Rationale: A serotonin (5-HT) reuptake inhibitor; cocaine potently inhibits 5-

HT reuptake, which may play a role in the dysphoric effects of cocaine;

medications such as FLX may accentuate such effects.

• (Walsh et al. 1992): Double-blind placebo crossover study (N = 5), FLX

30 and 40 mg, decreased response to cocaine 40 mg (IV), no correlation

between FLX level and cocaine responses.

• (Walsh et al. 1994a): Double-blind placebo crossover study (N = 8), dose

ranging FLX 0, 20, 40, 60 mg/d, cocaine 0, 20, 40 mg, FLX 40 mg and

60 mg doses decreased subjective effects of cocaine, no cardiovascular

toxicity.

• (Batki et al. 1993): Open treatment with FLX (mean dose = 45 mg/d) for

9 weeks in methadone-maintained, cocaine-dependent patients; quantitative

urine BE showed significant decrease in amount of cocaine used by the end

of the study.

• (Batki et al. 1993): FLX 40 mg versus placebo (N = 32) in cocaine

(“crack”)-dependent patients. FLX associated with longer retention (11

weeks versus 3 weeks), but there was no difference in quantitative urine BE.
56

increase heart rate and blood pressure. Mazindol had mild stimulant

effects and cocaine increased ratings for stimulant effects and desire for

cocaine. Mazindol followed by cocaine administration was associated with

larger and more sustained increases in heart rate and blood pressure as

compared to cocaine alone. Mazindol was not found to alter subjective

effects of cocaine. One subject had significant increases in heart rate and

blood pressure during mazindol-cocaine administration, which continued

for 3 hours. This subject also experienced anxiety and paranoia during

the mazindol-cocaine condition. One 12-week, double-blind, placebocontrolled clinical trial of mazindol 2 mg daily in cocaine-dependent

subjects has been reported (Stine et al. 1992) (table 7). Of 33 patients

who consented to participate, 16 dropped out, and the average length of

treatment was 5 weeks. Mazindol had no significant association with

depression or anxiety symptoms, nor has this dose been associated with

any reduction in cocaine use as measured by self-reports and urine

toxicology screens.

Fluoxetine. Cocaine has been found to inhibit the uptake of serotonin (5-

HT) two to four times more potently than that for DA (Ritz and Kuhar

1989). 5-HT synthesis or receptor blockade potentiates (but the 5-HT

precursor, 5-hydroxytryptophan, antagonizes) cocaine-induced

locomotor activity in animals (Cunningham et al. 1992). Studies have

demonstrated that chronic cocaine administration results in a net decrease

in 5-HT neurotransmission as a result of enhanced 5-HT autoregulatory

mechanisms (Pradhan et al. 1978). This has been postulated to be a

mechanism underlying the psychological consequences of chronic cocaine

abuse. These findings have led to trials of medications with effects on

central serotonergic regulation for the treatment of cocaine abuse. The

drug in this class that has been studied most extensively is fluoxetine.

Several well-controlled clinical trials with fluoxetine have been conducted

in patients with cocaine use disorders (table 7). One double-blind,

placebo-controlled, crossover study (N = 5) determined the effects of

treatment with 30 mg or 40 mg of fluoxetine followed by administration

of IV cocaine (40 mg). Fluoxetine was associated with decreased “rush,”

magnitude of drug effect, drug liking, and “good effects.” There was a

negative correlation between response to the cocaine dose and plasma

fluoxetine concentration, suggesting greater attenuation of cocaine

effects with higher plasma fluoxetine levels (Walsh et al. 1992). A

second study has been reported that examined the interaction of cocaine

and fluoxetine in a dose-ranging study (N= 8) using fluoxetine 0, 20, 40,

or 60 mg daily on an ascending schedule, with cocaine administration 0,

20, or 40 mg intravenously at each fluoxetine dose (Walsh et al. 1994a).

There was no evidence of cardiovascular toxicity under any of the
57

conditions. The 40 mg and 60 mg doses of fluoxetine were found to

decrease subjective effects of cocaine. Fluoxetine has been utilized in

outpatient clinical trials in both methadone-maintained, cocainedependent patients and in patients with primary cocaine use disorders. An

open study in which methadone-maintained, cocaine-dependent patients

were treated with a mean dose of fluoxetine 45 mg daily and followed with

quantitative plasma and urine cocaine and BE concentrations showed a

significant decrease in cocaine use by the end of the 9-week treatment

period, though most subjects did not achieve abstinence (Batki et al.

1993). Urine BE concentration has been reported to correlate with

patients’ self-reports regarding cocaine use and craving (Batki et al.

1992). Fluoxetine has also been used as a treatment for primary cocaine

dependence (Washburn et al. 1994). Subjects were randomized to receive

fluoxetine 40 mg daily or placebo over a 12-week study period (N = 32).

Subjects receiving fluoxetine remained in treatment for a significantly

longer period of time (11 weeks versus 3 weeks) and remained abstinent

for longer periods. An analysis of two double-blind, placebo-controlled

trials in primary cocaine-dependent patients and secondary (methadonemaintained) cocaine-dependent patients showed that fluoxetine increased

retention in primary cocaine-dependent outpatients and reduced cocaine

use and craving in secondary cocaine dependence (Batki et al. 1994).

These findings appear to indicate potential effectiveness of fluoxetine in

the treatment of cocaine dependence.

Carbamazepine. Carbamazepine (CBZ) is an anticonvulsant medication

hypothesized to have potential as a treatment for cocaine abuse

because of its ability to block cocaine-induced “kindling” in

rodents. Kindling has been postulated to be a model for the

neurophysiological basis of cocaine craving. CBZ may also

reverse the DA receptor supersensitivity that may result from

chronic cocaine use, and its potential as a treatment for cocaine

dependence has been examined in several studies (table 8). A

double-blind, placebo-controlled, crossover study of the

interaction of CBZ with cocaine in six cocaine users has been

reported (Hatsukami et al. 1991). In this study, subjects were

treated with CBZ 400 mg daily for 5 days, which was followed by

administration of one 40 mg dose of smoked cocaine base. No

changes in subjective responses to cocaine were observed, but

significant increases in heart rate and diastolic blood
58

TABLE 8. Cocaine antagonists

Carbamazepine (CBZ)

Rationale: Blocks cocaine-induced “kindling” in rodents; kindling has

been proposed as a neurophysiological mediator of cocaine

craving.

• (Hatsukami et al. 1991): Pretreatment of six cocaine users with

CBZ 400 mg for 5 days followed by 40 mg smoked dose of

cocaine; no change in subjective effects of cocaine; significant

increases in heart rate and diastolic blood pressure.

• (Gorelick et al. 1994): CBZ did not alter self-administration of

IV cocaine in cocaine-dependent subjects; CBZ levels of 1 to 3 or

4 to 7 &g/mL.

• (Halikas et al. 1993): CBZ 400 mg versus placebo as adjunct to

psychosocial therapy, in sample of 183 cocaine abusers for 12

weeks, significant decrease in cocaine-positive urines and reported

reduction in craving; CBZ levels not reported.

• (Montoya et al. 1993): CBZ versus placebo in sample of 62

cocaine- dependent patients for 8 weeks; CBZ levels 5.6 + 0.8

&g/mL, no significant differences between CBZ and placebotreated groups.

• (Kranzler and Bauer 1993) CBZ 400 to 600 mg versus placebo in

40 cocaine-dependent patients; no effect of CBZ on any measures

(craving, cocaine use, paranoia during cocaine use, urine

toxicology).

Naltrexone

Rationale: Opioid antagonist; opiate pathways may be involved in

some of the reinforcing effects of cocaine; could potentially be

blocked by naltrexone administration.

• (Kosten et al. 1992): 50 mg naltrexone or placebo daily for 10

days followed by IV cocaine administration (0.125 to 0.5 mg/kg);

“dollar value” of cocaine decreased following naltrexone

treatment; augmentation of heart rate but no effect on blood

pressure for the naltrexone-cocaine condition.

• (Carroll et al. 1993): Open pilot of disulfiram and naltrexone for

cocaine-dependent, alcohol abuse/dependent patients: naltrexone

had no effect on cocaine or alcohol use.

• (Walsh et al. 1994b): Naltrexone in dose range 3.125 mg to 200

mg (weekly dose increases) had no effect on subjective or

physiological effects of IV cocaine (0, 20, 40 mg).
59

pressure occurred. In another double-blind, placebo-controlled study that

directly examined the safety and efficacy of CBZ in reducing cocaine use

and craving, subjects were administered CBZ in dosages that resulted in

plasma concentrations of either 1 to 3 mcg/mL (doses of 200 mg daily)

or 4 to 7 mcg/mL (doses of 400 mg to 600 mg daily). CBZ did not alter

cocaine self-administration or craving in these cocaine-dependent

subjects. No evidence for safety problems or toxicity with the

combination of cocaine and CBZ was observed in this study (Gorelick et

al. 1994).

Several double-blind, placebo-controlled studies in outpatients with

cocaine use disorders have been reported. In a 20-day, controlled, fixeddose (CBZ 200 mg, 400 mg, or placebo) trial, 30 volunteers unmotivated

for treatment and whose use of cocaine was unchanged from their usual

during the study period were evaluated for cardiovascular effects before

and during CBZ treatment. Systolic blood pressure was increased (2.1 mm

Hg) and corrected QT intervals on electrocardiogram were shortened,

while pulse was significantly increased (2.3 beats/minute), although all

observations remained within normal limits throughout the study (Halikas

et al. 1991). Several other studies have been conducted to determine the

effectiveness of CBZ for the treatment of cocaine use disorders in

outpatients. One study was conducted in which 183 subjects meeting

diagnostic criteria for cocaine abuse were randomized to CBZ 400 mg or

800 mg daily or placebo as an adjunct to psychosocial therapy. CBZ 400

mg was associated with a significant decrease in cocaine-positive urines

and a reduction in cocaine craving, and these findings were negatively

correlated with CBZ level (Halikas et al. 1993). Another double-blind,

placebo-controlled study that investigated the efficacy and safety of CBZ

treatment in 62 subjects meeting diagnostic criteria for cocaine

dependence found no significant difference in cocaine use, cocainepositive urine samples, or depressive symptoms measured by the Beck

Depression Inventory. Plasma CBZ levels of 5.6Å0.8 mcg/mL were

achieved by week 4 of this study (Montoya et al. 1993). Another study

examined CBZ 400 mg to 600 mg daily in 40 cocaine-dependent males

over a 12-week study period. No significant effect of CBZ was observed

for any of the outcome variables, which included self-reports of cocaine

use, weekly urine for BE, cocaine craving, frequency or intensity of use,

or cocaine-associated paranoia (Kranzler and Bauer 1993).

Naltrexone. Naltrexone is an opioid antagonist that has been examined

as a treatment agent for cocaine abuse in several small studies to date

(table 8). The rationale for use of naltrexone for cocaine addiction is

that opiate pathways may be important to pleasurable or euphoric effects

of cocaine; an antagonist of this pathway might decrease the reinforcing
60

effects of cocaine and, as a result, decrease cocaine use. This hypothesis

is supported by primate studies in which an attenuation of cocaine selfadministration was observed during naltrexone treatment (Mello et al.

1991). One study examined the self-reported and cardiovascular effects

of intravenously administered cocaine (0.125, 0.25, 0.50 mg/kg) after 10

days of treatment with naltrexone 50 mg or placebo in a double-blind,

randomized, within-subjects design (Kosten et al. 1992; Silverman et al.

1993). Cocaine-induced increases in self-reported dollar “value of

cocaine” and “unpleasant” were less during naltrexone than placebo

administration. Cocaine increased peak heart rate, and this elevation was

augmented by naltrexone. Cocaine-induced alterations in blood pressure

did not differ across naltrexone and placebo conditions. Another study

examined the effects of a range of naltrexone doses (3.125 mg to 200

mg, with weekly dose increases) on the subjective and physiological

effects of IV cocaine (0, 20, and 40 mg) (Walsh et al. 1994b). In this

study, naltrexone had no effect on subjective or physiological responses

to cocaine. One open pilot study compared the effectiveness of

naltrexone 50 mg daily to that of disulfiram 250 mg daily for treatment

of outpatients with cocaine dependence and alcohol abuse (Carroll et al.

1993). Naltrexone did not appear to impact cocaine or alcohol use in

this study. Findings thus far with naltrexone indicate that it would be

suitable for large, controlled outpatient trials to determine efficacy in the

treatment of primary cocaine use disorders.

Disulfiram. Disulfiram is an inhibitor of aldehyde dehydrogenase that has

been used in the treatment of selected patients with alcohol abuse

or dependence. Three pilot studies have examined the efficacy

and safety of disulfiram treatment for cocaine dependence (table

9). One recent study in six cocaine-dependent volunteers

examined the effect of disulfiram 250 mg on responses to IN

cocaine (2 mg/kg) using a randomized double-blind, placebocontrolled design (Hameedi et al. 1995; McCance-Katz et al.

1993). There was no significant difference in cocaine “high” or

in physiological responses during disulfiram-cocaine

administration as compared to cocaine alone. However, subjects

reported decreased craving for cocaine when treated with

disulfiram prior to cocaine administration. Additionally, several

subjects reported significant dysphoria when disulfiram preceded

cocaine administration. Plasma cocaine concentration following

disulfiram and cocaine administration was significantly greater,

and this may have contributed to the decreased craving and

increased dysphoria observed in some subjects.
61

TABLE 9. Cocaine antagonists.

Disulfiram

Rationale: Many cocaine abusers are comorbid abusers of alcohol; use

of alcohol leads to cocaine use in some persons and alcohol

enhances euphoric effects and alleviates dysphoric effects of

cocaine; inability to use alcohol with cocaine may decrease

cocaine use.

• (Hameedi et al. 1995; McCance-Katz et al. 1993): Double-blind,

randomized study of the effect of disulfiram 250 mg on IN

cocaine administration (2 mg/kg); no effect on cocaine “high,”

but decreased craving, increased anxiety and paranoia, no evidence

for toxicity based on cardiovascular responses.

• (Carroll et al. 1993): Open pilot study in 18 cocaine-dependent,

alcohol-abusing outpatients found disulfiram 250 mg daily was

associated with significantly less cocaine and alcohol use as

compared to treatment with naltrexone 50 mg daily.

• (Van Etten et al. 1994): Open treatment of outpatients with

cocaine dependence and alcohol abuse found a significant decrease

in both cocaine (> twofold decrease in cocaine-positive urines)

and alcohol use.

Another study reported on the effects of adjunct disulfiram therapy in

outpatients meeting DSM-III-R criteria for cocaine dependence and

alcohol abuse (Van Etten et al. 1994). Patients were treated for Æ 2

weeks on and off disulfiram 250 mg daily. Significantly fewer days of

drinking and fewer drinks per occasion were reported during disulfiram

treatment. A greater than twofold decrease in cocaine-positive urinalysis

results was obtained during disulfiram treatment. An open pilot study has

been reported in which 18 outpatients meeting diagnostic criteria for

cocaine and alcohol dependence (but not physiologically dependent on

alcohol) were randomized to treatment with disulfiram 250 mg daily or

naltrexone 50 mg daily in conjunction with individual psychotherapy

during a 12-week open trial (Carroll et al. 1993). Primary outcome

measures included frequency and intensity of alcohol and cocaine use.

Subjects self-reports of substance abuse were collected during weekly

interviews with blind raters and verified by urine toxicology screens.

Breathalyzer samples were obtained at each visit and all were negative.
62

Subjects treated with disulfiram reported significantly lower alcohol use

days as compared to subjects taking naltrexone, fewer total days using

alcohol, fewer total drinks during treatment, and more total weeks of

abstinence. Cocaine use was also significantly reduced in the disulfiram

group, with patients reporting a significantly lower percentage of cocaine

use days, fewer days of cocaine use, and fewer observed positive urine

screens for cocaine. Subjects reported fewer total grams of cocaine use

and more total weeks of abstinence, although these differences were not

statistically significant. One explanation for these results was that

alcohol may be a powerful conditioned cue for cocaine craving and that

disulfiram treatment may reduce exposure to alcohol, thereby arresting

the chain of cues leading to cocaine use. In addition, findings from a

study of simultaneous cocaine and alcohol administration (McCance-Katz

et al. 1993) showed that cocaine abusers can reliably distinguish euphoria

associated with combined cocaine-ethanol use from that of cocaine alone

and prefer the combination. Disulfiram-maintained cocaine abusers may

be less inclined to initiate cocaine use if they know they cannot

potentiate cocaine euphoria or titrate negative acute cocaine effects

through concurrent alcohol use. These findings indicate that disulfiram

may have some efficacy in the treatment of cocaine dependence, but this

remains to be confirmed in large, well-controlled outpatient trials.

FUTURE DIRECTIONS

A variety of drugs are being examined in preclinical studies and early

clinical trials to determine their potential as medication treatments for

cocaine dependence. These include drugs that might be expected to act as

cocaine agonists, such as the DA uptake inhibitors, which have shown

some promise in attenuation of cocaine effects in animal studies.

Examples of such medications include benztropine (Acri et al. 1994),

ifenprodil (Acri et al. 1994), and GBR 12909 (Char et al. 1994; Glowa et

al. 1994) (table 10). Medications that might act as cocaine antagonists

are also in preclinical and early clinical trials to examine potential safety

and efficacy for treatment of cocaine dependence (table 10). One

example of such a drug is the 5-HT2 antagonist ritanserin. A single-blind

trial conducted with eight cocaine-abusing volunteers pretreated with

ritanserin, and who then participated in a cocaine administration study,

has been reported (Sullivan et al. 1994). Ritanserin (5 mg and 10 mg)

appeared to attenuate cocaine responses. Cocaine antagonist-type drugs

might also include atypical neuroleptics such as risperidone or clozapine

(Kosten and Nestler 1994) and the D1 antagonist SCH23390 (Heidbreder

and Shippenberg 1994). Human studies have been initiated to determine

the effects of clozapine pretreatment on cocaine administration (F.
63

Hameedi, personal communication, October 1994). The N-methyl-Daspartate (NMDA) (excitatory amino acid) antagonists dextrophan and

dextromethorphan have also been studied in animals with some evidence

for attenuation of expected cocaine effects (Sepinwall et al. 1992).

Although no medication has emerged that effectively treats the cocainedependent patient, research to date has yielded important information

about the utility of numerous medications in the treatment of this

disorder. As important, the work in this field has yielded information

that will be critical to the design of future studies that will then provide

even greater insights into the treatment of cocaine dependence.

Preclinical studies continue to make inroads into understanding the

complex neurobiological underpinnings of cocaine dependence and to

identify promising new agents for study in clinical trials. The future of

treatment for this widely prevalent and disabling disorder presents difficult

challenges, but there are many possibilities for solutions that await further

investigation.

TABLE 10. Future directions.

Cocaine agonists in preclinical studies

Rationale: Drugs with mild psychomotor stimulant effects (e.g., DA

uptake inhibitors), but with other effects that may block the

positive effects of cocaine or enhance the negative effects of

cocaine.

• (Acri et al. 1994)

GBR12935: Potent and highly selective DA uptake inhibitor.

Benztropine: DA uptake inhibitor with muscarinic antagonist

activity.

Ifenprodil: Inhibits DA uptake at concentrations comparable

to those observed for cocaine.

GBR12935: Increased locomotor activity in mice; substituted

for cocaine in rats trained to discriminate cocaine;

enhanced cocaine effects; caused convulsions alone

and in combination with cocaine.

TABLE 10. Future directions (continued).

Ifenprodil: Attenuated stimulant effects of cocaine at doses

that did not reduce spontaneous activity when given

alone.

Benztropine: Increased locomotor activity in mice and

substituted for cocaine in rats trained to discriminate
64

cocaine; overall low efficacy as a stimulant, reduced

ability to enhance behavioral effects of cocaine, no

evidence of toxicity alone or with cocaine.

• (Glowa et al. 1994)

GBR 12909: Decreased cocaine responding in monkeys and was

not self-administered by cocaine naive monkeys.

Cocaine antagonists in preliminary studies

Rationale: Blockade of cocaine pharmacological effects by treatment

with drugs with specific targets may alter acute cocaine effects.

• (Kosten and Nestler 1994)

Clozapine: An atypical neuroleptic has been shown to inhibit

cocaine-conditioned place preference.

• (Heidbreder and Shippenberg 1994)

SCH23390: A D1 antagonist that has been shown to attenuate

cocaine effects in an animal model.

• (Sepinwall et al. 1992)

Dextrophan and

dextromethorphan: NMDA antagonists that have shown some

evidence for attenuation of cocaine effects in animal

studies.

REFERENCES

Acri, J.B.; Seidleck, B.; and Witkin, J.M. Effects of dopamine uptake inhibitors

on behavioral and toxic effects of cocaine. In: Harris, L.S., ed.

Problems of Drug Dependence, 1993: Proceedings of the

55th Annual Scientific Meeting, The College on Problems of

Drug Dependence, Inc. National Institute on Drug Abuse

Monograph 141. NIH Pub. No. 94-3749. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1994. p. 441.

Alterman, A.I.; Droba, M.; Antelo, R.E.; Cornish, J.W.; Sweeney, K.K.;

Parikh, G.A.; and O’Brien, C.P. Amantadine may facilitate

detoxification of cocaine addicts. Drug Alcohol Depend

31:19-29, 1992.

Batki, S.L.; Manfredi, L.; Jacob, P.; Delucci, K.; Murphy, J.; and Jones, R.T.

Fluoxetine in cocaine abuse: Urine benzoylecgonine
65

concentrations and cocaine use, craving and depression. ACNP

Annual Meeting Abstracts 227, 1992.

Batki, S.L.; Manfredi, L.B.; Jacob, P.; and Jones, R.T. Fluoxetine for cocaine

dependence in methadone maintenance: Quantitative plasma

and urine cocaine/benzoylecgonine concentrations. J Clin

Psychopharmacol 13:243-250, 1993.

Batki, S.L.; Washburn, A.M.; Manfredi, L.; Murphy, J.; Herbst, M.D.; Delucci,

K.; Jones, T.; Nanda, N.; Jacob, P.; and Jones, R.T. Fluoxetine

in primary and secondary cocaine dependence: Outcome using

quantitative benzoylecgonine concentration. In: Harris, L.S.,

ed. Problems of Drug Dependence, 1993: Proceedings of the

55th Annual Scientific Meeting, The College on Problems of

Drug Dependence, Inc. National Institute on Drug Abuse

Monograph 141. NIH Pub. No. 94-3749. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1994. p. 140.

Brower, K.J.; Maddahian, E.; Blow, F.C.; and Beresford T.P. A comparison of

self-reported symptoms and DSM-III-R criteria for cocaine

withdrawal. Am J Drug Alcohol Abuse 14:347-356, 1988.

Carroll, K.M.; Rounsaville, B.J.; Gordon, L.T.; Nich, C.; Jatlow, P.; Bisighini,

R.M.; and Gawin, F.H. Psychotherapy and pharmacotherapy

for ambulatory cocaine abusers. Arch Gen Psychiatry 51:177-

187, 1994.

Carroll, K.; Ziedonis, D.; O’Malley, S.; McCance-Katz, E.; Gordon, L.; and

Rounsaville, B. Pharmacologic interventions for abusers of

alcohol and cocaine: Disulfiram versus naltrexone. Am J

Addict 2:77-79, 1993.

Char, G.U.; Baumann, M.H.; Chen, C.I.-T.; Rice, K.C.; de Costa, B.R.;

Matecka, D.; and Rothman, R.B. The cocaine-induced rise in

extracellular dopamine in the nucleus accumbens is reduced by

GBR-12909 pretreatment. In: Harris, L.S., ed. Problems of

Drug Dependence, 1993: Proceedings of the 55th Annual

Scientific Meeting, The College on Problems of Drug

Dependence, Inc. National Institute on Drug Abuse

Monograph 141. NIH Pub. No. 94-3749. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1994. p. 122.

Covi, L.; Montoya, I.D.; Hess, J.M.; and Kreiter, N. Desipramine for

treatment of cocaine dependence: Randomized, double-blind,

placebo-controlled study. ACNP Annual Meeting Abstracts

173, 1993.

Covi, L.; Montoya, I.D.; Hess, J.M.; and Kreiter, N. Double-blind comparison

of desipramine and placebo for treatment of cocaine

dependence. CPDD Annual Scientific Meeting Abstracts,

1994.
66

Cunningham, K.A.; Paris, J.M.; and Goeders, N.E. Serotonin neurotransmission

in cocaine sensitization. Ann N Y Acad Sci 654:117-127,

1992.

Dackis, C.A., and Gold, M.S. New concepts in cocaine addiction: The

dopamine depletion hypothesis. Neurosci Biobehav Rev

9:469-477, 1985.

Dackis, C.A.; Gold, M.S.; Sweeney, D.R.; Byron, J.R.; and Climko, R. Singledose bromocriptine reverses cocaine craving. Psychiatry Res

20:261-264, 1987.

Fibiger, H.C.; Phillips, G.A.; and Brown, E.E. The neurobiology of cocaineinduced reinforcement. Ciba Foundation Symposium 166:96-

124, 1992.

Fraser, A.D. Clinical toxicology of drugs used in the treatment of opiate

dependency. Clin Lab Med 10:375-386, 1990.

Gawin, F.H., and Ellinwood, E.H. Cocaine and other stimulants: Actions, abuse,

and treatment. N Engl J Med 318:1173-1182, 1988.

Gawin, F.H., and Ellinwood, E.H. Cocaine dependence. Annu Rev Med 40:149-

161, 1989.

Gawin, F.H., and Kleber, H.D. Pharmacological treatment of cocaine abuse.

Psychiatr Clin North Am 9:573-583, 1986.

Gawin, F.H., and Kleber, H.D. Evolving conceptualizations of cocaine

dependence. Yale J Biol Med 61:123-136, 1988.

Gawin, F.H.; Khalsa, M.E.; Brown, J.; and Jatlow, P. Flupenthixol treatment of

crack users: Initial double-blind results. In: Harris, L.S., ed.

Problems of Drug Dependence, 1992: Proceedings of the

54th Annual Scientific Meeting of the College on Problems of

Drug Dependence. National Institute on Drug Abuse

Monograph 132. NIH Pub. No. 93-3505. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1993. p. 319.

Giannini, A.J., and Baumgartel, P. Bromocriptine in cocaine withdrawal. J Clin

Pharmacol 27:267-270, 1987.

Glowa, J.R.; Wojnicki, F.H.; de Costa, B.; Matecka, D.; Rice, K.C.; and

Rothman, R.B. The effects of GBR-12909 on responding of

rhesus monkeys maintained under schedules of cocaine and

food delivery. In: Harris, L.S., ed. Problems of Drug

Dependence, 1993: Proceedings of the 55th Annual Scientific

Meeting, The College on Problems of Drug Dependence, Inc.

National Institute on Drug Abuse Monograph 141. NIH Pub.

No. 94-3749. Washington, DC: Supt. of Docs., U.S. Govt.

Print. Off., 1994. p. 12.

Gorelick, D.A.; Weinhold, L.L.; Cone, E.J.; and Henningfield, J.E.

Carbamazepine (CBZ) does not alter cocaine selfadministration in human cocaine addicts. In: Harris, L.S., ed.

Problems of Drug Dependence, 1993: Proceedings of the
67

55th Annual Scientific Meeting, The College on Problems of

Drug Dependence, Inc. National Institute on Drug Abuse

Monograph 141. NIH Pub. No.

94-3749. Washington, DC: Supt. of Docs., U.S. Govt. Print.

Off., 1994. p. 137.

Grabowski, J.; Schmitz, J.; Roache, J.D.; Rhoades, H.; Elk, R.; and Creson, D.L.

Methylphenidate (MP) for initial treatment of cocaine

dependence and a model for medication evaluation. In:

Harris, L.S., ed. Problems of Drug Dependence, 1993:

Proceedings of the 55th Annual Scientific Meeting, The

College on Problems of Drug Dependence, Inc. National

Institute on Drug Abuse Monograph 141. NIH Pub. No. 94-

3749. Washington, DC: Supt. of Docs., U.S. Govt. Print. Off.,

1994. p. 436.

Grinspoon, L., and Bakalar, J.B. Drug dependence: Non-narcotic agents. In:

Kaplan, H.I.; Freedman, A.M.; and Sadock, B.J., eds.

Comprehensive Textbook of Psychiatry. Baltimore: Williams

and Wilkins, 1980. pp. 1621-1622.

Haberny, K.A.; Walsh, S.L.; Ginn, D.; and Bigelow, G.E. Interaction of

selegiline and cocaine in human cocaine abusers. CPDD

Annual Scientific Meeting Abstracts, 1994.

Halikas, J.A.; Crosby, R.D.; Koop, L.P.; Crea, F.; Nugent, S.M.; and Carlson,

G.A. Daily monitored cardiovascular effects of carbamazepine

in chronic crack cocaine users. Psychopharmacol Bull

27:345-351, 1991.

Halikas, J.A.; Crosby, R.D.; Pearson, V.L.; Graves, N.M.; Nugent, S.M.; and

Carlson, G.A. Carbamazepine improves early cocaine

treatment retention and treatment effectiveness. ACNP

Annual Meeting Abstracts 175, 1993.

Hameedi, F.A.; Rosen, M.I.; McCance-Katz, E.F.; McMahon, T.J.; Price, L.H.;

Jatlow, P.I.; Woods, S.W.; and Kosten, T.R. Behavioral,

physiological and pharmacological interaction of cocaine and

disulfiram. Biol Psychiatry 37:560-563, 1995.

Hatsukami, D.; Keenan, R.; Halikas, J.; Pentel, P.R.; and Brauer, L.H. Effects

of carbamazepine on acute responses to smoked cocaine-base

in human cocaine users. Psychopharmacology 104:120-124,

1991.

Heidbreder, C., and Shippenberg, T.S. Sensitization to the conditioned

rewarding effects of cocaine: Pharmacological and temporal

characteristics. CPDD Annual Scientific Meeting Abstracts,

1994.

Hellerstein, D., and Meehan, B. Outpatient group therapy for schizophrenic

substance abusers. Am J Psychiatry 144:1337-1339, 1987.
68

Jaffe, J.H; Cascella, N.G.; Kumor, K.M.; and Sherer, M.A. Cocaine-induced

cocaine craving. Psychopharmacology 97:59-64, 1989.

Khalsa, E.; Jatlow, P.; and Gawin, F. Flupenthixol and desipramine treatment

of crack users: Double blind results. In: Harris, L.S., ed.

Problems of Drug Dependence, 1993: Proceedings of the

55th Annual Scientific Meeting, The College on Problems of

Drug Dependence, Inc. National Institute on Drug Abuse

Monograph 141. NIH Pub. No. 94-3749. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1994. p. 439.

Koob, G.F. Neural mechanisms of drug reinforcement. Ann N Y Acad Sci

654:171-191, 1992.

Koob, G.F.; Vaccarino, F.J.; Amalric, M.; and Bloom, F.E. Positive

reinforcement properties of drugs: Search for neural

substrates. In: Engel, J., and Oreland, L., eds. Brain Reward

Systems and Abuse. New York: Raven Press, 1987. pp. 35-50.

Kosten, T.A., and Nestler, E. Clozapine attenuates cocaine conditioned place

preference. Life Sci 55:PL9-14, 1994.

Kosten, T.A.; Miserendino, M.J.D.; Marby, D.W.; and Nestler, E.J. Chronic

haloperidol enhances cocaine conditioned place preference.

In: Harris, L.S., ed. Problems of Drug Dependence, 1993:

Proceedings of the 55th Annual Scientific Meeting, The

College on Problems of Drug Dependence, Inc. National

Institute on Drug Abuse Monograph 141. NIH Pub. No. 94-

3749. Washington, DC: Supt. of Docs., U.S. Govt. Print. Off.,

1994. p. 13.

Kosten, T.R.; Silverman, D.G.; Fleming, J.; Kosten, T.A.; Gawin, F.; Compton,

M.; Jatlow, P.; and Byck, R. Intravenous cocaine challenges

during naltrexone maintenance: A preliminary study. Biol

Psychiatry 32:543-548, 1992.

Kozel, N.J., and Adams, E.H. Cocaine Use in America: Epidemiologic and

Clinical Perspectives. National Institute on Drug Abuse

Monograph 61. DHHS Pub. No. 85-1414. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1985. pp. 35-49.

Kranzler, H.R., and Bauer, L.O. Carbamazepine for cocaine dependence. ACNP

Annual Meeting Abstracts 175, 1993.

Kumor, K.; Sherer, M.; and Jaffe, J. Effects of bromocriptine pretreatment on

subjective and physiological responses to IV cocaine.

Pharmacol Biochem Behav 33:829-837, 1989.

LeDuc, P.A., and Mittleman, G. Interactions between chronic haloperidol

treatment and cocaine in rats: An animal model of

intermittent cocaine use in neuroleptic treated populations.

Psychopharmacology 110:427-436, 1993.

Ling,W., and Wesson, D.R. Drugs of abuse: Opiates. West J Med 152:565-572,

1990.
69

Lyness,W.H.; Friedle, N.M.; and Moore, K.E. Destruction of dopaminergic

nerve terminals in nucleus accumbens: Effect of damphetamine self-administration. Pharmacol Biochem Behav

11:663-666, 1979.

Margolin, A.; Kosten, T.; Petrakis, I.; Avants, S.K.; and Kosten, T. Bupropion

reduces cocaine abuse in methadone-maintained patients. Arch

Gen Psychiatry 48:87, 1991.

Martin-Iverson, M.T.; Szostak, C.; and Fibiger, H.C. 6-hydroxydopamine

lesions of the medial prefrontal cortex fail to influence

intravenous self-administration of cocaine.

Psychopharmacology 88:310-314, 1986.

Martino, S.; Workman, J.; Boozang, J.; and McCance-Katz, E. The

development of a dual diagnosis partial hospital program.

Continuum: Developments in Ambulatory Mental Health Care

2:145-165, 1995.

McCance-Katz, E.F.; Price, L.H.; Kosten, T.R.; Hameedi, F.; Rosen, M.I.; and

Jatlow, P.I. Pharmacology, physiology and behavioral effects

of cocaethylene in humans. ACNP Annual Meeting Abstracts

237, 1993.

Mello, N.K.; Kamien, J.B.; Mendelson, J.H.; and Lukas, S.E. Effects of

naltrexone on cocaine self-administration by rhesus monkey.

In: Harris, L.S., ed. Problems of Drug Dependence, 1990:

Proceedings of the 52nd Annual Meeting, The Committee on

Problems of Drug Dependence, Inc. National Institute on

Drug Abuse Research Monograph 105. DHHS Pub. No. 91-

1753. Washington, DC: Supt. of Docs., U.S. Govt. Print. Off.,

1991. pp. 617-618.

Montoya, I.; Preston, K.; Cone, E.; Rothman, R.; and Gorelick, D. Safety and

efficacy of bupropion in combination with bromocriptine for

treatment of cocaine dependence. Neuropsychopharmacology

10:129S, 1994.

Montoya, I.D.; Levin, F.R.; Fudala, P.J.; and Gorelick, D.A. Double-blind study

with carbamazepine for treatment of cocaine dependence.

ACNP Annual Meeting Abstracts 173, 1993.

Moscovitz, H.; Brookoff, D.; and Nelson, L. A randomized trial of

bromocriptine for cocaine users presenting to the emergency

department. J Gen Intern Med 8:1-4, 1993.

O’Malley, S.S.; Jaffe, A.J.; Chang, G.; Shottenfeld, R.S.; Meyer, R.E.; and

Rounsaville, B. Naltrexone and coping skills therapy for

alcohol dependence. A controlled study. Arch Gen Psychiatry

49:881-887, 1992.

Pradhan, S.N.; Battacharya, A.K.; and Pradhan, S. Serotonergic manipulation

of the behavioral effects of cocaine in rats. Commun

Psychopharmacol 2:481-486, 1978.
70

Preston, K.L.; Sullivan, J.T.; Berger, P.; and Bigelow, G.E. Effects of cocaine

alone and in combination with mazindol in human cocaine

abusers. J Pharmacol Exp Ther 267:296-307, 1993.

Preston, K.L.; Sullivan, J.T.; Strain, E.C.; and Bigelow, G.E. Effects of cocaine

alone and in combination with bromocriptine in human

cocaine abusers. J Pharmacol Exp Ther 262:279-291, 1992.

Ritz, M.C., and Kuhar, M.J. Relationship between self-administration of

amphetamine and monoamine receptors in brain: Comparison

with cocaine. J Pharmacol Exp Ther 248:1010-1017, 1989.

Roberts, D.C.S.; Corcoran, M.E.; and Fibiger, H.C. On the role of ascending

catecholaminergic systems in intravenous self-administration

of cocaine. Pharmacol Biochem Behav 6:615-620, 1977.

Roberts, D.C.S; Koob, G.F.; Klonoff, P.; and Fibiger, H.C. Extinction and

recovery of cocaine self-administration following 6-

hydroxydopamine lesions of the nucleus accumbens.

Pharmacol Biochem Behav 12:781-787, 1980.

Roberts, L.J.; Shaner, A.; Eckman, T.A.; Tucker, D.E.; and Vaccaro, J.V.

Effectively treating stimulant abusing schizophrenics: Mission

impossible? New Dir Ment Health Serv 53:55-65, 1992.

Rothman, R.B. High affinity dopamine reuptake inhibitors as potential

cocaine antagonists: A strategy for drug development. Life Sci

46:PL17-21, 1990.

Rounsaville, B.J.; Anton, S.F.; Carroll, K.M.; Budde, D.; Prusoff, B.A.; and

Gawin, F. Psychiatric diagnosis of treatment-seeking cocaine

abusers. Arch Gen Psychiatry 48:43-51, 1991.

Schneier, F.R., and Siris, S.G. A review of psychoactive substance use and abuse

in schizophrenia, patterns of drug choice. J Nerv Ment Dis

175:641-652, 1987.

Sepinwall, J.; Vincent, G.P.; and Williams, S. Differential profiles of NMDA,

5-HT3 and D1 and D2 antagonists as antagonists of the

stimulant actions of cocaine in mice. ACNP Meeting Abstracts

224, 1992.

Sherer, M.A.; Kumor, K.M.; and Jaffe, J.H. Effects of intravenous cocaine are

partially attenuated by haloperidol. Psychiatry Res 27:117-

125, 1989.

Sholar, M.B.; Lukas, S.E.; Kouri, E.; and Mendelson, J.H. Acute and chronic

amantadine pre-treatment attenuates some of cocaine’s effect

in human subjects. In: Harris, L.S., ed. Problems of Drug

Dependence, 1993: Proceedings of the 55th Annual Scientific

Meeting, The College on Problems of Drug Dependence, Inc.

National Institute on Drug Abuse Monograph 141. NIH Pub.

No. 94-3749. Washington, DC: Supt. of Docs., U.S. Govt.

Print. Off., 1994. p. 431.
71

Silverman, D.G.; Kosten, T.R.; Fleming, J.; Kosten, T.A.; Gawin, F.H.;

Compton, M.; Jatlow, P.; and Byck, R. Intravenous cocaine

challenges during naltrexone maintenance. In: Harris, L.S., ed.

Problems of Drug Dependence, 1992: Proceedings of the

54th Annual Scientific Meeting of the College on Problems of

Drug Dependence. National Institute on Drug Abuse

Monograph 132. NIH Pub. No. 93-3505. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1993. p. 338.

Stine, S.; Krystal, J.; Kosten, T.; and Charney, D. Mazindol treatment of

cocaine abusers. ACNP Annual Meeting Abstracts 228, 1992.

Sullivan, J.T.; Testa, M.P.; Preston, K.L.; Blum, P.; and Jasinski, D.R.

Psychoactivity of ritanserin and its interaction with

intravenous cocaine. In: Harris, L.S., ed. Problems of Drug

Dependence, 1993: Proceedings of the 55th Annual Scientific

Meeting, The College on Problems of Drug Dependence, Inc.

National Institute on Drug Abuse Monograph 141. NIH Pub.

No. 94-3749. Washington, DC: Supt. of Docs., U.S. Govt.

Print. Off., 1994. p. 377.

Tennant, F.S., and Sagherian, A. Double-blind comparison of amantadine and

bromocriptine for ambulatory withdrawal from cocaine

dependence. Arch Intern Med 147:109-112, 1987.

Van Etten, M.L.; Higgins, S.T.; Budney, A.J.; Bickel, W.K.; Hughes, J.R.; and

Foerg, F. Disufiram therapy in patients abusing cocaine and

alcohol. In: Harris, L.S., ed. Problems of Drug Dependence,

1993: Proceedings of the 55th Annual Scientific Meeting, The

College on Problems of Drug Dependence, Inc. National

Institute on Drug Abuse Monograph 141. NIH Pub. No. 94-

3749. Washington, DC: Supt. of Docs., U.S. Govt. Print. Off.,

1994. p. 443.

Vocci, F.; Tai, B.; Wilkins, J.; Kosten, T.; Cornish, J.; Hill, J.; Li, S.H.;

Kraemer, H.; Wright, C.; and Bridge, P. The development of

pharmacotherapy for cocaine addiction: Bupropion as a case

study. CPDD Annual Scientific Meeting Abstracts 26, 1994.

Volpicelli, J.R.; Alterman, A.I.; Hayashida, M.; and O’Brien, C.P. Naltrexone

in the treatment of alcohol dependence. Arch Gen Psychiatry

49:876-880, 1992.

Walsh, S.L.; Preston, K.L., Sullivan, J.T.; and Bigelow, G.E. Fluoxetine

attenuates the effects of intravenous cocaine in humans.

ACNP Annual Meeting Abstracts 230, 1992.

Walsh, S.L.; Sullivan, J.T.; and Bigelow, G.E. Fluoxetine effects on cocaine

responses: A double-blind laboratory assessment in humans.

CPDD Annual Scientific Meeting Abstracts, 1994a.

Walsh, S.L.; Sullivan, J.T.; Preston, K.L.; Bigelow, G.E. Naltrexone

interactions with cocaine, hydromorphone, and a “speedball”
72

combination in substance abusers. In: Harris, L.S., ed.

Problems of Drug Dependence, 1993: Proceedings of the

55th Annual Scientific Meeting, The College on Problems of

Drug Dependence, Inc. National Institute on Drug Abuse

Monograph 141. NIH Pub. No. 94-3749. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1994b. p. 26.

Washburn, A.M.; Batki, S.L.; Delucci, K.; Murphy, J.; Jones, T.A.; and Nanda,

N. Predictors of outcome in a clinical trial of fluoxetine

treatment of primary cocaine dependence. In: Harris, L.S., ed.

Problems of Drug Dependence, 1993: Proceedings of the

55th Annual Scientific Meeting, The College on Problems of

Drug Dependence, Inc. National Institute on Drug Abuse

Monograph 141. NIH Pub. No. 94-3749. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1994. p. 139.

Weddington, W.W.; Brown, B.S.; Haertzen, C.A.; Cone, E.J.; Dax, E.M.;

Herning, R.I.; and Michaelson, B.S. Changes in mood, craving,

and sleep during short-term abstinence reported by male

cocaine addicts. Arch Gen Psychiatry 47:861-868, 1990.

Weddington, W.W.; Brown, B.S.; Haertzen, C.A.; Hess, J.M.; Mahaffey, J.R.;

Kolar, A.F.; and Jaffe, J.H. Comparison of amantadine and

desipramine combined with psychotherapy for treatment of

cocaine dependence. Am J Drug Alcohol Abuse 17:137-152,

1991.

Weiss, R.D., and Mirin, S.M. Subtypes of cocaine abusers. Psychiatr Clin North

Am 9:491-501, 1986.

Weiss, F.Y.; Hurd, Y.L.; Ungerstedt, M.A.; Plotsky, P.M.; and Koob, G.F.

Neurochemical correlates of cocaine and ethanol selfadministration. Ann N Y Acad Sci 654:220-241, 1992.

Weiss, R.D.; Mirin, S.M.; Griffin, M.L.; and Michael, J.L. Psychopathology in

cocaine abusers-changing trends. J Nerv Ment Dis 176:719-

725, 1988.

AUTHOR

Elinore McCance, M.D., Ph.D.

Assistant Professor of Psychiatry

Veterans Administration Connecticut Health Care System

Psychiatry 116-A

950 Campbell Avenue

West Haven, CT 06516
73

Methodologic Recommendations for

Cocaine Abuse Clinical Trials: A

Clinician-Researcher’s Perspective

Edward V. Nunes

INTRODUCTION

Dozens of medications have been tested as treatments for cocaine

abuse, but none has shown clear promise (Kosten 1992; O’Brien

1993). Intensive psychosocial treatments have shown some efficacy

(Carroll et al. 1991; Higgins et al. 1991, 1993; Magura et al. 1994;

McLellan et al. 1993; O’Brien 1993; Rawson et al. 1990, 1991), but

even with these, dropout rates and failure rates remain significant, and

powerful medication treatments for cocaine abuse are still needed.

This chapter develops the thesis that the medications development

effort for cocaine abuse would be improved by focusing on two

problems:

1. Viewing cocaine abuse as a unitary syndrome and testing drugs

on unselected samples. Instead, cocaine abusers may be

heterogenous and divisible into subgroups, which may respond to

different treatment approaches. For example, depression,

attention-deficit hyperactivity disorder, and alcohol abuse or

dependence all co-occur frequently with cocaine abuse and are all

amenable to pharmacotherapy.

2. Reliance upon simple open-label pilot trials in choosing

promising medications for further testing. Open-pilot trials have

tended to create false impressions of efficacy, which have not been

borne out in large placebo-controlled trials. O’Brien (1993) has

challenged the field to come up with alternatives to the open-pilot

trial. Designs for small, controlled pilot trials will be discussed.

This chapter builds from a review of controlled trials of tricyclic

antidepressants, mainly desipramine, for treatment of cocaine abuse.

This is the most thoroughly studied medication to date for treating

cocaine abuse and will serve as a case example, highlighting the

difficulties in testing medications for cocaine and motivating

subsequent methodologic recommendations.
74

CONTROLLED TRIALS OF TRICYCLIC ANTIDEPRESSANTS FOR

COCAINE ABUSE

Prospective, parallel group, placebo-controlled trials were selected for

review. In the following narrative, each trial is summarized, while the

main outcomes are collated in table 1.

The ground-breaking placebo-controlled trial of desipramine was that

by Gawin and colleagues (1989). Twenty-four patients completed at

least 1 week of treatment in each of three groups: placebo,

desipramine, and lithium were compared. Fifty percent of the sample

were intranasal (IN) users. The patients received counseling once per

week in addition to medication. Patients who dropped out during the

first week after randomization were replaced. The overall dropout

rate at 6 weeks of treatment, including those early dropouts, was about

45 percent. Desipramine patients remained in treatment significantly

longer than the other groups. The proportion of patients with 3 or

more consecutive cocaine-free weeks, urine confirmed, was

significantly greater on desipramine (59 percent) than placebo (17

percent). Robust effects of desipramine, compared to placebo, were

also found for quantity of cocaine use and for cocaine craving, both

self-report measures. For all groups, there was a substantial reduction

in both cocaine use and craving during the first week of treatment,

suggesting a moderate-sized placebo effect on these self-report

measures. Outcome of mood or psychological symptoms was not

reported, and less than 20 percent of the sample had comorbid DSMIII mood or anxiety disorders. However, removal of the small

subgroup with depressive disorders did not alter the favorable

desipramine effects. In summary, this trial replicated previous openlabel trials in suggesting substantial efficacy for desipramine in

unselected cocaine abusers.

A small, early trial by Giannini and Billett (1987) is of interest

because mood, instead of cocaine use, was the main outcome measure,

and again desipramine was found superior to placebo. Neither

cocaine use nor craving was measured in this trial. The trial is also

muddied because the desipramine group also received bromocriptine,

which was discontinued after the early weeks of treatment with patients

remaining on desipramine.
75

Percent

Intranasal

Users Dropout Rate

Abstinence

Measures

DMI > PBO

Self-Report

Cocaine Use

DMI > PBO

Cocaine

Craving

DMI > PBO

Depression/

Psych Sxs

DMI > PBO

Subgroups with Greater

Medication Effect

Gawin et al.

(1989)

50 45% @ 6 weeks + + (p) + (p) (removal of small

depressed subgroup did

not change effects)

Giannini et

al. (1987)

+

Weddington

et al. (1991)

30 50% @ 4 weeks + (trend) - (pp) - (pp) - (pp)

Kosten et al.

(1992)

11 25% @ 12 weeks - - (p) - (p) + Patients with

depression or without

antisocial personality

Arndt et al.

(1992)

(majority

using IV)

20% @ 12 weeks - + (weeks 2, 4)

- (weeks 8, 12)

- Patients without

antisocial personality

Carroll et al.

(1994)

29 21% @ 2 weeks

65% @ 12 weeks

- pp - (p) - (p) - (p) Patients with milder

cocaine abuse

Nunes et al.

(1995)

46 46% @ 4 weeks + (trend) - (p) + (p) + Patients with

depression or intranasal

use

KEY: (p) = moderate placebo response; (pp) = large placebo response.

Weddington and colleagues (1991) compared cocaine abusers who

completed at least 2 weeks of treatment on desipramine (N = 17),

placebo (N = 21), and amantadine (N = 16) over a 12-week trial. The

sample consisted of only 30 percent IN cocaine users. In addition to

medication, patients received twice-weekly psychotherapy. The

dropout rate was about 50 percent by week 4, if those who dropped

out prior to week 2 are included. The number of weeks of

consecutive, urine-confirmed cocaine-free weeks was analyzed as a

continuous measure. The report shows a one-way ANOVA

comparing the three groups, which was not significant. However, a

test of the difference between the desipramine and placebo means

would be a more appropriate gauge of the desipramine effect.

Comparing the means (Å standard error of mean) reported for the

desipramine (6.2Å1.1) and placebo (3.6Å0.8) groups yields a tstatistic of 1.96 with 36 degrees of freedom, which is a trend (p <

0.10) for a two-tailed test. An argument could even be made for a

one-tailed test (which would be significant here at the 0.05 level),

since consecutive cocaine-free weeks was a primary outcome measure

in the previous trial (Gawin et al. 1989), and this trial was a replication
76

attempt. For self-report cocaine use and craving, there were even

greater reductions across groups during the first week than those

observed by Gawin and colleagues (1989), again suggestive of a

substantial early placebo effect. With such large placebo effects,

demonstration of medication-placebo differences would be very

difficult, and in fact none were observed on these measures. Mood

outcome in the form of weekly Beck Depression Inventory scores was

reported in this trial. There was no desipramine-placebo difference

on the Beck, although the mean baseline score was less than 10,

suggesting the sample was at most mildly depressed to begin with,

leaving little room to demonstrate improvement from an

antidepressant. This trial has generally been presented as a negative

study and a failure to replicate. However, substantial placebo effects

on most measures, as well as relatively small sample sizes, severely

limit statistical power. Interestingly, on consecutive cocaine-free

weeks there is a less pronounced placebo effect and a marginally

significant desipramine-placebo difference.

A pair of studies were subsequently published evaluating desipramine

for cocaine abuse in methadone maintenance patients. Arndt and

colleagues (1992) randomized 79 patients to desipramine or placebo:

83 percent were intravenous (IV) users and only 11 percent were IN

users. The dropout rate was only 25 percent at 12 weeks, substantially

less than in the previous studies, likely reflecting the power of

methadone in a well-run, multimodality clinic. Side effects and the

dropout rate were greater on desipramine than placebo. No

desipramine-placebo differences were detected on self-reported

cocaine use or cocaine craving, and scores for these were about 40

percent reduced between baseline and end-study in the placebo group,

suggesting modest placebo effects. In contrast, the proportion of

drug-positive urines remained high throughout the trial, ranging from

60 percent to 90 percent, with no significant desipramine-placebo

difference, and little trend toward reduction in the placebo group over

time. Thus, similar to the pattern noted for other studies, abstinence

rates were relatively low with little placebo effect. A number of

Addiction Severity Index (ASI) factor scores and measures were

analyzed, and none showed significant desipramine-placebo

differences except for measures of psychiatric problems, where

desipramine demonstrated a significant beneficial effect. A secondary

analysis has subsequently suggested that medication effects were

greater when patients with antisocial personality are removed (Arndt et

al. 1994).
77

Kosten and colleagues (1992b) randomized 94 methadone

maintenance patients abusing cocaine to desipramine (N = 30),

amantadine (N = 33), or placebo (N = 31) for a 12-week trial. The

majority of patients were IV users. Dropout rates were again relatively

low at 27 percent on desipramine and 13 percent on placebo.

Interpretation of outcome is hampered by the fact that desipramine

and amantadine effects are not separated. For self-report cocaine use

there was a significant advantage for medication over placebo in the

second and fourth weeks of the trial, but no differences later in the

trial. Again, abstinence rates were low, with little improvement over

time (i.e., little placebo effect), and no medication-placebo

differences. In contrast to the other trials, there was also little

improvement in self-report cocaine use or craving over time. A

secondary analysis (Ziedonis and Kosten 1991) suggested the

subgroup with depression may have done better on medication than

on placebo. Another secondary analysis suggested medication effects

were enhanced by removing the subgroup with antisocial personality

(Leal et al. 1994).

Carroll and colleagues (1994a, 1994b) randomized outpatient cocaine

abusers (not on methadone) to two levels of psychotherapy (relapse

prevention or case management) and two levels of medication

(desipramine or placebo). There were 139 patients randomized; 110

completed two or more treatment sessions and 49 completed all 12

weeks, a large dropout rate consistent with that observed in the other

outpatient studies. The majority (62 percent) were freebase users,

while 29 percent were IN users. There were no effects of medication

assignment on any major outcome measures. Self-report measures of

cocaine abuse and for psychological problems (ASI composite scores)

showed moderate reductions over time on placebo. In a departure

from other trials, the proportion of abstinent days was high, around 70

percent in all groups. Analysis of interactions suggested a significant

advantage for desipramine over placebo on consecutive-abstinent days

in the subgroup with low-severity cocaine abuse at baseline.

The author and colleagues (Nunes et al., submitted) randomized 113

outpatient cocaine abusers to imipramine or placebo. All patients

received once-per-week counseling. Slightly under half the sample

(46 percent) were IN users. The attrition rate at 4 weeks was 46

percent (52/113). There were no medication-placebo differences in

self-report cocaine use. Interestingly, for abstinence-based measures,

there were at least trends favoring imipramine. Among 4-week

completers, the proportion of patients with three consecutive cocainefree weeks, urine- confirmed, was 11/34 (32 percent) on imipramine
78

versus 3/27 (11 percent) on placebo (p < 0.10). There were again

moderate-sized reductions in self-report cocaine use and craving on

placebo over time. Imipramine was superior to placebo on craving

and on the Hamilton Rating Scale for Depression score. This study

differed from the others in that it was stratified prospectively by route

of cocaine use and by level of depression. Analysis of these

subgroups suggested the imipramine effect on abstinence was

occurring mainly among the IN and depressed patients.

Summary of the Controlled Tricyclic Trials

Considering these trials together, and inspecting table 1, several points

become clear.

1. Dropout rates: Dropout rates are high, especially in the early

weeks of treatment.

2. Placebo effects: Substantial placebo effects are evident for selfreport measures of drug use and craving, although not for

measures of urine-confirmed abstinence.

3. Efficacy: The overall impression of efficacy, based both on

review of these trials and the author’s experience treating patients

in his own trial, suggests there is something there—some effect on

craving, or mood, or on cocaine use early in the trial, or perhaps

in some subgroup of patients. However, the effect is modest and

certainly not a large effect such as that of methadone upon opiate

dependence.

4. Subgroup hypotheses: Inspection of table 1 suggests tricyclic

effects on cocaine use may increase with the proportion of IN

users in the sample, suggesting that the subgroup of nasal users

may be more responsive. Posthoc analyses of several trials have

suggested other subgroup hypotheses—that depressed cocaine

users (Ziedonis and Kosten 1991) and mild cocaine users (Carroll

et al. 1994a, 1994b) may respond preferentially, and that cocaine

users with antisocial personality do not respond (Arndt et al.

1994; Leal et al. 1994). In the author’s trial, IN and depressed

groups, identified prospectively, appeared to respond

preferentially.

METHODOLOGIC ISSUES AND RECOMMENDATIONS
79

Sample Heterogeneity and Targeting Subgroups

Klein (1991) has argued that failure to recognize sample

heterogeneity can easily doom a drug development effort. If

response is restricted to a subgroup, and this is not recognized early in

Phase II, subsequent large Phase II or Phase III trials may falter

because study samples are diluted with unresponsive patients. As

noted in this chapter, subgroups based on addiction severity, route of

use, or depression may be relevant to cocaine abuse pharmacotherapy

and should be considered when devising interventions and designing

clinical trials, either in terms of restriction of inclusion criteria or

stratification.

A relatively unexplored strategy is treatment of comorbid psychopathology among cocaine abusers. Comorbid psychopathology is

more prevalent among substance abusers than in the general

population (Regier et al. 1990) and has consistently been associated

with poor prognosis (Carroll et al. 1993; Kosten et al. 1986;

Rounsaville et al. 1982, 1986). To the extent that psychopathology

may contribute to the etiology of substance abuse in an individual,

treatment of the psychopathology should improve outcome.

Treatment of depression with tricyclics in alcoholics and opiate

addicts has received some study. The author (Nunes and Quitkin, in

press) has recently reviewed this literature. The consensus from these

is encouraging in that depression appears identifiable and treatable.

Such treatment may improve substance abuse, although the evidence

for this is weaker. It seems likely that this strategy will prove to be a

useful adjunct to substance abuse treatment, but will not yield a largesized effect akin to methadone for opiate dependence. Nevertheless,

in the absence of powerful and globally effective anticocaine agents,

such subgroup strategies are probably worth pursuing.

Further, among cocaine abusers, there has been little study of the

treatment of subgroups with comorbid psychopathology. In addition

to depression, alcoholism, antisocial personality, attention-deficit

disorder, and schizophrenia are all associated with cocaine abuse. All

but antisocial personality can be effectively treated with

pharmacotherapy. Thus, a series of studies suggest themselves to

determine the extent to which targeting comorbid psychopathology is

useful in cocaine abuse.

The Placebo Effect and Open-Pilot Trials for Cocaine Abuse
80

Reflection on the placebo groups in the controlled tricyclic trials

suggests why open-pilot trials are likely to yield false-positive results

and reinforces the notion (Kosten 1992; O’Brien 1993) that this

design may be fundamentally flawed as a medications development

tool for cocaine abuse. In most of the trials, clear reductions over

time in self-report quantity of cocaine use and “craving” were

observed, especially over the first 1 to 3 weeks of the trial. Were these

uncontrolled pilot trials of new agents, most would have been

interpreted as indicating efficacy.

These “placebo” effects are probably created, in part, by the

psychosocial interventions that accompanied pharmacotherapy. All

the trials provided at least once-weekly counseling visits, and some

provided more (Carroll et al. 1994a, 1994b; Weddington et al. 1991).

Another contributor may be a reporting bias in which patients,

perhaps wishing to please their clinicians or significant others, report

less cocaine use over time when there had in fact been little real

change. This would be consistent with the observation that placebo

effects were more prominent for self-report measures, whereas for

more objective measures, urine-confirmed abstinence, and retention,

there was less placebo effect and dropout, and nonabstinence rates

remained high. A tendency of sicker patients to drop out, leaving the

sample progressively enriched with less severe cases, could also help

create the impression of improvement over time.

Placebo effects varied in strength across trials. This may simply

represent fluctuations due to sampling or differences between local

populations. However, it may also be that the psychosocial

interventions differed in their efficacy. This promoted the argument

that an overly effective psychosocial intervention might overwhelm

medication effects and that medications should therefore be tested in

the setting of minimal psychosocial interventions. On the contrary,

the relatively high rates of dropout and of failure to achieve

abstinence suggest there would still be plenty of room for a

medication to demonstrate an effect in such trials. An argument can

be made that medication trials should be superimposed on a strong

psychosocial intervention, so that the trial is informative in terms of

what medication has to add to good standard treatment. Anything less

may lack clinical credibility with the control group becoming a

“straw man” receiving poor care. The field can look to the

experience with methadone, which shows that this highly efficacious

medication is best applied in an adequate psychotherapeutic setting

(McLellan et al. 1993).
81

Recommendations

The above features of “placebo response” in cocaine abusers suggest

the following design features for preliminary trials:

1. A single-blind placebo lead-in phase: A 2-week, single-blind

placebo lead-in would “wash out” the early placebo effect and

early dropouts and provide a more stable baseline. The one

disadvantage of this feature would be loss of the opportunity to

see a medication effect on early attrition. On the other hand,

much early attrition may relate to insufficient motivation and

occur before a minimum adequate exposure to medication has

occurred.

The utility of the initial placebo lead-in phase has recently been

challenged in the setting of medication trials for outpatient

depression, based on analyses showing that it reduces ultimate

response rates about equally across groups and therefore does not

sharpen the discrimination between placebo and medication

(Trivedi and Rush 1994). On the other hand, Quitkin and

colleagues have shown, again in the setting of depression trials,

that removal of early responses (Quitkin et al. 1993) or

covariation by degree of early response (Quitkin et al., submitted),

does enhance power, although the advantage may be slight

(Quitkin et al., submitted). In cocaine abuse trials the advantage is

likely to be greater, since early placebo effects, and early attrition,

are more pronounced.

2. Some form of concurrent placebo control: Given the evident

variation in placebo effects in cocaine abuse trials, some estimate

of the placebo effect within the sample of a pilot study is needed,

even if the sample size is small.

3. A standardized and potent psychosocial intervention: The goals

of this would be to reduce attrition and reduce variation

contributed by nonpharmacologic factors. This would best be

manual driven, so that all patients receive approximately the same

“dose” of psycho-social/behavioral therapy. For example,

relapse prevention (Carroll et al. 1991, 1994b) has demonstrated

efficacy and is a reasonable choice. Simple once-per-week

counseling is probably not adequate treatment for outpatient

cocaine abusers (Kang et al. 1991), and trials may need to provide

more than this, particularly in the early weeks.
82

Providing positive incentives, contingent on clean urines, has proved a

powerful intervention (Higgins et al. 1991, 1993), and this might

indeed overpower medication effects. However, not all patients

respond. Medication might be tested as an adjunct in the incentiverefractory group, and this could be viewed as another example of the

strategy of restricting the inclusion criteria to target a specific

subgroup and reduce sample heterogeneity. Incentives might also be

applied, contingent on attendance, to improve retention in medication

trials.

Measurement of Outcome in Cocaine Abuse Pilot Trials

A second set of problems reflected in the controlled tricyclic trials has

to do with measurement of outcome. Reduced quantity of cocaine

use by self-report may not be all that meaningful clinically. Patients

wishing to please clinician-investigators may report less use over time,

giving the appearance of improvement in within-subjects comparisons

(i.e., an expectancy effect). The same problems may apply to

retrospective self-reports of craving. Objective outcomes may be

more likely meaningful. Urines remain the “gold standard” for

documenting abstinence, ultimately the most desirable outcome.

Quantitative urine cocaine metabolites from at least two samples per

week may provide more objective documentation of reduced use short

of abstinence (Batki et al. 1993). Several chapters in this monograph

present promising new methods for analyzing quantitative urines

(Preston et al., this volume). Response to cocaine-related cues in the

laboratory also deserves consideration. Cue response has been

associated with relapse (Ehrman et al. 1993) and includes objective

physiologic measures (Childress et al. 1992; Ehrman et al. 1992).

Nevertheless, Klein (1991) argues that in preliminary Phase II trials,

experienced clinicians should follow the patients because they may

observe important improvements not detected by the planned primary

outcome measures, or conversely they may judge improvement in

some primary outcome measure to be of little clinical significance.

The author found that direct clinical involvement with patients in his

own trial was helpful in interpreting the numerical outcomes.

Quitkin and colleagues (1984) and Klein (1991) also argue for the

importance of observing patients on a medication beyond an initial

6-week acute trial in a “maintained improver” design. An effect slow

to develop could be missed in a 6-week trial. More importantly, acute

improvements will be more clinically meaningful if sustained over

time, whereas transient improvements and “placebo effects” will wash
83

out. For example, in Gawin and colleagues’ (1989) original 6-week

desipramine trial, the response criterion of three or more consecutive,

urine-confirmed, cocaine-free weeks would be more impressive if

supplemented by a second 6 weeks of observation on medication as

opposed to long-term naturalistic followup during which treatment is

no longer controlled by design (Kosten 1992b).

Quitkin and Rabkin (1981) and Klein (1991) argue that it is useful to

study the medication withdrawal process systematically. For patients

who have improved on a medication, tapering back to placebo can

increase the information yield, since true medication responders

should relapse on placebo. This placebo-controlled discontinuation

design is discussed further below.

Recommendations for Design and Measurement

1. Emphasize “objective” outcome measures, including urineconfirmed abstinence, quantitative urine-cocaine metabolites, and

possibly response to cocaine-related cues.

2. Retain a role for the experienced clinician in judging whether a

clinically significant improvement has occurred and identifying

responsive subgroups.

3. Consider the “maintained improver” design (Quitkin et al. 1984),

in which patients remain on medication for a total of 12 weeks, a

6-week acute trial followed by a 6-week maintenance phase.

4. Consider the placebo-controlled discontinuation design (Quitkin

and Rabkin 1981), in which patients are systematically tapered

from medication back to placebo.

POTENTIAL EARLY PHASE II DESIGNS

Drawing together the methodologic issues discussed earlier, several

designs are considered as likely improvements over the open-pilot

trial. Again, the goal for “early Phase II” is to test drugs for

preliminary indications of safety and efficacy in small samples before

moving on to larger, more costly controlled trials. Each of the

following designs incorporates some form of placebo control and has

features that enhance power, allowing smaller samples to be utilized.

In keeping with the recommendations mentioned previously, all these

designs can include an initial placebo washout phase and a

manualized psychosocial intervention, received by all subjects, to
84

enhance retention and teach skills of abstinence initiation and relapse

prevention.

The Two-Period Crossover Design

This is a classic design aimed at extracting the maximum information

from a small sample. Power is in theory enhanced by the fact that

each patient serves as his or her own control. This design is best for

detecting effects with rapid onset, rapid offset, and few withdrawal or

“carryover” effects, in samples with low dropout rates (Fleiss 1986).

Unfortunately, it is not clear what offset or “carryover” effects might

occur with a cocaine abuse medication, and further, despite best

efforts at providing a psychotherapeutic foundation, dropouts will

occur. Batki and colleagues (1994) employed this design to test

fenfluramine in cocaine-abusing methadone patients. Interpretation

of the results was clouded both by dropouts and also by an effect of

time, such that patients in both groups who were retained into the

second period had reduced cocaine use compared to the first period.

Both the dropout and time effects are consistent with the results of the

desipramine trials reviewed earlier and are likely to hamper efforts to

employ this design. However, it might still be considered in stable

samples under highly controlled conditions such as inpatient or

intensive residential or day-treatment settings.

The Placebo-Controlled Discontinuation Trial

In this design, patients are at first treated in an open-label trial, and

responders are then randomly assigned to either remain on

medication or taper to placebo under a double-blind. This has the

advantage of an open-label trial that a larger number of patients get

initial exposure to the candidate medication. The open-label phase

can be analyzed for predictors of response. Only the relatively

homogenous sample of treatment responders enters the placebocontrolled phase, reducing heterogeneity and in theory enhancing

power (Klein 1991; Quitkin and Rabkin 1981). This would seem a

particular advantage, given the suggestions from the tricyclic trials that

subgroups (antisocial personality, mild severity, route of use,

depression) may be relevant to response. Of course, the randomized

experiment in this design bears more on maintenance of response or

relapse prevention, whereas a prospective randomized trial bears on

induction of initial response. These are different questions, both

relevant to cocaine abuse medications development.

The author and colleagues have successfully applied this design to a

study of imipramine treatment for depressed alcoholics (Nunes et al.
85

1993). However, a large number of patients had to be entered initially

(N = 85) in order to randomize a small number (N = 26), so that the

effort was ultimately larger and more labor intensive than one might

like for an initial pilot trial. This is partly due to dropouts and

nonresponders in the open phase, and partly to the problem that

patients who are doing well on open-label medication are often

reluctant to be randomized with a risk of coming off medication.

The Multiple Baselines Design

In a simple form of this design, patients are randomly assigned to two

groups, one of which receives the candidate medication and the other

placebo. At a later timepoint, the placebo group is crossed over to

medication. This provides an initial prospective, parallel-group,

placebo-controlled trial, yielding an estimate of the placebo effect

against which the effect of the candidate can be judged. At the same

time, this design affords advantage of the open-label trial that most

patients (i.e., those who do not drop out) can be observed on

medication. Such designs have yet to be implemented in clinical trials

of medications for substance abuse.

A Proposed Hybrid Design

Table 2 describes a hybrid design that combines features of the

multiple-baseline, crossover, and discontinuation designs. Treatmentseeking cocaine abusers enter a 2-week, single-blind, placebo baseline

phase, after which they are randomly assigned to one of two groups as

summarized in table 2, below.

TABLE 2. Proposed design for pilot clinical trials for cocaine

medications.

Schedule

2-Week

Baseline

Weeks

1-6

Weeks

7-12

Weeks

13-18

Weeks

19-24

Group

1

Placebo Candidate Candidate Placebo Placebo

Group

2

Placebo Placebo Candidate Candidate Placebo

The extended single-blind placebo phase at the front end is designed

to wash out early dropouts and early placebo effects. The first two 6-
86

week phases (weeks 1 through 6 and weeks 7 through 12) form a

multiple-baselines design, as discussed earlier. Finally, patients

remaining in treatment during weeks 13 through 24 are systematically

tapered back to placebo (double-blind), affording the opportunity to

observe whether symptoms of cocaine abuse recrudesce off

medication, as in a crossover or discontinuation design. For subjects

who complete the entire trial, the design may be viewed as an ABA

design, or a series of single-subject experiments. Ultimately, the

results of the initial between-groups comparison (weeks 1 through 6)

would be synthesized with the crossover discontinuations and withinsubjects comparisons, over several outcomes, and with clinicians’

impressions, to arrive at a preliminary impression of efficacy, safety,

and tolerability.

Data Analysis, Sample Size, and Power Considerations

Early Phase II clinical trials, such as the designs described previously,

are preliminary, exploratory studies with the purpose of suggesting

whether a candidate medication warrants consideration for larger,

more definitive trials. As such, investigators should be more

concerned about missing a true effect (Type II error) and more

tolerant of a Type I error, than in a larger, more definitive study.

The author would also argue that investigators should be interested

mainly in detecting medium to large effects. While small effects

might be of some theoretical interest, they are unlikely to have much

clinical impact on cocaine abuse.

Power will be discussed mainly with respect to a between-groups

medication versus placebo comparison, such as at the 6-week endpoint

in the hybrid design presented earlier. Power of within-subjects

comparisons (baseline versus endpoint on medication or ABA

designs) or of crossovers may be greater, although potentially more

clouded, by effects of time in treatment and attrition.

On an abstinence-based, dichotomous response measure, a low

placebo response rate could be anticipated based on the desipramineplacebo trials reviewed earlier. Assuming a placebo response rate of

10 percent, a sample size of 30 patients (15 per group) is sufficient to

detect large effects (10 percent response on placebo versus 65 percent

on medication), given the usual assumptions of beta = 0.20 and twotailed alpha = 0.05. Relaxing alpha to = 0.20 will begin to permit

detection of medium-sized effects (10 percent response versus 50

percent), at the expense of a greater Type I error rate (Fleiss 1981).
87

Likewise, for continuous measures such as self-report cocaine use,

proportion of positive urines across the weeks of a trial, or quantitative

urine cocaine metabolites, setting beta at 0.20 and two-tailed alpha

ranging from 0.05 to 0.20, 15 per group is sufficient to detect large

(1.1) to medium-large (0.80) effect sizes (Cohen and Cohen 1983).

These power estimates are based on simple two-group comparisons.

Power may be enhanced by stratifying the randomization on baseline

severity of cocaine use, and by entering baseline levels of outcome

measures as covariates in the data analysis. To the extent that baseline

correlates with outcome, power is increased (Fleiss 1986; Klein and

Ross 1993). The single-blind placebo lead-in, by reducing variance

contributed by early placebo effects, should protect power.

These power calculations assume two-tailed alphas. It can be argued

that interest is only in the one-tailed hypothesis that medication is

superior to placebo. Again, the goal is to determine whether a positive

effect is likely and whether further investigation with the candidate

medication is warranted. Failure to find an effect and finding

medication worse than placebo would have similar implications,

namely to discourage further research with that agent.

At N = 30, the designs proposed herein would not be highly powered

to detect statistical significance, particularly for small- to mediumsized effects. However, Cohen and Cohen (1983) argued that clinical

investigators should be more concerned with the sizes of effects than

with statistical significance per se. A useful alternative approach, then,

for early Phase II trials would be to place confidence limits on the

effect size. Investigators can then judge whether the likely range of

effect sizes warrants further trials. For example, it can be shown that

with a sample size of 15 per group, an observed effect size less than or

equal to zero virtually rules out a true effect in the medium to large

range. The more the observed effect exceeds zero, the greater the

probability of a medium to large effect.

IMPORTANCE OF LABORATORY MODELS

Medications development for many mental disorders enjoys the

advantage of prototype-effective medications. Examples include

methadone for opiate dependence or various medications effective

against depression. These prototypes can be used to validate

laboratory models, which then serve to screen and identify new agents

with potential efficacy. The prototype can also guide initial clinical

observations, serving as a model for how an effective agent should
88

perform clinically and what outcome measures are most appropriate.

An overarching problem with medications development for cocaine

abuse is that no such anticocaine prototype exists (O’Brien 1993).

Nevertheless, animal and human laboratory models with face validity

and at least limited predictive validity exist, and clinical investigations

need to be informed by them. Animal models will serve as a source

of hypotheses for candidate medications. Cocaine choice (Fischman

et al. 1990) and cue response (Childress et al. 1992; Ehrman et al.

1992) procedures are human laboratory models that can be used to

test potential medications. Early Phase II trials might be enhanced by

coordinated efforts between clinical trials and human laboratory

studies. Testing the same medication in both the clinic and the

laboratory would broaden the available data on safety and efficacy

and perhaps provide a clearer recommendation as to whether a

medication is promising for further Phase II or Phase III testing.

THE ROLE OF THE CLINICIAN-INVESTIGATOR

As discussed previously, Klein (1991) emphasizes the involvement of

clinician-investigators during early Phase II, arguing that their depth

of clinical experience can help to judge clinical significance when

statistical significance is detected on some measures, or to perceive

responsive or unresponsive subgroups. Direct work with patients can

also yield hypotheses, and the history of psychopharmacology

includes many advances that began with serendipity and clinical

observation.

Not surprisingly, then, many of the most senior principal investigators

and center directors at the National Institute on Drug Abuse (NIDA)

have strong clinical roots. At the author’s own institution, the role of

research-psychiatrist has always involved substantial clinical work.

However, the balance of priorities needed to flourish in the traditional

research-physician or research-clinician role is becoming more

difficult to achieve. Increased sophistication and complexity of

methodologies, regulatory burdens, and funding requirements, among

other issues, will perforce tend to draw principal investigators away

from regular contact with patients. A clinician-investigator who

spends substantial time with patients runs the risk of producing too

few papers, grants, and new initiatives to keep a research operation

going. Some balance needs to be struck. Furthermore, a steady

supply of new clinician-investigators is needed. NIDA is, therefore, to

be encouraged in its commitment to the funding of fellowships and

other early career mechanisms that afford research training to

clinicians and clinical experience to researchers.
89

SUMMARY AND CONCLUSIONS

This chapter reviewed the controlled tricyclic trials for cocaine abuse

with both a clinician’s and a researcher’s eye in order to develop

methodologic recommendations for future medications development

efforts. The review is summarized in table 2. The main points are

that attrition is high, particularly early in the trials; placebo effects are

high, particularly early and in subjective or self-report measures; and

the samples may be heterogeneous with responsive (depressed, mild

severity) and unresponsive (antisocial personality) subgroups.

Methodologic recommendations are summarized in table 3.

Emphasis is placed upon the potential heterogeneity of cocaine

abusers and targeting
90

TABLE 3. Summary of methodologic recommendations for early

Phase II clinical trials of medications for cocaine abuse.

Methodologic Problem Proposed Solutions

Sample heterogeneity • Target subgroups

(based, for example, on comorbid

psychopathology, route, or severity)

either by restricting inclusion or

stratification.

Large placebo effects

(especially on selfreport and subjective

measures)

• Emphasize

objective measures (e.g., urineconfirmed abstinence).

• Single-blind

placebo lead-in to wash out early

placebo effects and provide more stable

baseline.

• Discard the

uncontrolled, open-label pilot trial in

favor of small controlled pilot trials with

concurrent randomized placebo control.

• Standardized

psychosocial intervention.

High attrition • Single-blind

placebo lead-in to wash out early

dropouts.

• Increase intensity

of psychosocial intervention.

Measurement issues • Emphasize

objective measures, mainly urine-based

measures; consider also cue response.

• Weigh the

observations of experienced clinicians.

treatments to subgroups on the one hand, and various methodologic

recommendations to tighten up the design of early, small-scale pilot

trials on the other. These include use of potent, standardized

interventions to reduce attrition; a prolonged, single-blind placebo

lead-in to wash out early dropouts and placebo effects; discarding the

uncontrolled pilot trial in favor of crossover, discontinuation, or

multiple-baselines designs; and considering the impressions of

experienced clinicians as well as objective, urine-based measures when

judging efficacy. These recommendations are all arguable in that

they have disadvantages as well as advantages and that they all depart

to some extent from current practice and wisdom. It is hoped that
91

they will promote discussion and stimulate methodologic innovation

in the search for effective medications for cocaine abuse.

REFERENCES

Arndt, I.O.; Dorozynsky, L.; Woody, G.E.; McLellan, A.T.; and

O’Brien, C.P. Desipramine treatment of cocaine dependence in

methadone-maintenance patients. Arch Gen Psychiatry 49:888-

893, 1992.

Arndt, I.O.; McLellan, A.T.; Dorozynsky, L.; Woody, G.E.; and

O’Brien, C.P. Desipramine treatment for cocaine dependence:

Role of antisocial personality disorder. J Nerv Ment Dis

182(3):151-156, 1994.

Batki, S.; Washburn, A.; Manfredi, L.; Murphy, J.; Herbst, M.D.;

Delucchi, K.; Jones, T.; Nanda, N.; Jacob, P., III; and Jones, R.T.

Fluoxetine in primary and secondary cocaine dependence:

Outcome measured by quantitative benzoylecgonine. In: Harris,

L.S., ed. Problems of Drug Dependence, 1993: Proceedings of the

55th Annual Scientific Meeting, the College on Problems of Drug

Dependence, Inc. Vol. II. National Institute on Drug Abuse

Research Monograph 141. NIH Pub. No. 94-3749. Washington,

DC: Supt. of Docs., U.S. Govt. Print. Off., 1993.

Batki, S.L.; Bradley, M.; Herbst, M.; Jacob, P.; Jones, T.; Markman,

M.; and Jones, R.T. “A controlled trial of fenfluramine in cocaine

dependence: Preliminary findings.” Presented at American

Academy of Psychiatrists in Alcoholism and the Addictions

Annual Meeting, San Diego, December 1994.

Carroll, K.M.; Power, M.E.; Bryant, K.; and Rounsaville, B.J. One-year

follow-up status of treatment-seeking cocaine abusers. Psychopathology and dependence severity as predictors of outcome. J

Nerv Ment Dis 181:71-79, 1993.

Carroll, K.M.; Rounsaville, B.J.; and Gawin, F.H. A comparative trial

of psychotherapies for ambulatory cocaine abusers: Relapse

prevention and interpersonal psychotherapy. Am J Drug Alcohol

Abuse

17:229-247, 1991.

Carroll, K.M.; Rounsaville, B.J.; Charla, N.; Gordon, L.T.; Wirtz, P.W.;

and Gawin, F. One-year follow-up of psychotherapy and

pharmacotherapy for cocaine dependence; delayed emergence of

psychotherapy effects. Arch Gen Psychiatry 51:989-997, 1994a.

Carroll, K.M.; Rounsaville, B.J.; Gordon, L.T.; Nich, C.; Jatlow, P.;

Bisighini, R.M.; and Gawin, F.H. Psychotherapy and
92

pharmacotherapy for ambulatory cocaine abusers. Arch Gen

Psychiatry 51:177-187, 1994b.

Childress, A.R.; Ehrman, R.; Robsenow, D.J.; Robin, S.J.; and O’Brien,

C.P. Classically conditioned factors in drug dependence. In:

Lowinson, J.H.; Millman, R.; and Ruiz, P., eds. Substance Abuse:

A Comprehensive Textbook. 2d ed. Baltimore, MD: Williams and

Wilkins, 1992. pp. 56-69.

Cohen, J., and Cohen, P. Applied Multiple Regression/Correlation

Analysis for the Behavioral Sciences. 2d ed. Hillsdale, NJ:

Lawrence Erlbaum Associates, 1983.

Ehrman, R.N.; Robbins, S.J.; Childress, A.R.; and O’Brien, C.P.

Conditioned responses to cocaine-related stimuli in cocaine abuse

patients. Psychopharmacology (Berl) 107:523-529, 1992.

Ehrman, R.N.; Robbins, S.J.; Childress, A.R.; Carter, M.A.; and

O’Brien, C.P. Predictors of cocaine relapse following treatment.

In: Harris, L., ed. Problems of Drug Dependence, 1992:

Proceedings of the 54th Annual Scientific Meeting of the College

on Problems of Drug Dependence. National Institute on Drug

Abuse Research Monograph 132. NIH Pub. No. (ADM)93-3505.

Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1993.

Fischman, M.W.; Foltin, R.W.; Neustadt, G.; and Pearlson, G.D. Effects

of desipramine maintenance on cocaine self-administration by

humans. J Pharmacol Exp Ther 253:760-770, 1990.

Fleiss, J.L. Statistical Methods for Rates and Proportions. 2d ed. New

York: John Wiley and Sons, 1981.

Fleiss, J.L. The Design and Analysis of Clinical Experiments. New

York: John Wiley and Sons, 1986.

Gawin, F.H.; Kleber, H.D.; Byck, R.; Rounsaville, B.J.; Kosten, T.R.;

Jatlow, P.I.; and Morgan, C. Desipramine facilitation of initial

cocaine abstinence. Arch Gen Psychiatry 46:117-121, 1989.

Giannini, A.J., and Billett, W. Bromocriptine-desipramine protocol in

treatment of cocaine addiction. J Clin Pharmacol 27:549-554,

1987.

Higgins; S.T.; Budney, A.J.; Bickel, W.K.; Hughes, J.R.; Foerg, F.; and

Badger, G. Achieving cocaine abstinence with a behavioral

approach. Am J Psychiatry 150:763-769, 1993.

Higgins, S.T.; Delaney, D.D.; Budney, A.J.; Bickel, W.K.; Hughes,

J.R.; Foerg, F.; and Fenwick, J.W. A behavioral approach to

achieving initial cocaine abstinence. Am J Psychiatry 148:1218-

1224, 1991.

Kang, S.Y.; Kleinman, P.H.; Woody, G.E.; et al. Outcomes for cocaine

abusers after once-a-week psychosocial therapy. Am J Psychiatry

148:630-635, 1991.
93

Klein, D.F. Improvements of Phase III psychotropic drug trials by

intensive Phase II work. Neuropsychopharmacology 4:251-258,

1991.

Klein, D.F., and Ross, D.C. Reanalysis of the National Institute of

Mental Health Treatment of Depression Collaborative Research

Program general effectiveness report. Neuropsychopharmacology

8:241-251, 1993.

Kosten, T.R. Pharmacotherapies. In: Kosten, T.R., and Kleber, H.D.,

eds. Clinician’s Guide to Cocaine Addiction: Theory, Research,

and Treatment. New York: Guilford Press, 1992.

Kosten, T.R.; Gawin, F.H.; Kosten, T.A.; Morgan, C.; Rounsaville, B.J.;

Schottenfeld, R.; and Kleber, H.D. Six-month follow-up of shortterm pharmacotherapy for cocaine dependence. Am J Addict

1:40-49, 1992a.

Kosten, T.R.; Morgan, C.M.; Falcione, J.; and Schottenfeld, R.S.

Pharmacotherapy for cocaine-abusing methadone-maintained

patients using amantadine or desipramine. Arch Gen Psychiatry

49:894-898, 1992b.

Kosten, T.R.; Rounsaville, B.J.; and Kleber, H.D. A 2.5 year follow-up

of depression, life crises, and treatment effects on abstinence

among opioid addicts. Arch Gen Psychiatry 43:733-738, 1986.

Leal, J.; Ziedonis, D.; and Kosten, T. Antisocial personality disorder as

a prognostic factor for pharmacotherapy of cocaine dependence.

Drug Alcohol Depend 35(1):31-35, 1994.

Magura, S.; Rosenblum, A.; Lovejoy, M.; Handelsman, L.; Foote, J.;

and Stimmel, B. Neurobehavioral treatment for cocaine-using

methadone patients: A preliminary report. J Addict Dis 13:143-

160, 1994.

McLellan, A.T.; Arndt, I.O.; Metzger, D.S.; Woody, G.E.; and

O’Brien, C.P. The effects of psychosocial services in substance

abuse treatment. JAMA 269:1953-1959, 1993.

Nunes, E.V., and Quitkin, F.M. Treatment of depression in drug

dependent patients: Effects on mood and drug use. In: Onken,

L.S.; Blaine, J.D.; Genser, S.; and Horton, A.M. Jr., eds. Treatment

of Drug-Dependent Individuals With Comorbid Mental Disorders.

National Institute on Drug Abuse Research Monograph 172. NIH

Pub. No. 97-4172. Washington, DC: Supt.of Docs., U.S.Govt.

Print. Off., in press.

Nunes, E.V.; McGrath, P.J.; Quitkin, F.M.; Stewart, J.P.; Harrison, W.;

Tricamo. E.; and Ocepek-Welikson, K. Imipramine treatment of

alcoholism with comorbid depression. Am J Psychiatry 150:963-

965, 1993.

Nunes, E.V.; McGrath, P.J.; Quitkin, F.M.; Stewart, J.W.; OcepekWelikson, K.; Wager, S.; Tricamo, E.; Koenig, T.; and Klein, D.F.
94

“Imipramine Treatment of Cocaine Abuse; Efficacy and

Mechanism: Anti-euphoriant, Anti-craving Agent, or

Antidepressant?” Manuscript submitted for publication.

O’Brien, C.P. “Clinical Trials Methodology.” Paper presented at

Plenary Session: Drug Development to Treat Addictive Disorders,

American College of Neuropsychopharmacology Annual

Meeting, December 1993.

Quitkin, F.M., and Rabkin, J.G. Methodological problems in studies of

depressive disorder: Utility of the discontinuation design. J Clin

Psychopharmacol 1:283-288, 1981.

Quitkin, F.M.; Rabkin, J.G.; Ross, D.; and McGrath, P.J. Duration of

antidepressant drug treatment: What is an adequate trial? Arch Gen

Psychiatry 41:238-245, 1984.

Quitkin, F.M.; McGrath, P.J.; Stewart, J.W.; Ocepek-Welikson, K.;

Taylor, B.P.; Nunes, E.; Deliyannides, D.; Agosti, V.; Donovan,

S.J.; Ross, D.; and Klein, D. “The Placebo Run in Period in

Studies of Depressive Disorders: Clinical, Heuristic, and Research

Implications.” Manuscript submitted for publication.

Quitkin, F.M.; Stewart, J.W.; McGrath, P.J.; Nunes, E.; OcepekWelikson, K.; Tricamo, E.; Rabkin, J.G.; and Klein, D.F. Further

evidence that a placebo response to antidepressants can be

identified. Am J Psychiatry 150:566-570, 1993.

Rawson, R.A.; Obert, J.L.; McCann, M.J.; and Ling, W. Psychological

approaches for the treatment of cocaine dependence—a

neurobehavioral approach. J Addict Dis 11:97-119, 1991.

Rawson, R.R.; Obert, J.L.; McCann, M.J.; Smith, D.P.; and Ling, W.

Neurobehavioral treatment for cocaine dependency. J

Psychoactive Drugs 22:159-171, 1990.

Regier, D.A.; Farmer, M.E.; Rae, D.S.; Locke, B.Z.; Keith, S.J.; Judd,

L.L.; and Goodwin, F.K. Comorbidity of mental disorders with

alcohol and other drug abuse; results from the Epidemiologic

Catchment Area (ECA) study. JAMA 264:2511-2518, 1990.

Rounsaville, B.J.; Kosten, T.R.; Weissman, M.M.; and Kleber, H.D.

Prognostic significance of psychopathology in treated opiate

addicts: A 2.5 year follow-up study. Arch Gen Psychiatry 43:739-

745, 1986.

Rounsaville, B.J.; Weissman, M.M.; Crits-Christoph, K.; Wilber, C.;

and Kleber, H. Diagnosis and symptoms of depression in opiate

addicts; course and relationship to treatment outcome. Arch Gen

Psychiatry 39:151-156, 1982.

Trivedi, M.H., and Rush, J. Does a placebo run-in or a placebo

treatment cell affect the efficacy of antidepressant medications?

Neuropsychopharmacology 11:33-43, 1994.
95

Weddington, W.W.; Brown, B.S.; Haertzen, C.A.; Hess, J.M.; Mahaffey,

J.R.; Kolar, A.F.; and Jaffe, J.H. Comparison of amantadine and

desipramine combined with psychotherapy for treatment of

cocaine dependence. Am J Drug Alcohol Abuse 17:137-152,

1991.

Ziedonis, D.M., and Kosten, T.R. Pharmacotherapy improves

treatment outcome in depressed cocaine addicts. J Psychoactive

Drugs

23:417-425, 1991.

ACKNOWLEDGMENTS

This work was supported by the National Institute on Drug Abuse

grant nos. R01 DA03836, R18 DA06140, and K20 DA00154-01.

AUTHOR

Edward V. Nunes, M.D.

Research Psychiatrist

Depression Evaluation Service

New York State Psychiatric Institute

and

Assistant Professor of Clinical Psychiatry

Department of Psychiatry

Columbia University College of Physicians and Surgeons

722 West 168th Street

New York, NY 10032
96

Management of Clinical Trials With

New Medications for Cocaine

Dependence and Abuse

Ari Kiev

INTRODUCTION

Clinical trials of medicines for cocaine dependence are extremely

complex to conduct because of the varied nature of cocaine abusers,

imprecise methods of diagnosis, lack of well-defined endpoints that

can be measured independently of the subjective judgment of the

clinician and subject, lack of standardized rating scales, and lack of

interrater reliability. Additional problems in doing such studies

pertain to site selection, patient recruitment, patient compliance, and

study management.

This chapter examines some of these issues and offers important

management guidelines that may prove useful as cocaine abuse trials

move toward larger placebo-controlled Phase III studies.

CLINICAL TRIAL MANAGEMENT ISSUES

Clinical trials represent a significant departure from the ordinary

routines of clinical practice, so it is imperative that efforts be made at

the outset of a study to address all of the potential problems that may

occur in the course of a study.

Essentially, clinical trials require a proactive management approach

where the study objectives determine the steps to take to execute the

study rather than passively accept results and breakdowns as inherent

in the process, or in the patients, or in the condition. It is essential to

review every breakdown in the study process from recruitment to

maintenance of patients in the study for solutions that may increase

participation: Why did the patient drop out? How could that patient

have been kept in the study? What are the differences between

patients who stay in and who drop out? How many were in previous

studies? How are potentially noncompliant patients who drop out

shortly after starting recognized? Are there any differences between

different screening personnel and enrollment rates and retention rates
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of different raters? What role did the staff play in the process in terms

of attitudes, neglect, failure to follow up, or failure to go the extra

mile?

Proactive management means clear-cut responsibilities, clear lines of

communication, high levels of accountability, designated personnel,

and clear definition of duties for managing the project. It also means

a willingness to commit to objectives by doing whatever additional

steps it takes to produce the result and not simply attributing poor

results to the patient population. This may mean, for example, having

someone available in the evening in the early phases of a study who

knows inclusion/exclusion criteria so as not to lose eligible patients at

the moment when the patient first calls about participating in the

study—a telephone call may be the only available window in which to

enroll the caller.

It also means focusing on other measures to increase retention, such as

telephone calls and home visits between office visits, a regular review

of all breakdowns in communication, and introduction of essential

procedures to prevent breakdowns such as training staff in the

subtleties of study etiquette to bolster patient compliance.

The more complex the inclusion and exclusion criteria, the less wellspecified the diagnostic subtypes of patients being studied. This is a

special problem because it has not yet been determined how to

differentiate different types of patients in terms of type of drug use,

frequency of use, route of administration, and the various stages of

withdrawal, each of which may require a different treatment strategy

and a different model of psychotherapeutic management. Also, it

becomes especially difficult to train the staff in terms of the

appropriate attitudes and procedures to routinely maintain to ensure

participation and compliance with the study protocol.

The deficiencies demonstrated in data audits of clinical trials generally

reflect failure in communication among responsible parties and a

general breakdown in the process of total quality management.

The most common deficiencies in data audits are the absence of

informed consents, inadequate drug accountability, nonadherence to

protocol, inadequate and inaccurate recordkeeping, failure to obtain

approval from the institutional review board (IRB), and failure to

inform the IRB of protocol changes.

Adherence to a higher standard of quality control than what exists in

most practice settings requires a clarification of study objectives,
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commitment to the objectives, and a willingness to keep searching for

steps that are missing or procedures and personnel that must be

installed whenever problems are encountered. Since it is difficult to

anticipate all the possible potential patient presentation problems that

must be questioned in light of the inclusion/exclusion criteria, or all

the procedural breakdowns that may occur along the way that become

protocol violations, it is essential that a mechanism be included for

constant monitoring of the process as well as quality control of the

case report forms to ensure that as much as possible common

problems in data audits, and problems that ensue when applying a

theoretical protocol to real-life patients, are recognized early so that

corrective measures can be put in place.

It is especially critical to spend time in identifying patterns and

sources of problems such as the high rate of dropouts in cocaine

abuse drug trials and to determine whether they are due to the

unreliability of the patient population or to failures in management.

Here it is critical to know more about the different types of cocaine

patients and withdrawal patterns so as to ensure that the patients

recruited are suitable for the study. It is also important to train the

staff in ways of handling the variety of problems that frequently

surface in this patient population so that patterns of patient care at the

site that may not be entirely suitable for the proper conduct of a study

can be identified. It is critical to keep asking what is missing in the

staff procedures rather than simply attributing problems of dropouts

and no-shows to the underlying condition.

CLINICAL OBJECTIVES

A number of objectives have been pursued in the search for a

medication for cocaine dependence, no doubt because of the different

patterns of efficacy and pharmacological and theoretical

considerations associated with the different drugs tested (Adams and

Durell 1984).

Perhaps the most common objectives sought in most studies have been

the cessation or reduction of drug use and drug craving. Other

studies have sought to compare the efficacy of a single agent against

placebo or against a known drug such as desipramine or

bromocriptine, neither of which has achieved the status of a standard

as yet.
99

Additional objectives have included the retention of patients in

treatment, as has been demonstrated with desipramine; changes in the

patients’ occupational, legal, financial, medical, or psychological

status (McLellan et al. 1980); a reduction in the use of other drugs of

abuse; and a change in risk-taking behavior such as the sharing of

needles and unprotected sex with multiple partners (Battjes and

Pickens 1988).

Most pharmacological studies for cocaine abuse have focused either

on blocking cocaine euphoria with drugs such as imipramine,

bromocriptine, trazodone, or neuroleptics like haloperidol, or dealing

with withdrawal and craving during the first several weeks of

abstinence from cocaine as in studies with desipramine, imipramine,

bromocriptine, amantadine, carbamazepine, flupenthixol decanoate,

buprenorphine, and fluoxetine (Weddington 1992). While a number

of pharmacological agents have shown some promise in leading to a

reduction of craving and use among cocaine users, there have been

few placebo-controlled trials and no drug has been approved for use

in cocaine abuse, nor is there a standard drug against which to run

clinical trials.

The best results appear to have been with desipramine, which

increased periods of abstinence and decreased cocaine craving in the

early phase of outpatient treatment (Gawin and Kleber 1984; Gawin et

al. 1989a, 1989b). In a double-blind randomized trial, 59 percent of

patients treated for 6 weeks with desipramine achieved 3 or more

weeks of continuous cocaine abstinence compared to 25 percent of

those treated with lithium and 17 percent treated with placebo. But

desipramine had little effect on reducing attrition and did not decrease

relapse to cocaine abuse.

SITE SELECTION

While much of the recent work in cocaine dependence has been done

in university settings or in special settings devoted to the problems of

cocaine dependence, larger scale studies will have to expand to other

locations as well. It is critical to select sites that are organized for

research in a highly regulated environment with dedicated personnel

able to pay adequate attention to issues of informed consent, adequate

documentation, drug accountability, and recordkeeping.

Site selection is critical to the success of clinical trials. In the prestudy

phase it is important to establish that the sites have access to the
100

necessary patients, whether in their own patient pools or from referral

sources. Too many studies fall short of their required quotas because

of the optimism of clinicians or investigators eager to participate in

clinical trials without carefully reviewing whether they have the

requisite patient numbers, specifically patients who will meet the

inclusion criteria, who will be willing to take a new investigational

drug, who will participate in a placebo-controlled study, who will stop

taking an existing medicine, who will be subjected to repeated

venipunctures, who will make the necessary periodic visits, and so

forth.

Patient recruitment, in line with enrollment quotas, is especially

important and may be problematic for a given site and investigator.

Some clinicians hesitate to enroll patients in placebo-controlled

studies. They also may be reluctant to try to overcome the patient’s

resistance to enroll in a study, equating a proactive approach to

enrollment with coercion. Clinicians also may be reluctant to

advertise for symptomatic volunteers because of certain long-held

beliefs about the unprofessionalism of advertising or the self-selected

nature of such patients, even though in many studies this may be the

only way to recruit sufficient numbers of appropriate patients.

It is also important at the outset to establish the availability of

dedicated staff to ensure adherence to protocol inclusion criteria, to

maintain adequate source and regulatory documents, and to keep

abreast of the numerous changes and amendments to the protocols

that occur during the course of a study. These changes and

amendments must be coordinated among the site personnel as well as

the sponsor and IRB. In this regard it is critical that onsite staff

participate in startup meetings and that a complete meeting of all staff

take place at the site at the start of the study to ensure that all logistical

details are worked out.

It is important to choreograph patient flow, and to recognize the

importance of the right attitude of empathy and interest from the

telephone screening person to the lab technician, both of whom are

critical for enrolling patients, just as they may unwittingly say the

wrong thing to patients and encourage withdrawal. All staff members

must be familiar with the focus and philosophy of the project, and

scripts should be prepared if necessary so that the limits of what to

communicate are known.

Because patient screening is often done by nonclinical personnel, it is

important that they be made a central part of the research team and
101

trained in the inclusion/exclusion criteria. Their first contact with the

patient establishes a bonding with the site that is necessary to ensure

complete participation during the course of the study.

EXPERIENCED INVESTIGATORS

While independence and self-reliance are highly valued characteristics

of physicians in general, the clinical investigator may have to learn

certain new skills in teamwork to participate in research in a highly

regulated and closely managed framework. While the clinician’s

medical judgment is ultimately critical, it is crucial to always be

assessing activities in the framework of protocol requirements. This

means learning to feel comfortable in maintaining close

communication with the sponsor or clinical research organization

managing a trial, and learning not to hesitate to inquire about

uncertain issues so as to avoid making protocol errors.

It is especially important to ensure the availability of the targeted

population, as access to depressed and anxious patients and even other

difficult-to-locate groups such as schizophrenia and Alzheimer’s

cases does not necessarily prepare the investigator for the special

problems associated with recruiting and maintaining cocainedependent patients. The demonstration of past experience, a

continuous patient pool, or a proven network of referrals is critical in

collecting sites even among experienced investigators. It may be

desirable to begin building such a cadre of investigators by initiating

smaller studies, in anticipation of the larger scale studies that will be

needed in the future.

This will help the investigator build a pool of compliant patients who

are not placebo responders and who may be willing to participate in

subsequent clinical trials. These small-scale studies may also make it

possible to explore different methods of recruitment at particular sites

and establish actual numbers of screening calls, the percentage of

telephone-screened subjects who keep their appointments, the rate of

enrollment of telephone-screened subjects to studies, and the dropout

rate. This would help establish a measurable basis for site selection

for future large-scale studies.

A significant percentage of cocaine-dependent patients deviate from

protocols by dropping out because of cocaine craving, other drug

dependencies, and psychiatric illness. Experienced investigators are

essential in these studies because of their ability to select compliant
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patients and to maintain compliance without being overly “psychotherapeutic” and without putting patients at risk. The experienced

investigator is also alert to the early warning signs of noncompliance,

such as missed first appointments, inconsistencies in the information

given on the telephone screen and office screen, ambivalence about

signing the informed consent, and a past history of noncompliance or

nonresponsiveness to a variety of medication programs. The

investigator can make the decision not to include selected patients in a

study even though there is pressure to enroll them in terms of a highly

demanding timeline. The larger the investigator’s network, the easier

it is to be selective in including patients to increase full participation

and lower the dropout rate.

PATIENT SELECTION

It is important to identify the best geographic locations and

investigative sites where the targeted population can be located. There

are geocoded databases that can help with this. Given the high

dropout rates in cocaine dependence studies, it is best to locate

patients who are working and living with significant others who can

facilitate followup.

This is especially true for Phase II and Phase III efficacy studies but

less relevant in Phase I studies with less stable chronic users who are

needed for safety and interaction studies involving the administration

of cocaine. Chronic nontreatment-seeking abusers are suitable for

early Phase I studies especially when drug challenges are given or

controlled access to the abusable drug is available in a behavioral

paradigm to measure directly the effect of the medication on drugseeking behavior (Fischman et al. 1990). These individuals are not

generally included in or suitable for controlled clinical trials of

medication because they generally do not want to stop drug use.

In Phase II studies of drugs like flupenthixol, which block the effects

of cocaine, crack cocaine users theoretically may use more cocaine to

get high and counteract the effects of the medication, as has been

demon-strated in lab animals. As such it is usually necessary to

include some form of psychotherapy to ensure compliance with such

studies, of course possibly adding its own confounding effects.

Ideally the best Phase II studies of safety and efficacy are done with

small numbers in controlled inpatient settings for several days to

determine tolerance to the medication followed by outpatient
103

treatment. Here the criteria for inclusion are less stringent, and

recreational users are often included with chronic users to increase

compliance, perhaps at the cost of increasing the variability of the

results.

When moving to later Phase II studies and Phase III studies, patient

selection becomes more important especially because there are no

well-validated rating scales and no standard drug against which to

compare new drugs. Without such standardization, trends in

decreased cocaine usage at particular sites in multisite studies may

sometimes be attributed to the inclusion of nonhomogeneous patient

populations or to different treatment approaches at the different sites.

The clinical condition must be defined as precisely as possible. In

Phase III trials there is a need to distinguish between recreational and

chronic users whose patterns of usage and attitudes toward

participation in a study may be significantly different. It is difficult to

differentiate between subtypes of patients in terms of type of drug use,

frequency of use, route of administration, and the various stages of

withdrawal, each of which may require a different treatment strategy

and a different model of psychotherapeutic management, making it

especially difficult to train staff in terms of the appropriate attitudes

and procedures to routinely maintain to ensure participation and

compliance with the protocol. It is also important not to define

exclusion criteria too rigidly and to leave a large window or grace

period for followup visits so that missed visits do not constitute

protocol violation.

Local newspaper or radio advertising, which is often essential to

recruit the large numbers needed for Phase III trials, may be less

useful with the cocaine-using population than is true for symptomatic

volunteers with depression and anxiety symptoms. This requires

further study. It is also necessary to find new ways of working with

traditional sources of referral from other community medical or

psychiatric agencies, which oftentimes for philosophical reasons do

not support the concept of “testing” new medications in placebocontrolled clinical trials, or are threatened by issues of territoriality. It

may be necessary to begin to build relationships with other agencies,

including the drug-free therapeutic communities, which seem to have

a large number of cocaine-dependent patients in their patient and

graduate networks, many of whom may be interested in and may

benefit from participation in clinical trials with new medications for

cocaine dependence.
104

Problems at the time of recruitment pertain to problems in diagnosis

and making certain only to include those patients who fit the protocol.

The same applies to the care with which past medical histories are

obtained, so as not to include patients who after starting may reveal

the existence of conditions that would exclude them. The initial

interview must be extremely thorough and designed in anticipation of

subtleties about participation that are not generally considered in the

course of routine psychiatric care.

It is important to recruit patients who will be cooperative, compliant,

and willing to participate for the duration of the study. Patients must

also be capable of following instructions, returning medications,

making regular appointments, and adhering to the protocol. Meeting

these criteria is especially difficult in the case of cocaine abuse where

the condition itself seems to impinge on the very qualities necessary

for participation.

The same may be said for certain Axis II personality disorders such as

borderline personality and paranoid personality, which may be

particularly prevalent among cocaine-abusing patients and which also

may contribute to noncompliance in the study.

HOSPITAL OR OUTPATIENT SETTINGS

There are obvious advantages to hospital settings in terms of the

severity of withdrawal patterns, the control over medication and

retention, the measurement of side-effect profiles, and the monitoring

of plasma levels, all of which are more easily measured because of

increased compliance. Hospitals are also better environments in which

to conduct challenge studies where patients are given the test

medication and then are able to select differing amounts of the drug

of abuse in a patient choice paradigm designed to measure the

blocking effect of the test medicine.

Chronic users who are most suitable for these studies are easier to find

and easier to induce to remain in an inpatient facility than recreational

users, but they are often less motivated, have more medical problems,

are polysubstance abusers, and when moved to outpatient status may

rejoin the ranks of the homeless and be difficult to find for followup

visits.

A disadvantage of hospital settings is that they lack the environmental

cues and stimuli that often provoke a return to drug abuse and

therefore are not realistic settings in which to measure the control of
105

drug dependence with medication. The severity of the patient’s

illness and the stage of drug testing are critical factors here. To

measure cocaine use, craving, and the responsivity to environmental

cues, it is preferable to conduct a trial to measure the control of drug

dependence with medication in an outpatient department, despite the

risk of greater dropouts.

Because patients, especially recreational users, do not want to be

confined, there is a need for fast-acting drugs. While these may work,

the long-term beneficial effects that may be even more dramatic may

be hard to establish because of the problems of following up patients

after they have left an inpatient facility.

COMPLIANCE

Various attempts to increase compliance have been tried. The

anecdotal evidence on putting a computer chip in the medicine bottle

to see if the patient took the test medicine suggests that these bottles

are often opened as much as 25 times a day, making this virtually

useless as a measure of compliance. The use of depot flupenthixol to

circumvent the issue of compliance has been tried, but it raises ethical

questions of inducing in high doses dopamine (DA) side effects such

as tardive dyskinesia, which may not be justifiable in this population

as it is in patients with psychotic symptomatology. Moreover, some

patients may theoretically try to overcome the DA blockade by taking

more cocaine and risking overdose. The dropout rate in one such

study was 60 percent as compared to a dropout rate of 20 percent on

a 6- to 8-week trial of methadone main-tenance patients with cocaine

abuse. Another way to lower dropout rates is to exclude hardcore

patients who are more likely to use other drugs and take more cocaine

and to rely more heavily on more motivated individuals who may be

living with family members and working, which also may add to

compliance. Another approach is to design feasible studies, for

example by allowing a wider window for drug administration to

accommodate missed visits by patients.

PSYCHIATRIC DIAGNOSIS

The difficulty of making precise diagnoses often leads to

heterogeneous patient samples, which in turn makes it difficult to

accurately test the efficacy of new compounds. This is seen in

traditional psychiatric trials where there is often difficulty in
106

distinguishing schizophrenia from schizoaffective illness or manicdepressive illness, or in distinguishing discrete episodes of major

depression from chronic low-grade depressive mood of dysthymia.

The heterogeneity of drug users makes it especially difficult to find

treatments that may be effective with a selected portion of the drugusing population that enter into a study. On the other hand, limiting

study samples to homogeneous ones may limit the rate of enrollment

and generally slow the progress of comparable research at other sites.

It is therefore often essential to find some compromise between the

two extremes.

In cocaine studies there may be difficulty differentiating chronic users

from heavy recreational users. This is especially significant in Phase I

safety and interaction studies where it would be acceptable to use

chronic users who do not want to stop cocaine, but unethical to use

cocaine for nondependent recreational users who are motivated to

stop the drug. The distinction between chronic users and heavy

recreational users is less significant in Phase II dose-ranging and

efficacy studies where the use of recreational users is likely to make it

easier to show a response. These patients are usually more compliant

and motivated but harder to convince to stay in a facility for the

intense tests such as Holter monitoring required for such studies.

Differences among patients is also important in Phase III studies

attempting to differentiate active drug from placebo and measuring it

against a comparator. Fortunately, the problems of diagnosis can be

controlled to some extent by the use of standardized criteria and

standardized interview schedules, a number of which are available.

DEFINING THE COCAINE DEPENDENCY SYNDROME

The importance of defining specific diagnostic subgroups to study is

underlined by clinical findings of Weddington and his group that

cocaine addicts who sought treatment in his research facility reported

greatest craving for cocaine during the 24-hour period immediately

before admission and the greatest severity of mood distress on day 1

(Weddington et al. 1990). Mood states, craving, and reports of

waking during the night and of clearheadedness on awaking improved

gradually during the study and were not cyclical or phasic during the

first 4 weeks of abstinence. According to Weddington, the absence of

cocaine and other drugs as well as drug-taking stimuli in a controlled

environment may account for the lack of a classical postabuse

abstinence syndrome.
107

Elsewhere, Meyer and Mirin have proposed that drug craving is an

appetitive response: Where drugs are available to addicts, craving is

likely (Meyer and Mirin 1979). Wikler demonstrated that craving and

physiological responses to drugs and drug-taking cues are affected by

classic conditioning of exteroceptive stimuli (Wikler 1973). Other

work by Jaffee demonstrated the role of internal stimuli associated

with cocaine administration by demonstrating that giving cocaine to

experienced cocaine users increases their craving for the drug (Jaffee

et al. 1989).

All of this underscores the importance of studying the behavioral and

psychological components as well as the physiological components

and emphasizes the importance of clearly defining the parameters of

the study so as to take these factors into consideration and not simply

bunch people all together in heterogeneous samples.

PATTERNS OF DRUG ABUSE

It is also essential to differentiate among patterns of drug abuse, routes

of administration, the frequency of drug use, and the consequences of

use in terms of physical dependence, tolerance, craving, drug-induced

problems, and neurobiological system dysfunction, such as in the

adrenergic, dopaminergic, and serotonergic systems where these drugs

act (Blaine et al. 1994).

The stage of drug use is also an important variable. People in the

earliest stages of dependence who are more difficult to find are more

likely to respond to antagonist medications than those in later stages,

and they may be more suitable candidates for testing efficacy than

chronic long-term users.

Other factors to consider in differentiating among patients is the

nature of prior treatment, prior success in achieving abstinence, time

to relapse, or early treatment termination. Additionally, motivation

for treatment is a critical variable to assess. Here are encountered the

problems of denial and the desire to continue the drug-using pattern.

There may also be difficulty in distinguishing the effects of various

anticocaine medications when the patient populations are

heterogeneous. A review of some of the recent research literature

suggests that diagnostic distinctions must be made between nasal and

intravenous users who seem to respond differently in some studies,

patients on methadone maintenance as compared to those who are not,

and patients suffering from depression and cocaine abuse as in the
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studies at Yale where depressed cocaine abusers certainly showed

some response to desipramine.

Of course it is easier to recommend these finer diagnostic distinctions

than it may be to find homogeneous samples of cocaine abusers. The

reasons for this are severalfold:

1. Many patients are polysubstance abusers. Even if screening out

patients with positive drug screens for opiates or other substances,

patients are often unreliable and noncompliant and investigators

cannot be certain patients will use only cocaine in the course of

the trial. Moreover, the interaction of prescribed opiates such as

methadone with cocaine may further compound the results.

2. It is sometimes difficult to differentiate between treatment-resistant

chronic users who may be motivated by a need for food and

shelter and treatment-seeking chronic users who may qualify or

be appropriate for early Phase II studies but not for later studies.

3. Some patients may have multiple psychiatric diagnoses that may

not be identified at the screening interview. In addition to cocaine

abuse, patients may suffer from major depression or

schizophrenia, conditions that may respond to the test drug

resulting in some improvement of symptoms and a reduction of

the motivation for cocaine without directly impacting on the

cocaine abuse itself. This can create obvious problems in the

interpretation of the data.

TREATING PATIENTS WHO ARE CODEPENDENT OR ON

OTHER MEDICATION

A number of studies have been conducted with cocaine-dependent

individuals who were receiving methadone for opiate abuse. Using

such individuals for study can be problematic for several reasons.

Multidrug users are less likely to be compliant than single-drug

abusers and more problematic to maintain in an outpatient study

(Mirin and Weiss 1987). Additionally, the drugs may interact,

producing problems in interpreting the data. It has been reported that

methadone raises blood levels of desipramine thereby making for

complicated dosing of desipramine to control cocaine use and cocaine

craving (Kosten et al. 1987). Nevertheless, there is some strong

evidence that desipramine and amantadine may be helpful in reducing

cocaine use, craving, and depressive symptoms in a group of
109

methadone maintenance patients and that desipramine may be helpful

in keeping patients in treatment and cocaine-free at the end of the

study (Kolar et al. 1993).

COMORBIDITY

There is an extremely high incidence of comorbid mental disorders

among those with drug use disorders (Regier et al. 1990). In one

survey, 76 percent of those with a cocaine abuse or dependence

disorder gave a history of mental disorder. Recently Rosen and

Kosten found that the incidence of panic attacks among methadonemaintained patients has increased over a 10-year period from 1 to 6

percent to as high as 13 percent as a result of cocaine use as well as

environmental and constitutional factors (Rosen and Kosten 1992).

Schizophrenic patients have a lifetime prevalence rate of cocaine

abuse between 15 percent and 50 percent. In one study of

schizophrenic patients in a dual-diagnosis program, patients receiving

desipramine and antipsychotic agents were more likely to complete

the study and demonstrate substantially decreased cocaine usage than

did patients treated with antipsychotic medication alone (Ziedonis et

al. 1992).

Other comorbid problems relate to issues of HIV infection, alcohol

abuse, and multiple drug abuse patterns. In one study it was found

that informing drug abusers in treatment regarding positive HIV

serostatus was not associated with a lower treatment retention rate or

adverse psychological reactions when counseling regarding HIV

issues was integrated with drug abuse treatment (Weddington et al.

1991). Insofar as alcohol and cocaine abuse commonly occur

together, it is of interest that treatment for both can be accomplished

in the same setting if important demographic and pharmacological

differences are addressed (Closser and Kosten 1992). As to multiple

drug abuse there have been successful demonstrations of treatment

with disulfiram for alcohol-abusing patients and amantadine for

cocaine-abusing, methadone-maintained patients (Kosten 1991).

RATING SCALES

Efficacy of psychiatric medication is often difficult to measure

because of the variability of patient responses to medication,

especially when the patient sample is heterogeneous. The method of

measuring efficacy by having the investigator question the patient and

assign symptoms to a rating scale is fraught with error. There is often

a high degree of variability in the ways that patients can respond to
110

cue questions and a minimum of interrater reliability regarding

diagnosis, which makes for problems in multisite studies. Indeed,

there are no validated or universal tools as yet for measuring issues

relating to cocaine abuse.

The scales being used in cocaine studies, including the Visual Analog

Cocaine Use Scale and the Visual Analog Craving Scale as well as

various measures of mood states, are highly subjective and hard to

validate without a standard drug against which to compare the test

drug. One new test, the Self-Administration Paradigm, where patients

get to choose one of two drug regimens after active medication, has

some potential for being objective, but it has not been validated as yet.

A review of the literature suggests a wide variety of endpoints being

used in studies that make comparisons among studies very difficult.

Outcome measures include psychiatric outcomes, craving, subjective

drug effects, patterns of drug use, and retention in treatment. The

instruments and the data collection methods being used vary from

study to study, making comparison of studies virtually impossible.

There is an urgent need to standardize or at least reach some

consensus on the methodologies, instruments, rating scales, and

endpoints used in clinical trials so that cross-trial comparisons can be

made, thereby facilitating advancement of knowledge in the field.

There is also the difficulty of differentiating between symptoms and

side effects. Patients may be depressed before, during, and after using

cocaine. In testing a DA antagonist like flupenthixol, for example, it

might be difficult to test whether reports of depression were related to

the cocaine use or to the DA depletion caused by the medication. The

presence of side effects also may blunt the patient’s report of

symptomatology. The Hamilton Rating Scale for Depression often

used in studies of cocaine dependence is heavily weighted with items

relating to insomnia, GI disturbance, and anxiety—all three of which

may be adversely affected by selective serotonin uptake inhibitors like

fluoxetine, which is being studied at some sites for cocaine

dependence. During a trial the scale may indicate an increase in

depression when in fact the elevated scores may be due to common

physiological side effects of the selective serotonin reuptake inhibitors

(SSRIs).

DURATION OF CLINICAL TRIALS
111

Many studies have been done that did not last long enough to

establish clinical efficacy. Studies must be designed in terms of the

pharmacology and the intended use of the medication (Satel and

Kosten 1991). The duration of the study needs to be long enough to

demonstrate efficacy and yet short enough to ensure retention of

enough patients to do the statistical analyses needed to demonstrate

treatment effects.

The nature of the condition being studied must be considered so that

the study is not so short in duration that it misses certain clinical

events associated with the condition such as periodic binging, delayed

recovery, or delayed relapse (Kosten 1989). Studies should not be so

long as to increase the likelihood of dropout, which is a highly likely

event in drug-dependent populations. Twelve weeks seems to provide

sufficient time to assess both stabilization and the possibility of relapse

while on the drug.

Another critical factor in designing trials is to consider the latency of

onset of clinical effect, which may take far longer than the study is

designed or patients are able to remain in the study (Blaine et al.

1994). In some studies it has taken as long as 6 weeks for

improvement to begin on SSRIs, while it often takes from 12 to 16

weeks to provide maximum benefit. It is especially difficult to

include subjects with cocaine dependence in trials this long.

It is important to anticipate the problems of dropouts and to try to

exclude unmotivated patients as well as those who are being pressured

by others to enter into the program. Too many dropouts reduce the

power of the statistical analysis and may leave a sample of patients that

is unrepresentative of the group being studied. Special attention must

be paid to the characteristics of dropouts not only in terms of

demographic and clinical characteristics but also in terms of any kind

of subtle clinical events that may have influenced their responses to

treatment.

PLACEBO-CONTROLLED STUDIES

There seem to be many open-label noncontrolled studies with positive

results in the area of cocaine abuse. These results by and large are not

substantiated when controlled studies are done (Satel and Kosten

1991). The state of the field, the urgency of finding a new drug, and
112

perhaps the lack of standardized instruments no doubt contribute to

these unreliable results.

The use of placebo is essential in studying a medication whose effects

are as yet undetermined. The use of such a design reduces the

numbers of patients required to demonstrate statistical significance

between medication placebo and a known standard medication.

Distinguishing active drug from placebo is often difficult because of a

significant placebo response caused by too great a reliance on the

patient’s responses to the symptom cues that are given to elicit ratings,

without sufficient attention being paid to the subtleties of symptoms

and observation of the patient’s behavior. Too much support of the

patient, or encouragement of the patient to remain in a trial or

psychosocial or psychotherapeutic support programs (which seem

common in psychopharmacological trials for cocaine dependence)

may also produce positive responses in patients who are generally

believed to be highly susceptible to environmental and behavioral

cues.

These positive responses may be particularly difficult to differentiate

from positive responses to the medication.

PSYCHOSOCIAL INTERVENTION

There is no doubt that cocaine dependence is a condition very much

affected by nonmedical or social factors. This is perhaps what makes

the condition responsive to psychosocial intervention, and as such the

regular use of such methods to maintain compliance must be

questioned in any clinical trial of a new medication for cocaine.

While psychosocial intervention oftimes contributes to compliance

and may clearly have beneficial effects on cocaine dependency, it is

likely to confound the study of the efficacy of psychopharmacology

and must be measured against the effectiveness of new medications

rather than used to reinforce compliance with the program.

These interventions can mask drug effect. They can also enhance

drug effect, as in methadone maintenance programs where

psychotherapy has enhanced the efficacy of methadone treatment of

heroin addicts while being essentially ineffective when used alone

(Woody et al. 1983). The use of such approaches to ensure patient

compliance needs to be weighed carefully and utilized only when the

addition of such interventions is likely to bring out the beneficial

effects of a less potent pharmacological treatment. However, there are
113

problems in the use of such treatments especially in establishing a

standardized method of treatment that can be uniform over time and

among different therapists and multiple sites.

Given the sensitivity of the patient population and the fact that

psychosocial interventions are often required to maintain patients in

studies, it is important to keep asking the question of how various staff

interactions with patients contributed to the patient’s behavior and not

simply assume that this is an area that does not need to be examined

and that it can be assumed that there are no negative effects of staff

attitudes and interactions on the patients.

SUMMARY

Clinical trials require a quite distinct shift in attitudes and procedures

from ordinary clinical practice insofar as they require a proactive

approach to patient recruitment, enrollment, and followthrough as well

as significant attention paid to issues of documentation, regulatory

compliance, and error prevention. Take documentation, for example:

Today’s requirement to have an independent record of clinical events

that are recorded on the case report forms was until 5 or 7 years ago

not addressed in as much detail as it is today. This is one of the first

adjustments that the new investigator must address. The researcher

must keep looking to see what is missing from the location and

procedures as a study takes place in order to create the necessary

patient base for doing the study and ensuring that all needs necessary

to produce the result are in place and that procedures are done with as

few errors as possible. Everything must be done in conformance with

good clinical practice and the standards set by the protocol. The

researcher must be willing to deal with a world of breakdowns such as

missing data, and the failure of the patient to revisit the office within

the appropriate time dictated by the protocol and within the window

of time or grace period allowed by the study. The researcher must

ensure that the patients comply with the dosing schedule and that they

are trained to return medications for accurate pill counts. And so on.

This means creating new procedures that are motivated by a

commitment to producing a specific enrollment result defined by

specific criteria and increasingly because of the press of time enrolled

in a specific time period and put through a well-defined protocol

process. Clinical research is dependent on a willingness to commit to

a specific end result and do all that is necessary on a day-by-day basis

to produce that result in terms of specific numbers, clean and accurate
114

case report forms that are backed up by corroborating source

documents in line with a specific timeline in which to accomplish the

task, and an outreach effort to recruit and enlist patients, which may

involve advertising and promotion of the program, all of which may

contrast significantly with customary practice.

Clinical research involves reliance on additional dedicated personnel

who are critical parts of the research team, including the telephone

screening person who must be trained to follow a script and at the

same time to be aware of the nuances of enrolling appropriate and

compliant patients. The entire staff must be made part of the process

and must work in concert to recruit and maintain the patient in a study

while being aware of the effect these efforts may have on the placebo

effect. It also requires considerable training, review, and constant

communication among the staff to ensure that the complex

coordination of numerous patients and procedures works smoothly.

There needs to be a willingness among the staff and the investigators

to take correction from monitors who visit the site periodically and

whose focus is on the quality of the data and not so much on the

qualifications of the staff. This is not an action that people in

nonresearch environments are trained to take.

Failure to appreciate the complexity of conducting clinical trials can

contribute to much frustration to everyone involved. When there is

understanding of all the variables that influence the ultimate results,

there is a willingness to anticipate breakdowns and to turn breakdowns

into opportunities to create new structures and develop new

procedures that will ultimately facilitate a successful outcome.

REFERENCES

Adams, E.H., and Durell, J. Cocaine: A growing public health problem. In:

Grabowski, J., ed. Cocaine: Pharmacology, Effects, and

Treatment of Abuse. National Institute on Drug Abuse

Research Monograph 50. DHHS Pub. No. (ADM)87-

1326. Washington, DC: Supt. of Docs., U.S. Govt. Print.

Off., 1984. pp. 9-14.

Battjes, R.J., and Pickens, R., eds. Needle Sharing Among Intravenous Drug

Abusers: National and International Perspectives.

National Institute on Drug Abuse Research Monograph

80. DHHS Pub. No. (ADM)88-1567. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1988.
115

Blaine, J.D.; Long, W.; Kosten, T.R.; O’Brien, C.P.; and Chiarello, R.J.

Establishing the efficacy and safety of medications for the

treatment of drug dependence and abuse: Methodologic

issues. In: Prien, R.F., and Robinson, D.S., eds. Clinical

Evaluation of Psychotropic Drugs: Principles and

Guidelines. New York: Raven Press, 1994.

Closser, M.H., and Kosten, T.R. Alcohol and cocaine abuse. A comparison

of epidemiology and clinical characteristics. Recent Dev

Alcohol 10:115-128, 1992.

Fischman, M.W.; Foltin, R.W.; Nestadt, G.; and Pearlson, G.D. Effects of

desipramine maintenance on cocaine self-administration

in humans. J Pharmacol Exp Ther 253:760-770, 1990.

Gawin, F.H., and Kleber, H.D. Cocaine abuse treatment: Open pilot trial

with desipramine and lithium carbonate. Arch Gen

Psychiatry

41:903-910, 1984.

Gawin, F.H.; Allen, D.; and Humblestone, B. Outpatient treatment of

“crack” cocaine smoking with flupenthixol decanoate. A

preliminary report. Arch Gen Psychiatry 46:322-325,

1989a.

Gawin, F.H.; Kleber, H.D.; Byck, R.; Rounsaville, B.J.; Kosten, T.R.;

Jatolow, P.I.; and Morgan, C. Desipramine facilitation of

initial cocaine abstinence. Arch Gen Psychiatry 41:903-

910, 1989b.

Jaffee, J.H.; Cascella, N.G.; Kumor, K.M.; and Sherer, M.A. Cocaineinduced cocaine craving. Psychopharmacology 97:59-64,

1989.

Kolar, A.F.; Brown, B.S.; Weddington, W.W.; Haeertzen, C.C.; Michaelson,

B.S.; and Jaffe, J.H. Treatment of cocaine dependence in

methadone maintenance clients: A pilot study comparing

the efficacy of desipramine and amantadine. Int J Addict

27:849-68, 1993.

Kosten, T.R. Pharmacotherapeutic interventions for cocaine abuse;

matching patients to treatments. J Nerv Ment Dis 177:379-

389, 1989.

Kosten, T.R. Client issues in drug abuse treatment: Addressing multiple

drug abuse. In: Pickens, R.; Leukefeld, C.G.; and Schuster,

C.R., eds. Improving Drug Abuse Treatment. National

Institute on Drug Abuse Monograph 106. DHHS Pub. No.

(ADM)91-1754. Washington, DC: Supt. of Docs., U.S.

Govt. Print. Off., 1991. pp. 136-151.

Kosten, T.R.; Schumann, B.; Wright, D.; and Carney, M.K. A pilot study

using desipramine for cocaine abusing methadone

maintenance patients. J Clin Psychiatry 48:442-444, 1987.
116

McLellan, A.T.; Luborsky, L.; O’Brien, C.P.; and Woody, G.E. An

improved evaluation instrument for substance abuse

patients: The Addiction Severity Index. J Nerv Ment Dis

168:26-33, 1980.

Meyer, R.E., and Mirin, S.M. The Heroin Stimulus: Implications for a

Theory of Addiction. New York: Plenum Press, 1979. pp.

61-91.

Mirin, S.M., and Weiss, R.D. Cocaine. Washington, DC: American

Psychiatric Press, 1987.

Regier, D.A.; Farmer, M.E.; Rae, D.S.; Locke, B.S.; Keith, S.J.; and

Goodwin, F.K. Comorbidity of mental disorders with

alcohol and drug abuse. Results from the epidemiologic

catchment area (ECA) study. JAMA 264:2511-2518,

1990.

Rosen, M.I., and Kosten, T.R. Cocaine associated panic attacks in

methadone-maintained patients. Am J Drug Alcohol Abuse

18:57-62, 1992.

Satel, S.L., and Kosten, T.R. Designing drug efficacy trials in the treatment

of cocaine abuse. J Nerv Ment Dis 179:89-96, 1991.

Weddington, W.W. Use of pharmacologic agents in the treatment of

addiction. Psychol Annals 22:425-429, 1992.

Weddington, W.W.; Brown, B.; Haertzen, C.; Cone, E.; Dax, E.; Herning, R.;

and Michaelson, B. Changes in mood, craving, and sleep

during short-term abstinence reported by male cocaine

addicts: A controlled residential study. Arch Gen

Psychiatry 47:861-868, 1990.

Weddington, W.W.; Haertzen, C.A.; and Brown, B.S. Psychological

reactions and retention by cocaine addicts during

treatment according to HIV-serostatus: A matched-control

study. Am J Drug Alcohol Abuse 17:355-68, 1991.

Wikler, A. Dynamics of drug dependence: Implications of a conditioning

theory for research and treatment. Arch Gen Psychiatry

28:611-616, 1973.

Woody, G.E.; Luborsky, L.; McLellan, A.T.; O’Brien, C.P.; Beck, A.T.;

Blaine, J.; Herman, I.; and Hole, A. Psychotherapy for

opiate addicts: Does it help? Arch Gen Psychiatry 40:639-

645, 1983.

Ziedonis, D.; Richardson, T.; Lee, E.; Petrakis, I.; and Kosten, T.R.

Adjunctive desipramine in the treatment of cocaine

abusing schizophrenics. Psychopharmacol Bull 28:309-

314, 1992.
117

AUTHOR

Ari Kiev, M.D.

Medical Director

Social Psychiatry Research Institute

150 East 69th Street

New York, NY 10021
118

Outcome Measurement

Considerations: Pharmacological

Treatments for Substance Abuse

Karla Moras

INTRODUCTION

An extensive literature exists on outcome measurement for trials of

treatments for psychiatric disorders. Less has been written specifically

on outcome measurement for treatments for substance-related

disorders; even less specifically for trials of pharmacological agents

for substance disorders.

OVERVIEW

Six questions are presented to systematically guide investigators’

decisions on outcome assessment for randomized clinical trials of

pharmacological agents for substance-related disorders (American

Psychiatric Association 1994). Use of the questions is illustrated by

applying them to cocaine dependence. The questions were distilled

from four sources: the author’s experience conducting psychiatric

treatment outcome research, the extensive literature on treatment

outcome methodology (Kazdin 1994), a recent comprehensive text on

the clinical evaluation of psychotropic drugs (Prien and Robinson

1994), and Kraemer and Telch’s (1992) paper on outcome

measurement for clinical trials.

Because of the breadth of the existing relevant literature, a discussion

of outcome measurement considerations for trials of pharmacological

agents for substance-related disorders could result in a lengthy

treatise. Instead, a strategy was adopted for this chapter to make it

maximally useful with minimal length. The strategy is to articulate a

conceptual framework (actually, a set of six questions) to guide

investigators’ decisions on outcome measure selection and related

assessment issues for clinical trials of pharmacological agents for

substance-related disorders. Along the way, a few pertinent,

comprehensive references are provided.

FRAME OF REFERENCE
119

The focus of this chapter is considerations relevant to answering the

basic treatment outcome question: Does a pharmacological treatment

have intended and clinically important effects on substance-related

disorder(s) of interest? The discussion assumes that: (a) the

measurement is to be done in the context of a randomized clinical

trial (RCT), (b) the goal of the trial is to evaluate the efficacy of a

pharmacological intervention for a substance-related disorder (e.g., as

defined in the Diagnostic and Statistical Nomenclature of the DSMIV, American Psychiatric Association 1994), and (c) a

pharmacotherapy for adult outpatients is being examined. It is also

assumed that the goal of the trial is explanatory rather than pragmatic

(Lavori 1992). That is, the goal of the RCT is to draw conclusions

about a treatment’s causal effects on targeted outcomes.

Blaine and colleagues (1994) extensively discuss considerations

relevant to designing clinical trials of pharmacological agents for

substance-related disorders, including some of the particular problems

(such as high attrition rates) associated with treatment efficacy trials

for substance-related disorders. Moras (1993) discusses some of the

outcome measurement problems that are unique to treatment trials for

substance-related disorders, compared to trials for other common

psychiatric disorders.

GUIDING QUESTIONS FOR OUTCOME ASSESSMENT

Six basic questions can be used to guide investigators’ decisions on

outcome measures and related methodological issues for RCTs of

pharmacological agents for substance-related disorders (see table

1). The questions apply equally to RCTs of other psychiatric

disorders, but they are discussed and elaborated here for RCTs of

substance-related disorders. The six questions were distilled

mainly from four sources: the author’s experience conducting

psychiatric treatment outcome research, the extensive literature on

treatment outcome methodology (e.g., Kazdin 1994; Kraemer et

al. 1987; Lambert 1990; Lavori 1992; Rush et al. 1994), a recent

comprehensive text on the clinical evaluation of psychotropic

drugs (Prien and Robinson 1994), and an excellent paper by

Kraemer and Telch (1992) on outcome measurement in clinical

trials. Selected issues that pertain to answering each of the six

questions are considered in the sections that follow.
120

TABLE 1. The basic questions.

1. What problems do cocaine-dependent individuals have?

2. Which of the problems is the treatment intended to address?

3. What outcomes associated with the treatment are of primary interest?

4. Which of the outcomes of primary interest can be measured reliably

and validly?

5. How can investigators be sure that the pharmacological treatment of

interest contributed substantially to the outcomes obtained?

6. How can researchers be sure not to miss outcomes associated with

pharmacological treatments of interest?

NOTE: Questions 1 through 3 are adapted from Kraemer and Telch

(1992).

Step I: Identification of the Outcomes of Interest

Kraemer and Telch (1992) provide an exceptionally clear, yet

sophisticated and comprehensive reference on outcome measurement for

RCTs of psychiatric disorders. A systematic conceptual framework, in the

form of three questions, is presented to guide investigators’ selection of

outcome measures. The questions are the first three in table 1. Kraemer

and Telch (1992) illustrate and discuss the questions by applying them to

mood disorders. However, the questions are appropriate for RCTs of

other psychiatric disorders, including substance-related disorders. Once

the three initial questions are answered, the investigator must evaluate and

select (or develop, if necessary) measures to assess the outcomes of

interest. “Outcomes” (see question 3, table 1) are features of a patient,

such as frequency of drug use or frequency of associated high-risk

activities such as use of dirty needles. Kraemer and Telch (1992) define

an “outcome measure” as a procedure used “to obtain a number or

classification from or about the patient that is indicative of the ‘outcome’

[of interest]” (p. 86).

The three questions are interdependent. As Kraemer and Telch (1992)

point out, an “isomorphism” must exist between the disorder, the

treatment that is being tested for the disorder, and the outcome assessment
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procedures that will provide an index of the usefulness of the treatment

for the disorder. Moreover, the three questions logically precede other

central decisions for RCTs (e.g., design, assessment intervals, analysis).

The initial three questions might seem straightforward. However,

answering them is not necessarily straightforward, particularly when

substance-related disorders are to be examined. Some considerations

pertinent to answering the first basic question will be illustrated by

applying it to cocaine dependence.

Question 1. What problems do cocaine-dependent individuals have?

The perspective subquestion. Answering the first question requires

answering the subquestion, “From whose perspective?” Obviously

relevant perspectives, using the criterion of parties with a vested interest in

treatment outcomes, are: the cocaine abuser, the cocaine abuser’s family

and others with whom he or she has close personal ties, society, and the

clinical investigator.

Answering the first basic question from different perspectives will yield

different answers. Table 2 provides illustrative answers for cocaine

dependence from three perspectives: cocaine abuser, society, and clinical

investigator. The lists are not intended to be comprehensive. Their

purpose is to illustrate the fact that different problems will be identified as

central to a disorder, depending on the perspective from which the

problems question is addressed. One obvious implication is that the

outcome measures chosen will depend, at least partially, on an

investigator’s view of which perspectives are important.

A key variable: Low subjective distress. Problems 1 and 2 from the

cocaine abuser’s perspective (table 2) point to a key variable that

must be considered when designing RCTs of substance-related

disorders, in contrast to most other DSM-IV (American Psychiatric

Association 1994) Axis I psychiatric disorders. The variable can

be labeled in a variety of ways, e.g., “minimal subjective distress”

or “low motivation to change.” The point is that the symptoms

that constitute DSM-IV diagnostic criteria for substance-related

disorders often are not experienced as problematic by the person

who meets the criteria for the disorder. In
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TABLE 2. Perspectives: What problems do cocaine

abusers have?

1. Cocaine user

a. None.

b. Feelings of euphoria, mastery, well-being, interest in life aren’t

frequent enough without use of cocaine.

c. Loss of energy needed to sustain use pattern.

d. Social reproach; dissatisfaction of family and others.

e. Loss of life satisfactions.

f. Fear of health effects.

2. Society

a. If intravenous user, can transmit HIV.

b. Poor performance in social roles (parenting, work).

c. Criminal behaviors.

d. Service overutilization (medical, incarceration, public

assistance, foster care).

3. Clinical investigator

a. Features of cocaine use “syndrome.”

• Binges: repeated self-administration with

larger and larger doses.

• Withdrawal symptoms.

• Craving.

• Relapse.

b. Clinical depression.

c. HIV risk.

d. Poor quality of life even if stops drug use.

e. Activity of reward centers in brain.

f. Drug use maintained by operant and classical conditioning.

contrast to most other common DSM-IV Axis I disorders of adulthood,

substance-related disorders often are not associated with subjective

distress. In fact, the subjective experiences associated with drug use often
123

are very positive: The experience typically is not just a neutral one of

lack of subjective distress. The pleasure-producing or reinforcing effects

of the “symptom” of substance use can be expected to compete with any

associated negative effects or problems that could provide motivation for

treatment.

The central relevance of this fact for outpatient RCTs of treatments for

substance-related disorders is suggested by the high attrition rates in such

studies (typically greater than 50 percent dropout in the initial phase of

treatment). In fact, high attrition is one of the most robust findings from

substance abuse treatment research to date. The fundamental problems

posed by attrition to the interpretation of findings from RCTs are

described by Howard and colleagues (1990).

Attrition in RCTs of substance-related disorders typically is substantially

higher than in RCTs of other common disorders, such as mood and

anxiety disorders. Attrition rates ranging from 20 percent to 40 percent

generally are found in RCTs of mood and anxiety disorders (e.g., Elkin et

al. 1989). Even attrition in the placebo control conditions of outpatient

treatment studies of such disorders tends to be 40 percent or lower. The

difference in attrition rates in RCTs of substance-related disorders and

other psychiatric disorders typically is attributed to the relative lack of

subjective distress and pleasurable effects associated with substance use

which, in turn, reduces motivation for treatment.

What are the implications of the foregoing points for outcome

measurement in RCTs of pharmacological treatments for substancerelated disorders? One implication is that investigators should try to

identify problems associated with the targeted substance-related disorder

from the patient’s perspective. The more able investigators are to find

some source(s) of subjective distress associated with the disorder and the

more effectively the pharmacological treatment, or the “treatment

package” within which the pharmacological treatment is embedded,

affects problems that are associated with subjective distress, the more

likely that interpretable efficacy findings will be obtained (i.e., from a

study with low attrition rates). A second implication of the low subjective

distress feature is that society’s perspective on the problems associated

with a disorder is likely to exert more influence on outcome measure

selection for substance-related disorders than for disorders in which the

treated individual identifies the primary problems to be treated.

A consideration: Outcomes assessed from different perspectives are likely

to yield different findings. The perspective subquestion is relevant to

outcome assessment of pharmacological treatments in yet another way. A
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basic methodological conclusion from psychotherapy outcome research

over the years is that outcomes typically differ depending upon the

perspective from which outcome data are obtained, e.g., the patient, the

therapist, an independent clinical evaluator, or a significant other (Strupp

and Hadley 1977). The observation has led investigators to include

outcome measures from multiple perspectives in studies, based on the

premise that several perspectives typically must be recognized as valid

when evaluating the state of a disorder. In other words, reasonably

complete information on a treatment’s efficacy requires outcome data

from the perspectives that are most affected by, can provide expert

opinions on, and/or can provide judgments that are less affected by the

subjective biases inherent in the other important perspectives on the state

of the disorder being examined.

Other considerations: Necessary and sufficient conditions for defining a

substance-related disorder, and the central role of society’s perspective in

evaluating outcomes. The disorder of cocaine dependence also illustrates

a point that is infrequently discussed when designing RCTs for substancerelated disorders. The first basic question, “What problems do patients

with the disorder have?” can confront investigators with the prominent

role played by social values in the identification of substance use

“disorders.” For example, in a literature review prepared for the DSMIV Substance-Related Disorders Workgroup, Irwin (1994) noted that

“prior to the 1980's cocaine was considered to be a relatively safe,

nonaddictive, euphoriant agent” (p. 169).

What are the scientific implications of the fact that society’s opinions can

change about what is and what is not problematic substance use? First, as

already mentioned, society’s perspective is a central one in identifying the

problems associated with a substance-related disorder. Second, as

recognized in the diagnostic criteria for substance-related disorders in the

DSM-IV (American Psychiatric Association 1994), use of an illicit

substance in itself does not merit being labeled a “disorder.” Rather,

certain patterns of use, i.e., patterns that are associated with functional

impairment and/or high risk to oneself or others (in the absence of

subjective distress), are required to be designated as a disorder.

The principle that the primary problems of substance users are patterns of

use that are associated with functional impairment and/or types of risk to

oneself or others is an important one for investigators to consider when

choosing outcomes for pharmacological treatments for substance-related

disorders. Conceptualizing the problem to be treated as a pattern of

behavior (or use) will doubtless lead to different decisions about the most

appropriate outcome measures and measurement strategies. Furthermore,

the principle could affect investigators’ decisions about which treatments
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or treatment packages merit testing in RCTs. For example, if a particular

pharmacological agent targets only an isolated feature of use of a

substance, such as craving or withdrawal symptoms, embedding the agent

in a treatment package that consists of psychosocial interventions and,

perhaps, other sequentially administered pharmacological agents, might

be considered. For pharmacological agents that target narrow outcomes, a

modular treatment package is likely to be needed to produce clinically

significant outcomes in substance-related disorders, especially the

outcomes of most interest from society’s perspective.

Question 2. Which of the problems is the treatment intended to address?

Possible answers to the second question, using the example of cocaine

dependence, are shown in table 3. The answers there are based on a

review of recent treatment studies for cocaine dependence and the

discussion by Weiss and Mirin (1990). The table illustrates the kinds of

problems and outcomes that currently tend to be examined in RCTs of

cocaine dependence.

Question 3. What outcomes associated with the treatment are of

primary interest? Table 4 presents examples of how the third basic

question might be answered by investigators who want to examine a

pharmacological treatment for cocaine dependence, based on current

conventions in treatment research on cocaine use.

Step II: Identification of Measures and Methodological Considerations

Once the first three questions have been answered, three more questions

must be addressed to answer the basic treatment outcome question: Does

pharmacological treatment X affect the desired outcomes for substancerelated disorder Y? The next three questions are 4, 5, and 6 in table 1.
126

TABLE 3. Question 2: Which of the problems is the treatment

intended to address?

1. Binge use (compulsive self-administration).

2. All use.

3. Withdrawal symptoms.

4. Craving.

5. Relapse.

6. Reward centers in brain.

7. Possible use-maintaining symptoms (e.g., depression).

TABLE 4.Question 3: What outcomes associated with the problems are of

primary interest?

1. Reduced frequency of use.

2. Reduced amount of use.

3. Initial abstinence period (e.g., > 1 month).

4. Long-term abstinence.

5. Relapse prevention after a period of abstinence.

6. Less impairing or dangerous use pattern.

7. Less dangerous route of ingestion.

Question 4. Which of the outcomes of primary interest can be measured

reliably and validly? Answers to the first three basic questions rely

mainly on an investigator’s conceptual skills, understanding of the

disorder to be treated, knowledge of the potential effects of the treatment

of interest, and value judgments. The next question requires

psychometric expertise to answer. Reliability and validity (e.g., Guilford
127

1954; Kraemer and Telch 1992; Nunnally 1978) are the fundamental

psychometric features of any measure that could be used to assess

outcomes in RCTs. Simply defined, reliability refers to the repeatability

of scores obtained on a measure. For scientific purposes, researchers want

to know that the score or value assigned to a respondent based on a

measure is a replicable index of his/her status on the measure at the time

when the measurement was made. Psychometric methods for determining

the reliability of a measure are designed to estimate the “true score

variance” (e.g., compared to either random or nonrandom error variance)

in a score on the measure. Alternatively stated, reliability statistics are

estimates of the signal-to-noise ratio contained in scores on a measure.

More reliable measures have more signal, less noise (error). Validity is

the extent to which scores on a measure do, in fact, reflect the construct or

variable that researchers think they do. An outcome measure’s reliability

and validity credentials are the fundamental determinants of the potential

strength of the evidence (e.g., effect sizes) (Leon et al. 1995) and the

accuracy of the conclusions (interpretation of the findings) obtained from

an RTC.

Despite the linchpin importance of a measure’s reliability and validity

statistics, both tend either to be ignored or acknowledged only in

superficial ways in psychiatric clinical outcome research. Well-established

methodologies exist for the evaluation of a measure’s reliability and

validity (Nunnally 1978). Familiarity with the methods and knowledge of

how to interpret reliability and validity statistics are required to choose

between alternative measures to examine an outcome of interest. If an

investigator does not have the required expertise, consultation on this

aspect of measure selection should be sought.

A full discussion of reliability and validity evaluation of outcome

measures is beyond the scope of this chapter. Only two additional points

will be made here: One concerns a prominent error about reliability in

psychiatric research and the other concerns the use of measures intended

to circumvent self-report to evaluate drug use outcomes (e.g., urinalysis).

Kraemer and Telch (1992), Leon and colleagues (1995), and Rush and

colleagues (1994) provide additional discussion of reliability and validity

of outcome measures, and of the critical need for psychometrically sound

measure development for psychiatric treatment research.

Reliability of observer-judged measures. One of the most common

investigator errors in published RCTs for psychiatric disorders is the belief

that reliability inheres in observer-rated measures, such as the Hamilton

Rating Scale for Depression (Hamilton 1960), the Structured Interview

Guide for the Hamilton Depression Rating Scale (SIGH-D, Williams
128

1988), and the Structured Clinical Interview for DSM-IV Disorders (SCID,

First et al. 1996). This belief is reflected in statements like “the SCID has

been shown to have adequate reliability for the diagnosis of X.” Such

statements are sometimes followed by a kappa coefficient and a citation of

a study that reported the kappa.

The reliability of scores on observer-rated instruments is always a function

of both the instrument and the specific observer/user. Reliability-relevant

features of observer/users typically include their clinical experience, both

general and with the specific patient population being studied, and the

training they received to use the instrument. Because reliability is never

inherent in observer-judged instruments, reliability must be evaluated for

every study. Figures from other studies in which other observers provided

the data give no information whatsoever on the reliability of the data from

the measures in the current study.

Validity of self-report measures of drug use. A second highly relevant

point for outcome measurement in RCTs of substance-related disorders

concerns the validity of self-report measures. It is commonly assumed by

both investigators and clinicians who work in substance use treatment that

self-report data on drug use during treatment cannot be relied upon as

accurate. This concern has led to the standard utilization of other

measures to evaluate drug use, i.e., measures that can circumvent

dissimulation. To date, urinalysis is the most commonly used alternate

method in RCTs of substance-related disorders.

Technical complexities associated with using urinalysis results to measure

the outcome of reduced drug use are well detailed in several other

chapters in this monograph and in Blaine and associates (1994). Less

often considered are the psychological impacts and possible impact on

attrition associated with the requirement to provide urine samples as part

of a treatment program. Investigators of substance use treatments must

closely consider (a) the probable validity of self-report measures of drug

use and possible ways to enhance their validity (see Moras 1993), and (b)

the benefits and costs (including low reliability and validity, and technical

complexity) associated with methods that are designed to circumvent selfreport indices of drug use.

Question 5: How can an investigator be sure that the pharmacological

treatment of interest contributed substantially to the outcomes obtained?

Answering this question requires sophistication and expertise in

experimental design in general, the design of RCTs in particular, and

careful attention to the implications of each design decision for the

internal validity of the study (Cook and Campbell 1979). Internal validity
129

refers to the extent to which a study’s design, methods, and procedures

allow the data obtained to be interpreted as evidence of the main

hypothesis(es) being examined. The aforementioned edited volume by

Prien and Robinson (1994) contains several chapters on relevant design

and methodological issues, specifically for RCTs of pharmacological

agents for substance-related disorders.

Table 5 presents an abbreviated list of pertinent design, methodological,

and procedural questions that must be considered to plan an RCT that

yields findings that can be interpreted as effects of a pharmacological

agent on the outcomes of interest. All design considerations included in

the list are discussed in chapters in Prien and Robinson (1994).

Problems posed by adjunctive treatments. Only one of the points listed in

table 5, i.e., number 3, “Control and/or limit adjunctive psychosocial and

pharmacological interventions,” will be discussed here. The point

concerns one of the most common sources of low internal validity in

RCTs of treatments for substance-related disorders. The relevant principle

is a simple one: Interpreting outcome findings as evidence for the

efficacy of a treatment of interest requires, at minimum, that patients’

receipt of other treatments is proscribed or somehow controlled.

Despite the logical necessity of the foregoing principle, patients in RCTs

of treatments for substance abuse commonly receive many ancillary

treatments and, even more problematic for the internal validity of a trial,

often receive them on an as-needed (uncontrolled) basis. (Ancillary or

adjunctive treatments are therapeutic or potentially therapeutic interventions that are not regarded by the investigators as part of the

treatment[s] being examined.) Moreover, investigators often neglect to

report any information on the ancillary treatments (e.g., what they were,

what percentage of the patients in each treatment condition received each

one, etc.). Failure to control ancillary treatments in an RCT will

fundamentally compromise interpretation of any effects found as due to

the pharmacological treatment of interest.
130

TABLE 5. Question 5: How can researchers be sure that the

pharmacological agent contributed substantially to the outcomes?

1. Pretrial “lead-in” placebo washout phase.

2. Placebo control condition in design.

3. Control and/or limit adjunctive psychosocial and pharmacological

interventions.

4. Control use of substances.

5. Assess compliance with the pharmacological treatment.

Substance-related disorders are maintained by multiple variables. A

common rationale for providing ancillary treatments to patients in

substance disorder treatment studies is that the patients have multiple

problems (Moras 1993). Furthermore, it is often argued that the

treatment of interest is unlikely to be efficacious if the patients’ other

problems are not also addressed. Oddly, when the latter statement is

made, it is not linked to the logical implication that the findings of the

study cannot be interpreted as evidence for the treatment being examined

alone: The efficacy data necessarily pertain to the entire treatment

package within which the treatment of interest was (sometimes

naturalistically) embedded.

The foregoing points are likely to be particularly relevant for RCTs of

pharmacological agents for substance disorders. Many experienced

substance abuse treatment investigators hypothesize that substance-related

disorders are caused and/or maintained by a network of variables, with

psychosocial factors playing a substantial role in maintaining, if not

causing, patterns of substance abuse. Such hypotheses, plus the

commonly acknowledged limitations in the efficacy of methadone, the

most efficacious pharmacological intervention for a substance-related

disorder to date, have obvious implications for the development of other

pharmacological interventions. They suggest that efforts to develop other

pharmacological agents for substance disorders will be limited unless the

interventions are provided in the context of more comprehensive

treatment packages or programs.

Need for multicomponent treatments. What do the preceding arguments

suggest about the development of new pharmacological treatments for

substance-related disorders? One implication is that investigators are well
131

advised to consider the range of problems associated with the disorder of

interest, which aspects of the disorder the pharmacological agent can

reasonably be expected to affect, and other interventions that might be

needed in conjunction with the pharmacological agent to attain clinically

significant outcomes. Another implication is that pharmaco-logical

agents that are intended to have only narrow effects (e.g., on craving)

might be most cost-effectively examined in basic research studies with

human beings; then, if efficacious, included as a component of a more

comprehensive treatment. The comprehensive treatment would then be

examined in an RCT, not the pharmacological treatment alone. The

National Institute on Drug Abuse’s Behavioral Therapies Development

Program (1994) provides an incentive for the development of such

treatment packages.

Question 6. How can researchers be sure not to miss outcomes

associated with a pharmacological treatment of interest? Similar to

question 5, answering this question requires sophistication in experimental design. It also requires expertise in the conduct of pharmacological treatment trials, particularly knowledge of variables that affect the

effects of pharmacological agents. Table 6 lists a few central

considerations for answering this question. The points listed will be

discussed briefly. The reader is referred again to the comprehensive

edited text by Prien and Robinson (1994) with chapters on the relevant

considerations.

The first two points in table 6 concern a topic previously discussed, the

severe compromise posed by high attrition to obtaining interpretable

efficacy findings from an RCT. Point 1 in table 6, matching the outcome

goals of patients who have the substance disorder to be treated with the

probable effects of the treatment, will reduce attrition as long as the

treatment itself is not unduly noxious in some way. The second point,

“stability of the patient’s motivation for the goal,” also relates to attrition

concerns, but is focused on sample selection. Comorbid psychiatric

disorders and comorbid substance-related disorders are examples of

variables that can undermine the stability of patients’ motivation for a

treatment that they actually endorse. Therefore, the presence of such

comorbid conditions can increase attrition. On the other hand, adding

exclusion criteria to sample selection criteria can compromise a study’s

external validity, i.e., the generalizability of the results.
132

TABLE 6.Question 6: How can researchers be sure not to miss outcomes

associated with the pharmacological agent?

1. Patient goal and treatment goal matching.

2. Stability of patient’s motivation for goal.

a. Polysubstance abuse

b. Comorbid psychiatric diagnoses

3. Reliable measures.

4. Variables that affect pharmacokinetics and pharmacodynamics.

5. Optimal psychosocial treatment “context” for pharmacological

agent.

6. Statistical analyses.

Point 3 highlights the role of reliable measures in obtaining scores that

have minimal error variance which will, in turn, increase the probability of

finding desired outcomes if they are, in fact, effected by a treatment.

Point 4 highlights the fundamental importance of using knowledge of the

pharmacokinetics and pharmacodynamics of a pharmacological agent

(Greenblatt et al. 1994) in design and sampling decisions for an RCT.

Needed knowledge of this type ideally will be generated in preparation

for an RCT so that it can be used in designing the RCT. Such knowledge

is a central determinant of the effects that will be found in an RCT of a

pharmacological agent. The knowledge is equally as central to the

findings as are the reliability and validity of the outcome measures. For

example, knowledge of gender differences associated with pharmacokinetics, such as the impact of the menstrual cycle, is critical information

for planning RCTs of agents intended to be used with both male and

female substance users.

The earlier section of this chapter on basic question 5 (table 1) also is

relevant to point 5 in table 6. A pharmacological intervention might be

capable of potentiating a desired effect, but will do so only if other aspects

of a patient’s substance-related disorder also are treated in some way.

Point 6 highlights the importance of using appropriate statistical

techniques intelligently (Lavori et al. 1994). Also, new and sophisticated
133

statistical procedures are being identified that can be applied to RCTs.

For example, random regression (Gibbons et al. 1993) might be

productively applied to evaluate and compare the rates of change of

various outcomes associated with different treatments when repeated

measures of outcomes are obtained.

CONCLUDING REMARKS

This chapter was intended to be concise, despite the broadness and

complexity of the topic. Thus, main points will not be summarized here.

Rather, for a summary, refer to table 1, which contains six basic questions

for planning outcome assessment for RCTs of pharmacological agents for

substance-related disorders. As noted, the six questions are equally

applicable to RCTs of other common psychiatric disorders. For more

information on any of the questions, the reader should turn to the relevant

section of the text.

One potentially controversial point made here is that investigators who are

interested in developing and examining pharmacological agents for use in

the treatment of substance-related disorders are encouraged to closely

consider the requisite psychosocial treatment “context” for optimal

delivery of the agent of interest, i.e., the context that is needed for the

agent to be associated with clinically significant effects. This point was

made based on the relative lack of highly efficacious treatments for

substance-related disorders, either pharmacological or psychosocial,

despite many years of research effort. The difficulty in developing

treatments with the desired levels of efficacy has led many experienced

substance abuse researchers to posit a complex network of maintaining

variables that, even if not causative, make strong contributions to the

continuation of substance-related disorders in adults. The preceding

speculation, in turn, is associated with a clear current trend to recommend

the development of comprehensive treatment packages for substancerelated disorders, including treatments that combine psychosocial and

pharmacological components.

A final point to be made is that a considerable amount of knowledge has

been amassed over the years on the conduct of RCTs for psychiatric

disorders. This knowledge is well illustrated in several references that

were cited such as Kazdin (1994), Kraemer and Telch (1992), and the

chapters in Prien and Robinson (1994). As alluded to by Kraemer and

Telch (1992), one of the main problems now faced in generating

interpretable findings from RCTs is the failure of many investigators to

implement available knowledge (e.g., about the central importance of
134

selecting reliable and valid outcome measures). One contribution to this

problem, perhaps, is the incentive system that affects investigators who

work in university settings. Promotion typically is largely contingent on

number of publications, rather than their quality. In addition, designing

and conducting rigorous studies is more labor intensive than completing

weaker studies. The time and effort involved in a rigorously done study

also can be associated with longer time to publication and, perhaps, fewer

publications. Investigators interested in pharmacological treatments for

substance-related disorders who have been strongly influenced by

standards applied in many pharmaceutical company-sponsored trials

might be especially susceptible to design and methodological

“shortcuts.” In any event, the point to be made is that much

sophistication now exists about the critical considerations for, and

necessary elements of, interpretable RCTs. This sophistication is ready to

be applied to pharmacological treatments for substance-related disorders.

REFERENCES

American Psychiatric Association. Diagnostic and Statistical Manual

of Mental Disorders. 4th ed. Washington, DC: American Psychiatric

Association, 1994.

Blaine, J.D.; Ling, W.; Kosten, T.R.; O’Brien, C.P.; and Chiarello, R.J.

Establishing the efficacy and safety of medications for the

treatment of drug dependence and abuse: Methodologic issues. In:

Prien, R.F., and Robinson, D.S., eds. Clinical Evaluation of

Psychotropic Drugs: Principles and Guidelines. New York: Raven

Press, 1994.

pp. 593-624.

Cook, T.D., and Campbell, D.T. Quasi-experimentation: Design and

Analysis Issues for Field Settings. Boston: Houghton Mifflin

Company, 1979.

Elkin, I.; Shea, M.T.; Watkins, J.T.; Imber, S.D.; Sotsky, S.M.; Collins,

J.F.; Glass, D.R.; Pilkonis, P.A.; Leber, W.R.; Docherty, J.P.; Fiester,

S.J.; and Parloff, M.B. National Institute of Mental Health

Treatment of Depression Collaborative Research Program: General

effectiveness of treatments. Arch Gen Psychiatry 46:971-972,

1989.

First, M.B.; Spitzer, R.L.; Gibbon, M.; and Williams, J.B.W. Structured

Clinical Interview for DSM-IV Axis I Disorders - Patient Edition.

February 1996. Final SCID-I/P, Version 2.0. Biometrics Research

Dept., New York State Psychiatric Institute, 1996.

Gibbons, R.D.; Hedeker, D.; Elkin, I.; Waternaux, C.; Kraemer, H.C.;

Greenhouse, J.B.; Shea, M.T.; Imber, S.D.; Sotsky, S.M.; and
135

Watkins, J.T. Some conceptual and statistical issues in analysis of

longitudinal psychiatric data. Arch Gen Psychiatry 50:739-750,

1993.

Greenblatt, D.J.; Abernethy, D.R.; and Chaikin, P. Pharmacologic

considerations. In: Prien, R.F., and Robinson, D.S., eds. Clinical

Evaluation of Psychotropic Drugs: Principles and Guidelines. New

York: Raven Press, 1994. pp. 123-138.

Guilford, J.P. Psychometric Methods. New York: McGraw-Hill, 1954.

Hamilton, M.A. A rating scale for depression. J Neurol Neurosurg

Psychiatry 23:56-62, 1960.

Howard, K.I.; Cox, W.M.; and Saunders, S.M. Attrition in substance

abuse comparative treatment research: The illusion of

randomization. In: Onken, L.S., and Blaine, J.D., eds.

Psychotherapy and Counseling in the Treatment of Drug Abuse.

National Institute on Drug Abuse Research Monograph 104. NIH

Pub. No. (ADM)90-1722. Washington, DC: Supt. of Docs., U.S.

Govt. Print. Off., 1990. pp. 66-79.

Irwin, M.R. Cocaine and amphetamine: Psychostimulant abuse. In:

American Psychiatric Association DSM-IV Sourcebook. Vol. 1.

Washington DC: Author, 1994. pp. 159-168.

Kazdin, A.E. Methodology, design, and evaluation in psychotherapy

research. In: Bergin, A.E., and Garfield, S.L., eds. Handbook of

Psychotherapy and Behavior Change. New York: John Wiley and

Sons, 1994. pp. 19-71.

Kraemer, H.C., and Telch, C.F. Selection and utilization of outcome

measures in psychiatric clinical trials: Report on the 1988

MacArthur Foundation Network I Methodology Institute.

Neuropsycho- pharmacology 7:85-94, 1992.

Kraemer, H.C.; Pruyn, J.P.; Gibbons, R.D.; Greenhouse, J.B.;

Grochocinski, V.J.; Waternaux, C.; and Kupfer, D.J. Methodology

in psychiatric research: Report on the 1986 MacArthur Foundation

Network I Methodology Institute. Arch Gen Psychiatry 44:110-

1106, 1987.

Lambert, M.J. Conceptualizing and selecting measures for treatment

outcome: Implication for drug abuse outcome studies. In: Onken,

L.S., and Blaine, J.D., eds. Psychotherapy and Counseling in the

Treatment of Drug Abuse. National Institute on Drug Abuse

Research Monograph 104. NIH Pub. No. (ADM)90-1722.

Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1990.

Lavori, P.W. Clinical trials in psychiatry: Should protocol deviation

censor patient data? Neuropsychopharmacology 6:39-48, 1992.

Lavori, P.W.; Laska, E.M.; and Uhlenhuth, E.H. Statistical issues for

the clinical evaluation of psychotropic drugs. In: Prien, R.F., and

Robinson, D.S., eds. Clinical Evaluation of Psychotropic Drugs:
136

Principles and Guidelines. New York: Raven Press, 1994. pp. 139-

160.

Leon, A.C.; Marzuk, P.M.; and Portera, L. More reliable outcome

measures can reduce sample size requirements. Arch Gen

Psychiatry 52:867-871, 1995.

Moras, K. Substance abuse research: Outcome measurement

conundrums. In: Onken, L.S.; Blaine, J.D.; and Boren, J.J., eds.

Behavioral Treatments for Drug Abuse and Dependence. National

Institute on Drug Abuse Research Monograph 137. NIH Pub. No.

(ADM)93-3684. Washington, DC: Supt. of Docs., U.S. Govt. Print.

Off., 1993.

National Institute on Drug Abuse. Behavioral therapies development

program. Program Announcement #PA-94-078. Catalog of

Federal Domestic Assistance No. 93.279. July 1994.

Nunnally, J.C. Psychometric Theory. 2d ed. New York: McGraw-Hill,

1978.

Prien, R.F., and Robinson, D.S., eds. Clinical Evaluation of

Psychotropic Drugs: Principles and Guidelines. New York: Raven

Press, 1994.

Rush, A.J.; Gullion, C.M.; Raskin, A.; Kellner, R.; and Bartko, J.J.

Assessment and measurement of clinical change. In: Prien, R.F.,

and Robinson, D.S. , eds. Clinical Evaluation of Psychotropic

Drugs: Principles and Guidelines. New York: Raven Press, 1994.

Strupp, H.H., and Hadley, S.W. A tripartite model of mental health

and therapeutic outcomes. Am J Psychol 32:187-196, 1977.

Weiss, R.D., and Mirin, S.M. Psychological and pharmacological

treatment strategies for cocaine dependence. Ann Clin Psychiatry

2:239-243, 1990.

Williams, J.B.W. A structured interview guide for the Hamilton

Depression Rating Scale. Arch Gen Psychiatry 45:742-747, 1988.

AUTHOR

Karla Moras, Ph.D.

Director

Assessment Unit

Center for Psychotherapy Research

University of Pennsylvania

3600 Market Street, Room 701

Philadelphia, PA 19104-2648
137

Variability in Treatment-Seeking

Cocaine Abusers: Implications for

Clinical Pharmacotherapy Trials

Kathleen M. Carroll, Charla Nich, and Bruce J. Rounsaville

Variability in cocaine abusers seeking treatment in terms of potential

prognostic dimensions such as severity of dependence, route of

administration, concurrent use or dependence on other drugs and

alcohol, psychiatric comorbidity, treatment history, and many others,

has been a long-recognized feature of this population. Consideration

of hetero-geneity among cocaine abusers is important as it may point

to treatment strategies for some subpopulations. For example,

identification of subgroups with distinct clinical characteristics or who

have differential response to treatment is useful, as it may point to

specialized treatment strategies that may be effective for these

subgroups or for patient-treatment matching. At the same time,

however, patient heterogeneity often confounds the interpretation of

data from many pharmacology and psychotherapy treatment trials

conducted thus far, by introducing noise and decreasing power to

detect treatment effects.

In considering the implications of patient variability for cocaine

pharma-cotherapy trials, it should first be noted that no

pharmacotherapies are universally effective. For example,

methadone maintenance, by far the most effective treatment for

opioid dependence, is not universally successful in retaining patients

or affecting complete cessation of illicit opioid use (Lowinson et al.

1992). Although program characteristics are associated with a great

deal of variability in outcome (Ball and Ross 1991), patient

characteristics such as psychiatric severity is another important

predictor of response to methadone maintenance treatment

(McLellan et al. 1993; Rounsaville et al. 1982). Similarly, although

naltrexone has had limited impact on the drug abuse treatment system

because of compliance and retention issues, it nevertheless retains a

place in the treatment system because it is successful with some types

of patients, typically middle-class patients and those with less severe

or less chronic opioid dependence (Rounsaville 1995). Thus, success

profiling, i.e., identifying patient characteristics associated with

optimal outcome in well-defined treatments, is an important strategy

for enhancing the effectiveness of treatment by providing treatment

primarily to those most likely to benefit from it. Evaluation of
138

patient-treatment interactions has become a cornerstone of research

on psychosocial treatments for substance dependence, where main

effects of one form of treatment over another are rare, and response

to even the most effective psychosocial approaches is incomplete.

Evaluation of patient-treatment interactions may be an underutilized

strategy in medications development.

To illustrate how evaluation of variability in treatment response as a

function of patient characteristics may lead to a more complete

understanding of a treatment’s effects and help make sense of

apparently contradictory findings across different studies, two

examples from recent clinical trials evaluating pharmacotherapy for

cocaine dependence will be presented. The first example illustrates

variations associated with patient characteristics as moderators of

treatment response (variables that affect the strength or direction of

treatment response); the second illustrates implications of a patient

characteristic as a mediator of treatment response (a mediator is a

variable that produces a relationship between the independent and

dependent variable). In other words, mediators determine the nature

or mechanism of a matching effect, and moderators determine the

strength of a match (see Baron and Kenny 1986, and DiClemente et

al. 1994 for a fuller description).

Example 1: Desipramine Treatment of Cocaine Dependence

Enormous excitement was generated by the initial promising findings

concerning the effectiveness of tricyclic antidepressant treatment of

cocaine dependence, first in an open trial (Gawin and Kleber 1984)

and later in a randomized, double-blind, controlled trial (Gawin et al.

1989), which indicated significant reductions in cocaine use for

desipramine compared to lithium and placebo. However, later studies

conducted in other settings with different patient populations

generally failed to find main effects supporting the effectiveness of

desipramine among the general population of cocaine abusers,

including those on methadone maintenance (Arndt et al. 1992;

Kosten et al. 1992; Weddington et al. 1991). What happened?

While this set of studies underlines the importance of replicating a

treatment’s effects in multiple studies before it is widely adopted, it

also highlights the point that variations in a medication’s

effectiveness may be explained by the changing nature of the patient

population.

To illustrate this, findings from the Gawin study will be compared with

outcomes from a later randomized controlled trial of desipramine and
139

cognitive-behavioral relapse prevention, in a 2X2 design, as

treatment for 121 cocaine abusers (Carroll et al. 1994a). This study

was conceived in part as a replication of the initial promising findings

of desipramine, but more importantly to extend those findings by

systematically evaluating the effectiveness of psychotherapy as well.

Therefore, the authors strove for a high level of methodological rigor

in specifying and implementing both pharmacologic and

psychotherapeutic aspects of treatment. For example, design features

of the study included:

•Random assignment to treatment condition (desipramine plus

relapse prevention treatment, desipramine plus clinical

management, placebo plus relapse prevention, or placebo plus

clinical management.

•Careful selection of appropriate control conditions for both the

desipramine treatment (placebo) and the cognitive-behavioral

psychotherapy (clinical management, which provided nonspecific

aspects of psychotherapy but not active ingredients of the coping

skills treatment).

•Specification of all aspects of treatment delivery in manuals

(Carroll et al. 1991b; Fawcett et al. 1987).

•Adequate duration of treatment (12 weeks) to allow emergence

of specific effects of both pharmaco- and psychotherapy.

•Avoiding confounding of treatment through limiting subjects’

exposure to nonstudy treatments.

•Delivery of treatments by experienced therapists committed to

the type of treatment they conducted (doctoral-level

psychologists conducted the cognitive-behavioral relapse

prevention treatment, and postresidency psychiatrists conducted

clinical management).

•Extensive therapist training, which included both a 2-day didactic

seminar and successful completion of at least one closely

supervised training case.

•Efforts to improve adherence to manual guidelines and prevent

drift through the main phase of the study, which included regular

meetings with therapists in each condition to discuss case material

and review session videotapes.
140

•Close monitoring of both forms of treatment, which included

regular assessment of medication plasma levels and process

assessment of session videotapes by independent raters, which

showed the relapse prevention and clinical management

treatments were discriminable (Carroll et al., in press).

•Multidimensional assessment of outcome from multiple sources,

including clinical evaluators blind to treatment condition (Carroll

et al. 1994a).

•1-year followup, where 80 percent of all patients randomized to

treatment were interviewed at least once (Carroll et al. 1994b).

Results: Main and Interaction Effects

After 12 weeks of treatment, subjects as a group showed significant

improvement on most outcome measures, including cocaine use and

psychosocial outcomes. However, significant main effects of desipramine, relapse prevention, or their interaction were not seen on

primary outcomes, which included urine toxicology screens, frequency of

cocaine use in the past 30 days, and Addiction Severity Index (ASI)

cocaine composite scores (see Cacciola et al., this volume). Therefore,

despite the authors’ clinical sense of marked variations in outcome among

patients in the sample, outcomes appeared similar across treatments when

the sample was evaluated as a whole. However, there were data from two

previous studies suggesting that severity may be an important moderator

of treatment response in cocaine abusers. Therefore, by not evaluating

outcome with respect to severity differential treatment effects may be

masked. The first of these studies reported on a 1-year followup from a

diagnostic study of 298 treatment-seeking cocaine abusers (Carroll et al.

1993b), which found that the most consistent and robust predictor of

functioning was the subjects’ severity of cocaine dependence at baseline

(as assessed by total number of DSM-III-R cocaine dependence criteria

endorsed). The second study, pointing to severity as a moderator of

treatment response in cocaine abusers, was a pilot psychotherapy study

that compared two forms of psychotherapeutic treatments: cognitivebehavioral relapse prevention (RP) or interpersonal psychotherapy (IPT)

(Carroll et al. 1991a). In that study, while again there were no main

effects of psychotherapy type on cocaine outcomes, marked differences

in response to treatment were found after stratifying for baseline severity:

At low levels of severity subjects both IPT and RP fared about equally in

achieving at least 3 weeks abstinence during treatment. However, at high

levels of severity, subjects in RP were significantly more likely to attain 3
141

weeks of abstinence than high-severity patients treated with IPT (54

percent versus 9 percent).

Thus, as previous research suggested that severity of cocaine use may be

an important moderator of treatment response in cocaine abusers, data

from the relapse prevention-desipramine study evaluating interactions of

treatment type by severity were reanalyzed. However, severity was not

defined a priori as a factor. The sample was stratified into three levels (to

sharpen contrasts between high and low severity use): low (1 to 2.5 g of

cocaine per week at baseline), moderate (2.6 to 4.4 g per week), and high

severity (more than 4.5 g per week). Univariate ANOVAs indicated this

classification of severity was associated with other indicators, including

chronicity of use and route of administration.

Results of the exploratory 2X2X3 (medication by psychotherapy by

severity) ANOVAs are illustrated in figure 1. There were consistent

severity by psychotherapy (relapse prevention versus clinical

management) interactions, with higher severity subjects who received

relapse prevention reporting significantly longer consecutive periods of

abstinence, better retention, and fewer cocaine-positive urine toxicology

screens.

There were no significant pharmacotherapy (desipramine/placebo) by

severity interactions for primary outcomes for the full sample. However,

for the subsample that completed at least five sessions and therefore had

greater opportunity for emergence of medication effects, there was a

significant interaction between medication and baseline severity. Lowseverity subjects treated with desipramine had significantly longer periods

of consecutive abstinence than low-severity subjects taking placebo; for

moderate and high-severity subjects desipramine and placebo were

comparable in effectiveness.

Comparison With Other Desipramine Studies

Thus, in this study desipramine appeared most effective among the least

severe cocaine abusers. These findings were thus inconsistent with the

data reported by Gawin and colleagues (1989), which suggested a robust

main effect for desipramine. As these two studies were conducted in the

same clinic, by overlapping groups of investigators, using parallel sets of

procedures and inclusion/exclusion criteria, the differences in desipramine

effects is puzzling, until characteristics of the two samples are compared:

Subjects in the Gawin and colleagues 1989 study were
142

recruited between 1984 and 1987 during the burgeoning of the cocaine

epidemic, while the Carroll and colleagues 1994 study recruited

patients between 1987 and 1991, a period characterized by rapid shifts

in the treatment-seeking population and increasing predominance of

freebase and crack use.

As indicated in table 1, the two subject samples differed on a number of

dimensions. The Gawin sample included fewer blacks and Latinos, more

patients who were employed, and more intranasal and fewer freebase

users. Subjects in the Gawin sample also reported using fewer grams of

cocaine per week on average, and had approximately half the rate of Axis

I disorders with respect to the Carroll and colleagues 1994 study. Thus, it

appears that subjects in the Gawin study, which suggested the general

effectiveness of desipramine, were most similar to the less severe

subsample of the authors’ study (the only subgroup for which desipramine

was found to have an effect on cocaine use). Similarly, Arndt and

associates (1994) reported a desipramine effect among methadonemaintained cocaine abusers only when those with concurrent antisocial

personality were excluded. Antisocial personality disorder has been

associated with severity of cocaine abuse (Carroll et al. 1993a). Thus,

exclusion of those with antisocial personality disorder in
143

TABLE 1. Variations in sample characteristics, Gawin et al. (1989)

compared to Carroll et al. (1994a)

Characteristic Gawin et al. Carroll et al.

(N = 72) (N = 121)

Percent female 24% 27%

Percent white 76% 46%

Percent employed (mean 10 yr) 52%

Percent single/divorced 71% 71%

Mean age 29 29

Mean cocaine g/wk 3.6 4.4

Route of administration

Percent intranasal 50.0 29.0

Percent freebase 32.0 62.0

Percent intravenous 18.0 9.0

Lifetime rates, DSM-III-R psychiatric disorders

Any Axis I disorder 14% 26%

Any affective disorder 11% 20%

Any anxiety disorder * 13%

Antisocial personality * 49%

Alcohol dependence * 33%

NOTE:* Indicates not reported.

the Arndt and colleagues 1994 sample may have left a less severe

subsample that, like the less severe sample in the authors’ study, was more

responsive to desipramine treatment.

Example 2: Desipramine Treatment of Depressed Cocaine Abusers

The growing literature on desipramine treatment of cocaine dependence

provides another example of how variations in sample characteristics

across studies may influence conclusions about a medication’s

effectiveness. Recall that there are two principal rationales for antidepressant treatment of cocaine dependence, each targeted to different

groups. First, desipramine may reverse cocaine-induced disregulation in

reward mechanisms, hence cocaine craving and use, in the general

population of cocaine abusers (Gawin and Kleber 1984; Gawin et al.

1989). The example above suggests that severity may be a moderator of

this effect. However, a second rationale for desipramine is that it may

work through treating depression in the subgroup of cocaine abusers who

may be attempting to self-medicate depressive symptoms (see Kosten
144

1989). Here, the presence of depression would serve as a mediating

variable for desipramine effects (e.g., desipramine would work only for

depressed subjects and reduction in depression would lead to reductions in

cocaine use). This distinction is also important in relation to the

inconsistent reports of the effectiveness of antidepressant treatment for

cocaine abusers across studies, as variations in rates of depression across

studies could affect conclusions about desipramine’s effectiveness if it

exerted effects primarily through an antidepressant mechanism or was

differentially effective with depressed cocaine abusers (Carroll et al.

1995).

However, few studies have reported on the effectiveness of antidepressants in reducing both cocaine use and depressive symptoms, or on

differences in desipramine’s effectiveness for general (nondepressed)

versus depressed subpopulations. Giannini and colleagues (1986) reported

a significant reduction in depression for cocaine addicts treated with

desipramine in an open trial, but did not report on cocaine outcomes. As

mentioned earlier, Gawin and colleagues (1989) reported that desipramine

significantly reduced cocaine use regardless of whether patients were

depressed. Weddington and colleagues (1991) found no effect of

desipramine over placebo on either cocaine or depression outcomes;

however, in that study, desipramine doses may have been subtherapeutic.

Among methadone-maintained opioid addicts who also abused cocaine,

Arndt and colleagues (1992) reported that desipramine improved

psychological functioning but did not affect cocaine use. Ziedonis and

Kosten (1991) found that depressed methadone-maintained opiate addicts

showed significant reduction in cocaine use when treated with amantadine

or desipramine compared with placebo, although these medications were

not effective in reducing cocaine use for nondepressed subjects. They also

reported that neither desipramine nor amantadine reduced depressive

symptoms significantly, a small increase in depressive symptoms was seen

for those treated with placebo.

In the 1994 study, the rationale for use of desipramine was as an

anticraving agent, intended to facilitate abstinence initiation in a

heterogeneous sample of cocaine users. Thus, the initial analyses did not

evaluate either (a) the effectiveness of desipramine as an antidepressant

agent for depressed cocaine abusers, or (b) whether desipramine might

have greater efficacy in reducing cocaine use among depressed patients.

The data were therefore reanalyzed to address these issues. For these

analyses, treatment response was assessed based on level of current

depressive symptoms (rather than presence of a DSM-III-R depressive

disorder) for several reasons: First, diagnosing affective disorders in

current substance users is complicated because it is difficult to distinguish
145

transient, substance-induced symptoms from more enduring syndromes

(Meyer 1986). Second, stringent guidelines for diagnosing affective

disorders in cocaine users, which require a period of stable abstinence

before symptoms can be counted as meeting criteria for affective

disorders, may underestimate rates of depressive disorders in current

cocaine abusers (Rounsaville et al. 1991). For example, although subjects’

mean pretreatment Beck Depression Inventory (BDI) and Hamilton

Rating Scale for Depression (HRSD) scores were 9.03 (SD = 6.36) and

7.66 (SD = 5.64), respectively, only 1 subject met criteria for a current

and 17 (20.7 percent) for a lifetime diagnosis of major depressive

disorder. This was in large part due to these subjects’ chronic substance

use histories, which typically began in early adolescence, with few periods

of stable abstinence that would allow definitive assessment of psychiatric

symptomatology independent of drug effects.

Thirty-seven subjects (35 percent) were identified as having at least

mildly elevated depressive symptoms at baseline, defined by BDI scores of

8 or above, and HRSD scores of 7 or above. Beck identified a score of 8

or above as consistent with moderate depression (Beck and Beck 1972).

While the HRSD has no standard scales for interpretation, Frank has

proposed a cutoff of seven to indicate presence of partial or full

expression of depression (Frank et al. 1991). The combination of the

two criteria was used to provide a more reliable indicator of level of

depressive symptoms and to identify a sample where independent

evaluators’ clinical impressions were consistent with patient self-reports

of depressive symptoms. Compared to the 72 subjects who did not meet

these criteria for elevated depressive symptoms, the 37 depressed subjects

were significantly more likely to be female and white, which is consistent

with recent studies evaluating gender (Griffin et al. 1989) and race

(Ziedonis et al. 1994) differences in clinical samples of cocaine abusers.

As expected, depressed subjects were significantly more likely to have a

lifetime history of a major depressive episode (36 percent versus 15

percent). There were no differences between the depressed and

nondepressed groups in terms of marital status, education, socioeconomic

status, or treatment group assignment. Regarding severity of cocaine use,

there were no differences between the depressed and nondepressed groups

on frequency or quantity of cocaine use nor principal route of

administration. However, the ASI cocaine composite score (see Cacciola

et al., this volume) suggested significantly higher severity for the

depressed group. Because of the baseline differences between depressed

and nondepressed subjects with respect to ASI cocaine composite scores

and gender, the analyses described below were repeated controlling for

these two variables. Neither gender nor baseline cocaine use had a

significant main effect on cocaine or depression outcomes, nor did
146

controlling for these variables alter the patterns or significance of the

findings presented below.

Treatment Response in Depressed Versus Nondepressed Cocaine

Abusers

Depressive symptoms dropped significantly more for the depressive

subgroup than the nondepressed subgroup as measured by both the BDI

and the HRSD, regardless of treatment condition. As shown in table 2,

although the depressed subjects were comparable to or more severe than

the nondepressed users on baseline measures of cocaine use, regardless of

treatment condition, the depressed subjects tended to accrue more days of

consecutive abstinence than nondepressed subjects (25.1 versus 18.8 days,

NS), and reported a higher percentage of abstinent days (0.86 versus 0.81,

NS), although these differences were not statistically significant.

Table 2 also shows that depressed subjects treated with desipramine had a

significantly greater reduction in depressive symptoms than placebotreated depressed subjects, as measured by the BDI (F = 3.80, p < 0.05).

Desipramine-treated subjects had a significant reduction in depressive

symptoms, as measured by the HRSD, regardless of whether or not they

were depressed (F = 3.37, p < 0.01). Relapse prevention treatment was

not associated with greater reduction in depressive symptoms than clinical

management for either the whole sample or the depressed subgroup.

For cocaine outcomes, desipramine was not associated with significant

improvements over placebo for either the full sample or the depressed

subgroup. However, there was a significant interaction for psychotherapy

type and depression on some cocaine outcomes. Depressed subjects

treated with relapse prevention reported significantly more days of

consecutive abstinence than the depressed subgroup, which received

clinical management (30.3 versus 20.2 days), while nondepressed
147
148
149

subjects accrued more abstinence in clinical management (23.7 versus

14.6 days, F = 6.95, p < 0.01). While this pattern was also seen for

percent days abstinent during treatment, the interaction was not

statistically significant.

Thus, analyses of desipramine effects on depressed cocaine users suggested

that desipramine was an effective antidepressant in this sample, but

appeared to have little effect on cocaine use. There were, however,

moderate correlations between reductions in depressive symptoms and

cocaine use (range 0.20 to 0.35). The direction of the moderate cocaine

depression relationship could not be determined from the data; that is,

whether reductions in cocaine use led to improvements in depression or

reduction of depression made it easier for patients to reduce their cocaine

use or both. That these correlations were higher for patients who

received desipramine compared to placebo suggests that the early but

transient desipramine-associated reductions in cocaine use may have been

associated with an antidepressant effect. To evaluate these relationships

further and to explore the role of depression as a potential mediator of

desipramine effects, further research, particularly desipramine trials that

specify depression as an a priori matching variable (such as those

described by Nunes, this volume) are needed.

RECOMMENDATIONS

Currently there is no medication that has been shown to be broadly

effective for retaining cocaine abusers in treatment, nor in reducing their

cocaine use. However, as illustrated in these two examples, there is

growing evidence that available treatments may be more effective in

some subgroups of cocaine abusers. Thus, rather than abandon current

approaches because of their apparent modest effects in treating the

general population of cocaine abusers, a more fruitful strategy may be

identification of characteristics associated with differential response to

treatment (that is, it may be better to effectively treat some cocaine

abusers some of the time than no cocaine abusers none of the time). A

crucial advance in this process would be more careful assessment and

description of study samples, as well as examination of outcome

variability as a function of selected patient characteristics. Moreover, a

thorough description of study samples in terms of clinically important

and theoretically relevant features would also provide an important means

of facilitating comparison of outcomes across different studies conducted

by different investigators.
150

A small set of potential moderating variables is listed below. First,

however, it is important to note that in evaluating identifying matching

variables, investigators much be cautious about collinearity among

matching variables. Many key prognostic variables may be moderately to

highly correlated among clinical samples of cocaine abusers. For

example, as noted earlier, the data suggested that depression was

associated with differential response to psychotherapy and pharmacotherapy; however, several other variables, particularly gender and race,

were significantly associated with depressive symptomatology. Although

our findings held even when controlling for these variables, it was not

completely clear whether it was the presence of depressive symptoms, or

another related variable, that was responsible for the observed

interactions. Thus, in many cases it will be unclear whether it is the

identified matching variable, or another correlated variable, that was

responsible for the “match.” Therefore, it should be noted that in the

following list some variables may be highly associated with others.

1. Gender. While few studies have found gender effects in treatment

response (McLellan et al. 1994), in most studies conducted to

date, samples of women have been too small to conduct analyses

of gender effects with adequate power. Female cocaine patients

may differ from males on a number of clinically relevant variables

that may be associated to outcome and treatment response

(Griffin et al. 1989), including severity and chronicity of cocaine

use, psychopathology, and social and family support.

2. Race. Some studies have found race to be a prognostic variable

(Grabowski and Higgins 1992) for medication response in cocaine

abusers. However, it is not yet clear to what extent

characteristics associated with race in specific samples (e.g.,

socioeconomic status, source of referral, social supports) may

account for apparent race effects.

3. Education and employment status. Education and employment have

been among the more consistent predictors of treatment

retention and response in the drug abuse treatment literature.

Again, it is not clear whether these variables have a direct effect

on treatment response or a more indirect effect through

relationships with other moderators such as motivation for

treatment, compliance, and so on.

4. Severity of cocaine dependence. Emerging evidence points to

severity as an important prognostic indicator in general (Carroll

et al. 1993b; McLellan et al. 1994), as well as a treatment-
151

matching variable (Carroll et al. 1994a). As there is likely to be

high correla- tions between severity and other prognostic

variables such as socio-pathy, family history, severity of

psychosocial problems, age of onset, and so on, a more

parsimonious strategy for evaluating this set of variables may be

through multidimensional subtyping, a promising strategy

developed in the alcohol field (Babor et al. 1992), which has been

recently shown to generalize to cocaine abusers (Ball et al. 1995).

5. Route of administration. Nunes (this volume) reports data linking

route of administration to antidepressant response, with better

outcome for intranasal users than freebase/crack users. Again,

route of administration may function as a proxy for a number of

indicators, such as severity and chronicity of drug use, SES, and

polysubstance use.

6. Primary drug and treatment setting. Findings based on individuals

whose principal drug dependence diagnosis is cocaine may not

generalize to samples composed of methadone-maintained opiate

addicts who have developed secondary cocaine dependence, and

vice versa, because of large differences in patterns and levels of

psychopathology between opioid and cocaine populations

(Rounsaville et al. 1991), reinforcement contingencies in the two

treatment settings, and so on.

7. Comorbid alcohol and other drug use. Alcohol dependence

frequently co-occurs with cocaine dependence (Regier et al. 1990)

and has been associated with poorer prognosis (Carroll et al.

1993b). Several distinctive features of this subpopulation suggest

specialized treatment strategies may be needed (Carroll et al.

1993c; Higgins et al. 1991).

8. Comorbid psychopathology. As noted earlier, differences in rates of

comorbid disorders across studies are likely to produce differences

in medication effects, particularly for psychotropic agents where

effects may be mediated by the presence of psychopathology. At

a minimum, any study sample should be described in terms of rates

of current and lifetime DSM-IV disorders, particularly affective,

anxiety, and antisocial personality disorder. Global ratings of

psychopathology, such as the psychological section of the

Addiction Severity Index (ASI), should also be included, as should

continuous ratings of specific psychological symptoms, including

depression and anxiety. The recent reports regarding the

significance of sociopathy as a moderating variable for medication
152

response (Arndt et al. 1994) also suggests that categorical (e.g.,

DSM-IV diagnosis) and continuous ratings of sociopathy, such as

the California Psycho-logical Inventory-So (Cooney et al. 1990;

Megargee 1972) should also be included.

9. Motivation and contingencies. An individual’s motivation for

treatment and level of readiness to change may be an important

determinant of treatment compliance and response (Prochaska et

al. 1992). For example, Hall and colleagues (1991) found cocaine

abusers’ commitment to abstinence significantly associated with

the likelihood of relapse. This important dimension has been

infrequently assessed in clinical trials evaluating pharmacologic

treatments for substance use disorders and may be helpful in

identifying those individuals who are not likely to benefit from

treatment in a given trial (Moras 1993). Similarly, the source of

the individuals’ treatment referral and powerful contingencies

associated with some referral sources (e.g., employee assistance

program, court system, child welfare) may play a role in their

motivation for treatment and should be assessed and described.

SUMMARY

The two examples provided in this chapter suggest that the inconsistent

findings across studies evaluating identical pharmacologic agents may be

associated with variations in sample characteristics, particularly those

associated with (a) general treatment responsiveness (e.g., severity of

cocaine use, sociopathy), or (b) responsiveness to specific treatment

strategies (e.g., rates of depression where antidepressant agents are

evaluated). Describing study samples and evaluating treatment response

along multiple dimensions, using a common set of standardized

assessments, would be an important advance in understanding variation in

subjects’ response to medication effects and comparison of findings across

different studies. Moreover, consistent description of study samples

across a number of dimensions would set the stage for meta-analyses of

patient-treatment interactions. Similarly, as new medications are

developed and evaluated, variables that have a theoretical basis as

mediators of treatment response should be identified and evaluated. It

should be noted, however, that success profiling and matching research is

more complex than the search for simple main effects (Finney and Moos

1986; Project MATCH Research Group 1993). In particular, adequate

power to detect patient-treatment interactions requires much larger

sample sizes than those that have to date characterized pharmacotherapy

research for cocaine dependence. This strategy, however, is likely to
153

enhance the development of effective pharmacological interventions for

this very challenging patient population as researchers’ understand the

complex processes associated with treatment seeking, retention, and

outcome among cocaine abusers.

REFERENCES

Arndt, I.O.; Dorozynsky, L.; Woody, G.E.; McLellan, A.T.; and O’Brien,

C.P. Desipramine treatment of cocaine dependence in

methadone maintained patients. Arch Gen Psychiatry

49:888-893, 1992.

Arndt, I.O.; McLellan, A.T.; Dorozynsky, L.; Woody, G.E.; and O’Brien,

C.P. Desipramine treatment for cocaine dependence: Role

of antisocial personality disorder. J Nerv Ment Dis

182:151-156, 1994.

Babor, T.F.; Hoffman, M.; DelBoca, F.K.; Hesselbrock, V.; Meyer, R.E.;

Dolinsky, Z.S.; and Rounsaville; B.J. Types of alcoholics.

I. Evidence for an empirically derived typology based on

indicators of vulnerability and severity. Arch Gen

Psychiatry 49:599-608, 1992.

Ball, J.C., and Ross, A. The Effectiveness of Methadone Maintenance

Treatment. New York: Springer-Verlag, 1991.

Ball, S.A.; Carroll, K.M.; Rounsaville, B.J.; and Babor, T.F. Subtypes of

cocaine abusers: Support for a Type A/Type B distinction.

J Consult Clin Psychol 63:115-124, 1995.

Baron, R.M., and Kenny, D.A. The moderator-mediator variable

distinction in social psychological research: Conceptual,

strategic and statistical considerations. J Pers Soc Psychol

51:1173-1182, 1986.

Beck, A.T., and Beck, R.W. Screening depressed patients in family

practices: A rapid technique. Postgrad Med 52:81-85,

1972.

Carroll, K.M.; Ball, S.A.; and Rounsaville, B.J. A comparison of alternate

systems for diagnosing antisocial personality disorder in

cocaine abusers. J Nerv Ment Dis 181:436-443, 1993a.

Carroll, K.M.; Nich, C.; and Rounsaville, B.J. Differential symptom

reduction in depressed cocaine abusers treated with

psychotherapy and pharmacotherapy. J Nerv Ment Dis

183:251-259, 1995.

Carroll, K.M.; Powers, M.D.; Bryant, K.J.; and Rounsaville, B.J. One-year

follow-up status of treatment-seeking cocaine abusers:

Psychopathology and dependence severity as predictors of

outcome. J Nerv Ment Dis 181:71-79, 1993b.
154

Carroll, K.M.; Rounsaville, B.J.; and Gawin, F.H. A comparative trial of

psychotherapies for ambulatory cocaine abusers: Relapse

prevention and interpersonal psychotherapy. Am J Drug

Alcohol Abuse 17:229-247, 1991a.

Carroll, K.M.; Rounsaville, B.J.; Gordon, L.T.; Nich, C.; Jatlow, P.M.;

Bisighini, R.M.; and Gawin, F.H. Psychotherapy and

pharmaco-therapy for ambulatory cocaine abusers. Arch

Gen Psychiatry 51:177-187, 1994a.

Carroll, K.M.; Rounsaville, B.J.; and Keller, D.S. Relapse prevention

strategies in the treatment of cocaine abuse. Am J Drug

Alcohol Abuse 17:249-265, 1991b.

Carroll, K.M.; Rounsaville, B.J.; and Nich, C. Use of observer and therapist

ratings to monitor delivery of coping skills treatment for

cocaine abusers: Utility of therapist session checklists. In

press.

Carroll, K.M.; Rounsaville, B.J.; Nich, C.; Gordon, L.T.; Wirtz, P.W.; and

Gawin, F.H. One year follow-up of psychotherapy and

pharmacotherapy for cocaine dependence: Delayed

emergence of psychotherapy effects. Arch Gen Psychiatry

51:989-997, 1994b.

Carroll, K.M.; Ziedonis, D.; O’Malley, S.S.; McCance-Katz, E.; Gordon, L.;

and Rounsaville, B.J. Pharmacologic interventions for

abusers of alcohol and cocaine: A pilot study of disulfiram

versus naltrexone. Am J Addict 2:77-79, 1993c.

Cooney, N.L.; Kadden, R.M.; and Litt, M.D. A comparison of methods for

assessing sociopathy in male and female alcoholics. J Stud

Alcohol 51:42-48, 1990.

DiClemente, C.; Carroll, K.M.; Connors, G.; and Kadden, R. Process

assessment in treatment matching research. J Stud

Alcohol [Suppl.] 12:156-162, 1994.

Fawcett, J.; Epstein, P.; Fiester, S.J.; Elkin, I.; and Autry, J.H. Clinical

management-imipramine/placebo administration manual:

NIMH treatment of depression collaborative research

program. Psychopharmacol Bull 23:309-324, 1987.

Finney, J.W., and Moos, R.H. Matching patients with treatments:

Conceptual and methodological issues. J Stud Alcohol

47:122-134, 1986.

Frank, E.; Prien, R.F.; Jarrett, R.B.; and Keller, M.B. Conceptualization

and rationale for consensus definitions of terms in major

depressive disorder. Remission, recovery, relapse, and

recurrence. Arch Gen Psychiatry 48(9):851-855, 1991.

Gawin, F.H., and Kleber, H.D. Cocaine abuse treatment: Open pilot trial

with desipramine and lithium carbonate. Arch Gen

Psychiatry 41:903-909, 1984.
155

Gawin, F.H.; Kleber, H.D.; Byck, R.; Rounsaville, B.J.; Kosten, T.R.;

Jatlow, P.I.; and Morgan, C.B. Desipramine facilitation of

initial cocaine abstinence. Arch Gen Psychiatry 46:117-

121, 1989.

Giannini, A.J.; Malone, D.A.; Giannini, M.C.; Price, W.A.; and Loiselle,

R.H. Treatment of depression in chronic cocaine and

phencyclidine abuse with desipramine. J Clin Pharmacol

26:211-214, 1986.

Grabowski, J., and Higgins, S. (co-chairs). “Relationship of Problem

Severity to Treatment Outcome in Cocaine Dependence.”

Symposium conducted at the 100th Annual Convention of

the American Psychological Association, Washington,

DC, August 17, 1992.

Griffin, M.L.; Weiss, R.D.; Mirin, S.M.; and Lange, U. A comparison of

male and female cocaine abusers. Arch Gen Psychiatry

46:122-126, 1989.

Hall, S.M.; Havassy, B.E.; and Wasserman, D.A. Effects of commitment

to abstinence, positive moods, stress, and coping on

relapse to cocaine use. J Consult Clin Psychol 59:526-

532, 1991.

Higgins, S.T.; Delaney, D.D.; Budney, A.J.; Bickel, W.K.; Hughes, J.R.;

Foerg, F.; and Fenwick, J.W. A behavioral approach to

achieving initial cocaine abstinence. Am J Psychiatry

148:1218-1224, 1991.

Kosten, T.R. Pharmacotherapeutic interventions for cocaine abuse:

Matching patients to treatments. J Nerv Ment Dis

177:379-389, 1989.

Kosten, T.R.; Morgan, C.M.; Falcioni, J.; and Schottenfeld, R.S.

Pharmacotherapy for cocaine abusing methadone

maintained patients using amantidine or desipramine. Arch

Gen Psychiatry 49:894-898, 1992.

Lowinson, J.H.; Marion, I.J.; Joseph, H.; and Dole, V.P. Methadone

maintenance. In: Lowinsohn, J.H.; Ruiz, P.; and Millman,

R.B., eds. Comprehensive Textbook of Substance Abuse.

2d edition. New York: Williams and Wilkins, 1992. pp.

550-561.

McLellan, A.T.; Alterman, A.I.; Metzger, D.S.; Grissom, G.R.; Woody,

G.E.; Luborsky, L.; and O’Brien, C.P. Similarity of

outcome predictors across opiate, cocaine, and alcohol

treatments: Role of treatment services. J Consult Clin

Psychol 62:1141-1158, 1994.

McLellan, A.T.; Arndt, I.O.; Metzger, D.S.; Woody, G.E.; and O’Brien,

C.P. The effects of psychosocial services in substance

abuse treatment. JAMA 269:1953-1959, 1993.
156

Megargee, E.I. The California Psychological Inventory Handbook. San

Francisco: Jossey-Bass, 1972.

Meyer, R.E. How to understand the relationship between psychopathology

and addictive disorders: Another example of the chicken

and the egg. In: Meyer, R.E., ed. Psychopathology and

Addictive Disorders. New York: Guilford, 1986. pp. 3-16.

Moras, K. Substance abuse research: Outcome measurement conundrums.

In: Onken, L.S.; Blaine, J.D.; and Boren, J.J., eds.

Behavioral Treatments for Drug Abuse and Dependence.

National Institute on Drug Abuse Research Monograph

No. 137. DHHS Pub. No. (ADM)93-3684. Washington,

DC: Supt. of Docs., U.S. Govt. Print. Off., 1993.

pp. 217-248.

Prochaska, J.O.; DiClemente, C.C.; and Norcross, J.C. In search of how

people change: Applications to addictive behaviors. Am

Psychologist 47:1102-1114, 1992.

Project MATCH Research Group. Project MATCH: Rationale and

methods for a multisite clinical trial matching alcoholism

patients to treatment. Alcohol Clin Exp Res 17:1130-

1145, 1993.

Regier, D.A.; Farmer, M.E.; Rae, D.S.; Locke, B.Z.; Keith, S.J.; Judd, L.L.;

and Goodwin, F.K. Comorbidity of mental disorders with

alcohol and other drug use. JAMA 264:2511-2518, 1990.

Rounsaville, B.J. Can psychotherapy rescue naltrexone treatment of

opioid addiction? In: Onken, L., and Blaine, J., eds.

Potentiating the Efficacy of Medications: Integrating

Psychosocial Therapies with Pharmacotherapies in the

Treatment of Drug Dependence. National Institute on

Drug Abuse Research Monograph 105. NIH Pub. No.

(ADM)95-3899. Washington, DC: Supt. of Docs., U.S.

Govt. Print. Off., 1995. pp. 37-52.

Rounsaville, B.J.; Anton, S.F.; Carroll, K.M.; Budde, D.; Prusoff, B.A.; and

Gawin, F.I. Psychiatric diagnosis of treatment seeking

cocaine abusers. Arch Gen Psychiatry 48:43-51, 1991.

Rounsaville, B.J.; Tierney, T.; Crits-Christoph, K.; Weissman, M.M.; and

Kleber, H.D. Predictors of outcome in treatment of opiate

addicts: Evidence for the multidimensional nature of

addicts’ problems. Comp Psychiatry 23:462-478, 1982.

Weddington, W.W.; Brown, B.S.; Haertzen, C.A.; Hess, J.M.; Mahaffey,

J.R.; Kolar, A.F.; and Jaffe, J.H. Comparison of

amantadine and desipramine combined with

psychotherapy for treatment of cocaine dependence. Am

J Drug Alcohol Abuse 17:137-152, 1991.
157

Ziedonis D.M., and Kosten T.R. Depression as a prognostic factor for

pharmacological treatment of cocaine dependency.

Psychopharmacol Bull 27:337-343, 1991.

Ziedonis, D.M.; Rayford, B.S.; Bryant, K.J.; and Rounsaville, B.J.

Psychiatric comorbidity in white and African-American

cocaine addicts seeking substance abuse treatment. Hosp

Commun Psychiatry 45:45-49, 1994.

ACKNOWLEDGMENTS

Support was provided by National Institute on Drug Abuse grant nos.

RO1-DA04299, R18-DA06963, and P50-DA09241.

AUTHORS

Kathleen M. Carroll, Ph.D.

Associate Professor

Charla Nich, M.S.

Associate in Research

Bruce J. Rounsaville, M.D.

Professor

Department of Psychiatry

Yale University School of Medicine

Substance Abuse Center/S208

34 Park Street

New Haven, CT 06519
158

Baseline Assessment, Study Entry,

and Stabilization: Double-Blind

Clinical Trials in Drug Dependence

John Grabowski, Gila Arnoni, Ronith Elk, Howard

Rhoades, and Joy Schmitz

INTRODUCTION

The conduct of clinical trials in psychopharmacology, including the

area of drug dependence, has special complexity because the

disorders reflect the interplay of pharmacological, biological,

behavioral, and environmental determinants. Many issues concerning

clinical trials in psychopharma-cology have been addressed by Prien

and Robinson (1994). The study of new medications for the

treatment of drug dependence has presented challenges (Blaine et al.

1994). In the case of cocaine dependence, these have included

difficulty in recruiting uncomplicated patients (i.e., those who do not

have multiple medical, psychiatric, or severe additional drug

dependence problems), and high dropout rates. Many of the

problems are not unique to drug-dependent patients generally, or

cocaine-dependent patients specifically, although they are still

described in these terms (Blaine et al. 1994). Rather, there are

commonalties in problems, research issues, and probably treatment

elements across disorders that are heavily imbued with both behavioral

and biological components. This is particularly true with respect to

issues of “compliance” or adherence to treatment. O’Brien and

McLellan (1996) reported that observed rates of noncompliance with

medication regimens and other features of treatment are equally

common with disorders such as diabetes and heart disease, as they are

in substance abuse. Clearly, differences among habitual behaviors

(Levison et al. 1983), and medical disorders where problems of

compliance are common, cannot be ignored, but the drug-dependent

population is not unique with respect to adherence to treatment

regimens. At least some of the issues can be resolved by precision in

defining the design and mechanics of each clinical research study.

Some clinic-specific efforts have been described previously (Elk et al.

1993).

Conducting definitive scientific studies of medications becomes more

difficult in the face of noncompliance or multiple disorders. Yet
159

many of these difficulties can be confronted and resolved in planning

systems for the conduct of the research (Kartzinel et al. 1994).

Particularly important are the initial contact, intake, and period of

stabilization before study entry. Overeagerness to conduct the clinical

trial may produce simple procedural errors that negate the studies

value. This can result in failure to demonstrate efficacy where it

exists, or perhaps more damaging, produce reports of efficacy in the

absence of actual benefit.

It is assumed at the outset that there is little value in nonblinded trials

lacking placebo controls. Indeed, as Kupfer and colleagues (1994)

have noted, “it can take years to overcome the results of flawed

trials,” and at least some of the research in this field has been devoted

to that task. Thus, this chapter is pro forma and the information

should be familiar. Nonetheless, investigators may benefit from

rethinking standards, biases, preferences, and idiosyncrasies of the

field. The goal is to describe some mechanical steps contributing to

effective baseline assessment and study entry. Precision at this stage is

critical insofar as subsequent measurements hinge on the validity of

initial contact, intake, and stabilization. The procedures and issues

considered here are drawn from experience and problems evident in

the current literature. Strategies described have been used

successfully over the years at the Substance Abuse-Medications

Development Research Center (SARC), at the University of Texas.

Some theoretical and practical issues in clinical trials that might

influence the generalizability of study results are also discussed.

BASELINE ASSESSMENT

Standardization

Underlying the data collection process is the need for standardization

of recruitment, baseline assessment, and stabilization. Standardization

is critical if replicable and generalizable results are to be obtained

from clinical trials evaluating new medications for the treatment of

drug dependence. At the level of mechanics, important factors may

be overlooked by novice and experienced investigators alike.

The SARC Clinic

The SARC Clinic was developed under National Institute on Drug

Abuse (NIDA) demonstration grant DA 06143 as a new research

treatment facility in 1989 and has no nonresearch service component.
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The focus was on new treatments for drug dependence and reduction

in HIV transmission. There existed the opportunity to explore

optimal procedures (Elk et al. 1993), although there is continuing

refinement. A major issue in developing the clinic was to avoid

pitfalls including eliminating or minimizing common deterrents to

patients seeking treatment or deflecting them from research

participation. Many of these problems emerged during the initial

contact and stabilization. There is benefit in detecting misassignments

or other problems early, thereby increasing efficiency of the process.

An important feature in the development of the clinic was that it

should be comfortable and provide readily accessible service to drugdependent patients with little risk. It seemed likely that this would

maximize the baseline level of retention with respect to obvious

resolvable problems. The physical environment is well maintained

and is a standard reasonably appointed outpatient clinical care facility

resembling that of other specialty clinics. A variety of provisions to

assure comfort, safety, and efficiency of service were also established,

while at the same time maximizing collection and accuracy of data for

clinical trials. Those devoted to assuring the safety and comfort of

staff and subjects/patients are listed in table 1 (also see Grabowski et

al. 1993).

The description derives from approximately 25 projects implemented

between 1988 and 1994. These have involved about 1,000 enrolled

patients and many more initial contacts and screens, in studies of

opiate, cocaine, nicotine, benzodiazepines, and other forms of drug

dependence. The studies, which included a range of special

populations as well as “uncomplicated” patient population, included

about 31,000 urine screens, 67,000 doses of medication, and multiple

administrations per patient of Profile of Mood States (POMS),

Addiction Severity Index (ASI), and other instruments to each patient.

Patient Recruitment and Advertising

Advertising is a common means to obtain subjects for clinical trials;

each successive advertisement increases the number of telephone

calls. Although not yet thoroughly documented, there appear to

be differences
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TABLE 1. Examples of fixed clinic-wide contingencies and the

nature of consequences for patients.

 1. Regular attendance for continued treatment +/-

 2. Maintain appointment time for counseling +/-

 3. Maintain appointment time for medication +/-

 4. Complete data and information update forms +/-

 5. Return medication bottles +/-

 6. Provide urine samples for drug screens as scheduled +/-

 7. Arrive and depart in reasonable time (no loitering) -

 8. Maintain clean air (no smoking) -

 9. Contribute to a physically healthy clinic (no weapons) -

10. Support the clinic as the sole vendor (no drug dealing) -

11. Responsiveness to chemistry laboratory findings (no arguing)

NOTE: This table lists issues/behaviors that underlie problems in

some drug dependence treatment clinics. Focus on these issues

often interferes with service delivery. Generic provisions can be

added or eliminated as needed. Positive (+) and negative

(-) consequences must be clearly stated and systematically

applied. The goal is specification of positive consequences

where the absence of that consequence is itself unpleasant.

Items 9 and 10 have attached consequences of warnings and

potential discharge. Some issues such as discussion of

accuracy of laboratory drug screen results have neither

positive nor negative consequences; they are not open for

discussion just as blood pressure readings are medical test

results accepted without discussion.

in the populations as a function of advertising site, even within the

same newspaper (e.g., front news section, sports, entertainment

sections). These differences also prevail as a function of contacts with

emergency rooms, psychiatric facilities, and the extent to which

current patients refer new patients. This affects the rate of acceptable

patients for any particular study.
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Screening

Sites that advertise for subject patients must screen call-in and walk-in

candidates alike. The proportion of acceptable subjects depends in

part on the specificity of the advertisements. Some individuals call

because they have learned from friends, or from other treatment sites,

that treatment research opportunities are available. Since treatment

research sites often pay for initial interviews and other time devoted to

research, it can be expected that some individuals call for the

opportunity to earn money. The number of false-positives invited for

a full-intake screening appointment depends in part on the adequacy

of the prescreening interview whether administered by telephone or in

person (table 2).

Two problematic features emerge in recruitment at this level. One is

that different information accrues to subjects depending on the source

(advertisements, professionals, friends). Second, there is a tendency to

treat potential subjects who walk in differently from those who make

initial contact by telephone. Using the “bird in the hand”

philosophy, an investigator’s eagerness to enroll subjects may lead to

special provisions being made for subjects who are already at the site.

The inherent bias in these differences dictate that all subjects should

have the same initial screening interview, whether by telephone or in

person. Until it can be demonstrated that there are no differences

between the patient who takes the time and trouble to attend the clinic

for initial screening and those who call in, differences should be

assumed.

Each deviation risks additional variability. Following this constant first

contact, the same procedures are applied to patients regardless of source

of entry. There is no difference between subjects in scheduling of

appointment; for example, candidates who call, are referred, or walk in are

scheduled in the first available intake session. No preferential provisions

are used in this regard.

The use of the prescreening form also permits the researcher to obtain

rudimentary data on the characteristics of individuals from the

community who are seeking treatment. This provides additional

information for a cumulative database on the status of treatment research

seekers in the community.

Some special prescreening provisions should exist when there are multiple

investigators with multiple studies at a site. The “big primate” principle

may prevail in assignment, with the most senior investigator
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TABLE 2. Prescreening (telephone or walk-in) questionnaire.

A. Introduction

1. Treatment Research Clinic, this is (your name). May I help

you? Determine why individual is calling. If not immediately

obvious from response, ask:

—Are you calling about an advertisement? (If so, which

ad?)

—Are you calling about receiving treatment? (If so, what

program?)

2. Preamble

We have several different research programs available to

provide different treatment for different drug or medicationrelated problems.

I must ask you some questions to learn if you qualify for these

and to decide which one might be best for you.

Before I do, I want you to know that all of the information you

give me will be strictly confidential.

I will not ask for your name or telephone until we complete the

interview so that you can feel free to answer without any

problems if you decide not to continue. If you decide to make

an appointment, I get the necessary information. I will now

ask the questions—may I start?

B. Determination of Study Type

1. For what type of drug or medication-related problem are you

seeking treatment? (circle 1): None, Cocaine, Opiates, Antianxiety medications, nicotine, other______________

If cocaine:

a. Are you currently having a problem with depression?

(Elaborate) YesNo

b. If yes: Do you think your depression is only a result of your

cocaine use or does it seem to be a separate problem? If

response = separate, refer to Cocaine+Depression Project.

2. Circle: Male Female

3. If female: Are you pregnant? YesNo

(Use flowsheet to determine procedure for pregnancy study.)
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TABLE 2. Prescreening (telephone or walk-in) questionnaire

(continued).

4. Have you have a positive TB skin test? Yes No

a. If yes: Have you had treatment for it? Yes No

b. If yes: How long was the treatment? ________

C. Standard Questions (all studies)

1. How did you hear about us?

_____________________________

2. How long have you been using this drug?

___________________

3. Have you had any therapy for your drug use in the past 6

months? _____________

4. What is your ethnic background? a. Caucasian, b. Black, c.

Hispanic, d. Asian, e. Other

5. How old are you? _______________

6. What is your Zip code? ___________

D. GO TO APPROPRIATE STUDY-SPECIFIC QUESTIONNAIRE.

NOTE: All potential subjects are queried with the above form. If

they qualify at this level, the next set of questions concerns a

specific study that is appropriate for the presenting condition.

The entire prescreening process takes about 15 minutes. An

appointment is made for an intake interview scheduled within 24-

48 hours.

having first access to subjects for his or her studies, and this may be a

source of bias. A site should have a systematic means to rotate

through candidates if multiple studies with similar criteria are

ongoing. The screening procedure for inclusion and exclusion then

becomes stepped, as follows.

1. Summary demographic information and statement of problem.
165

2. Designation for screening for a particular study or rotation for a

class of studies.

3. Screening to determine appropriateness before making intake

appointment.

4. Return to the general screening pool if the potential subject is

found to be ineligible for the study for which he/she was first

screened.

The extent to which preferential recruitment for one or another study

introduces bias is unknown. However, it is intuitively sound to avoid

the possibility of assignment bias whenever possible.

INTAKE

The intake procedures in all studies should be pedestrian but rigorous,

systematic, and unbiased, protective of subjects rights, and informative

of subjects’ responsibilities. Failure in this domain can produce high

dropout rates and produce results that cannot be replicated.

Consent Procedures

Sites differ in the characteristics of the consent procedures since

variation within the broad National Institutes of Health (NIH)

guidelines is permissible under the arrangement of local Initial Review

Boards (IRBs). Requirements vary for style and other features of

advertisements, consent forms, and supplementary information,

despite the common required elements of consent procedures. The

likelihood of this having an effect on recruitment, screening, and

intake procedures is unknown.

Variation in initial intake may occur at a site due to differences across

intake personnel and most certainly occur across sites. Sources of

within-site differences may be due to different approaches to

candidates based on biases involving perceived differences among

patients. Thus, potential subjects may receive more or less

information depending on unspecified ad libitum criteria imposed by

the intake staff members (e.g., perceptions of intelligence, affluence,

etc.). Thorough, well-documented consent forms, intake procedures,

regular training and retraining, and relatively inflexible interviewing

guidelines should minimize these problems. Further, monitoring for

consistency within and across staff members should occur. This can

be accomplished through regular audiotaping of consent, intake, and
166

other sessions. Regular meetings of intake and diagnostic staff

members may help preclude drift in adherence to the criteria applied

during the course of a study.

Since local IRB criteria may produce differences in length or other

characteristics of consent forms, greater consistency can be achieved

by having supplemental descriptive material, though this too must be

submitted to the IRB. The material may be a useful additional guide

to a patient after he or she has departed the premises. It should

include information about fixed appointment days, times, and detail

regarding provisions for continued participation as well as

reimbursement. Here, as in other procedures, the goal is to reduce

unnecessary variability in the experiences of subjects/patients entering

a study.

When the agreement to participate has been obtained, the evaluative

intake process is another source in which variability may arise.

Consistency of measurement and application of diagnostic criteria is

essential.

Diagnoses

Specific instruments used in diagnoses have been discussed at length

elsewhere in other volumes in the NIDA Research Monograph Series.

However, two points should be made. First, recall that many

instruments were standardized on populations that may be rather

different from the drug-dependent population. Further, some, such as

the ASI, were developed using populations that may or may not be

representative of the broader treatment-seeking population. Second,

from the point of view of research and data analysis there should be

an effort to minimize the number of instruments. This quest resides

in the simple problem that increasing the number of measures and

items increases the opportunity for statistically significant but spurious

and clinically irrelevant findings. Assuming that appropriate

instruments are being used, the critical issue is that inclusion or

exclusion relies on the standardized criteria. The authors’ intake

procedures included:

A. Prescreening for general acceptability for study as

described above.

B. Intake screen.
167

1. Complete medical evaluation including HIV, TB, EKG,

drug screens, and other standard tests.

2. Complete psychiatric/behavioral evaluation including

SCID, ASI, POMS, Hamilton A/D, and detailed drug

history.

3. HIV testing/counseling-HIV risk behaviors.

4. Self-report instruments: POMS, Beck, desire to use drugs

(craving).

If at any point during the intake process a potential subject is to be

excluded from his or her assignment, there are two possible outcomes.

First, the individual may be appropriate for evaluation for another

ongoing study. At this point the intake continues, including any special

items appropriate to the new assignment. If the subject cannot be

included in any of the available studies, he or she has the opportunity to

meet with a therapist to arrange for referral to other treatment sites.

A special problem emerges in the domain of substance use disorders.

Oddly, because of the imprecise use of language, implementation of

studies sometimes falls victim to words such as “abuse” when

“dependence” is intended, and vice versa. Precision in terms of daily

discussion among staff members should be encouraged since it reduces

confusion and contributes to the integrity of the subject intake and

baseline assessment procedures. Beyond this there is the lay vernacular,

which permeates the field. In its 1994 publication guidelines, NIDA

explicitly noted that terms with pejorative baggage, such as “addict,”

should be avoided, and this applies as well to the extant clinic and staff

meeting vocabularies. There are no parallels evident in other domains of

medicine or psychology, yet the problem of applying nontechnical terms

to drug-dependent patients is common in the professional community.

Care in language may also contribute to better educating the subject about

the disorder and thus real benefit can accrue to the patient as a research

subject. Prior to each study, all intake staff members and clinicians as a

group must review the conditions and criteria for entry again with a view

to assuring that there is familiarity with the study-specific procedures (i.e.,

that they are implementing the same study).

Further, the authors have found it useful to be exclusive in screening with

respect to diagnosis, preferring to err on the side of not including subjects

for whom the diagnosis is less clear. Inclusion of dual-diagnosis patients

can occur and have obvious undesirable consequences in a study intended

to focus on one disorder, e.g., cocaine dependence. An extremely
168

heterogeneous patient population with a variety of secondary disorders,

e.g., depression, antisocial personality disorder, and no ability or intent to

stratify, may produce substantial variability. Clearly, this may be

particularly problematic in an early efficacy trial, though it may be more

acceptable in effectiveness studies, which typically account for this using a

variety of procedures including larger sample sizes. As a matter of

comparison to other areas, inclusion criteria in studies of antihypertensive

medications, dermatological preparations, or other medications for

medical conditions, tend to be characterized by considerably less

variability for confounding conditions than is often found in studies of

medications for drug dependence. Though it is often argued that users of

single substances are rare, the authors have found persistence in

recruitment can result in an adequate sample of subjects meeting the

specified requirements and intent of the study without compromising the

inclusion/exclusion criteria.

Heterogeneity of patient populations and differences across sites may

have contributed to the equivocal results reported in the literature for

some medications for drug dependence. For example, some studies

reported modest or great improvement and still others report no change

with desipramine (Arndt et al. 1992; Gawin and Kleber 1984; Gawin et al.

1989). Similar uncertainty has arisen in the case of fluoxetine (Batki et

al. 1993; Grabowski et al. 1995). Characteristically excluding patients

who have additional diagnoses (depression, antisocial personality

disorder) or secondary conditions (AIDS) other than the specific drug

dependence of interest may contribute to definitive findings in both

efficacy and effectiveness trials (Grabowski et al. 1995). Arguably, costs

are increased at the front end of a study due additional screening to

achieve the desired sample. Nonetheless, it appears worthwhile to reduce

variability to permit focus on the key issue; i.e., does medication X, under

setting conditions A and B, and behavior therapy conditions C and D,

produce benefit, no effect, or harm. Unambiguous criteria must be

determined and applied during the initial screening, intake, and

stabilization phases, and continuity must be sustained, often over a period

of many months or several years.

Urine Drug Screens

Drug screens provide a critical element in defining the characteristics of

the patient population at entry and during stabilization. Clinical and

research staff must emphasize the importance of these data and the need

for care in collection, transport, testing, and reporting (Hawks and Chiang

1987). Having a professionally constituted analytical chemistry

laboratory on site provides greater assurance of reliability. Equally
169

important for behaviorally based studies is that an onsite facility provides

for immediate results when called for by contingency management

procedures. Not all sites can afford or require this level of participation

by chemists and other technical personnel on site. Offsite laboratories

providing slower turnaround times may be satisfactory during ongoing

standard medication clinical trials. However, this necessarily slows the

process of study entry, while awaiting the results of intake and

stabilization drug screens. Slowing the intake process may in turn lead to

failure of patients to return and slow overall study progress.

There is ongoing discussion of the type of screen required: qualitative,

semiquantitative, or quantitative. In standard clinical trials

semiquantitative urine screens should be sufficient and even qualitative

results may suffice. Arguments for quantitative screens have emerged, but

the supporting data for this position are not entirely persuasive. One

concern is that qualitative or even semiquantitative screens must be

interpreted in terms of cutoffs (e.g., 350 ng/mL). This was an arbitrary

determination originally standardized for workplace screening where no

use was acceptable and a minimal allowance for error was permitted. It is

argued that a medication may reduce the level of dependence or abuse,

but that this may go undetected unless quantitative screens are used. It

could be argued that an effective medication (such as paralleling methadone in efficacy), would produce group reductions from 100 percent

positive to 10 to 20 percent positive screens even by this stringent criteria.

An alternative position is that a higher cutoff point could be used that

would itself indicate relatively low levels of drug use. For example, since

cocaine-dependent or -abusing patients often have benzoylecognine levels

between 100,000 and 1 million ng/mL, a cutoff of 5,000 to 10,000 ng/mL

would reflect significant change for most groups of patients.

The perspectives represented in the ongoing debate reflect conceptual as

well as practical shifts in thought. There is increasing recognition that

both risk reduction and risk elimination are important, with the former

being satisfactory when the latter cannot be achieved. Whether strict

elimination or risk reduction views are held, definitive and consistent

criteria and effective procedures must be established and maintained at

intake and stabilization as well as throughout the study. Drift in

procedures can occur over the course of clinical trials that may take

several years to complete. Permitting consistent comparison of data over

time and within and across subjects must be avoided.

Other problems emerge with respect to medication-taking behavior and

drug screens. To accommodate this, it may be useful and cost effective to

differentiate phases of evaluation with respect to the comprehensiveness of

screens. Given a relatively high level of tricyclic antidepressant use in the
170

community of cocaine-dependent patients (approximately 8 percent) the

authors screened for both drugs of abuse and a full range of therapeutic

medications in the initial screens. Reviewing this process, it was

determined that an acceptable level of safety and rigor can be achieved by

conducting comprehensive semiquantitative drug screens for common

psychiatric medications at intake and monthly thereafter, while the twiceweekly (or more frequent) screens during study are restricted to

commonly abused drugs.

In discussing the quantitative-qualitative issue, it may be necessary in early

trials or certain types of combined medication behavioral therapy trials to

obtain quantitative screens. However, semiquantitative screens should be

adequate. The adequacy of this approach is testable. The authors’

approach is that in a new series of studies quantitative screens are

conducted for all drugs on all patients, and then varying cutoffs and

criteria and results with respect to clinical utility are compared and

applied. Future screening procedures will depend on the outcome of this

comparison. Periodic blood screens may be useful for determining

medication levels. At the same time, several studies in the literature,

including the authors’ work with fluoxetine, suggest little relationship

between clinical effect and blood levels of commonly examined

therapeutic medications. Clearly, when examining new medications, this

issue must be evaluated.

Medical Evaluation

The medical evaluation while standard requires special attention to

preclude unnecessary exclusion of potential subjects. Patients should

generally be in good health except for problems directly related to drug

use. Problems at intake may include results indicating aberrant EKG or

liver dysfunction, placing a patient in a position of being borderline

acceptable for a study. However, if the patient is otherwise acceptable,

monitoring during the stabilization period will either mitigate concerns as

symptoms abate or lead to exclusion. Dubious results that indicate greater

than average risk as specified by the IRB human subjects provision

require special attention. Thus, it may be necessary for a specialist, e.g., a

cardiologist, to review a record before the patient may actually receive the

study medication. Unlike many of the compliance issues, this matter is of

greater concern with drug-dependent patients since they may take

additional drugs while receiving the therapeutic agent. Even with an

effective medication it can be expected that this will be particularly likely

early in treatment, thereby increasing risk and potential harm. It is during

baseline assessment that these issues must be addressed. Thus, in the

authors’ studies of stimulant replacement, EKGs were conducted three
171

times weekly in the first 2 weeks and once weekly thereafter. Sites

unprepared, or unable to provide this level of evaluation, should be still

more cautious in these initial evaluations.

Behavioral and Social Evaluation

Behavioral and social status/function evaluations are typically viewed as

essential during the course of the baseline assessment. Data pertaining to

these domains can be derived from standard diagnostic instruments,

notably the ASI and SCID interviews. There appears to be increasing

evidence that most demographic measures (e.g., race, income) have little

relevance in examination of correlations with treatment outcome. Rather,

factors proximate to drug use (e.g., drug, dose, severity, route), as well as

comorbid psychiatric conditions may be most important. Certainly, a

comprehensive drug history, particularly with respect to recent patterns of

use, can be important and can be linked to the drug screen data. Further,

the behavioral features of drug taking serve as the best dependent and

independent variables. Of less clear value are measures such as dollars

spent, grams used, and so on, unless they can be documented and

validated against status of drug supplies in the community, (e.g., through

the DEA). Drug prices and quality vary tremendously from time to time

and across sources at the same time, thus diminishing even the face

validity of such measures. While often reported, the generalizability or

utility of such surrogate measures of drug use has yet to be demonstrated.

Useful data can be collected using queries focusing on patterns and

circumstances of drug use. The Drug Use Desire Inventory, which relies

extensively on operational definitions of behaviors thought to reflect

craving, is used in the SARC Clinic. The principal problem with such

measures is establishing definitive linkage to actual drug use. Particularly

problematic, though conceptually interesting, is the not uncommon result

of divergence of drug taking and self-report measures of desire to use as

has been reported by Fischman and colleagues (1990), with desipramine.

Summary

The process of assuring quality and consistency in these phases of

research is iterative and developmental; each member of the group

contributes to inservice training on components of the process.

Effectively, a checklist is developed assuring that all components are in

place and agreed to before studies commence. The screening and intake

process should be viewed as mechanical, with little room for error,

producing data on which success of the results hinge. Each individual

involved in the process can inadvertently tinker and contribute variability.
172

Many baseline assessment data can be directly entered into a

computerized database, while others must be entered by hand at the

earliest possible time. All files, papers, and computers should be sampled

for accuracy. Further, all files must be retained to permit retrospective

checks as needed. The authors have developed a computerized network

system with terminals at the pharmacy medication-dispensing window, in

intake interview offices, with research assistants, and in data coordinators’

offices, to provide for regular patient checks and data entry. Messages to

patients flow easily between clients and staff they have contact with to

assure intake elements are completed and medicating sequences are

initiated. Making a brief summary of the intake procedures produces an

interactive process that permits improvements and minimizes errors.

Beyond this a clinic operations manual should be available for all new

staff members and should be reviewed periodically by all staff members

to keep the manual procedures current.

STABILIZATION AND STUDY ENTRY

2 Weeks of Stabilization

Patients accepted for studies undergo a stabilization period prior to study

entry. The scientific and practical advantages and disadvantages are

discussed below.

As outlined earlier, there is concerted effort to assure that all patients

receive the same information, agree to the same requirements of

participation, and receive similar treatment at entry. Beyond this, however,

there is a need to verify that the initial determinations are accurate.

Acutely, it is to the investigator’s disadvantage to need to reexamine since

it is costly and may result in discharge of subjects; in the longer term it

assures the validity of the sample and the results of costly and timeconsuming clinical trials.

Evaluations During Stabilization

Patients should be monitored closely for a period of 10 to 14 days after

intake. Study requirements and complexity of expected problems may

result in clinic attendance from 2 to 7 days per week. Drug use may

likewise be monitored through two to seven scheduled urine screens per

week. Immediate return of urine screen results (within an hour) may be

necessary in some cases, but return by the next visit is essential.

Medication doses should be increased systematically during this period

and the consequences of dosing observed; this will vary across
173

medications. For fluoxetine, ritanserin, risperidone, and methylphenidate

studies, the authors considered it appropriate to obtain additional EKGs,

while in methadone studies this requirement was not included.

Patients must be monitored to determine whether conditions apparent at

entry such as depression wane during this period, and to determine

whether previously unobserved symptoms emerge. It has been noted in

the literature (e.g., Blaine et al. 1994; Kadden et al. 1995) that psychiatric

diagnoses should be reassessed to determine whether an observed

condition was stable or an artifact immediately preceding drug use.

Ostensible coexisting depression is commonly noted in individuals who

have recently ceased using cocaine, but in 60 percent or more of the cases,

reevaluation demonstrates that the dual diagnosis disappears within 2

weeks. While demographic factors seem to have little bearing on

outcome, comorbid psychiatric conditions or their absence does seem to

be important with respect to treatment outcome, and thus with respect to

the conduct and results of the clinical trial.

Finally, a fixed series of general queries should be posed at each session

during this period concerning changes in legal status, living conditions,

and social status in terms of significant others. These can warn of

potential problems, assure that the patient continues to meet study criteria,

and can also be checked against intake data derived from measures such

as the ASI. Assuring that the subject clearly understands the requirements

of the study can be accomplished by through repetition during the

stabilization period through formal and informal means. It may be

necessary to revisit consent procedures if it becomes apparent that the

patient was not intact during the initial study introduction (Grabowski et

al. 1979).

Therapists, research assistants, nurses, and any other staff members having

contact with subjects can establish the framework for patients’

participation during the stabilization period, making certain that fixed

appointment conditions are met, that urine screens are delivered, and that

materials are completed. Patients can be given a printed description that

includes their regularly scheduled appointment time, other scheduled

events such as urine screens, and delineation of items for which they

receive research payments. These efforts promote a baseline level of

compliance on which medications and behavioral therapy combinations

can be evaluated. These constructive procedures are standard of care in

some clinical settings but are rarely used in drug dependence research,

where compliance is essential to rigorous evaluation.

Other Factors Confounding Assessment and Treatment Studies
174

Disregarding a long list of minor factors that may confound baseline

assessment specifically and treatment research projects generally, there

remain examples of major issues that may dramatically affect results. An

illustrative example is provided here that is typically ignored, accepted

with resignation, or encouraged and defended by many in the field of

drug dependence. This is the issue of patient/subject attendance of selfhelp groups in the community and outside the control and purview of the

study.

The baseline assessment is an important opportunity to determine whether

other factors may confound the basic study of medication (or behavioral)

therapy efficacy. The problem with self-help groups is clear. When

evaluating a medication for hypertension, diet modification, exercise

behavior, or seeking other treatments during the course of the study

would be discouraged. Thus, researchers are particularly attentive to the

issue of alternative ongoing therapies of any form for several reasons.

Baseline data collection will be distorted in unknown ways by these

activities. Beyond this, encouraging or not dissuading patients from

extracurricular treatment activities assures a source of confound of

unknown dimensions. During the stabilization period, researchers

consistently emphasize the importance of adherence to the current

therapeutic program. It is clear that the other activities may or may not be

helpful but that the subject has agreed to participate in a specified

treatment regimen for a defined period. In brief, researchers are

committed to providing a particular range of treatment and committed to

complying with this regimen. A variety of strategies are used.

Remarkably, investigators conducting evaluations of medications for drug

dependence both fail to discourage and may encourage attendance at selfhelp groups. Arguably, patients can seek to deceive the investigator. The

authors view the effort at educating and obtaining compliance on this

issue critical. Other sites prefer to account for this in other ways but only

infrequently report the data. This single factor may contribute

substantially to some problems observed in the literature. So-called selfhelp groups can have positive or negative effects and vary widely in focus,

format, and extent to which they alter behavior. Often the message

conveyed therein is directly contradictory to some cognitive behavioral

strategies. The authors feel strongly that there is a need to assure that the

treatment being evaluated is to the extent possible is the one being

delivered at the study site. Again, by analogy, if patients in the

hypertension study or a psychotherapy study were receiving prescription

medications elsewhere or were self-medicating with active OTC

medications, it would be cause for exclusion. The same should apply to

supplemental doses of self-help groups. Other sources of variability are

much more widely recognized and accounted for and will not be
175

addressed here. The example of self- help groups is emblematic of some

of the problematic issues that confront the field and must be considered in

the baseline assessment phase.

Another problem is that of accepting intent to treat as an essential

criterion. At the extreme, it proposes that every subject who enters the

clinic and signs a consent form must be included in subsequent analyses

since there was a so-called intent to treat. The question is: Intent to treat

what? Should misdiagnosed individuals be included? For example, in a

study of depression+cocaine dependence should subjects be included

whose depression lifts after several days? Or should patients who do not

tolerate a dose of a widely used medication be considered as failures?

The liabilities of this strategy are considerable. An obvious potential

problem will come from rejecting medication or behavioral therapies that

are effective.

Other problems common to the study of drug dependence treatment

research, baseline evaluations, and design result from common myths or

untested assumptions that are woven into the fabric of clinical trials. The

problem of self-help groups has been mentioned; the view that patients

must hit bottom is sacrosanct only in drug dependence and would be

anathema in any other domain of medicine; the views regarding optimal

setting conditions (e.g., inpatient, long duration therapy); that drug

dependence is not fundamentally a real biological/psychological disorder:

all contribute to confounds in efforts to develop optimal treatments.

While there is an increasing body of literature contesting these beliefs,

they present continuing challenges in the objective study of substance use

disorders. These are apparent problems to the extent that these views

permeate the views of staff members conducting the intake process.

Study Entry

The subject who completes the 2-week stabilization period with a stable

diagnosis, with all other medical and psychiatric criteria met, and

accepting all other conditions of study inclusion enters study and is not

replaced. The importance of this continuing assessment period is

exemplified in studies whether fixed or variable dosing prevails. The

issue is particularly important in the former case such as the authors’

fluoxetine study involving a placebo, 20 mg, and 40 mg of medication

(Grabowski et al. 1995). If subjects were considered entered to a study

before it is was determined that they can tolerate the assigned dose,

differential dropout may skew the results. The same problem applies to

other factors as well. For example, patients may state that they can attend

a clinic 2 or 5 days per week but differential attrition may prevail for
176

working patients assigned to the condition, requiring more frequent visits.

Again the results will be skewed. Many patients enter a study with liver

function values that are borderline; the stabilization period permits

determination of whether the values are stable, improving, or deteriorating

(thus making the subject unacceptable for inclusion). In sum, the

stabilization period permits evaluation of the practicability of study

conditions for a particular patient while also providing for monitoring of

the validity of the initial intake assessment.

When the subject is considered an active study participant a standard

metric is applied to continued participation. The subject must sustain a

level of 75 percent of his or her study commitments (e.g., urine screens,

self-report form sessions, medication visits, therapy appointments). The

actual percentage is arbitrary and should be established for the study and

be somewhat flexible. In practice, the main function of this criterion is to

provide a definitive endpoint for patients who drop out.

Problems

There are obvious problems with the stabilization strategy. For example,

in the normal course of events, many subjects/patients leave treatment

shortly after entry or within the first 2 weeks. Thus, apparent retention

may be inflated if patients are not considered subjects until they have

stabilized. This can be accommodated in the data-analytic process and

description where the progression of attrition should be noted. For

example, the number of individuals who underwent initial prescreening

can be specified: those who entered intake but dropped out or were

excluded and those who dropped out during stabilization. Data should be

maintained for all patients and examined for differences among and

between individuals who departed during stabilization and those who

remained to become active subjects. Again, in a large study of fluoxetine,

this procedure was found to be effective and there were no significant

differences on the measures used between patients who departed during

stabilization and those who were retained. Another obvious problem

resides in added cost; however, it should be apparent that careful

screening, albeit costly, is ultimately one of the most cost-effective

features of the study process.

Summary

Despite the seeming complexity of the procedures described, they have

proven generally acceptable in the authors’ studies. Much of the

mechanical character of the process is transparent to the patient. Precision

is requisite for the difficult area of study comprised of clinical trials to
177

determine the efficacy of medications for drug dependence. There are

considerations in medications development clinical trials that are

overlooked. These include reevaluation postentry; prestudy to permit

replicable comparison throughout the study, and finally assuring that the

treatment being evaluated is the only one that the patient is receiving.

In the fluoxetine trial used as an example to this point, approximately 500

patients called (or walked in) and were thus screened using the telephone

screening form. Most screened out at this level were polydrug users or

had legal charges pending that might have interfered with participation.

About 228 went through the intake procedure. Ultimately, 156 were

completed stabilization and were formally considered having started

study. The stringent requirements described to this point were applied.

The end result was an uncompromised double-blind trial (Grabowski et al.

1995). Randomization has been successful in all of the authors’ studies

to date using these procedures. It is possible that consis-tently similar

results could be obtained with less rigorous procedures; however, less

rigorous or inconsistent intake procedures may well contribute to

equivocal results in the literature.

OPTIMAL DESIGNS

Comment on design issues is warranted here at two levels, in addition to

those by Nunes (this volume). First, it appears that despite flaws, the

stabilization period as a formal study component is essential in this

population, at the current level of understanding of the conduct of

medications development trials. As noted earlier, this is particularly

important to assure that all patients identified as such received the full

dose. This was and is critical to evaluation of clinical efficacy and

effectiveness.

Beyond this, it is suggested that variations in experimental designs should

enhance detection of benefit, lack of change, or harm in medication trials.

Medication trials for drug dependence are confronted with the issue of

complexity of the disorder. Elaborate behavioral treatments as a baseline

could conceivably obliterate differences between groups attributable to

medications. Yet it is recognized that joint actions between behavioral

therapies and medication may enhance effectiveness. These can be

approached as two distinct types of studies. They may at times be

examined concurrently, in the following manner: An extended (e.g., 6-

week) double- blind baseline period with placebo and medication using

standard care (e.g., one therapy session per week) could provide a

rigorous test of the medication. Substantive reinforcers could be provided

for retention but not contingent on reductions in drug use. If an effect is
178

observed under the austere standard condition, the medication might be

viewed as an important candidate for further examination. During such a

period, a medication such as methadone would readily be determined to

reduce opiate use. If no difference was observed during this period, the

medication might be sacrificed as a candidate. If pronounced or even

modest differences are observed, application of intensive behavioral

interventions could be applied to half of the initial remaining subjects in

each group. This would permit evaluation of the extent to which a

behavior therapy medication interaction produces further change.

Disproportions in group size could emerge in the second phase of this

design if the medication was effective. However, this design or some other

hybrid could greatly reduce the cost, time, and steps involved in initial

trials of efficacy and effectiveness.

OPTIMAL DATA-ANALYTIC STRATEGIES

The authors are currently examining optimal data-analytic strategies

permitting capture of the best possible baseline assessment data for

comparison to later progress through the study. New analytic tools are

being evaluated for consideration of dropouts, missing data, and other

hazards of this research. By maintaining records at each stage of the

process—from initial screening onward—comparisons are feasible.

Considerable concern has emerged regarding the adequacy of commonly

used measures. Psychometrics must be impeccable for obvious reasons

but problems do emerge. For example, the authors have found that factor

analytic strategies with the POMS may create problems in this field since

the factors wash out on careful scrutiny. This may be due to the

population on which it was standardized and the comparisons that are

being made. In one analysis, using education as a surrogate variable for

reading ability, the authors found that the factors can be isolated for those

who have a 12th-grade reading level or higher, but not if less education

than 12th grade. This suggests that there may be further problems with

other measures adapted from other psychiatric populations. Thus, these

measures may be inappropriate to detect the changes at a later time.

Beyond this, the utility of using many surrogate measures and attempting

to identify predictors must be considered. As previously noted certain

key variables such as severity appear to be important while many demographic variables are of limited or no value. At this point, the field would

do well to focus on the main task of developing effective treatments for

the substance use disorder. While there is rarely such correlation seeking

in other areas of medicine, it does emerge in other areas of psychological

disorders such as panic and phobias. In these fields there have been calls
179

for a return to the focus on the core disorder, and the advice would seem

to apply to substance use disorders as well.

SUMMARY AND CONCLUSIONS

To summarize, perhaps most important, but most difficult to achieve will

be commonalties and standardization across trials so that rigorous

comparison is possible. Researchers will do well to examine clinical trials

in other areas, mimicking those elements that are compatible, avoiding

those that are not, and above all, avoiding costly reinvention.

REFERENCES

Arndt, I.O.; Dorozynsky, L.; Woody, E.; McLellan, A.T.; and O’Brien, C.P.

Desipramine treatment of cocaine dependence in

methadone maintained patients. Arch Gen Psychiatry

49:888-893, 1992.

Batki, S.L.; Manfredi, L.B.; Jacob, P.; and Jones, R.T. Fluoxetine for

cocaine dependence in methadone maintenance:

Quantitative plasma and urine cocaine/benzoylecognine

concentrations. J Clin Psychopharmacol 13:243-250,

1993.

Blaine, J.; Ling, W.; Kosten, T.R.; O’Brien, C.P.; and Chiarello, R.

Establishing the efficacy and safety of medications for the

treatment of drug dependence and abuse: Methodologic

issues. In: Prien, R., and Robinson, D., eds. Clinical

Evaluation of Psychotropic Drugs: Principles and

Guidelines. New York: Raven Press, 1994.

Elk, R.; Grabowski, J.; Rhoades, H.; and McLellan, A.T. A substance abuse

research-treatment clinic. Subst Abuse Treat 10:459-471,

1993.

Fischman, M.W.; Foltin, R.W.; Nestadt, G.; and Pearlson, G.D. Effects of

desipramine maintenance on cocaine self-administration

by humans. J Pharmacol Exp Ther 253:760-770, 1990.

Gawin, F.H., and Kleber, H.D. Cocaine abuse treatment-open pilot trial with

desipramine and lithium carbonate. Arch Gen Psychiatry

41:903-909, 1984.

Gawin, F.H.; Kleber, H.D.; Byck, R.; Rounsaville, B.J.; Kosten, T.R.; Jatlow,

P.I.; and Morgan, C. Desipramine facilitation of initial

cocaine abstinence. Arch Gen Psychiatry 46:117-121,

1989.

Grabowski, J.; Rhoades, H.; Elk, R.; Schmitz, J.; and Creson, D. Clinic-wide

and individualized behavioral interventions in drug

dependence treatment. In: Onken, L.; Blaine, J.; and
180

Boren, J., eds. Behavioral Treatments for Drug Abuse and

Dependence. National Institute on Drug Abuse Research

Monograph 137. NIH Pub. No. 93-3684. Washington,

DC: Supt. of Docs., U.S. Govt. Print. Off., 1993.

pp. 37-72.

Grabowski, J.; Rhoades, H.; Elk, R.; Schmitz, J.M.; Davis, C.; Creson, D.;

and Kirby, K. Fluoxetine is ineffective for treatment of

cocaine dependence or concurrent opiate and cocaine

dependence: Two placebo-controlled, double-blind trials.

J Clin Psychopharmacol 15:163-174, 1995.

Grabowski, J.; O’Brien, C.P.; Greenstein, R.; Long, M.; Steinberg-Donato,

S.; and Ternes, J. Effects of contingent payment on a

naltrexone regimen. Am J Drug Alcohol Abuse 6:355-365,

1979.

Hawks, R., and Chiang, C.N., eds. Urine Testing for Drugs of Abuse.

National Institute on Drug Abuse Research Monograph

73. DHHS Pub. No. (ADM)87-1481. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1987.

Kadden, R.M.; Kranzier, H.R.; and Rounsaville, B.J. Validity of distinction

between substance induced and independent depression

and anxiety disorders. Am J Addict 4:107-117, 1995.

Kartzinel, R.; Lisook, R.; Rullo, B.; Severe, J.; and Spilker, B. Clinical trial

implementation. In: Prien, R., and Robinson, D., eds.

Clinical Evaluation of Psychotropic Drugs: Principles and

Guidelines. New York: Raven Press, 1994. pp. 161-184.

Kupfer, D.; Kraemer, H.; and Bartko, J. Documenting and reporting the

study results of a randomized clinical trial (spicy meatballs

not pabulum). In: Prien, R., and Robinson, D., eds.

Clinical Evaluation of Psychotropic Drugs: Principles and

Guidelines. New York: Raven Press, 1994. pp. 237-260.

Levison, P.; Gerstein, D.; and Maloff, D. Commonalities in Substance

Abuse and Habitual Behavior. Lexington, MA: Lexington

Books, 1983.

O’Brien, C.P., and McLellan, A.T. Myths about the treatment of addiction.

Lancet 347:237-240, 1996.

Prien, R., and Robinson, D., eds. Clinical Evaluation of Psychotropic

Drugs: Principles and Guidelines. New York: Raven Press,

1994.
181

AUTHOR

John Grabowski, Ph.D.

Director, Substance Abuse Research Center

Professor, Psychiatry and Behavioral Sciences

Department of Psychiatry

University of Texas

1300 Moursund Street

Houston, TX 77030
182

The Addiction Severity Index in

Clinical Efficacy Trials of

Medications for Cocaine

Dependence

John S. Cacciola, Arthur I. Alterman, Charles P.

O’Brien, and A. Thomas McLellan

INTRODUCTION

The Addiction Severity Index (ASI) is a semistructured clinical or

research interview (McLellan et al. 1980, 1985, 1992b). It was

developed more than 15 years ago to fill the need for a standardized,

reliable, and valid instrument with which to evaluate substance-abusing

patients. More specifically, it was created to enable clinical

researchers to evaluate the treatment outcome of drug and alcohol

patients. Since that time, it has been widely used and has become a

standard. The ASI is used internationally and has been translated into

numerous languages. Nationally, a number of States, counties, and

cities, in programs that they fund, have mandated the use of the ASI

for clinical and program evaluation purposes. Finally, the ASI has

become a mainstay in substance abuse research, which is the reason

that the role of the ASI in medication trials to treat cocaine

dependence is a topic of interest.

Given this kind of popularity, the ASI must have a lot going for it.

The ASI is especially valuable as a tool to conduct assessments for

clinical purposes and to obtain information to evaluate broad-based

rehabili-tations. To what extent, however, is the ASI applicable to

clinical trials of pharmacotherapy for cocaine dependence? To

address this question, first the structure of the ASI will be briefly

reviewed. Then the appropri-ateness and the strengths and weaknesses

of the ASI as a baseline assessment instrument and as an outcome

measure in clinical efficacy trials of medications for the treatment of

cocaine dependence will be addressed.

OVERVIEW OF THE ADDICTION SEVERITY INDEX

The ASI is a semistructured interview that can be administered by

trained interviewers. It assesses patient status in seven areas and

obtains demographic information as well. The seven following
183

potential problem areas are evaluated within the ASI: medical,

employment, drug use, alcohol use, legal, family/social, and

psychological. Questions in each area address lifetime and current

functioning (i.e., past 30 days).

Each problem area has several different types of items. The large

majority are considered objective items that detail the type, number,

and duration of problems and, to a lesser extent, assets. Two more

subjective items in each problem area are included: a patient rating of

recent problem severity and a patient rating of current need for

treatment. The ASI has two summary measures available for each

problem area:

1. Interviewer severity ratings are 0- to 9-point estimates of problem

severity, defined as the “need for additional treatment.” Each

severity rating is a subjective synthesis of all the information in a

specific problem area.

2. Composite scores (McGahan et al. 1982) are a second type of

summary measure and are considered to be more objective indices

of problem severity than interviewer severity ratings. Each

composite score is developed from a subset of items that reflect

current status in a given problem area.

The items are standardized and summed to produce a mathematically

derived composite score, which ranges from 0.00 to 1.00 for each ASI

problem area. Baseline composite scores and interviewer severity

ratings have been found to be highly correlated (Brown et al. 1993;

McLellan et al. 1985). The final items in each area are confidence

ratings, two items that are interviewer ratings of the veracity of the

information elicited from the patient.

The ASI is designed such that it is capable of repeat administration(s),

at least 1 month apart, with a followup version that is essentially a

subset of items from the full ASI. Composite scores are calculated

using the same items in full and followup ASIs. A baseline or

admission ASI used in conjunction with a followup ASI(s) can

provide a profile of change.

USE OF THE ADDICTION SEVERITY INDEX TO EVALUATE

PSYCHOSOCIAL TREATMENTS

The multidimensionality and breadth of information collected on the

ASI are its major strengths as an outcome measure for psychosocial
184

inter-ventions. These strengths are in some ways handicaps when the

ASI is used as an outcome measure to evaluate pharmacologic

interventions.

Alterman and colleagues (1994) used the ASI as a primary outcome

measure to determine the effectiveness of 1 month of inpatient versus

day-hospital cocaine rehabilitation. This was a near-perfect fit of the

ASI to evaluate a treatment intervention. These two intensive

programs, inpatient and day hospital, would be expected to effect

change over a number of dimensions (not just cocaine use), and

followup evaluations several months following admission would be

appropriate (in this case 4 months and 7 months) insofar as treatment

effects would be expected to emerge and persist over time. Since

these assumptions apply to many psychosocial interventions, it is no

surprise that the ASI is a primary assessment instrument in these types

of treatment studies for cocaine dependence. Actually, it is a rare

study that has evaluated the efficacy of a psychosocial intervention for

cocaine dependence that has not used the ASI.

USE OF THE ADDICTION SEVERITY INDEX TO EVALUATE

PHARMACOTHERAPY

General Considerations

Measures other than or in addition to the ASI may be more

appropriate to evaluate the efficacy of pharmacotherapy for cocaine

dependence. Medications would very likely be expected to effect

change in fewer areas, primarily cocaine use and perhaps psychiatric

symptomatology. Change in other areas, for example, criminal

behavior, employment status, and interpersonal functioning, would

likely be secondary to reduced cocaine use or to any psychosocial

treatment coupled with the pharmacotherapy. Furthermore, the

timing of pharmacologic and psychosocial treatment effects may be

different (Carroll et al. 1994b). The medications that have been

developed are generally expected to have a rapid onset. Since this is

the case, evaluations several months apart or even monthly are not

sufficient to capture the course of the treatment effect. At least

initially, weekly or more frequent evaluations may be needed to

adequately monitor change.

It is important to keep in mind that the ASI was developed as a

generic instrument for assessing substance abusers. Therefore, its

application to cocaine dependence and more specifically to
185

pharmacotherapy of cocaine dependence will not necessarily address

in sufficient detail the nature of the treatment effects. There are

actually only three items in the ASI that specifically address cocaine

use, i.e., days of cocaine use in the past 30, years of regular cocaine

use, and primary route of cocaine administration. One of these items,

route of administration, was added in the fifth and most recent edition

of the ASI (McLellan et al. 1992b), in part because route of

administration of cocaine may be an important severity/prognostic

variable. A second item, years of regular use, was modified in the

fifth edition to include a binge pattern of drug use and not strictly use

of three or more times a week. This change was made in part because

a typical pattern of cocaine use is bingeing. It is apparent that the ASI

does not include important information such as amount of cocaine

used and consecutive days of abstinence from cocaine. Furthermore,

the interviewer severity rating and composite score for drug use are

not cocaine specific. Insofar as these two summary measures of drug

use severity are sensitive to and elevated by multiple drug use, they do

not necessarily reflect severity of cocaine use.

Weiss and Mirin (1990) have identified four ways in which broad

classes of pharmacotherapeutic agents may impact cocaine use. These

medications may:

1. Block the effects of cocaine.

2. Treat premorbid, coexisting psychiatric disorders.

3. Treat cocaine withdrawal/craving.

4. Produce aversive reactions following cocaine use.

The ASI does not include items that assess specific variables that may

be most relevant to determining whether a medication is producing its

anticipated effect. For instance, craving/withdrawal are only addressed

on the ASI within the broader item of days of drug problems.

Psychiatric symptoms are assessed such that the presence of symptoms

such as anxiety and depression are noted, as are the frequency and

severity of psychological distress in general. The ASI does not,

however, rate the frequency or severity of specific psychiatric

symptoms.

This brief review lays the groundwork to outline how the ASI can best

be used in clinical efficacy trials of pharmacological treatments for

cocaine dependence.
186

The Addiction Severity Index as a Baseline Measure

At baseline, the ASI can provide a description of the study sample on

a standard set of potentially important background characteristics over

and above demographics, such as years of cocaine use, number of

previous drug treatments, years of alcohol use, arrest history, and

psychiatric symptom and treatment history. Current status in the

seven problem areas can also be described with individual items as

well as with interviewer severity ratings and composite scores. This

information creates a multidimensional profile of the subjects.

The scores on ASI individual items and summary measures can be

used to determine whether randomization to treatment conditions has

been successful, and in multisite trials to evaluate whether intersite

compara-bility has been achieved. ASI variables can also serve as

control variables if important differences do exist. To the extent that

the ASI is widely used, it supplies a standard set of variables to

compare one investigation with another, and thus provides

information that may assist in making sense of conflicting results.

The ASI also yields a number of severity variables that can be

explored as predictor variables.

As mentioned, the ASI collects valuable background and current

status information in seven problem areas, including psychiatric status.

It does not, however, elicit the necessary information to determine

psychiatric diagnoses. Specifically, although frequency of drug and

alcohol use and problems are obtained, the individual diagnostic

criteria for substance-related disorders are not assessed. Also,

although the ASI has questions about legal history and criminal and

violent behavior, it does not supply enough information to make a

diagnosis of antisocial personality disorder. Similarly, a positive

response to the depression or anxiety items in the ASI psychiatric

section does not necessarily indicate a diagnosable mood or anxiety

disorder.

It is apparent that there are two general types of information in a

baseline assessment that would be a helpful supplement to the ASI.

First, psychiatric diagnoses, especially substance-related disorders, are

necessary to adequately characterize a study sample. Other Axis I

disorders and personality disorders may be important descriptors as

well. Second, more detailed information on patients’ history and

current pattern of cocaine use is recommended.
187

The Addiction Severity Index as an Outcome Measure

With regard to the ASI as an outcome measure, the authors have in

many ways already alluded to its strengths and weaknesses. The ASI

alone does not provide the information to adequately assess outcome

in pharmacotherapy studies. The main areas in which more

information may be necessary are those concerning cocaine use and

problems— amount of use, craving/withdrawal, abstinence, treatment

attendance, urinalysis results, etc. Related to this point, Carroll and

colleagues (1994a) have added a few items to the ASI that, in

combination with the standard ASI item “days of cocaine use in past

30 days,” can be used to calculate a cocaine composite score. This

score is a specific measure of cocaine severity and is unaffected by

other drug use (see table 1).

Composite scores and specific items relating to frequency and severity

of problems in the seven ASI domains can be compared from

admission to varying followup points as measures of change.

(Interviewer severity ratings should generally not be used as pre- and

postmeasures because they are based on different information at

baseline and followup.) For the purposes of pharmacotherapy studies,

changes in the ASI problem areas (other than the drug use area),

however, are probably best thought of as secondary outcomes. That

is, broader changes would most likely be related to a reduction in

cocaine use or the psychosocial aspects of the treatment in which the

medication is embedded, and not direct results of the medication per

se. Insofar as the medications are expected to treat coexisting

psychopathology such as depression, the ASI psychiatric scale may be

considered a primary outcome measure as well. Nevertheless, in these

cases, more syndrome-specific scales may be valuable supplements,

e.g., the Hamilton Rating Scale for Depression (Hamilton 1960) or the

Beck Depression Inventory (Beck and Beck 1972).

The timeframe reflected in the ASI followup is primarily the past 30

days. If medications are to affect early abstinence, weekly

evaluations, at least at first, are probably necessary. The ASI is not

designed for such frequent evaluations. There are several other

points related to the
188

TABLE 1. Questions and formula for the cocaine composite

score.

The cocaine composite score is based on the algorithm for the ASI

alcohol composite score.

The cocaine composite includes the first part of question 8 in the ASI

Drug and Alcohol Section; i.e., number of days of cocaine use in the

past 30. It also requires adding the three following additional cocaine

questions to the ASI:

1. How many days in the past 30 have you experienced cocaine

problems?

2. How troubled or bothered have you been in the past 30 days by

these cocaine problems?__ (Answer = 0-4, not at all - extremely)

3. How important to you now is treatment for these cocaine

problems? __ (Answer = 0-4, not at all - extremely)

The formula to compute the cocaine composite score is as follows:

Cocaine Composite Score = Drug and Alcohol Q8 /120 +

Cocaine Q1 /120 + Cocaine Q2 /16 + Cocaine Q3 /16.

D & A Q8 = number of days used cocaine in the past 30.

C Q1 = number of days problems with cocaine in the past 30.

C Q2 = how bothered by cocaine problems in the past 30 days.

C Q3 = need for treatment for cocaine problems.

SOURCE: Carroll, personal communication.

timeframe of the evaluation period covered by the ASI. When

evaluations are several months apart, the most detailed information

collected on the ASI concerns the past 30 days, and that is the

information on which the composite scores are based. Regarding the

remainder of the followup period, the ASI covers only major events,

such as hospitalizations and arrests. Therefore, the course of cocaine

use or psychiatric symptoms or alcohol use is not continuously

documented unless the ASI is conducted monthly or supplemented by

additional timeline followback procedures in the domains of interest.

For example, if a baseline ASI and a 3-month ASI followup are

conducted, the data available for the comparative analyses are

essentially snapshots of the 30 days prior to each evaluation. In this
189

case, important information such as duration of continuous abstinence

and occurrences of relapse episodes is not obtained.

Measuring the Treatment Context

The ASI does not document the treatment services that patients

receive. There are important benefits in evaluating the amount and

nature of treatment that patients are receiving during the medication

trial. The treatment context within which a medication is delivered

may well impact on its effectiveness. The Treatment Services Review

(TSR) (Alterman et al. 1993; McLellan et al. 1992a) is a structured,

technician- administered interview designed to assess the type and

amount of treatment that patients receive. In this brief interview,

treatment services are categorized along the lines of the seven ASI

problem areas. The period addressed with the TSR is 1 week.

Repeated TSR interviews can therefore detail the course of a patient’s

treatment over time. The authors have been focusing on patient

variables that can be measured with the ASI. Treatment or program

variables, in addition to patient variables and type and dose of

medication, may account for individual and site differences in

response to medication. The TSR can provide a standard evaluation

of treatment services in the same way that the ASI can provide a

standard set of patient variables. Therefore the TSR items and

summary measures can be used to determine whether patients in

different treatment conditions (e.g., active medication versus placebo)

are receiving similar levels of ancillary services. In multisite trials, the

TSR can be used to determine whether treatment among sites is

comparable. The TSR can also supply a standard set of variables to

compare one investigation with another. Lastly, the TSR can assist in

the effort to determine the overall treatment conditions necessary for a

medication to show a therapeutic effect.

SUMMARY

In sum, the ASI provides a standard and multidimensional initial

evaluation of the subject. Furthermore, a profile of subjects is

obtained that can be compared at different evaluation points,

providing secondary outcomes. However, for the purposes of clinical

trials evaluating phar-macotherapy for cocaine abusers, supplemental

measures are needed at both baseline and followup to more

specifically address cocaine use and problems.
190

REFERENCES

Alterman, A.I.; McLellan, A.T.; and Shifman, R.B. Do substance abuse

patients with more psychopathology receive more

treatment? J Nerv Ment Dis 189:576-582, 1993.

Alterman, A.I.; O’Brien, C.P.; McLellan, A.T.; August, D.S.; Snider, E.C.;

Droba, M.; Cornish, J.W.; Hall, C.P.; Raphaelson, A.H.;

and Schrade, F.X. Effectiveness and costs of inpatient and

day hospital cocaine rehabilitation. J Nerv Ment Dis

182:157-163, 1994.

Beck, A.T., and Beck, R.W. Screening depressed patients in family practice:

A rapid technique. Postgrad Med 52:26-33, 1972.

Brown, L.S.; Alterman, A.I.; Rutherford, M.J.; Cacciola, J.S.; and Zaballero,

A.R. Addiction Severity Index scores of four racial/ethnic

groups of methadone maintenance patients. J Subst Abuse

Treat 4:269-279, 1993.

Carroll, K.M.; Rounsaville, B.J.; Gordon, L.T.; Nich, C.; Jatlow, P.;

Bisighini, R.M.; and Gawin, F.H. Psychotherapy and

pharma-cotherapy for ambulatory cocaine abusers. Arch

Gen Psychiatry 51:177-187, 1994a.

Carroll, K.M.; Rounsaville, B.J.; Nich, C.; Gordon, L.T.; Wirtz, P.W.; and

Gawin, F.H. One year follow-up of psychotherapy and

pharmacotherapy for cocaine dependence: Delayed

emergence of psychotherapy effects. Arch Gen Psychiatry

51:989-997, 1994b.

Hamilton, M. A rating scale for depression. J Neurol Neurosurg Psychiatry

23:56-62, 1960.

McGahan, P.L.; Griffith, J.A.; Parante, R.; and McLellan, A.T. Composite

Scores from the Addiction Severity Index. Washington, DC:

National Institute on Drug Abuse Project DA02554 and

the Veterans Administration, 1982.

McLellan, A.T.; Alterman, A.I.; Cacciola, J.; Metzger, D.; and O’Brien,

C.P. A new measure of substance abuse treatment: Initial

studies of the Treatment Services Review. J Nerv Ment Dis

2:101-110, 1992a.

McLellan, A.T.; Kushner, H.; Metzger, D.; Peters, R.; Smith, I.; Grissom,

G.; Pettinati, H.; and Argeriou, M. The fifth edition of the

Addiction Severity Index. J Subst Abuse Treat 9:199-213,

1992b.

McLellan, A.T.; Luborsky, L.; Cacciola, J.; and Griffith, J. New data from

the Addiction Severity Index: Reliability and validity in

three centers. J Nerv Ment Dis 173:412-423, 1985.

McLellan, A.T.; Luborsky, L.; Woody, G.E.; and O’Brien, C.P. An

improved diagnostic evaluation instrument for substance
191

abusers: The Addiction Severity Index. J Nerv Ment Dis

168:26-33, 1980.

Weiss, R.D., and Mirin, S.M. Psychological and pharmacological treatment

strategies in cocaine dependence. Ann Clin Psychiatry

2:239-243, 1990.

AUTHORS

John S. Cacciola, Ph.D.

Research Psychologist

Arthur I. Alterman, Ph.D.

Scientific Director

Charles P. O’Brien, M.D., Ph.D.

Vice Chair and Professor of Psychiatry

A. Thomas McLellan, Ph.D.

Professor of Psychiatry

Center for Studies of Addiction

University of Pennsylvania School of Medicine/

 Philadelphia VA Medical Center

3900 Chestnut Street

Philadelphia, PA 19104-6178
192

Cognitive-Neuromotor Assessment

of Substance Abuse: Focus on

Issues Related to Cocaine Abuse

Treatment

E.H. Ellinwood, Jr., and T.H. Lee

INTRODUCTION

Choice of the procedures and types of cognitive-neuromotor testing

used in assessment of cocaine abusers and their treatment is dependent

on a clear definition of the purposes of testing and the characteristics

of the individual tests. This chapter will first discuss published studies

of testing in cocaine abusers and pharmacodynamic effects of

stimulants and withdrawal. The types of tests available and their

characteristics will be discussed in terms of the purpose of testing.

The case will be made for the value of computerized cognitiveneuromotor testing when repeated assessment is needed in a busy

clinical setting.

Questions to be asked regarding the assessment of cognitiveneuromotor testing in substance abuse are: (1) who is to be tested, (2)

at what point in the abuse cycle are the tests to be conducted, (3)

what pattern and duration of drug abuse is to be tested, and (4) what is

the purpose of testing (e.g., for drug abuser evaluation? for change

with therapeutic efforts?). Secondary questions include what is the

most appropriate test for assessment and whether there is a means of

assessing test sensitivity and stability and establishing external

validation. Since this monograph is focused on treatment of cocaine

abuse, the authors will primarily explore the effects and questions

related to stimulant abuse; examples of the effects other types of

drugs of abuse have on testing performance will be presented to

highlight differences.

REPORTED COGNITIVE-NEUROMOTOR CHANGES IN CHRONIC

COCAINE ABUSERS

In assessing cognitive-neuromotor testing (CNT) deficits resulting

from chronic stimulant abuse, one must differentiate between effects

occurring during the initial 1 to 2 weeks of withdrawal and protracted
193

deficits occurring following extended abstinence. Since the turn of the

century, clinicians have observed diminished intellectual ability in

chronic cocaine abusers. More recently, several groups have assessed

chronic cocaine abusers during various times after withdrawal with

standardized cognitive-neuromotor testing. O’Malley and Gawin

(1990) assessed 25 chronic cocaine abusers who had accrued an

average of 135 days of abstinence and whose previous use, over a 4-

year period, had been approximately 11 g per month. Compared to

matched controls, the cocaine abusers performed worse on cognitive

motor skills and simple motor skills, as well as in their composite

scores. Deficits were reported in spatial relations, grooved pegboard,

grip strength, and retaining nonverbal material. In the same report, a

greater impairment was observed during the early abstinence period,

suggesting that there was a slight improvement with prolonged

abstinence. More recently, Berry and colleagues (1993), assessing

over a much briefer abstinence period (i.e., at 72 hours and again at

14 to 18 days) found that, in the first test session, cocaine abusers

scored significantly worse than the control group on various measures

including visuospatial construction (the Rey-Osterrieth figure),

Wechsler Adult Intelligence Scale (WAIS) block design, verbal

memory, and concentration. Furthermore, when retested 2 weeks

later, the cocaine abusers demonstrated less improvement than

controls on measures of psychomotor speed and verbal memory.

This finding suggests that selective cognitive deficits are identifiable

at least 2 weeks beyond withdrawal. Ardila and colleagues (1991)

went further to demonstrate that the duration of previous chronic

cocaine abuse was correlated with performance, particularly on the

digits subtest of the WAIS, memory quotient, and visual memory of

the Rey-Osterrieth figure. In contrast, Manschreck and associates

(1990) have reported that, in a group of 33 Bahamian cocaine

abusers, most of the mental status features such as intelligence,

memory, somatic processing, and motor functions did not differ from

controls. The only demonstrable impairment was a decrease in shortterm recall of auditory material. In contrast to a number of “paper

and pencil” studies cited above, the only computerized

neuropsychological testing was reported by Herning and colleagues

(1990). They found that both auditory and visual rare event

monitoring tasks were not different between patients and control;

however, the Sternberg Memory Task appeared to worsen over the

course of abstinence. An important caveat to the neuropsychological

differences cited above is to what extent there is a corresponding

difference in the number of affective disorders and/or attentional

deficit disorders; those disorders have been reported, to exceed onethird of the patients who have been receiving treatment for cocaine
194

abuse (see Rounsaville et al. 1991). Differences in the incidence of

affective and/or attentional status certainly could complicate

interpretation of cognitive-neuromotor performance results.

Moreover, these underlying conditions may require treatment before

improvement in CNT performance is observed.

In addition to affective attentional disorders, other medical history of

the patient needs to be considered. For example, a history of seizures,

strokes, hypertensive crisis, etc., also needs assessment for possible

contribution to impairment (Kaye and Fainstat 1987; Levine et al.

1987; Rowbotham 1988; Stein and Ellinwood 1990; Tuchman et al.

1987). Furthermore, the fact that nonspecific cognitive deficits are

found in many types of chronic drug abusers, whether due to drug

effects, infections, or other medical complications including chronic

malnutrition (Bruhn et al. 1981; Carlin 1986; Parsons and Farr 1981),

needs consideration. A final caveat is that clinicians report loss of

mental energy, incentive, and motivation in the intermediate

withdrawal period (see Gawin and Ellinwood 1988 for review), which

is difficult to factor out of neuropsychological testing.

Acute Pharmacodynamic Effects of Cocaine and Withdrawal

Most assessments of the direct pharmacodynamic effects of

stimulants on cognitive-neuromotor skills have been performed with

amphetamine or methylphenidate at moderate doses. Stimulants

improve WAIS performance including spatial relations, form

constancy, visual scanning, visual memory, and short-term recall for

learned paired associates (Hurst et al. 1969; Mohs et al. 1978;

Rapaport et al. 1978; Weingartner et al. 1980). However, stimulantinduced improvement in performance is specific for moderate doses.

Cocaine in moderate doses has also been found to improve vigilance

and motor functions in fatigued individuals (Fischman and Schuster

1980). At high doses, stimulants are not effective, especially with

complex tasks (MacWorth 1950; Smith and Beecher 1959). Highdose stimulant use can lead to either hyperactive distractibility or

highly stereotyped focused attention to details. Although these are

opposite effects, both can preclude flexibility in directed attention

needed in complex tasks. High-dose use is also associated with more

marked withdrawal changes. In addition, because cocaine has a shorteffect half-life, an abuser using late into the night or to a point of

stimulated exhaustion is also at risk of precipitous withdrawal

impairment as the excitatory effects of the cocaine suddenly wear off.

Rapid withdrawal may be especially important to vehicle traffic

accidents late at night. Prevalence of recent cocaine use in fatal
195

accident drivers (age 16 through 45) was above 15 percent between

1984 and 1987 in New York City (Marzuk et al. 1990). Thirteen

percent of drivers stopped for reckless driving in Memphis in 1993

had urines positive for cocaine (Brookoff et al. 1994). A model

representation of the relationship of stimulant dosing level as well as

withdrawal on performance is shown in figure 1, indicating that both

high dosing and withdrawal effects impair performance and judgment.

The “crash” withdrawal performance is also further deteriorated by

use of alcohol and sedatives to come down from the high (Gawin and

Ellinwood 1988).

COGNITIVE-NEUROMOTOR TESTING FOR THERAPEUTIC DRUG

TRIALS

Germane to the theme of this monograph is the consideration that

knowledge of stimulant-associated residual impairment is important to

the identification and effective treatment in chronic cocaine abusers.

In addition, therapeutic drug effects need consideration from two

view-points: (1) the therapeutic drug may either improve or impair

perfor-mance, and (2) the interactive effects of the therapeutic drug

with subsequent cocaine use may impair performance. Both need

consider-ation for acute and chronic administration of the therapeutic

drug.

For Phase I and Phase II studies, initial pharmacological assessment of

new central nervous system (CNS) active drugs testing is needed to

ensure that it either induces no impairment or that the effect

concentration (EC) curve or the 50 percent impairment

concentration (EC50 ) is well above the EC50 for the therapeutic

effect. To accomplish this type of testing the cognitive-neuromotor

tests used need to have: (1) a reasonable linear scale of impairment,

and (2) the capacity to establish a stable baseline across drug dosing

sessions. Tests that assess attentional capacities, psychomotor speed,

and coordination most often fit these criteria whereas verbal learning

performance does not. The ability to establish a baseline plateau is

also important in assessment of actual cocaine abusers undergoing

treatment over time, where they can act as their own controls. More

difficult to assess is the interactive impairment or even toxic

consideration of the treatment drug with subsequent abuse of cocaine.

Examples might be catechol-enhancing drugs or drugs with local

anesthetic properties (e.g., the tricyclic antidepressants that could

potentiate cocaine’s potential for toxicity).
196

MERITS OF COMPUTERIZED COGNITIVE-NEUROMOTOR TESTING

In assessment of treatment over time, the neuropharmacologist’s task

is not unlike that of the industrial environmental toxicologist, i.e., to

detect modest changes under conditions where contributions to

variance have multiple sources. Thus, using the individual as his or

her own control and repeated testing over the period of extended

cocaine abstinence (i.e., longitudinal assessment) is important in

establishing reliable indices of therapeutic efficacy. A single impaired

score flanked by stable baseline scores is likely to indicate a

temporary change (e.g., potential recidivism). Usually testing over

time involves the use of a battery of tests administered at intervals

between testing with one or two reliable performance tasks given

more frequently as indicators of changes in the clinical picture (e.g.,

recidivism). Computer-driven performance batteries, with their
197

capacity to maintain a running profile of the individual’s scores over

time, certainly facilitate this process and reduce personnel costs

dramatically. In addition, computerized batteries of tasks can be

presented in a consistent objective manner and can provide ready

databases for multisubject and multicenter studies.

Additional merits of computerized batteries need mention. Most

paper-and-pencil tests provide summary scores. For example, the

powerful component of the WAIS test: digit symbol substitution

(DSS), is typically scored as the number of correct answers in a given

time period. The version used in the computerized CNT requires the

subject to key in the correct number on a telephone keypad as one of

the symbols is presented at the bottom of a digital screen; at the

screen top the corresponding number-to-symbol code pairs are

displayed. Importantly, with computers, the same type of test can

provide the reaction time and its profile over the testing period (i.e.,

learning curve): the number of correct answers, and the composite

power score, as well as fluctuations in performance indicating

attentional variance. Since DSS is one of the tests with high “G,” i.e.,

tests requiring multiple capacities, these can be fractionated into

components. Although DSS provides a powerful screening tool, with

additional parallel testing a more definitive breakdown of component

capacities is possible. For example, the psychomotor speed

component can be obtained by reducing the task to keying in a

number that is presented on the screen. When this simple keypad

task reaction time is subtracted from the DSS reaction time, an

estimate of the central processing speed of the DSS can be obtained.

Other versions of the DSS test for posttest memory retrieval of the

code by erasing the code from the screen and asking the subject to

recall the code pairs from memory.

With appropriate simple transducers and manipulandi, computer

testing can assess many neuromotor and sensory components in

addition to cognitive function. Extremely sensitive testing of

postural stability, eye tracking and saccades, dynamic visual acuity,

and hand tremor are some of the tasks available in the task battery in

the authors’ CNT laboratories. Attentional components are easily

tested, including sustained, selective, and divided attention. Other

cognitive tasks sensitive to drug effects and easily performed by

computers include: Trails A&B various complex or choice reaction

time tasks as well as pattern recognition, hidden figure, and memory

tests (Ellinwood and Nikaido 1987a). Detailed descriptions of many

computerized testing systems can be found in the review by Kane and

Kay (1992).
198

In summary, testing with computers is being increasingly used

clinically because repeated testing at fairly frequent intervals is a

sensitive means of comparing treatment and underlying illness

interactions. The specific strengths of computerized procedures

include: (1) standardized presentation of stimuli and recording of

responses; (2) use of everyday manipulandi (e.g., telephone keypad,

car steering wheel), which are familiar to subjects; (3) efficient,

accurate, and rapid collection of detailed data components by

computer; (4) collection of more precise detailed data or sensory

visuomotor and neuromotor function than is usually assessed by

qualitative neurological exam; (5) immediate onsite analysis of data

and availability to the clinician; and (6) the ease of compiling and

analyzing data across subjects and centers.

EFFORTS TOWARD EXTERNAL VALIDATION OF TESTING

External validation in neuropsychological testing has always

presented problems: do tests predict real-world situations (e.g.,

activities of daily life)? For example, IQ tests in fact have

predictiveness for academic performance and job success.

Unfortunately, academic and job success data are not readily available

from the substance abuser on the “street,” whose academic career may

have been truncated in early adolescence. In fact, poor school

attendance by drug abusers may preclude use of tests such as verbal

learning, which are education-level sensitive. Therefore the

discussions of the relation of testing to the real world will rely on the

driving accident yardstick since even drug abusers are motivated to

maintain a driver’s license.

Well-documented alcohol studies provide a transitional framework to

relate other drugs of abuse induced impairment to: (1) automobile

accidents, and indeed (2) the legal limits for blood alcohol

concentrations (BACs) while driving are defined. The alcohol

accident rate is based on a number of different studies of blood alcohol

levels in drivers of both fatal accidents or accidents in general,

compared with BACs of drivers in the vicinity who were not involved

in the accident (Hurst 1973). By far, the largest study ever

accomplished was that of the Grand Rapids, Michigan, analysis where

approximately 6,000 blood alcohol determinations from drivers

involved in automobile crashes were compared with traffic scenematched controls. Whereas these data have been analyzed and

reanalyzed for potential biases (Hurst 1973), the curves (see figure
199

2A) indicate that the relative probability of alcohol-related crash is

minimal below 0.04 mg/mL BAC, but rapidly increases with higher

blood level concentrations. In figure 2B, the laboratory testing with

the sensitive digit substitution task shows similar impairment as a

function of BAC (i.e., there is a linear relationship between BAC and

impairment similar to that of the relative probability of the crash

data). Illustrated in figure 2B from a study of eight young, eight

middle-aged, and eight elderly subjects (Tupler et al. 1995) are the

average change in performance score related to alcohol

concentrations. The slope of the curve (figure 2B) is not only very

similar to that of figure 2A, but intersects the placebo range at 0.04

BAC, the point in figure 2A in which accident rates begin to rise. At

the top of the impairment scale it can be noted that the elderly

sample baseline (from which the changed scores are calculated) is very

much higher than the alcohol-dosed impairment effects for the young

subjects. This indicates the absolute necessity of age-matched

controls in any study. Thus, laboratory testing with the “gold

standard,” alcohol, indicates that the shape of the concentration

effect (impairment) curve is similar to what would be predicted from

accident rates. Similar results were obtained from several other tasks.

As discussed earlier, the published studies on abused stimulants are

sparse. Moderate doses of stimulants actually improve most

cognitive- neuromotor performance. Only at the higher stimulant

doses or during withdrawal from the higher doses is the marked

impairment reported to occur. Obviously, experimental studies with

higher doses and chronic stimulant administration present hazards

that laboratory researchers cannot risk. Thus, results from safer drugs

(e.g., sedative/anxiolytic) studies can serve as examples of potential

drugs of abuse to compare with alcohol for relative impairment.

There is extensive experimental literature on benzodiazepine

impairment detailing both dose response effects as well as plasma

concentration profiles (Gupta and Ellinwood 1995). Figure 3A and

3B compare the effects of the popular benzodiazepines, triazolam and

alprazolam, in young and elderly subjects (Nikaido et al. 1990) with

alcohol (Tupler et al. 1995). As can be noted, the concentration

effect curves for alcohol are marked (see arrow, figure 3) by

significant impairment at the legal intoxication concentrations of

0.08 mg/mL and above in both young and elderly subjects. The

concentration effect curves for triazolam and alprazolam illustrate

that in single doses used clinically (the lower dose for both drugs),

there is an impairment equal to or greater than that produced by

alcohol at the legal intoxication limit. The other concentration
200
201
202

effect curve for alprazolam and triazolam is at twice the highest

recommended dose, comparable to what might be expected with

sedative drug abusers.

At the higher dose for these two sedatives, the impairment is well

above the impairment found with the legal BAC when driving. The

legal alcohol intoxication level was established in the early

epidemiological studies demonstrating that 0.10 mg/mL BAC had an

accident rate approximately four times that of the control rate (Hurst

1973) and even higher in recent studies (Zador 1991). These

impairment studies are similar to impairment findings with on-theroad driving studies (Ray et al. 1993; van Laar et al. 1992; Volkerts

and O’Hanlon 1986). Epidemiological studies of driving and

benzodiazepine use, although limited, demonstrate an increased risk of

crash involvement with the use of benzodiazepines and other

anxiolytic and hypnotic drugs. The elevated relative risk of crashes is

reported to increase from 1.5 to upward of 4.9 for benzodiazepine and

moderate tranquilizer users (Ray et al. 1993). Because it is quite

difficult to garner a sample of sedative abusers during the time of their

high-dose use, an examination was accomplished with 68 chronic pain

patients to compare heavy and light sedative use. Heavy

sedative/anxiolytic users were in general more impaired on cognitiveneuromotor tests than light sedative users or no sedative users.

Sedative use is defined as muscle relaxants such as baclofen, sedatives,

and anxiolytic drugs. In contrast, utilization of the narcotic

methadone in chronic pain patients had little relationship to

impairment. The authors have also examined driving records of the

pain patients involved and found that heavy sedative users have

higher incidence of multiple accidents. The heavy sedative abuser

sample represented 28 percent of chronic pain patients, yet had 51

percent of all the accidents of pain patients.

With regard to external validation of neuropsychological testing,

several indices of cognitive sensory and neuromotor capacity have

been related to accident rates. One example is the nondetection of

the rapid approach of another vehicle in the peripheral vision (Ball

and Owsley 1991). One such selective attention measure known as

the useful field of view (UFOV) has been related to accident rates in

older drivers. For example, Ball and Owsley (1991) have reported a

significant correlation of UFOV impairment with previously reported

accidents, especially if the accidents were at an intersection.

Another laboratory measure associated with accidents is selective

attention, which requires the ability to both focus as well as shift
203

attention on stimulus locations or salient features. It can be evaluated

by such tests as dichotic listening, visual search (e.g., trail-making

test), and a cue-directed detection. For example, dichotic listening

task errors had a correlation of 0.37 with accident rates over a 1-year

period in professional bus drivers (Weiner 1984). A major problem of

correlating laboratory tests with accident rates is that accident rates

are low-frequency events; thus, the data-relating laboratory tests to

driving accident rates remains sparse.

CHOICE OF TESTS THAT HAVE EXTENSIVE COMPARATIVE

DATA LIBRARIES OF NEUROPHARMACOLOGICAL EFFECTS

The types of tasks to be included in a CNT battery obviously are

dependent on the particular experimental questions being addressed.

The tests included in the CNT battery used at the authors’ laboratory

were derived from an examination of the literature for tasks most

consistently sensitive to drug effects and ones that had the most

linear drug concentration effect relationships (see Ellinwood and

Nikaido 1987a). Actually, the type of test used in the CNT lab and

other neuropharmacology labs is very similar to those used by

environmental neurotoxicologists. The World Health Organization

battery, for example, includes simple reaction time, digit span, digit

visual retention, digit symbol, an aiming or coordination task, and a

Santa Ana motor coordination task. The reason for using these tests

from well-recognized batteries includes the fact that there is a much

larger database including normative data with which to relate findings

in any given study (Cassitto et al. 1989). In the authors’ CNT lab,

normative and drug-induced performance data on literally hundreds of

subjects have been acquired. Drug classes such as anticholinergic drugs

(Nikaido et al. 1990), sedative anxiolytics (Ellinwood et al. 1990;

Gupta and Ellinwood 1995; Johnson and Chernik 1982), alcohol

(Tupler et al. 1995), etc., have concentration effect curves that can

be generated across studies, increasing the size of the background

comparison groups. Thus the EC50 s for new drugs in their early

developmental phase can be compared with libraries of other welldocumented drugs in young, middle-aged, or elderly men and women

for comparison purposes. The use of larger libraries of background

data helps considerably when analyzing and interpreting data from a

given sample of subjects since age, sex, and genetics all contribute to

both the pharmacokinetic and pharmacodynamic variance.
204

CONCLUSION

In conclusion, cognitive-neuromotor testing can be utilized in several

areas of assessment in cocaine abusers, including: (1) evaluation of

residual withdrawal effects of chronic abuse, (2) timecourse of these

effects, (3) testing of the acute effects of cocaine and subsequent

withdrawal, (4) evaluation of novel early-phase therapeutic drugs for

treatment of stimulant abuse, and (5) evaluation of baseline withdrawal

impairment profiles of cocaine abusers for the relation to treatment

outcome. The choice of the specific cognitive-neuromotor tests to be

used in assessments should be made after consideration of pharmacological

sensitivity, linearity to dose or plasma concentration, and capacity to

establish a stable baseline performance. External validation specific to a

drug abuser population will be difficult. In contrast to paper-and-pencil

testing, computerized testing allows for the needed reliability and ease of

testing in a busy treatment setting as well as facilitating data collection

across individuals and treatment sites. Several computerized tasks have

current data libraries on drug effects that would provide background

information for new studies.

REFERENCES

Ardila, A.; Rosselli, M.; and Strumwasser, S. Neuropsychological deficits in

chronic cocaine abusers. Int J Neurosci 57:73-79, 1991.

Ball, K., and Owsley, C. Identifying correlates of accident involvement for the

older driver. Hum Factors 33(5):583-595, 1991.

Berry, J.; van Gorp, W.G.; Herzberg, D.S.; Hinhin, C.; Boone, K.; Steinman,

L.; and Wilkins, J.N. Neuropsychological deficits in abstinent

cocaine abusers: Preliminary findings after two weeks of

abstinence. Drug Alcohol Depend 32:231-237, 1993.

Brookoff, D.B.; Cook, C.S.; Williams, C.; and Mann, C.S. Testing reckless

drivers for cocaine and marijuana. N Engl J Med 331(8):518-

522, 1994.

Bruhn, P.; Arlien-Soberg, P.; Glydensted, C.; and Christensen, E.L. Prognosis

in chronic toxic encephalopathy. Acta Neurol Scand 64:259-

272, 1981.

Carlin, A.S. Neuropsychological consequences of drug abuse. In: Grant, I., and

Adams, K.M., eds. Neuropsychological Assessment of

Neuropsychiatric Disorders. New York: Oxford University

Press, 1986. pp. 478-497.

Cassitto, M.G.; Gilioli, R.; and Camerino, D. Experiences with the Milan

Automated Neurobehavioral System (MANS) in occupational

neurotoxic exposure. Neurotoxicol Teratol 11:571-574, 1989.
205

Ellinwood, E.H., and Nikaido, A.M. Perceptual-neuromotor

pharmacodynamics of psychotropic drugs. In: Meltzer, H.Y.,

ed. Psychopharmacology: The Third Generation of Progress.

New York: Raven Press, 1987a. pp. 1457-1466.

Ellinwood, E.H., and Nikaido, A.M. Stimulant induced impairment: A

perspective across dose and duration of use. Alco Drugs

Driving 3(1):19-24, 1987b.

Ellinwood, E.H., Jr.; Nikaido, A.M.; Gupta, S.K.; Heatherly, D.G.; and Nishita,

J.K. Comparison of central nervous system and peripheral

pharmacodynamics to atropine pharmacokinetics. J

Pharmacol Exp Ther 255(3):1133-1139, 1990.

Fischman, M.W., and Schuster, C.R. Cocaine effects in sleep-deprived humans.

Psychopharmacology 72(1):1-8, 1980.

Gawin, F.H., and Ellinwood, E.H., Jr. Cocaine and other stimulants: Actions,

abuse and treatment. N Engl J Med 318:1173-1182, 1988.

Gupta, S.K., and Ellinwood, E.H., Jr. Pharmacokinetic-pharmacodynamic

correlation of benzodiazepines. In: Handbook of

Pharmacokinetic/ Pharmacodynamic Correlation. Boca

Raton, FL: CRC Press, 1995. pp. 171-184.

Herning, R.I.; Glover, B.J.; Koeppl, B.; Weddington, W.; and Jaffe, J.H.

Cognitive deficits in abstaining cocaine abusers. In: Spencer,

J.W., and Boren, J.J., eds. Residual Effects of Abused Drugs on

Behavior. National Institute on Drug Abuse Research

Monograph 101. DHHS Pub. No. (ADM)91-1719.

Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1990.

pp. 167-178.

Hurst, P.M. Epidemiological aspects of alcohol in driver crashes and citations.

J Safety Res 5(3):130-148, 1973.

Hurst, P.M.; Radlow, R.; Chubb, C.N.; and Bagley, S.K. Effects of Damphetamine on acquisition, persistence, and recall. Am J

Psychol 82:307-319, 1969.

Johnson, L.C., and Chernik, D.A. Sedative-hypnotics and human performance.

Psychopharmacology (Berl) 76:101-113, 1982.

Kane, R.L., and Kay, G.G. Computerized assessment in neuro-psychology: A

review of tests and test batteries. Neuropsychol Rev 3(1):1-

117, 1992.

Kaye, B.R., and Fainstat, M. Cerebral vasculitis associated with cocaine abuse.

JAMA 258:2104-2106, 1987.

Levine, S.R.; Washington, J.M.; Jefferson, M.F.; Kiernan, S.W.; Moen, M.;

Feit, H.; and Welsh, K.M. Crack cocaine-associated stroke.

Neurology 37:1849-1853, 1987.

MacWorth, N.H. Research on the measurement of human performance. MRC

Special Report Series, 268. London: HM Stationary Office,

1950.
206

Manschreck, T.C.; Schneyer, M.L.; Weisstein, C.C.; Laughery, J.; Rosenthal,

J.; Celada, T.; and Berner, J. Free base cocaine and memory.

Compr Psychiatry 31(4):369-375, 1990.

Marzuk, P.M.; Tardiff, K.; Leon, A.C.; Stajic, M.; Morgan, E.B.; and Mann,

J.J. Prevalence of recent cocaine use among motor vehicle

fatalities in New York City. JAMA 263(2):250-256, 1990.

Mohs, R.C.; Tinklenberg, J.R.; Roth, W.T.; and Kopell, B.S.

Methamphetamine and diphenhydramine effects on the rate

of cognitive processing. Psychopharmacology 59:13-19,

1978.

Nikaido, A.M.; Ellinwood, E.H., Jr.; Heatherly, D.; and Gupta, S. Age-related

increase in CNS sensitivity to benzodiazepines as assessed by

task difficulty. Psychopharmacology 100(1):90-97, 1990.

O’Malley, S.S., and Gawin, F. Abstinence symptomatology and

neuropsychological impairment in chronic cocaine abuser. In:

Spencer, J.W., and Boren, J.J., eds. Residual Effects of Abused

Drugs on Behavior. National Institute on Drug Abuse

Research Monograph 101. DHHS Pub. No. (ADM)91-1719.

Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1990.

pp. 179-190.

Parsons, E.S., and Farr, S.D. The neuropsychology of alcohol and drug abuse.

In: Filskov, S.B., and Boll, T.S., eds. Handbook of Clinical

Neuropsychology. Vol. 1. New York: Wiley, 1981. pp. 320-

365.

Rapaport, J.L.; Buchsbaum, M.S.; Zahn, T.P.; Weingartner, H.; Ludlow, C.;

and Mikkelsen, E.J. Dextroamphetamine: Cognitive and

behavioral effects in normal prepubertal boys. Science

199:560-563, 1978.

Ray, W.A.; Thapa, P.B.; and Shorr, R.I. Medications and the older driver. Clin

Geriatr Med 9(2):413-438, 1993.

Rounsaville, B.J.; Anton, S.F.; Carroll, K.; Budde, D.; Presoff, B.A.; and Gawin,

F. Psychiatric diagnoses of treatment seeking cocaine abusers.

Arch Gen Psychiatry 48:43, 1991.

Rowbotham, M.C. Neurologic aspects of cocaine abuse. West J Med 149:442-

448, 1988.

Smith, G.M., and Beecher, H.K. Amphetamine sulfate and athletic

performance. I. Objective efforts. JAMA 170:542-557, 1959.

Stein, R.M., and Ellinwood, E.H., Jr. Medical complications of cocaine abuse.

Drug Ther 20(10):40-50, 1990.

Tuchman, A.J.; Daras, M.; Zalzal, P.; and Mangiardi, J. Intracranial

hemorrhage after cocaine abuse. JAMA 257:1175, 1987.

Tupler, L.A.; Ellinwood, E.H., Jr.; and Hege, S. Alcohol pharmacodynamics in

the elderly contrasted with young and middle-aged subjects.

Psychopharmacology 118(4):460-470, 1995.
207

van Larr, M.W.; Volkerts, E.R.; and van Willigenburg, A.P.P. Therapeutic

effects and effects on actual driving performance of

chronically administered buspirone and diazepam in anxious

outpatients. J Clin Psychopharmacol 12:86-95, 1992.

Volkerts, E.R., and O’Hanlon, J.F. Hypnotics’ residual effects on driving

performance. In: O’Hanlon, J.F., and de Gier, J.J., eds. Drugs

and Driving. Basingstoke, Hampshire: Taylor and Francis,

1986. pp. 123- 135.

Weiner, E.L. Vigilance and inspection. In: Warm, J.S., ed. Sustained Attention

in Human Performance. London: Wiley, 1984. pp. 207-246.

Weingartner, H.; Rapoport, J.L.; Buchcaum, M.S.; Bunney, W.F., Jr.; Ebert,

M.H.; Mikkelsen, F.J.; and Caine, E.D. Cognitive processes in

normal and hyperactive children and their response to

amphetamine treatment. J Abnorm Psychol 89:25-37, 1980.

Zador, P.L. Alcohol-related relative risk of fatal driver injuries in relation to

driver age and sex. J Stud Alcohol 52(4):302-310, 1991.

ACKNOWLEDGMENT

This research was supported by National Institute on Drug Abuse grant

nos. 5 P50 DA05303 and 5 RO1 DA02883.

AUTHORS

E.H. Ellinwood, Jr., M.D.

Professor

Department of Psychiatry and Pharmacology

T.H. Lee, M.D., Ph.D.

Assistant Research Professor

Department of Psychiatry

Duke University Medical Center

PO Box 3870

Durham, NC 27710
208

Treatment Effectiveness Score as

an Outcome Measure in Clinical

Trials

Walter Ling, Steven Shoptaw, Donald Wesson, Richard

A. Rawson, Margaret Compton, and C. James Klett

A variety of measures are used for evaluating patients’ responses to

substance abuse treatments. These range from physical measures

(such as samples of urine, breath, hair, or blood), self-reports of drug

use (such as the Addiction Severity Index (ASI) or the Time Line

Follow-Back), self-reports of psychological or physiological

functioning (such as symptom checklists or craving or mood ratings),

and collateral reports. Physical indices of recent drug use, such as

urine toxicology screens, are preferable to self-report or collateral

reports for evaluating patients’ responses to drug abuse treatments

because of their objectivity. In order to optimize the likelihood of

both detecting individual episodes of problem drug use and correctly

inferring drug abstinence based on urine toxicology results, guidelines

have been suggested for collection procedures and timing for

collection of urine specimens (Blaine et al. 1994; Cone and Dickerson

1992; Jain 1992). However, the difficult task of aggregating urine

toxicology results remains, whether when interpreting the response of

a single patient to a specific treatment or when evaluating a

treatment’s effectiveness based on a group of patients’ responses in a

clinical trial. Difficulties in aggregating urine toxicology results

include, but certainly would not be limited to, such problems as the

frequency and sensitivity of toxicology screens, early termination of

some patients from treatment (or, conversely, the continued

participation of some patients who respond poorly to treatment), and

problems of analyzing a data matrix that contains a large number of

missing datapoints. This chapter reviews the objective indices of

treatment response that have traditionally been used and suggests

three composite methods for evaluating these data: the Treatment

Effectiveness Score (TES), the Joint Probability score (JP), and the

Clinical Stabilization Score (CSS).

TRADITIONAL OBJECTIVE METHODS FOR MEASURING

TREATMENT EFFECTIVENESS

Many of the traditional objective measures of treatment effectiveness

have been characterized as imperfect indices (Ling et al. 1976) due to
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their inability to accurately and completely describe the various

aspects of treatment response. For example, retention in treatment

is one commonly used method for measuring clinical response.

However, reliance on retention as a sole indicator of treatment

efficacy can be misleading if concomitant use of illicit drugs is not

taken into account. A patient who shows little to no alteration in

drug use cannot be considered an unqualified therapeutic success

regardless of how long he or she remains in treatment.

In addition to retention, clinical reports typically include some type

of urine toxicology results to indicate treatment efficacy. Several

approaches have been used for interpreting drug use or drug abstinence

based on analyzed urine samples. These have included single-point

urine test results (such as urine samples collected at posttreatment

followup), percent of urine samples during the trial that are negative

for drug metabolite, and percent of patients able to achieve a specific

criterion (such as a varying number of consecutive weeks of samples

negative for drug metabolite).

Most commonly used to document long-term followup status, singlepoint urine samples can detect recent drug use, but cannot indicate

patterns of drug use throughout the followup interval. Further,

patients who provide urine samples at followup are usually those who

can be located, which further increases the threat to the internal

validity of this treatment response indicator. Still, many trials of

substance abuse treatments will include long-term followup urine

results as a primary indicator of treatment efficacy.

Clinical trials of substance abuse treatments depend on urine

toxicology results gathered during treatment to evaluate efficacy.

Researchers have debated the merits of using qualitative versus

quantitative values for interpreting urine toxicology results (Cone and

Dickerson 1992). However, these data are most commonly reported

as percent of samples negative for the metabolite of the problem

drug. Simple percent-negative indices can provide some indication of

patients’ overall response, but do not characterize accurately those

patients who terminate early despite all samples being negative for

metabolite or those who remain in the trial, yet continue to use the

problem drug. One alternative to a simple percent-negative index is

the achievement of a specific criterion based on achieving some

number of consecutive weeks of negative urinalysis (Carroll et al.

1991; Higgins et al. 1991) or percent of patients with continued

abstinence. Criterion-linked indices can suffer from the problem of

setting cutoff levels. That is, liberal cutoff levels can inflate the
210

actual clinical utility of a specific treatment, while conservative

cutoffs can underrepresent treatment efficacy. There are at least two

other problems associated with this approach. One is the loss of

ability to discriminate among patients with various drug use patterns,

e.g., using an 8-week criterion in a 16-week trial would count each of

the following patients as a success: (1) a patient who consistently

gives drug-free urines for 16 weeks; (2) a patient who uses drugs at the

beginning of the trial but then “cleans up” and gives drug-free urines

for the last 8 weeks; and (3) a patient who initially is fully compliant,

gives consistently drug-free urines for 8 weeks, and then relapses to

drug use or drops out of the program altogether. A second problem is

that the use of such a criterion yields a noncontinuous (i.e.,

categorical) dependent variable that is not optimal from a statistical

point of view.

All traditional approaches to interpreting urine toxicology results are

vulnerable to the effects of missing data. At a minimum, missing

datapoints are a nonrandom influence on the data matrix. Further,

missing data likely indicate treatment inadequacy—patients typically

do not attend a clinic regularly when treatment is ineffective. Missing

data heavily influence single-point urine results since the reason for

the missing data cannot be accurately represented in subsequent

analyses. It is often unknown whether missing data are due to

patients’ resolution of their drug problem, to patients’ continuing

drug use, or to patients’ refusal to participate. By contrast, percentnegative urinalysis methods can overrepresent patients’ responses

when patients discontinue treatment early but provide all samples

negative for drug during the trial. Least affected by missing data are

estimates of achievement of specific criteria, since patients with

missing data usually fail to meet the specific criteria.

Traditional methods for interpreting objective clinical indices also

commonly focus on one indicator to the exclusion of others.

Synthesis of information that describes patients’ treatment response

(as measured by urine toxicology), treatment compliance (as measured

by retention), and treatment toleration (as measured by lack of severe

side effects/toxicity) allows for a more complete evaluation of various

aspects of the efficacy of a given treatment. Dissatisfaction with the

limitations of traditional methods for interpreting objective measures

led the authors to experiment with new ways to compile and interpret

these data to address specific concerns that have been encountered

while conducting clinical trials.
211

NEW METHODS OF INTERPRETING OBJECTIVE MEASURES OF

CLINICAL RESPONSE

The Treatment Effectiveness Score

One important concern for any trial is objective evidence of

treatment efficacy. As an alternative to the methods reviewed earlier

for interpreting retention and urine data, the authors developed the

TES, which is a different approach to interpreting retention and urine

toxicology results with conceptual advantages. Using the TES,

“clean” urines rather than “dirty” urines can be counted. This simple

shift emphasizes patient success rather than failure, but avoids the

explicit imputation of a missing specimen as “dirty.” That is, a

patient either provides a “clean” urine as scheduled, or does not.

“Clean” urines are counted for the full scheduled tenure of each

patient in the trial.

For example, in a study of 17 weeks’ duration requiring three urine

samples each week, there would be 51 scheduled urine specimens. If

each “clean” urine earns a point, a metric is established with a range

of 0 to 51. The most successful therapeutic outcome is represented

by a patient who attends the clinic reliably, completes the full

duration of the trial, gives urine specimens as requested, and whose

urine samples are consistently clean. Such a patient would obtain a

score of 51. Patients may achieve scores of less than 51 in two ways:

either by providing one or more urines positive for the drug of abuse

being tested or by providing fewer than 51 specimens due to missed

clinic visits or leaving the trial early. The TES provides a measure of

relative standing in comparison to other patients in the trial. In the

above example, each patient has the opportunity to earn 51 points by

complying with the therapeutic expectations.

Conceived in this way, sample attrition is not a concern. Every

patient who is randomized has a score and is included in the analysis.

There are no dropouts in the usual sense and there is no assumption of

whether or not patients who are no longer actively participating have

returned to illicit drug use. Within a single clinical trial, there is no

need to convert the score to a percentage because all patients have

the same denominator, although doing so facilitates comparison

across studies of different duration or different scheduling of urine

collection. It is important to understand that the TES is not a pure

measure of illicit drug use, nor is it a measure of retention, although it

is heavily influenced by both. It is also influenced by other clinically

important parameters such as adherence to clinic policy, drug craving,
212

and withdrawal symptoms, to the extent that these affect retention

and drug use. Thus, the TES is intended as a composite score that

reflects multiple aspects of therapeutic success.

The authors have applied the TES to data gathered as part of two

large pharmacotherapy trials. In an opiate pharmacotherapy trial,

the TES was compared with the more commonly used percent of

urine samples negative for opiate metabolite (Ling et al., in press).

Results of comparisons of patients’ responses to different opiate

medication treatment conditions using the two indices showed similar

patterns when using the two measures. This similarity of results

indicates that the TES can provide a valid alternative to percentnegative urine samples yet also captures retention. The advantage of

the TES over the percent-negative urine samples is that this measure

provides a clear indication of treatment response: averaged TES

scores represent the expected value of negative urine samples for

similar patients who receive an identical treatment.

The TES has also been applied to urine toxicology data generated

from a cocaine pharmacotherapy trial and has been found to correlate

significantly with traditional objective and subjective measures of

treatment outcome (Ling et al. 1995). Specifically, the data showed

the TES to exhibit significant positive associations with the percent

of patients who achieved criteria of 3 and 8 consecutive weeks of

urine samples negative for cocaine metabolite, with the average

number of weeks of retention, and with the average number of

counseling sessions attended by patients. Significant negative

associations were found between the TES and the ASI drug scale and

the Profile of Mood States (POMS) depression score (McNair et al.

1992).

These findings provide strong evidence for the validity of using the

TES as an outcome indicator of clinical response. Application of the

TES to data from these two large pharmacotherapy trials has

indicated that the TES is a conceptually encompassing and succinct

indicator of outcome. Implicit in its measurement, the TES provides

an indication of another important factor: patients’ acceptance of

the treatment. Patients can reject treatment for a variety of reasons

that range from resumption of drug use, to being incarcerated, to

resolution of the drug problem. Assumptions of “automatic positive”

for missing data when using traditional methods for interpreting urine

toxicology results are avoided with the TES. By not imputing the

cause of missing data, the TES simply interprets missing data as an

indirect measure of patients’ acceptance of the treatment.
213

While the TES is an improvement over unidimensional scores, it is

not perfect. There will always be a few patients who are unable to

complete the trial for reasons beyond their control and for reasons

that have nothing to do with the treatment. However, the authors’

current position is that early termination is either drug related or it is

random. A relatively few random events could distort trial results, but

this risk seems preferable to layers of assumptions that might have

the same effect. It is obvious that information about drug use during

the trial is lost whenever the vector of test results is collapsed into a

single score. Patients with the same score can have different drug use

profiles with quite different therapeutic or prognostic implications.

The authors are interested in this and intend to explore other

approaches.

The Joint Probability Score

Another limitation of traditional outcome measures involves the lack

of a conceptually linked method for understanding the clinical

relevance of the trial. A method for estimating a given patient’s

probability of successful outcome at a specific point in time would be

useful to both clinicians and researchers. Most reports of clinical

trials customarily present a retention curve and an illicit drug use

curve as a means for summarizing objective treatment response data.

Using these to estimate patients’ responses can result in biased

appraisals, since both of these indicators are vulnerable to nonrandom

influences. Although broad statements about the value of a particular

treatment can be inferred for a group of patients, such retention and

drug use aggregate estimates cannot provide accurate information

about the probability of treatment success over time.

One method for compiling retention and illicit drug use data that

approaches the purpose of estimating patients’ response is to plot the

number of samples negative for illicit drugs during a given week

divided by the number of scheduled urine tests for that week times the

number of patients still active in the trial (Ling et al., in press). This

technique intends to correct for patients who terminate participation

early, though plots of such data are likely to demonstrate a gradual

upward trend, which a casual reader might interpret as clinical

improvement in patients. Such an association is likely to be spurious,

since in most clinical trials the number of patients who terminate

early increases over time, and attrition in this group is likely not due

to a random process. Rather, dropouts are more likely to be those

patients who have more severe levels of drug dependence and/or who
214

show poor response to the treatment than those who resolve their

dependency or who have external forces that preclude continued

participation. Thus, plots that illustrate the performance of the

residual sample will likely show an upward trend since those remaining

in the trial are those who tolerate the treatment and who may show

positive treatment responses.

A correction to this problem is to multiply each point of the plot

described above by the probability of retention to that point. In

essence, the plot is converted to a JP curve. For example, in a trial

requiring one sample per week, the point at week X would be p1 (i.e.,

the number of patients still in the study at week X divided by number

of patients who started treatment) times p2 (i.e., the number of urines

negative for illicit drugs at week X divided by the number of patients

still in the study at week X). Since the numerator of p1 and the

denominator of p2 cancel out, the curve can be constructed simply by

dividing the number of negative urines obtained each week by the

number of patients who started the study. This curve will tend to take

a downward path unless the loss of patients over time is fully

compensated for by better performance of the residual sample. As

presented, the JP is a conservative measure of treatment efficacy in a

clinical trial. Upward drift over time can be attributed to the

effectiveness of the treatment program rather than to influences on

the data of differential dropout of treatment nonresponders.

Validated using data in a large opiate pharmacotherapy trial (Ling et

al., in press), the JP has yet to be applied to data from clinical trials

of cocaine or other drug abusers. However, the logic underlying the

JP index argues for its use in trials using these other drug-dependent

patients. Knowing the retention rates, the number of samples

negative for illicit drugs over the weeks of a trial, and the original

number of patients, researchers and clinicians can easily calculate

accurate probabilities that their patients will produce a negative urine

sample at a given point when using a specific type of treatment.

Plotting the JP index produces a curve that can also be useful in

comparing outcomes from different studies of the same medication.

The Clinical Stabilization Score

The need for a composite index of treatment response, retention, and

acceptance has been identified by the authors when conducting doseranging studies of new medications for substance abusers. In such

trials, information that describes the safety and efficacy of a

particular medication at a particular dose level is crucial, yet often
215

incomplete. Measurements of good therapeutic response to a

medication should a priori indicate the elements that demonstrate

that response. The CSS is an index developed by the authors to

address this point.

The CSS is based on a set of criteria devised to study therapeutic

responses to variable doses of medications in the treatment of drug

dependency. As the name implies, the CSS is used to indicate that a

specific dose of a specific medication has stabilized the patient’s drug

dependence problem. The criteria that comprise the CSS are based on

a logic that incorporates clinically important elements of the

patient’s response to medication: reduction of illicit drug use,

continued treatment compliance, lack of adverse symptoms, and

absence of drug toxicity. CSS criteria are framed in a 2-week time

period. The window of observation moves forward in real time as the

patient remains in the trial. The clinical assessment consists of three

elements:

1. Urine toxicology. Monitored urine samples are collected at a set

rate over the course of the clinical trial. Samples are collected on

Mondays, Wednesdays, and Fridays, with no substitutions allowed.

Urine samples are immediately analyzed (within 24 hours) for the

presence of metabolite of the problem drug. The sample must be

free of this drug for the patient to earn a CSS point.

2. Clinic attendance. To earn a CSS point, patients must attend the

clinic as scheduled on a Monday, Wednesday, or Friday. Patients

who receive a CSS point comply with treatment. Conversely,

patients unable to comply with treatment likely will not attend

clinic and, hence, cannot earn a CSS point.

3. Adverse signs and symptoms. At each occasion for submitting

urine samples, the patient must report that he or she is free of

moderate to severe medication-related or withdrawal-related

symptoms and adverse medical events to earn a CSS point. For a

drug abuse medication to be clinically useful, it cannot induce

symptoms or effects that produce moderate to high levels of

discomfort in patients. Patients who report moderate to high

levels of adverse signs and symptoms cannot earn a CSS point.

Using these criteria, the authors provided the opportunity for patients

to earn CSS points three times per week, which corresponds with each

occasion for providing a monitored urine specimen. Patients must

achieve all three CSS criteria (come to the clinic, provide a drug-free
216

urine specimen, and be free of moderate to severe symptoms) to

achieve one CSS point. Using the scheduled visits in the authors’

research, patients can earn a possible six points over any 2-week

period. Patients who earn five or six out of the six possible CSS

points in a 2-week period, and who earn one of those points on the

most recent assessment occasion, are considered to have stabilized on

a therapeutic dose of medication. Study designs that use different

numbers of assessment points per week will have correspondingly

different ranges of possible CSS points. However, the rolling 2-week

period for evaluating CSS scores should be retained.

The CSS is not conceptualized as an outcome evaluation tool for

comparison among patients. Rather, it is a measure of how well a

given dose of study medication is helping a particular patient reduce

his or her problem drug use, without causing untoward symptoms and

adverse effects. In a clinical pharmacotherapy trial, the CSS can be

used in dose runup phases of studies or in studies that have variable

medication levels to monitor patient safety and to trigger study

medication dose changes. Unless a satisfactory CSS is achieved (e.g., a

CSS of five or six out of the six possible points), the dose of study

medication is increased by one increment at each weekly review. If

the occurrence of adverse symptoms reduces the CSS, the medication

is not increased or may be decreased by one increment. If a

satisfactory CSS is achieved, the dose remains unchanged.

It is conceivable that some patients could show positive response to a

study medication such that good therapeutic response can be

maintained with less frequent clinic attendance than the three times

per week required by the authors’ studies. Further, good therapeutic

response may be affected by a medication, though some patients may

find it inconvenient to attend the clinic on scheduled days. The CSS

would be unable to discriminate between such instances and poor

response to medication. Another problem is that the CSS suffers

from all indices that use a cutoff for classifying response outcomes.

For some patients, four of six scheduled urine samples being negative

for illicit drugs over a 2-week period could be classified as a treatment

“success.” At this point, the authors are planning to evaluate the

sensitivity and specificity of various cutoff levels using the above

criteria for the CSS. Finally, the CSS was conceived as an index to

address needs specific for a certain type of pharmacotherapy trial and

has been used by the authors for this purpose.
217

CONCLUSIONS

It is agreed that objective methods for assessing patients’ responses to

clinical trials offer the best indication of treatment efficacy.

However, the authors maintain that traditional methods of

interpreting such data are imperfect. Development of alternative

methods for interpreting objective data should be driven by

researchers’ needs to understand various aspects of treatment

response during the trial. The three indices suggested in this chapter

are intended to provide empirically derived integration of retention

and urine toxicology measures to indicate treatment outcome (TES),

probable treatment response (JP), and good therapeutic response

(CSS). Although these indices are still in the development and

evaluation phase, they offer clear advantages to traditional methods

for assessing patients’ responses in clinical trials.

REFERENCES

Blaine, J.D.; Ling, W.; Kosten, T.R.; O’Brien, C.P.; and Chiarello,

R.J. Establishing the efficacy and safety of medications for the

treatment of drug dependence and abuse: Methodologic issues. In:

Prien, R.F., and Robinson, D.S., eds. Clinical Evaluation of

Psychotropic Drugs: Principles and Guidelines. New York: Raven

Press, 1994.

pp. 593-623.

Carroll, K.M.; Rounsaville, B.J.; and Gawin, F.H. A comparative trial

of psychotherapies for ambulatory cocaine abusers: Relapse

prevention and interpersonal psychotherapy. Am J Drug Alcohol

Abuse 17(3):229-247, 1991.

Cone, E.J., and Dickerson, S.L. Efficacy of urinalysis in monitoring

heroin and cocaine abuse patterns: Implications in clinical trials

for treatment of drug dependence. In Jain, R.B., ed. Statistical

Issues in Clinical Trials for Treatment of Opiate Dependence.

National Institute on Drug Abuse Research Monograph 128.

DHHS Pub. No. (ADM)92-1947. Washington, DC: Supt. of Docs.,

U.S. Govt. Print. Off., 1992. pp. 46-58.

Higgins, S.T.; Delaney, D.D.; Budney, A.J.; Bickel, W.K.; Hughes,

J.F.; Foerg, F.; and Fenwick, J.W. A behavioral approach to

achieving initial cocaine abstinence. Am J Psychiatry 9:1218-

1224, 1991.

Jain, R.B. Analysis of clinical trials for treatment of opiate

dependence: What are the possibilities? In: Jain, R.B., ed.

Statistical Issues in Clinical Trials for Treatment of Opiate
218

Dependence. National Institute on Drug Abuse Research

Monograph 128. DHHS Pub. No. (ADM)92-1947. Washington,

DC: Supt. of Docs., U.S. Govt. Print. Off., 1992. pp. 116-134.

Ling, W.; Charuvastra, V.C.; Kaim, S.C.; and Klett, C.J. Methadyl

acetate and methadone as maintenance treatment for heroin

addicts. Arch Gen Psychiatry 33:709-720, 1976.

Ling, W.; Shoptaw, S.; Rawson, R.A.; and Klett, C.J. A composite

score for evaluating treatment response in cocaine

pharmacotherapy trials (TES). In: Harris, L.S., ed. Problems of

Drug Dependence, 1994: Proceedings of the 56th Annual

Scientific Meeting of the College on Problems of Drug

Dependence, Inc. Vol. II. National Institute on Drug Abuse

Research Monograph 153. NIH Pub. No. (ADM)95-3883.

Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1995.

p. 495.

Ling, W.; Wesson, D.R.; Charuvastra, C.; and Klett, C.J. A controlled

trial comparing buprenorphine and methadone maintenance. In

press.

McNair, D.; Lorr, M.; and Droppleman, L.F. POMS Manual: Profile

of Mood States. San Diego, CA: EdITS/Educational & Industrial

Testing Service, 1992.

ACKNOWLEDGMENTS

The authors gratefully acknowledge the support of the Los Angeles

Addiction Treatment Research Center; Matrix Center, Inc.; Friends

Medical Science Research Center, Inc.; National Institute on Drug

Abuse, Medications Development Division; and the West Los Angeles

Veterans Administration Medical Center.

AUTHORS

Walter Ling, M.D.

Associate Chief of Psychiatry for Substance Abuse

West Los Angeles Veterans Administration

Medical Center

Research Services (B151S)

Building 257, Room 7

11301 Wilshire Boulevard

Los Angeles, CA 90073
219

Steven Shoptaw, Ph.D.

Research Director

Los Angeles Addiction Treatment

Research Center (LAATRC)

Suite 340

10350 Santa Monica Boulevard

Los Angeles, CA 90025

Donald Wesson, M.D.

Medical Director and Scientific Director

Merritt-Peralta Institute Treatment Services

435 Hawthorne Avenue

Oakland, CA 94609

Richard A. Rawson, Ph.D.

Executive Director

Matrix Center and

Matrix Institute on Addictions

Suite 330

10350 Santa Monica Boulevard

Los Angeles, CA 90025

Margaret Compton, Ph.D.

Researcher

Los Angeles Addiction Treatment

Research Center (LAATRC)

Suite 340

10350 Santa Monica Boulevard

Los Angeles, CA 90025
220

C. James Klett, Ph.D.

Co-Director

Los Angeles Addiction

Treatment Research Center (LAATRC)

Suite 340

10350 Santa Monica Boulevard

Los Angeles, CA 90025
221

Pharmacokinetics of Cocaine:

Considerations When Assessing

Cocaine Use by Urinalysis

Reese T. Jones

INTRODUCTION

Changes in a patient’s patterns of cocaine use are generally

considered an important outcome measure of treatment efficacy.

Other treatment outcome measures are important as well, but if a

treatment does not stop or significantly decrease the intensity of a

cocaine addict’s cocaine use, many would question the treatment’s

efficacy. Examination of a patient’s urine for evidence of cocaine or

cocaine metabolites is an objective index of cocaine use. Like many

biochemical measures useful in medical practice, urinalysis to measure

cocaine or its metabolites, although relatively simple and

straightforward from an analytic standpoint, is subject to

misinterpretation and erroneous conclusions if the underlying

biological principles are not properly considered.

This chapter considers selected aspects of cocaine clinical

pharmacology, particularly cocaine pharmacokinetics as it applies to

the use of urinalysis to measure treatment outcome in cocaine

addiction treatment trials. The focus will be on examination and

assessment of urine, though cocaine and its metabolites are also

measurable in other biological media—hair, sweat, saliva and, of

course, blood. Saliva, hair, and sweat offer advantages in terms of

accessibility but have not been sufficiently studied to fully understand

the biodisposition and kinetics of cocaine. At this time, there are

insufficient data to make proper quantitative interpretations.

Consideration of future use of hair and saliva assays to measure

cocaine use and discussion of assay procedures in general are

included elsewhere in this volume.

The pharmacokinetics and metabolism of cocaine make for easy

monitoring of illicit cocaine use in most clinical situations. Typical

patterns of use result in substantial levels of cocaine and metabolites in

urine. A variety of immuno- and chromatographic assays make

quantitative urine measures relatively easy compared to other drugs of

abuse. Cocaine is taken by a variety of routes. In the United States,
222

cocaine is most commonly smoked or snuffed, but it is also used

intravenously, particularly by individuals likely to enter treatment

research programs. Some kinetic considerations are route dependent.

Smoking in particular has special attributes (Jones 1990).

PHARMACOKINETICS AND METABOLISM

Cocaine hydrochloride, a crystalline salt, is commonly snuffed or

injected. Cocaine base (crack) is the form usually smoked because

the base is more volatile, vaporizing at a lower temperature, in contrast

to cocaine hydrochloride, which decomposes before it volatizes when

heated. Cocaine is a weak base with a pKa of 8.6. In its basic form in

blood and smoke, cocaine crosses cell membranes quickly and

efficiently. Like nicotine in tobacco smoke, cocaine, when it reaches

the small airways and alveoli of the lung, is rapidly absorbed into the

blood. Although cocaine’s pulmonary kinetics are not as well studied

as nicotine, rapid absorption of cocaine through the lungs,

presumably because of the large surface area of the alveoli and small

airways, probably accounts for the appeal of that route of

administration.

The rate and the relative amount of cocaine entering systemic

circulation depend greatly on the route of administration. Figure 1

illustrates differences in time of peak plasma levels of cocaine when

approximately equipotent doses were administered to the same 10

volunteer subjects by different routes. Absorption from nasal mucosa

when snuffed and absorption from mouth and the gastrointestinal

tract when taken orally are similar and much slower than after

smoking or after intravenous (IV) administration (Jeffcoat et al. 1989;

Jones 1990). Peak plasma levels occur on average about 60 minutes

after nasal or oral intake; though, like many attributes of cocaine

kinetics, individual variability is great, ranging from 30 to 120

minutes in different individuals. An individual’s kinetics vary

between laboratory sessions as well. Oral and nasal bioavailability are

both about 30 to 40 percent, though variability is greater by the oral

route.

Like nicotine in cigarette tobacco, cocaine has smoked bioavailability

of between 10 and 20 percent, more commonly the lower amount with

typical smoking devices. When cocaine is smoked, the relatively low

and variable bioavailability is a consideration if attempts are made to

infer cocaine dose consumed by examination of only urine

concentrations.
223

A patient may report buying and putting considerable cocaine in a

pipe and smoking it, report experiencing intense effects, and yet show

less benzoylecgonine (BE) in urine assays than an IV or nasal user

(Jones 1990).

Peak venous blood concentrations and, by inference, peak arterial

blood levels after self-administered doses of cocaine vary enormously.

Not only do cocaine doses vary but, with IV administration, rate of

injection is as important a determinant of peak cocaine levels in blood

as is total dose. Cocaine doses commonly range from 0.2 to 3 or 4

mg/kg, depending on route. Peak plasma levels can range from 50 to

2,000 ng/mL or greater, depending on route and rate of injection.

Peak arterial blood levels of cocaine should be several times higher

than venous levels when cocaine is smoked or taken intravenously

(Chiou 1989).

Cocaine, after intake, is widely distributed through body tissues.

Volume of distribution usually ranges between 1.5 to 2 L/kg (Ambre

et al. 1988; Jeffcoat et al. 1989). Cocaine is rapidly metabolized.

Major metabolic pathways are by enzymatic hydrolysis to BE or

ecgonine methyl ester, then to ecgonine (Ambre et al. 1988). About

1 to 5 percent of a cocaine dose is excreted unchanged in urine.

Cocaine is rapidly cleared from plasma, but variably, at 20 to 30

mL/min/kg. Elimination half-life of cocaine is similarly variable,
224

averaging 1 to 1.5 hours. BE elimination half-life is 6 to 8 hours.

Ecgonine methyl ester half-life is 3 to 8 hours.

Metabolic pathways are illustrated in figure 2. Hydrolysis to BE

accounts for about 45 percent of a dose (Ambre 1985). Enzymatic

hydrolysis to ecgonine methyl ester accounts for approximately the

same or slightly less. Neither BE nor ecgonine methyl ester has

significant biological activity in humans. Norcocaine is a potentially

active metabolite but occurs in only small and probably

pharmacologically insignificant amounts in humans.

Cocaine and ethanol are commonly consumed at the same time by the

majority of people who use cocaine regularly. In the presence of

ethanol, cocaine is transesterified by liver esterases to ethyl cocaine,

also called cocaethylene (Dean et al. 1991). Cocaethylene has

cocaine-like pharmacologic properties. Cocaethylene is measurable

by the same techniques used for assaying cocaine in urine, saliva, hair,

or sweat, as are the ethyl homologs of BE and ecgonine ethyl ester.

When smoked, the cocaine pyrolyzes to a number of chemicals

depending on temperature (Martin et al. 1989). Anhydroecgonine

methyl ester (AEME), also known as methyl ecgonidine, can be

measured in the urine of people who have smoked relatively small

amounts of cocaine (Jacob et al. 1990). AEME does not appear in

the urine after injection or snuffing. Thus, if treatment-related

changes in typical route of use are of interest as a treatment outcome

measure, it might be possible to objectively measure by urinalysis a

patient’s shifts from or to cocaine smoking. Thus, in principle, even

typical routes of use and concurrent use of alcohol can be measured.

The human pharmacology of AEME has not been studied, but in

animals it is pharmacologically active.

BE is the commonly assayed metabolite for monitoring treatment

outcome. With most commercially available assays, BE can be

detected in urine for 3 to 4 days after last cocaine use. The detection

duration obviously depends on the amount of cocaine used in the

recent past, on the definition of the cutoff value required before

reporting the presence of BE, and on assay sensitivity.

ROUTE OF ADMINISTRATION

Route of administration can also determine amount of cocaine

entering the body and thus the amount of BE in urine. Figure 3

shows mean plasma
225
226

BE levels from the same 10 subjects as in figure 1. The higher

maximum concentrations and greater area under the time

concentration curve (AUC) after the nasal and oral doses of cocaine

are typical. Smoked doses of cocaine, though producing more

intense transient effects, result in relatively smaller amounts of cocaine

actually absorbed into the body; hence, smaller peak levels and AUC

for BE.

Although the plots in figure 3 represent BE levels after only a single

dose, and are from plasma rather than urine, they illustrate the

importance of considering route of administration when inferring

patterns of cocaine use from urine (or plasma) concentrations alone.

Smoking, because of the relatively low bioavailability, often results in

smaller absorbed amounts of cocaine after each smoked dose and

results in relatively lower levels of BE when compared to fewer but

larger doses of nasal cocaine or IV doses of cocaine. Of course,

increased numbers of smoked doses over whatever time is being

considered could change this pattern, but the principle holds; other

things being equal, a cocaine smoker may have relatively lower levels

of BE in urine than someone snuffing cocaine or using cocaine

intravenously.

PHARMACOKINETICS AND COCAINE DOSE

Taking only a single dose of cocaine is not a characteristic pattern of

use in the real world. A session of illicit cocaine use often involves

taking multiple doses over many hours. One approach for

administering doses of cocaine closer to real-world conditions is by

use of sustained infusions. Figure 4 illustrates mean BE levels in urine

during and 48 hours after a 4-hour continuous infusion of IV

cocaine hydrochloride given to a group of 10 nondependent

volunteers hospitalized on a hospital research unit. All had extensive

experience with IV use. The plotted values are midpoints of 12-hour

collections of total urine output. In test sessions spaced 2 days apart,

subjects received over the 4-hour infusion total cocaine doses of 105

mg, 210 mg, 420 mg, and a placebo infusion. The cocaine doses were

administered as 0.3, 0.6, and 1.2 mg/kg loading doses followed by

constant rate infusions at a rate calculated to equal previously

determined clearance.

The 420 mg dose was judged by all 10 subjects as very high and close

to exceeding what they could comfortably tolerate during a typical

session
227

of self-administered cocaine. During the 420 mg dose, toward the

end of the infusion, three subjects became very restless and showed

hints of beginning delusional thinking. None of the subjects

described the effects of that dose as a pleasant experience. In contrast,

the lowest dose (105 mg) was judged by most subjects as less than

they would have liked. The effects were described as less than

typically experienced during a session of self-administered use.

Each of the doses was significantly different in effects and in BE

AUCs and plasma concentrations during the log linear phase of

clearance. However, if a 300 ng/mL cutoff criteria was used for

determining positive or negative urines, the three very different doses

would appear equal at 48 hours, i.e., all urines were still positive. By a

least square fit for the log linear phase, the lowest dose would have

become negative at about 49 hours, the medium (210 mg) dose at

about 60 hours, and the highest (420 mg) dose at about 65 hours. If

an investigator’s goal was, by some treatment or other, to decrease

total amount of cocaine use during a user’s typical session of cocaine
228

use, then quantitative urinalysis would distinguish the three different

dose exposures at almost any point after cessation of cocaine use. A

qualitative (positive or negative) urine test would not distinguish

unless daily tests were performed.

In this study, there was no evidence of dose-dependent differences in

clearance. The maximum levels of BE in urine were in the range of

levels commonly encountered in cocaine addicts participating in

treatment trials. The data indicate that, with a 300 ng/mL cutoff

criteria, patients who have used cocaine for 4 hours or so during a

single evening can test positive 60 hours later. Although the plot in

figure 4 does not show individual variability, in fact there was little

variability between subjects. Cocaine levels in urine showed more

between-subject variability, as might be expected with a drug where

urine pH might have greater effect on clearance.

Another method to administer cocaine doses that result in urine levels

similar to those associated with real-world illicit use is to give repeated

doses under controlled and close medical supervision. Figure 5

illustrates urine cocaine and BE levels from one of nine volunteers

given repeated 140 mg oral doses of cocaine hydrochloride every 4

hours during the period beginning on day 7 and ending on day 11.

Twenty-four hour urine collections began on the first day of

admission to the University of California General Clinical Research

Center and continued each day, 0800 to 0800, until discharge on day

21. The kinetics of the oral cocaine doses approximated nasal doses.

While on this 840 mg/day dose schedule, urine levels of BE were

approximately 100,000 ng/mL; levels not unlike the BE

concentrations measured in the urine of some cocaine addicts in

treatment trials. Cocaine levels in urine during the period of repeated

oral doses were about 3,000 ng/mL and also in the range observed in

cocaine addicts in treatment.

When the oral doses of cocaine were replaced by placebo capsules late

in the afternoon of day 11, the 24-hour urine BE concentrations

decreased over the next 3 days. Noteworthy in this typical patient was

that by the third day after cocaine administration stopped, by criteria

commonly used in treatment trials (a 300 ng/mL cutoff), the patient

would probably have tested negative for BE with a urine sample

containing 180 ng/mL.
229

Only 3 days before, this individual was markedly intoxicated by

cocaine while receiving doses of cocaine similar to daily doses

associated with binge-type use behaviors. If a quantitative assay was

used, in this instance gas chromatography with mass spectrography

with cutoff of 10 ng/mL, the patient had measurable BE 9 days after

the last dose of cocaine. The increase in BE levels on day 4 resulted

from a single 140 mg nasal dose of cocaine. That single dose

produced very modest effects and also was followed by a negative

urine 2 days later, if a 300 ng/mL cutoff criteria was applied. The

point is, using nonquantitative urine criteria there was only 1-day

difference in changing from positive to negative after a single,

pharmacologically trivial dose of nasal cocaine as compared to the

urine change after cocaine doses that produced a period of sustained

and pharmacologically intense effects.

HOW MUCH BENZOYLECGONINE IS IN AN ADDICT’S URINE?

After becoming aware of typical urine levels of BE after cocaine

administration in conditions that partially mimic the real world of

cocaine use, as illustrated in figure 4 or figure 5, it seemed important

to determine what urine concentrations might be in typical cocaine

addicts participating in treatment trials. Curiously, no one had
230

bothered to measure actual concentrations of BE in urine despite the

enormous amount of money and time spent on nonquantitative urine

assays in treatment trials. It was well known that patients arriving in

emergency rooms with cocaine-related medical complications not

uncommonly had urine BE levels over 100,000 ng/mL, but nothing

was known about actual levels in typical cocaine addicts in treatment

programs (Batki et al. 1993). Gas chromatographic quantitative

assays of urines from cocaine addicts in treatment trials showed that

urine BE levels above 10,000 ng/mL were common and 22,562 ng/mL

was the median value for a group of 16 patients just entering

treatment. Patients with urine levels of 100,000 ng/mL or more were

not unusual. Occasional patients with urine BE levels as high as

300,000 ng/mL did not report any noteworthy acute toxicity or

unusual cocaine-related events.

The pharmacokinetic data on cocaine and BE levels in urine collected

in the author’s research laboratory experiments with nonaddict,

cocaine-using volunteers are remarkably congruent with the realworld urine levels in a cocaine treatment clinic. In light of typical

urine BE levels of 10,000 to 100,000 ng/mL, routine application of a

300 ng cutoff to define positive or negative (or clean or dirty) urines

may be a little shortsighted and holds cocaine treatment trials to a

higher standard for determining a clinically significant change than is

commonly applied in other medical treatments. For example,

consider a patient who had been using cocaine almost every day and

enters a treatment trial with urine levels of about 100,000 ng/mL of

BE. The patient would test positive for urine BE. After 8 weeks’

treatment if the patient was still using some cocaine almost every day

but taking much smaller doses, and if the patient had levels of 310

ng/mL at the time of testing, the urine still would be reported as

positive if judged by binary criteria and the patient might be termed a

treatment failure despite a 99.7 percent decrease in the amount of

cocaine used. Most treatments in medicine that change maladaptive

behavior or symptoms by 99.7 percent would be considered

successful.

SPECULATIONS ABOUT HISTORY AND RATIONALES

One argument for the binary urine assessment strategy is that

quantitative urinalysis is more time-consuming and more costly.

However, considering the total cost of a typical, well-designed Phase II

clinical treatment trial and the hidden costs of falsely accepting a

treatment that later turns out to be less useful, the true cost differences
231

may not be as great as assumed. Worse yet, consider missing

significant decreases in amount of cocaine use in a treatment trials and

thus falsely and prematurely rejecting a promising treatment. In

medical practice, it is rare for a quantitative biochemical test,

particularly one that may be important in clinical decisionmaking, to

be judged on a simplistic binary positive or negative report. Drug

abuse research almost stands alone in using such data as an outcome

measure.

Perhaps the original justification for the use of binary assessments was

a common treatment goal in addiction treatment research: achieving

total abstinence. However, if an acceptable treatment goal is fewer

occasions of cocaine use or use of a lower dose or a more acceptable

route on each occasion of use, then consideration of the

pharmacokinetics of cocaine becomes important when using

urinalysis to measure treatment outcome.

Until recently, most cocaine addiction treatment trials used the same

urinalysis methods and the same rationale when interpreting urinalysis

results as were developed for detecting or following illicit cocaine use

in the workplace or for clinical monitoring, mainly to make

therapeutic decisions regarding illicit drug use in opiate addiction

treatment programs. The assays generally were immunoassays for

BE. Because of concerns about cross-reactivity and resulting falsepositive reports, a common practice was to specify a 300 ng

concentration cutoff for BE. Any sample with a BE concentration

below 300 ng/mL was reported negative or a clean urine. A sample

with BE concentration above 300 ng/mL was reported a positive

sample (or a dirty urine).

Selection of the 300 ng/mL cutoff did not involve any formal

consideration of cocaine’s pharmacokinetics. In fact, when currently

popular cutoffs were established, there were no data on typical BE

levels in the urine of cocaine users entering treatment trials. The 300

ng/mL cutoff was largely determined by committee, with considerable

input from marketing and legal advisers, as a compromise to minimize

false-positives and limit, to an acceptable number, false-negatives in

workplace testing programs. Given the goals of typical workplace

testing programs (zero tolerance for any cocaine use), absolute or

upper levels of BE in a urine sample were irrelevant. Whatever

workplace sanctions imposed as a consequence of urine test results

were the same at 325 ng/mL as at 100,000 ng/mL levels. To apply the

same logic when establishing an appropriate cutoff in a clinical trial

may be inappropriate.
232

CONCLUSIONS

Of what practical value is information on cocaine kinetics for

someone designing or evaluating a treatment trial outcome and

considering urinalysis data? Patients participating in treatment trials

might typically enter with concentrations of 100,000 or 200,000

ng/mL of BE in their urine. How long BE would be measurable after

complete abstinence, of course, depends on assay sensitivity or the

selection of cutoff criteria. With commonly available gaschromatographic assays, sensitivities of 10 to 100 ng/mL are not

unreasonable. A patient might have measurable BE in urine 5 days

after last use if an assay sensitive to 10 ng/mL is used. If the clinician

chooses to or has to discard some of the potentially available

quantitative data and instead applies some higher cutoff (200, 300,

400 ng/mL), then obviously the window of urine positivity following

complete abstinence narrows considerably.

BE concentration in urine is a dose-dependent quantitative measure of

systemic cocaine dose actually delivered. In contrast, addict selfreports of money spent on cocaine or reports of days cocaine was

used are subject to greater error due to bioavailability considerations,

memory impairment related to cocaine-induced delirium, unreliable

underestimation or overestimation, or deliberate lying. Cocaine dose

differences as small as 100 mg are distinguishable (see figure 4).

With daily urine measures, even the taking of a single 140 mg nasal

dose is detectable for 1 or 2 days after use. With frequent enough

urine sampling, changes in urine BE levels accurately reflect very

small changes in dose patterns, assuming some measure of the usual

pattern of dosing. Since frequency and amount of cocaine use per

time unit are interrelated, BE assays will never completely distinguish

dose frequency from dose amount. However, for estimates of the

amounts of cocaine used over a 24-hour period, the pharmacokinetic

data indicate that reliable estimates of dose are possible.

How the pharmacokinetic information might best be applied depends

greatly on treatment goals. If total abstinence is the treatment goal,

then whatever the assay, whether semiquantitative or quantitative, a

very low cutoff used to define the urine as negative is most desirable.

A 300 ng/mL cutoff may be too high if abstinence is the treatment

goal. If urine samples are obtained only two or three times a week,

and the patients are other than regular daily users, episodes of cocaine

use will be missed if a 300 ng/mL cutoff criteria is applied. If a
233

treatment goal is to significantly decrease cocaine use in terms of

typical dose used or frequency of dosing, then quantitative urine BE

assays obtained as frequently as possible would be the ideal

continuous variable to measure that aspect of outcome. How

frequently urines can be obtained depends on the clinical setting and

research budget. The best advice would be to obtain urine samples as

frequently as possible—daily if possible. Any frequency of urine

sampling less than daily will tend to underestimate the frequency of

use and typical dose used over days or weeks.

An individual addict’s cocaine taking is a behavior as complicated as

any other behavior. A single snapshot or sample of a behavior at any

point in time cannot give an accurate representation of complicated

behavioral patterns over the previous few days or week. A urine

sample every day is probably more than is necessary to track small

changes in cocaine-using behavior. However, even a cursory

consideration of cocaine pharmacokinetics suggests a single weekly

urine sample is not enough and even every-other-day sampling will

miss small fluctuations. Measurement of BE levels in urine offers an

objective, quantitative, biological measure of treatment outcome; to

some extent clinical researchers can get from it what they are able to

afford.

REFERENCES

Ambre, J.J. The urinary excretion of cocaine and metabolite in

humans: A kinetic analysis of published data. J Anal Toxicol

9:241-245, 1985.

Ambre, J.J.; Belknap, S.M.; Nelson, J.; Ruo, T.I.; Shin. S.; and

Atkinson, A.J., Jr. Acute tolerance to cocaine in humans. Clin

Pharmacol Ther 44:1-8, 1988.

Batki, S.L.; Manfredi, L.B.; Jacob, P., III; and Jones, R.T. Fluoxetine

for cocaine dependence in methadone maintenance: Quantitative

plasma and urine cocaine/benzoylecgonine concentrations. J Clin

Psychopharmacol 13:243-250, 1993.

Chiou, W.L. The phenomenon and rationale of marked dependence

of drug concentration on blood sampling site. Clin

Pharmacokinet 17:175-199, 1989.

Dean, R.A.; Christian, C.D.; Sample, R.H.B; and Bosron, W.F. Human

liver cocaine esterases: Ethanol-mediated formation of

ethylcocaine. FASEB J 5: 2735-2739, 1991.

Jacob, P., III; Lewis, E.R.; Elias-Baker, B.A.; and Jones, R.T. A

pyrolysis product, anhydroecgonine methyl ester
234

(methylecgonidine), is in the urine of cocaine smokers. J Anal

Toxicol 14:353-357, 1990.

Jeffcoat, A.R.; Perez-Reyes, M.; Hill, J.M.; Sadler, B.M.; and Cook,

C.E. Cocaine disposition in humans after intravenous injection,

nasal insufflation (snorting), or smoking. Drug Metab Disp

17:153-159, 1989.

Jones, R.T. The pharmacology of cocaine smoking in humans. In:

Chiang, C.N., and Hawks, R.L., eds. Research Findings on

Smoking of Abused Substances. Washington, DC: Supt. of Docs.,

U.S. Govt. Print. Off., 1990. pp. 30-41.

Martin, B.R.; Lue, L.P.; and Boni, J.P. Pyrolysis and volatilization of

cocaine. J Anal Toxicol 13:158-162, 1989.

ACKNOWLEDGMENTS

This chapter was prepared with support from the National Institute on

Drug Abuse grant nos. DA01696 and DA00053, and Contract

N01DA-4-8306 and carried out in part in the General Clinical

Research Center at University of California, San Francisco, with

support of the Division of Research Resources, National Institutes of

Health (RR-0079).

AUTHOR

Reese T. Jones, M.D.

Professor of Psychiatry

Langley Porter Psychiatric Institute

University of California, San Francisco

401 Parnassus Avenue

San Francisco, CA 94143-0984
235

Quantitative Urine Levels of Cocaine

and Other Substances of Abuse

Jeffery N. Wilkins

INTRODUCTION

Quantitative urine levels of cocaine and other substances of abuse hold

the promise of providing new and important information that goes

beyond the scope of qualitative results. This chapter describes clinical

and treatment research applications of quantitative urine levels of

substance abuse analytes. A historical review is presented, caveats are

discussed, and a single-step dilution Abbott ADX/TDX method is

provided. Examples are presented that support the utility of

quantitative urines in pharmacotherapy trials of cocaine and other

substances of abuse, in health services research, in studies of

polysubstance abuse, and in studies associating biological markers with

phases of physiological dependence and risk to relapse.

By tradition, substance abuse urine results are expressed in qualitative

terms of positive or negative. However, urine levels of substance of

abuse may also be expressed with quantitative/scalar values. For

example, a patient’s urine level of the cocaine metabolite

benzoylecgonine (BE) can range from 0 to 300,000 ng/mL or higher.

The numerator of a quantitative urine analyte level contains either a

measure of weight of the respective analyte (e.g., ng) or its molarity

(e.g., mol). The denominator contains either a measure of urine

volume (e.g., mL) or the amount of excreted creatinine (Cn). Cn is

employed as an indicator of renal clearance since it is a byproduct of

cellular metabolism excreted steadily by the kidney and not reabsorbed

through the renal tubule. Analyte adjustment with Cn compensates

for dilute or concentrated urine resulting from the patient’s fluid

intake. Cn adjustment is helpful in a number of circumstances,

including when a patient has ingested large volumes of liquid, perhaps

in order to defeat the urine test. A Cn-adjusted level is produced by

dividing the concentration (mg/mL) of excreted Cn into the analyte

concentration. As an example, Cn values of 0.5 and 2.0 mg/mL

would adjust a BE level of 100,000 ng/mL to 200,000 ng/mg and

50,000 ng/mg, respectively.

BACKGROUND
236

Quantitative urine levels of lead and other toxins, adjusted for urine

dilution, have been employed in the fields of environmental and

industrial medicine for 50 years (Levine and Fahy 1945, reviewed by

Elkins and Pagnotto 1974). In the early 1970s, smoking cessation

investigators embraced the quantitative method and Cn adjustment for

expressing urine levels of the nicotine metabolite cotinine (reviewed

by Sepkovic and Haley 1985). Yet, despite the long-standing

recognition of urinalysis as a critical tool in the treatment of

substance abuse (Harford and Kleber 1978), only a limited number of

substance abuse investigators have employed quantitative urines.

Manno (1986) described how replacing qualitative results with Cn

adjusted quantitative urine levels of the carboxy metabolite of delta-9-

tetrahydrocannabinol prevented both false-positive and false-negative

interpretations of cannabinoid use (see figure 1). Additional

publications have supported this position for cannabinoids (Bell et al.

1989; Lafolie et al. 1991), as well as cocaine (Weiss and Gawin 1988,

Wilkins et al. 1994a), opioids and benzodiazepines (Lafolie et al.

1991), and buprenorphine, a mixed agonist/antagonist opioid (Watson

1992). Weiss and Gawin (1988) noted that quantitative urine BE

levels allowed for differentiation of positive BE levels arising from

washout, from positive BE levels resulting from new cocaine use. The

demonstration of protracted BE washout in cocaine-using patients

(Burke et al. 1990; Cone and Weddington 1989) amplifies the need to

distinguish washout from new cocaine use in clinical practice and

research.

SINGLE-STEP DILUTION PROTOCOL

Table 1 outlines a single step dilution protocol for the determination

of quantitative urine BE levels, based on the Abbott ADX/TDX

Net P value (Wilkins et al. 1994b). The Net P value is inversely

proportional to the analyte concentration (see figure 2),

representing the intensity of polarization/fluorescence produced

by the sample. Since the Abbott ADX/TDX printout provides the

Net P value in all of its assays, the dilution protocol can be

applied to a number of substance abuse analytes (see table 2). For

example, the initial Abbott ADX/TDX run of a sample

presumably containing BE will produce a numeric value from 0 to

5,000, or the printout will state “greater than 5,000”; i.e., out of

the Abbott
237

assay range. In this latter case, a dilution step and subsequent

rerun of the assay is required. The single-step dilution protocol

provides BE values to 150,000 ng/mL (a maximum dilution of

thirtyfold times 5,000), a range that includes most sample

values and identifies new cocaine use in most circumstances. If

following the dilution step the Abbott printout again reads

“greater than 5,000,” this indicates that the BE value is >

150,000. The author’s laboratory generally employs 150,000

as its maximal reporting value since a second dilution step

significantly increases the range of dilution-based error and

routine clinical needs do not require values beyond 150,000

ng/mL. When it is desirable to
238

TABLE 1. One-step dilution protocol.

1. First, analyze undiluted sample.

2. Do not dilute if within assay range (i.e., < 5,000 ng/mL for BE).

3. If exceeds assay range, dilute as follows using Abbott buffer.

4. Mix sample before taking aliquot and mix diluted sample well

before assay.

5. Can adjust final result by dividing by excreted creatinine.

1st run

Net P Dilution*

Sample

Volume

Diluent

Volume

75-80 1:3 100 L 200 L

70-75 1:5 100 L 400 L

60-70 1:10 100 L 900 L

50-60 1:20 100 L of

1:10

100 L

40-50 1:30 100 L of

1:10

200 L

KEY: * = Repeat sequence if postdilution result is > 5,000.

NOTE: The one-step process dilutes samples up to a maximum of

150,000 ng/mL (generally over 90% of samples encountered in a

pharmacotherapy trial).

produce values over 150,000, a second dilution step is performed

according to the same steps employed for the first dilution. Once a

diluted value is produced, adjustment with Cn can be performed.

Using samples obtained from a pharmacotherapy trial of cocaine

abuse/dependence (Margolin et al. 1995), the reliability of the singlestep dilution protocol was evaluated by comparing final BE

concentrations with the levels predicted by the Abbott ADX/TDX

Net P values. Almost all of the 1,619 samples (97.5 percent) were

diluted correctly by the procedure. The validity of the single-step

dilution protocol was evaluated by split-sample comparisons of

Abbott’s fluorescence polarization immunoassay (FPI) method with

high-pressure liquid chromatography (HPLC) and diode array

detection according to a modification of Svenson (1986). Across 26

random samples, a Pearson
239

correlation of 0.992 was demonstrated between the FPI and HPLC

methods. Once urine BE levels exceeded 150,000 ng/mL, the FPI

values were consistently higher than the HPLC values, producing an

across-sample variance of 11.79 percent.

HEALTH SERVICES RESEARCH

Quantitative urine levels for substance of abuse have been used to

define the prevalence of substance use in the week prior to admission

in patients admitted to psychiatric inpatient programs at the Veterans

Administration Medical Center (VAMC) West Los Angeles (Shaner et

al. 1993; Wilkins et al. 1991). Quantitative urine levels have also

been used to define the cascade process that begins with a mentally ill

patient’s use of a substance of abuse and ends with hospitalization

(Shaner et al. 1995). In this latter study, serial quantitative urine BE

levels from 155 schizophrenic patients were analyzed to track new

cocaine use. New use was defined within 3-day intervals. The results

demonstrated a clear relationship between receipt of disability pension

money, subsequent cocaine use, the development of cocaineassociated psychiatric symptomatology, and subsequent admission to

the hospital.

TABLE 2. Application of single step dilution protocol to Abbott

Assays of abusable substances other than cocaine.
240

Predilution

upper limit

of assay

New upper assay

limit following

thirtyfold dilution

Amphetamine class18,000 240,000

Amph./methamphetamine

II2

8,000 240,000

Barbiturates II U 2,000 60,000

Benzodiazepines 2,400 72,000

Benzodiazepines serum 2,400 72,000

Cannabinoid 135 4,050

Cocaine metabolite 5,000 150,000

Ethanol (urine) 300 9,000

Methadone 4,000 120,000

Opiates 1,000 30,000

Phencyclidine II 500 15,000

Propoxyphene 1,500 45,000

KEY: 1 = Includes both dextro and levo isomers of amphetamines.

2

 = Assays only dextro isomer of amphetamine and methamphetamine.

The investigators are continuing to use quantitative levels to evaluate

the impact on cocaine use from treatment interventions based on

contingency management.

POLYSUBSTANCE ABUSE

Serial collection of quantitative urine levels can be used to track

sequences of polysubstance abuse. As an example, opioid and cotinine

levels have been compared across time using Box-Jenkins Time Series

analysis (Wilkins et al., in review, see figure 3). These results suggest

that cigarette smoking and opioid use are behaviorally linked.

QUANTITATIVE URINE LEVELS AND BIOLOGICAL MARKERS OF

SUBSTANCE ABUSE

Biological markers may prove clinically useful in characterizing a

patient’s level of physiological dependence as well as risk to relapse
241

once abstinent. Preliminary data suggest that quantitative urine levels

may be useful as covariates in identifying endogenous substance abuseassociated biological markers. At a 1-year followup of patients

treated for cocaine abuse, circulating levels of cortisol and prolactin

(HPrl) were found to vary according to the range of the quantitative

urine BE level (Wilkins et al. 1992; figure 4). Cortisol levels reached

their highest elevations when urine BE reflected a later stage of

abstinence (i.e., < 200 ng/mL > 0) and returned to baseline when BE

was no longer present in the urine. Circulating HPrl levels were at

their lowest when BE levels reflected recent cocaine use (i.e., >

50,000 ng/mL), increased when BE levels reflected early abstinence

(i.e., > 10,000 ng/mL), and, unlike cortisol, remained elevated above

baseline even when BE levels were no longer present. The cortisol

results suggest that patients
242

experience a significant stress response approximately 3 to 4 days

after initiating abstinence from cocaine. Relatively lower HPrl levels

at the earliest stages of abstinence are consistent with inhibition of

HPrl release secondary to cocaine-induced increases in hypothalamic

dopamine. Subsequent elevations of HPrl, as abstinence from cocaine

progresses, are consistent with previous studies demonstrating

elevated HPrl during most phases of cocaine abstinence (Dackis and

Gold 1985; Mendelson et al. 1988). In sum, these preliminary results

suggest that HPrl and cortisol may serve as biological markers of the

varying stages of abstinence from cocaine.
243

PHARMACOTHERAPY TRIALS OF COCAINE ABUSE

Quantitative urine levels of abused substance may become an

important adjunctive measure in pharmacotherapy trials for cocaine

and other substances of abuse. Based on their ability to detect changes

in amount and frequency of cocaine use (Li et al. 1995), quantitative

urine levels may be used to screen potential subjects, assist in

determinations of sample size power analysis, and provide pre- and

postmedication outcome comparisons.

Inclusion criteria in substance abuse pharmacotherapy studies are

employed, in part, to assure that study patients are selected from the

same population. Quantitative urine levels may distinguish a study

population based on baseline substance use. For example, although

the two patients represented in figure 5 would meet conventional

study inclusion criteria for cocaine use based on qualitative urines

positive for BE (i.e., > 300 ng/mL), quantitative urine levels reveal a

fiftyfold variance between the patients in baseline BE levels.

According to their baseline cocaine use, these potential subjects may

not represent the same population. Thus, inclusion of both patients

into a pharmacotherapy trial as equals may introduce confounds

contributing to a Type II error.

Premedication quantitative baseline levels may also be helpful in

power analysis determinations. For example, quantitative urine BE

values are substantially different for the two populations

demonstrated in figure 6. Although both groups are made up of

cocaine-using, methadone-maintained patients, significantly different

research designs may be required to test for medication effect in each

population. Total abstinence might be the goal for the population

with 56.7 percent positive urines, whereas a consistent diminution in

urine BE levels might be the endpoint for the population with 90.8

percent urines positive for BE.

In addition, quantitative urine levels have been proposed to serve as a

primary outcome variable in pharmacotherapy trials for cocaine abuse

(Batki et al. 1993). The author notes that qualitative urine measures

would have failed to recognize a potential therapeutic effect of

fluoxetine for the treatment of cocaine abuse. The study results,

confounded by elevated premedication BE levels in the placebo group,

raises a number of timely questions including whether it is useful to

identify medications that do not necessarily produce complete

abstinence but reliably reduce cocaine use and frequency.
244

CAVEATS

Despite the strengths offered by quantitative urine levels, research

investigators and clinicians need to proceed with caution when

interpreting the clinical significance of the levels. Tracking of

quantitative urine levels does not definitively demonstrate the dose,

time of drug usage, clinical condition and/or behavioral impairment at

the time of sample collection (Jatlow 1992), despite careful and

thorough evaluation by Ambre and colleagues (1991). Quantitative

and qualitative urine results are influenced by variance in the

appearance of substance abuse analytes in urine (see reviews by Catlin

et al. 1992, Chiang and Hawks 1986, and Osterloh 1993) resulting

from interindividual differences in frequency and amount of substance

used, the presence of contaminants in the substance, route of

administration, sex, race, age, weight, diet, metabolic enzyme activity

(e.g., cholinesterase activity for cocaine), rate of excretion,

formation of condensation products (e.g., cocaethylene in users of

cocaine and alcohol), drug interactions, and
245
246

physiological parameters including blood flow, urine flow, and body

fluid pH.

Variability in the appearance of a substance abuse analyte is evident in

serial urine samples collected from subjects who received intravenous

cocaine (see figure 7) as part of a cardiovascular protocol (Nademanee

et al. 1990). BE excretion varied despite the use of identical doses

administered at the same time of day. It is noteworthy that this

problem may be reduced by employing recently introduced algorithms

that control for interindividual differences in BE excretion (Preston

and Cone, this volume).

Caveats also apply to Cn adjustment of analyte levels. Extremely low

or high Cn levels (e.g. < 0.1 or > 4.0) may produce spurious results.

Each investigative group needs to define a range that avoids excessive

adjustment with Cn, pending further research. In addition, all

substance abuse analytes may not be appropriate for Cn adjustment.

Alessio and colleagues (1985) have noted that not all environmental

toxins parallel Cn in renal excretion. Similarly, additional data

analysis from a pharmacotherapy-cocaine interaction safety study of

52 serial urines collected over 3 days of cocaine administration in four

subjects (Haberny et al. 1995) suggests that not all urine substance

abuse analyte levels parallel urine Cn levels. Pearson correlation

coefficients of Cn and analyte urine levels demonstrate close

correlations between Cn and amphetamine (0.95) and

methamphetamine (0.91), a reduced correlation between Cn and BE

(0.65), and even less of a correlation between Cn and ecgonine

methyl-ester (0.48) and Cn and cocaine (0.35).

Thompson and colleagues (1990) have proposed a methodology to

improve Cn adjustment in smoking cessation studies with potential

applications to other substance abuse research. In a study of 279 male

smokers, they demonstrated an increased correlation from 0.83 to

0.91 between urinary cotinine and plasma cotinine when the urine Cn

value was modified according to a regression line of log-transformed,

population-specific urine Cn levels. Alternatively, Simpson and

associates (1993) have proposed a cost-saving procedure of limiting

laboratory measures of Cn only when the urine color suggests dilution.

They report that 96.5 percent of 516 samples were correctly

identified by a visual inspection procedure, although the method has

been criticized as being too subjective (Lafolie 1991). Li and

colleagues (1996) performed a preliminary evaluation of various
247

methods to adjust BE with urine Cn levels. This exercise has yet to

identify a superior method, even when
248
249

employing the Thompson method. The effort is hampered by the lack of an

obvious “gold standard” for comparison with quantitative urine levels (i.e.,

the kinetics of renal clearance differ from the kinetic processes producing

blood, brain, and cerebrospinal fluid).

SUMMARY

Used appropriately, quantitative levels can address research hypotheses and

clinical issues that are otherwise untested by traditional qualitative urine

results. Quantitative urine levels can provide new information in health

services research, pharmacotherapy trials, studies of the interaction of

cigarette smoking and substance abuse, additional studies of polysubstance

abuse, and the linking of biological markers with phases of addiction and risk

to relapse.

REFERENCES

Alessio, L.; Berlin, A.; Dell’Orto, A.; Toffoletto, F.; and Ghezzi, I. Reliability of

urinary creatinine as a parameter used to adjust values of urinary

biological indicators. Int Arch Occup Environ Health 55:99-106, 1985.

Ambre, J.J.; Connelly, T.J.; and Ruo, T.I. A kinetic model of benzoylecgonine

disposition after cocaine administration in humans. J Anal Toxicol 15:17-

20, 1991.

Batki, S.I.; Manfredi, L.B.; Jacob, P.; and Jones, R.T. Fluoxetine for cocaine

dependence in methadone maintenance: quantitative plasma and urine

cocaine/benzoylecgonine concentrations. J Clin Psychopharmacol

13:243-249, 1993.

Bell, R.; Taylor, E.H.; Ackerman, B.; and Pappas, A.A. Interpretation of urine

quantitative 11-nor-delta-9-tetrahydrocannabinol-9-carboxylic acid to

determine abstinence from marijuana smoking. J Clin Toxicol 27:109-

115, 1989.

Burke, W.M.; Ravi, N.V.; Dhophesh, V.; Vandegrift, B.; and Maany, I. Prolonged

presence of metabolite in urine after compulsive cocaine use. J Clin

Psychol 51(4):145-148, 1990.

Catlin, D.; Cowan, M.; Donike, M.; Fraise, D.; Oftebro, H.; and Rendie, S. Testing

urine for drugs. Clin Chem Acta 207: S13-S26, 1992.

Chiang, C.N., and Hawks, R.L. Implications of drug levels in body fluids: Basic

concepts. In: Hawks, R.L., and Chiang, C.N., eds. Urine Testing for Drugs

of Abuse. National Institute on Drug Abuse Monograph 73. DHHS Pub.

No. (ADM)87-1481. Washington, DC: Supt. of Docs., U.S. Govt. Print.

Off., 1986. pp. 63-83.
250

Cone, E.J., and Weddington, W.W. Prolonged occurrence of cocaine in human

saliva and urine after chronic use. J Anal Toxicol 13:65-68, 1989.

Dackis, C.A., and Gold, M.S. New concepts in cocaine addiction: The dopamine

depletion hypothesis. Neurosci Biobehav Rev 9:469-477, 1985.

Elkins, H.B., and Pagnotto, L.D. Concentration adjustments in urinalysis. J Am

Industrial Hygiene Assoc 56:559-565, 1974.

Haberny, K.A.; Walsh, S.L.; Ginn, D.H.; Wilkins, J.N.; Garner, J.E.; Setoda, D.;

and Bigelow, G.E. Absence of cocaine interactions with the MAO-B

inhibitor selegiline. J Drug Alcohol Depend 39:55-62, 1995.

Harford, R.J., and Kleber, H.D. Comparative validity of random-interval and

fixed-interval urinalysis schedules. Arch Gen Psychiatry 35:356-359,

1978.

Jatlow, P. The role of drug analysis in cocaine abuse treatment and research. In:

Kosten, T.R., and Kleber, H.D., eds. Clinician’s Guide to Cocaine

Addiction. New York/London: The Guilford Press, 1992. pp. 193-205.

Lafolie, P.; Beck, O.; Blennow, G.; Boreus, L.; Borg, S.; Elwin, C.E.; Karlsson, L.;

Odelius, G.; and Hjendahl, P. Importance of creatinine analyses of urine

when screening for abused drugs. Clin Chem 37:1927-1931, 1991.

Levine, L., and Fahy, J.P. Evaluation of urinary lead determinations, 1. the

significance of specific gravity. J Indus Hygiene Toxicol 27:217-23,

1945.

Li, S-H.; Chiang, N.C.; Tai, B.C.; Marschke, C.K.; and Hawks, R.L. Quantitative

versus qualitative urinalysis for benzoylecgonine in clinical trials for the

assessment of cocaine use. Psychoharmacol Bull 31:671-679, 1995.

Li, S-H.; Wilkins, J.N.; Wheatley, S.; Setoda, D.; Ashofteh, A.; Lee, S.; and Ling,

W. Adjustment of benzoylecognine by excreted creatinine: Comparison

of methods. In: Harris, L.S., ed. Problems of Drug Dependence 1995:

Proceedings of the 57th Annual Scientific Meeting. National Institute on

Drug Abuse Research Monograph 162. NIH Pub. No. 96-4116.

Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1996.

Manno, J.E. Interpretation of urinalysis results. In: Hawks, R.L., and Chiang,

C.N., eds. Urine Testing for Drugs of Abuse. National Institute on Drug

Abuse Research Monograph 73. DHHS Pub. No. (ADM)87-1481.

Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1986. pp. 54-61.

Margolin, A.; Kosten, T.R.; Avants, S.K.; Wilkins, J.N.; Ling, W.; Beckson, M.;

Arndt, I.; Cornish, J.; Li, S.H.; Bridge, P.; and Ascher, J.A. Bupropion for

cocaine dependence: A multicenter trial of bupropion for cocaine

dependence in methadone-maintained patients. J Drug Alcohol Depend

40:125-131, 1995.

Mendelson, J.H.; Teoh, S.K.; Lange, U.; Mello, N.K.; Weiss, R.; Skupny, A.; and

Ellingboe, J. Anterior pituitary, adrenal, and gonadal hormones during

cocaine withdrawal. Am J Psychol 1456:1094-1098, 1988.

Nademanee, K.; Wilkins, J.W.; Gorelick, D.A.; Taylor, R.D.; Wong, M.;

Josephson, M.A.; Robertson, H.A.; Harwood, B.J.; Chipin, L.; and
251

Antimisiaris, M.G. Altered Catecholamine Homeostasis and Sympathetic

Responses Induced by Cocaine. Abstract. American College of

Cardiology, March 1990.

Osterloh, J. Testing for drugs of abuse: Pharmacokinetic considerations for

cocaine in urine. Clin Pharmacokinetics 24(5):335-361, 1993.

Sepkovic, D.W., and Haley, N.J. Biomedical applications of cotinine quantitation

in smoking related research. Am J Pub Health 75:663-665, 1985.

Shaner, A.; Eckman, T.; Roberts, L.; Wilkins, J.N.; Tucker, D.E.; Tsuang, J.W.;

and Mintz, J. Disability income, cocaine use, and repeated hospitalizations

among schizophrenic cocaine abusers: A government sponsored revolving

door? N Engl J Med 333:777-783, 1995.

Shaner, A.; Khalsa, H.; Roberts, L.; Wilkins, J.; Anglin, D.; and Hsieh, S.C.

Unrecognized cocaine use among schizophrenic patients. Am J Psychiatry

150(5):758-762, 1993.

Simpson, D.; Jarvie, D.R.; and Moore, F.M.L. Measurement of creatinine in urine

screening for drugs of abuse (letter) (and response by P. Lafolie). Clin

Chem 39:698-699, 1993.

Svenson, J.O. Determination of benzoylecgonine (cocaine metabolite) in urine

from drug abusers using ion pair HPLC. J Anal Toxicol 10:122-124, 1986.

Thompson, S.G.; Barlow, R.D.; Wald, N.J.; and van Vunakis, H. How should

urinary cotinine concentrations be adjusted for urinary creatinine

concentration? Clin Chem Acta 187:289-296, 1990.

Watson, I.D. Analysis of commonly abused drugs in urine at selected threshold

(cutoff) concentrations (letter). Clin Chem 38:441, 1992.

Weiss, R.D., and Gawin, F.H. Protracted elimination of cocaine metabolites in

long-term, high-dose cocaine users. Am J Med 85:879-880, 1988.

Wilkins, J.; Gorelick, D.A.; Ling, W.; Setoda, D.; Ashofteh, A.; and Lee, S. A

report on 10 years of experience with quantified urine benzoylecgonine,

morphine, and other analytes in clinical treatment and pharmacologic

trials of cocaine and other substance dependence. In: Harris, L.S., ed.

Problems of Drug Dependence, 1993: Proceedings of the 55th Annual

Scientific Meeting. National Institute on Drug Abuse Monograph 141.

NIH Pub. No. 94-3749. Washington, DC: Supt. of Docs., U.S. Govt.

Print. Off., 1994a. p. 447.

Wilkins, J.N.; Jarvik, M.E.; Ashofteh, A.; Davis, A.; Setoda, D.; Wheatley, S.;

Jerger, D.; Dixon, W.; Charuvastra, C.; Wesson, D.; and Ling, W.

Cigarette smoking and opioid use covary: Autocorrelations in opioidmaintained patients. In review.

Wilkins, J.N.; Khalsa, M.E.; Setoda, D.; and Gawin, F.H. “Prolactin Level as a

Possible Indicator of Neurobiological Impact of Cocaine Use.” Abstract.

Fifty-fourth Annual Scientific Meeting, The College on Problems of Drug

Dependence, Inc., June 1992.
252

Wilkins, J.N.; Setoda, D.; Li, S-H.; and Bridge, P. Application of Abbott

ADx/TDx-based procedures to yield semiquantitative urine results in a

NIDA pharmacologic trial. In: Harris, L.S., ed. Problems of Drug

Dependence, 1994: Proceedings of the 56th Annual Scientific Meeting of

the College on Problems of Drug Dependence, Inc. Vol. II. National

Institute on Drug Abuse Research Monograph 153. NIH Pub. No. 95-

3883. Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1994b.

Wilkins, J.N.; Shaner, A.L.; Patterson, C.M.; Setoda, D.; and Gorelick, D.A.

Discrepancies between patient report, clinical assessment, and urine

analysis in psychiatric patients during inpatient admission.

Psychopharmacol Bull 27 (2):149-154, 1991.

ACKNOWLEDGMENT

The author wishes to acknowledge the following laboratory staff: David

Setoda, Azita Ashofteh, Sabrina Lee, Fernando Lau, and Daniel Jerger, and

consultants Richard Hawks, Ph.D., Shou-Hua Li, Ph.D., and Nora Chiang,

Ph.D.

AUTHOR

Jeffery N. Wilkins, M.D.

Chief

Clinical Psychopharmacology Laboratory

WLA VAMC Medication Development Unit

and

Medical Director

Comprehensive Homeless Programs

West Los Angeles VA Medical Center (116S)

11301 Wilshire Boulevard

Los Angeles, CA 90073

and

Professor of Psychiatry and Biobehavioral Sciences

UCLA School of Medicine

Neuropsychiatric Institute and Hospital

760 Westwood Plaza

Los Angeles, CA 90024
253

Use of Quantitative Urinalysis in

Monitoring Cocaine Use

Kenzie L. Preston, Kenneth Silverman, Charles R.

Schuster, and Edward J. Cone

NEED FOR SENSITIVE MEASURES OF COCAINE USE

Cocaine use is a serious social and economic problem for which no

solution currently exists. Considerable efforts have been expended to

develop medications and other treatments for cocaine abuse, including

clinical trials of a number of pharmacologic agents and behavioral

approaches (Stitzer and Higgins 1995; Tutton and Crayton 1993).

The primary goal of drug abuse treatment is to have patients decrease

or stop their cocaine use. Because illicit drug use is a covert activity,

it is usually measured indirectly through urine toxicology screens.

Thus, urinalysis has become the primary outcome variable in most

clinical trials of cocaine abuse treatments.

A major difficulty confronting drug abuse researchers is that

appropriate pharmacological approaches to treatment are not clear.

The exact basis for the rewarding effects of cocaine are not yet

known, and although long-term neurochemical changes in cocaine

abusers have been proposed, the exact nature of these changes have

not been definitively identified (Cunningham et al. 1991; Johanson

and Schuster 1995). Medications acting on different

neurotransmitters (e.g., dopamine, serotonin, norepinephrine)

through a variety of mechanisms (e.g., reuptake blockade, receptor

antagonism, receptor agonism) have been evaluated (Tutton and

Crayton 1993). The identification of medications with even partial

efficacy could be valuable in guiding the direction of medication

development activities. Therefore, the outcome measures used in the

clinical trials in which experimental treatments are evaluated must be

adequately sensitive to detect relatively small changes in cocaine use.

The most commonly used method for monitoring cocaine use in

clinical trials is urinalysis. Typically, urine specimens are tested by

qualitative immunoassays that detect benzoylecgonine (BE), the

primary metabolite of cocaine. The standard cutoff concentration

used in clinical trials to define positive and negative qualitative

screens is 300 ng/mL of cocaine metabolite, the same requirement set

in the Mandatory Guidelines for Federal Workplace Drug Testing
254

Programs (Department of Health and Human Services 1994). BE has

a urinary excretion half-life of 6 to 8 hours (Ambre 1985) and can

usually be detected in the urine for about 48 hours after cocaine

administration (Saxon et al. 1988). The actual duration of

detectability, however, is highly dependent on the amount of cocaine

taken and individual rates of metabolism and excretion.

The persistence of cocaine metabolite in urine can lead to a

phenomenon referred to as “carryover.” Carryover occurs when a

single episode of cocaine use results in multiple positive urine screens.

This is particularly likely when specimens are collected frequently, at

48-hour intervals or less. When carryover occurs, it causes

overestimation of the rate of cocaine use and, thus, may diminish the

likelihood of detecting decreases in drug use in treatment studies. In

addition, there is evidence to suggest that qualitative urinalysis is a

relatively insensitive outcome measure. For example, significant

decreases in self-reported cocaine use without concomitant significant

decreases in rates of positive results from quantitative urinalysis has

been found in a number of clinical trials (Covi et al. 1994; Kolar et al.

1992). Although the possibility of underreporting of cocaine use by

cocaine users cannot be discounted (Magura et al. 1987; Sherman and

Bigelow 1992), it is also possible that cocaine metabolite carryover

obscures the true effects of treatment.

Another potential problem associated with urinalysis is the effect of

fluid intake on BE concentration. Urine dilution can occur through

normal variation in fluid consumption and excretion; however,

deliberate dilution is known to occur, particularly when drug-positive

urine specimens are linked to negative consequences. In fact, there

are commercial products marketed for the purpose of defeating urine

toxicology screen. Generally, the action of these products is based on

urine dilution, encouraging the ingestion of large amounts of liquids.

Unusually dilute specimens can be detected by measuring creatinine

concentration and specific gravity. Guidelines recommended by the

U.S. Department of Transportation for determination of abnormally

dilute urine include a measurement of creatinine concentration of less

than 20 mg/dL and a specific gravity of less than 1.003 (Goldberger et

al. 1995).

Quantitative urinalysis may be a useful alternative to qualitative

urinalysis as a primary outcome measure in clinical trials. This

approach, coupled with creatinine concentrations, can be used to

overcome problems of carryover and of urine dilution. Recently, the

authors’ laboratory examined BE and creatinine concentrations in
255

urine specimens collected in a clinical trial of a behavioral treatment

for cocaine abusers (Silverman et al. 1995, 1996) to determine the

usefulness of quantitative urine testing. Criteria for estimating

whether cocaine use has occurred during the interval between urine

specimen collections have been developed (see table 1). These new

use criteria could aid in the identification of urine specimens that are

positive due to carryover and might improve the sensitivity of

urinalysis for detecting decreases in cocaine use. This chapter

presents information on the new use criteria and the application of

those criteria to representative patients from the clinical trial.

RULES FOR NEW USE CRITERIA

The new use criteria are based on assumptions about the pharmacokinetics of BE. As noted earlier, BE rapidly appears in urine after use,

is excreted according to first-order kinetics, and has an average

elimination half-life of 7.5 hours (Ambre 1985). Urine specimens

that contain cocaine metabolite concentrations over 300 ng/mL, but

that do not meet the new use criteria, are identified as positive

specimens resulting from carryover from previous cocaine use. Urine

specimens that contain cocaine metabolite concentrations less than

300 ng/mL and that do not meet the criteria were identified as

negative. The new use criteria are summarized below.

TABLE 1. Criteria for defining new use and carryover from

quantitative urinalysis results.

Assume new use if the sample meets any of the following criteria:

RULE 1 An increase in cocaine metabolite concentration to any

value over 300 ng/mL compared to preceding urine specimen

collected at interval of more than 48 hr

RULE 2A Concentration decreased to less than one-half of

concentration in preceding urine specimen collected at interval of

more than 48 hr

RULE 2B Concentration decreased to less than one-quarter of

concentration in preceding urine specimen collected at interval of

more than 48 hr
256

TABLE 1. Criteria for defining new use and carryover from

quantitative urinalysis results (continued).

RULE 3 Cocaine metabolite is greater than 300 ng/mL in the first

urine specimen

RULE 4 If the previous urine is missing (not collected), any urine

specimen with cocaine metabolite greater than 300 ng/mL

RULE 5 Creatinine less than 20 mg/dL (does not have to be

positive for cocaine metabolite and cocaine metabolite/creatinine

ratio) is increased compared to that of previous specimen

Rule 1

Assume new cocaine use occurred for a patient when: (a) the

concentration of cocaine metabolite in the newly collected specimen

exceeds the cutoff concentration for a positive specimen (300

ng/mL), and (b) the previous specimen (collected more than 48 hours

ago) was negative (less than 300 ng/mL). This rule accounts for the

appearance of a positive specimen when previous specimens tested

negative and assumes that a new appearance of BE in the urine must

result from a new use of cocaine.

Rule 2A

Assume new cocaine use occurred for a patient when: (a) the

concentration of cocaine metabolite in the newly collected specimen

exceeds the cutoff concentration for a positive specimen (300

ng/mL), and (b) the concentration of cocaine metabolite in the newly

collected specimen has not decreased by a factor of 2 (50 percent)

below the concentration of the previous specimen (One-Half Rule).

Rule 2B

Assume new cocaine use occurred for a patient when: (a) the concentration of cocaine metabolite in the newly collected specimen exceeds

the cutoff concentration for a positive specimen (300 ng/mL), and

(b) the concentration of cocaine metabolite in the newly collected

specimen has not decreased by a factor of 4 (75 percent) below the

concentration of the previous specimen (One-Quarter Rule).
257

Rules 2A and 2B assume that urine BE should be decreased by at least

50 percent or 75 percent, respectively, if no use of cocaine has

occurred since the previous urine specimen collection at least 48

hours earlier. Two different criteria are being evaluated because of

uncertainty about the exact amount of decrease expected under the

natural conditions that exist in outpatient treatment research with

patients who self-administer large and varying amounts of cocaine.

Based on pharmacokinetic considerations of the excretion half-life of

BE determined under laboratory conditions, these criteria are quite

liberal. In fact, when a second specimen is obtained 48 hours

following a positive specimen, the concentration of cocaine

metabolite should be diminished to less than 2 percent of the original

starting concentration, assuming a half-life of 8 hours. If the cocaine

metabolite half-life is as long as 12 hours, then the concentration in

the second specimen should have diminished to less than 10 percent

of the original concentration. These liberal criteria were chosen

because significant variability in the pharmacokinetics of cocaine and

other factors can occur among individuals. An increase in BE

concentration would also be counted as a new use under either Rule 2A

or Rule 2B by the same rationale as given in Rule 1.

Rules 3 and 4

Rules 3 and 4 were developed because of practical considerations in

outpatient treatment trials. Rule 3—if the initial specimen is positive

for cocaine metabolite, it is considered a new use. Rule 4—if a

previous specimen is missing (not collected), the next collected

specimen is considered a new use if it exceeds the cutoff

concentration for a positive specimen (300 ng/mL). Rule 3 was

adopted because of the lack of a previously collected comparison

urine specimen for the first specimen collected in a trial. Rule 4 was

needed because missed urine specimens are common in clinical trials.

Under the conditions of the study in which these specimens were

collected, a missed specimen would result in a

4- to 5-day interval between the previous specimen and the new

specimen. As noted above for Rules 2A and 2B, it would be expected

that the BE concentration would have decreased to below 300 ng/mL

if no new cocaine use had occurred in that interval.

Rule 5

Assume new cocaine use occurred for a patient when: (a) a dilute

urine specimen, i.e., creatinine less than 20 mg/dL (does not have to

be positive for cocaine metabolite) is obtained, and (b) the cocaine
258

metabolite/creatinine ratio is greater than that of the previous

specimen. This rule was developed for occasions when subjects

attempt to subvert test results by ingestion of excess fluids.

URINE BENZOYLECGONINE AND CREATININE CONCENTRATIONS

IN URINE SPECIMENS OF PATIENTS IN CLINICAL TRIALS

Urine specimens from a clinical trial were used to evaluate the

potential utility of the new use criteria. Specimens had been collected

three times per week for up to 17 weeks in methadone maintenance

patients participating in a clinical trial of a behavioral treatment for

cocaine abuse (Silverman et al. 1996). The behavioral treatment was

based on an abstinence reinforcement model in which patients earned

vouchers exchangeable for goods and services for each cocainenegative urine specimen. Assays for the cocaine metabolite (BE)

concentrations were performed with TDx® Cocaine Metabolite Assay

reagents (TDx) (Abbott Laboratories, Abbott Park, IL) on a TDx

instrument according to manufacturer’s recommended procedures.

The cross-reactivity of this assay for BE was 100 percent and less

than 1 percent for cocaine, ecgonine methyl ester, and ecgonine.

The lower limit of sensitivity of the assay for cocaine metabolite was

30 ng/mL. Specimens that contained concentrations of cocaine

metabolite greater than 5,000 ng/mL were diluted with TDx reagent

buffer and reanalyzed with the appropriate control samples.

Creatinine measurements were performed by the Jaffe method with

Boehringer Mannheim Diagnostic reagents on a Hitachi 704 analyzer

(Boehringer Mannheim, Indianapolis, IN).

Visual inspection of graphs of urine BE concentrations from

individual subjects suggested that most participants used cocaine

intermittently, with cyclical patterns of high and low BE

concentrations. BE concentrations from a representative subject are

shown in figure 1 on a log scale. Concentrations greater than 300

ng/mL are indicated by circles, and concentrations less than 300

ng/mL are indicated by triangles. Horizontal lines indicate the cutoff

for the qualitative testing (300 ng/mL) and the limit of detection for

the assay (LOD; 30 ng/mL). This subject participated for a period of

approximately 13 weeks, during which there were a total of 40 urine

collections. The individual missed two urine collections, days 34 and

37, indicated by dashed lines on the figure. BE equivalent

concentrations varied over a wide range, from below 30 to 86,700

ng/mL. Of the 38 specimens collected, 34 were considered positive

(greater than 300 ng/mL), and 4 were negative (less than 300 ng/mL).
259

Application of the new use criteria to the urine BE concentrations

identified 11 of the 34 (32 percent) positive urine specimens as

possible cases of carryover by the One-Half Rule (Rule 2A), indicated

on the figure as open circles. When the new use criteria were applied

using the more stringent One-Quarter Rule (2B), two fewer specimens

were identified as carryover, specimens 13 and 15. The new use

criteria consistently identified as carryover those specimens in which

there were substantial decreases in concentration compared to the

prior specimen, but not to below the 300 ng/mL cutoff. Thus, these

cases appear to be due to carryover rather than to a new use of

cocaine between two consecutive urine specimen collections.

There were two samples, 35 and 38, that were identified as new uses

via Rule 4, the Missing Specimen Rule. If the missing specimens (34

and 37) had been ignored, and the concentration compared to the

next previous specimens (33 and 36), both specimens would have

been identified as carryover positives by the One-Half Rule (2A), but

as new uses by the One-Quarter Rule (2B). Given the circumstances

(missed clinic visits) and the continued presence of BE at

concentrations well above the 300 ng/mL level, these BE

concentrations are very likely to be due to cocaine use that occurred

after collections of specimens 34 and 37.

Rule 5 was designed to adjust for dilute urine specimens. Adulteration

by dilution was relatively rare in the clinical trial in spite of the fact

that subjects in the experimental group could earn vouchers for being

cocaine abstinent and, thus, had a relatively strong incentive for

having cocaine-negative specimens. No specimens with creatinine

concentrations below the 20 mg/dL were found in the subject whose

data are shown in figure 1; however, some cases of suspected urine

dilution were found in other subjects. BE and creatinine

concentrations for one such individual with multiple dilute urine

specimens are shown in figure 2. This participant was among the

group of subjects who could earn vouchers for cocaine- negative urine

specimens. Drug use was monitored in urine specimens throughout

the study. Test results had no programmed consequence in specimens

1 through 15; vouchers became available to subjects beginning with

the 16th specimen. This subject had three urine specimens with

creatinine concentrations at or below 20 mg/dL, the cutoff for dilute

urine. Two of those specimens (22 and 23) coincided with BE

concentrations below 300 ng/mL. The BE/creatinine ratios were

increased relative to
260

the previous urine specimens and, thus, met the criteria as new uses as

outlined in Rule 5. The suggestion that the subject used cocaine during

this period is supported by the fact that five consecutive specimens

(19 through 23) all contained BE concentrations around 200 ng/mL,

below the 300 ng/mL cutoff but well above the limit of detection of

the assay. Based on the known pharmacokinetic profile of excretion

of cocaine and BE, it is extremely unlikely that BE concentrations

would remain in the 200 ng/mL range over a period of several days

without use. Data from other subjects indicate that when cocaine use

is completely stopped, concentrations fall to below the limit of

detection within several days.

CONCLUSION

There is growing interest in the use of quantitative urine testing in

clinical trials. Changes in the pattern, frequency, and amount of use

that are not apparent from qualitative urinalysis are discernible from

quantitative urinalysis. Overestimation of drug use from carryover

also can be avoided by the development of criteria (such as the new

use
261

criteria described here) that are based on the pharmacokinetic profile

of cocaine and its metabolites. These criteria can be applied

objectively and consistently. However, quantitative urine testing is

more expensive than qualitative testing, and urine drug/metabolite

concentration can be affected by many variables such as the time

between drug use and urine collection, fluid intake, and interindividual

metabolic differences. For example, a urine specimen collected

several days after self-administration of a large amount of drug could

have the same drug/metabolite concen-tration as a specimen collected

just after self-administration of a small amount of drug. Thus, the

time of specimen collection could have greater impact on

concentration than the total amount of drug used. Fluid intake is

sometimes used by subjects to alter urine drug/metabolite

concentration. As found in the present study, however, corrections

can be made using a biological indicator such as creatinine to adjust for

water consumption. Few clinical trials have been conducted with

quantitative testing, though at least one study suggests that

quantitative testing may be more sensitive to decreases in drug use

than qualitative tests (Batki et al. 1993). McCarthy (1994) has also
262

reported on the utility of quantitative urine drug testing in the

context of substance abuse treatment. Future studies will be needed to

determine the true conditions under which quantitative analysis of

drugs in urine is useful and cost effective.

REFERENCES

Ambre, J. The urinary excretion of cocaine and metabolites in

humans: A kinetic analysis of published data. J Anal Toxicol 9:241-

245, 1985.

Batki, S.L.; Manfredi, L.B.; Jacob, P.; and Jones, R.T. Fluoxetine for

cocaine dependence in methadone maintenance: Quantitative

plasma and urine cocaine/benzoylecgonine concentrations. J Clin

Psychopharmacol 13:243-250, 1993.

Covi, L.; Hess, J.M.; Kreiter, N.A.; and Haertzen, C.A. Three models

for the analysis of a fluoxetine placebo controlled treatment in

cocaine abuse. In: Harris, L.S., ed. Problems of Drug Dependence,

1993: Proceedings of the 55th Annual Scientific Meeting, The

College on Problems of Drug Dependence, Inc. National Institute

on Drug Abuse Research Monograph 141. DHHS Pub. No.

(ADM)94-3749. Washington, DC: Supt. of Docs., U.S. Govt.

Print. Off., 1994. p. 138.

Cunningham, K.A.; Dworkin, S.I.; and Smith, J.E. Neurobiology of

cocaine: Reinforcing and stimulus effects. In: Lakoski, J.M.;

Galloway, M.P.; and White, F.J., eds. Cocaine Pharmacology,

Physiology, and Clinical Strategies. Boca Raton, FL: CRC Press,

1991. pp. 91-113.

Department of Health and Human Services. Mandatory Guidelines for

Federal Workplace Drug Testing Programs; Notice. Substance

Abuse and Mental Health Services Administration. Federal

Register 59:29908-29931, 1994.

Goldberger, B.A.; Loewenthal, B.; Darwin, W.D.; and Cone, E.J.

Intrasubject variation of creatinine and specific gravity

measurements in consecutive urine specimens of heroin users. Clin

Chem 41:116-117, 1995.

Johanson, C-E., and Schuster, C.R. Cocaine. In: Bloom, F.E., and

Kupfer, D.J., eds. Psychopharmacology: The Fourth Generation of

Progress. New York: Raven Press, Ltd., 1995. pp. 1685-1697.

Kolar, A.F.; Brown, B.S.; Weddington, W.W.; Haertzen, C.C.;

Michaelson, B.S.; and Jaffe, J.H. Treatment of cocaine dependence

in methadone maintenance clients: A pilot study comparing the

efficacy of desipramine and amantadine. Int J Addict 27:849-868,

1992.
263

Magura, S.; Goldsmith, D.; Casriel, C.; Goldstein, P.J.; and Lipton,

D.S. The validity of methadone clients’ self-reported drug use. Int

J Addict 22:727-749, 1987.

McCarthy, J. Quantitative urine drug monitoring in methadone

programs: Potential clinical uses. J Psychoactive Drugs 26:199-

206, 1994.

Saxon, A.J.; Calsyn, D.A.; Haver, V.M.; and Delaney, C.J. Clinical

evaluation of urine screening for drug abuse. West J Med 149:296-

303, 1988.

Sherman, M.F., and Bigelow, B.E. Validity of patients’ self-reported

drug use as a function of treatment status. Drug Alcohol Depend

30:1-11, 1992.

Silverman, K.; Higgins, S.T.; Brooner, R.K.; Montoya, I.D.; Cone,

E.J.; Schuster, C.R.; and Preston, K.L. Sustained cocaine abstinence

in methadone maintenance patients through voucher-based

reinforcement therapy. Arch Gen Psychiatry 53:409-415, 1996.

Silverman, K.; Higgins, S.T.; Brooner, R.K.; Montoya, I.D.; Schuster,

C.R.; and Preston, K.L. Differential reinforcement of sustained

cocaine abstinence in intravenous polydrug abusers. In: Harris, L.S.,

ed. Problems of Drug Dependence, 1994: Proceedings of the 56th

Annual Scientific Meeting of the College on Problems of Drug

Dependence, Inc. Vol. II. National Institute on Drug Abuse

Monograph 153. NIH Pub. No. (ADM)95-3883. Washington, DC:

Supt. of Docs., U.S. Govt. Print. Off., 1995.

Stitzer, M.L., and Higgins, S.T. Behavioral treatment of drug and

alcohol abuse. In: Bloom, F.E., and Kupfer, D.J., eds.

Psychopharmacology: The Fourth Generation of Progress. New

York: Raven Press, Ltd., 1995. pp. 1807-1819.

Tutton, C.S., and Crayton, J.W. Current pharmacotherapies for

cocaine abuse: A review. J Addict Dis 12:109-127, 1993.

ACKNOWLEDGMENTS

This research was funded by the National Institute on Drug Abuse

Intramural Research Program. Quantitative assays were performed by

Christopher Sheppard and Rosalind Jones; data were analyzed by Chris

Johnson and Nancy Kreiter.
264

AUTHORS

Kenzie L. Preston, Ph.D.

Chief, Clinical Trials Section

Treatment Branch

Edward J. Cone, Ph.D.

Chief, Chemistry and Drug Metabolism

Clinical Pharmacology Branch

Addiction Research Center

NIDA Intramural Research Program, NIH

PO Box 5180

Baltimore, MD 21224

Kenneth Silverman, Ph.D.

Assistant Professor

Department of Psychiatry and Behavioral Biology

Johns Hopkins University School of Medicine

5510 Nathan Shock Drive

Baltimore, MD 21224

Charles R. Schuster, Ph.D.

Professor

Department of Psychiatry

Wayne State University

2751 East Jefferson

Detroit, MI 48207
265

Is Quantitative Urinalysis More

Sensitive?*

Shou-Hua Li, Nora Chiang, Betty Tai, Charles K.

Marschke, and Richard L. Hawks

Outcome measures for assessing clinical efficacy of cocaine addiction

pharmacotherapy should reliably and accurately reflect the benefits of

the treatment. A core battery of outcome measures has been

proposed by the Food and Drug Administration (FDA) and used by

investigators for such trials. These measures include: (1) cocaine use

by urinalysis, self-report, or both; (2) retention in treatment; (3)

patient self-assessment; and (4) physician global assessment.

Currently, urinalysis is the only generally accepted surrogate

biological marker for objectively monitoring cocaine intake.

Cocaine is eliminated from the body primarily by metabolism and has

an elimination half-life of approximately 1 to 1.5 hours (Cook et al.

1985; Jones 1984). Benzoylecgonine (BE) is a major metabolite of

cocaine. Approximately 30 to 50 percent of the dose of cocaine is

excreted in the urine as BE, whereas only 2 to 3 percent is excreted in

the urine as unchanged cocaine (Ambre 1985; Cook et al. 1985;

Hamilton et al. 1977). The elimination half-life for BE of 7 hours is

much longer than that for cocaine; BE can be detected in the urine for

2 days or longer after a single dose of cocaine (Reid et al. 1995).

Therefore, BE is the most commonly screened target for assessment

of cocaine use. In general, urinary BE concentrations are highly

variable and depend on dose and route of administration,

pharmacokinetics for each individual, urine volume, and factors such

as disease state and drug interactions that may affect the

pharmacokinetics.

Qualitative urinalysis has been widely employed for detecting illicit

drug use in the workplace (Hawks and Chiang 1986). Immunoassays

such as radioimmunoassay (RIA), enzyme immunoassay (EIA), and

fluorescence polarization immunoassay (FPIA) are the most

commonly used methods for detecting BE in the urine. A BE

concentration of 300 ng/mL has been typically established as the

cutoff point. Any concentration below the

_____________________

[*A similar version of this paper has been published in

Psychopharmacology Bulletin 31(4):671-679, 1995.]
266

level of 300 ng/mL is considered a negative sample (a clean urine),

any sample that has a BE concentration above 300 ng/mL is a

positive sample (a dirty urine). This approach provides binary data

(clean or dirty).

Recently, there has been increased interest in the use of quantitative

urinalysis as an outcome measure in clinical trials. Instead of urine

samples being assessed in a binary fashion, data can be evaluated

quantitatively to assess an increase or reduction in urinary BE

concentrations. Batki and colleagues (1993), studying the effect of

fluoxetine on cocaine use, showed that qualitative urinalysis did not

reveal a statistically significant difference between the treatment and

control groups, whereas quantitative urinalysis did.

Chromatography assays such as gas chromatography/mass

spectrometry (GC/MS) provide a precise estimate of BE

concentration. However, the high cost of these assays could limit

their utility in clinical trials where a large number of urine samples are

collected. Immunoassay methods, such as FPIA and EIA, can provide

a quantitative estimate of urinary BE concentrations (Crosby et al.

1991). The quantitative immunoassay is inexpensive compared with

the chromatographic method, although it is still more costly than

qualitative urinalysis. The recent development of quantitative

techniques for automated mass screening using immunoassays has

made this approach feasible for use in clinical trials (Foltz et al., this

volume).

This study uses simulated BE data from a set of simple clinical models

to evaluate whether quantitative urinalysis is a more sensitive measure

of the reduction in frequency or amount of cocaine use than is

qualitative urinalysis. The model defined a treatment effect as a 60

percent reduction in cocaine use—either in daily amount or weekly

frequency (at the same daily amount). A 60 percent reduction in

cocaine use was considered to be clinically significant (Tai 1993). In

addition, comparison was made of urine sampling schemes of three

times per week and once per week for assessing treatment outcomes.

METHODS

Pharmacokinetic Model

Cocaine disposition can be described by a one-compartment model as

depicted in figure 1 (Ambre 1985). The pharmacokinetic parameters
267

used in this simulation were obtained from a clinical

pharmacokinetic study involving 10 subjects (Jones 1992). The

averages of the overall elimination rate constant for cocaine (k), the

urinary excretion rate constant for BE (km), and the fraction of

cocaine dose metabolized to BE (f) were 0.44 hr-1, 0.097 hr-1, and

30 percent, respectively, and the standard deviations were 0.074 hr-1,

0.020 hr-1, and 7.2 percent, respectively. The parameters of k and

km are in good agreement with those reported by Ambre (1985) and

the parameter f is in good agreement with recent reports of f values

equal to 0.22 and 0.36 by Ambre and colleagues (1988) and Jeffcoat

and colleagues (1989), respectively. The individual subjects'

pharmaco-kinetic parameters for the simulation were randomly

generated, assuming normal distribution, so that the mean and

standard deviation of the simulated group parameters matched those

calculated from the clinical pharmacokinetic study.

Assumptions

The model assumed that there were no intrasubject variations in

pharmacokinetic parameters or in urine volumes and that selfadministration was by the intravenous (IV) route. The urine flow rate

was taken as 1 mL/min (0.06 L/hr). Urinary BE concentrations were

calculated for a 9:00 a.m. sample for Monday, Wednesday, and
268

Friday. Self-dosing times were randomly assigned from 6:00 a.m. to

12 midnight throughout the study. The following equation was used

to describe the urinary BE concentrations at time t (see the

Appendix):

Simulation

Three groups of urinary BE concentrations were simulated to mimic a

12-week clinical study. Each group consisted of data from a

simulation with a sample size of 30 where the IV dose of 200 mg/day

was given for 7 days a week before the treatment period. Group A

served as a control or placebo group and groups B and C were

treatment groups. In group B, it was assumed that treatment resulted

in a reduction in the daily amount of cocaine use with no change in

the frequency. In group C, it was assumed that treatment resulted in a

reduction in the weekly frequency of use with no change in the daily

amount. A treatment effect (reduced cocaine use) was assumed to

start during week 2 and continue through week 5, after which no

further reduction would occur through week 12. The extent of the

daily dose reduction for group B was assumed to be linear and at a rate

of 15 percent per week; this reduction was equivalent to a 1 day/week

reduction for group C. Overall, this treatment assumption resulted in

an approximately 60 percent decrease in cocaine use for both groups.

The specific weekdays of cocaine use from weeks 2 to 12 were

assigned randomly for group C. Table 1 presents these dosing

assumptions.

Statistical Analysis

Because a 60 percent reduction in cocaine use was considered to be

clinically significant, it was necessary to establish statistically that

this degree of reduction could be detected in urine. The approach

taken was to assume a reduction in four increments of 15 percent

each over 4 weeks to achieve the 60 percent level and to analyze

the simulated urine concentrations at each increment to be sure

that the reduction could be detected at or before the 60 percent

point. A simple t test was used to test the difference between each

treatment group (group B or group C) and
269

TABLE 1. Assumed daily cocaine consumption as altered by

treatment.

Weeks 1 2 3 4 5 to

12

Control (A)

Daily dose (mg)

Frequency (days/week)

200

7

200

7

200

7

200

7

200

7

Treatment effects

% Reduction of weekly dose 0 15 30 45 60

Reduction in daily amount (B)

Daily dose (mg)

Frequency (days/week)

200

7

170

7

140

7

110

7

80

7

Reduction in frequency (C)

Daily dose (mg)

Frequency (days/week)

200

7

200

6

200

5

200

4

200

3

the placebo group (group A) in the quantitative urinalysis scenario for

each week. A chi-square test was used to test the difference between

each treatment group and the placebo group in the qualitative

urinalysis scenario for each week.

RESULTS

Comparison of Simulated Data and Clinical Data

Urine BE concentration simulated for a representative of group C is

presented in figure 2. The variability of the BE concentrations is

seen to increase significantly when the frequency of cocaine use

decreased starting in week 3. When cocaine use was reduced to 3 days

per week (weeks 5 to 12), the BE concentration fell below the cutoff

concentration in several samples but rebounded to concentrations

three orders of magnitude higher in the subsequent samples. These

results are similar to the large variations reported in clinical studies

(Batki et al. 1994; Crosby et al. 1991).

Table 2 presents a comparison of the BE data generated from the

simulation model with the baseline data for 50 cocaine abusers who

were methadone patients participating in a clinical trial to evaluate

fluoxetine
270

for treating cocaine addiction (Batki et al. 1994). The cocaine usage

pattern, based on self-reports by the 50 subjects before the trial

started, showed an average frequency of cocaine use of 4.8 days/week.

BE urine concentrations were simulated for two 50-subject groups

using the proposed pharmacokinetic model, but with different dosage

regimens. An IV usage pattern of 200 mg/day, 7 days/week was

assumed for the first group (as in the placebo group A of the

comparison simulations). The second group was assumed to ascribe to

the same weekly usage pattern as reported for the clinical trial but at

an IV dose of 600 mg/day.

There was a wide distribution of BE concentrations for the clinical

data, with most subjects tending toward high BE concentrations

between 10,000 and 1,000,000 ng/mL. The distribution of BE for

group A (control) was very narrow (10,001 to 100,000 ng/mL).

When a frequency of use the same as that for the clinical data was

assumed and the daily dose increased to 600 mg, the BE distribution

for these simulated data was similar to the clinical data.

TABLE 2. Urinary benzoylecgonine concentrations for simulated

and clinical data (sample size = 50).
271

Urine BE

concentrations

(ng/mL) 0-300 301-1,000

1,001-

10,000

10,001-

100,000

100,001-

1,000,000

Clinical data* 4 5 7 19 15

Simulated data

based on 200 mg

daily use

0 0 4 46 0

Simulated data

based on 600 mg

and Batki’s selfreport pattern

4 1 7 25 13

KEY: * = Clinical data provided by Batki et al. (1994) with the

following frequency of use pattern from self-report.

Days/week of cocaine use 0 1 2 3 4 5 6 7

# of subjects 1 3 3 7 7 6 6 17

The mean and standard deviation of the clinical data

(86,000Å118,000 ng/mL) was much larger than for the simulated

control group (32,000 Å 16,000 ng/mL) but closer to those for the

simulated data (74,000Å78,000 ng/mL) using a larger dose and the

same usage pattern of the clinical data. The coefficient of variation

for the clinical data (137 percent) was slightly larger than that for the

simulated data (105 percent) in the second case. This variance might

be expected because the subjects in the clinical trial would likely use

various amounts of cocaine and routes of administration. The similar

mean and similar pattern of BE distribution for the simulated and

clinical data support the assumption that the pharmacokinetic model

is valid.

Quantitative Urinalysis

Table 3 presents the weekly group mean and the standard error for

urinary BE concentrations for a urine sampling schedule of three

times
272

TABLE 3. Weekly group mean for urine benzoylecgonine

concentration simulated for three times per week sampling.

Week

Control

Group (A)

Reduction in Daily

Amount (B)

Reduction in

Frequency (C)

1 31,984

(2165)*

32,079

(2031)

29,738

(2238)

2 26,944

(2180)

28,832

(1844)

29,596

(1924)

3 29,510

(2477)

25,620

(1739)

25,193

(3004)

4 30,514

(2051)

18,002**

(1095)

21,346**

(2161)

5 37,342

(2719)

14,199**

(957)

16,131**

(1914)

6 34,592

(2850)

13,691**

(1186)

11,308**

(1157)

7 37,633

(3199)

13,134**

(883)

15,092**

(1828)

8 33,783

(2062)

13,970**

(1408)

15,666**

(2479)

9 31,944

(2371)

14,622**

(1153)

20,373**

(2309)

10 35,121

(2756)

14,360**

(954)

12,649**

(1722)

11 30,753

(2313)

12,614**

(983)

15,071**

(2144)

12 30,591

(2458)

11,704**

(796)

17,320**

(2004)

KEY: * = Standard error; ** = significantly different from group A,

p < 0.05.

per week. The simulated BE values for each week were determined as

the mean of the BE concentrations on Monday, Wednesday, and

Friday for the week. A statistically significant difference (p < 0.05)

was shown between the control group and the treatment groups in

week 4 when a 45 percent reduction in the weekly dose was reached—

in daily amount of cocaine used (group B) or in frequency of use

(from 7 days to 4 days per week, group C). The weekly mean for BE

concentrations was similar for groups B and C. The standard errors

for group C were about twice those for group B when the reduction in
273

the weekly dose reached 30 percent (at week 3). This reduction is a

result of the large fluctuation resulting from the variations in the

interval between dosing and sampling.

Table 4 presents the weekly data for urinary BE concentrations for a

sampling schedule of once a week. The Monday samples were used.

The weekly means for group B were similar to those for group C,

whereas the standard errors for group B were smaller than those for

group C. A statistically significant difference could be detected

between either treatment group (group B or group C) and the control

group (group A) when there was a 60 percent reduction in the weekly

dose (week 5). The statistical difference was observed for every week

from weeks 5 to 12 of group B. However, group C failed to show a

statistical difference for weeks 9 and 12 even though the reduction

had occurred from week 5 on as a result of the large variability for the

BE data for group C.

When the data for the two sampling schedules (one time and three

times per week) were compared, the means for each corresponding

group were similar, but the standard errors for one time per week

sampling were much larger than those for the three times per week

sampling (figures 3 and 4). A further reduction in cocaine use of 15

percent (from 45 percent to 60 percent or fourth week to fifth in the

figures) was required to detect the statistical difference for the one

time per week sampling because of the large variations of the weekly

BE concentrations associated with one time per week sampling. The

weekly mean of three samples would smooth out these variations.

The reduction in daily amount of cocaine use curve (figure 3) had a

smoother curve than the reduction in frequency curve (figure 4) after

week 5.

Qualitative Urinalysis

Figure 5 presents the weekly percentage of positive (dirty) urine

samples for the three times per week urine collection schedule

using the “majority rule” analysis. This analysis, widely used in

clinic trials, assumes the weekly urine is dirty if at least two of the

three samples for the week are positive. Group A (control) and

group B (reduction in amount) always presented 100 percent

positive samples with no significant difference (chi-square test)

between them. However, a significant difference was observed

between groups C and A for 5 of the 8 weeks when the
274

TABLE 4. Weekly group mean for urine benzoylecgonine

concentration simulated for once a week sampling.

Week

Control

Group (A)

Reduction in Daily

Amount (B)

Reduction in

Frequency (C)

1 33,814

(3162)*

37,674

(3745)

29,566

(3404)

2 28,414

(4325)

31,753

(3012)

32,373

(2872)

3 33,231

(4438)

29,613

(3014)

28,256

(4785)

4 31,204

(3910)

21,684

(1985)

24,525

(3587)

5 37,768

(5637)

16,929**

(1758)

19,684**

(3560)

6 36,626

(4967)

13,569**

(1729)

8946**

(2277)

7 31,270

(4013)

13,692**

(1334)

10,183**

(2432)

8 32,969

(3725)

15,738**

(2103)

14,460**

(4004)

9 32,440

(4293)

15,419**

(1996)

23,818

(4061)

10 36,516

(4391)

17,931**

(1723)

9755**

(2313)

11 27,696

(2684)

13,566**

(1581)

16,307**

(2907)

12 27,805

(2904)

9432**

(867)

18,766

(4057)

KEY: * = Standard error; ** = significant different from group A, p

< 0.05.

frequency of use of group C was reduced to three times per week

(weeks 5 to 12).

Because groups A and B presented 100 percent positive samples all

the times, neither a thrice-weekly nor a once-weekly sampling

schedule for
275

qualitative urinalysis could detect the difference in the amount of

daily dose between these two groups.

Figure 6 compares the percentage of positive (dirty) urine samples for

group A and group C using (1) the one time a week sampling schedule,

(2) the three times per week schedule using the majority rule analysis,

and (3) the three times per week schedule using the actual percentage

of positive urine samples. Group A presented 100 percent positive

urines at all times. For group C, the data using the majority rule for

the three times
276

per week schedule always gave the highest estimates for the

percentage of positive urines, higher than did the actual percentage of

positive samples. The one time per week sampling could give either

higher or lower estimates than the actual percentage of dirty urines.

When the frequency of use was reduced to three times per week (week

5), a significant difference was detected between the treatment (group

C) and control (group A) groups for all the remaining 8 weeks using

the actual data for three times per week sampling. Group C differed

significantly from
277

group A in 6 of 8 weeks when one time per week sampling was

simulated. This difference was reduced to 5 of 8 weeks when the

majority rule analysis was used for the three times per week schedule.

DISCUSSION

Urinary data in general are not a very sensitive marker for the

assessment of cocaine use and vary widely because of the differences

in the amount of cocaine used, the frequency of use, the route of

administration (intranasal, oral, or smoking), the urine volume (urine

flow rate), sampling times, and factors such as disease state and

concomitant medications. In addition, there are intraindividual

differences in these parameters from day to day. It is difficult to use

urine data to estimate the frequency and amount of cocaine use.

Depending on the frequency of urine sampling and the pattern of

cocaine use (daily versus binge use), a
278

negative urine sample may not indicate a lack of cocaine use, and a

positive urine sample may reflect the carryover effects of an episode

several days before sampling.

Cocaine is usually administered by an intranasal, IV, or smoked route

of administration. The absorption is different for the different routes

of administration, which results in different urinary excretion profiles

after a single dose (Cook et al. 1985; Jeffcoat et al. 1989; Jones 1984;

Jones, this volume). Intranasal absorption is slow and the

bioavailability is approximately 40 to 80 percent. Smoking provides

a rapid absorption but low bioavailability (approximately 20 to 45

percent). The pharmaco-kinetic profile for smoking is similar to that

for IV administration, but a much larger dose is required to achieve the

same plasma and urine concentrations. Because of the wide range of

street doses a subject may have used as well as the uncertainty of when

the dose was taken, similar urinary BE concentrations were observed

for cocaine addicts following different routes of administration.

Because the IV dose provides a simple pharmacokinetic model, it was
279

chosen for the simulation. A dose of 200 mg was used because the

pharmacokinetic parameters were derived from a clinical

pharmacokinetics study using this dose. In addition, the urinary BE

after this dose can be detected (using the 300 ng/mL cutoff) for 2 to 3

days, which is consistent with the report that the detection window

for BE is 1 to 2 days after a regular cocaine dose.

These simulated data were based on a simple clinical situation with an

ideal homogeneous patient population with the same usage pattern,

dose, and route of administration. The only variables were the dosing

times and individual pharmacokinetic parameters. In actual clinical

settings, urinary BE concentrations are more variable, as noted in the

Results section in which a coefficient of variation calculated for actual

clinical data (137 percent) was much larger than that for the two

simulated cases (105 percent and 50 percent). Because the number of

subjects required to detect a specified reduction in cocaine use depends

on the variability of the BE concentrations, a sample size of 30 for

each group would be too small to detect any difference between the

treatment and the control groups in actual clinical situations. Based

on the BE concentrations in the clinical data of Batki and colleagues

(1993), the number of subjects required to detect a 60 percent

reduction in cocaine use at a significance level of 0.05 and with a

power of 80 percent would be 90 subjects per group. If a power of 95

percent is required, the number of subjects would have to increase to

140 per group. It should be noted that these estimates of group size

are based on this single clinical data set (that of Batki et al.)—the

only one available to the authors.

Two hypothetical situations were used to compare the treatment

effects: a change in daily amount of use and a change in frequency of

use. All the individuals were assumed to be equally affected by the

treatment. In an actual situation, the treatment group would be a

mixture of subjects, some of whom would manifest a reduction in

amount used, some in frequency, and others showing no change in

habits. The magnitude of the individual reductions and the time

required to reach and maintain those concentrations would be

expected to be variable across subjects and to further complicate the

detection of treatment outcome. For instance, if a treatment has a

significant effect on a small segment of the group leading perhaps to

cessation of use, an analysis based on the average across the group

might not be able to detect any significant difference from the

control group, but an obvious subgroup might emerge if the analysis

includes an assessment of consecutive negative urine days or weeks.
280

For this simulation, qualitative urinalysis could not detect a reduction

in the amount of daily dose for daily users but could detect a reduction

in the frequency of cocaine use from 7 to 3 days per week. Urinary

BE concentration depends on dose, route of administration,

pharmacokinetics, and sampling time. If a large dose is used and the

frequency of use is reduced from daily to every other day on those

days (e.g., Sunday, Tuesday, and Thursday) preceding the sampling

days (rather than randomly assigned), it is possible for the subjects to

have positive results all the time. If a homogenous group of heavy

daily cocaine users participates in the clinical trial, qualitative

urinalysis is less likely to show a statistically significant decrease even

though there is a reduction of cocaine use from 7 to 3 times per week

(every other day). On the other hand, if the cocaine dose is lower or

the cocaine use less frequent, negative results may occur even if there

is less than a 60 percent reduction of frequency of cocaine use. In

clinical situations, there will be a heterogeneous population and it is

likely that statistically significant results can be detected by

qualitative analysis if enough subjects are used. Quantitative urinalysis

would be more powerful than qualitative urinalysis in clinical trials for

detecting reductions in both frequency and in amount.

From the clinical aspect, a period of sustained abstinence, not the

reduction of drug amount, might be the most acceptable therapeutic

goal. If the efficacy criterion is to demonstrate an increase in the

number of days of abstinence, then the only acceptable therapeutic

goal is a reduction in frequency, not in daily dose; qualitative

urinalysis as the outcome measure would probably be able to meet this

goal and quantitative urinalysis would provide only a limited

advantage. On the other hand, a reduction in dose only and not

frequency would appear to require quantitative analysis.

Currently, the most popular sampling schemes for urine collection are

either three times per week (Monday, Wednesday, and Friday) or

once a week. This simulation indicates that a three times per week

schedule is more powerful than a one time per week schedule in

detecting a treatment effect using quantitative urinalysis data. This

indication is in agreement with the report by Cone and Dickerson

(1992) that the most efficient testing schedule for judging the

outcome for a cocaine medication trial would be three times per week.

For qualitative urinalysis, a one time per week sampling schedule could

underestimate or overestimate the positive samples compared with

the actual data for the three times per week schedule. Because a

conservative approach is generally taken for the assessment of
281

clinical efficacy, a three times per week schedule would seem

preferable, even though the majority rule approach always provides

an artificially higher estimate of percentage positive samples. The

use of actual data, which is not commonly practiced in clinical trials,

appears to be advantageous and its utility in clinical trials should be

considered.

CONCLUSION

A simple simulation model was used to study the advantages and the

limitations of quantitative versus qualitative urinalysis for daily

cocaine abusers with an assumed reduction of cocaine use up to 60

percent. In addition, one time per week versus three times per week

urine sampling schedules for the assessment of treatment outcomes

were compared. The following general conclusions can be made based

on this simplified model of simulation:

• Qualitative urinalysis using a cutoff concentration of 300

ng/mL is capable of statistically detecting a reduction in frequency

of daily cocaine use, although it is less powerful than that from the

quantitative analysis. Qualitative analysis cannot detect significant

differences in reduction in the daily amount of use.

• Quantitative urinalysis is capable of detecting reductions both

in frequency and amount of cocaine use. Quantitative urinalysis is

more sensitive in detecting a reduction in the daily amount than a

reduction in the frequency when the reduction is greater than 30

percent.

For quantitative urinalysis, a three times per week urine collection

schedule provides more statistical power than does a one time per

week collection.

For qualitative urinalysis, the majority rule analysis for a three times

per week schedule provides a higher estimate of percentage positive

samples than is actually the case. The one time per week schedule

could give either higher or lower estimated percentage positive

samples. Sampling and analysis of three times per week sampling

would seem to be the preferable approach.

Finally, it is abundantly clear from this exercise that an increasing

database of actual quantitative clinical urine values will greatly

enhance the potential for developing more realistic simulations,
282

which in turn will enhance the design and analysis of outcome data in

future clinical trials.

REFERENCES

Ambre, J.J. The urinary excretion of cocaine and metabolites in

humans: A kinetic analysis of published data. J Anal Toxicol

9:241-245, 1985.

Ambre, J.J.; Ruo, T.I.; Nelson, J.; and Belknap, S. Urinary excretion

of cocaine, benzoylecgonine, and ecgonine methyl ester in

humans. J Anal Toxicol 12:301-306, 1988.

Batki, S.L.; Manfredi, L.B.; Jacob, P.; and Jones, R.T. Fluoxetine for

cocaine dependence in methadone maintenance: Quantitative

plasma and urine cocaine/benzoylecgonine concentrations. J Clin

Psychopharmacol 13:243-250, 1993.

Batki, S.L; Washburn, A.; Manfredi, L.; Murphy, J.; Herbst, M.D.;

Delucchi, K.; Jones, T.; Nanda, P.; Jacob, P., III; and Jones, R.T.

Fluoxetine in primary and secondary cocaine dependence:

Outcomes using quantitative benzoylecgonine concentration. In:

Harris, L.S., ed. Problems of Drug Dependence, 1993:

Proceedings of the 55th Annual Scientific Meeting, The College

on Problems of Drug Dependence, Inc. National Institute on

Drug Abuse Research Monograph 141. DHHS Pub. No. (ADM)94-

3749. Washington, DC: Supt. of Docs., U.S. Govt. Print. Off.,

1994. p. 140.

Cone, E.J., and Dickerson, S.L. Efficacy of urinalysis in monitoring

heroin and cocaine abuse patterns: Implications in clinical trials

for treatment of drug dependence. In: Jain, R.B., ed. Statistical

Issues in Clinical Trials for Treatment of Opiate Dependence.

National Institute on Drug Abuse Research Monograph 128.

DHHS Pub. No. (ADM)92-1947. Washington, DC: Supt. of Docs.,

U.S. Govt. Print. Off., 1992. pp. 46-57.

Cook, C.E.; Jeffcoat, A.R.; and Perez-Reyes, M., Pharmacokinetic

studies of cocaine and phencyclidine in man. In: Barnett, G., and

Chiang, C.N., eds. Pharmacokinetics and Pharmacodynamics of

Psychoactive Drugs. Foster City, CA: Biomedical Publications,

1985. pp. 48-74.

Crosby, R.D.; Halikas, J.A.; and Bowers, L.D. Quantitative cocaine

urine testing in clinical research settings. Ann Clin Psychiatry

3:243-249, 1991.

Gilbaldi, M., and Perrier, D. Pharmacokinetics. New York: Marcel

Dekker, 1982.
283

Hamilton, H.E.; Wallace, L.E.; Shimek, E.L., Jr.; Land, P.; Harris,

S.C.; and Christenson, J.G. Cocaine and benzoylecgonine

excretion in humans. J Forensic Sci 22:697-707, 1977.

Hawks, R.L., and Chiang, C.N., eds. Urine Testing for Drugs of Abuse.

National Institute on Drug Abuse Research Monograph 73. DHHS

Pub. No. (ADM)87-1481. Washington, DC: Supt. of Docs., U.S.

Govt. Print. Off., 1986.

Jeffcoat, A.R.; Perez-Reyes, M.; Hill, J.M.; Sadler, B.M.; and Cook, E.

Cocaine disposition in human after intravenous injection, nasal

insufflation or smoking. Drug Metab Dispos 17:153-159, 1989.

Jones, R.T. Cocaine: The pharmacology of cocaine. In: Grabowski,

G., ed. Pharmacology Effects and Treatment of Abuse. National

Institute on Drug Abuse Research Monograph 50. DHHS Pub. No.

(ADM)84-1326. Washington, DC: Supt. of Docs., U.S. Govt.

Print. Off., 1984. pp. 34-53.

Jones, R.T. National Institute on Drug Abuse contract report no. 271-

87-8123, 1992.

Reid, K.; Peters, J.E.; Chou, J.; Borg, L.; and Kreek, M.J. Quantitative

measurement of benzoylecgonine as a marker for relapse to

cocaine abuse. In: Harris, L.S., ed. Problems of Drug Dependence,

1994: Proceedings of the 56th Annual Scientific Meeting of the

College on Problems of Drug Dependence, Inc. Vol. II. National

Institute on Drug Abuse Research Monograph 153. NIH Pub. No.

(ADM)95-3883. Washington, DC: Supt. of Docs., U.S. Govt.

Print. Off., 1995. p. 331.

Tai, B. Clinical Decision Network of Cocaine Addiction

Pharmacotherapy: Summary Report. National Institute on Drug

Abuse, 1993.

ACKNOWLEDGMENT

The authors gratefully acknowledge Steven L. Batki, M.D., and his

collaborators at the University of California, San Francisco,

Department of Psychiatry, Drug Dependence Clinical Research

Program and the San Francisco General Hospital Substance Abuse

Services, for their valuable assistance in providing the urine

benzoylecgonine data from their research program.
284

AUTHORS

Shou-Hua Li, Ph.D.

Statistician

Clinical Trials Branch

Nora Chiang, Ph.D.

Pharmacokineticist

Chemistry and Pharmaceutics Branch

Betty Tai, Ph.D.

Chief

Regulatory Affairs Branch

Charles K. Marschke, B.S.

Chemist

Chemistry and Pharmaceutics Branch

Richard L. Hawks, Ph.D.

Chief

Chemistry and Pharmaceutics Branch

Medications Development Division

National Institute on Drug Abuse, NIH

Parklawn Building, Room 11A-55

5600 Fishers Lane

Rockville, MD 20857
285

APPENDIX

The cumulative amount (M) of benzoylecgonine (BE) excreted in the

urine until time t is described by the equation (1.48) of Gibaldi and

Perrier (1982). The following for M is obtained by rearranging the

equation.

M=(k*f*dose)*(km*(l-e

-k*t

)-k*(l-e

-km*t

)) / k*(km-k) (1)

Assuming the urine is collected during t1 and t2, t is defined as the

midtime between t1 and t2. In this simulation, 9 a.m. is assumed to be

the midtime (t) and the collection period is assumed to be 2 hours.

t2 -t1= 2 (2)

t2= t + 1 (3)

t1 = t - 1 (4)

The cumulative amount of BE excreted in the two consecutive

sampling times, t1 and t2, is given by:

M(t2)=(k*f*dose)*(km*(l-e

-k*(t+l)

)-k*(l-e

-km*(t+l)

)) / k*(km-k) (5)

and

M(t2)=(k*f*dose)*(km*(l-e

-k*(t+l)

)-k*(l-e

-km*(t+l)

)) / k*(km-k) (6)
286

Amount of BE excreted for the mid-time t, É M, is the amount

collected during t2 and t1. É M equals to M (t2) - M (t1) and is given by

subtracting equation 6 from equation 5.

M=(k*f*dose)*(km*e

-(k*t)

 *( e

 k

 -e

(-k)

)-k*e 

-(km*t)

 *( e

 km

 -e

(-km)

) / k*(km-k) (7)

Urinary flow rate is assumed to be 1 mL/min or 0.06 L/hr. The urine

volume for the 2-hour interval is (0.06*2). The BE concentration at

time t obtained by dividing equation 7 by the urine volume (0.06*2)

yields

(BE)t=(k*f*dose)*(km*e

-(k*t)

 *( e

 k

 -e

(-k)

)-k*e 

-(km*t)

 *( e

 km

 -e

(-km)

) (8)

/ k*(km-k)*(0.06*2)
287

Comparison of Immunoassays for

Semiquantitative Measurement of

Benzoylecgonine in Urine

Rodger L. Foltz, Christine Botelho, Scott A. Reuschel,

David J. Kuntz, David E. Moody, and Gloria M. Bristow

INTRODUCTION

One way of monitoring the effectiveness of a treatment for cocaine

addiction is to analyze a patient’s urine at regular intervals for

benzoylecgonine (BE), the major metabolite of cocaine. Total

absence of BE from the urine indicates that the patient has stopped

using cocaine, while a significant reduction in the urinary

concentration of BE indicates that the patient is using less cocaine,

and therefore is receiving some benefit from the treatment. To

determine if there has been a reduction in the amount of cocaine used,

it is necessary to employ a quantitative, or at least semiquantitative,

method of analysis. However, because many factors can affect the

concentration of a drug or any of its metabolites in urine,

determination of urine concentrations can only provide an

approximate indication of the amount of drug recently introduced

into the body.

Analysis of urine for drugs of abuse most often involves an initial

screening by an immunoassay to determine the presence or absence of

the drug or its metabolites. If the drug is shown to be present by the

immunoassay, a quantitative assay is often performed by gas chromatography/mass spectrometry (GC/MS). However, the cost of the

GC/MS confirmation assay is high relative to the cost of an

immunoassay screening test, and may be prohibitive where multiple

specimens from each patient are to be analyzed.

The purpose of this study was to determine the feasibility of using a

relatively inexpensive immunoassay to quantitatively determine the

concentration of BE in urine from patients undergoing treatment for

cocaine addiction.

Three different types of immunoassays were evaluated: (1) an

enzyme immunoassay (EIA), (2) a fluorescence polarization

immunoassay (FPIA), and (3) a kinetic interaction of microparticles
288

in solution immunoassay (KIMS). The antibodies used for each of the

immunoassays were raised against BE, the major metabolite of

cocaine. However, the study included determination of the crossreactivity of each of the immunoassays to cocaine, ecgonine methyl

ester, and ecgonine; each of these compounds can be present in the

urine of a cocaine user in significant concentrations, a fact

substantiated by quantitative GC/MS measurement of cocaine,

norcocaine, BE, ecgonine methyl ester, and ecgonine in 39 urine

samples previously shown to be positive for cocaine metabolites.

It was also important to determine the range of BE concentrations

that could be measured by each of the immunoassays without

performing a dilution, to indicate the number of dilutions that would

be required to cover the range of BE concentrations anticipated in the

urine from cocaine users.

Finally, the BE concentrations determined by GC/MS in urine samples

from cocaine users were compared to the BE concentrations

determined by each of the three immunoassays.

EXPERIMENTAL SECTION

Immunoassays

The EIA and KIMS analyses were performed at Northwest

Toxicology, Inc., on a Hitachi 717 autoanalyzer. The EIA employed

the Syva EMIT II cocaine reagents, while the KIMS used the Roche

Diagnostics ONLINE cocaine reagents. Both immunoassays were

performed according to manufacturers’ recommended procedures

except that 6-point calibration curves were used (0, 150, 300, 600,

1,000, and 2,000 ng/mL of BE). The FPIA analyses were performed

at the Center for Human Toxicology, University of Utah, on an

Abbott TDx analyzer using the Abbott TDx cocaine reagents and

recommended procedure. For the immunoassay linearity study and

the comparison of BE concentrations as determined by each of the

immunoassays, samples were analyzed undiluted, after either 1:7 or

1:10 dilutions, and after 1:100 dilutions.
289

Gas Chromatography/Mass Spectrometry (GC/MS)

Urine concentrations of cocaine, norcocaine, BE, ecgonine methyl

ester, and ecgonine were determined by GC/MS analysis performed at

Northwest Toxicology using an extraction procedure similar to that

reported in two recent publications (Okeke et al. 1994; Peterson et al.

1995). Deuterium-labeled isotopomers for each of the analytes were

added to the urine samples as internal standards. The concentrations

of the deuterated internal standards were: BE-2H3 and cocaine-2H3,

each 100 ng/mL; norcocaine-2H3, ecgonine methyl ester-2H3, and

ecgonine- 2H3, each 50 ng/mL. The pH of the urine was made acidic

by addition of 0.1 M acetate buffer (pH 4.0) and the cocaine and

metabolites were extracted on Bond Elute LRC-SCX cation exchange

solid-phase columns. The extraction columns were conditioned by

washing with 2 mL of methanol followed by 2 mL of 0.1 M acetate

buffer. After 1 mL of urine sample was added to each column, the

columns were washed with 2 mL of 0.1 M HCl and 4 mL of methanol.

The cocaine and metabolites were then eluted with 3 mL of

methanol:ammonium hydroxide (98:2) freshly prepared just before

using. The metabolites in each extract were derivatized by heating at

70 %C with 100&L of hexafluoroisopropyl alcohol and 100&L of

pentafluoropropionic anhydride for 30 minutes. The derivatized

extracts were then analyzed by GC/MS using a 5 percent phenyl

methylsilicone fused silica capillary column (J&W Scientific, DB5MS,

12.5m x 0.2mm ID with a 0.33 m film thickness) temperature

programmed from 135 to 250 %C at 15 %C/min. The analytes were

detected by electron ionization with selected ion monitoring

performed on a Finnigan SSQ7000 GC/MS system. The ions

monitored for each analyte and internal standard and the retentiontime windows during which each set of ions was monitored are listed in

table 1.

The concentrations of the analytes were determined from the ratio of

the peak area of each analyte to the peak area of its corresponding

deuterated internal standard; these ratios were compared with 6-point

calibration curves that were generated from the analysis of urine

fortified with known concentrations of the analytes and the internal

standards.

The lower limit of quantitation for each analyte was 5 ng/mL.
290

TABLE 1. GC/MS data for cocaine, derivatized metabolites, and

their internal standards.

Analytes and Internal

Standards

Retention Time

Windows

M/Z of Ions

Monitored

Derivatized ecgonine 1.0 - 2.15 min. 318

Derivatized ecgonine-2H3 1.0 - 2.15 min. 321

Derivatized EME 2.15 - 3.2 min. 345

Derivatized EME-2H3 2.15 - 3.2 min. 348

Derivatized BE 5.7 - 6.9 min. 439

Derivatized BE-2H3 5.7 - 6.9 min. 442

Derivatized norcocaine 6.9 - 9.0 min. 105

Derivatized norcocaine2H56.9 - 9.0 min. 110

Cocaine 6.9 - 9.0 min. 303

Cocaine-2H3 6.9 - 9.0 min. 306

RESULTS AND DISCUSSION

Benzoylecgonine Concentrations Quantifiable by the

Immunoassays

Each of the immunoassays in this study is intended to be used to

determine the presence of BE above or below a “cutoff”

concentration of 300 ng/mL. To determine the range of linearity of

each of the immunoassays, drug-free urine was fortified with known

concentrations of BE ranging from 100 ng/mL to 200,000 ng/mL.

Each fortified urine sample was analyzed in triplicate by each of the

immunoassays using a 5-point calibration curve. Aliquots of each

urine sample were also analyzed in triplicate by the EIA and KIMS

immunoassays after either 1:10 or 1:100 dilution with drug-free urine.

Only undiluted urine aliquots were analyzed by the FPIA. Table 2

compares the BE concentrations determined by each of the

immunoassays with the concentrations determined by GC/MS and with

the target (weighed-in) concentrations. The concentrations

determined by EIA and KIMS in undiluted aliquots were in reasonable
291

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ntrations from 100 to 1,000 ng/mL, while the acceptable

BE Target

Conc. GC/MS

EIA

Undil. 1:10 dil. 1:100 dil. Undil.

100 116 131 137

200 235 282 230

500 519 620 531

1,000 1,075 1,143 1,117 1,038

2,000 2,147 2,363

5,000 5,175 6,113 5,700

10,000 10,096 10,927 12,400

20,000 20,419 30,433

50,000 50,454 71,867

100,000 107,870 125,000

200,000 266,885 277,400
292

concentrations determined by FPIA for undiluted aliquots extended to

2,000 ng/mL. By appropriate dilution, the range of acceptable

agreement between GC/MS-determined concentrations and the EIAand KIMS-determined concentrations extend to 100,000 ng/mL. It is

reasonable to assume that analysis of diluted aliquots by FPIA would

give comparable results.

Cross-Reactivities of the Immunoassays

To determine the cross-reactivities of each of the immunoassays,

drug-free urine was fortified with either cocaine, ecgonine methyl

ester, or ecgonine at concentrations ranging from 100 ng/mL to 1

mg/mL. Each fortified urine sample was analyzed in triplicate by each

of the immuno-assays. Immunoassay responses equivalent to less

than 50 ng/mL were considered below the limit of quantitation of the

immunoassay and were reported as not detected (ND). The average

percent cross-reactivities, calculated by dividing the indicated BEequivalent concentration by the actual concentration of cocaine or

the cocaine metabolite, are listed in table 3.

The percent cross-reactivities for the three immunoassays are similar

and are all quite low, particularly at the higher analyte concentrations.

Therefore, the measurement of BE in urine should not be significantly

affected by cross-reactivity to the concentrations of cocaine,

ecgonine methyl ester, and ecgonine, which are likely to be present in

urine from cocaine users. The cross-reactivities of the immunoassays

to norcocaine were not determined because the concentrations of this

metabolite in urine are negligible.

Concentrations of Cocaine and Its Metabolites in Urine

From Cocaine Users

The metabolism of cocaine in man has been extensively studied

(Ambre et al. 1988; Jatlow 1988; Jindal and Lutz 1986; Jones

1984; Zhang and Foltz 1990). Ambre reported that after

intravenous infusion of cocaine to five subjects, an average of 16

percent of the dose was excreted in the urine as BE, 15 percent as

ecgonine methyl ester, and 2 percent as unchanged cocaine. In

that study, as in most published investigations of the metabolism

of cocaine, ecgonine concentrations were not determined due to

analytical difficulties in measuring this very hydrophilic

metabolite. In order to gain further insight into the relative

concentrations of cocaine
293

TABLE 3. Cross-reactivities of immunoassays.

Spiked Conc.

(ng/mL)

Percent Cross-Reactivities

Cocaine Ecgonine EME

KIMS BE Assay:

100

200

500

1,000

2,000

5,000

10,000

20,000

50,000

100,000

200,000

500,000

1,000,000

ND

ND

ND

ND

3.1%

2.1%

1.8%

1.5%

1.1%

1.0%

1.0%

1.1%

ND

ND

ND

5.7%

4.4%

2.7%

1.8%

1.4%

1.0%

0.9%

1.3%

ND

ND

ND

ND

ND

ND

ND

0.2%

0.1%

0.1%

0.0%

0.0%

Ave. % CrossReactivity = 1.6% 2.4% 0.1%

EIA BE Assay:

100

200

500

1,000

2,000

5,000

10,000

20,000

50,000

100,000

200,000

500,000

1,000,000

ND

ND

ND

ND

ND

1.3%

1.6%

1.7%

1.3%

1.4%

1.2%

1.5%

1.4%

ND

ND

ND

ND

ND

ND

0.6%

0.7%

0.9%

0.7%

0.9%

0.8%

0.7%

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

0.0%

Ave. % CrossReactivity = 1.4% 0.8% 0.0%
294

TABLE 3. Cross-reactivities of immunoassays (continued).

Spiked Conc.

(ng/mL)

Percent Cross-Reactivities

Cocaine Ecgonine EME

FPIA BE Assay:

100

200

500

1,000

2,000

5,000

10,000

20,000

50,000

100,000

200,000

500,000

1,000,000

ND

ND

ND

ND

ND

ND

ND

ND

1.6%

1.6%

1.6%

ND

ND

ND

ND

ND

ND

ND

ND

1.5%

1.5%

1.5%

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

Ave. % CrossReactivity = 1.6% 1.5% 0.0%

and its metabolites in urine from cocaine users, a newly developed GC/MS

assay for cocaine, norcocaine, BE, ecgonine methyl ester, and ecgonine was

used to analyze urine samples that had been previously found to be positive

for cocaine metabolites. Table 4 lists the measured concentrations of

cocaine and three of its metabolites in 39 urine samples. Norcocaine was

also measured, but its concentrations are not listed in the table because most

of them were below the limit of quantitation. The average concentrations

of each compound expressed as a percent of the concentration of BE were:

cocaine, 3.0 percent; norcocaine, 0.2 percent; ecgonine methyl ester, 19.1

percent; and ecgonine, 46.8 percent. However, the concentrations relative

to the concentration of BE varied widely (cocaine, 0 to 16 percent;

norcocaine, 0 to 2 percent; ecgonine methyl ester, 0 to 83 percent; and

ecgonine, 0 to 215 percent).

Comparison of Benzoylecgonine Concentrations in Donor

Samples Determined by GC/MS and Each of the Immunoassays

Table 5 compares the concentrations of BE in the 39 donor urine samples

as determined by GC/MS and by each of the immunoassays.
295

TABLE 4. GC/MS measured concentrations of BE, cocaine, ecgonine

methyl ester, and ecgonine in urine from cocaine users.

BE Cocaine EME Ecgonine

(g/mL) (g/mL) % of

BE

(g/mL) % of

BE

(g/mL) % of

BE

0.27 0.05 16.9% 0.17 60.7% 0.13 48.9%

0.29 0.04 12.1% 0.24 82.7% 0.20 70.2%

0.30 0.02 6.7% 0.21 69.3% 0.26 85.3%

0.32 0.02 5.7% 0.09 27.3% 0.17 52.7%

0.34 <LOQ 0.0% <LOQ 0.0% <LOQ 0.0%

0.36 <LOQ 0.0% 0.06 17.8% 0.77 215.0%

0.36 <LOQ 0.0% <LOQ 0.0% <LOQ 0.0%

0.38 <LOQ 0.0% <LOQ 0.0% 0.01 2.9%

0.41 0.01 3.2% <LOQ 0.0% 0.01 2.5%

0.41 <LOQ 0.0% 0.01 2.9% 0.34 84.0%

0.45 0.01 2.4% 0.07 16.1% 0.30 66.7%

0.46 <LOQ 0.0% <LOQ 0.0% <LOQ 0.0%

0.55 <LOQ 0.0% 0.11 19.0% 0.29 52.9%

0.69 0.01 2.0% 0.09 12.9% 0.35 50.5%

0.77 <LOQ 0.0% 0.05 7.0% 0.13 16.9%

0.78 0.07 8.7% 0.36 46.0% 0.95 121.8%

1.02 0.10 9.8% 0.20 19.6% 1.44 141.2%

1.12 0.02 1.8% 0.12 10.7% 1.05 93.8%

1.14 0.02 1.8% 0.35 30.7% 0.20 17.5%

1.22 0.02 1.9% <LOQ 0.0% 0.04 3.0%

1.28 0.02 1.5% 0.15 12.0% 0.28 21.5%

1.47 0.04 2.7% 0.03 2.0% 0.74 50.3%

1.54 0.03 2.1% 0.12 7.6% 1.07 69.5%

1.54 0.04 2.6% 0.34 22.1% 0.55 35.7%

2.55 0.12 4.7% 1.09 42.7% 0.98 38.4%

2.73 0.24 8.8% 0.23 8.4% 1.32 48.4%

2.73 0.03 1.1% 0.14 5.1% 0.96 35.2%

4.09 ND 0.0% 1.10 26.9% 0.52 12.7%

4.95 ND 0.0% 0.20 4.0% 1.02 20.6%

5.29 0.10 1.9% 0.26 4.9% 2.58 48.8%

6.40 ND 0.0% 0.05 0.8% 2.39 37.3%

6.60 0.16 2.4% 0.98 14.8% 3.15 47.7%

TABLE 4. GC/MS measured concentrations of BE, cocaine,

ecgonine methyl ester, and ecgonine in urine from cocaine users

(continued).
296

BE Cocaine EME Ecgonine

(g/mL) (g/mL) % of

BE

(g/mL) % of

BE

(g/mL) % of

BE

8.44 0.09 1.1% 1.77 21.0% 5.23 62.0%

9.19 0.09 1.0% 0.89 9.7% 2.03 22.1%

10.13 0.10 1.0% 1.08 10.7% 3.11 30.7%

11.74 0.09 0.8% 1.97 16.8% 3.17 27.0%

14.37 0.11 0.8% 2.83 19.7% 2.61 18.2%

22.01 0.04 0.2% 3.12 14.2% 3.49 15.9%

93.81 9.67 10.3% 72.55 77.3% 55.09 58.7%

Average % of BE = 3.0% 19.1% 46.8%

Range of % of BE = 0 to 16% 0 to 83% 0 to 215%

The concentrations shown for the immunoassay determinations are

the values obtained from analysis of an undiluted aliquot, or a 1:10 or

1:100 diluted aliquot. The immunoassay-determined concentrations

from undiluted urine aliquots were used for samples found by GC/MS

analysis to have BE concentrations between 0.1 and 1.0 g/mL. For

samples found by GC/MS to have BE concentrations from 1.0 to 10.0

g/mL, the immunoassay-determined concentrations from 1:10

diluted aliquots were used, and for samples found by GC/MS to have

BE concentrations from 10.0 to 100.0 g/mL, the immunoassaydetermined concentrations from 1:100 diluted aliquots were used. No

donor samples were available having BE concentrations above 100

g/mL. The percent differences between the concentrations

determined by GC/MS and each immunoassay are also listed in table 5.

The average of the percent differences for each immunoassay and the

GC/MS measured concentration was FPIA,

-13 percent; EIA, 27 percent; and KIMS, 12 percent. The

concentrations of BE determined by GC/MS were plotted against

the concentrations determined by the KIMS assay in figure 1.

The slope of the linear regression line is 1.003 and the r 2 is

0.979. The corresponding plot for EIA versus GC/MS is shown in

figure 2; the slope is 1.414 and the r2 is 0.978, and the plot for

FPIA versus GC/MS (figure 3) gives a slope of 0.749 and an r 2 of

0.907. The data for the sample containing 93.8 ng/mL
297

TABLE 5. Measured concentrations (g/mL) of BE in donor

samples.

BE Conc. FPIA EIA KIMS

by GC/MS Conc. % Dif. Conc. % Dif. Conc. % Dif.

0.27 0.30 0.10 0.37 0.36 0.38 0.40

0.29 0.27 -0.07 0.38 0.31 0.40 0.38

0.30 0.30 0.00 0.43 0.43 0.50 0.67

0.32 0.44 0.40 0.48 0.52 0.50 0.59

0.34 0.41 0.21 0.42 0.24 0.41 0.21

0.36 0.30 -0.16 0.40 0.11 0.45 0.25

0.36 0.31 -0.14 0.37 0.03 0.34 -0.06

0.38 0.11 -0.71 0.33 -0.13 0.31 -0.18

0.41 0.25 -0.38 0.39 -0.04 0.33 -0.19

0.41 0.51 0.25 0.69 0.70 0.64 0.57

0.45 0.66 0.45 0.60 0.32 0.65 0.43

0.46 0.31 -0.33 0.38 -0.18 0.37 -0.20

0.55 0.65 0.17 0.92 0.66 0.81 0.46

0.69 0.50 -0.27 0.75 0.09 0.74 0.07

0.77 0.22 -0.71 0.82 0.07 0.57 -0.26

0.78 0.77 -0.01 0.80 0.03 0.85 0.09

1.02 0.90 -0.12 0.96 -0.06 1.15 0.13

1.12 1.00 -0.11 1.65 0.47 1.44 0.29

1.14 1.80 0.58 1.79 0.57 2.09 0.83

1.22 0.60 -0.51 1.01 -0.17 1.07 -0.12

1.28 0.30 -0.77 0.70 -0.45 0.58 -0.55

1.47 0.70 -0.52 1.91 0.30 1.94 0.32

1.54 0.50 -0.67 1.61 0.05 1.51 -0.02

1.54 1.40 -0.09 2.40 0.56 2.04 0.32

2.55 2.50 -0.02 2.85 0.12 2.32 -0.09

2.73 2.00 -0.27 3.36 0.23 2.55 -0.07

2.73 3.00 0.10 3.60 0.32 2.38 -0.13

4.09 2.20 -0.46 5.45 0.33 4.50 0.10

4.95 5.00 0.01 7.55 0.53 6.19 0.25

5.29 3.50 -0.34 6.30 0.19 5.90 0.12

6.40 4.50 -0.30 8.11 0.27 5.31 -0.17

6.60 5.30 -0.20 9.23 0.40 7.43 0.13

8.44 4.80 -0.43 13.23 0.57 6.30 -0.25

TABLE 5. Measured concentrations (g/mL) of BE in donor

samples (continued).
298

BE Conc. FPIA EIA KIMS

by GC/MS Conc. % Dif. Conc. % Dif. Conc. % Dif.

9.19 11.60 0.26 11.31 0.23 10.00 0.09

10.13 8.00 -0.21 10.10 0.00 9.00 -0.11

11.74 8.00 -0.32 18.20 0.55 13.70 0.17

14.37 7.00 -0.51 17.90 0.25 13.30 -0.07

22.01 18.00 -0.18 33.20 0.51 22.80 0.04

93.81 195.00 1.08 210.70 1.25 134.60 0.43

Average % Difference with

GC/MS determined conc. -

13%

27% 12%

of BE (table 5) are not included in the linear regression plots because

they strongly biased the correlation determination.

Limitations to the Interpretation of the Urine Drug and Metabolite

Concentrations

In addition to the size of dose and the elapsed time between use of

cocaine and collection of the urine, many other factors can

affect the concentration of cocaine and its metabolites in urine

specimens. They include route of administration, intersubject

differences in metabolism, volume of fluid intake prior to giving

a urine specimen, and chemical hydrolysis occurring in the urine

prior to analysis.

The urine samples were received at Northwest Toxicology as

part of its workplace drug-testing business. From the time a urine

specimen is collected to the time the testing is completed is

typically 3 to 4 days. During this time the specimens are not

refrigerated. The donor urine specimens used in this study were

stored frozen after they were initially found to be positive for

cocaine metabolites. After collecting positive samples over a 4-

week period, the immunoassays and GC/MS analyses described

here were performed over an additional 4-week period, during

which the urine samples were stored at normal refrigerator

temperatures. The measured concentrations of BE in these

samples decreased by an average of only 2 percent and a

maximum of 13 percent from the time the initial GC/MS

confirmation was performed until the time the GC/MS determination

of cocaine and its four metabolites was performed.
299
300

CONCLUSIONS

The data presented here show that three commercially available

immunoassays can be used with appropriate dilutions to obtain semiquantitative measurement of BE in urine over a concentration range

of at least 0.1 to 1000 &g/mL. Even though cocaine, ecgonine

methyl ester, and ecgonine can be present in urine from cocaine users

at widely varying concentrations, they have only a minor effect on

the immunoassay responses due to their low cross-reactivity to the

antibodies used in these immunoassays.

REFERENCES

Ambre, J.; Ruo, T.I.; Nelson, J.; and Belknap, S. Urinary excretion of

cocaine, benzoylecgonine, and ecgonine methyl ester in

humans. J Anal Toxicol 12:301-306, 1988.

Jatlow, P. Cocaine: Analysis, pharmacokinetics and metabolic disposition.

Yale J Biol Med 61:105-113, 1988.

Jindal, S.P., and Lutz, T. Ion cluster technique in drug metabolism: Use of a

mixture of labeled and unlabeled cocaine to facilitate

metabolite identification. J Anal Toxicol 10:150-155,

1986.

Jones, R.T. The pharmacology of cocaine. In: Grabowski, J., ed. Cocaine:

Pharmacology, Effects, and Treatment of Abuse. National

Institute on Drug Abuse Research Monograph 50. DHHS

Pub. No. (ADM)84-1326. Washington, DC: Supt. of

Docs., U.S. Govt. Print. Off., 1984. pp. 34-53.

Okeke, C.C.; Wynn, J.E.; and Patrick, K.S. Simultaneous analysis of

cocaine, benzoylecgonine, methylecgonine, and ecgonine

in plasma using an exchange resin and GC/MS.

Chromatographia 38:52-56, 1994.

Peterson, K.L.; Logan, B.K.; and Christian, G.D. Detection of cocaine and

its polar transformation products and metabolites in

human urine. Forensic Sci Int 73:183-196, 1995.

Zhang, J.Y., and Foltz, R.L. Cocaine metabolism in man: Identification for

four previously unreported cocaine metabolites in human

urine. J Anal Toxicol 14:201-205, 1990.

ACKNOWLEDGMENT

The research described here was supported in part by National

Institute on Drug Abuse contract no. N01-DA-1-9205.
301

AUTHORS

Rodger L. Foltz, Ph.D.

Technical Director

Christine Botelho, B.S.

Screening Lab Supervisor

Scott A. Reuschel, M.S.

Senior Analyst
302

David J. Kuntz, Ph.D.

Laboratory Director

Northwest Toxicology, Inc.

1141 East 3900 South

Salt Lake City, UT 84124

David E. Moody, Ph.D.

Associate Director

Gloria M. Bristow, B.S.

Technologist

Center for Human Toxicology

University of Utah

Room 490

Biomedical Polymers Building

Salt Lake City, UT 84112
303

Appendix I: Workshop Summary

Outcome Measures and Success

Criteria

Betty Tai

On October 8, 1992, the second Clinical Decision Network workshop

sponsored by the Medications Development Division (MDD), National

Institute on Drug Abuse (NIDA) was held in Bethesda, Maryland.

There were 30 attendees at this workshop (see attachment I). The

agenda of this workshop addressed specific issues regarding

standardized outcome measures and definitions of success of clinical

efficacy trials for cocaine addiction pharmacotherapy. These two

issues were identified in an earlier workshop (held April 20-21, 1992)

as missing elements in current research and development processes for

cocaine addiction pharmacotherapy. The meeting program was

divided into two parts. The morning session included brief

presentations by invited participants, which provided introduction,

overview, background, and objectives of the workshops. Two

workshops were conducted during the afternoon session, with

participants divided into small groups. Discussions were focused on

specific issues regarding using biological markers, e.g., urine, to assess

cocaine use (workshop I), and defining abstinence as an outcome

measure (workshop II) in conducting clinical efficacy trials.

Workshop I - “Assessment of Drug Use” group 1 was moderated by

Richard Hawks and Paul Fudala; group 2 was moderated by Nora

Chiang and Reese Jones. Workshop II, “Definition of Abstinence”

group 1 was moderated by Peter Bridge and Jeff Wilkins; group 2 was

moderated by Frank Vocci and Jim Cornish.

EFFICACY OUTCOME MEASURES

Participants generally agreed that the outcome measures for assessing

the clinical efficacy of cocaine addiction pharmacotherapy should

reliably and accurately reflect the benefits of the treatment. A core

battery of outcome measures has been proposed by Dr. Charles

O'Brien's group. Participants unanimously agreed that urinalysis

should be used as an efficacy outcome measure. The advantage of

this is obvious, as this is the best of the currently available surrogate

markers for monitoring cocaine intake. However, this method has its
304

limitations; therefore, it is important to thoroughly understand the

basic pharmacokinetics concepts and analytical methods applied to

the urine screening of cocaine exposure to ensure proper

experimental design and data analysis. Participants also expressed the

desire to have some standardized method of collecting, analyzing, and

interpreting urinalysis data so that results may be readily compared

across studies.

USE OF URINE DATA TO ASSESS COCAINE USE BEHAVIOR

Urinalysis of cocaine, benzoylecgonine (BE), or other metabolites is a

surrogate measure for cocaine exposure. To use urine data reliably

and accurately to estimate actual cocaine use, it is important to fully

understand the underlying principles and the current state-of-the-art

technology for urinalysis.

Pertinent Issues

Some of the following issues (the pharmacokinetics of cocaine and

the clinical relevance of urinalysis in measuring drug use) were

discussed in the workshop, some (the chemical analysis, the sampling

scheme of the urine samples, and the trial designs) were not. For the

purpose of having a complete record as a general background for

later discussion, the author has supplemented some of the

information.

Pharmacokinetics. Cocaine, whether administered intranasally or

intravenously, has a fast onset of action coupled with a speedy rise of

plasma cocaine concentration. The bioavailability via the intranasal

(IN) route is about 50 to 80 percent and via the smoke route is about

10 to 20 percent. Cocaine has short half-life of about 1.5 hours. BE

and ecgonine methyl ester, the major nonactive metabolites of

cocaine, have half-lives of 7.5 and 3.5 hours, respectively. Therefore,

BE is the most commonly screened target and can be detected in the

urine for up to 2 days after the last cocaine use. Depending on the

frequency of urine sampling and the pattern of cocaine use (daily use

versus binge use), a negative urine sample may not be a clear

indication of lack of cocaine use, and a positive urine sample may be

due to the carried-over effects of a previous episode 3 to 5 days

before sampling.

Chemistry. Both immunoassay and chromatography methods have

been used to detect urine BE. Immunoassays such as EMIT, RIA, and
305

Abbott ADX have been popular for qualitative measurements because

they are less expensive, have fast turnaround, and are reliable.

Generally, 300 ng/mL is set as the cutoff. Results are expressed as

positive or negative on the basis of BE concentrations. Recently, some

laboratories have been using GC or GC/MS for quantitative assays of

BE concentrations in urine. This raises new possibilities for analysis

and interpretation of urine data. Extensive discussion on this

implication was part of the workshop agenda. Different methods have

different sensitivity, specificity, and reproducibility of detection.

Therefore, it may be advantageous to have a central laboratory

analyze all the samples collected from multisite trials. This becomes

critical when considering whether quantitative urine measures would

be useful in particular studies.

Trial Design (Statistics). Although it was not the focus of discussion

at this workshop, design and statistical issues are unavoidable in

meaningful discussions about using urinalysis to monitor cocaine

intake. Major relevant issues are the design of sampling schemes

(random or fixed schedule) used to collect samples, the frequency and

timing of sampling, and quantitative versus qualitative analysis of

urine data. These issues are critical in designing trials that would

minimize the carryover effect and maximize the possibility of

detecting cocaine intake. The issue of how to treat missing samples is

critical in analyzing urinalysis data. Conservative methods usually

count a missing sample as a positive sample. However, justification

for such statistical treatment is needed. One strategy is to shorten the

trial duration to minimize the missing datapoints.

Clinical Relevance. From the above discussions it is clear that there

are limitations in using urinalysis data to estimate cocaine use

behavior. Generally, urinalysis data are not very sensitive markers

because of high variability. It is extremely difficult to use urine data

to estimate the frequency and amount of cocaine use. Changes

observed in urinalysis data have not been correlated with changes in

any other outcome variables such as patients' well-being, employment

status, or marital status. Until such correlations are established, the

clinical usefulness of urine data is limited to validating reported drug

use.

Urine Data Analysis: Qualitative Versus Quantitative

The current urine analysis methods were developed for detecting illicit

drug use in the workplace. For cocaine detection, the urine

concentration of BE (a major inactive metabolite with longer half-life)
306

is analyzed by immunoassays. A BE concentration of 300 ng/mL was

set as the cutoff point. Any sample with a concentration below 300

ng/mL is a negative sample (a clean urine), any sample with a BE

concentration above 300 ng/mL is a positive sample (a dirty urine).

This is the qualitative method of cocaine detection, which only

provides information on whether a cocaine metabolite is present in the

urine sample. Lately, several laboratories have been applying

chromatography assays and a fluorescence polarization immunoassay

to determine actual urine BE concentrations. Therefore, instead of

binary assessments of urine samples as either clean or dirty, it is

possibile to evaluate urine data in a continuous, quantitative manner.

However, the quantitative urinalysis is more time consuming and

costly. The advantages and the limitations of the quantitative

urinalysis to project cocaine intake behavior were therefore

extensively discussed. There was general consensus that it holds

significant promise for use in outcome measures of some trials, but

that it may offer limited (or no) advantage in others. Clearly more

research is needed to resolve the value of the quantitative approach

versus the qualitative approach.

Urine Data Interpretation

Reduction in Use. Traditionally, the treatment goal for addiction

disorder is to achieve total abstinence. The idea of accepting

reduction in use of abused substance as an interim goal for treatment

was new and novel to many workshop participants. However, it was

felt that because the outcome for treatment for any group of patients

is a continuum, measuring improvement by a reduction in the amount

of illicit drug use was not unreasonable. Similar to that for many

other incurable diseases, the treatment objective may be to bring

symptoms into remission. Fewer episodes of use, or reduction in

amount of illicit drug use, certainly is an encouraging sign for

treatment success. Treatment success may also be viewed as phases or

stages: initially, reduction in use may be the goal; ultimately, reduced

use leads to availability for other treatments that leads to abstinence.

Reduction in use means reduced amount or/and frequency of cocaine

intake. The latter has a significant implication for intravenous (IV)

cocaine users, because this would reduce the risk for HIV exposure

and conversion. However, some of the participants pointed out that

the validity of the assumption that reduction in cocaine use will lead to

abstinence or improved scores on the other Addiction Severity Index

(ASI) measures and/or prevent the deterioration due to cocaine

addiction has not been established through long-term treatment
307

studies. There was a legitimate difference of opinion as to the

prognostic significance of minor reductions in cocaine use, although

all participants agreed that major reduction in cocaine use was a good

prognostic sign.

With qualitative urinalysis, reduction in use may be expressed

collectively in decreased numbers (or percentages) of positive (dirty)

samples or increased numbers (or percentages) of negative (clean)

samples within a specified study period, and individually as decreased

or increased number of days of urine samples being positive or

negative. However, in a recent report by Batki and Jones on the effect

of fluoxetine on cocaine use, the authors' results showed that with

qualitative urinalysis a statistically significant difference was not

achieved between the treatment and control, whereas a statistically

significant difference was achieved with quantitative urinalysis. This

report sparked extensive discussion on how quantitative urinalysis

could provide additional information or improve the sensitivity of

urine data in assessing cocaine use behavior.

In quantitative urinalysis, if a significant decrease of mean urine BE

quantity between the treatment and placebo groups is observed, the

following issues need to be addressed: (1) Is the spread (variability)

of the data wide or narrow? The data may reflect only a few heavy

users who changed their use behavior. (2) Are subjects stratified by

their preferred route of cocaine administration? The bioavailability of

the smoking route is much lower than those of the IN and IV routes

of cocaine administration. (3) Does an X percent decrease in mean

urine BE concentration indicate a parallel X percent reduction in the

amount of cocaine intake? If not, what is the correlation between the

urine data and amount of cocaine use? (4) Should this reduction be

interpreted as X percent of the population achieved a certain level

reduction of cocaine intake or that everybody in the study reduced

the use by X percent? At present, the demonstration of a reduction of

mean urine BE quantity is collective information, i.e., it does not

reveal the nature of the reduction. Until these issues are addressed,

quantitative urinalysis will be more effective in projecting cocaine use

only when it is backed up with additional evidence of efficacy.

Participants generally felt that because of the insensitivity of the

biological marker as an outcome measure, any statistically significant

reduction in the biological marker measure must project a much more

pronounced reduction at the behavior level. Participants also

suggested that the acceptable reduction criteria must be set at the

behavior level rather than at the urine level. In designing the trial, it is
308

important to set a target for reduction, so that the N (number of study

subjects) that will give maximal power may be determined.

Abstinence. Participants generally agreed on the definition of

abstinence as continuously drug-free days; abstinence can be

expressed by urinalysis data as continuous clean days. Note that

because of intermittent sampling and possible carryover, clean urine

days rather than abstinent days are measured. In other words, days of

negative urine do not equal days of abstinence. Urinalysis data can

only demonstrate clean urine days and cannot tell the difference

between a slip and a relapse. A slip is considered a minor instance of

use, but a relapse is a return to addiction. As relapse is not defined by

the extent of use, but by symptoms of dependence, urinalysis data are

therefore not helpful in differentiating the two. No participant was

comfortable about judging relapse on the basis of urinalysis data.

Participants agreed that the proper duration for assessing abstinence

depends on the addict's cocaine use pattern. For a daily cocaine user,

4 weeks of observation is considered sufficient. However, for a

binger, the time for observation needs to be longer. Most participants

considered the patient's being able to abstain for 50 percent of the

trial duration a significant improvement. An occasional slip is not

considered significant.

In summary, abstinence is not a terribly useful concept. The concept

of relapse is important but cannot be evaluated with urinalysis data

because relapse is defined by the dependence criterion. It is

important to establish the baseline use pattern, i.e., daily user versus

binge user. Many participants felt that for cocaine abuse, episodes of

compulsive use is a more meaningful measure of efficacy than is

abstinence.

Success Criteria. What kind and magnitude of reduction in use is

considered clinically significant? Participants expressed the following

opinions:

1. If a 10 percent reduction means everybody in the study

reduced cocaine use by 10 percent, it is not significant, but if

1 out of 10 subjects stopped using cocaine, it is significant.

2. A reduction in use from seven to three injections per day is

significant because it reduced the risk for HIV transmission.
309

3. A reduction in use from seven to five injections per day is not

impressive, but a reduction from 7 to 5 days per week is

impressive.

4. For a daily cocaine user, 1 abstinent day per week is

significant. However, for a cocaine binger, days of abstinence

do not mean much.

5. The timing of the reduction in use is also important in

determining the significance; if the reduction in use occurred

at the beginning of the trial and toward the end of the trial, the

use pattern returned and the reduction cannot be viewed as

effective.

CONCLUSION

While clear consensus on all the discussion points was an elusive goal,

it was clear that much more thought is currently being given to more

innovative ways to use urine data for outcome measures in clinical

efficacy trials. Researchers are at the stage where new technology

allows the generation of relatively quantitative results on urine

samples, and such data hold interesting promise for identifying trends

in drug efficacy. The many technical, clinical, and statistical issues

raised in these discussions has laid critical groundwork for developing

standardized approaches to the application of urinalysis for drug

abuse pharmaco-therapeutics development. Having a marker that

could accurately and reliably measure the episodes and amount of

each cocaine intake would be ideal.

Unfortunately, current available technology and methods of urine

screening do not provide such information. For effective use of

urinalysis results as a surrogate outcome measure of the effect of

pharmacotherapy on cocaine usage, the participants recommended the

following:

1. Urinalysis is a useful objective outcome measure to monitor

cocaine usage.

2. The sampling frequency should be appropriate to the

objectives of the study; for cocaine, more than once weekly is

needed.
310

3. A baseline measure of use pattern should be established with

more than one urine sample and for longer than 1 week.

4. Urine data should be collected in a way that allows quantitative

and qualitative analysis and is not dependent on a specific

collection hypothesis or analytical plan.

5. The urine data should be investigated at specific points as well

as over periods to see if there is a trend of reduction. If a

trend is noted, what is the timecourse of the reduction? Is the

reduction at the beginning or the end of the trial?

6. Self-reports, which provide information of timing, episodes,

and amount of use, should be collected along with urine

samples.

7. All urine data should be evaluated for the individual as well as

the group, because there will be some who stopped use, some

who reduced use, some who did not change. For those who

have reduced or stopped use, other signs of improvement

(employ-ment, marriage, etc.) should be examined to see if

there is any correlation.

8. When submitted for Food and Drug Administration (FDA)

review (according to Dr. Curtis Wright), the urine data should

be collected, analyzed, and summarized in the most

straightforward way possible. In some cases it may be

advantageous to have the clinician evaluate the urine data

while the trial is still blind, integrating the urine toxicology

with the clinical reports. In other cases it may be best to keep

the urine data confidential during the double-blind period. In

either case, rules for collection procedures, attribution of

missing samples, handling of dropouts, and the proposed

analysis should be specified in advance.

ATTACHMENT I

Participant List

The participants of the workshop are listed below. Many of them

have read and commented on this summary report. However, the

choices of what to incorporate and how to present the materials are
311

those of the author, who, therefore, takes full responsibility for any

errors.

Tanya Alim, M.D.

George Bigelow, Ph.D.

Jack Blain, M.D.

Peter Bridge, M.D.

Nora Chiang*, Ph.D.

James Cornish, M.D.

Everett Ellinwood, M.D.

Marian Fischman, Ph.D.

Paul Fudala, Ph.D.

Donald M. Gallant, M.D.

Charles Grudzinskas*, Ph.D.

Sue Herbert, M.A., R.N.

Richard Hawks*, Ph.D.

Reese Jones*, M.D.

Thomas Kosten, M.D.

Frances Levine, M.D.

Walter Ling, M.D.

Juri Mojsiak, D. Pharm.

Jack Mendelson, M.D.

Ann Montgomery, M.S., R.N.

Charles O'Brien, M.D., Ph.D.

Kenzie Preston, Ph.D.

Adel Roman, R.N.

Doralie Segal, M.S.

Charles Schuster, Ph.D.

Betty Tai, Ph.D.

Jeffery Wilkins, M.D.

George Woody, M.D.

Curtis Wright*, M.D., M.P.H.

Frank Vocci*, Ph.D.

* = Participants who have read and commented on the summary

report.
312

Appendix II: Workshop Summary

Clinical Decision Tree for Cocaine

Addiction Pharmacotherapy

Betty Tai, Charles V. Grudzinskas, Peter Bridge, and Nora

Chiang

A coherent research and development (R&D) plan to effectively and

efficiently move compounds into multicenter efficacy trials for cocaine

addiction pharmacotherapy does not exist at present. In light of this, in

1992, the Medications Development Division (MDD) of the National

Institute of Drug Abuse (NIDA) sponsored three Clinical Decision Network

workshops to identify, investigate, and develop actions that would facilitate

the development of such a plan. From the first workshop, it was identified

that the key missing element is the lack of a clinical decision tree that

provided guidance in critical decision making regarding the selection,

prioritizing, and discontinuation/ elimination of compounds from R&D

process. In subsequent workshops (held on November 13, 1992)

proposals were reviewed to address these issues, and a clinical decision tree

(see figure 1) was developed with the following key features: (1) an

assumption that the investigational compounds are with or without a strong

clinical pharmacology model (table 1); (2) if the compound has a strong

clinical pharmacology model, then development rationale, in initial safety,

pharmacokinetics, and interaction with abused substances may be tested in

human laboratory settings (table 2), if not other proper hypothesisgenerating trials; and (3) for all compounds, the efficacy confirmation trials

may be tested with designs specific to the proposed indication (table 3).
313
314
315
316
317

Authors

Betty Tai, Ph.D.

Chief, Regulatory Affairs Branch

Medications Development Division

Charles V. Grudzinskas, Ph.D.

Director, Medications Development Division

Nora Chiange, Ph.D.

Chemistry and Pharmaceutics Branch

Medications Development Division

Peter Bridge, M.D.

Chief, Clinical Trials Branch

Medications Development Division

National Institute on Drug Abuse

Parklawn Building, Room 11A-55

5600 Fishers Lane

Rockville, MD 20857
318

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26 THE BEHAVIORAL

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69 OPIOID PEPTIDES: MEDICINAL CHEMISTRY.

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NCADI #M102 NTIS PB #91-172866/AS (A11)

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103 DRUGS AND VIOLENCE: CAUSES, CORRELATES, AND

CONSEQUENCES. Mario De La Rosa, Ph.D.;

Elizabeth Y. Lambert, M.S.; and Bernard Gropper, Ph.D., eds.
325

NCADI #M103 NTIS PB #91-172874/AS (A13)

$36.50

104 PSYCHOTHERAPY AND COUNSELING IN THE

TREATMENT OF DRUG ABUSE. Lisa Simon Onken, Ph.D., and

Jack D. Blaine, M.D., eds.

NCADI #M104 NTIS PB #91-172874/AS (A07)

$27.00

106 IMPROVING DRUG ABUSE TREATMENT.

Roy W. Pickens, Ph.D.; Carl G. Leukefeld, D.S.W.; and

Charles R. Schuster, Ph.D., eds.

NCADI #M106 NTIS PB #92-105873(A18) $50.00

107 DRUG ABUSE PREVENTION INTERVENTION RESEARCH:

METHODOLOGICAL ISSUES. Carl G. Leukefeld, D.S.W., and

William J. Bukoski, Ph.D., eds.

NCADI #M107 NTIS PB #92-160985 (A13) $36.50

108 CARDIOVASCULAR TOXICITY OF COCAINE:

UNDERLYING MECHANISMS. Pushpa V. Thadani, Ph.D., ed.

NCADI #M108 NTIS PB #92-106608 (A11) $36.50

109 LONGITUDINAL STUDIES OF HIV INFECTION IN

INTRAVENOUS DRUG USERS: METHODOLOGICAL ISSUES IN

NATURAL HISTORY RESEARCH. Peter Hartsock, Dr.P.H., and

Sander G. Genser, M.D., M.P.H., eds.

NCADI #M109 NTIS PB #92-106616 (A08) $27.00

111 MOLECULAR APPROACHES TO DRUG ABUSE RESEARCH:

RECEPTOR CLONING, NEUROTRANSMITTER EXPRESSION,

AND MOLECULAR GENETICS: VOLUME I. Theresa N.H. Lee,

Ph.D., ed.

NCADI #M111 NTIS PB #92-135743 (A10) $36.50

112 EMERGING TECHNOLOGIES AND NEW DIRECTIONS IN

DRUG ABUSE RESEARCH. Rao S. Rapaka, Ph.D.;

Alexandros Makriyannis, Ph.D.; and Michael J. Kuhar, Ph.D.,

eds.

NCADI #M112 NTIS PB #92-155449 (A15) $44.50

113 ECONOMIC COSTS, COST EFFECTIVENESS, FINANCING,

AND COMMUNITY-BASED DRUG TREATMENT.

William S. Cartwright, Ph.D., and James M. Kaple, Ph.D., eds.

NCADI #M113 NTIS PB #92-155795 (A10) $36.50

114 METHODOLOGICAL ISSUES IN CONTROLLED STUDIES

ON EFFECTS OF PRENATAL EXPOSURE TO DRUG ABUSE.

M. Marlyne Kilbey, Ph.D., and Khursheed Asghar, Ph.D., eds.
326

NCADI #M114 NTIS PB #92-146216 (A16) $44.50

115 METHAMPHETAMINE ABUSE: EPIDEMIOLOGIC ISSUES

AND IMPLICATIONS. Marissa A. Miller, D.V.M., M.P.H., and

Nicholas J. Kozel, M.S., eds.

NCADI #M115 NTIS PB #92-146224/ll (AO7)

$27.00

116 DRUG DISCRIMINATION: APPLICATIONS TO DRUG

ABUSE RESEARCH. R.A. Glennon, Ph.D.;

Toubjörn U.C. Järbe, Ph.D.; and J. Frankenheim, Ph.D., eds.

NCADI #M116 NTIS PB #94-169471 (A20) $52.00

117 METHODOLOGICAL ISSUES IN EPIDEMIOLOGY,

PREVENTION, AND TREATMENT RESEARCH ON DRUGEXPOSED WOMEN AND THEIR CHILDREN.

M. Marlyve Kilbey, Ph.D., and Kursheed Asghar, Ph.D., eds.

GPO Stock #O17-024-01472-9

$12.00

NCADI #M117 NTIS PB #93-102101/LL (A18)

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118 DRUG ABUSE TREATMENT IN PRISONS AND JAILS.

Carl G. Leukefeld, D.S.W., and Frank M. Tims, Ph.D., eds.

GPO Stock #O17-024-01473-7

$16.00

NCADI #M118 NTIS PB #93-102143/LL (A14)

$44.50

120 BIOAVAILABILITY OF DRUGS TO THE BRAIN AND THE

BLOOD-BRAIN BARRIER. Jerry Frankenheim, Ph.D., and

Roger M. Brown, Ph.D., eds.

GPO Stock #017-024-01481-8

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NCADI #M120 NTIS PB #92-214956/LL (A12)

$36.50

121 BUPRENORPHINE: AN ALTERNATIVE TREATMENT

FOR OPIOID DEPENDENCE. Jack D. Blaine, Ph.D., ed.

GPO Stock #017-024-01482-6 $5.00

NCADI #M121 NTIS PB #93-129781/LL (A08)

$27.00

123 ACUTE COCAINE INTOXICATION: CURRENT METHODS

OF TREATMENT. Heinz Sorer, Ph.D., ed.

GPO Stock #017-024-01501-6 $6.50

NCADI #M123 NTIS PB #94-115433/LL (A09)

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327

124 NEUROBIOLOGICAL APPROACHES TO BRAIN-BEHAVIOR

INTERACTION. Roger M. Brown, Ph.D., and

Joseph Fracella, Ph.D., eds.

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NCADI #M124 NTIS PB #93-203834/LL (A12)

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125 ACTIVATION OF IMMEDIATE EARLY GENES BY DRUGS

OF ABUSE. Reinhard Grzanna, Ph.D., and

Roger M. Brown, Ph.D., eds.

GPO Stock #017-024-01503-2 $7.50

NCADI #M125 NTIS PB #94-169489 (A12) $36.50

126 MOLECULAR APPROACHES TO DRUG ABUSE RESEARCH

VOLUME II: STRUCTURE, FUNCTION, AND EXPRESSION.

Theresa N.H. Lee, Ph.D., ed.

NCADI #M126 NTIS PB #94-169497 (A08) $27.00

127 PROGRESS AND ISSUES IN CASE MANAGEMENT.

Rebecca S. Ashery, D.S.W., ed.

NCADI #M127 NTIS PB #94-169505 (A18) $52.00

128 STATISTICAL ISSUES IN CLINICAL TRIALS FOR

TREATMENT OF OPIATE DEPENDENCE.

Ram B. Jain, Ph.D., ed.

NCADI #M128 NTIS PB #93-203826/LL (A09)

$27.00

129 INHALANT ABUSE: A VOLATILE RESEARCH AGENDA.

Charles W. Sharp, Ph.D.; Fred Beauvais, Ph.D.; and

Richard Spence, Ph.D., eds.

GPO Stock #017-024-01496-6

$12.00

NCADI #M129 NTIS PB #93-183119/LL (A15)

$44.50

130 DRUG ABUSE AMONG MINORITY YOUTH: ADVANCES IN

RESEARCH AND METHODOLOGY. Mario De La Rosa, Ph.D.,

and Juan-Luis Recio Adrados, Ph.D., eds.

GPO Stock #017-024-01506-7

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NCADI #M130 NTIS PB #94-169513 (A15) $44.50

131 IMPACT OF PRESCRIPTION DRUG DIVERSION CONTROL

SYSTEMS ON MEDICAL PRACTICE AND PATIENT CARE.

James R. Cooper, Ph.D.; Dorynne J. Czechowicz, M.D.;

Stephen P. Molinari, J.D., R.Ph.; and

Robert C. Peterson, Ph.D., eds.
328

GPO Stock #017-024-01505-9

$14.00

NCADI #M131 NTIS PB #94-169521 (A15) $44.50

132 PROBLEMS OF DRUG DEPENDENCE, 1992:

PROCEEDINGS OF THE 54TH ANNUAL SCIENTIFIC MEETING

OF THE COLLEGE ON PROBLEMS OF DRUG DEPENDENCE.

Louis Harris, Ph.D., ed.

GPO Stock #017-024-01502-4

$23.00

NCADI #M132 NTIS PB #94-115508/LL (A99)

133 SIGMA, PCP, AND NMDA RECEPTORS.

Errol B. De Souza, Ph.D.; Doris Clouet, Ph.D., and

Edythe D. London, Ph.D., eds.

NCADI #M133 NTIS PB #94-169539 (A12) $36.50

134 MEDICATIONS DEVELOPMENT: DRUG DISCOVERY,

DATABASES, AND COMPUTER-AIDED DRUG DESIGN.

Rao S. Rapaka, Ph.D., and Richard L. Hawks, Ph.D., eds.

GPO Stock #017-024-01511-3

$11.00

NCADI #M134 NTIS PB #94-169547 (A14) $44.50

135 COCAINE TREATMENT: RESEARCH AND CLINICAL

PERSPECTIVES. Frank M. Tims, Ph.D., and

Carl G. Leukefeld, D.S.W., eds.

GPO Stock #017-024-01520-2

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NCADI #M135 NTIS PB #94-169554 (A13) $36.50

136 ASSESSING NEUROTOXICITY OF DRUGS OF ABUSE.

Lynda Erinoff, Ph.D., ed.

GPO Stock #017-024-01518-1

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NCADI #M136 NTIS PB #94-169562 (A13) $36.50

137 BEHAVIORAL TREATMENTS FOR DRUG ABUSE AND

DEPENDENCE. Lisa Simon Onken, Ph.D.; Jack D. Blaine, M.D.;

and John J. Boren, Ph.D., eds.

GPO Stock #017-024-01519-9

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NCADI #M137 NTIS PB #94-169570 (A15)

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138 IMAGING TECHNIQUES IN MEDICATIONS

DEVELOPMENT: CLINICAL AND PRECLINICAL ASPECTS.

Heinz Sorer, Ph.D., and Rao S. Rapaka, Ph.D., eds.
329

NCADI #M138

139 SCIENTIFIC METHODS FOR PREVENTION

INTERVENTION RESEARCH. Arturo Cazares, M.D., M.P.H., and

Lula A. Beatty, Ph.D., eds.

NCADI #M139

140 PROBLEMS OF DRUG DEPENDENCE, 1993:

PROCEEDINGS OF THE 55TH ANNUAL SCIENTIFIC MEETING,

THE COLLEGE ON PROBLEMS OF DRUG DEPENDENCE, INC.

VOLUME I: PLENARY SESSION SYMPOSIA AND ANNUAL

REPORTS. Louis S. Harris, Ph.D., ed.

NCADI #M140

141 PROBLEMS OF DRUG DEPENDENCE, 1993:

PROCEEDINGS OF THE 55TH ANNUAL SCIENTIFIC MEETING,

THE COLLEGE ON PROBLEMS OF DRUG DEPENDENCE, INC.

VOLUME II: ABSTRACTS. Louis S. Harris, Ph.D., ed.

NCADI #M141

142 ADVANCES IN DATA ANALYSIS FOR PREVENTION

INTERVENTION RESEARCH. Linda M. Collins, Ph.D., and

Larry A. Seitz, Ph.D., eds.

NCADI #M142

143 THE CONTEXT OF HIV RISK AMONG DRUG USERS AND

THEIR SEXUAL PARTNERS. Robert J. Battjes, D.S.W.;

Zili Sloboda, Sc.D.; and William C. Grace, Ph.D., eds.

NCADI #M143

144 THERAPEUTIC COMMUNITY: ADVANCES IN RESEARCH

AND APPLICATION. Frank M. Tims, Ph.D.;

George De Leon, Ph.D.; and Nancy Jainchill, Ph.D., eds.

NCADI #M144

145 NEUROBIOLOGICAL MODELS FOR EVALUATING

MECHANISMS UNDERLYING COCAINE ADDICTION.

Lynda Erinoff, Ph.D., and Roger M. Brown, Ph.D., eds.

NCADI #M145

146 HALLUCINOGENS: AN UPDATE. Geraline C. Lin, Ph.D.,

and Richard A. Glennon, Ph.D., eds.

NCADI #M146

147 DISCOVERY OF NOVEL OPIOID MEDICATIONS.

Rao S. Rapaka, Ph.D., and Heinz Sorer, Ph.D., eds.

NCADI #M147
330

148 EPIDEMIOLOGY OF INHALANT ABUSE: AN

INTERNATIONAL PERSPECTIVE.

Nicholas J. Kozel, M.S.; Zili Sloboda, Sc.D.;

and Mario R. De La Rosa, Ph.D., eds.

NCADI #M148

149 MEDICATIONS DEVELOPMENT FOR THE TREATMENT

OF PREGNANT ADDICTS AND THEIR INFANTS.

C. Nora Chiang, Ph.D., and Loretta P. Finnegan, M.D., eds.

NCADI #M149

150 INTEGRATING BEHAVIORAL THERAPIES WITH

MEDICATIONS IN THE TREATMENT OF DRUG

DEPENDENCE. Lisa Simon Onken, Ph.D.; Jack D. Blaine, M.D.;

and John J. Boren, Ph.D., eds.

NCADI #M150
331

151 SOCIAL NETWORKS, DRUG ABUSE, AND HIV

TRANSMISSION. Richard H. Needle, Ph.D., M.P.H.;

Susan L. Coyle, Ph.D.; Sander G. Genser, M.D., M.P.H.; and

Robert T. Trotter II, Ph.D., eds.

NCADI #M151

152 PROBLEMS OF DRUG DEPENDENCE 1994: PROCEEDINGS

OF THE 56TH ANNUAL SCIENTIFIC MEETING, THE

COLLEGE ON PROBLEMS OF DRUG DEPENDENCE, INC.

VOLUME I: PLENARY SESSION SYMPOSIA AND ANNUAL

REPORTS. Louis S. Harris, Ph.D., ed.

NCADI #M152

153 PROBLEMS OF DRUG DEPENDENCE 1994: PROCEEDINGS

OF THE 56TH ANNUAL SCIENTIFIC MEETING, THE

COLLEGE ON PROBLEMS OF DRUG DEPENDENCE, INC.

VOLUME II: ABSTRACTS. (1995) Louis S. Harris, Ph.D., ed.

NCADI #M153 GPO Stock #017-024-01564-4

$22.00

154 MEMBRANES AND BARRIERS: TARGETED DRUG

DELIVERY. (1995) Rao S. Rapaka, Ph.D., ed.

NCADI #M154 GPO Stock #017-024-01583-1

$10.00

155 REVIEWING THE BEHAVIORAL SCIENCE KNOWLEDGE

BASE ON TECHNOLOGY TRANSFER. (1995)

Thomas E. Backer, Ph.D.; Susan L. David; and Gerald Soucy,

Ph.D., eds.

NCADI #M155 GPO Stock #017-024-01581-4

$12.00

156 ADOLESCENT DRUG ABUSE: CLINICAL ASSESSMENT

AND THERAPEUTIC INTERVENTIONS. (1995)

Elizabeth Rahdert, Ph.D.; Zili Sloboda, Ph.D.; and Dorynne

Czechowicz, M.D., eds.

NCADI #M156 GPO Stock #017-024-01585-7

$14.00

157 QUALITATIVE METHODS IN DRUG ABUSE AND HIV

RESEARCH. (1995)

Elizabeth Y. Lambert, M.S.; Rebecca S. Ashery, D.S.W.; and

Richard H. Needle, Ph.D., M.P.H., eds.

NCADI #M157 GPO Stock #017-024-01581-4

158 BIOLOGICAL MECHANISMS AND PERINATAL EXPOSURE

TO DRUGS. (1995) Pushpa V. Thadani, Ph.D., ed.

NCADI #M158 GPO Stock #017-024-01584-9
332

159 INDIVIDUAL DIFFERENCES IN THE BIOBEHAVIORAL

ETIOLOGY OF DRUG ABUSE. (1996) Harold W. Gordon, Ph.D.,

and Meyer D. Glantz, Ph.D., eds.

NCADI #M159
333

161 MOLECULAR APPROACHES TO DRUG ABUSE RESEARCH.

VOLUME III: RECENT ADVANCES AND EMERGING

STRATEGIES. (1996) Theresa N.H. Lee, Ph.D., ed.

NCADI #M161

162 PROBLEMS OF DRUG DEPENDENCE, 1995.

PROCEEDINGS FROM THE 57TH ANNUAL SCIENTIFIC

MEETING OF THE COLLEGE ON DRUG DEPENDENCE, INC.

(1996)

Louis Harris, Ph.D., ed.

NCADI #M162

163 NEUROTOXICITY AND NEUROPATHOLOGY

ASSOCIATED WITH COCAINE/STIMULANT ABUSE. (1996)

Dorota Majewska, Ph.D., ed.

NCADI #M163

164 BEHAVIORAL STUDIES OF DRUG-EXPOSED OFFSPRING:

METHODOLOGICAL ISSUES IN HUMAN AND ANIMAL

RESEARCH. (1996) Cora Lee Wetherington, Ph.D.;

Vincent L. Smeriglio, Ph.D.; and Loretta P. Finnegan, Ph.D.,

eds.

NCADI #M164

165 BEYOND THE THERAPEUTIC ALLIANCE: KEEPING THE

DRUG-DEPENDENT INDIVIDUAL IN TREATMENT. (1996)

Lisa Simon Onken, Ph.D.; Jack D. Blaine, M.D.; and

John J. Boren, Ph.D., eds.

NCADI #M165

166 TREATMENT FOR DRUG-EXPOSED WOMEN AND

CHILDREN: ADVANCES IN RESEARCH METHODOLOGY.

(1996) Elizabeth Rahdert, Ph.D., ed.

NCADI #M166

167 THE VALIDITY OF SELF-REPORTED DRUG USE:

IMPROVING THE ACCURACY OF SURVEY ESTIMATES.

(1996) Lana Harrison, Ph.D., and Arthur Hughes, M.D., eds.

NCADI #M167

168 RURAL SUBSTANCE ABUSE: STATE OF KNOWLEDGE

AND ISSUES. (1996) Zili Sloboda, Sc.D.;

Eric Rosenquist; and Jan Howard, Ph.D., eds.

NCADI #M168

169 TREATMENT OF PAIN IN ADDICTS AND OTHERS WHO

MAY HAVE HISTORIES OF DEPENDENCE. (1996)
334

Alan I. Trachtenberg, M.D., M.P.H., F.A.A.F.P., D.AA.P.M.,

ed.

NCADI #M169

170 META-ANALYSIS OF DRUG ABUSE PREVENTION

PROGRAMS. (1996) William J. Bukoski, Ph.D., ed.

NCADI #M170

171 TREATMENT OF COCAINE DEPENDENCE: OUTCOME

RESEARCH. (1996). Frank M. Tims, Ph.D., ed.

NCADI #M171

172 TREATMENT OF DRUG-DEPENDENT INDIVIDUALS

WITH COMORBID MENTAL DISORDERS. (1996). Lisa Simon

Onken, Ph.D.; Jack D. Blaine, M.D.; Sander Genser, M.D.,

M.P.H.; and Arthur MacNeill Horton, Jr., Ed.D., eds.

NCADI #M172

173 PHARMACOKINETICS METABOLISM, AND

PHARMACEUTICS OF DRUGS OF ABUSE. (1997)

Rao S. Rapaka, Ph.D., ed.

NCADI #M173

174 PROBLEMS OF DRUG DEPENDENCE 1996: PROCEEDINGS

OF THE 58TH ANNUAL SCIENTIFIC MEETING. THE COLLEGE

ON PROBLEMS OF DRUG DEPENDENCE, INC.

(1997) Louis S. Harris, Ph. D., ed.

NCADI #M174

175 MEDICATIONS DEVELOPMENT FOR THE TREATMENT

OF COCAINE DEPENDENCE: ISSUES IN CLINICAL EFFICACY

TRIALS. (1997) Betty Tai, Ph.D., ed.

NCADI #M175