Integrated Summary 

of Effectiveness 

Guidance for Industry 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
U.S. Department of Health and Human Services 

Food and Drug Administration 

Center for Drug Evaluation and Research (CDER)
  
Center for Biologics Evaluation and Research (CBER) 
 
 
October 2015 

Procedural 

 
   
Integrated Summary 

of Effectiveness 

Guidance for Industry 

 
 
 
Additional copies are available from: 

 
Office of Communications, Division  of Drug Information 

Center for Drug Evaluation  and Research 

Food and  Drug Administration 
 
10001 New Hampshire Ave., Hillandale Bldg., 4th Floor  
 
Silver Spring, MD  20993-0002  

Tel: 855-543-3784 or 301-796-3400;  Fax: 301-431-6353; Email:  druginfo@fda.hhs.gov  

http://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/default.htm 

or 
 
Office of Communication, Outreach, and Development  

Center for Biologics Evaluation and Research 
 
Food and  Drug Administration 
 
10903 New Hampshire Ave., Bldg. 71, rm. 3128 

Silver Spring, MD   20993-0002 

Tel: 800-835-4709 or 240-402-7800;  Email:  ocod@fda.hhs.gov 
 
http://www.fda.gov/BiologicsBloodVaccines/GuidanceComplianceRegulatoryInformation/Guidances/default.htm 

 
 
 
 
 
 
 
 
 
 
U.S. Department of Health and Human Services 

Food and Drug Administration 

Center for Drug Evaluation and Research (CDER)
  
Center for Biologics Evaluation and Research (CBER) 
 
 
October 2015 

Procedural 

 
   
TABLE OF CONTENTS 
 
 
I.   INTRODUCTION............................................................................................................. 1
  
II.   BACKGROUND ............................................................................................................... 2
  
III.   FORMAT AND CONTENT OF THE ISE..................................................................... 3 
 
A.   Listing and Brief Results of Individual Studies ........................................................................... 4 
 
B.   Analysis of Study Designs.............................................................................................................. 5
  
C.   Overall Analysis of Effectiveness Results .................................................................................... 7
  
1.  Comparison of Results of Individual Studies ................................................................................... 9 
 
2.  Pooled Analyses of Data From More Than One Study .................................................................. 10 
 
D.   Comparison of Results in Subpopulations ................................................................................. 11 
 
E.   Analysis of Clinical Information Relevant to Dosing Recommendations ............................... 13
  
F.   Time Course of Effect, Persistence of Effect and/or Tolerance, Distribution of Responses  . 13 
 
G.   Exploratory Investigations.......................................................................................................... 14 
 
GLOSSARY................................................................................................................................. 15 
 
REFERENCES............................................................................................................................ 16 
 
  Contains Nonbinding Recommendations 
Integrated Summary of Effectiveness  

1
 
Guidance for Industry  
 
 
 
 
This guidance represents the current thinking of the Food and Drug Administration (FDA or Agency) on 
this topic. It does not create any rights for any person and is not binding on FDA or the public.  You can 
use an alternative approach if it satisfies the requirements of the applicable statutes and regulations.  To 
discuss an alternative approach, contact the FDA staff responsible for this guidance as listed on the title 
page. 
 
 
 
 
I.  INTRODUCTION 
 
This guidance describes the recommended content of the integrated summary of effectiveness 
(ISE) for inclusion in a new drug application (NDA) or biologics license application (BLA).2   
Although there are no regulations requiring an ISE for BLA submissions, applicants are 
encouraged to provide an ISE because it represents an opportunity to present a coherent analysis 
and presentation of the drugs benefits. 
 
The recommendations in this guidance reflect the FDAs current thinking regarding information 
that industry should include in an ISE to provide an integrated analysis that offers insights 
beyond those observable in individual clinical trials.3  This guidance does not apply to medical 
devices regulated as biologics under the Public Health Service Act. 
 
This guidance supersedes section II.G., Integrated Summary of Effectiveness Data, of the 
guidance for industry Guideline for the  Format and Content of the Clinical and Statistical 
Sections of an Application (Clin-Stat guidance).4  It also incorporates the conceptual framework 
of section 2.7.3, Summary of Clinical Efficacy (SCE), from the ICH guidance for industry M4E 
The CTD  Efficacy. 
 
                                                 
1  This guidance has been prepared by the Office of New Drugs and the Office of Biostatistics in the Center for Drug  
Evaluation and Research in cooperation  with  the Center for Biologics Evaluation and Research at the Food and Drug 
Administration.   
 
2 See the Glossary for definitions and  usage of specific terms used throughout this guidance. 
 
3 See 21 CFR 314.50(d)(5)(v).  The ISE satisfies the regulatory requirement in 21 CFR 314.50(d)(5)(v) for drugs.   
 
4  We  update  guidances periodically.  To make sure you  have the most recent version of a guidance, check the FDA  
Drugs guidance Web page  at  
http://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/default.htm.  
  1
  Contains Nonbinding Recommendations 
In general, FDAs guidance documents do not establish legally enforceable responsibilities.  
Instead, guidances describe the Agencys current thinking on a topic and should be viewed only 
as recommendations, unless specific regulatory or statutory requirements are cited.  The use of 
the word should in Agency guidances means that something is suggested or recommended, but 
not required. 
 
 
II.  BACKGROUND 
 
The ISE is a comprehensive integrated analysis of the effectiveness of a study drug.  The purpose 
of the ISE is to describe the available information regarding effectiveness, delineate strengths 
and weaknesses, and highlight important missing information.  Generally, analyses in the ISE are 
based primarily on the clinical effectiveness data included in the application, but they may also 
include other sources of information relevant to efficacy.  Such sources include nonclinical 
studies; clinical pharmacology studies (e.g., pharmacokinetic (PK), pharmacodynamic, and in 
vitro studies) that describe dose-response, concentration-response, and drug-drug and drug-
disease (e.g., renal dysfunction) interactions; human factor studies for drug-device combinations; 
and in vitro  studies that clarify drug activity.  
 
Since 1985, the regulation under 21 CFR 314.50(d)(5)(v) has required that the ISE be part of an 
NDA submission, but the regulation does not describe the specific components of the ISE in 
detail except for the components listed below.  Under 21 CFR 314.50(d)(5)(v), the ISE must 
include: 
 
 	  An integrated summary of the data demonstrating substantial evidence of effectiveness 
for each claimed indication 
 
 	  Evidence that supports the dosage and administration section of the labeling, including 
support for the recommended dosage and dose interval 
 
 	  Effectiveness data analyzed by sex, age, and racial subgroups, identifying any 

modifications of dosing for specific subgroups 

 
 	  Effectiveness data from other subgroups of the population of patients treated, when 
appropriate, such as patients with renal failure or patients with different levels of severity 
of the disease 
 
The first description of the purpose of an ISE was in the Clin-Stat guidance.  Section II.G., 
Integrated Summary of Effectiveness Data, of that guidance stated:   
 
The individual controlled studies to a great extent speak for themselves with respect to 
their ability to provide the evidence of effectiveness required by law.  This section should 
provide an overview of the results, showing that they do satisfy the regulatory 
requirements for approval, i.e., represent adequate and well-controlled studies 
demonstrating the claimed effect, particularly if results are inconsistent or marginal.  For 
example, the sponsor would explain here his basis for seeking to rely on a single study.  
  2
  Contains Nonbinding Recommendations 
Equally important, this section should include an examination of study-to-study 
differences in results, effects in subsets of the treated population, dose-response 
information from all sources, any available comparisons with alternative drugs, and any 
other information, so that the nature of the drugs effectiveness can be as fully defined as 
possible, and the user of the drug can be given the best possible information on how to 
use the drug and what results to expect. 
 
The Agency interprets the regulation to refer not only to a discussion of the major effectiveness 
studies results and design, but also to detailed integrated analyses of relevant sources of 
information concerning effectiveness.  Such analyses generally fall into two broad categories:  
(1) comparing the individual studies to better understand the overall results (see section III.C.1., 
Comparison of Results of Individual Studies); and (2) using the greater power of pooled analyses 
to gain insight into the nature of the drugs effectiveness in demographic (e.g., age, sex, race, and 
ethnicity) and other subpopulations, into dose-response, and into onset and duration of effect (see 
section III.C.2., Pooled Analyses of Data From More Than One Study).   
 
 
III.  FORMAT AND CONTENT OF THE ISE5  
 
The format (including section titles) of the ISE is flexible.  In many cases (as described below) 
the ISE can closely follow the format of the SCE.  Although applicants should take note of the 
following suggestions for content, they should choose the format that best suits the application.  
Applicants can consult with the appropriate review division to discuss specific plans for the ISE. 
 
When critical to the understanding of study results, tables and figures from individual studies and 
pooled data should be embedded in the text (e.g., tables or figures showing results of important 
endpoint analyses). Lengthy tables, detailed endpoint assessments, and presentations of 
statistical approaches should be placed in an appendix, rather than the main body of the ISE.  For 
the electronic common technical document (CTD), hyperlinks to tables should be provided 
within the body of the ISE. 
 
When more than one ISE is provided for an application with more than one indication, each ISE 
should have its own appendix with tables. 
 
The FDA is aware that there is a need for clarification regarding the scope and purpose of the 
ISE in relation to the content of the SCE.  The ISE is a self-contained, detailed analysis that  
comprehensively examines relevant data from multiple sources intended to provide the 
substantial evidence of effectiveness for a given drug, and describes additional information 
related to that effectiveness, such as dose-response, effects in population subsets, or timing of 
response. The ISE should provide integrated analyses of the cumulative information that can 
help guide the effective use of a new drug. In contrast, the SCE is a compact summary of the 
critical findings reported in the ISE, including individual trial reports and the overall evidence of 
                                                 
5 Some of the section headings in this guidance may be different  from the section headings in  2.7.3, Summary of 
Clinical Efficacy.  The headings in this guidance have been amended to correspond to the content within each 
section.  
  3
  Contains Nonbinding Recommendations 
effectiveness. The SCE should not contain any information or data not discussed or explained in 
the ISE. 
 
In some cases, the SCE can serve as the ISE if appropriate data can be included within the space 
limitations of the SCE.  This approach can be feasible for relatively simple drug development 
programs such as those that rely on a single adequate, and well-controlled effectiveness trial, or a 
few trials of similar design.  With respect to location of information within the CTD, the ISE 
should be included in Module 5, section 5.3.5.3, and the SCE in Module 2, section 2.7.3, as 
described in the guidance for industry Integrated Summaries of Effectiveness and Safety:  
Location Within the Common Technical Document.   
 
A.  Listing and Brief Results of Individual Studies 
 
A tabular listing of all studies relevant to drug effectiveness should be provided in this section.  
The tabulation and study descriptions will be used as an overview for subsequent analyses and 
comparisons of individual studies, as well as for analyses of pooled results.  In addition to 
completed studies, the listing should include ongoing studies and those that were terminated (for 
such studies, there may be no results available).  The listing should include studies reported both 
as integrated full reports and as abbreviated reports6 as well as trials reported only as 
publications in the medical literature.  Both positive studies and studies that failed to show 
effectiveness should be included. 
 
The listing should be followed by concise descriptions of all completed well-controlled studies, 
whether or not they supported effectiveness.  For each study, critical design features and 
important results should be briefly described, including the prospectively identified endpoints 
and planned statistical analyses.  Similar studies can be described together, but the individual 
study results should be provided. These brief study descriptions should include references or 
electronic links to the full study reports.  Each study presentation should provide enough detail to 
understand critical aspects of the study design and the study findings, including (as applicable) 
treatments compared, sample size, population studied, number and location of study sites, study 
drug dose and regimen, treatment duration, and results for primary and important secondary 
endpoints. In all cases, the observed results and estimates of effect (e.g., mean change from  
baseline on drug and placebo for blood pressure, progression-free survival for treatment and 
control arms in oncology studies, percent responders, hazard ratios), as well as confidence 
intervals and p-values should be provided. 
 
                                                 
6 See the ICH guidance for industry  E3  Structure and Content of Clinical Study Reports. 
  4
  Contains Nonbinding Recommendations 
B.  Analysis of Study Designs 
 
This section should include discussion and critique of the important design features of all studies 
that sought to assess effectiveness, irrespective of whether the data support or do not support a 
conclusion of effectiveness. To the extent possible, the important design features and the 
statistical methodologies used to analyze the results of the controlled studies that were intended 
to support effectiveness should be presented for the studies as a group.  Important similarities 
and differences among studies should also be presented (e.g., design, population, dose, duration, 
endpoints). Individual study reports should discuss these matters in greater detail. 
 
Examples of these important design features are as follows (see ICH E3 for additional important 
study characteristics): 
 
   Important inclusion and exclusion criteria that define the study population, for example: 
 
  Disease characteristics (e.g., severity, duration)   

  Demographic characteristics 
 
  Prior and concomitant illnesses 

  Treatment allowed, required, or not permitted 
 
 
 	  Potential differences between the population(s) included in effectiveness studies and the 
overall patient population expected to receive the drug when it is marketed (e.g., exclusion 
of patients over 75 years old in studies of a drug for a disease common in the elderly).  
 
 	  Type of control7   
 
  Placebo 
 
  No treatment 

  Active 
 
  Dose-response 

  Historical 

 
 	  Specific treatments (e.g., dose, frequency) used in each group. 
 
 	  Description of how concomitant treatment was chosen, if allowed for the disease or  
condition under study. For example, was it left to investigator choice?  Were there any 
limitations?  Were particular treatments required in both groups?  Any differences in 
permitted concomitant therapies between treatment groups should be noted. 
 
 	  Description of particular ancillary treatments (e.g., nonsteroidal anti-inflammatory drugs, 
proton pump inhibitors, drugs to manage hypertension) if required, encouraged, 
discouraged, or proscribed, and, where appropriate, the reasons for the treatments. 
 
                                                 
7 See 21 CFR 314.126. 
  5
  Contains Nonbinding Recommendations 
	   Basis for choice of active control treatments, with particular attention to selection of the 
active control used in noninferiority designs, choice of noninferiority margin,8 and support 
for the constancy assumption (i.e., the reason to believe that the effect of the active control 
drug in the present study is likely to have been similar to its effect in past studies). 
 
 	  Choice of endpoints (primary and secondary), with particular attention to the validity of 
surrogate endpoints and novel clinical or patient assessments.   
 
 	  Use of adjudication committees to assess endpoints.  
 
 	  Study duration; treatment duration. 
 
 	  Use of blinding, specific methods of blinding, and potential weaknesses (e.g., tablet 

enclosed in a capsule, odor of the study drug). 

 
 	  Dosage selection and assessment of dose-response.  Dose-response designs can include 
randomized fixed-dose dose-response, forced titration, and optional titration.9  If the fixed-
dose study had a titration phase or allowed upward or downward titration, this should be 
described. 
 
	   Randomization (e.g., stratified, nonstratified, allocation ratios). 
 
	   Use of enrichment approaches10 to identify subjects with high likelihood of events 
(prognostic enrichment) or high likelihood of response (predictive enrichment), including 
randomized withdrawal design (a type of predictive enrichment).  Any pharmacogenomic 
or proteomic assessments used in enrichment should be described. 
 
	   Use of other enrichment maneuvers (e.g., placebo run-in, means of encouraging 

compliance, exclusion of subjects with high baseline variability, use of less variable 

measurements, retention strategies).  

 
 	  Adaptive features.11  
 
 	  Use of a data monitoring committee and its specific responsibilities. 
 
                                                 
8 See the draft guidance for industry Non-Inferiority Clinical Trials. When  final, this guidance will represent the 
FDAs current  thinking on this topic.   
 
9 See the ICH guidance for industry  E4  Dose-Response Information to  Support Drug  Registration. 
 
10 See the draft guidance for industry Enrichment Strategies for Clinical Trials to  Support Approval  of Human 
Drugs and Biological Products.  When final, this guidance will represent the FDAs current thinking on this topic. 
 
11 See the draft guidance for industry Adaptive Design Clinical Trials for Drugs and Biologics.  When final, this 
guidance will represent the FDAs current thinking  on this topic. 
  6
  Contains Nonbinding Recommendations 
 	  Planned endpoints, including primary endpoint(s) and secondary endpoint(s) 
 
	   Prespecified plans for statistical analyses, including: 
 
	  Planned analysis for the primary efficacy endpoint 
 
	  Planned sequential analyses 
 
  Analysis population (e.g., intent-to-treat, per protocol, as treated), with specific 
definitions  
 
	  Methods for handling missing data  
 
  Methods of controlling type I error rate within studies when more than one endpoint 
or subpopulation is analyzed 
 
	  Planned interim analyses 
 
	   Important changes in study design made after the start of the study, noting whether they 
were made before or after study unblinding 
 
	  Change of primary endpoints during conduct of trial 
	  Dropping or adding treatment arms  
	  Changes in inclusion and/or exclusion criteria 
	  Sample size modification  
	  Planned adaptive features 
 
C.  Overall Analysis of Effectiveness Results  
 
The term integrated analysis  refers to using all relevant data from controlled trials, as well as  
other sources (e.g., clinical pharmacology trials), to enhance the understanding of the overall 
evidence of effectiveness.  Integrated analyses include both close examination of individual 
study results and, when appropriate, combined quantitative analyses (pooled analyses).  The 
integrated analysis is not a substitute for the analysis of individual studies.  Instead, it is intended 
to provide a clearer understanding of responses across studies, different populations (e.g., 
demographic, disease-related), and dosing regimens.  Differences in responses among studies 
should be described. 
 
This section of the ISE should provide a comprehensive, integrated, in-depth analysis of the 
overall effectiveness results, with a rationale for the methods used in the analysis.  All studies 
that sought to assess effectiveness should be included, irrespective of whether the data support, 
or do not support, a conclusion of effectiveness.  The extent to which the results of the relevant 
studies reinforce or do not reinforce each other should be discussed.   
 
The individual studies that are considered adequate and well-controlled investigations and that 
demonstrate the effect of the drug should be identified.  These are studies that provide the 
  7
  Contains Nonbinding Recommendations 
substantial evidence of effectiveness required for approval.  Applicants should describe any 
aspects of study design and conduct that could call into question the adequacy of the studies, 
together with an explanation of why the studies should nonetheless be considered adequate and 
well-controlled. 
 
The overall evidence of effectiveness should be examined, including assessments of study-to-
study consistency with respect to, for example, subpopulation results, cumulative distribution of 
effects (i.e., not just mean effects), time of onset, and duration of effect. 
 
The role of supportive data (such as data from animal models, pharmacologic effects, 
biomarkers, or studies of related diseases) should be described when appropriate, for example, 
when there is intent to rely on a single adequate and well-controlled clinical trial or where trials 
in different indications are intended to support approval for both conditions. 
 
In general, applicants should seek to provide the following information in this section of the ISE:  
  
	   A discussion of what the collective evidence shows, including critical limitations.  
 
	   A discussion of all studies that were intended to support efficacy, including those that 
failed to achieve statistical significance on their efficacy endpoint(s), with an explanation 
of the observed differences in results, if possible. 
 
	   A discussion of incomplete studies, including:  (1) studies terminated early because of  
lack of efficacy, a concerning safety signal(s), or other reasons; and (2) ongoing studies 
(e.g., long-term extension trials). 
 
 	  The estimated effect sizes, confidence intervals, and p-values for the individual studies 
supporting effectiveness. A presentation of p-values alone would not be adequate. 
 
 	  An assessment of the clinical meaningfulness of endpoints and their observed effect 
sizes.  
 
 	  The consistencies and inconsistencies across studies, including subpopulation effects, 
dose-response. 
 
 	  The reasons for considering some studies more persuasive than others.  
 
	   The problems arising from missing data and how these problems were addressed. 
   
 	  The study features that posed particular analytic challenges (e.g., effectiveness scales, 
patient-reported outcomes, composite endpoints), when appropriate. 
 
  8
  Contains Nonbinding Recommendations 
 	  In addition to effects on planned primary endpoints, an assessment, for studies that show 
an effect of time to onset of effect, and cumulative distribution of effects12 (see section 
III.F., Time to Onset of Effect, Persistence of Effect and/or Tolerance, Distribution of  
Responses, for additional information). 
 
As part of a comprehensive summary of experience related to effectiveness, this section of the 
ISE should include results of any other studies conducted using the study drug, published or 
unpublished, not conducted by the applicant, of which the applicant has become aware.  Of 
particular interest are: 
 
 	  Randomized, double-blind controlled clinical studies for the proposed indication  
 	  Randomized, double-blind controlled clinical studies for a closely related indication 
 	  Clinical studies exploring dose-response 
 
In addition, this section of the ISE should include discussion of pertinent clinical pharmacology 
data (including population PK and concentration-response modeling data).  Such data can clarify 
the exposure-response relationship, can contribute to a better description of dose-response, and 
can sometimes explain subpopulation differences.  In addition to comparing estimates of 
exposure-response across trials, it is generally desirable to perform an exposure-response 
analysis on pooled data. Such an analysis may reveal relationships that would not be detected in 
a single study. 
 
Particular attention should be paid to any recognized limitations of the effectiveness studies, such 
as short duration of study compared to specified use, small effect size, a number of failed studies 
of apparently adequate design, or reliance on a surrogate endpoint.  Thus, if an effectiveness 
claim is based on a surrogate endpoint, the basis for choice of the endpoint should be discussed 
and its validity as a predictor of clinical outcome should be supported.  This discussion may not 
be needed if the surrogate endpoint has been validated and relied upon as the basis of approval.  
For example, antihypertensive, oral hypoglycemic, and low density lipoprotein (LDL)-lowering 
drugs generally have been approved on the basis of demonstrated effects on blood pressure, 
blood sugar and HbA1c, and LDL cholesterol, respectively, without new evidence of an effect of 
the particular drug on survival or morbidity.  However, any novel surrogate endpoint (i.e., one 
not used previously by the FDA as a basis for approval) should be discussed and supported.   
 
As noted earlier, the analyses of effectiveness results generally should include two kinds of 
analyses: (1) comparison of results of individual studies; and (2) pooled analyses of data from  
more than one study. 
 
1.  Comparison of Results of Individual Studies  
 
Results from all controlled studies should be summarized, examined, and compared, as 
appropriate, using tables and figures (such as forest plots).  Important similarities and differences 
in patient populations (e.g., demographics, disease severity), control groups, doses, durations of 
                                                 
12 See the guidance for industry Clinical Studies Section  of Labeling for Human Prescription  Drug  and Biological  
Products  Content and Format. 
  9
  Contains Nonbinding Recommendations 
exposure, inclusion or exclusion criteria, endpoints, and statistical methods should be identified.  
Applicants should describe differences in quality  of blinding, dropout profiles, and variations in 
study conditions (such as differences in standard of care), as well as other factors they consider 
important.   
 
Tables that show major study design features, number of subjects, number of dropouts, baseline 
values, and major outcomes can be of value. 
 
Support for the proposed claim should be described in terms of the strength of statistical 
evidence, including consistency of findings, individual study strength, p-values, and confidence 
intervals. Findings that appear to weaken or limit the claim (e.g., failed or negative studies, 
including studies stopped for futility at an interim analysis) are important and should be 
described as well. 
 
Comparisons of results across studies should focus on the prespecified primary endpoints.  
However, when important data elements are common to all studies (even if not the primary 
endpoint), analyses of such elements can provide an important assessment of consistency.  For 
example, in a series of studies where an important variable was assessed at multiple time points, 
an analysis comparing results obtained at a common time point should be shown, even if the time 
point for the primary analysis differed among studies.  For studies employing composite 
endpoints, where there are clinically important events that occur infrequently (e.g., death), a 
comparison of frequencies or rates of this event across studies should be displayed.  If results as 
a function of time are important, study results can be displayed in a figure that illustrates the 
change over time in each study, again, even if this was not a primary endpoint.  Important 
secondary endpoints, particularly in the context of a study that succeeded in achieving the 
primary endpoint, should also be shown.    
 
Ordinarily, studies with similar controls (e.g., placebo control, active control) should be 
discussed together. Graphic displays of common analyses can be helpful.  Forest plots can be 
used to display study results on a common axis.  These plots can show individual study p-values 
and confidence intervals. 
 
If there are important differences in outcome among studies of generally similar design, these 
differences should be displayed and discussed. Factors such as differences in subject 
demographics, disease definition, disease stage, disease severity, prior treatment, drug dose or 
regimen, or methods of observation may underlie such differences.  Unanticipated study 
conditions (e.g., site-related differences in standard of care) that could explain differences in 
effectiveness should be identified where possible.  Often such analyses will raise questions for 
future exploration rather than provide definitive answers. 
 
2.  Pooled Analyses of Data From More Than One Study 
 
Analyses that use information combined from all studies also should be performed as part of the 
ISE. In contrast to the overview of individual studies, which compares and contrasts outcomes 
from individual studies, these analyses should be performed by pooling subject-level data or 
pooling common outcomes from individual studies.  There is no consensus on how best to 
perform pooled analyses, and a variety of methods can be used.  The applicant should explain the 
  10
  Contains Nonbinding Recommendations 
specific analyses used and the reasons for their selection.  Formal meta-analysis procedures that 
produce valid effect estimates and associated uncertainties should be used when appropriate. 
 
Data should be pooled to examine the effect of demographic (e.g., age, sex, race, and ethnicity) 
and other characteristics (e.g., presence of specific concomitant illnesses or treatments), where 
the individual studies would have too few subjects with these characteristics to support 
meaningful conclusions.  These subpopulation analyses are discussed in section III.D., 
Comparison of Results in Subpopulations.  Pooled analyses can be performed on study-level 
summary data or on subject-level data. 
 
Differences among individual studies can affect the validity and interpretability of pooled 
analyses. Particular caution is warranted when the studies differ with respect to: 
 
 	  Important demographic or disease characteristics (e.g., duration, severity, specific signs 
and symptoms, previous treatment, concomitant diseases and treatments, prognostic or 
predictive biomarkers) 
 
 	  Treatment practices, including methods of assessing effectiveness, specific test 

procedures (e.g., methods of exercise testing, pulmonary function testing) 

 
 	  Study design features (e.g., study duration, study size, doses studied, allocation ratio to 
treatment and control arms, visit frequency) 
 
Such differences can make study results heterogeneous, requiring cautious interpretation.  Thus, 
consistency of populations and treatment practices across studies should be examined before 
pooling. When significant heterogeneity is not observed, pooling can reveal subpopulation 
differences that could not be detected in individual studies.  Differing allocation ratios across 
studies need to be taken into account in pooling (Dong 2005).   
 
Although there are occasional clinical development programs that include a planned analysis of 
efficacy across more than one study, such analyses are unusual.  For example, an NDA could 
include two large cardiovascular outcome studies, each examining major adverse cardiovascular 
events as their primary endpoint (e.g., cardiovascular death, nonfatal heart attack, and nonfatal 
stroke). A prospectively planned analysis of mortality across both studies can be specified as 
part of the development plan.  Because prospectively planned efficacy analyses across two or 
more studies in a development program is uncommon, the majority of pooled analyses described 
for inclusion in the ISE are exploratory in nature. They are designed to probe the data for trends 
across more than one study (e.g., in disease-specific subgroups, trends across multiple doses).   
 
D.  Comparison of Results in Subpopulations 
 
Subpopulation assessments, required under 21 CFR 314.50(d)(5)(v), can identify differences in 
the effectiveness profile of the drug among subpopulations.  Such differences, if found, may be 
important.  Subgroup analyses should be viewed as a component of the overall assessment of 
safety and efficacy but generally should not be intended to support statistically meaningful 
interpretations of the data in a particular subgroup.  To that end, an integrated analysis of the 
  11
  Contains Nonbinding Recommendations 
effect of treatment in subpopulations of interest should summarize and compare results across 
the controlled studies that are described in the ISE, both in individual studies, where there is 
sufficient subgroup representation, and in pooled analyses.  Although all controlled trials should 
be pooled for these analyses, applicants also should provide a separate analysis that excludes 
studies in which no overall treatment effect was demonstrable.  
 
Subpopulations analyzed should include those defined by major demographic factors (e.g., age, 
sex, and race or ethnicity), as required by 21 CFR 314.50(d)(5)(v), and those that can be 
analyzed by other predefined or relevant intrinsic and extrinsic factors (e.g., disease severity, 
prior treatment, concomitant illness, concomitant drugs, alcohol or tobacco use, body weight, 
renal or hepatic function), or by region. For continuous variables (e.g., age, weight, creatinine 
clearance), subgroup analyses by quartile or quintile should be considered, in addition to 
analyses using fixed cut-points (e.g., age older than 75).   
 
The integrated analysis should examine the consistency of the observed treatment effect across 
individual studies for demographic subpopulations and for other relevant subpopulations.  For 
example, if effectiveness data are generated from trials both within and outside the United States, 
there should be comparisons of results in U.S. and non-U.S. populations.  The assessment across 
subpopulations can highlight apparent variations in effectiveness that call for further 
investigation and discussion.  However, the limitations of such analyses should be recognized.13   
It is important to note that their purpose is not to provide the basis for specific claims or to 
attempt to improve the evidence of effectiveness in situations where the individual study results 
are disappointing. 
 
As noted, the integrated subpopulation analyses should include both individual studies (where 
subpopulations are large enough for this to be useful) and pooled analyses.  For the larger 
subpopulations (e.g., sex subgroups), there should be a side-by-side summary and comparison of 
individual study results. For ease of visual comparison, results could be presented as forest plots 
and as tabular summaries showing point estimates and confidence intervals.  Forest plots can be 
used to display subset results in large outcome  trials and meta-analyses of trials to assess  
dichotomous cardiovascular endpoints, (i.e., event:  yes/no). They also could be used to show 
subset analyses of pooled data from trials designed to ameliorate the symptoms of a disease or 
condition. 
 
In most cases, analyses of subpopulation effects in data pooled across studies are more likely 
than analyses in individual studies to have adequate power to assess differences.  A quantitative 
analysis of data pooled across studies generally should be shown.  Consideration should be given 
to conducting analyses that both include and omit studies that failed to show an effect.  
Differences among subpopulations that are consistent across studies and of a meaningful size 
from a clinical perspective may generate hypotheses that can be tested in future studies.  In some  
cases, where results are persuasive, it is important to describe differences in effects in 
subpopulations.  
 
                                                 
13 See the ICH guidance for industry  E9  Statistical Principles for Clinical Trials. 
  12
  Contains Nonbinding Recommendations 
E.  Analysis of Clinical Information Relevant to Dosing Recommendations 
 
This section should provide an integrated summary and analysis of all data, including data from  
individual dose-response clinical studies, relevant pooled analyses, and clinical pharmacological 
studies, that pertain to the dose-response or blood level-response relationships of effectiveness 
(including dose-blood level relationships).  These data contribute importantly to dosing 
recommendations, including the choice of dose interval.  The individual study results and any 
cross-study analyses that will be used to support the dosing recommendations (including the 
recommended starting and maximal doses, the method of dose titration, dose schedule, and any 
other instructions regarding individualization of dosage) should be summarized here.  These 
results and analyses should include descriptions of relatively straightforward dose-response or 
blood level-response relationships as well as any identified deviations caused by nonlinearity of 
pharmacokinetics, delayed effects, tolerance, or enzyme induction.   Limitations of the data (e.g., 
titration designs were used instead of fixed-dose designs) should be described and assessed. 
 
Differences in PK or pharmacodynamic responses should be discussed, or discussions can be 
cross-referenced in section 2.7.2, Summary of Clinical Pharmacology Studies, CTD Module 2.  
Differences in dose-response relationships that result from age, sex, race, ethnicity, disease, or 
other factors should also be described.  The methods for evaluating differences should be 
described, even if no differences were found.  Examples include specific studies in 
subpopulations, analyses of effectiveness results by subpopulation, and blood level 
determinations of the study drug.  
 
F. 	 Time Course of Effect, Persistence of Effect and/or Tolerance, Distribution of 
Responses 
 
For both symptomatic treatments and drugs that affect outcome (e.g., cardiovascular outcome  
studies, oncology studies), the time course of the effect should be displayed.  These can usually 
best be displayed graphically (e.g., difference in symptom scores between drug and placebo over 
time; Kaplan-Meier curves for cardiovascular outcome studies and oncology studies).14  
 
Therapeutic effects of a treatment can decline over time because of tolerability issues (subjects 
who experience adverse events and refuse treatment), or from the development of drug resistance 
or tolerance (loss of therapeutic effects over time), or because the disease tends to resolve 
spontaneously. Applicants should provide the number of subjects for whom long-term  
effectiveness data are available; the dose, duration of exposure, and the reason for 
discontinuation. 
 
The focus of the analysis of persistence of effectiveness and/or tolerance effects analyses should 
be controlled studies specifically designed to collect effectiveness data.  For example, a 
randomized withdrawal study is a powerful method of assessing persistence of effect.  The 
controlled studies should be clearly differentiated from other, less rigorous studies, such as open-
                                                 
14 See the guidance for industry Clinical Studies Section  of Labeling for Human Prescription  Drug  and Biological  
Products  Content and Format. 
  13
  Contains Nonbinding Recommendations 
label extension studies. Data relevant to withdrawal or rebound effects should be presented in 
the appropriate safety sections. 
 
In addition to mean drug effect in a study, the distribution of responses in individuals should be 
examined and displayed.  Distributions can be displayed using histograms to show outcomes or 
changes of various sizes for treatment and control groups (e.g., the number or percentage of 
subjects with worsening symptoms or change in effectiveness measure, and 0 to 10 percent, more 
than 10 to 20 percent, more than 20 to 30 percent, etc., improvement in symptoms or change in 
effectiveness measure) or by using cumulative distribution curves, showing the effect in all 
subjects in treatment and control groups. 
 
G.  Exploratory Investigations 
 
Results of exploratory analyses based on endpoints, patient subpopulations, and pooled data not 
specified in the protocol can be reported.  Such analyses may provide important insights, or lead 
to hypotheses for examination in future studies.   
 
  14
  Contains Nonbinding Recommendations 
GLOSSARY 

 
Drug  For purposes of this guidance, this term  refers to both human drugs and biological drug 
products regulated by the Center for Drug Evaluation and Research and the Center for Biologics 
Evaluation and Research unless otherwise specified. 
 
Efficacy and Effectiveness  These terms are used variably and often interchangeably by the 
scientific and regulatory communities.  For purposes of this guidance, the term  effectiveness is 
being used because it is the more commonly cited term in the Code of Federal Regulations, and 
is defined for purposes of this guidance as referring to the therapeutic effect (i.e., effect on signs, 
symptoms, or outcomes of a disease or condition) of the drug. 
 
Integrated Analysis  For purposes of this guidance, this term refers to using the collective 
results of individual studies to provide further insight into the effectiveness of a study drug.   
 
Pooled Analyses  This term has sometimes been referred to broadly as meta-analyses but 
many observers have distinguished between the two terms based on the methodological rigor 
needed for valid meta-analyses.  Nevertheless, for purposes of this guidance, this term refers to 
all analyses of data from more than one study. 
 
Subgroups, Subpopulations, and Subsets  For purposes of this guidance, these terms are 
used interchangeably. 
 
 
  15
  Contains Nonbinding Recommendations 
REFERENCES 
 
 
Literary  
 
Dong, J, 2005, Simpsons Paradox, Encyclopedia of Biostatistics, Online, John Wiley & Sons, 
Ltd., http://onlinelibrary.wiley.com/doi/10.1002/0470011815.b2a10055/compoundindex.  
 
EMEA, 2000, Committee for Proprietary Medicinal Products (CPMP) Points to Consider on 
Validity and Interpretation of Meta-Analyses, and One Pivotal Study (DRAFT), EMEA, EWP 
secretariat, October, 
http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2009/09/WC500 
003659.pdf. 
 
National Research Council, 2010, The Prevention and Treatment of Missing Data in Clinical 
Trials, Washington, DC:  The National Academies Press. 
 
Guidances and MAPPs15  
 
Draft guidance for industry Adaptive Design Clinical Trials for Drugs and Biologics16  
 
Draft guidance for industry Enrichment Strategies for Clinical Trials to Support Approval of 
Human Drugs and Biological Products17  
 
Draft guidance for industry Non-Inferiority Clinical Trials18  
 
Guidance for industry Clinical Studies Section of Labeling for Human Prescription Drug and 
Biological Products  Content and Format  
 
Guidance for industry Guideline on Format and Content of Clinical and Statistical Sections of an 
Application  
 
Guidance for industry Integrated Summaries of Effectiveness and Safety:  Location Within the 
Common Technical Document  
 
                                                 
15  Guidances for industry  can be  found on the FDA Drugs guidance  Web page at 
http://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/default.htm.  MAPPs can be  
found on the Manual  of Policies and Procedures Web page at  
http://www.fda.gov/AboutFDA/CentersOffices/OfficeofMedicalProductsandTobacco/CDER/ManualofPoliciesProce 
dures/default.htm.  
 
16  When final, this guidance will represent the FDAs current  thinking on this topic. 
 
17  When final, this guidance will represent the FDAs current  thinking on this topic. 
 
18  When final, this guidance will represent the FDAs current  thinking on this topic. 
  16
  Contains Nonbinding Recommendations 
Guidance for industry Providing Clinical Evidence of Effectiveness for Human Drug and 
Biological Products  
 
Guidance for industry Providing Regulatory Submissions in Electronic Format  Standardized 
Study Data   
 
ICH guidance for industry E3 Structure and Content of Clinical Study Reports  
 
ICH guidance for industry E5 Ethnic Factors in the Acceptability of Foreign Clinical Data  
 
ICH guidance for industry E9 Statistical Principles for Clinical Trials  
 
ICH guidance for industry E10 Choice of Control Group and Related Issues in Clinical Trials  
 
ICH guidance for industry M4E The CTD  Efficacy, Section 2.7.3, Summary of Clinical 
Efficacy 
 
MAPP 6010.3 Rev.1 Clinical Review Template, Attachment A, Section 6, Review of Efficacy 
 
MAPP 6010.4 Good Review Practice: Statistical Review Template  
 
  17