The Costs and Effectiveness of Cervical

Cancer Screening in Elderly Women

February 1990

OTA-BP-H-65

NTIS order #PB90-166018
Recommended Citation:

U.S. Congress, Office of Technology Assessment, The Costs and Effectiveness of Screening

for Cervical Cancer in Elderly Women-Background Paper, OTA-BP-H-65 (Washington,

DC: U.S. Government Printing Office, February 1990).

Library of Congress Catalog Card Number 89-600780

For sale by the Superintendent of Documents

U.S. Government Printing Office, Washington, DC 20402-9325

(order form can be found in the back of this report)
Costs and Effectiveness of Cervical Cancer Screening

in Elderly Women

by

Charlotte Mullera

Jeanne Mandelblattb

Clyde B. Schechtera

aDepartment of Community Medicine

Mt. Sinai School of Medicine

bNew York city Health and Hospitals Corporatio n

and

Elaine J. Power

Brigitte M. Duffy

Judith L. Wagner

Health Program

Office of Technology Assessment

U.S. Congress

Washington, DC 20510-8025

February 1990

A Background Paper

in OTA’s Series on

Preventive Health Services Under Medicare

This paper was prepared for desk-top publishing by Karen Davis and Carol Guntow.

The views expressed in this paper do not necessarily

represent those of the Technology Assessment Board,

the Technology Assessment Advisory Council,

or their individual members.
in the

FOREWORD

Interest in health promotion and disease prevention strategies for the elderly has grown

last ten years, at least partly as a result of the search for ways to moderate the rising

costs of health-care in this growing segment of the population. Reflecting this interest, the

House Committee on Ways and Means requested that OTA analyze the effectiveness and costs of

providing selected preventive health services to the elderly under the Medicare program. The

Senate Labor and Human Resources Committee has also requested that OTA provide information on the value of preventive services for the American people. This paper, Costs and Effectiveness of Cervical Cancer Screening in Elderly Women, is the fourth in a series of papers being

prepared in response to these requests.

Cervical cancer screening with the Pap smear test is a preventive service that is routinely

performed on women of all ages but that is much less common among elderly than among

younger women. This paper examines what is known about the course of cervical cancer in

elderly women; the effectiveness of the Pap test and its accuracy in this age group; the relative

costs and effectiveness of different screening test schedules for elderly women; and the implications of these findings for Medicare.

Previous papers in this series on “Preventive Health Services Under Medicare” have assessed screening for open-angle glaucoma, the current use of preventive services by the elderly,

and screening for cholesterol. Future papers will assess screening for colorectal cancer and analyze broad issues related to Medicare financing of preventive health services for the elderly.

Directo r

. . .

Ill
CONTENTS

Chapter Page

1. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....... . 1

2. Cervical Cancer in Elderly Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Cervical Neoplasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Incidence, Prevalence, and Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Natural History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Diagnosis and Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Screening: The Pap Smear . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Pap Smear Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Effectiveness of Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Screening Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Utilization of Screening by the Elderly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

3. The Cost-Effectiveness of Screening in Elderly Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

The Cost-Effectiveness Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Implications for Medicare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Coverage Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Quality and Reimbursement Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Resource Considerations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Appendix

A. Advisory Panel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

B. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

C. Expert Panel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

D. Review of Estimates of Progression Probabilities and Duration of States of

Cervical Neoplasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

E. Markov Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

F. Basis for Input Assumptions and Calculation of Cost Components in

the Cost-Effectiveness Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. 75

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ........ 76

iv
CONTENTS (cent’d)

Boxes

Box Page

A. Human Papilloma Virus and Cervical Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

B. Other Potential Screening Technologies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

C. Types of Bias in the Evaluation of Screening Programs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Tables

Table Page

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

Annual Incidence of CIN, CIS, and Invasive Cervical Cancer in Elderly Women ...................5

Prevalence of CIN, CIS, and Invasive Cervical Cancer in Elderly Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Cervical Cancer Mortality, 1973-85 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Selected Prospective Studies of Progression/Regression of Cervical Neoplasia...... . . . . . . . . ..1 3

Duration of Cervical Neoplasia: Selected Study Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Duration of Cervical Neoplasia: Findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Studies Assessing the Accuracy of the Pap Smear . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Case-Control Studies of Pap Smear Effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Recommendations for Cervical Cancer Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Utilization of Routine Pap Smear Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Cost-Effectiveness Model Input Data Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Summary of Cost Estimates for Different Components of Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Model Results: Life-Years Saved . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Model Results: Numbers of Smears Taken and Cases Detected . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Model Results: Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Cost-Effectiveness of Screening Under Alternative Screening

Assumptions: Base Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Cost-Effectiveness Model Input Data Assumptions Selected Sensitivity Analyses ................45

Cost-Effectiveness of Screening Under Alternative Screening Assumptions:

Selected Sensitivity Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Prices for Services

Estimated Costs of

Estimated Costs of

Estimated Costs of

Estimated Costs of

Estimated Costs of

Estimated Costs of

Estimated Costs of

Figure

Figure

Related to Cervical Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Diagnosing and Treating Cervical Intraepithelial Neoplasia....................68

Diagnosing and Treating Carcinoma In Situ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

Diagnostic Admission for Cervical Cancer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

Diagnosing and Treating Early Invasive Cervical Cancer........................7l

Diagnosing and Treating Late Invasive Cervical Cancer .........................72

Followup Care for CIN and CIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Followup Care for Invasive Cervical Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

1. Calculation of Sensitivity and Specificity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1. SUMMARY

Cancer of the uterine cervix is not a disease restricted to young women. One-fourth

of new cases of invasive cervical cancer occur

in women age 65 and over; 1,867 elderly

women died of this disease in 1986.

Compared to young women, elderly

women appear to have lower rates of localized (noninvasive) tumors, 1 but they have

higher rates of invasive cervical cancer.

Elderly women are also more likely than

younger women to have advanced (rather

than early) invasive disease at the time of

diagnosis.

The prevalence of invasive cervical cancer in elderly women is estimated to be between approximately 2 and 8 per 1,000, or

roughly 38,000 to 152,000 women age 65 and

over. Incidence is about 0.25 to 0.35 new

cases per 1,000 elderly women per year, or

about 4,800 to 6,700 new cancers each year.

Across all ages, women at high risk of cervical cancer are those who are poor, are nonwhite, were young at age of first intercourse,

have had multiple sexual partners, or smoke.

Among elderly women, those who have not

previously been screened are at especially

high risk.

Pap smear screening, combined with appropriate treatment, is an effective method of

reducing mortality and morbidity from cervical cancer. In areas where it has been introduced, Pap smear screening has generally

been associated with lower mortality from the

disease. Case-control studies have found that

women who have been screened are two to

ten times less likely than others to develop

cervical cancer. The protection associated

with prior screening is found in elderly

women as well as among younger women.

Elderly women, however, are less likely to be

1 The finding that elderly women have low rates of

noninvasive tuners relative to their overall rat e

of invasive cancer may be due in part to lowe r

screening (i. e. , less opportunity to detect such

symptomless tuners) in older women.

screened than younger women and have seen

less reduction in mortality rates than other

groups. Future cohorts of elderly women

may be better-screened, as the current group

of younger women (with higher screening

rates) ages.

Although elderly women as a group

would reap benefits from cervical cancer

screening, the implications of screening

elderly women are different from those for

younger women. Pap smears probably yield a

higher proportion of both false positive and

false negative tests in elderly women. Pap

smears from elderly women are sometimes inadequate due to anatomical changes associated

with age, which may increase the number of

false negative test results. Also, some conditions that are prevalent in older women can

lead to false positive test results. No studies

directly comparing the accuracy of the Pap

test in elderly and nonelderly women have

been performed.

Medicare coverage of Pap smear screening is one possible measure to increase

utilization of this test among elderly women.

Until very recently, however, Medicare paid

for Pap smears only as a diagnostic test (e.g.,

after symptoms of cervical cancer developed).

2 One consideration in the implementation of a screening benefit is the relative

cost-effectiveness of different Pap smear

screening schedules for elderly women. The

cost-effectiveness model in this paper simulated the costs (to the health care system) and

the benefits of Pap smear screening for a

hypothetical cohort of women who enter the

system at age 65. The results of the model

indicate that Pap smear screening in elderly

women does not appear to be very costly for

2 The Omnibus Reconciliation Act of 1989 extended

Medicare coverage to Pap smear screening. Test s

are reimbursable if a woman has not had a Medicarecovered test within 3 years. The Secretary of th e

Department of Health and Human Services has th e

option to make high-risk women eligible for mor e

frequent coverage. The benefit takes effect Jul y

1, 1990.

1
2 ■ Costs and Effectiveness of Cervical Cancer Screening

the potential years of life saved from this

technology, although it is unlikely to actually

save health care costs.

Under base case assumptions, the model

found that a single screening of women at

age 65, when they became eligible for

Medicare, would save 14,400 life years per 1

million women screened (discounted at 5 percent) and would cost the health care system

$1,666 Per year of life saved.

s The incremental cost per year of life saved is least

for 5-year screening ($1 ,453) and is progressively greater as screening frequency increases. It amounts to $5,956 per life-year

saved for the incremental effects of a 3-year

screening cycle over a 5-year cycle, and rises

to $39,693 for annual screening. The model

considers only direct cancer-related health

care costs and the benefits of lives saved.

Potential benefits such as employment and

disability-free days, and costs such as future

medical costs incurred by extending life, are

not included.

The cost-effectiveness of cervical cancer

screening under base-case assumptions is

comparable to other preventive services for

elderly individuals. The cost-effectiveness of

3 "Cost per year of life saved” is a measure tha t

enables direct comparisons of different health in -

terventions (in this case, cervical cancer screen -

ing at different time intervals) . In this analy -

sis, the medical costs of each screening program--

including screening, diagnosis, treatment, an d

identification of women who had false-positiv e

screening test--were weighed against the benefit s

of preventing deaths due to cervical cancer i n

women whose disease was detected by the screening

program.

Pap tests every 3 years is similar to that of

vaccination against pneumococcal pneumonia

(136,155); the cost-effectiveness of annual

Pap tests is comparable to annual mammogram screening for breast cancer in elderly

women (156).

The cost-effectiveness ratio for Pap

smear screening depends heavily on the extent to which high-risk, rather than low-risk,

women are screened. Low-risk women derive

some benefit from screening, but at very high

cost to the health care system. Screening

only high-risk women, on the other hand,

has a very low cost per life-year saved. This

difference has implications for the results of

the new Medicare benefit that extends

coverage to all elderly women. The cost per

life-year saved by screening could be considerably reduced if such a benefit were combined with measures to raise the utilization of

the benefit by high-risk women above the

average rate for the population as a whole

(even though the resultant higher utilization

would raise total program costs). Because the

cost of screening is also highly sensitive to

the accuracy of the test, increased investment

in laboratory accuracy would likewise increase program effectiveness and reduce the

cost per year of life saved.

Cervical cancer is only one of many gynecological diseases that can affect elderly

women. Endometrial cancer, for example, is

particularly prevalent in this age group (79).

A negative Pap smear does not necessarily

protect against other uterine cancers. The

results of this paper cannot be used to draw

any conclusions about the general need for

gynecological care in elderly women.
2. CERVICAL CANCER IN ELDERLY WOMEN

INTRODUCTION

Despite widespread acceptance of the Pap

smear, death from cervical cancer has not

been eliminated. Among the elderly, 1,867

women in the United States died from cervical cancer in 1986(96). Over 43 percent of

deaths from cervical cancer occur in women

age 65 and older (165).

Cervical cancer, and screening for the

disease, has some unique features in the

elderly age group. First, the profile of the

disease is different in elderly than in nonelderly women; in particular, the disease in

elderly women is more likely to be at an advanced stage at the time it is diagnosed (63).

Second, elderly women have much lower

screening rates than younger women (61), and

they have a different perspective on the place

of the test in gynecological care. Whereas

most younger women have lived in an era in

which Pap smear screening is part of the

standard medical regimen, many of today’s

elderly women were already past childbearing, and no longer seeing a gynecologist, by

the time the test came into widespread use.

This paper deals with the usefulness of

the Pap smear in preventing morbidity and

mortality from invasive cervical cancer in

elderly women. This chapter reviews the

known natural history of cervical cancer, the

accuracy of the Pap smear in screening for

cancer, the effectiveness of Pap smear

screening programs in preventing the disease,

and the utilization of screening by elderly

women . Chapter 3 presents a costeffectiveness model simulating a Pap smear

screening program for the elderly and discusses the implications of the model results

for Medicare if such a benefit were offered

as part of that program.

CERVICAL NEOPLASIA

Terminology

The term “cervical neoplasia”l encompasses the spectrum of abnormalities of

the uterine cervix (the neck of the uterus)

that relate to cancer and its precursors. Cervical neoplasia can be divided into two categories depending on the extent that abnormal,

undifferentiated cells have replaced normal

tissue. 2

In the first category, abnormal cells are

confined to the surface (epithelial) tissue

layer. Traditionally, dysplasia has been used

to refer to the partial replacement of normal

epithelial cells with abnormal cells (dysplasia

is subcategorized as mild, moderate, or

severe, depending on the extent of replacement). Carcinoma in situ (CIS) is the traditional term describing the condition in which

abnormal cells extend throughout the entire

depth of the epitheliums.

Under newer terminology, both terms are

often subsumed under the single category of

cervical intraepithelial neoplasia (CIN).

1 ”Neoplasia" is a generic term (meaning “new

growth’1) that applies to the abnormal proliferation

of cells and tissues.

2 Normal cells show normal maturation and growth

and are "differentiated" with certain characteristics that accompany their function (e. g., a s

epithelial cells) . In cancer, the mature cells ar e

replaced by abnormal cells that are undiffer -

entiated, immature in appearance, and have certain

chromosomal changes indicative of the abnorma l

proliferation that is associated with cancer.

3
4 • Costs and Effectiveness of Cervical Cancer Screening

Three grades of CIN are distinguished by the

extent to which abnormal cells occupy the

epithelial layer:

■ CIN grade 1 --abnormal cells are confined to the bottom one-third of the

epitheliums (corresponds roughly to mild

dysplasia).

• CIN grade 2--abnormal cells occupy the

bottom two-thirds of the epitheliums

(corresponds to moderate dysplasia).

■ CIN grade 3--all, or all but the surface

cell layer, of the epitheliums is composed

of abnormal, undifferentiated cells (includes both severe dysplasia and CIS)

(102).

The terms used in related literature vary

depending on whether they predate the introduction of CIN terminology. Most early

reports discuss the states of neoplasia in terms

of dysplasia and CIS. In practice, however,

severe dysplasia and CIS are difficult to distinguish. This difficulty was one of the reasons for implementing the CIN terminology,

where the two are encompassed by the single

state of CIN grade 3. To simplify the terms

used and to represent literature results as accurately as possible, this paper uses “CIN” to

represent mild and moderate dyplasia (i.e.,

CIN grades 1 and 2) and “CIS” as shorthand

for severe dysplasia/CIS (i.e., CIN grade 3).

The second category of cervical neoplasia

comprises all stages of invasive cervical cancer, in which abnormal cells “invade” the

body by extending into inner cervical tissue

and eventually spreading to other parts of the

body. Cervical cancer has traditionally been

subcategorized according to whether it was

symptomatic and the extent to which it has

spread to the uterus and the rest of the body.

The four stages of invasive cancer are:

■ Stage I--cancer is confined to cervix,

■ Stage II--cancer extends beyond cervix

but has not reached pelvic wall,

■ Stage III--cancer extends to pelvic wall,

and

■ Stage IV--cancer extends beyond pelvis.3

Each of the four stages is further subcategorized according to spread and symptoms. For example, stage IA includes

preclinical cancer-- cancer that is visible only

through a microscope and that has no overt

signs. In this paper, “cervical cancer” and

“invasive cancer” refer to stages I-IV; “early

invasive cancer” refers to stage I only, and

“late invasive cancer” to stages II through IV.

Incidence, Prevalence, and Risk

Incidence and Prevalence Rates

Data on the incidence and prevalence of

cervical neoplasia in elderly women are

scarce. Many programs do not target older

women and consequently do not report agespecific rates for women in this age group.

Existing incidence and prevalence rates for

the various states of cervical neoplasia in elderly women are presented in tables I and 2.

These rates are derived from a variety of

sources and require some caution in interpretation and comparison. Some important

caveats are:

■ Rates in each source are dependent on

the protocol for that particular study or

program (e.g., interval between screening tests, number of prior tests) and accuracy of diagnosis.

● Reported rates combine women who are

asymptomatic (but test positive) with

those who have symptoms of cancer.

■ Rates may be underestimated in the

elderly due to under-screening.

3 Stage O is often used with this terminology to

indicate CIS.
Costs and Effectiveness of Cervical Cancer Screening ■ 5

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8 ■ Costs and Effectiveness of Cervical Cancer Screening

Rates may be underestimated in the

elderly due to under-ascertainment when

death from other causes occurs before

diagnosis.

Incidence rates may be falsely elevated

when women with prior false-negative

smears and women who have not been

screened previously are included in the

rates. These factors are particularly

likely to occur among elderly women.

Many rates are from studies over two

decades old and may not be applicable

to current and future cohorts of elderly

women.

Compared to younger women, elderly

women have lower incidence rates of CIS but

higher incidence rates of invasive cancer

(3,27,30,39,46,69,157). This observation has

prompted the suggestion that the course of

cervical neoplasia may be faster in elderly

women, with a high proportion of CIS progressing to invasive cancer. Some researchers

have found a slower progression of CIN in

older women, however (100). It remains unclear whether the lower apparent incidence of

CIS in elderly women is due to less new disease, or whether it is due to lower screening

Table 3--Cervical Cancer

rates (with elderly women more likely to have

undiagnosed CIS or CIS detected just before

it progresses to invasive cancer).

As shown in table 3, mortality from cervical cancer is higher in older women than in

younger women and higher in black women

than in white women (160). Rates have

decreased substantially over time in both

older and younger age groups; between 1973-

1974 and 1985-1986, mortality rates declined

by 17 percent for women age 50 and over

and by a striking 43 percent for younger

women. Nevertheless, mortality rates in

black women age 50 and ever are still nearly

triple the rates of white women in this age

group (160).

Risk Factors

General Factors-- As discussed later in

this chapter, prior screening reduces a

woman’s risk of developing invasive cervical

cancer, presumably because precancerous abnormalities are discovered and treated. Based

on the little information available, the protective effect of screening appears to be particularly strong for elderly women (29).

Mortality Rates,a 1973-85

I

Percent change

1973 1975 1977 1979 1981 1983 1985 1973-1985

Under age 50

White women 1 . 6 1 . 4 1 . 2 1 . 2 1 . 2 1.1 1.1 -31 .3%

Black women 5.0 4.2 3.6 3.3 2.7 2.8 2.4 -52.0

Age 50 and over

White women 12. 9 11. 6 10. 6 9 . 8 9.0 8.1 7.5 -41. 9

Black women 37. 5 31. 9 29. 8 25. 7 24. 5 23. 5 21. 1 -43. 7

All ages and races 5. 2 4 . 6 4 . 1 3 . 8 3 . 6 3 . 3 3 . 1 -37. 5

a

Rates per 100,000 women. Rates are age-adjusted to the 1970 U.S. standard population.

SOURCE : Office of Technology Assessment, 1990; from data in U.S. Department of Health and Human Services,

National Institutes of Health, National Cancer Institute, 1987 Annual Cancer Statistics Review, N I H

Pub. No. 88-2789 (Bethesda, MD: National Cancer Institute, February 1988).
Costs and Effectiveness of Cervical Cancer Screening • 9

Most other information regarding the

risk of developing invasive cervical cancer

among different populations is derived from

studies of nonelderly populations. In general,

risk of cervical cancer is strongly related to

sexual activity; women with a history of

several sexual partners and women who were

young at the age of first intercourse are at

much higher risk than women who have

never had sex ( 119). The observed association between cervical cancer and sexual activity may be due in part to the human papilloma virus (HPV), a sexually transmitted

virus that has been implicated in cervical

neoplasia (box A). Women who have used

foam or jelly as contraceptive methods are at

relatively low risk of cervical cancer, and

women with genital infections are at higher

risk, supporting the hypothesis that cervical

cancer derives from a sexually transmitted

disease (137).

Other personal and socioeconomic characteristics are also associated with risk of cervical cancer. Smoking has been associated

with an increased risk of the diseas e

(138,174). In addition, black women, women

from the southwestern United States, and

poor women have higher incidence and

prevalence rates of cervical neoplasia than

other groups (1 19,160). In 1986, for example,

the incidence of invasive cervical cancer in

black women age 50 and over was more than

double that for white women in this age

group (38 v. 15 per 100,000) (160).

Age-Specific Factors--Some indirect

evidence suggests that elderly women may be

more vulnerable to cervical cancer than

younger women as a result of diminished immune function. First, viral agents, against

which the immune system acts, are probably

involved in the initiation or promotion of

cervical neoplasia. Second, women whose

immune systems are deliberately suppressed

(e.g., as an adjunct to organ transplants) have

higher than expected risks for developing

cervical neoplasia (109,134). Elderly women

with either latent viral infection or other

promoting factors may therefore be predisposed to rapid progression of cervical

neoplasia due to their reduced immune function. It is not clear, however, whether the

decline in immune function seen as a part of

normal aging is comparable to that seen in

younger, iatrogenically immunosuppressed individuals.

The proportion of women who have had

hysterectomies increases with age. This factor should generally decrease the risk of cervical cancer, since the number of women who

have cervices, and therefore can get the disease, is reduced. However, prior to the early

1960s, many women had partial hysterectomies, leaving the cervix intact. In one

study, one-third of the elderly women with a

history of a hysterectomy had an intact cervix

on clinical exam (92). Between 4 and 8 percent of cervical cancers arise in these cervical

stumps ( 123,175). Also, women who have

had a hysterectomy because of cancer have a

high risk of subsequent development of

vaginal cancer (1 3). Today, the majority of

women with hysterectomies have their cervices removed. In the future, the reason for

the prior surgery will be the best indicator of

whether screening should be continued

(screening would likely be advised only if the

surgery was for malignant disease).

Cohort Factors --The incidence rate for

cervical cancer at any point in time for a

particular age group reflects not only changes

in risk with age but the background risk of

that cohort of women. Sexual practices,

smoking habits, hysterectomy rates, and

prevalence of HPV are different for each

cohort. The changes in these risk factors

make it difficult to predict accurately the risk

of future 65-year-olds based on rates among

the current cohort of 65-year-olds.

Researchers have noted higher rates of

cervical neoplasia in two cohorts of women,

those born between 1906 and 1921 (women

age 68 to 83 in 1989), and those born after

1931 (women under age 58) (62,105). Recently, rates of cervical neoplasia seem to be

increasing among young women as well
10 • Costs and Effectiveness of Cervical Cancer Screening

Box A--Human Papilloma Virus and Cervical Cancer

Human papilloma virus (HPV) was first proposed as a possible precursor of cancer in 1935

(121), but it did not receive widespread attention as a possible causative agent for cervical cancer until 1976 (95). Recently, with the use of technology permitting identification of subtypes

of HPV, data have emerged implicating two specific subtypes (HPV-16 and HPV-18) as

etiologic agents in cervical cancer. These viruses cause a distinctive concave lesion in cervical cells, known as “koilocytosis” (77).

Koilocytocis indicative of HPV is found in 1 to 3 percent of routine Pap smears (57), and

HPV-associated venereal warts (condylomas) have been noted to coexist in approximately 25 to

50 percent of neoplastic cervical lesions (l10,151). Recent studies have reported that more than

75 percent of cervical cancers contain evidence of HPV types 16 and 18, and a further 20 percent contain evidence of other types (94). Only 5 percent of squamous carcinomas of the cervix

have no detectable evidence of HPV. It is hypothesized that these cancers contain a type of

HPV that has not yet been identified or contain too low a concentration of the virus to be

detected by current technology.

Overall, preliminary reports suggest that women with HPV infections are up to 10 times

more likely to develop CIN than women without HPV infection (57). In addition, some researchers have suggested that some types of HPV infection may be causing a new type of cervical cancer that has a shorter progression time than cancers that occurred in the past

(38,106,126). If this is the case, shorter screening intervals and/or a test to screen for HPV

might need to be implemented. One HPV test for this purpose was recently approved by the

Food and Drug Administration (82).

There are few prospective studies of the natural history of HPV infection. Syrjaren et al.,

followed a cohort of 343 women with HPV infection for an average of 1 1/2 years (152). In a

subsample of these infections, the behavior of the cervical lesion was correlated with HPV type.

Progression was more likely with types 16 and 18 than with types 6 and 11 (153). Recently,

two studies have followed women with abnormal smears and HPV infection without treatment.

Virtually all of the lesions that progressed contained HPV type 16 0r 18(21,124).

Complicating this picture of HPV infection and cervical cancer is the detection of evidence

of HPV in as many as 11 percent of healthy women. Although HPV is believed to be a transforming virus, infection with the virus is not a sufficient condition for the development of cervical neoplasia. Possible co-factors include age, immune status, and repeated infection (74).

There are no studies of the prevalence or behavior of HPV in cervical lesions in the elderly

in the United States. A particularly important question is whether HPV behaves in a biologically similar manner in younger and older women. Factors such as the aging immune system, for

example, might make elderly women more susceptible than younger women to the effects of the

virus. Immunosuppression creates conditions favorable to maturation of HPV (131), and

patients whose immune systems have been deliberately suppressed (e.g., renal transplant

patients) are up to 14 times more likely than nonsuppressed patients to develop CIS (109,125).

With the increasing prevalence of HPV in the population, understanding the interaction between

this possible neoplastic promoter and various host factors, including aging and immune status,

will assume greater importance.
Costs and Effectiveness of Cervical Cancer Screening • 11

(157), presaging future cohorts of elderly

women at elevated risk. To the extent that

screening history influences risk, however,

future cohorts of elderly women (with high

rates of past screening) should be at lower

risk of developing cervical cancer than the

present cohort of women in this age group.

Natural History

Cervical cancer screening is predicated

on the assumption that the disease progresses

through several preclinical and early clinical

phases, and that treatment during these

phases reduces morbidity and mortality. The

effectiveness of screening, thus, crucially

depends on the natural history of the disease

and the extent to which assumptions about

the systematic progression of the disease are

true.

Cervical neoplasia most commonly arises

in an area of the cervix known as the transformation zone. In the standard model of

cervical cancer, the abnormal cells that arise

in this area are first confined to the surface

(epithelial) tissue (CIN and CIS) but eventually invade the body of the cervix. The cancer

then spreads to surrounding pelvic tissues

and, finally, to more distant parts of the

body.

Indirect evidence supports the link between CIN, CIS, and invasive cancer. Cells

from in situ and invasive tumors have similar

biological properties (58), and biopsy studies

have found CIS to both predate and coexist

with invasive lesions (49,53,56). Furthermore, the epidemiologic evidence strongly

supports the postulated disease progression;

the peak incidence of each of the disease

stages occurs at progressively older ages (22).

Thus, it is generally agreed that cervical

neoplasia passes through the states of CIN

and CIS before becoming invasive. There is

less agreement regarding:

1. what proportion of CIN and CIS develops into invasive cancer, and

2. how quickly the progression from CIN

to CIS to invasive cancer occurs, particularly in elderly women.

Four methods have been used to estimate

the probability and speed of progress of cervical neoplasia through its various states. The

first has been through direct observation of

patients with untreated nonmalignant disease

(a method now considered unethical unless

the subjects have been offered and have

refused treatment) (see app. D). In two

studies of small numbers of women with nonmalignant disease, most women eventually

developed invasive cancer. In up to 30 percent of women, however, the disease apparently regressed (e.g., Pap smears no longer

revealed abnormal cells) (71,107). Disease

regression was more likely in young women

and in women with lower grades of CIN. It

is unclear whether this apparent regression

represented false-positive cases or true

regress ion of disease. Additional uncertainties are introduced because observation

itself can alter the natural history of the disease. Diagnostic biopsy, which is necessary

to accurately evaluate the extent of a lesion,

may act as a curative procedure by excising

the tumor (1 12). Women with CIN who have

biopsies have higher regression and lower

progression rates than those who do not have

biopsies (100), and women who refuse biopsy

as well as treatment have a high rate of invasive disease (142).

A second method uses modal age-specific

incidence rates to estimate the duration of

different states of neoplasia. For each state

(e.g., CIS), the researchers determine the age

at which the most cases of that state occur

(the mode4

). The assumption underlying this

method is that the duration of a state is the

difference between the modal age for that

state and the modal age for the next state.

For example, if the modal age of CIS were 35

and the modal age for invasive cancer were

50, the average duration of CIS would be

estimated to be 15 years. This method may

overestimate the duration of CIS if symptomatic as well as asymptomatic cases of in4 The mode is the point in a frequency distribution

at which the most events occur.

19-754 0 - 90 - 2
12 • Costs and Effectiveness of Cervical Cancer Screening

vasive cancer are represented. This occurs

because cases discovered as a result of symptoms, on average, are discovered at a later

state than asymptomatic cases discovered

through screening, resulting in a higher

modal age for the apparent onset of invasive

cancer.

A third method uses differences between

incidence and prevalence rates to infer the

duration of a state, which is estimated by

dividing prevalence by incidence. In general,

the average duration of a disease (or disease

state) is a function of the prevalence of that

disease (or state) at the end of a time period

(e.g., the end of a year) and the incidence of

new cases during that time period (e.g., the

preceding year) (88). In a simplistic example,

if there are 10 new cases each year and a total of 100 cases always exists at the end of

each year, the average duration of the disease

is 10 years. (This result is derived from the

fact that if there are 10 new cases each year,

it will take 10 years to reach the equilibrium

of 100 cases, and at equilibrium, one case

must be lost (e.g., cured) for every new case.)

Somewhat more complicated formulas can be

used to infer the duration of a disease (or

disease state)at different ages.

The fourth method, used to estimate both

the duration of different states and the proportion of each state that progresses to the

next state, is modelling. Various researchers

have used techniques such as statistical

regression and simulation models to estimate

duration times and progression probabilities

(app. D). Coppleson and Brown, for example, used a Markov model and applied various

estimates of progression probabilities until

they succeeded in obtaining results that

mimicked actual prevalence and incidence

data. Based on the probability estimates and

other assumptions that yielded these results,

they concluded that the progression from CIN

to CIS to invasive cancer was probably age

dependent--i.e, that the probability of progression and the duration of each state

depended on the age of the woman with the

disease.

Table 4 summarizes estimates from the

literature of the likelihood that someone

diagnosed with CIN will progress to CIS and

to invasive cancer. Tables 5 and 6 summarize

estimates of the average duration of each

state of neoplasia. The studies and methods

on which these estimates are based are described in detail in appendix D. As a group,

the existing estimates from the literature support the following conclusions:

■ Most CIN (about two-thirds of grades 1

and 2) eventually progresses to CIN

grade 3/CIS.

■ The majority - -probably the grea t

majority--of CIS cases eventually progress to invasive cancer.

■ Some CIN regresses to normal. The

proportion may be a substantial minority, although it is likely that some

“regressions” are actually the result of an

initial false-positive test result (i.e., CIN

never actually existed).

• Some CIS lesions probably also regress.

However, CIS is less likely to regress

than CIN. Also, Disappears to be less

likely to regress in older than in younger

women.

■ There is little information on the average duration of CIN. More estimates

exist for CIS. This state is estimated in

various studies to last from 1 to 17

years, with about 10 years being rough

middle estimate. However, CIS appears

to be much shorter in elderly women,

probably lasting an average of 1 to 5

years. It is possible that the apparent

shorter duration is an artifact of lower

screening and detection rates of CIS in

elderly than in younger women (i.e., in

the elderly, CIS may, on average, be

detected at a later stage of disease).

Diagnosis and Treatment

Diagnosis

Three tools exist for detecting cervical

cancer. The first is the Pap smear, a sample

of cells from the cervix that is examined with
Costs and Effectiveness of Cervical Cancer Screening ■ 13

Table 4--Selected Prospective Studies of Progression/Regression

of Cervical Neoplasia

Basis for initia l Population Progression Regression

Source diagnosis of CIN studied probabilit y probabilit y

Barron and 3 smears 557 women aged 20 66% of CIN prog- 6% regressed in

Richart, 196 8

a

to 39 with CIN in ressed to CIS in 10 10 years

Virginia and New years; progression

York more likely in

higher-grade lesion

-------- . . . . . . . . . --------- . . . . . . . . . --------- --------- --------- --------- --------- --------- --------- ---

F O X, 196 7

b

1 smear 278 women attending 60% of CIN prog- 31% (13% dehospital-based ressed to CIS veloped CIN

clinics in Virgini a again )

(all under age 65)

-------- --------- . . . . . . . . . . . . . . . . . . . . . . . . . . . --------- --------- --------- --------- --------- --------- ---

Stern and Neely, Biopsy 130 women attending - - 38%/year for

1964 =

a clinic in Los CIS in women

Angeles, CA; about <45; 29%/year

half over age 45 in women>45

----- ------ ------ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- ------

Nasiell et al.,

s

Abnormal 894 Stockholm 30% of CIN grade 2 54% of CIN

1983 smears (CIN women; 197 age 45- progressed to CIS in grade 2

grade 2) for 72 average of 4.3 regressed in

one year years; progression average 6.5

time longer in women year s

over age 50 (6.5

years )

ABBREVIATIONS: CIN = cervical intraepithelial neoplasia; CIS = carcinoma in situ.

a

B.A. Barron and R.M. Richart, " A statistical Model of the Natural History of Cervical Carcin- Based On a

Prospective Study of 557 Cases," J. Nat. Cancer Inst. 41:1343-1353, 1968.

b

C.H. F O X, llBiologic Behavior of Dysplasia and Carcinoma In Situ,” Am. J. Obstet. Gmecol. 99:960-9748 1967.

C

E. Stern and P.M. Neely, llDysplasia of the Uterine Cervix: Incidence of Regression, Recurrence and Cancer,”

~Cancer 17:508-512, 1964 .

K. Nasiell, M. Nasiell, and V. Vaclavinkova, llBehavior Of Moderate Cervical Dysplasia During Long-Term

Follow-Up, ~ ~tet. G~eco(. 61(s):60Q-61ft, lgasSOURCE: Office of Technology Assessment, 1990.
14 ■ Costs and Effectiveness of Cervical Cancer Screening

Table 5--Duration of Cervical Neoplasia:

Selected Study Characteristics

Characteristics o f

study study type study populatio n

Canadian Task Force, 197 6

a Cross-sectiona l Women screened in British Columbia, Canad a

. . . . . . . . . . . . . . . . . . . . . . . -------- -------- -------- -------- -------- -------- -------- -------- -------

Barren and Richart, 196 8

b

Longitudina l Women at Medical College of Virginia ,

Columbia Presbyterian Hospital (New York) ,

and Barbados, West Indies; no elderly wome n

. . . . . . . . . . . . . . . . . . . . . . . . . . . ------- ------- ------- ------- ------- ------- ------- ------- ------- ----

Coppleson and Brown, 197 5

C Cross-sectiona l Used data from :

1) study of women attendin g

Chicago clinics (University of Chicag o

Planned Parenthood), an d

2) national data o n

U.S. women from the Third Nationa l

Cancer Surve y

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- ------- ------ . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Kashgarian and Dunn, 197 0

d

Cross-sectiona l Over 110,000 women in Memphis, TN ;

over 2% age 65 and ove r

------ ------- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- ------- ------- ------- ------- --

Dunn, 196 6

e

Cross-sectiona l White women in Memphis, TN ;

a few age 65 and ove r

------ ------- --..... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Fidler et al., 196 8

f

Cross-sectiona l Uomen screened in British Columbia, Canad a

including over 12% of elderly wome n

. . . . . . . . . . . . . . . . . . . . . . . . . . . ------- ------- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Petersen, 195 6

g

Longitudina l 212 Danish women referred to the Copenhag e

Radium Center for gynecologic care fro m

1930 to 1950; a few over age 4 0

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Barron, Cahill , Cross-sectiona l Data from studies of women in Barbados an d

and Richart, 197 8

h

British Columbia, Canada (see Fidler et al .

1968, and Barron and Richart, 1968 )

Canadian Medical Association Journal IICervical Cancer screening programs,” Can. Med. , ASSO C. J. 114: 1

Inxx I07A

‘B.A.”Barren and R.M. Richart 11A Statistical Model of the Natural History of Cervical Carcinoma Base , d

Prospective Study of 557 Cases ,

n Nat. Cancer Inst. 41:1343-1353, 1968 J . .

C

L.U. Coppleson and B.U. Brown Ilobservation , on a Model of the Biology of Carcinoma of the Cervix: A

dFit Between Observation and Theory,~ Am. J. Obstet. Gynecol. 122:127-136, 1975 .

M. Kashgarian and J.E. Dunn , IiThe Duration of Jntraepithelia[ and Prt2C[iniCal Squamous cell CarcinOmS

the Uterine Cervix ,

n Am. J. Epidemiol. 92:211-222, 1970 .

‘J.E. Dunn ,

llThe presymptmtic Diagnosis of Cancer Uith Special Reference to CerViCal Cancer,” prO

fsoc. Med. 59:1198-1204, 1966 .

H.K. Fidler, D.A. Boyes, and A.J. IICervical Horth, Cancer Detection in British Col@ia,1° J. Obstet.

Gynaecol. Brit. Cwlth. 75:392-404, 1968 .

‘O. Petersen ‘Spontaneous Course of Cervical Precancerous Conditions,” Am. J. , Obstet. Gynecol. 72 :

1071, 1956 .

‘B.A. Barron, M.C. Cahill, and R.M. Richart, 11A Statistical Model of the Natural History Of Cervical

Neoplastic DiseaseThe Duration of Carcinoma In : Situ,” Gynecol. Oncol. 6:196-205, 1978 .

SOURCE: Office of Technology Assessment, 1990 .
Costs and Effectiveness of Cervical Cancer Screening • 15

Table 6--Duration of Cervical Neoplasia: Findings

3 . 7

5 . 7

17

5

Duration ( Years )

Age group/study CIN CIS EiCC Basis for estimat e

hAll ages:

Petersen, 195 6

a

average 3.7 Direct observation

(range: 0.4-8.8 )

Dunn, 1966 b

10. 4 4 . 1 Prevalence/incidence=duration c

a

Canadian Task Force, < -------25-35, all states-------- > Modal age

1968 9.7-13. 4 3 . 4 Mean age

Fidler et al., 196 8

e

6-9. 5 Prevalence/incidence=duration c

12 Mean age

Kashgarian and Dunn, 1970f

white women 10. 7 Prevalence/incidence=duration c

black women 8 . 5 Prevalence/incidence=duration c

Barron et al., 197 8

g

10

(upper bound)

Prevalence/incidence=duration c

3

(lower bound)

Young women:

Kashgarian and Dunn, 1970f

age under 25 10 Prevalence/incidence=duration c

age 25-35 16 Prevalence/incidence=duration c

age 40-50 5 Prevalence/incidence=duration c

Barron and Richart, 1969’

age 20-39 Markov model (median age)

Markov model (mean age)

Coppleson and Brown, 1975i

under age 50 Markov model

Older women:

Coppleson and Brown, 1975i

age 50 and over 4 Markov model

Kashgarian and Dunn, 1970f

over age 65 1 Prevalence/incidence=duration c

ABBREVIATIONS: CIN = cervical intraepithelial neoplasia; CIS = carcinoma in situ; and EICC = early invasive — —

cervical cancer.

a

O. Petersen, "Spontaneous Course of cervical precancerous conditions,” Am. J. Obstet. Gynecol. 72:1063-1071,

1956.

b

J.E.Dunn, "The Presymptomatic Diagnosis of Cancer With Special Reference to Cervical Cancer,” proc. R. Soc.

~ 59:1198-1204, 1966 .

c

Dunn (1966) estimated the duration of a given state of neoplasia by dividing the sun of all age-specific

prevalence for that state by the sum of all age-specific incidence of the state. Kashgarian and Dunn

(1970) estimated duration by first graphing the incidence of each state (CIS, preclinical invasive, clinical

invasive), with age along the bottom axis of the graph. They then estimated the area under the graph between given ages for CIS. Next, they calculated the age at which the graph of the incidence of preclinical

invasive cancer had an area under it equivalent to the area under the defined CIN age interval. The duration of CIS was then presumed to be the difference between this age and the upper limit of the specified CIS

~a9e r~nge. This latter method yields results that are equivalent to those derived from the first method.

Canadian Medical Association Journal, IICervica[ Cancer Screening programs: Sumnary of the 1982 Canadian Task

Force Report, M Can . Med. ASSOC. J. 127:581-589, 1982.

‘H.K. Fidler, D.A. Boyes, and A.J. Uorth, IICervica[ Cancer Detection in British Cottiia,tl J. ObStet.

fGynaecol. Brit. Cwlth. 75:392-404, 1968 .

M. Kashgarian, and J.E. Dunn, ~The Duration of Intraepithelial and Preclinical SqUamOUS Cell CarCinOmS of th e

Uterine Cervix ,

m Am. J. Epidemiol. 92:211-222, 1970 .

gB.Ao BarrOn, M.C. Cahill, and R.M. Richart, UA statistical Model of the Natural History Of Cervical

~Neoplastic Disease: The Duration of Carcinoma In Situ,” Gynecol. Oncol. 6:196-205, 1978.

R.M. Richart, and B.A. Barron, 11A Fo[low-up St@ of Patients Uith Cervical Dysplasia,” Am. J. Obstet.

iGynecol. 105:386-393, 1969 .

L.U. Coppleson, and B.W. Brown , ItObservation on a Model of the Biology of Carcinoma of the Cervix: A Poor Fit

Between Observation and Theory,” Am. J. Obstet. Gynecol. 122:127-136, 1975 .

SOURCE: Office of Technology Assessment, 1990.
16 ■ Costs and Effectiveness of Cervical Cancer Screening

a microscope for abnormalities. The Pap

smear is most commonly used for screening

and as supportive information for a diagnosis.

A second tool is direct examination of the

cervix through a colposcope, a magnifying

instrument that allows the examiner to see the

surface of the cervix in detail. Colposcopy is

most often used after a Pap smear has been

judged positive for abnormal cells. In addition to verifying the results of a positive Pap

smear, C OlPOSCOPY can identify the appropriate site from which a biopsy should be

taken. The third tool, generally used (together with COlPOSCOPY) for confirmatory diagnosis after one of the other methods has disclosed a possible abnormality, is biopsy --a

tissue sample removed from the cervix and

examined for evidence of cancer.

It can be difficult for the examiner to

gain access to and sample the transformation

zone (where neoplasia most commonly arises)

in elderly women, for three reasons:

■ the vagina narrows with age;

■ the cervix undergoes atrophic changes

(wasting and diminution of tissue); and

■ the transformation zone moves into the

inner cervix after menopause (60).

Thus, Pap smears are often more difficult to

take and to assess in elderly than in younger

women, probably leading to a higher rate of

false-negative results and lower test sensitivity. Unfortunately, there are no studies

that shed light on the magnitude of this

potential problem.

In addition to a probable higher rate of

false negatives, smears from elderly women

may also have a higher rate of false-positive

results (and lower test specificity) than smears

from younger women. An initial abnormal

smear in an elderly woman may simply

reflect a lack of adequate estrogen or an infection. Thus, some physicians suggest that

elderly women with an initial smear whose

results indicate a mild abnormality undergo

treatment with estrogen or anti-inflammatory

agents, to eliminate certain potential causes of

noncancerous abnormalities, before further

diagnostic testing is employed (68,143,168).

Before being treated, a woman with a

smear indicating cervical neoplasia undergoes

a thorough evaluation to determine the extent

of the lesion (i. e., the area of physical

manifestation of disease) and to assess the

possibility of invasive cancer. For most early

lesions, this may be accomplished by removing a small tissue sample (biopsy) from the

suspect area identified by colposcopy. This

procedure can usually be done on outpatients

without general anesthesia (130). However,

in up to one-third of elderly women, the

transformation zone is inaccessible and the

appropriate area is consequently very difficult

to visualize (18,72,120,135). In these cases a

cone biopsy --removal of a conical segment

from the cervix -- must be taken (120,143,

177). Women with diagnosed invasive disease

subsequently undergo in-depth evaluation to

determine the extent to which the cancer has

spread. This “staging workup” can also disclose coexisting diseases or problems that may

influence treatment decisions (102).

Treatment and Followup

The course of treatment and followup

medical care provided to women with cervical

neoplasia varies depending on the physician

providing the care and considerable controversy exists regarding which protocol is

most appropriate. Nonetheless, there is little

disagreement regarding the goal of treatment:

to remove all abnormal tissue as early as possible in order to prevent the development (or

spread) of invasive cancer. Differences in

treatment practices are often due to differences in judgment regarding the trade-off

between sufficiently aggressive treatment to

“cure” the patient-- i.e., eradicate the entire

lesion- - and the desire not to inflict unnecessarily invasive treatments on the patient.

Depending on the extent of the lesion,

treatment for noninvasive cervical neoplasia

may include local therapy (e. g., freezing,

cautery, or laser treatment), cone biopsy, or

hysterectomy. In general, lesions that cannot

be fully visualized require more aggressive
Costs and Effectiveness of Cervical Cancer Screening • 17

treatment to ensure that the entire lesion is

removed. Most CIN is fully removed after a

single treatment with local therapy or cone

biopsy, with a small proportion requiring further treatment (45, 102). For CIS, however, a

hysterectomy may be performed if visualization of the full extent of the lesion is difficult. After re-treatment of patients in

whom the initial treatment did not fully

remove the lesion, the overall treatment failure rate (i. e., the proportion of patients in

whom some CIN remains after treatment) is

about 3 percent (12). Fewer than 1 percent

of treated patients develop invasive cancer

within the subsequent 5 years (33).

Treatment of invasive cervical cancer is

guided by the stage of disease. Generally,

stage I disease, with lesions confined to the

cervix, is treated with a radical hysterectomy

(removal of the uterus and surrounding tissue). For elderly women whose other medical

conditions make them poor surgical candidates, radiation therapy would be the likely

treatment of choice. Although surgery is

often considered preferable to radiation

therapy, the two treatments yield similar outcomes, with 5-year survival rates of 85 to 88

percent (33,45,160).

Women with more advanced disease

(stages II, III, or IV) are generally treated

with radiotherapy. If the patient’s condition

permits, pelvic exenteration--the removal of

the pelvic organs--can be considered, but this

drastic procedure is rarely performed on

elderly women (45,130). Five-year survival

rates are 51 percent for women with regional

cancer and 14 percent for women with cancer

that has spread to distant sites (157).

Cervical neoplasia recurs in less than 5

percent of all women with CIN (grades 1 and

2), approximately 2 to 10 percent of women

with CIS, 10 to 20 percent of women with

early invasive cancer, and 30 to 100 percent

of women with late invasive cancer. Among

women with late cancer, those at the most

advanced stage (stage IV) have the greatest

likelihood of recurrence (130). Most recurrences are within 3 years (130).

Medical textbooks recommend that all

women with cervical neoplasia be followed

for life (102). The type of followup depends

on the state of neoplasia (and, of course, the

practice style and preferences of the physician). Women with former low-grade CIN

should receive regular Pap tests. Women with

CIS should have frequent Pap tests and/or

Colposcopy. Women with invasive disease are

recommended to have regular checkups,

which may include x-ray and other diagnostic

procedures as well as physical exams (130).

SCREENING: THE PAP SMEAR

Pap Smear Accuracy

The Pap smear is the universal screening

test for cervical cancer in asymptomatic

women. Although other tests have been proposed for this purpose, none has so far

proven to be as simple and as useful as the

Pap test (box B).

A Pap smear consists of a sample of

cells, scraped or aspirated from the cervix,

affixed to a glass slide. 5 The sample is

derived from the thin layer of cells on the

surface of the cervix that is continually being

exfoliated, or shed, in the normal day-to-day

process of cellular growth and aging. The

sample includes cells from the outer surface

of the cervix, the inner cervix, and the transformation zone between. The slides are sent

to a laboratory, where they are examined and

the results communicated back to the

physician. The physician then decides what

course of followup is necessary, based on the

abnormalities reported.

Components of Accuracy

Accuracy of the Pap smear has two basic

components: the sampling component when

the smear is taken, and the evaluation comS See the recent review by Koss (76) for a detailed

discussion of ideal methods of sampling and issues

in the evaluation of Pap smears.
18 ■ Costs and Effectiveness of Cervical Cancer Screening

Box B--Other Potential Screening Technologies

Both colposcopy and cervicography (a method combining colposcopy with a permanent photographic record) have been suggested as methods of screening for cervical neoplasia. In general, screening by these technologies has not been considered practical due to the cost of performing the procedure and the additional skill required of the examiner. No published data exist on

the use of these technologies in screening elderly women.

A recent study of colposcopy in younger age groups found that this technology, when used

in conjunction with a smear, has greater accuracy in identifying small CIN lesions than the Pap

smear alone (54), but whether the smaller lesions are clinically important is not known. The

cervigram has been noted to be more sensitive than the Pap smear (17,141,154), but much less

specific (154). The cervigram’s high rate of false positive results and associated costs have led

to some skepticism regarding its usefulness as a screening procedure (139).

A test to screen for HPV has recently been approved by the Food and Drug Administration

for marketing (82). It is possible that simultaneous Pap smear and HPV typing will detect cervical neoplasia more accurately than the Pap smear alone (box A) (103,1 13), but this has not yet

been shown. No studies of the accuracy and use of the HPV test in elderly women have been

published.

ponent when the smear is read. Each cornponent includes both avoidable errors (e.g.,

due to an error in reading the slide) and unavoidable errors (e.g., due to the biological

characteristics of a lesion) that prevent Pap

smear accuracy from being 100 percent even

under the best circumstances.

Sampling errors, which generally lead to

false-negative results, occur when no

neoplastic cells are included on the smear

even though a woman actually has cervical

cancer. Some of these errors are introduced

by the examiner and can be minimized by

careful sampling. However, if a lesion is

small or inaccessible, or if too few abnormal

cells exfoliate, it is entirely possible that an

adequately taken smear will still not detect

potentially cancerous lesions.

Sampling errors that are due to biological

characteristics of the lesion and its accessibility are particularly likely in elderly

women. A failure of exfoliation of abnormal

cells is more likely in post-menopausal than

in younger women (64), as a result of anatomic changes associated with aging (e.g., the

movement of the transformation zone up into

the cervix). Also, narrowing of the vagina

and entry to the cervix may make adequate

sampling more difficult. All of these biological factors suggest higher false-negative rates

in older than in younger women.6

Evaluation errors lead to false-negative

results (generally avoidable ones) when cancerous cells on a smear are missed by the

cytotechnologists. Evaluation errors lead to

false-positive results when normal cells are

identified as abnormal or when abnormalities

that are unrelated to cervical cancer are

identified as possible neoplasia. Some falsepositive evaluation errors are also avoidable

(e.g., mislabeling or inadequate reporting of a

slide), but many are not; they arise because

infections, estrogen deficiencies, and many

other causes can result in abnormal smears

that require comprehensive followup to rule

out cervical neoplasia.

6 Despite these problems, the International Agenc y

for Research on Cancer has noted that the sen -

sitivity of the Pap test is not appreciably lowe r

in older women (age 50 to 64) than in younger women

(66) . This group did not draw any conclusion regarding test sensitivity in women age 65 and over.
Costs and Effectiveness of Cervical Cancer Screening • 19

In some cases, efforts to minimize

evaluation errors may increase sampling errors. For example, lubricating jelly is

generally not recommended for use when a

Pap smear is taken because it is believed to

diminish cellular detail, making accurate

evaluation of the smear difficult. In elderly

women, however, the use of lubrication can

increase patient comfort and thus enable the

examiner to obtain a more complete smear.

One recent study found that small amounts of

lubrication could be used without sacrificing

the adequacy of smears (92).

Overall Pap Smear Accuracy

A Pap smear is not simply reported by

the laboratory as “positive” or “negative”;

rather, there are a number of categories with

different implications for followup (e.g.,

“atypia, n ‘suspicious for malignancy”). In

general, for the purposes of cervical cancer

and this paper, a “positive” slide is any slide

diagnosed as atypia or worse, except that

atypical smears that are judged to be attributable to a cause other than neoplasia

(e.g., infection) would be considered negative.

The term “positive” is not consistently

defined, and most studies give little detail

regarding the exact definition that is used.

The overall accuracy of the Pap smear is

the sum of both the sampling and evaluation

components. It is quantified by estimating

the sensitivity and specificity rates for

smears. (Figure 1 displays the calculation of

sensitivity and specificity and the relationship

of these measures to false-positive and falsenegative rates). Calculating these rates is not

always simple. For example, determining the

true sensitivity requires retesting all women

who originally tested negative, while determining the true specificity requires knowing

the number of women who are truly free of

the disease.

Figure l--Calculation of Sensitivity and

Specificity

I

Diseas e

Tes t

result : ~::::::: -

a+c b+d

I

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Sensitivity = a Specificity = d

G b+d

False-positive rate = 1-sensitivity = c

a + c

I

False-negative rate = 1-specificity = b

b+d

SOURCE : Off ice of Technology Assessment, 1990.

A substantial number of published studies exist that attempt to measure the accuracy

of the Pap smear (table 7). A review of these

studies requires three comments. First, the

majority of the studies were designed to

ensure very careful smear evaluation. Consequently, the rates they report represent accuracy under ideal circumstances, rather than

under normal conditions of varying laboratory

quality. Second, few elderly women are

represented in the studies; because sampling

is more difficult in elderly than in younger

women, and because estrogen deficiencies and

other abnormalities may confound the interpretation of the smear, rates for older women

are probably lower than those reported here.

Third, study designs and environments vary

considerably. Some of the studies were conducted outside the United States, and it is

quite possible that the differences in the

other nations’ health care systems (e.g., in

how services are delivered, how laboratories

are run, who evaluates smears and how the

evaluators are trained) would make the results

of those studies inapplicable to the United

States.
Table 7--Studies Assessing the Accuracy of the Pap Smear

Country Elderly

study (region) Population Study design Sensitivity Specificity a

population Comments

Richart and United States Patients receiving After initial screening 95% NA

Barron, 1969b

screening from two 120 slides were

hospitals relabeled and examined

again

----- ------ ------ -..-.. . . . . . . ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ --..-

Coppleson and United States Women in two Mathematical model using MDYS = 60.1% NA

Brown, 1974C

screening programs empirical incidence and CIS = 55.1-80%

in the United prevalence data to ICC = 76%

States estimate a falsenegative rate

. . . . . ------ ------ ------ . . . . . . ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ . . . . . . --- ------ .----- . . .

None

. . . . . ------ ------ -..

NA

Since results were never

verified by colposcopy or

biopsy false-negative rate

only reflects evaluation error

----- ------ ------ ------ . . . . . . ------ ---

Rates not derived directly

from successive smears on. individual women

. . . . . . . . . . . ------ . . . . . . . . . . . . . . . . . . ------ ------ ------ ---.--

Davis, Hind- United States 87 women referred Comparison of smears and 79% NA NA Group is not representative

man, PapLanus (Arizona) to hospital biopsies

et al., 1981d dysplasia clinic

since all participants were

referred because of cytologic

abnormalities; false negative

errors were categorized by

type of error; of 19, 13 were

either purely sampling (10) or

combined sampling and evaluation (3); 6 were evaluation

errors

----- ------ ------ ------ ------ ------ ------ . . . . . . ------ ------ ------ ------ ------ ------ ------ ------ . . . . . . ------ ------ ------ . . . . . . ------ ------ ------ ------ ------ -------- ------ ----

Dunn and United States Women who deveL- Retrospective review of 81.5% NA NA False-negative rate only an

Schweitzer, (California) oped cervical can- 53 negative slides (for

1981e

cer

estimate of evaluation errors

27 women who Later developed cervical cancer); also reviewed 50

control slides (both

negative and positives);

original and review interpretations were compared

----- ------ . . . . .. ------ ------ . . . . . . ------ ------ ------ ------ ------ ------ ------ ------ --.--- ------ ------ ------ ------ -.---- ------ ------ ------ ------ ------- ------ ------ ------ -----

Gay, Donald- United States 339 tissue proven Retrospective review of Overall = 80% NA NA False-negative rate includes

son, and cases of cervical negative slides of women CIS=83 % both evaluation and sampling

Goellner, malignancies be- who developed malignancy ICC = 77%

1985f

components; rate also includes

tween January 1980 within a year of smear detection of lymphoid and

and December 1983 adenocarcinoma

------ ------- ------- ------- ------- ------- ------- ------- ------- ------- ------- ------- ------- ---.--- ------- --.---- ---.--- ------- ------- ------. ----.-- -------- ------- ------- -----
Costs and Effectiveness of Cervical Cancer Screening ■ 21

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Table 7--Studies Assessing the Accuracy of the Pap Smear (continued)

Country Elderly

study (region) Population Study design sensitivity a

Specificity apopulation comments

MacCormac, Australia Women screened be- Comparison of biopsies Overall = 84.6% 94.6% NA

Lew, Kim et

Smears were not reexamined,

tween 1959 and with n-ret recent smear DYS = 77.9%

al., 1988[

original diagnosis presumed

1982 result CIS = 88.2% correct; no indication of time

ICC = 82.6% intervals between smear and

biopsy; sensitivity was higher

if calculated on the basis of

the mast abnormal smear instead of the most recent

. . . . . ..--.. ------ ------ . . . . . . ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------- ------ ------ -----. ------ . . . . . . ------ ------ ------ ---.-

Giles, Hudson, Great Britain 200 asymptomatic Comparison of colposcopy Overall = 68.2% 99%

Crow et al.,

2.5% of None of the elderly women had

women in a general and cytology done during CIN1 = 100% study popu1988W

abnormal Pap smears

practice the same visit CIN2 ❑ 40% lation >65

CIN3/CIS = 69% years old

ABBREVIATIONS: CIN = cervical intraepithelial neoplasia (includes grades 1,2,3); CIS = carcinoma in situ; DYS = dysplasia (corresponds roughly to CIN);

ICC = invasive cervical cancer; MDYS = mild dysplasia (corresponds roughly to CIN grade 1); NA = not available.

a

Sensitivity is related to the false-negative rate; specificity is related to the false positive rate. See figure 1 for definitions. The falsenegative rate has two components: errors resulting from the probability that the sample did not collect dysplastic cells present on the cervix

(sampling error) and errors resulting from the cytologists evacuation of the slide (evacuation error). Not all studies estimated both ccwponents

(see text).

h.M. Richart and B.A. Barron, IIA Fo~~ow.up st~y of patients With cervical Dysp~asia,ll Am. J. Obstet. GYneco~. 105:386-393, 1969.

cL.u. Coppleson and B. Brown, llEstimati~n of the Screening Error Rate From the Observed Detection Rates in Repeated CeIWiCa[ cytOIOgy,ll Am. J. Obstet. Gyneco~. 119(7):953-958, 1974.

‘F.R. Davis, U.M. tiindnan, S.If. Pap[anus et al., Mva[ue of Du~[icate Smars in Cervica[ cyto~ogy,ll Acta. Ctyol. 25(5):533-538, 1981.

eJ.E. Dunn and V. Schweitzer, I!The Relationship of cervical Cancer ad Mortality in Alameda County, California, 1960-1974,!! Am. J. Obstet. Gynecol.

139(8):868-876, 1981.

‘J.D. Gay, L.D. Dona~dson, and J.R. Goe(lner, llFa~se-Negative Results in Cervica[ cytologic st~ies,ll Acta. Cyto[. 29:1043-1046, 1985 .

gD.A. Boyes, B. Morrison, E.G. Knox et al., IIA Cohort of cervical cancer Screening in British col~ia,ll Clin. Invest. )44. 5:1-29, 1982.

h~.A. Husain, E.B. Butler, D.M. Evans et al., llQua[ity control in Cervical CYt0109Y, ,, J. Clin. patho[. 27(12):935-944, 1974-

iE. Rylander, I!Negative smears in Women Developing 1tWaSiVC! Cervical Cancer,” Acta. Obstet. Gynecol. Scand. 56(2):115-118, 1977.

jA. Berget, J. Olsen, and P. Poll, ttsensitjvjty ad S%cificity of screening by Cervico-vaginal Cytology,” Dan. Med. Bul~. 24(lf):26-291 1977.

‘J.O. Beilby, R. Bourne, J. Guillebaud et al., ltpajr~ Cervical s~ars: A Meth~ of Reducing the Fa[se-Negative Rate in popl#lation Screeningrll &bstet. Gyneco~. 60(1):46-48, 1982.

IL. MacCormac, U. Lew, G. King et al., I!Gynecological Cytology screening in South Austraiia: A 23-Year Experience,” Med. J. Aust. 149(10):530-536,

1988.

mJ.A. Giles, n Er. Med. J. Z96:1OW-IIOZ, 19~. E. Hudson, J. Crow et al., llco[~scopic Assessment of the Accuracy of Cervical Cytolo9y Screenin9, .

SOURCE: Office of Technology Assessment, 1990.
Costs and Effectiveness of Cervical Cancer Screening • 23

Sensitivity -- Most sensitivity rates reported in the literature are between 56 and 95

percent (i.e., false-negative rates of 5 to 44

percent), with a few studies reporting lower

rates (table 7). In some cases, the rates

reflect only the evaluation component of accuracy. For instance, Barren and Richart

calculated the false-negative rate based on the

accuracy of one smear reading compared to

the result when the same slide is read by different individuals (114). The calculated

sensitivity rate in this case (95 percent) is a

maximum one, since it does not take into account the probability that the slide sample

might not contain precancerous cells that actually are present on the cervix.

Other studies attempt to account for both

evaluation and sampling components. These

studies compare the diagnosis based on a Pap

smear with the diagnosis based on another

procedure (a second Pap smear, colposcopy,

or biopsy). The studies comparing two

smears assume that if a woman actually has

cervical cancer, one of the two smears will be

positive. For studies comparing a single

smear with colposcopy or biopsy, it is assumed that “true positive” is defined by a

positive result on the second procedure.

In general, the Pap smear sensitivity rates

determined by these studies range from about

69 to 85 percent (false-negative rates of 15 to

31 percent) (11,36,54,64,85), although there

are a few studies where Pap smear sensitivity

has been substantially lower. Rylander, for

example, found sensitivity to be 37.5 percent

(122). In this study, the incorrectly diagnosed smears could be subcategorized into

those obtained at a mass screening (with a

sensitivity rate of 30 percent) or those done

by private practitioners (with a 50 percent

sensitivity rate). In a study of 50 postmenopausal women referred for hormone

therapy, Roberts and colleagues (116) found a

sensitivity rate of zero. Eleven of the 50

women in this study had abnormal colposcopic exams, including 4 cases diagnosed as

CIN; all of them had had normal Pap smears.

It is unknown what effect the need for

hormone therapy might have on the accuracy

of the test, so this study’s results are not easily generalizable. However, they do suggest

that the Pap test may have a low sensitivity

in this subpopulation of elderly women.

Finally, some studies attempt to estimate

sensitivity rates by reviewing the negative

slides of women who were later diagnosed

with cervical cancer. Dunn and Schweitzer,

following this procedure, found a sensitivity

rate of 91.5 percent (41). These researchers

reviewed slides only to see if they were improperly diagnosed, so this rate does not

reflect sampling errors. One study from

Denmark took this method a step further by

combining the observed evaluation errors

with an estimated sampling error, to come up

with an overall sensitivity of 93.4 percent

(14). This rate is quite high and probably

represents the minimum error that can be obtained under optimal conditions.

Specificity --The few studies that calculate the specificity of the Pap smear place the

rate within a range of 95 to 99 percent for

nonelderly women (20). The specificity of

the test in elderly women is potentially lower,

since the normal atrophic changes occurring

in post-menopausal women can result in vulnerability to inflammation and injury,

responses that can mimic the cellular changes

characteristic of CIN (50,78,92).

A study by Weintraub and colleagues

demonstrated the variety of abnormalities that

may complicate the interpretation of a Pap

smear in elderly women (172). In this study,

127 elderly women were given cytologic and

physical examinations. Nineteen of the Pap

smears (15 percent) were positive for an abnormality requiring some sort of followup,

and 16 of the patients remained in the study

for followup. Of these, 7 were followed up

for possible cervical neoplasia; 1 of the 7 was

subsequently diagnosed as having invasive

cervical cancer, and a second had persisting

atypia at the time the study was concluded.

The remaining 9 patients were followed up

because the Pap smear suggested other abnormalities; followup resulted in a significant

diagnosis in one of these patients.
24 ■ Costs and Effectiveness of Cervical Cancer Screening

Communication and Followup Errors

Although not strictly a component of the

accuracy of the Pap smear itself, communication and followup errors can complicate appropriate patient followup after an abnormal

(or normal) smear. They also result in lower

real-world rates of sensitivity and specificity

than the rates reported from research studies.

Communication errors are compounded

by variations in reporting of results. One

study of Pap smear evaluation at eight Baltimore, Maryland laboratories found that they

varied substantially in the nomenclature used

to report results back to physicians (127).

For example, one laboratory used “atypia” to

mean “dysplasia,” while at another, “atypia”

implied that the smear specimen was neither

normal nor dysplasia. Laboratories in this

study also varied in the extent to which the

laboratory pathologist included followup

recommendations to the clinician (one

laboratory always provided a recommendation

for followup for all abnormal smears, while

another never did).

Most communication and followup errors

are theoretically avoidable. A recent workshop convened by the National Cancer Institute published its recommendations on how

to minimize such errors (101). The recommendations proposed a new classification system for the reporting of Pap smear results,

under which each report from the laboratory

to the physician would include:

■

9

■

a statement of the adequacy of the

smear specimen (for unsatisfactory

slides, the cytopathologist would recommend that the physician take a repeat

smear);

a general categorization of the smear to

indicate whether any abnormalities exist

(i.e., whether the smear appears to be

within normal limits); and

a descriptive diagnosis for slides with

abnormalities, such as “infection- -

cellular changes associated with herpesvirus simplex,” or “high-grade squamous

intraepithelial lesion” (i.e., CIN grade 2

or 3).

A major purpose of this classification

system is to ensure that inadequate slides are

described as such and returned to the sampler

(reducing false-negative errors due to poor

samples). In the case of adequate slides, the

purpose is to ensure that the information

conveyed to the physician leads to appropriate followup decisions. For example, a

descriptive diagnosis of “infection--cellular

changes associated with herpesvirus simplex”

would indicate that the abnormality detected

is not likely to be cervical neoplasia and that

followup for herpes probably will be the appropriate course of action.

Effectiveness of Screening

The effectiveness of Pap smear screening

in preventing cancer mortality and morbidity

has never been tested directly in a prospective, controlled study. Instead, evidence for

screening effectiveness is based on two types

of studies:

1.

2.

Trend studies-- analyses of cancer incidence and mortality in a population

before and after the institution of Pap

smear screening. Trend evidence is

more convincing if it can be linked

with a “dose-response” effect- -i.e., if

the incidence of cancer drops more

sharply as the intensity of screening increases.

Case-control studies--studies in which

cases (women who developed cervical

cancer) are compared with controls (a

sample of women from the general

population) with respect to their utilization of screening, to see if screening

utilization is associated with a lower

risk of developing cancer.

As with the studies of Pap smear accuracy, a discussion of these studies as they

relate to elderly women requires some important caveats. Elderly women make up a relatively small proportion of the populations in

most of the studies. Consequently, the conclusions that can be drawn from these studies

regarding the effectiveness of Pap smear
Costs and Effectiveness of Cervical Cancer Screening • 25

screening are less clearly applicable to older

than to younger women. (This issue is addressed at the end of the discussion.) Both

types of studies are subject to important

forms of bias that can artificially inflate or

deflate the apparent effectiveness of the

screening program, particularly when variables other than incidence and mortality rates

are used as endpoints (box C). In addition,

each study type has its own characteristics

that confound simple evaluations. The

relevant studies and their implications are

discussed below.

Trend Studies

Pre- and Post-screening Trends--In Virtually every study reported, the incidence of

invasive cervical cancer and the mortality

from the disease declined after the introduction of Pap smear screening. Several U.S.

studies have reported such trends. The

studies have focused on nonelderly populations, so the results are not necessarily directly applicable to the elderly.

■ In Toledo, Ohio, average annual incidence rates of invasive cancer declined

Box C--Types of Bias in the Evaluation of Screening Programs

Many screening services are sufficiently integrated into normal medical practice that it is

not considered ethical to perform a prospective, randomized controlled trial to assess their effectiveness. Consequently, the assessment of effectiveness is based on less rigorous experimental

designs and historical observations. The use of such techniques introduces the possibility of bias

in interpreting the results. Three important types of bias that frequently confound the interpretation of Pap smear screening programs are lead-time bias, length bias, and selection bias.

These types of bias are most severe when the outcome measure is survival rates or survival time

after diagnosis; mortality rates are the least affected by these types of bias.

Lead-time bias makes a screening program appear effective because it increases the time

between diagnosis of the disease and death from disease. Individuals whose disease is diagnosed

as a result of screening are identified earlier in the course of the disease than those whose disease is diagnosed as a result of symptoms. Thus, the screened group will have a longer survival

after diagnosis than the unscreened group regardless of the actual effectiveness of the screening

program (and resultant treatment) in preventing disease, simply because their disease is

identified earlier.

Length bias also tends to make a screening program appear more effective than it is. It occurs because slow-growing tumors are more likely to be “picked up” over time in a screening

program than are fast-growing tumors, which may progress quickly between screening encounters. Consequently, those individuals with disease identified as a result of screening are

more likely to have slow-growing tumors than individuals identified as a result of symptoms.

Since those with slow-growing tumors will have better prognoses and longer survival times, the

overall effect is to enhance the apparent effectiveness of the screening program.

Selection bias often causes the effectiveness of a screening program to be overstated, although it can potentially cause it to be understated as well. Selection bias results from the fact

that people who choose to be screened often differ from those who avoid screening. The factors associated with this self-selection to be screened are themselves associated with the risk of

disease and can confound interpretation of the program results. If middle-class, low-risk

women are more likely to participate in a cervical cancer screening program than poor, highrisk women, for example, the incidence of cervical cancer in the screened group will be correspondingly lower, regardless of whether screening itself contributes to disease prevention.
26 ■ Costs and Effectiveness of Cervical Cancer Screening

by 66 percent over a 16-year period

after screening was introduced, and this

decline was accompanied by a 61 percent reduction in mortality rates (70).

In Louisville, Kentucky, incidence rates

8 years after screening was introduced

were 23 percent lower than in the prescreening period .

Dickinson et al., noted declines in incidence and mortality during the period

of screening in Minnesota, compared to

a pre-screening period. The decline in

mortality paralleled an increase in

screening rates (37).

Before-and-after trend studies present a

major difficulty for interpretation, because a

change in cancer incidence after the introduction of Pap smear screening may be due

to other factors (such as a change in the

epidemiology of the disease itself), rather

than to the screening program. In fact, incidence of invasive cervical cancer was apparently beginning to decline in the United

States even before the introduction of screening (108), and the decline did not accelerate

with the onset of screening. However, other

countries have experienced a reversal of

rising incidence immediately after comprehensive Pap smear screening was introduced,

implying that screening played a role in

bringing about lower incidence rates (67).

Also, since the introduction of screening in

the United States, invasive cancer incidence

and mortality rates have continued to fall

steadily (160) despite indications that greater

numbers of women are at risk of invasive

disease, and despite a dramatic increase in the

rate of CIS in some age groups (108).

Canadian researchers tested the possibility that the general decline in cervical

cancer incidence rates in that country might

be due to increased hysterectomy rates in the

population. To address this potential bias,

data from British Columbia were adjusted for

age-specific hysterectomy rates. This adjustment did not change the rate of decline in

incidence rates to any substantial degree (99).

Comparisons Between Intensely and Less

Intensely Screened Populations--Studies from

various parts of the world have concluded

that regions with aggressive, intensive screening programs show a greater decrease in the

incidence and mortality from cervical cancer

than regions where screening is less intensive.

In Canada, data on the intensity of screening

within a province have been linked to cancer

registry incidence and mortality rates, and

provinces with the most comprehensive

screening have the largest decline in incidence and mortality rates (98).

Comparisons among the Nordic countries

show similar trends. Denmark, Sweden, Finland, and Iceland have introduced organized

population screening, while Norway has not.

The first four countries have seen considerable reductions in cervical cancer incidence

rates, but rates in Norway have declined very

little (59). The amount of decline in these

countries is correlated with the proportion of

women screened, with the greatest decline in

the country with the most extensive screening

program .

Studies from Canada and Iceland have

found that while cancer incidence rates have

declined over time for women who are

screened, rates among unscreened women are

equal to or higher than pre-screening rates

for the entire population (46,67). While selection bias undoubtedly accounts for some of

the differences in rates among screened and

unscreened groups, the continued decline in

incidence even while an increasing proportion

of women are being reached by screening

suggests that screening itself is contributing

to the decline.

If screening is effective, the proportion

of invasive cancer diagnosed early should increase, and later-stage diagnoses should

decrease.’ This expectation has been largely

‘7 Women with late stage disease (II-IV) are likel y

to have symptoms (e.g., vaginal bleeding) an d

therefore are likely to be diagnosed even in th e

absence of screening. Women with early disease are

less likely to be diagnosed without screening. In

a recent review of one New York City hospital s

experience with cervical cancer, 75 percent o f

elderly women with stage IA disease, and 17 percent

of women with stage IB disease, were asymptomatic

at the time of diagnosis (51).
Costs and Effectiveness of Cervical Cancer Screening • 27

borne out. In Minnesota, the proportion of

invasive disease diagnosed at stage I increased

from 7 percent in the period 1935-1946 to 63

percent in the period 1957-1967 (37). In

Kentucky, stage I disease increased from

about one-third of all invasive disease in

1953-1955 to slightly less than half of diagnosed invasive disease in 1971-1973 (27).

Differences among screened and unscreened

women in stage at diagnosis are also consistent with the hypothesis that screening increases the proportion of invasive cancer

detected at an early stage. Of unscreened

women 14 to 40 percent (median 32 percent)

are diagnosed at stage I (22,28,37,44,46,

104,146), compared to 22 to 65 percent

(median 50 percent) of all women (22,28,37,

46,158).

Opposite trends were found in British

Columbia, with a higher proportion of invasive cancer detected at later stages after

screening became well-established (19). Total

incidence and mortality continued to decline,

however (3), and the author attributed the

worsening state distribution to the most difficult and aggressive lesions being unaffected

by screening (19).

Case-Control Studies

Another method of assessing the effectiveness of screening programs is the casecontrol method, in which women with invasive cancer (cases) are compared with other

women (controls) regarding their use of

screening. If women with cancer are less

likely to have been screened, then screening

presumably lowers the risk of developing invasive cancer. Selection bias often confounds

interpretation of case-control studies, since

some factors (e.g., lower socioeconomic

status) are independently correlated with both

a higher risk of cervical cancer and a lower

probability of screening. The more closely

matched the cases and controls are for such

confounding risk factors, the more confidence

one can have that screening, not other risk

factors, accounts for the difference in cancer

between the groups.

Case-control studies have been conducted

in several areas of the world and have all

yielded similar results. These studies are

summarized in table 8. Overall, women who

have never been screened have a risk of developing invasive cervical cancer that is 2 to

10 times greater than the risk in women who

have been screened at least once (4,15).

Of particular interest is the Toronto

case-control study, which included only

symptomatic invasive cancer cases. In this

study attempts were made to minimize selection bias by matching study subjects for age

and location and type of housing (as a proxy

for socioeconomic status). The study found

that over half of the control subjects had

been screened by Pap smear within the past 5

years, compared with only one-third of cases

(29). The relative risk of invasive cancer was

2.7 times greater in women who had not been

screened than in those who had been, and for

unscreened elderly women (over age 60) the

relative risk was even higher (3.4).

Effectiveness of Screening in the Elderly

Despite the problems in assessing studies

of cervical cancer screening effectiveness, the

evidence from a multitude of settings and

geographic locations is fairly consistent and

supports the contention that, in general, Pap

smear screening is effective in reducing the

incidence of invasive cervical cancer and the

mortality from this disease. There is far less

evidence regarding Pap smear effectiveness in

reducing morbidity and mortality in elderly

populations, since elderly women are poorly

represented in screening programs and

studies.

Most studies that have examined incidence rates by age group have found that

younger women are both more likely to be

screened and have a lower incidence of invasive cancer than older women (27,28,39,70).

Mortality rates from cervical cancer have also

declined less in older than in younger women

(39,87) and, in

rate for women

not decline at all

some studies, the mortality

in the oldest age group did

(27,1 15).

19-754 0 - 90 - 3
28 • Costs and Effectiveness of Cervical Cancer Screening

Table 8--Case-Control Studies of Pap Smear Effectiveness

Increased risk of ICC for

Control never-screened women

Source Country population All age s Older women

Aristizaba l Columbia Women matched for age, 9 . 9 11. 5

b

et al., 198 4

a

neighborhood of residence

------ . . . . . . . ------- . . . . . . . . . . . . . . . . . . . . . ------- ------- ------- ------- ------- ------- ------- ------- --

Berrino et al., Ital y Hospital patient s 2 . 0

- .

1986 C

------ -.....- --..... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -...-. . . . . . . . . . . . . . . . . . . . . . . . . . . . . -------

Celentano United State s Women matched for age, 5 . 0

. .

et al., 198 9

d

(Maryland) neighborhood of residence

Randomly selected women matched 3 . 3

. .

for age, race, and geographic area

....-- ------- ------- . . . . . . . ------- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- . . . . . . . . . . . .

Clarke and Canada Middle-class women 2 . 7 3 . 4

f

Anderson, 1979e matched for age,

housing type

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- ------- ------- ------- --

LaVecchia et al., Ital y Hospital patient s 4

. .

1984g

------ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------

MacGregor et al., L

Scotland Other resident s 3 . 3

i

. .

1985 who had been screened

at least onc e

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . --------- . . . . . . . . . . . . . . . . . . --------- --------- --------- -

Raymond et al., Switzerland Swiss residents 5 . 3

k

. .

1984J matched for age,

marital statu s

....-- ------- . . . . . . . ------- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Stenkvist et al., Sweden Cross-section of 4

. .

1984 entire countr y

....-- ...-.-. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

van *r Graa f Netherlands Age-matched women from 4 . 5

. -

et al., 198 8

m

registrar’s roll s

ABBREVIATION: ICC = invasive cervical cancer.

aN. Aristizabal, C. Cuello, P. Correa et al. , llThe Impact of Vaginal Cytology on Cervical Cancer Risks i n

Cali, Coltiia,n Int. J. Cancer 34:5-9, 1984 .

b

Age 45 and older.

CF. Berrino, G. Gatta, M. d’Alto et al. , IiEfficacy of Screening in preventing Invasive CerVical CanCer: A

Case-Control Study in Milan, Italy, M Screening for Cancer of the Uterine Cervix, M. Hakame, A.B. Millerr

and N.E. Day (eds.), IARC Scientific Publications No. 76 (Lyon, France : International Agency for Research

on Cancer, 1986).

‘D.D. Celentano, A.C. Klassen, C.S. Ueisman et al. , ItDuration of Relative Protection of Scre~ning for Cer -

vical Cancer,~ Prev. Med. 18:411-422, 1989 .

‘E.A. Clarke and T.W. Anderson, ‘Does Screening b y ‘Pap’ Smears Help Prevent Cervical Cancer?lf Lance t

2(8132):1-4, 1979.

‘Age 60 and older.

gc. LaVecchia, s. Franceschi, A. Decarli et al., Illpapl Smar and the Risk of Cervical Neoplasia: QUantita-

~tive Estimates From a Case-Control Study,M Lancet 2(8406):779-782, 1984.

J.E. MacGregor, S.M. Moss, M.D. Parkin et al., WA Case-control St@ of Cervical Cancer Screening in North

iEast Scotland,” Br. Med. J. 290:1543-1546, 1985.

.Relative risk for women uith no previous negative smear conpared with negative smear 10 or more years ago.

JL. Ram, M. Obradovic, and G. Riotton, JIUW Et~e Cas-T~ins Pour llEvaluation du Depistage Cytologique

du Cancer du Col Uterin,M Rev. EDideMiO[. Sante Publ. 32:10-15, 1984, as summarized in IARC Uorking Grou p

on Cervical Cancer Screening, ItScreening for !kquamous Cervical Cancer- - The Duration of Low Risk Following

Negative Results in Cervical Cytology Tests: Introduction ,

w and Wsnnary Chapter, W Screening for Cancer o f

the Uterine Cervix, M. Hakama, A.B. Miller, and N.E. Day (eds.), IARC Scientific Publications No. 76 (Lyon,

kFrance: International Agency for Research on Cancer, 1986).

~Relative risk for women with no previous negative smear compared with negative smear 5 or more years ago.

B. Stenkvist, R. Bergstrom, G. Eklung et al., IIPapanicolaou Smear Screening and Cervical Cancer: Uhat Can

You Expect?” J.A.M.A. 252:1423-1426, 1984.

‘Y. van der Graaf, G.A. Zielhuis, and P.G. Peer , ItThe Effectiveness of Cervical Screening: A pOpUlatiOnBased Case-Control Study, U J . Clin. EPidemiol. 41(1):21-26, 1988 .

SOURCE: Office of Technology Assessment, 1990.
Costs and Effectiveness of Cervical Cancer Screening • 29

Elderly women with invasive cancer are

more likely than younger women to have advanced disease at the time of diagnosis. In

the Kentucky study, 76 percent of newly

diagnosed invasive disease in women aged 20

to 29 was stage I, compared to only 38 percent for women aged 60 to 69, and only 29

percent for women aged 70 or more (83).

The authors attribute the age-related differences to less Pap smear coverage in older

women, although no age-specific rates of

screening are presented in their published research. Even though the 29 percent figure

for elderly women presumably includes a

large proportion of unscreened women, it

may be high. A study that included unscreened women aged 60 to 69 found that

only 14 percent were diagnosed early (44).

In summary, it appears that Pap smear

screening has had some effect in reducing the

general incidence of and mortality from invasive cervical cancer, and it may also have

had some effect on the stage at diagnosis.

For elderly women, however, these trends are

much weaker. In many studies there is no

apparent improvement in cervical cancer

statistics for the older age group at all. Population denominators and age-specific screening rates are unavailable in most studies, so

firm conclusions about the reasons for the

poorer outcomes in this age group cannot be

drawn. It is possible that screening may be

less effective in elderly women (e.g., due to

faster progression of tumors and lower accuracy of Pap smears). But it seems likely

that at least some of the age-related differences in incidence and mortality when

screening is offered are related to lower

screening rates among elderly women.

Screening Recommendations

Government, professional, and consumer

groups, both in the United States and abroad,

have published recommendations regarding

Pap smear screening (table 9). Current

recommendations for Pap smear screening of

U.S. women vary depending on the recommending organization, but they generally suggest that screening every 1 to 3 years is appropriate, with the exact frequency to be

determined by a woman’s physician based on

her risk status (47,140,170). Of existing

recommendations by various U.S. groups, two

specifically address screening in elderly

women. Both advise that screening may cease

at some upper age limit, but only if the

woman has a well-documented history of

negative smears (140,162). Several other

countries that have developed Pap smear

screening recommendations have concluded

that screening elderly women is not productive (table 9).

U.S. Recommendations

From the 1950s through the 1970s, the

American Cancer Society (ACS) recommended

that Pap smears be one component of an annual pelvic examination. This policy was

supported by the American College of Obstetricians and Gynecologists (ACOG). Then,

in 1981, ACS amended its recommendations

to suggest that asymptomatic women aged 20

and over, and those under 20 who were

sexually active, have a Pap smear annually

until there are two consecutive negative examinations and then at least once every 3

years until age 65 (43). Until 1988, however,

ACOG continued to recommend annual

screening for cervical neoplasia in most

women beginning at age 18 (or when a

woman became sexually active) (l).

In the fall of 1987, ACS developed new

guidelines for cervical cancer screening,

which recommended that:

■

■

The

limit

All women who are or have been

sexually active, or are 18 years or older,

should have an annual Pap test and pelvic examination.

After 3 consecutive normal exams the

Pap test may be performed less frequently at the discretion of th e

physician (47).

recommendations place no upper age

on screening.
30 • Costs and Effectiveness of Cervical Cancer Screening

Table 9--Recommendations for Cervical Cancer Screening

Country/organization Recommended Distinctions fo r

(date of recommendation) screening frequency screening elderly women

United States=

ACS, ACOG, NCI, et al. Three consecutive annual normal Pap

(1988 )

a

tests starting at age 18 or onset of

sexual activity, then screening fre -

quency determined at physicians

discretio n

USPSTF (1989) b

Screening at 1 to 3 year intervals

determined by physician

NIH (1980 )

C

Screening at 1 to 3 year intervals

determined by physician

ASCP (1988) d Annually

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -------

Canada:

Task Force on Cervical Annually for sexually active women

Cancer Screening (1982) e

aged 18 to 35; every 5 years from

age 35 onward

Canadian Task Force on When first sexually active, and once

the Periodic Health Exam- within a year of first smear; ever y

ination (1979 ) 3 years until age 35; every 5 years

thereafte r

--------------------------------------------------------------------- -

None; no upper age limit is given

for screening

Screening may be discontinued at

age 65 if previous smears have

been consistently normal

For women over 60 with two negative smears screening is not productiv e

No distinctions made between

elderly and younger women

.-.-.. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Discontinue screening at age 60 if

repeated satisfactory smears were

obtained previousl y

Every 5 years or at interval based

on Physician's clinical judgment

----------------------------------

lhiited Kingdom:

Working Party on Cervical Every 3 years Screening may end at age 64 if 3

Cytology Screening (1987) g

consecutive negative smears have

been obtained (the latest not more

than 3 years previously)

------------------------------------------------------------------------------------------------------ -

Denmark:

Department of Health (1988 )

h Every 3 year s Women are not invited for smear

after age 7 0

------------------------------------------------------------------------------------------------------ -

Australia:

National Health and Medical Every 3 years No distinctions made between

Research Council (1987) 1

elderly and younger women

ABBREVIATIONS: ACOG = American College of Obstetricians and Gynecologists; ACS = American Cancer Society;

ASCP = American Society of Clinical Pathologists; NCI = National Cancer Institute;

NIH = National Institutes of Health; and USPSTF = U.S. Preventive Services Task Force.

a

D.J. Fink, ‘Change in American Cancer Society Checkup Guidelines for Detection of Cervical Cancer," ~

bCancer Journal for Clinicians 38(2):127-128, 1988.

U.S. Department of Health and Human Services, Preventive Services Task Force, Guide to Clinical Preventive

Services (Baltimore, MD: William & Wilkins, 1989).

c

Southern Medical Journal, " NIH Consensus Develo~nt panel Smnary--Cervical Cancer Screening: The pap

dSmear,” Southern Medical Journal 74(1):87-89, 1981.

Washington Report, I I Organ i

zat io n s Speak Out on Pap Smear Frequency,rl Washington Rem rt 6(2):1, 1988 .

‘Canadian Medical Association Journa(, IICervical Cancer Screeni ng Programs: Sumnary of the 1982 Canadia n

~Task Force Report, n Canadian Medical Association Journal 127:581-589, 1982.

Canadian Task Force on the Periodic Health Examination, ItThe periodic Health Examination 1979,” Canadian

Medical Association Journal 121:1193-1254, 1979.

gIntercol[egiate Working Party on Cervical Cancer Screenin9, Rewrt of the Intercollegiate Working Party on

~Cervica( Cytology Screening (London, England: Progress Press Ltd., 1987).

E. Lynge, ItMass Screening for Cervical Cancer and Breast Cancer in Denmark,il unpublished P@W for the

,Danish Cancer Society, June 1988.

‘P.U. Shield, B. Daunter, and R.G. Uright, ItThe Pap Smear Revisited,ll The Australian and New Zealand Journa l

of Obstetrics & Gynecology 27(4):269-282, 1987.

SOURCE: Office of Technology Assessment, 1990.
Costs and Effectiveness of Cervical Cancer Screening • 31

The National Cancer Institute (NCI),

ACOG, and a number of other medical associations have approved similar or identical

recommendations. Three other groups,

however--the American Society of Clinical

Pathologists (ASCP), the American Society of

Cytology, and the College of American

Pathologists-- do not entirely agree with these

guidelines. ASCP recommends, for example,

that all women who are (or have been)

sexually active continue to have annual Pap

smears even after a past series of normal

smears. ASCP makes no distinctions between

elderly and younger women (170).

The National Institutes of Health (NIH),

of which NCI is a part, have been actively

involved in the formulation of cervical cancer

screening recommendations. In 1980, NIH

convened a Consensus Development Panel to

examine the scientific basis for screening and

make recommendations for the use of the Pap

smear in screening for cervical cancer. The

panel recommended that all asymptomatic

women who are or have been sexually active

be screened at intervals between 1 and 3

years if the first and second smears are

normal, with the exact frequency to be

determined by the woman and her physician

(140). Screening in women over age 60 who

had had two previous negative smears was

believed to be “unrewarding.” These recommendations of the consensus pane 1

participants are slightly at variance with the

1988 ACS guidelines adopted by NCI itself.

In 1984, the Federal Government appointed a Task Force on Preventive Services

to develop age- and sex-specific recommendations for a variety of clinical preventive services, including Pap smears. The

recommendations, published in spring 1989,

included regular Pap testing for all women

starting at the beginning of sexual activity,

with repeat smears every 1 to 3 years at the

physician’s discretion. The task force recommended that screening stop at age 65 if previous smears have been consistently normal.

However, since many older women have not

been screened regularly throughout their

lives, the task force recommended that elderly women without a documented history of

negative smears continue to receive screening

(162).

Recommendations in Other Countries

Canada--Canada’s first recommendations

regarding Pap smear screening were issued in

a 1976 report from the Canadian Task Force

on Cervical Cancer Screening Programs. This

report suggested that all sexually active

women over age 18 receive an initial smear

followed by a second smear done within 1

year. If the two initial smears and all subsequent smears are satisfactory, further

smears should be taken at 3-year intervals

until the age of 35, and at 5-year intervals

from 35 to 60. Women over 60 who had

repeated satisfactory smears may be dropped

from the cervical cancer screening program

(22). The task force amended its recommendations in 1982, advising annual screening for sexually active women between ages

18 and 35. Annual screening of women over

35 was concluded to be unnecessary if a

woman had had normal smears until that

time. The task force reaffirmed its recommendation that women over 60 who have had

repeated satisfactory smears without significant atypia may be dropped from a

screening program (23). The recommendations of the Canadian Task Force on the Periodic Health Examination, issued in 1979,

echoed this advice (24).

Great Britain -- Until the governmentappointed Working Party on Cervical Cytology Screening issued standard guidelines for

cervical cancer screening, groups in Great

Britain supported varied and contradictory

screening protocols. The working party,

composed of representatives of relevant

medical organizations, recommended routine

Pap smear screening every 3 years for all

women beginning at age 20. The group also

recommended opportunistic screening of

younger women at high risk due to sexual activity. They suggested that screening should

end at age 64 provided the woman has had 3
32 ■ Costs and Effectiveness of Cervical Cancer Screening

consecutive negative smears, the most recent

one no more than 3 years previously (65).

The policy of the National Health Services

towards screening for cervical cancer in the

elderly is that cervical cytology is available to

women 65 and over who have not had two

consecutive negative smears in the previous

10 years (35).

Denmark and Australia--Both the Danish

and the Australian governments have issued

screening guidelines, although neither has a

formal nationwide cervical cancer screening

program. The Danish Department of Health

recommended in 1986 that screening be done

every 3 years. Screening is aimed at women

between ages 23 and 59, but all women are

invited until age 70 (84). In Australia, the

National Health and Medical Research Council issued a report on the frequency of cervical cytology in 1984; it recommended that

women be screened every 3 years from the

start of sexual activity onward (129).

Utilization of Screening by

the Elderly

Utilization Rates

Utilization of Pap smear screening is

lower for elderly than for other women. This

pattern may be partly related to the fact that

many of today’s elderly women were already

past childbearing, and no longer seeing an

obstetrician/gynecologist, when Pap smear

screening became widespread. Among w o -

men in general, both the proportion of women who have ever been screened and the

proportion who have been screened recently

has been growing over time. Elderly women,

however, continue to have lower utilization

by either measure.

Slightly more than one-half (52 percent)

of elderly women have had a Pap smear

within the past 3 years (55).8 Utilization has

8 Because of the data coding practices followed by

the National Health Interview Survey (NHIS), o n

which this figure is based, “within the past 3

years” actually means “within the past 3 years and

11 months. ”

increased over time but still remains lower

than in younger age groups. 1n One study,

the proportion of women aged 60 to 79 who

had had a Pap test within the past 2 years

rose from 38 percent in 1973 to 43 percent in

1985. Nonetheless, the 1985 screening rates

were still only two-thirds as high as the rate

in younger women (89). A second study,

based on a 1986 national telephone survey,

shows similarly dramatic differences in the

use of routine Pap smears between older and

younger women (table 10) (61). The decrease

in utilization associated with age in this study

cannot be attributed to a clinical decision to

withhold preventive care from women already

ill, since the results were unchanged when the

investigators controlled for health status.

A sizable group of elderly women who

have never been screened for cervical cancer

persists. Estimates of the number of U.S.

elderly women who have never been screened

range from 24 to 61 percent (86,150,169,172).

In a 1986 survey, 11 percent of elderly women said that they had never had Pap smears,

nearly double the 6 percent rate for women

in general (61). In a 1980 telephone survey

of Maryland women in non-metro -politan

communities, 23 percent of women aged 65

and older reported never having had a Pap

test and an additional 28 percent reported not

having had one within the past 5 years (26).

These results, although not generalizable to

metropolitan communities, are consistent with

the findings from the 1986 survey.

Table 10--Utilization of Routine

Pap Smear Screening

Age group

Received 65 and

last Pap smear 20-3 9 40-6 4 older

Within past year. . . . . . . . . 68% 49% 30%

Within past 3 years

(if age 20-64 )

or past 5 years

(if age 65 0r older) ....91% 73 % 59%

SOURCE : Adapted from R.A. Hayward, M. Shapiro,

H.F. Freeman et al., Who Gets Screened

for Cervical and Breast Cancer?" Arch.

Intern. Med. 148:1177-1181, 1988.
Costs and Effectiveness of Cervical Cancer Screening w 33

Correlates of Utilization in the Elderly

The factors a.ssociated with increased risk

of cervical cancer are also associated with low

utilization of screening for the disease.

Elderly women who refuse screening are

probably at higher risk than those who are

screened, as they are older, nonwhite, and not

previously screened (86). Elderly black

women living in non-metropolitan areas have

particularly low screening rates (73); in one

study, 68 percent of the women in this

category had never had a Pap smear (6). 9

Elderly Hispanic women also have very low

utilization rates (157).

Women with health insurance, and

women with private insurance supplements to

Medicare, are more likely to have had a

recent Pap smear than less insured and

uninsured women (55,61,176). Many insurance policies do not cover preventive care, so

these findings are probably not due solely to

coverage of preventive services. Rather, having health insurance may be correlated with

other factors such as greater affluence,

greater concern with health, or lower overall

out-of-pocket health expenditures that are

themselves related to higher use of preventive

services. Educational level and income have

also been found to be related to the probability of having had a recent test (61).

Going to a physician increases the probability of being tested, but it does not ensure

screening. In one study, among older women

who had never had a Pap test, 82 percent had

had a recent physician contact (89). In another study, the type of provider was associated with the regularity and the recency of

Pap testing: having a gynecologist as the

usual source of care was associated with a

9 In an analysis of 1982 NHIS data, race did not

have an independent effect on utilization of cervical cancer screening among elderly women (55).

Observed race differences in other studies may well

be explained by factors such as income and education .

greater probability of receiving regular Paptests (26). Relatively few elderly women,

however, have a gynecologist as their usual

source of medical care (only 1 percent of

women aged 65 to 74 in this study, for instance), and some elderly women receive most

of their medical care from specialists who

rarely provide gynecological care (e.g., carbiologists (26). Among younger women, gynecologists perform most Pap smears; for

elderly women, however, the proportion of

smears performed by gynecologists is less

than one-half (46 percent). Internists and

family practitioners perform most of the rest

(166).

It has long been assumed that elderly

women would be hard to recruit for screening

(133). However, a New York study (172)

found that Pap smear screening was acceptable to elderly women attending a municipal

hospital clinic: there was only a 25 percent

no-show rate for scheduled visits exclusively

for Pap tests, and none of the patients offered screening during a primary medical

care visit refused it. Outreach programs,

using mailed letters or telephone calls to invite women to come in for a screening appointment, have increased Pap smear utilization in both younger and older women in

England (l17,132). These strategies may well

be effective in elderly American women as

well, although recruitment of older women to

cancer screening is not necessarily inexpensive (75).

CONCLUSIONS

Pap smear screening, combined with appropriate treatment, can reduce the incidence

of invasive cervical cancer and the mortality

from the disease in the general population.

Elderly women are as likely as younger

women to develop invasive cervical cancer,

and they are considerably more likely to die

from the disease. Thus, routine Pap smear

screening of elderly women holds potential

for extending substantial health benefits to

this population.
34 ■ Costs and Effectiveness of Cervical Cancer Screening

Screening in elderly women, however,

has some characteristics that might yield different results from screening in younger populations. First, there appears to be less CIN

and CIS in elderly women. This finding may

be in part an artifact of lower screening rates

in elderly women. It is possible, however,

that either more of these lesions progress to

invasive cancer in elderly women, or that

progression is faster, or both. This suggests

that to detect cervical cancer at a preinvasive state, an optimal screening program

for older women would emphasize outreach to

previously unscreened women and may include more frequent tests. Second, the

potential for inaccurate Pap smears is higher

for elderly women, because it is more difficult obtain a sample of cells from the appropriate region of the cervix and because

elderly women may have a variety of disorders that can lead to abnormal smears.

Thus, ensuring the accuracy of sampling and

smear interpretation are also important components of a screening program.

Irrespective of other risk factors, women

who have been screened in the past are at

lower risk of developing invasive cervical

cancer than those who have not been

screened. This is presumably due to the

detection and treatment of noninvasive cervical neoplasia in screened women. Poor and

nonwhite elderly women are particularly likely not to have been previously screened.

Future cohorts of elderly women may

have either higher or lower risks of cervical

cancer than today’s cohort, due to differences

in such factors as history of sexuaI activity

and hysterectomy rates, and previous use of

Pap tests. Little research has been done that

elucidates the contributions of different risk

factors in the older age group or the natural

history of cervical neoplasia in this group.
3. THE COST-EFFECTIVENESS OF

SCREENING IN ELDERLY WOMEN

INTRODUCTION

Given that screening can be an effective

method of reducing morbidity and mortality

from cervical cancer in elderly women, what

are the actual likely costs and outcomes that

would result from screening women in this

group? This chapter describes a costeffectiveness analysis that assesses the health

and cost impacts of different Pap smear

screening alternatives for elderly women who

are screened. The chapter then examines

some of the implications of the model results

for the Medicare program.

THE COST-EFFECTIVENESS

MODEL

Description

The model examines the relative costs

and effectiveness of four different screening

alternatives:

one-time screening at age 65,

screening every 5 years (beginning at

age 65),

screening every 3 years, and

annual screening.

A Markov model (described in app. E) is

used to simulate the process of screening,

diagnosis, and treatment in a hypothetical

population of one million women, beginning

at age 65. Because one purpose of the model

was to lend insight into the usefulness of a

Medicare benefit, and because Medicare has

no records on most individuals before they

reach age 65, the model assumes that nothing

is known about the specific screening history

of any individuals before that age.

Five states of health are included in the

model and are labeled as follows:

■ healthy,

■ CIN (corresponding to cervical intrae -

pithelia neoplasia (CIN) grades

2--mild and moderate dysplasia),

1 and

■

■

■

CIS (corresponding to CIN grade 3--

severe dysplasia and carcinoma in situ

(CIS)),

early invasive cervical cancer (EICC,

corresponding to stage I cancer), and

late invasive cervical cancer (LICC, corresponding to stages II, III, and IV).

Within each state of health, two possible substates exist; a woman’s condition may be unrecognized (i.e., not yet brought to the attention of the medical system) or recognized

(i.e., diagnosed through screening or through

the diagnostic evaluation of symptoms). (Following the logic that “recognized” indicates

further contact with the medical system,

“healthy-recognized” is the label given in the

model to healthy women who have falsepositive Pap smear results and thus undergo

diagnostic workups. ) An additional state is

included to represent deaths as the model

progresses.

The simulation program tracks the progress of the hypothetical cohort of 1 million

65-year-old women until they reach age 109.

The remaining survivors are assumed to die

before reaching age 110. Each iteration of

the model corresponds to 1 year. Running

tallies are maintained of the number of

smears performed, the number of cases diagnosed at each disease stage, and overall cohort

survival.

A significant limitation of the Markov

model as it is applied here is that all tumors

are assumed to have a constant probability of

moving from one state to another in any

given time period. In real life there are likely to be multiple populations of tumors with

different progression rates depending on

etiology, host factors, and so forth. Cruciaaly, a screening program will be most sensitive

to finding the slowly progressing lesions

(length bias), leading to an overestimate of

the program’s effectiveness in preventing

35
36 • Costs and Effectiveness of Cervical Cancer Screening

mortality. The importance of this issue in

interpreting the model results is discussed at

the end of this chapter.

Assumptions

Model Inputs

A Markov model simulation requires two

sets of inputs (app. E). First, one must

specify the proportion of subjects in a cohort

falling into each state at the outset--i. e., the

proportion of 65-year-old women who are

healthy, have CIN, etc. In this model, the

proportion of women who begin the model in

a state other than healthy corresponds to the

prevalence of CIN, CIS, EICC, and LICC in

women at age 65. The probability of starting

in the healthy state is simply one minus the

total of the other probabilities. All women

begin the model in an unrecognized substate.

Second, one must specify, for each state,

the probability that a woman will move to a

different state (e.g., from CIN to CIS) during

each iteration of the model (i.e., per year).

Not all movements between states can occur;

no cases can move out of the dead state, for

example. Only the following types of transitions

■

■

■

■

■

are allowed in this model:

recognition -- transition from an unrecognized state to the corresponding

recognized state (through screening or

diagnosis);

clearance--transition from one healthy

substate to the other by ascertaining that

a Pap smear result was a false positive

(somewhat counterintuitively, this corresponds to transition from “healthyrecognized’ f to “healthy-unrecognized”);

progression --transition to the next most

advanced disease state (e.g., CIN to CIS);

regression or cure--permitted only for

transition from CIN or CIS to the

healthy state; and

death--transition to the dead state from

any other state.

In any year, women who do not make one of

these transitions remain in their current state.

The specific numbers used as inputs to

the model are derived from the medical

studies described in chapter 2. For mos t

relevant aspects of cervical cancer in elderly

women, no definitive studies or unified consensus exists. Thus, to enhance confidence in

the results of this model, a range of estimates

for each data element was obtained. A base

case was chosen to represent the “best

estimate” of the true value of the data item.

A high estimate and a low estimate are

chosen as well, in order to test the sensitivity

of the base-case results to the model assumptions. Such sensitivity analyses can enhance

confidence in the overall conclusions of the

simulation and identify the areas where uncertainty has the greatest implications. The

various estimates are presented in table 11

and discussed briefly below. Appendix F

presents the rationale for selecting specific

estimates in greater detail.

Recognition Probabilities--For women

with disease, the probability of transition

from an unrecognized to a recognized state in

the model is dependent on the sensitivity of

the Pap test. 1 For healthy women, “recognition” depends on the specificity of the test--

i.e., the rate at which healthy women are falsely identified as having disease. Base-case

rates of sensitivity and specificity used in the

model are within the range of estimates

reported in the literature, but they are from

the low end of that range to accommodate the

likelihood that real-world accuracy for Pap

smears from elderly women is somewhat

lower than the test accuracy found in carefully monitored studies and studies of

younger women.

Women with CIN and CIS can have their

disease recognized only through screening.

Invasive cancer, however, may also become

recognized as a result of symptoms. Reliable

1 The actual probability for women with CIN and CIS

is the product of test sensitivity and survival

probability; for women with EICC and LICC, the rate

of development of symptoms is an added factor.
Costs and Effectiveness of Cervical Cancer Screening ■ 37

Table n--Cost-Effectiveness Model Input Data Assumptions

Data assumption s

Lou Base High

Pap smear sensitivity and specificit y

Sensitivity for: CIN . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 0 . 7 5 . 0 0

CIS/EICC/LICC . . . . . . . . . . . . . . . . . 5 0 . 7 5 . 8 2

Specificit y . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. 8 7 . 9 5 . 9 9

Annual probability of recognizing disease due to symptoms

EICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 7 . 1 2 . 2 7

LICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. 8 0 . 8 0 . 8 0

Initial state distribution for Pap smear simulation

HEALTHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .99013 .98721 .97940

CIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .00380 .00480 .00580

CIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .00239 .00239 .00620

EICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .00081 .00280 .00559

LICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .0028 7 .00280 .00301

Age-group -specific mortality rates for invasive cervical cancer

EICC mortality at age: 65-69 . . . . . . . . . . . . . . . . . . . . . . . . .076618 .076618 .076618

70-74 . . . . . . . . . . . . . . . . . . . . . . . . .070786 .070786 .070786

75-79. . . . . . . . . . . . . . . . . . . . . . . . . .078677 .07867 7 .078677

80-108 . . . . . . . . . . . . . . . . . . . . . . . .138621 .138621 .138621

109 . . . . . . . . . . . . . . . . . . . . . . . . . . 1 . 0 1 . 0 1 . 0

LICC mortality at age: 65-69 . . . . . . . . . . . . . . . . . . . . . . . . .151742 .151742 .151742

70-74 . . . . . . . . . . . . . . . . . . . . . . . . .172282 .172282 .172282

. . . . . . . . . . . . . . . . . . . . . . . . .217248 .217248 .217248

.28101 7 .28101 7 .281017

85-108 . . . . . . . . . . . . . . . . . . . . . . . .331627 .331627 .331627

109 . . . . . . . . . . . . . . . . . . . . . . . . . . 1 . 0 1 . 0 1 . 0

Annual probabilities of progression between states ( p e r 1,000 cases )

HEALTHY --> CIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 4 3.2 8 5.4 1

CIN --> CIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73. 6 178. 0 267. 0

CIS --> EICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181. 0 261. 0 632. 0

EICC --> LICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220. 0 390. 0 860. 0

Annual regression rate (per 1,000 cases )

CIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 . 4 38. 1 265. 0

CIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 . 0 0 . 0 201. 0

Annual cure rate (Pe r 100 cases)

CIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85. 0 95. 0 98. 0

CIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90. 0 98. 0 98. 0

Key: CIN--cervical intraepithelial neoplasia (grades 1 and 2 )

CIS--carcinoma in situ and severe dysplasia

EICC--early invasive cervical cancer

LICC--late invasive cervical cancer

SOURCE: Office of Technology Assessment, 1990. See appendix F for sources of information and basis for

individual data assumptions.
38 • Costs and Effectiveness of Cervical Cancer Screening

data on the rates of symptom development

are not available. The assumptions regarding

the likelihood of symptom development are

based on data on the stage distribution of

cancers at diagnosis, the probability of progressing from EICC to LICC, and the assumption that the great majority of women

with LICC will develop symptoms within a

year (app. F).

Clearance- - Clearance occurs when a

woman with a false-positive test undergoes a

comprehensive diagnostic workup. It is assumed that all false positives are identified in

this workup.2

Progression, Regression/Cure, and Death

Probabilities--Some research suggests that the

probability of progressing from one state of

neoplasia to the next is dependent on age

(32). Base-case estimates in the model are

thus derived from age-dependent dat a

reported in the literature. The age-dependent

assumption may not be correct; however, the

high and low estimates of progression probabilities encompass a range of probabilities

that includes

Women

spontaneous

Women with

the healthy

data from other age groups.

with CIN or CIS may exhibit

regression to the healthy state.

recognized disease may revert to

state subsequent to treatment

(cure). Women with CIS are actually considered to be slightly more likely to be cured by

a single treatment than women with CIN, because more women with CIS undergo very

aggressive treatment (e.g., total hysterectomy).

Consequently, there is a slight increase in the

number of cases in which the lesion is entirely removed with a single treatment.

2 A special feature of this model is that the

healthy- recognized state is a “virtual” state :

after entering that state and being tallied (so

that costs of work-up can be assessed), these women

are returned to the healthy-unrecognized state immediately, rather than waiting for the next year.

Death rates in the model for women in

healthy, CIN, or CIS states are based on national, age-specific, all-cause mortality data

(164). They are considered highly reliable

assumptions and do not appear in table 11.

The situation for invasive cancer--EICC

and LICC--is different. Although some

women with EICC are probably cured, data

to estimate the probability of this are not

available. This model therefore does not

permit transitions from the invasive cancer

states back to earlier states. Consequently,

the model probably slightly overestimates

morbidity from invasive cancer; once a

woman moves into the EICC state, she will be

categorized as having invasive cancer until

she dies. This does not affect her chance of

survival in the model, however. The death

probabilities in the model for women with

invasive cancer are based on all-cause

mortality data specific to the cohorts of

women diagnosed in each stage of cervical

cancer. Thus, for a woman with EICC, the

statistical likelihood of dying in the model

depends only on the fact that she was once

diagnosed with EICC, not on the fact that the

model continues to classify her in that

category.

Service and Cost Assumptions

Each woman in the model diagnosed with

CIN, CIS, EICC, and LICC incurs the costs

of diagnosis, treatment, and followup associated with that state. At any given screening

frequency, a single iteration of the model

(representing the passage of a year of time) is

accompanied by a specific number of women

newly diagnosed in each state. These women

then begin to accrue the costs associated with

those diagnoses. At the end of the simulation, the total costs associated with each

screening frequency can be tallied and compared.

The costs of screening itself and of

clearing false-positive cases are also included

in the total costs for each screening frequency. In the model, a “positive” test is any
Costs and Effectiveness of Cervical Cancer Screening •39

Pap smear result that leads to a further investigation of the possibility of neoplasia. A

“false-positive” test is any so-defined positive

smear in which the investigation does not

lead to a diagnosis of neoplasia, even if some

other condition is diagnosed and followed up.

This model considers neither the additional

costs nor the additional benefits incurred

after this point from the incidental diagnosis

of other conditions. The cost of a workup to

clear a false positive is equivalent to the

diagnostic segment of care for CIN.

To calculate the average cost per woman

in each state (CIN, CIS, EICC, and LICC), a

set of services related to the diagnosis, treatment, and followup of each state were

specified. The specified protocol is based on

current oncological practice, supplemented by

observations of members of an expert panel

from their clinical experience (app. C).

Modifications were made in the indicated

protocol based on statistical data from the

National Hospital Discharge Survey, which

made possible an analysis of the proportion of

hospitalized elderly women with a given

diagnosis who actually received specific services. It must be emphasized that the

resultant modified protocol is not, and is not

intended to be, an example of an ideal

protocol for treating cervical neoplasia.

Rather, it is an approximation of actual current practice.

Table 12 summarizes the total costs for

all services described below. 3 The itemized

components of these costs and the calculation

3 The estimate of the total cost of late cance r

care, $13,266, is lower than estimates by othe r

analysts based on 1974-1981 data from the Con -

tinuous Medicare History File (5). Their analysi s

would lead to an estimated total cost of approximately $7,000 for a woman dying of cervical cancer

2 years after diagnosis. Their estimates are no t

directly usable in this cost-effectiveness analysis

because they do not distinguish between cases

diagnosed in early versus late stages, as is required for this model . In addition, changes i n

clinical practices , substitution of outpatient fo r

inpatient locations, and so forth, make i t

desirable to avoid reliance on data from the 1970s.

Table 12--Summary of Cost Estimates for

Different Components of Ca

Diagnosis/

Component treatment Followup Total

CIN. . . . . . $ 669.6 5 $ 432.7 1 $1,102.3 6

CIS. . . . . . 3,925.9 6 432.71 4,358.6 7

EICC.... . 8,033.7 0 1,182.7 6 9,215.7 6

LICC.... . 12,232.0 0 1,126.7 6 13,358.7 6

Fals e

positives: $ 575.51 $ -- $ 575.5 1

Screening: $ 11.37 (base estimate )

11.37 (low estimate )

43.25 (high estimate )

a

Cost per woman with indicated condition when it

occurs. (Costs as presented in this table are un -

discounted; they are discounted at the point i n

the model where they are incurred.)

KEY: CIN--cervical intraepithelial neoplasi a

CIS--carcinoma in situ

ElCC--early invasive cervical cancer

LICC--late invasive cervical cancer

SOURCE: Office of Technology Assessment, 1990 .

See appendix F for calculation of indi -

vidual costs.

of total cost for each service package (e.g.,

treatment of CIS) are detailed in appendix F.

Screening --All women are screened in

the model (except in the no-screening

scenario). The updated Medicare average allowed charge for a simple Pap smear and associated specimen collection fee ($11.37) is

used as the assumed cost of the screening service for both the base case and the low

estimate. 4 The high-cost estimate for screening includes the cost of a limited visit to a

gynecologist as well as the cost of the test itself. If the result of Pap smear screening is

4 The Medicare average allowed charge for a service

is used as the basis for Medicare payments t o

health care providers ; Medicare pays a proportion

of the allowed charge for all covered services .

Actual physician and laboratory charges may b e

higher than the Medicare allowed charge.
40 • Costs and Effectiveness of Cervical Cancer Screening

negative, the patient receives no further service, and she is returned to the population

with the expectation of routine rescreening at

the time interval under study (e. g., in 5

years).

Diagnosis--If the result of the screening

is positive for abnormal cells, a C OlPOSCOPY is

done (assumed to require an office visit).

Subsequent procedures depend on the adequacy and results of COlPOSCOPY, as follows:

If a satisfactory view is obtained at colposcopy, then positive cases undergo a

directed biopsy. Negative cases repeat

the Pap test. If it, too, is negative, the

case is returned to the population, but if

it is positive, ionization is performed.

This is an inhospital procedure.

If colposcopy does not provide satisfactory visualization of the suspect area,

ionization is done. If the finding is

negative, the Pap test is repeated, and if

that is positive, other biopsies are done;

if the Pap test is negative, the patient is

returned to the population. If the conization finding is positive, the case is

diagnosed as CIN, CIS, or invasive cancer.

This is the extent of the diagnostic

workup for women with false-positive tests

and for women with CIN or CIS. Women

with invasive cancer must also undergo a

staging workup to determine the extent to

which the cancer has spread. The staging

protocol includes chest X-ray, pelvic computed tomography scan, sigmoidoscopy,

barium enema, cystoscopy, intravenous

urography, and blood tests (complete blood

count, blood urea nitrogen, and creatinine

determination). 5 Most of this protocol can be

completed on an outpatient basis, although a

5 The use of ultrasound evaluation in place of some

other tests is gaining favor in some institutions,

but since the practice is apparently not ye t

widespread and there are no data on its frequency,

it is not reflected in the cost assumptions of thi s

model.

minority of women (20 percent of those with

EICC and 30 percent with LICC) receive the

workup as hospital inpatients.

Treatment--For CIN, treatment options

include cryosurgery, cauterization, and laser

surgery, while for CIS the options are

therapeutic ionization or hysterectomy. It is

assumed that all true-positive CIN cases, and

all CIS, EICC, and LICC cases, are treated.

The assumed frequency with which various

procedures are undertaken is drawn from existing hospital discharge data on patients with

cervical cancer (app. D).

EICC treatment options are implantation

of radioactive agents and/or hysterectomy.

LICC options include distant radiation,

chemotherapy, pelvic exenteration, or combinations of these. Some advanced cases are

admitted to hospitals for supportive terminal

care. (This protocol probably underestimates

the actual total costs of LICC, since it does

not include some relevant outpatient services--e. g., the cost of drugs to reduce pain.)

Followup Services and Costs--Each condition that requires treatment is assumed to

have attendant 5-year followup costs. The

services associated with followup of different

disease states are adapted from Mandelblatt

and Fahs (91).

6 The specific services and associated costs are presented in detail in appendix D for each disease state. In summary,

the protocol for 5-year followup of each state

is as follows:

■ CIN and CIS--office visits and annual

Pap smears for all patients. A small

proportion of patients undergo repeat

treatments (cryosurgery or ionization)

during the first followup year.

ElCC--office visits and various diagnostic tests, including intravenous

6 In pricing the followup services, clinic visit s

in their protocol are replaced by physician offic e

visits for applicability to the general populatio n

of elderly women.
Costs and Effectiveness of Cervical Cancer Screening • 41

■

pyelograms (IVPS), chest X-rays, and

pelvic sonograms. Numbers of visits

and tests are greatest in the first year.

LICC--office visits, IVPS, and chest Xrays in followup years 1 through 3;

office visits, an IVP, a chest X-ray, and

a pelvic sonogram in each of years 4

and 5.

Followup accounts for 8 percent of the

total cost of LICC, for 12 percent of EICC,

and for 9 percent of CIS costs. Since CIN

evaluation is not very costly compared to

evaluation of these other stages, followup

amounts to 38 percent of total cost per CIN

case.

Results

This model calculates the health care

costs associated with screening, diagnosis, and

treatment of cervical neoplasia at each

alternative screening frequency. The benefits

calculated include only the years of life saved

by implementing screening. Other potential

costs (e.g., cost of medical care for conditions

unrelated to cervical cancer in those lifeyears saved) and other benefits (e.g., disability days avoided) are not considered.

Both costs and life-years saved are discounted

in the reported results.’

The results of the cost-effectiveness

model under base-case assumptions are shown

in tables 13 through 15. They are presented

for 3, 5, and 7 percent discount rates. The

discussion below focuses on the base-case

results for a 5-percent discount rate.

Health Effects of Screening

In the base case, 14,400 discounted life

years are gained for the model cohort of one

million women by instituting a single screen7 Discounting accommodates the economic assumption

that something of value received today is worth

more than that same thing received later. A 5

percent discount rate assumes that a $100 benefit

(or cost) 1 year from now is equal to a $95 benefit

(or cost) today . Discounting thus displays al l

benefits or costs in their present value.

Table 13--Model Results: Life-Years Saved

(Base-Case Assumptions)a

Discount rat e Years of life of cohort

and screening (in thousands)

schedule Total Additional

3% discount rate

No screening . . . . . . . 13,364.9 .

One-time at 65..... 13,384. 2 19: 3

Every 5 years . . . . . . 13,416.1 31. 9

Every 3 years . . . . . . 13,425.8 12. 7

Every year. . . . . . . . . 13,435.2 9 . 4

5% discount rate

No screening . . . . . . . 11,383.1 .

One-time at 65..... 11,397. 5 14. 4

Every 5 years . . . . . . 11,419.3 21. 8

Every 3 years . . . . . . 11,426.3 7 . 0

Every year. . . . . . . . . 11,433.1 6 . 8

7% discount rate

No screening . . . . . . . 9,877.4 .

One-time at 65..... 9,888. 4 11. 0

Every 5 years . . . . . . 9,903.5 15.1

Every 3 years . . . . . . 9,908.6 5 . 1

Every year. . . . . . . . . 9,913.7 5 . 1

‘Per 1 million women beginning at age 65,

SOURCE: Office of Technology Assessment, 1990.

ing at age 65 (table 13). There are successive

increments in discounted life-years gained as

the intensity (frequency) of screening is increased, although the size of the increase

declines at frequencies greater than 5 years.

In progressing from a 5-year to a 3-year

schedule, for example, the incremental gain is

reduced to 7,000 life-years. There is some

gain at every increase in screening frequency,

however, so total life-years of the cohort are

greatest at the most frequent screening schedule. Annual screening adds 50,000 more

years of life than no screening at all, or an

average of 18 more days of life per woman in

the cohort.

The added years are expected to be of

good quality, because they are obtained

through the prevention of late-stage cancer

cases, not just through extending life for

women with late-stage disease. (As table 14

shows, the number of cases of LICC decreases from 23,500 with no screening to
42 • Costs and Effectiveness of Cervical Cancer Screening

Table 14--Model Results: Numbers of Smears Taken and Cases

Detected (Base-Case Assumptions)a

,

b

I

Numbe r

Smear s Fals e Case s

(mi11 ions )positive s C I N C I S EIC C LIC C

No screening . . . . . . . . . . . . -- . - . . . . 34,46 1 23,53 2

One-time at 65.. . . . . . . . . 1.0 49,36 1 3,60 0 1,30 6 30,82 5 20,21 1

Every 5 years . . . . . . . . . . . 4.1 199,57 0 29,25 7 8,18 0 14,28 1 8,16 2

Every 3 years . . . . . . . . . . . 6.4 317,34 0 38,82 9 7,70 5 9,73 1 5,85 4

Every year. . . . . . . . . . . . . . 18 3 910,14 1 53,82 4 3,51 1 4,52 4 4,09 9

a

The same actual numbers of cases accrue for each screening alternative regardless

Only the ultimate value of those cases expressed as life-years saved, is discounted , .

b

Per 1 million women beginning at age 65 .

KEY : CIN--cervical intraepithelial neoplasi EICC--early invasive cervical cance a r

CIS--carcinoma in sit u LICC--late invasive cervical cance r

SOURCE Office of Technology Assessment, 1990 : .

4,100 cases with annual screening.) Women

live longer because they are cancer-free, or

because they have early rather than late cancer. The cost of increasing years of cancerfree life among some members of the group,

however, is increased detection and treatment

of CIN. Some women whose CIN is detected

and treated would not have gone on to develop invasive cervical cancer in their lifetimes.

For these women, screening does not improve

the quality of life; rather, it brings with it

only the psychological costs and physical discomfort of undergoing the diagnostic and

treatment procedures. This problem is

greatest with annual screening, where the

greatest number of CIN cases are detected.

costs

The costs associated with cervical cancer,

including screening, diagnosis, treatment, and

identification of false positives, are shown in

detail in table 15. Total costs of services are

higher with screening than without it, and

they increase as the frequency of screening

increases. The total cost of cervical cancer

care for the cohort (of 1 million women) in

the absence of screening is $218 million in

the base case. By comparison, the cost associated with the least-intensive screening

schedule--one-time screening at age 65--is

$242 million, an incremental cost of $24million. Total costs increase as the screening

schedule intensifies and rise dramatically for

annual screening, which has a total cost of

$585 million (an incremental increase of $270

million over an every-3-year screening

schedule).

The relative cost-effectiveness of screening at various intervals depends on whether

the increase in life-years gained as screening

frequency increases is more rapid than the

rise in total costs associated with more frequent screening. Comparison of costs and effects of different schedules produces a costeffectiveness ratio showing the added cost per

year of life gained by screening (table 16).

In the base case this amount is $1,666 for a

one-time screen, but it increases with frequency of Pap testing, so that moving from a

5-year to a 3-year schedule costs $5,956 per

additional discounted life-year gained. Annual screening costs considerably more--

$39,693 per discounted life-year added to the

cohort’s life expectancy.

Sensitivity Analyses

Favorable/Unfavorable Cases--This

analysis tests the sensitivity of the model

results to changing the base-case assumptions
Costs and Effectiveness of Cervical Cancer Screening ■ 43

Table 15--Model Results: Costs (Base-Case Assumptions)a

cos t

Discount rat e (in millions ) Cost of car e Tota l

and screenin g Confirmation o f (in millions ) cost s

schedul e Screenin g false positive s CIN CIS EICC LICC (in millions )

3% discount rat e

No screening . . . . . . . . . . $-- $

. . $

. . $

. - $ 4 9 $21 2 % 261

One-time at 65.. . . . . . . 11 2 8 4 6 5 4 1 7 7 281

Every 5 years . . . . . . . . . 36 8 9 2 3 2 7 5 2 8 4 3 1 1

Every 3 years . . . . . . . . . 56 1 3 9 3 1 2 6 4 2 6 4 3 5 8

Every year. . . . . . . . . . . .1 5 6 3 9 2 4 4 1 3 2 4 4 8 6 7 7

------ . . . . . . . . . . . . . . ------- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5% discount rat e

No screening . . . . . . . . . . $-- s

. . $. - $

. . $ 4 0 $17 8 $21 8

One-time at 65.. . . . . . . 11 2 8 4 4 6 1 4 7 2 4 2

Every 5 years . . . . . . . . . 31 7 8 2 0 2 3 4 5 7 7 2 7 3

Every 3 years . . . . . . . . . 1 2 0 2 2 3 8 3 1 5

Every year. . . . . . . . . . . .1 3 2 3 3 3 3 7 1 2 2 3 4 8 5 8 5

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7% discount rat e

No screening . . . . . . . . . . $-- $-- $-- -- $ $ 3 3 $15 3 $ 18 6

One-time at 65.. . . . . . . 11 2 8 4 6 4 0 1 2 5 2 1 4

Every 5 years . . . . . . . . . 28 6 9 1 7 2 0 4 0 7 2 2 4 5

Every 3 years . . . . . . . . . 42 105 2 3 2 0 3 4 5 9 2 8 2

Every year. . . . . . . . . . . .1 1 4 2 8 8 3 2 11 2 3 4 7 5 1 6

a

Per 1 million women beginning at age 65 .

KEY: CIN--cervical intraepithelial neoplasiEICC--early invasive cervical cance a r

CIS--carcinoma in sit u LICC--late invasive cervical cance r

SOURCE: Office of Technology Assessment, 1990 .

Table 16--Cost-Effectiveness of Screening Under Alternative Screening

Assumptions: Base Case (5% Discount Rate)

Discounted life-years ’ Cost-effectiveness rati o

Screenin g (in thousands ) Costs (in millions ) (added cost per

schedule Cohort Added Total Added life-year gained )

I I

No screening . . . . . . . . 11,383. 1 $217.7 9

One-time at 65..... . 11,397. 5 14. 4 241.7 8 $23.9 9 $ 1,66 6

Every 5 years . . . . . . . 11,419. 3 21. 8 273.4 6 31.6 8 1,45 3

Every 3 years . . . . . . . 11,426. 3 7 . 0 315.1 5 41.6 9 5,95 6

Every year. . . . . . . . . . 11,433. 1 6 . 8 585.0 6 269.91 39,69 3

a

Per 1 million women beginning at age 65.

SOURCE: Office of Technology Assessment, 1990.
44 • Costs and Effectiveness of Cervical Cancer Screening

to more extreme high and low estimates (under a 5-percent discount rate). It includes:

a “favorable” case in which all high and

low input estimates most favorable to

screening (e.g., high test accuracy, high

prevalence) are combined; and

an “unfavorable” case that combines all

assumptions most unfavorable to screening. 8

The specific set of high and low assumptions used for each case are presented in table

17; results are presented in table 18. Varying

all assumptions in a direction favorable to

screening results in absolute savings for all

increases in Pap test frequency except for

shifting from 3 years to 1 year. In addition,

the gain in life years is substantially greater

than in the base case. Compared to no

screening, even a single screening gains

29,600 years of life. In contrast, if unfavorable assumptions are used, the greatest

incremental gain occurs in going from no

screening to a single screen but results in the

addition of only 2,500 years of life. More

frequent screening results in some additional

gains, but at very high cost; at annual screening, the incremental cost per life-year gained

is nearly $800,000.

High Risk/Low Risk Populations--In a

further analysis, the model was applied separately to hypothetical cohorts of high-risk

and low-risk women.

■ The “high-risk” case includes assumptions of high incidence, prevalence, and

progression rates and low regression

rates (table 17). The low rate for symptom development for early cancer was

also used, representing lower ability or

willingness to enter the medical system

after the development of mild symptoms

of cancer. All other probabilities are as

in the base case.

8 High estimates of progression rates may be either

favorable or unfavorable to screening, depending on

how rapidly progression is assumed to occur in the

base case. In this model, it turns out that lower

estimates of progression rates are unfavorable ,

while higher estimates are favorable (table 17).

■ The “low-risk” case assumes low incidence, prevalence, and progression

rates; and high regression and symptomaticity rates. Other assumptions are

as in the base case.

Marked differences in outcome were

found for the two groups (table 18). For

high-risk women, the gain in discounted life

years was substantial throughout, and 5- and

3-year schedules result in actual cost savings.

Even annual testing would cost less than

$6,500 per incremental life-year saved. For

low-risk women, gains were small for all but

one-time testing. One-time testing yielded a

cost-effectiveness ratio of $11,666 per lifeyear gained; cost-effectiveness ratios for

more frequent intervals range from over

$73,000 to nearly $500,000.

The “high-risk” and “low-risk” groups in

the model do not directly correspond with

known risk factors for individuals (e.g., past

history of multiple sexual partners, no prior

screening). The set of assumptions used to

define these groups in the model, however,

are those that most likely underlie higher

real-world risk. A lack of prior screening,

for example, means that any existing disease

has not been detected; thus, elderly women

with this risk factor would have higher average prevalence rates of neoplasia (one of the

inputs for the high-risk group in the model).

Individual Sensitivity Analyses--In order

to test the robustness of the clinical and economic assumptions used in the baseline

model, one-way sensitivity analyses were performed for the worst-case assumption (either

high or low estimate, depending on the parameter) for individual model parameters. For

the previously described sensitivity analyses,

the results compared the relative costeffectiveness of screening under different

screening schedules. To judge the effect of

varying each individual parameter, however,

all variables except the individual parameter

of interest -- including the screening schedule -- are held constant. Thus, a single

screening schedule must be chosen for the
Costs and Effectiveness of Cervical Cancer Screening • 45

Table 17--Cost-Effectiveness Model Input Data Assumptions:

Selected Sensitivity Analyses

Data assumption s

Favorable/unfavorabl e

a

High risk/low ris k

b

Pap smear sensitivity and specificit y

Sensitivity for: CIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 0 . 5 0 . 7 5 . 7 5

CIS/EICC/LICC . . . . . . . . . . . . . . . . . . 8 2 . 5 0 . 7 5 . 7 5

Specificit y . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 9 . 8 7 . 9 5 . 9 5

Annual probability of recognizing disease due to symptoms

EICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 7 . 2 7 . 0 7 . 2 7

LICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 0 . 8 0 . 8 0 . 8 0

Initial state distribution for Pap smear simulation

HEALTHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .97940 .99013 .99013 .97940

CIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .00580 .00380 .00380 .00580

CIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .00620 .00239 .00239 .00620

EICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .00559 .00081 .00081 .00559

LICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .00301 .0028 7 .0028 7 .00301

Mortality rates for invasive cervical cancer

(Same as base case for all alternatives--see table 9)

Annual rate of progression between states (per 1,000 cases)

HEALTHY --> CIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 1 0.9 4 5.4 1 0.9 4

CIN --> CIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267. 0 73. 6 267. 73. 6

CIS --> EICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 632. 0 181. 0 632. 181. 0

EICC --> LICC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 860.0 220. 0 860. 220. 0

Annual regression rate ( Pe r 1,000 cases)

CIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 . 4 265. 0 5 . 4 265. 0

CIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 . 0 201. 0 0 . 0 201. 0

Annual cure rate (De r 100 cases)

CIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98. 0 85. 0 95. 0 95. 0

CIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98. 0 90. 0 98. 0 98. 0

a

The ‘favorable" sensitivity analysis combines all high and low assumptions most favorable to screening.

bThe "unfavorable~ sensitivity analysis combines all assumptions least favorable to screening.

The ‘high risk ~ case assumes high incidence, prevalence, and progression rates and low regression rates,

while the "low risk” case uses opposite assumptions for these factors. Other assumptions (e.g., test ac -

curacy) are as in the base case.

Key: CIN--cervical intraepithelial neoplasi a EICC--early invasive cervical cancer

CIS--carcinoma in situ LICC--late invasive cervical cancer

SOURCE: Office of Technology Assessment, 1990. See appendix F for sources of information and basis for

individual data assumptions.
46 ■ Costs and Effectiveness of Cervical Cancer Screening

Table 18--Cost-Effectiveness of Screening Under Alternative Screening Assumptions:

Selected Sensitivity Analyses (5% Discount Rate)a

Discounted life- year s

a

cost s Cost-effectiveness ratio

Screening (in thousands) (in millions ) (added cost per life -

schedule Cohort Added Total Added year gained)

Favorable case

No screening . . . . . . . . . 11,264. 3 s 553.75 $ --.-” $

. . .

One-time at 65.. . . . . . 11,293. 9 29. 6 531.1 8 -22.5 7

*

Every 5 years . . . . . . . . 11,343. 3 49. 4 436.3 3 -94.8 5

*

Every 3 years . . . . . . . . 11,366. 9 23. 6 400.5 4 -35.7 9

*

Every 1 year. . . . . . . . . 11,395. 0 28. 1 430.2 7 29.7 3 1,05 8

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ------- ------- ------- ------- ------- ------- ------- ------ ------ ---

Unfavorable case

No screening . . . . . . . . . 11,439. 5

. $ 52.87 $ ----- $

. . .

One-time at 65.. . . . . . 11,442. 0 2 . 5 173.0 9 120.2 2 48,08 8

Every 5 years . . . . . . . . 11,442. 8 0 . 8 382.3 7 209.2 8 261,60 0

Every 3 years . . . . . . . . 11,443. 3 0 . 5 557.1 9 174.8 2 349,64 0

Every 1 year. . . . . . . . . 11,444. 4 1.1 1,434.4 6 877.2 7 797,51 8

High-risk women

No screening . . . . . . . . . 11,264. 3

. $ 553.75 s ----- $

- - -

One-time at 65.. . . . . . 11,292. 3 28. 0 554.9 5 1.2 0 4 2

Every 5 years . . . . . . . . 11,338. 9 46. 6 504.3 4 -50.6 1

*

Every 3 years . . . . . . . . 11,362. 1 23. 2 502.8 0 -1.5 4

*

Every 1 year. . . . . . . . . 11,392. 3 30. 2 697.41 194.61 6,44 4

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -

low-risk women

No screening . . . . . . . . . 11,439. 5

. $ 52.87 $ ----- $. . .

One-time at 65.. . . . . . 11,443. 3 3 . 8 97.2 0 44.3 3 11,66 6

Every 5 years . . . . . . . . 11,444. 3 1 . 0 170.5 4 73.3 4 73,34 0

Every 3 years . . . . . . . . 11,444. 8 0 . 5 230.8 0 60.2 6 120,52 0

Every 1 year. . . . . . . . . 11,445. 4 0 . 6 530.4 2 299.6 2 499,36 7

*Cost-saving.

a

Per 1 million women beginning at age 65.

SOURCE: Office of Technology Assessment, 1990.

analysis. Results for the one-way sensitivity

analyses below are based on comparing a 3-

year screening schedule with no screening.

They can be contrasted with the analogous

comparison under the base case, where 3-year

screening (compared to no screening) costs

$2,254 per life-year gained. (Note that this

figure is substantially different from the figure presented earlier, which was the incremental cost-effectiveness of 3-year compared to 5-year screening.)

to no screening, 34,200 life years are

gained for the cohort at an added cost

of over $303 million, or $8,866 per lifeyear gained. In other words, if test accuracy deteriorated from base-case to

low-case estimate--all else equal--the

deterioration in test accuracy would cost

nearly $7,000 more per life-year saved

than what could otherwise have been

achieved.

■ Disease Prevalence-- Lower prevalence

■

rates have minimal effect. This happens

Test Accuracy --Low estimates for ex- because the model depends for the most

pected rates of sensitivity and specificity part on prevalence rates only at initiaaffect the efficiency of the program tion of the screening program.

considerably. With the low assumptions, ■ Disease Incidence and Progression--The

comparing a 3-year screening schedule model is much more sensitive to as-
Costs and Effectiveness of Cervical Cancer Screening • 47

sumptions regarding annual progression

probabilities (including the probability

of progressing from no disease to disease, that is, the incidence rate). The

“worst-case” assumptions of progression

probabilities result in a cost-effectiveness ratio of $11,971 per year of life

saved in going from no screening to a

3-year cycle. It is the sensitivity of the

model results to disease incidence and

progression that is responsible for a

large part of the much lower cost per

life-year saved of screening high-risk

women.

Disease Regression and Cure--Estimates

of low cure rates have a minimal effect

on the results. However, the high estimates of annual regression probabilities

raise the cost-effectiveness ratio substantially, with a rise to $8,851 for 3-

year screening.

Rate of Symptom Development--Assuming a lower rate of symptom development in early and late invasive cancer

has minimal effect on cost-effectiveness

ratios.

Conclusions

The cost-effectiveness model employed

here examined the question: Given that a

woman, beginning at age 65, gets screened

for cervical cancer, what is the relative cost

effectiveness of different screening schedules? The model found that, under base-case

assumptions (5-percent discount rate), the

lowest cost per life-year saved for screening

elderly women is obtained with an every 5-

year screening frequency, which costs $1,453

per life-year saved. The incremental cost per

year of life saved is progressively greater as

screening frequency increases, amounting to

$5,956 per life year for a 3-year screening

cycle (compared to a 5-year cycle) and rising

to $39,693 for annual screening. These costeffectiveness ratios are comparable to other

preventive health services for the elderly that

have been legislatively mandated, such as the

vaccine used to prevent pneumococcal

pneumonia and mammography to prevent

breast cancer (136,155,156).

It is likely that these findings underestimate somewhat the true cost per lifeyear saved of screening elderly women. The

model assumes a constant probability of

moving from one state to another during any

given time period, which probably leads to an

overestimation of screening benefits. In

reality, tumors progress at varying speeds.

Since screening programs are more likely to

detect slow-growing tumors than fastgrowing ones, g

and since slow-growing

tumors are presumably less likely than fastgrowing ones to be fatal, the real benefits of

screening are probably not as great as those

predicted by this model.

Comparing some of the implications of

this model to the estimates of other researchers does indeed suggest that this model overestimates the effectiveness of screening, although not dramatically so. The lifetime incidence of cervical cancer that this model

predicts under the base case is about 3.5 percent for elderly women receiving no screening and about 1.4 percent for elderly women

being screened every 3 years. Some other researchers, using data from the National Cancer Institute’s database, have estimated a

lifetime incidence for elderly women of less

than 1 percent under existing screening conditions (where only one-half of elderly

women have been screened within 5 years)

(128). An overestimate in this model of the

total lifetime likelihood of developing cancer

would lead to a corresponding overestimate of

lives saved from screening.

Results from the model suggest that the

cost per life-year saved for high-risk women

who receive screening is quite low (about

$1,000 for annual screening and cost-saving

for less frequent schedules), while the costeffectiveness ratio for low-risk women is

substantially higher (even for one-time

screening). These results have major implications for any generalized screening program.

For any given age group, the lowest-risk

women have generally had the highest utiliza9 See discussion of length bias (ch. 2., box C).
48 • Costs and Effectiveness of Cervical Cancer Screening

tion of Pap smear screening programs. If this

experience holds true for elderly women as a

group, the cost per life-year saved is likely to

be highest if the implementation of the

benefit does not change the mix of women

receiving Pap smears (i. e., mostly low-risk

women being screened). If the proportion of

screened women who are high-risk increases,

the cost per life-year saved will decline,

making the program more cost-effective.

Thus, investing in outreach to increase

utilization by high-risk women could reduce

the incremental cost per year of life saved.

(Total costs could even decrease if all

screened women are high-risk, since for this

group screening actually saves costs at 3- and

5-year screening frequencies.)

The cost-effectiveness model presented

here is very sensitive to the accuracy of the

Pap smear and certain assumptions about the

natural history of disease. Estimates of lower

and upper bounds for the cost-effectiveness

ratios, incorporating these and other factors,

are provided by the “favorable” and “unfavorable” sensitivity analyses that incorporate

the high- and low-probability estimates that

as a group are most favorable and least favorable to screening. The results of these

scenarios imply that, under very optimistic

assumptions, screening could pay for itself;

under pessimistic assumptions, screening

yields a positive benefit, but only at relatively high cost.

Considerable uncertainty regarding the

epidemiology of cervical cancer in elderly

women still exists, even about things so basic

as whether the known risk factors predict risk

in elderly women to the same extent as in

younger women. Additionally, less is known

about the natural history of the disease in the

elderly than in younger populations. If the

development of human papilloma virus (HPV)

typing technology proves to predict cancerous

outcomes more accurately than the Pap test

alone, it will be particularly important to

study the prevalence and predictive value of

HPV infection in elderly women.

IMPLICATIONS FOR MEDICARE

Coverage Considerations

As of July 1, 1990, Medicare will pay

for Pap smear screening tests up to every 3

years. More frequent screening of high-risk

women is permitted under the law at the discretion of the Secretary of the Department of

Health and Human Services (DHHS).

Medicare has always paid a proportion of

the costs of cervical cancer. With no screening, under the baseline assumptions of the

model used here, the lifetime financial costs

of diagnosis, treatment, and followup of cervical cancer are estimated to average $218 per

65-year-old woman (in present dollars).

With Medicare coverage of Pap smear

screening, costs to the program will almost

certainly increase. The amount of increase

(and the realized benefit) depends on: 1) the

frequency of screening covered by the program, and 2) the extent to which beneficiaries utilize the service.

The frequency of the benefit is fundamental to a coverage decision. The costeffectiveness analysis presented here does not

have a “most” cost-effective solution, since

additional benefits continue to accrue at each

more frequent screening level, but it is

generally consistent with the recently enacted

benefit. The rapid rise in cost per life-year

saved when screening frequency is increased

from every 3 years to annually (in the

baseline case) makes annual screening slightly

more difficult to justify than less frequent

screening for the overall elderly population.

For high-risk women, however, even annual

screening yields substantial benefits at modest

cost per life-year gained. (In contrast, for

low-risk women, very frequent screening

yields virtually no incremental benefits over

less frequent screening.)
Costs and Effectiveness of Cervical Cancer Screening ■ 49

Two different approaches are theoretically available to consider the different needs

and potential benefits for women at different

levels of risk of developing cervical cancer.

The first approach is to set a Medicare

benefit for which all elderly women are

eligible, leaving it to each woman and her

physician to determine the most appropriate

actual screening strategy for that woman.

This approach could be supplemented with

outreach programs targeted towards high-risk

women, since these women are less likely to

participate otherwise but reap the greatest

benefit from screening. Outreach in this case

could range from educational programs to

direct financial incentives, such as free

screening at public health clinics.

A second approach is to differentiate in

a Medicare benefit itself between high- and

low-risk women, through a proxy of risk.

One potential proxy of risk is a record of

previous screening; thus, for example,

Medicare might pay for screening at some

specified frequency, but only until a woman

had a Medicare-documented history of

screening (e.g., up to a maximum of 3 tests).

A second potential proxy of risk is evidence

of low income; thus, Medicare might differentiate between women who are and are not

dually eligible for Medicare and Medicaid

when providing benefits. Medicare might

pay for both the visit and the screening test

for women who are also Medicaid-eligible,

for example, but pay only for the test itself

for other women. These two proxies --

number of previous screens under Medicare

and eligibility for other programs, such as

Medicaid or Supplemental Security Income--

could be combined in various ways as well.

The existing new law combines elements

of both approaches. A general benefit is set

by law, but the law empowers DHHS to provide differential benefits to high- and lowrisk women. Whether DHHS acts on this option may depend in part on the administrative

difficulty of a differential benefit. Administrative concerns are not trivial; any new

benefit for which eligibility depends on factors such as time since last screen, total number of past screens, and eligibility for other

non-Medicare programs can rapidly become

very complex and costly to administer. Minimizing the number of different factors on

which the benefit depends would reduce this

potential problem.

Quality and Reimbursement

Considerations

The relative costs and effectiveness of

Pap smear screening depend on the accuracy

of the test as it is performed and evaluated in

10 Fewer false Positive s

everyday practice.

mean fewer unnecessary followup procedures;

fewer false negatives mean fewer women

diagnosed during the later stages of invasive

cancer, when treatment costs are greatest and

cure rates lowest. Improved accuracy may

raise some costs, too, since more women with

the disease (including those with CIN and

CIS) will be diagnosed and treated.

Measures to improve Pap smear accuracy,

and particularly those to improve the quality

of cytologic evaluation, have their own costs.

To make evaluation more accurate, for example,

such

■

■

■

■

a laboratory might implement strategies

as:

monitoring/testing programs to evaluate

the proficiency of cytotechnologists,

requiring cytotechnologists or pathologists to re-evaluate a proportion of negative slides,

limiting the number of slides per day

cytotechnologists can examine, and

continuing education programs for

cytotechnologists.

All of these strategies have been considered in the current debate of how to improve

laboratory accuracy. In 1988, for example,

10 A recent study of laboratory accuracy suggest s

that there is considerable room for improvement .

Eight of eighteen laboratories surveyed by th e

American Society of Cytotechnology were found to

have critical deficiencies in their cytology operations (171 ).
50 • Costs and Effectiveness of Cervical Cancer Screening

the Health Care Financing Administration

proposed a set of requirements, including

many of these features, that laboratories must

meet in order to qualify for Medicare reimbursement (53 FR 29591). The proposal

would also require that laboratory reports to

physicians identify inadequate smears, employ

detailed descriptions of abnormal smears, and

include followup recommendations.

Whether voluntary or mandated, such

strategies would likely raise provider costs,

which in turn would probably raise the cost

of screening to Medicare. This investment

would likely improve the cost-effectiveness

of screening, although it would raise overall

program costs. (Note that it is not absolutely

certain that implementation of these strategies

would raise costs; e.g., a laboratory beset with

costly lawsuits as a consequence of errors

might conceivably see a net saving as a consequence of implementing quality-improving

strategies.)

Some conflicts may arise between

Medicare efforts to improve accuracy of Pap

smears and the Medicare reimbursement

structure. At present, reimbursement is

structured to reward quantity rather than

quality; laboratories (or physicians) are paid a

set fee per smear, and laboratories reap the

greatest profit by encouraging their cytotechnologists to process a maximum number of

smears per day. Under this system, fear of

medical liability lawsuits and physician dissatisfaction are the only counteracting pressures to improve quality. Strategies to improve evaluation accuracy might require raising Medicare reimbursement rates per smear

if the current reimbursement structure were

maintained.

Resource Considerations

Medicare coverage of routine Pap smear

screening would almost certainly increase the

utilization of the test and require more

laboratory services to evaluate the additional

smears. However, a perceived shortage of

cytotechnologists already exists (163). Market

responses to increased demand for cytotechnology services, such as raising salaries to

draw people into the profession, would probably raise screening costs to Medicare. If

Medicare reimbursement rates did not rise, an

alternative result would likely be long lag

times between sampling and evaluation, with

consequent delays in diagnosis for women

with positive tests.

Strategies to improve the quality of Pap

smear evaluation have additional implications

for the availability of services. Limiting the

number of slides per day that cytotechnologists could evaluate would increase

evaluation time per slide, presumably improving accuracy, but it would also increase

the need for cytotechnologists. Again, increased screening costs to Medicare would

probably result.

Automated cytologic evaluation of Pap

smears might reduce the number of cytologists needed, easing the perceived shortage

of these professionals. Such technology is

under investigation (149), but its accuracy

compared to manual cytologic evaluations is

not yet established.
Appendix A: Advisory PaneI

Gordon De Friese, Panel Chair

Health Services Research Center

University of North Carolina, Chapel Hill, NC

Marianne C. Fahs

Department of Health Economics

Mt. Sinai Medical Center

New York, NY

John Frank

Department of Preventive Medicine &

Biostatistics

University of Toronto

Ontario, Canada

Gary D. Friedman

Epidemiology and Biostatistics Division

Permanence Medical Group, Inc.

Oakland, CA

Lawrence Gottlieb

Clinical Guidelines Program

Harvard Community Health Plan

Brookline Village, MA

Mary Knapp

John Whitman and Associates

Philadelphia, PA

Risa Lavizzo-Mourey

Geriatrics Program

University of Pennsylvania

Philadelphia, PA

M. Cristina Leske

Department of Preventive Medicine

State University of New York

Stony Brook, NY

Donald Logsdon

Woodhull Medical & Mental Health Center

Brooklyn, NY

Mildred B. McCauley

American Association of

Retired Persons

Washington, DC

Peter McMenamin

Chevy Chase, MD

Meredith Minkler

Center on Aging

University of California, Berkeley

Berkeley, CA

Marilyn Moon

Public Policy Institute

American Association of Retired Persons

Washington, DC

George Morley

Department of Obstetrics/Gynecology

University of Michigan Medical Center

Ann Arbor, MI

Gilbert Omenn

School of Public Health &

Community Medicine

University of Washington

Seattle, WA

George Pickett

Department of Public Health Policy

School of Public Health

University of Michigan

Ann Arbor, MI

Donald Shepard

Department of Health Policy

and Management

Harvard School of Public Health

Boston, MA

Barry Stults

Division of General Internal Medicine

University of Utah Medical Center

Salt Lake City, UT

Advisory Panel members provide valuable guidance during the preparation of OTA reports.

However, the presence of an individual on the Advisory Panel does not mean that individual

necessarily agrees with or endorses the conclusions of this particular paper.

51
Appendix B: Acknowledgments

The OTA staff would like to express our appreciation of the following people for their

valuable guidance. This acknowledgment should not be construed in any way to imply that the

individuals agree with or endorse the conclusions of this paper.

John Boyce

State University of New York

Health Science Center

Brooklyn, NY

William F. Bridgers

University of Alabama

Birmingham, AL

Martin Brown

National Institutes of Health

Bethesda, MD

Cathy Cohen

American Society of Clinical Pathologists

Washington, DC

William T. Creasman

Medical University of South Carolina

Charleston, SC

Peter Dattino

Mount Sinai School of Medicine

New York, NY

James DeLozier

National Center for Health Statistics

Hyattsville, MD

David Eddy

Jackson, WY

J. Michael Fitzmaurice

National Center for Health Services

Research

Rockville, MD

Robert Fried

University of Colorado School of Medicine

Denver, CO

Harvey W. Friedman

Empire Blue Cross/Blue Shield

New York, NY

Rachel Fruchter

State University of New York

Health Science Center

Brooklyn, NY

Michael Gluck

Johns Hopkins University

Baltimore, MD

Robert Kane

University of Minnesota

Minneapolis, MN

Larry Kessler

National Cancer Institute

Bethesda, MD

Samuel P. Korper

National Institute on Aging

Bethesda, MD

Leopold Koss

Montefiore Medical Center

Bronx, NY

Lewis Kuller

University of Pittsburgh

Pittsburgh, PA

Herman Lehman

University of Alabama

Birmingham, AL

Michael McMullan

Health Care Financing Administration

Baltimore, MD

Anthony B. Miller

University of Toronto

Toronto, Ontario, Canada

Mary Moien

National Center for Health Statistics

Hyattsville, MD

52
Costs and Effectiveness of Cervical Cancer Screening • 53

Philip Prorock William Sobaski

National Cancer Institute Health Care Financing Administration

Bethesda, MD Baltimore, MD

Ralph Richart

Columbia-Presbyterian Medical Center

New York, NY

Seymour Romney

Albert Einstein School of Medicine

Bronx, NY

Klaus Schreiber

Montefiore Medical Center

Bronx, NY

Jane Scott

National Center for Health Services

Research

Rockville, MD

Alex Sedlis

State University of New York

Health Science Center

Brooklyn, NY

Michael Shwartz

Boston University

Boston, MA

Fred Sillman

State University of New York

Health Science Center

Brooklyn, NY

Charles Smart

National Cancer Institute

Bethesda, MD

Katharine Bauer Sommers

Institute of Medicine

Washington, DC

Evelyn Talbott

University of Pittsburgh

Pittsburgh, PA

William Taylor

Centers for Disease Control

Atlanta, GA

Sten Vermund

Albert Einstein School

of Medicine

Bronx, NY

Carolyn Westoff

Columbia-Presbyterian Medical Center

New York, NY

T. Franklin Williams

National Institute on Aging

Bethesda, MD

Steven H. Woolf

Office of Disease Prevention

and Health Promotion

Washington, DC
Appendix C: Expert Panel

Although the literature on cervical cancer

is voluminous, information on this disease as

it specifically relates to elderly women is

scarce. To supplement the literature review

that formed the basis of this paper and the

assumptions used in the cost-effectiveness

model, the contractors convened a small panel

of experts to discuss the literature and to

elicit information based on the clinical experience of these experts. The panel, consisting

of epidemiologists, pathologists, and gynecologic oncologists, focused primarily on three

areas:

■ the duration of the various states of cervical neoplasia,

■ the probability of progression or regression from each of the preinvasive states,

and

■ diagnostic and treatment protocols for

each state.

Other factors that might affect the yield of

screening in elderly women, such as characteristics of the Pap test in this age group,

utilization of screening age-specific rates of

disease, and cohort effects, were also discussed.

Prior to the meeting, each expert was

furnished with a synopsis of the relevant literature and was asked to fill out a questionnaire based on his or her interpretation of

that literature and personal clinical experience. The panel then met for 3 hours and

discussed their initial responses to the

questionnaire, after which each expert again

independently filled out the same questionnaire. The discussion emphasized identifying

a reasonable range for model assumptions and

did not specifically attempt to come to consensus on any issue. A list of participants

follows.

John Boyce, MD

Health Science Center

State University of New York

Brooklyn, NY

Peter Dattino, MD

Mount Sinai School of Medicine

New York, NY

Rachel Fruchter, PhD, MPH

Health Science Center

State University of New York

Brooklyn, NY

Leopold Koss, MD

Montefiore Medical Center

Bronx, NY

Ralph Richart, MD

Columbia-Presbyterian Medical Center

New York, NY

List of Participants

Seymour Romney, MD

Albert Einstein School of Medicine

Bronx, NY

Klaus Schreiber, MD

Montefiore Medical Center

Bronx, NY

Alex Sedlis, MD

Health Science Center

State University of New York

Brooklyn, NY

Sten Vermund, MD, PhD

Albert Einstein School of Medicine

Bronx, NY

Carolyn Westoff, MD, PhD

Columbia-Presbyterian Medical Center

New York, NY

54
Appendix D: Review of Estimates of Progression

Probabilities and Duration of States

of Cervical Neoplasia

This appendix discusses the major studies

yielding estimates of the duration of the various states of cervical neoplasia, the probability of progressing from one state to the next,

and the probability of regressing to a previous state. The studies are summarized in

chapter 2(tables 4, 5, and 6).

Duration of States of Cervical

Neoplasia

The first major study of the natural history of cervical neoplasia in the medical literature is that of Petersen (107), in which a

number of women with a diagnosis of cervical intraepithelial neoplasia (CIN) were followed without intervention for a number of

years. The researchers observed that the

average duration of carcinoma in situ (CIS) in

these women was 3.7 years, with the time

from onset of CIS to onset of invasive cancer

ranging from less than 1 year to nearly 9

years in individual women.

Withholding treatment from women diagnosed with CIN rapidly became unacceptable,

so subsequent researchers have attempted to

estimate the duration of the states of cervical

neoplasia in various other ways. One method

has been to assume that the process of cervical cancer can be approximated by a Markov

process, a type of model that uses a given set

of probabilities to relate one state to the next

(app. E). Observable variables can be used as

inputs to such a model and used to estimate

the durations of the various states. A

homogeneous model assumes the same transition probabilities for all age groups; a nonhomogeneous model allows the probabilities

to vary depending on the group to which they

apply.

Barron and Richart used a homogeneous

Markov process to assess the duration of CIN

using two very different data sets (7,8,9).

The first of these was a prospective followup

of 557 women in Virginia and New York

with known CIN, whose diagnosis was based

on 3 successive abnormal Pap smears. Women

in the study were followed every 1 to 4

months without intervention if their status

was unchanged. The researchers attempted to

minimize diagnostic errors by using clearly

delineated diagnostic criteria, requiring three

smears with CIN for admission to the study,

and reviewing smears for reliability and accuracy. Accordingly, the inter-reade r

reliability in classifying smears was 95 percent, and the Pap smear diagnoses agreed

with the colposcopic and ultimate histological

diagnoses. Some important information about

the sample is not presented in the published

accounts: the distribution by age and race of

study participants, the comparative characteristics of women who participated and those

who refused participation, and the profile of

all women with abnormal smears in the institutions studied. The authors found no evidence that transition from one state to another was age-related, but few older women

were represented in the sample (the median

age was 26, and the maximum age was 65)

(8). The median duration of CIN (including

severe dysplasia) derived from this population

was 3.7 years; the mean duration was 5.7

years (l14).

The second population that Barron and

Richart used to estimate duration of CIN was

a sample of 11,814 previously unscreened

asymptomatic women iiving in Barbados,

West Indies, who attended family planning

clinics between 1965 and 1968 (9). The

sample included 171 women aged 60 to 64.

55
56 • Costs and Effectiveness of Cervical Cancer Screening

However, the model only used prevalence

data from women aged 20 to 39 to determine

the duration of CIN. The resulting estimates

were similar to those yielded by the original

model. Although this study is based on a

population that probably differs from the

general U.S. population in risk of cervical

neoplasia, the consistency of results between

the two studies supports the validity of these

researchers’ estimates.

In contrast, Coppleson and Brown (32)

attempted to demonstrate that the results of a

homogeneous Markov model, which assumes

that transition probabilities are independent

of age, did not fit observed data. They used

data collected by Bibbo et al. and agespecific incidence rates for invasive cervical

cancer from the Third National Cancer Survey for their estimates, and they used a nonhomogeneous Markov model to simulate a

process that would yield these real-world

results.

The published data used by Coppleson

and Brown had some limitations. Bibbo et

al.’s series was based on 148,735 women attending the University of Chicago and

Planned Parenthood clinics (16). Most of the

women were young; only 12 percent of the

sample was over age 49. The mean age of

this subsample of 17,133 women was given as

65, but no information on the actual age distribution was published. For their model,

Coppleson and Brown assumed all of these

women to be the average age-- i.e., 65.

Based on their models, Coppleson and

Brown estimated the average duration of CIS

to be 17 years in women under 65 and 4

years in women aged 65 and over ( 132).

Their findings are valuable because the researchers expressly examined the possibility

of differences between age groups, and they

concluded that a real difference in the behavior of the disease probably does exist.

However, there are several caveats to their

findings. Their assumption that all women

over 49 were age 65 may invalidate their

conclusions for older women, since even if

the average age of this group were 65, using

the actual distribution of ages would give

different results from assuming that a l l

women were age 65. The effect of this assumption is probably to underestimate the

duration of disease states in older women. In

addition, several of the assumptions made to

fit the model to observed data are at variance

with many other researchers’ beliefs about the

natural history of the disease. For example,

Coppleson and Brown assumed that CIN prior

to CIS (i.e., dysplasia) was a transient condition, lasting less than one year, and that CIS

regressed to normal in a large proportion of

cases. In summary, while it may be true that

a homogeneous model does not fit the observed natural history of the disease, this

analysis does not resolve the issue.

Dunn (40) and Kashgarian and Dunn (69)

drew upon the relationship betwee n

prevalence and incidence to estimate the

duration of a given state of cervica l

neoplasia. In his paper, Dunn (4 O) divided

the sum of all age-specific prevalence rates

for a given state by the sum of all agespecific incidence rates for that state to

derive the duration of the state. Kashgarian

and Dunn (69) used an equivalent method

that did not depend on pre-determined age

ranges over which age-specific rates were

calculated. They estimated duration by first

graphing the incidence of each state (CIS,

preclinical invasive cancer, and clinical invasive cancer), with age along the bottom axis

of the graph. They then estimated the area

under the graph between given ages for CIS.

Next, they calculated the age at which the

graph of the incidence of preclinical invasive

cancer had an area under it equivalent to the

area under the defined CIS age interval. The

duration of CIS was then presumed to be the

difference between this age and the upper

limit of the specified CIS age range.

The analyses of these researchers used

data for 110,000 white women screened in

Memphis (40) and 106,000 person-years of

observation of white women and an unspecified number of black women from
Costs and Effectiveness of Cervical Cancer Screening • 57

Memphis and Shelby counties, Tennessee (69).

In both of these samples women aged 20 to

39 were over-represented and women aged 55

to 74 were under-represented. Incidence

rates were determined from the result of the

third screening test. The literature reports

did not specify diagnostic criteria for cytology, although most smears were read at one

university laboratory. The authors concluded

that older women and black women had

shorter durations of CIS than other women.

Their estimates for black and white women

were 8.5 and 10.7 years, respectively (69).

For white women, they estimated the duration of CIS to be between 5 and 16 years for

young women and to be 1 year for women

aged 65 and over (69).

Difficulties in true ascertainment of a

particular disease state due to cytology and

misclassification may affect the accuracy of

estimates of duration derived in this manner.

In addition, estimates derived from this formulation will only be correct if the incidence

and prevalence rates over the time of

measurement are constant and if both are

measured from the same state in the disease

process. If prevalence rates are increasing or

if screening rates differ, these conditions may

not hold true. Also, these types of estimates

assume similar population mortality rates for

women at all ages. For elderly women, who

have higher mortality rates than younger

women, this assumption may underestimate

the true duration of cervical neoplasia.

However, other authors, using similar

methods applied to different data sets, have

derived estimates of duration that are similar

to those of Kashgarian and Dunn, arguing for

the validity of this method. Barron et al. applied this method to two data sets: 1) the incidence and prevalence of CIS in British

Columbia, Canada, and 2) the prevalence of

CIS in Barbados, West Indies. They examined

these two sets of data in two ways: first by

using the simple relationship between

prevalence and incidence described above,

and second by examining the equivalent areas

under the curves on graphs of the incidence

of each stage at each age. They concluded

that the duration of CIS is an age -

independent variable with upper and lower

limits of 3 to 10 years, respectively(7).

Fidler et al. likewise estimated the duration of CIS in two ways: 1) from the relationship between observed prevalence and incidence among women participating in the

British Columbia screening program, and 2)

from the difference in mean ages of incidence of CIS and preclinical invasive cancer

in this population (46). Age-specific rates

were presented for this series, but the number of elderly women was small, yielding

estimates with a wide range of error. In

1966, 22 percent of the female population in

British Columbia was age 60 or over, but this

age group represented only 8.5 percent of

women screened (46). The estimate of the

duration of CIS using the first method is between 6 and 9.5 years, compared to 12 years

using the second method.

Another method of estimating the duration of neoplasia is to determine the modal

age-specific incidence rates (the modal number of cases per age group). The Canadian

Task Force presented such estimates using

data from the British Columbian population

(22). As with the data used by most other

researchers, these data are cross-sectional and

may obscure differences among cohorts.

Also, estimates obtained as a result of subtracting modal, or even mean, ages of incidence only yield a correct estimate if the

durations of all states being considered are

equal. This is not likely to be true since the

probability of ascertainment is a function of

the duration of the lesion (7). The estimates

derived in this manner agree the least with

estimates from other methodologies, and they

are most likely overestimates.

The uncertainties about the duration of

cervical neoplasia in elderly women arise

primarily from the lack of data on women in

this age group. The critical question in assessing the duration of each state of cervical

neoplasia is whether the duration of disease
58 • Costs and Effectiveness of Cervical Cancer Screening

is, or is not, dependent on age. Although

Coppleson and Brown’s analysis suggested

that duration of different states was indeed

different in the elderly than in the younger

population, there is still little direct evidence

to support or refute this hypothesis. The

hypothesis is biologically plausible based on

current knowledge of the interactions between age and hormonal and immune factors

(see ch.2}

Probability of Progression

Regression of Each State

The probabilities of remaining

state, progressing to the next

and

in a given

state, or

regressing to the prior state are difficult to

determine for cervical cancer. The best

estimates of early disease are based on groups

of women with CIN and CISl who were followed without intervention. In one such

series, Barron and Richart followed 557

women with CIN (8) and collected data on

the distributions of grades of CIN after the

initial and two followup exams. Using a

Markov model with these data as inputs, the

authors estimated that after 10 years 66 percent of all CIN lesions will progress to CIS,

28 percent will remain in CIN, and 6 percent

will revert to normal. Regression to normal

only occurred from very mild or mild CIN,

and the overall probability of progression to

CIS increased with the severity of dysplasia

(8}

In contrast, Fox (48) followed 278

women with CIN and noted that 31 percent

regressed to normal, 9 percent remained in

CIN, and 60 percent progressed to CIS. This

1 As noted in ch. 2, CIN as used in this report

include mild and moderate dysplasia; CIS generall y

includes CIS and severe dysplasia, because thes e

latter two conditions are hard to distinguish .

Barren and Richart, however, specifically attempted

to separate different levels of dysplasia and CIS.

In the discussion of their studies, CIN include s

severe dysplasia ; CIS includes only carcinoma in

situ .

—

high regression rate may be due in part to

misclassification, as only one smear interpreted as CIN was necessary for inclusion in

the study; several women ‘regressed” after

termination of pregnancy or completion of

anti-infection treatment. In addition, 13 percent of the women whose smears originally

returned to normal subsequently developed

CIN.

The “re-development” of CIN after

regression to normal has been noted in other

series as well (147). In fact, in one series,

among women over age 45 whose initial CIN

lesions ‘regressed,” 40 percent recurred (147).

All these factors suggest that estimates of the

regression rate of CIN have often been overstated, due to misclassification biases. In

contrast, three smears interpreted as CIN

were necessary for inclusion in Barron and

Richart’s series, which should minimize this

type of bias.

A Swedish study of 894 women age 15 to

72 with CIN, who were followed for an average of over 4 years, found that 54 percent of

lesions regressed, 16 percent persisted and 30

percent progressed (lOO). A number of

patients with “persisting CIN” in this study

had periods of normal smears for more than

12 months before being rediagnosed as having

CIN.

Evidence on the relationship between

regression rates and age is mixed. One study

noted a lower regression rate for older than

for younger women. In this study, women

under age 45 with CIN had a regression rate

of 38 percent per year, compared to 29 percent per year for women age 45 and over

(147). Another study, however, found that

fewer lesions progressed, and more regressed,

in older women than in young women (100).

The difference in rates of regression

noted in nonbiopsy studies compared to

biopsy studies suggests that the act of establishing the diagnosis can produce a cure, and

that the act of measurement often alters the

results (8). Nasiell and colleagues (100)
Costs and Effectiveness of Cervical Cancer Screening • 59

found that significantly more biopsied than

nonbiopsied lesions disappeared during followup (50 v. 57 percent), and fewer biopsied

lesions progressed (25 v. 27 percent). Thus,

different biopsy rates may be one reason

studies report varying results. In addition,

nonuniformity of diagnostic criteria and observer variability contribute to the wide range

of reported probabilities.

Confounding these difficulties i n

determining the “true” course of cervical

neoplasia in elderly women is the lack of

age-specific observational data. The main

source of findings regarding age-specific information is the research of Coppleson and

Brown, which found that an age-dependent

model of disease progression fit actual incidence and prevalence data best (32). The

researchers concluded that there is no regression from the state of CIS and that the probability of disease progression from CIS to invasive cancer increases with age. For CIN,

the probability of progression did not vary

with age in their model. As discussed above,

however, their conclusions have some uncertainties due to limitations of the underlying data. Also, the older women in their data

set had lower screening rates than young

women, which may have resulted in older

women being detected at the end of a given

state more often than younger women. This

could bias the model to predict a higher

probability of disease progression in the

elderly. Still, as with the duration of disease

states, a higher probability of disease progression is biologically plausible in older

women.
Appendix E: Markov Modelsl

A Markov model describes the movements of members of a population through a

set of states. A simple Markov model requires only two sets of information:

the distribution of the population among

the defined states at the initiation of the

model; and

for each state, the probability that any

individual in that state will move into a

different state (transition probabilities).

In a simple Markov model, these probabilities remain the same with each

iteration of the model. In the Markov

model used in chapter 3, some probabilities change with successive iterations

(e.g., the probability that women will

die increases as the cohort grows older).

rhe transition probabilities can be

portrayed in a matrix. For example, imagine

a Markov model in which two states exist:

healthy and cancer. Assume that in any

given period, the chance of a healthy person

getting cancer is 10 percent, and the chance

of remaining healthy is 90 percent. For

people with cancer, the chance of being

cured (becoming healthy) during this period

is 50 percent, and the probability of continuing to have cancer is also 50 percent. This

situation is summarized in the following

matrix:

Period 2

Healthy Cancer

Period I

Healthy 0. 9 0.1

Cancer . 0.5

Now, assume that there are 100 people in

the population, and that initially (at the beginning of the model) 90 are healthy and 10

have cancer. Applying the above probabil1 The information in this appendix is drawn from E.

Stokey and R. Zeckhauser, A primer for policy

Analysis (New York: W.W. Norton & Co., 1978).

ities, the distribution of the population after

one iteration of the model--i. e., in period 2--

would be:

Healthy: (90 x 0.9) + (lo x 0.5) =

81 + 5 = 86 people

Cancer: (90 x 0.1) + (lo x 0.5) =

9+5 = 14 people

In this simple example, applying the

transition probabilities successively to the

population distribution from each previous

iteration of the model, the population soon

reaches a stable distribution:

Percent of Period

population that: 1234 5

Is healthy . . . . . . . . . . . 90 86 84 84 84

Has cancer . . . . . . . . . 10 14 16 16 16

(In the model used in chapter 3, the population is artificially required to be stable by

imposing the requirement that all women still

alive at age 109 die in that iteration of the

model (before reaching age 110).)

Markov models rely on certain assumptions that affect their application. Most important for the model applied in chapter 3 is

that the probability that an individual will

move into a different state depends only on

her present state. A simple Markov model

has no memory; a person’s chance of having

cancer in the next period in the example

above depends only on his or her health in

the current period. Also, the model can be

applied only where there are mutually exclusive and exhaustive categories; an individual

cannot be represented in two categories at

once.

The conditions of Pap smear screening

for elderly women are generally amenable to

simulation with a Markov model. In the

model used in the cost-effectiveness analysis

(ch. 3), states of health are defined to be

mutually exclusive and exhaustive as they relate to cervical cancer. The initial population

60
Costs and Effectiveness of Cervical Cancer Screening • 61

distribution for the model is the existing The most troublesome aspect of Markov

prevalence of disease; the transition probabil- modeling for cervical cancer screening is the

ities are mortality rates and rates for identifi- assumption that the transition probabilities

cation, progression, regression, and cure of are the same for all individuals in each state.

disease. The purpose of the model as applied Some of the implications of this underlying

here is not to define a stable population dis- assumption are discussed in the text.

tribution, but to track the costs and cases of

cervical cancer through the lifetime of the

defined cohort of women.
Appendix F: Basis for Input Assumptions and

Calculation of Cost Components in the

Cost-Effectiveness Model

Data Input Assumptions

For the cost-effectiveness model employed in chapter 3, several methods were

used to choose base, high, and low estimates,

Typically, after exclusion of irrelevant and

seriously flawed studies, only a few studies

remained. Where a single study was clearly

more applicable to the elderly population than

other studies, it was used as the base case; in

other cases, the base case was derived from a

study whose results were in the middle of the

range of study findings available. For low

and high estimates, the lowest and highest

values from available studies were generally

used. In some cases where a single study

served as the base case, computed 95 percent

confidence limits served as the extremes.

Where no applicable studies are available at

all, assumptions were based on the opinions

of the expert panel (see app. C).

The sources and rationale for the individual estimates used in the model and presented in table 11 (ch. 3) are discussed in

detail below.

Initial Conditions

■

62

Cervical intraepithelial neoplasia (CIN--

grades 1 and 2): Most initial conditions

for CIN and carcinoma in situ are drawn

directly from results in studies published

in the literature. The prevalence of CIN

at age 64 in the base case is drawn from

Stern’s study of women in a Los Angeles

clinic (146), the more recent of the two

large reported studies of dysplasi a

prevalence in this age group. The less

recent study, which reported lowe r

prevalence, was used directly as the source

for the low estimate and indirectly as the

source of the high estimate (the high

estimate was the upper bound of the 95

percent confidence interval around the

reported figure) (145).

■ Carcinoma in situ (CIS)/severe dysplasia:

Two studies are reported in the literature

that measured the prevalence of CIS in

older women and whose results are applicable to the initiation of the model.

The base-case prevalence is drawn from a

study of British Columbian women (46),

the study with the largest reported sample

of women in this age group tha t

measured this parameter. This figure was

also used as the low estimate. The high

estimate is drawn from the second study,

which reported a substantially higher

prevalence (40).

■ Early and late invasive cervical cancer

(EICC, LICC): The prevalence of EICC

and LICC are not reported in the literature in the way those terms are defined

for the model. For this model, the

reported overall prevalence of invasive

cancer was combined with the reported

fractions of cancers in the early or late

stages to produce a stage-specifi c

prevalence at the initiation of the model.

Base and high estimates of the prevalence

of invasive cancer are drawn from Dunn

(42); low estimates are drawn from

Mandelblatt et al. (92). Stage distributions

of cancer at presentation are drawn from

Fidler et al. (46) for the base case, Dickinson et al. (37) for the high estimate, and

from data from the National Cancer Institute’s Surveillance, Epidemiology, and

End Results (SEER)l database for the low

case (158).

Transition Probabilities

Death--Age-specific general population

mortality probabilities (164) are applied for

women in the healthy, CIN, and CIS states.

A weighted average of the race-specific figures for each age is used, reflecting the racial

1 The SEER data base includes results of a cancer

registry maintained in 9 different regions in th e

United States (16).
Costs and Effectiveness of Cervical Cancer Screening • 63

distribution of American women in 1980

(164). In the EICC and LICC states, mortality probabilities are taken from overall

age-group specific cancer survival data (including deaths from other causes among cancer patients) in the National Cancer Institute’s

SEER (1978-1984) database (158). A weighted average of race-specific rates was applied

to these mortality probabilities as well. Because the sources for these mortality probabilities are considered highly reliable, high

and low estimates for sensitivity analysis were

not made.

Progression Probabilities--The relationship of non-mortality transition probabilities to epidemiologic data is not straightforward, since standard epidemiologic statistics

(mean duration, median duration, survival

probability) do not always correspond directly

to the terms of the model. With some simple

assumptions and mathematical manipulation,

however, the available epidemiologic statistics

can be re-stated as annual probabilities of

transition from one stage of disease to the

next, the data items necessary for the model.2

Only age-dependent progression probabilities

(i.e., estimates derived from samples of older

women) are used, because the extreme high

and low assumptions bracket the available

age-independent progression probabilities.

2 Let p = annual transition probabi1ity, m = median

duration, x = mean duration, and Sn = n-year sur -

vival probability . Assume that the distribution of

transition times is exponential, and let r denot e

the rate constant of the exponential distribution.

Then:

p=l - exp( -r) (Eq. 1 )

m = (n 2 / r (Eq. 2 )

‘= I/ x r

(Eq. 3 )

S n = exp(-n x r) = 1 - (l-p )

n (Eq. 4 )

Equation 1, 2, 3, and 4 can be used to determine r,

depending on the statistics available, and the re -

quired probability, p, can then be calculated from

equation 1. Since only those who do not die can

undergo further state transitions, the actua l

transition probability used in the model is (l-f) x

p, where f is the mortality probability . ( For

further information about these equations and ex -

ponential survival distributions in medical prog -

nosis see Beck, Pauker & Kassirer (10). )

The base-case probability assumption for

the progression from healthy to CIN is drawn

from Stern (146), the only published study

found that reported information on the incidence of dysplasia specifically for elderly

women. Probabilities for progression to CIS

and to EICC are drawn from Coppleson and

Brown’s simulation analysis of screening in

elderly women (32).

High estimates of the incidence of CIN

and the annual rate of progression from CIN

to CIS are extrapolations from the base case,

since few alternative estimates exist. High

incidence of CIN is based on a 95 percent

upper confidence bound of the reported

estimate; high progression to CIS is calculated

as 50 percent greater than the base-case value

(since a confidence interval could not be applied to this estimate). The high estimate of

progression from CIS to EICC is derived

from the data presented by Kashgarian and

Dunn (69).

Low estimates of CIN incidence and

progression to CIS are derived from

preliminary data on women being screened in

British Columbia (96). These estimates are

lower than the estimates that would result

from extrapolations like those made to arrive

at high estimates, so they were considered a

more appropriate low assumption. The low

estimate for progression to EICC is drawn

from Dunn (42).

No published estimates are available on

the annual progression rate from EICC to

LICC. Consequently, the base, low, and high

estimates were all based on the opinions of

the expert panel (see app. C).

Regression or Cure --Women with CIN or

CIS may exhibit spontaneous regression to the

healthy state, but the rates of regression

reported in the literature vary enormously.

For the base case, the regression rate for CIN

of 38.1 per 1,000 women with disease

reported by Campion et al. (121) was used.

The high estimate (265.0) is drawn from

Robertson et al. (1 18), and the low estimate
64 ■ Costs and Effectiveness of Cervical Cancer Screening

(5.4) is drawn from Richart and Barron (1 14).

For regression of CIS, the base and low

estimates of zero were derived from the personal observations reported by members of

the expert panel (app. C). The high estimate

is drawn from Kinlen (71).

Women with recognized CIN and CIS

may revert to the healthy state subsequent to

treatment (cure). Cure is actually considered

slightly more likely for women with CIS than

women with CIN in the model, because it is

assumed that in actual practice women with

CIS receive more aggressive treatment, and

thus it is more likely that the entire lesion

will be removed with the initial treatment.

Assumptions of cure rates used in the model

are derived from conclusions of cure rates

from four sources: 1) the opinions and experiences of members of the expert panel (app.

C); 2) Creasman (34); 3) Shingleton and Orr

(130); and 4) Nelson et al. (102).

The situation for EICC and LICC is different. Although some women with EICC are

probably cured, data to estimate the probability of this are not available. This model

therefore does not permit transitions from the

invasive cancer states back to earlier stages.

Consequently, the model will overestimate

morbidity from invasive cancer; once a

woman moves into the EICC stage, she will

be categorized as having invasive cancer until

she dies. This does not affect her chance of

survival in the model, however. The death

probabilities are based on all-cause mortality

data in cohorts of women diagnosed in each

stage; thus, in the model, a woman’s statistical

likelihood of dying depends only on the fact

that she was diagnosed with EICC, not on the

fact that the model continues to classify her

in that category.

.

Recognition --Transition to a recognized

state results either from screening or from

diagnostic evaluation of symptoms.

The former possibility occurs only in

years for which screening is designated in the

program under study. Not all women will

avail themselves of the screening opportunity,

and among those who do, some women with

disease will have false-negative smears. The

overall transition probability is the product of

the survival probability, the utilization probability, and the stage-specific Pap smear

sensitivity.

Most Pap smear sensitivity results

reported in the literature are within the range

of 60 to 85 percent, with the majority of

these finding sensitivities of 80 to 85 percent.

One study reported very low sensitivity (35

percent) ( 122) and two studies reported

sensitivities of over 90 percent (14,1 14).

Most of these studies probably overstate realworld test accuracy, especially for elderly

women . The model thus uses a low

sensitivity estimate of 50 percent for all disease states (lower than that found in the bulk

of studies, but higher than the lowest

reported rate); it uses a base estimate of 75

percent for all disease states (within the range

of the bulk of studies, but in the lower part

of that range). The high-case estimate is in

the upper range of the bulk of studies; in the

high case, sensitivity is also permitted to be

higher for invasive cancer than for noninvasive neoplasia (82 and 80 percent, respectively). This possibility is suggested in the

results found by Boyes et al. (20) based on

screening in the British Columbian population.

Symptoms do not usually arise from CIN

or CIS. Invasive cancer, on the other hand,

eventually becomes symptomatic in most

cases. By combining the assumption that 80

percent of all women with late cancer who

have not yet developed symptoms will do so

within 1 year,3 with the estimates used for

the annual probability of progression from

early to late cancer, it is possible to approximate numerically what the annual hazard of

3 Although this 80 percent assumption is entirel y

arbitrary, the true rate is almost certainly ver y

h i gh. Also, changing this assumption makes virtually no difference to model results unless th e

nunber is very low.
Costs and Effectiveness of Cervical Cancer Screening • 65

developing symptoms with early cancer must

be to produce the observed distribution of

stages among diagnosed women. The results

of this calculation are used as the annual

probability of recognition of EICC due to

symptoms. High and low symptomaticity

rates combine high and low progression probability rates with the 80 percent assumption.

Clearance- - In this model, “clearance”

refers to the uncovering of false-positive Pap

smear results among healthy women, which

depends on the specificity of the Pap smear.

As with sensitivity, specificity results presented in the literature probably overstate

real-world test specificity for Pap smears

from elderly women. Three studies report

specificities of 99 percent or greater; one

study reports a specificity of slightly under

95 percent. The model thus uses 99 percent

as the high estimate of Pap smear specificity,

95 percent as the base-case estimate, and a

much lower rate- -87 percent--as a low

estimate that might obtain under conditions

of mediocre laboratory quality.

Cost Assumptions

The protocols of service described in

chapter 3 were applied in the costeffectiveness model to data from the National

Hospital Discharge Survey (NHDS) to identify

the in-hospital services used in each phase of

care for cases with abnormal findings (either

asymptomatic screened cases or symptomatic

cases presenting for care). The NHDS data

used included patients aged 65 and over who

were discharged between 1984 and 1987 with

a diagnosis of either malignant neoplasm of

the cervix or CIS. Length of stay, discharge

status, and surgical and non-surgical procedures coded from the face sheet of the medical record were printed out. Only those cases

with malignant neoplasm or CIS as the firstlisted diagnosis were used. The resulting set

of data on 210 women was used as an indicator of services received by patients with

diagnoses of invasive cervical cancer (ICC) in

different stages of disease, and with CIS, according to current practices.

The NHDS data showed that the basic

oncologic protocols for different stages of

disease could be approximately matched to

the service experience of admitted cases. The

cost estimates used in this analysis followed

the actual survey data with several modifications. The following describes features of

this set of calculations.

An assortment of pelvic surgical procedures

that were received by ICC and CIS patients

and interpreted to be related to the cancer

diagnosis (although, unlike cervical biopsy,

ionization, and hysterectomy, they were

not in the basic protocol) were included in

the inpatient care used in the cost estimation in chapter 3.

In early cancer, patients receiving total or

radical hysterectomies were considered to

have received the more expensive radical

(Wertheim) procedure that would constitute definitive treatment. CIS patients

with hysterectomies were considered to

have received the less expensive total

hysterectomy operation.

Bilateral salpingo-oophorectomy (removal

of both ovaries and fallopian tubes) was

not priced. It was usually coded in conjunction with a hysterectomy and was assumed to be included in the price of this

procedure. 4

Doses of chemotherapy or radiation therapy

were derived from lengths of stay for those

receiving these services.

Prices of services were derived as follows:

• Hospital costs were based on 1986

statistics published by the American

Hospital Association for all community

hospitals. The given average expense

per inpatient day was updated by applying the National Hospital Input

Price Index (provided by the Office of

4 Based on the experience of Enpire Blue Cross/Blue

Shield, the Medicare Part B carrier in the New York

City area, a separate fee is not usually paid when

these two procedures are done together.
66 ■ Costs and Effectiveness of Cervical Cancer Screening

the Actuary of the Health Car e

Financing Administration (HCFA).)5

Fees for professional and clinical services were provided by HCFA, which

supplied 1986 average allowed charges

under Medicare for a list of procedures in the basic protocol for cervical

cancer diagnosis and treatment in and

out of the hospital. In addition,

certain additional services (an assortment of pelvic surgical procedures that

were received by elderly ICC and CIS

patients in the NHDS and were interpreted to be related to the cervical

cancer diagnosis, plus charges for different types of physician visits), were

priced from 1987 Medicare average allowed charges. All prices were updated to 1988 by applying the Consumer Price Index component for

professional medical services.

Quantity information for specific services

(supplied by HCFA), together with Medicare

allowed charges, was used to weigh prices

when several types of biopsy or treatment

were combined to develop per case averages

in the cost estimates.

5 This index, published in the Federal Register,

excludes capital items and medical fees from th e

priced market basket.

The basis for the cost figures applied in

the model is presented in tables 19 through

26. Table 19 shows the prices for specific

component procedures with their sources and

the points in the calculations where each

price figure was used. These components--

e.g., the cost of a hospital visit, the cost of a

particular procedure--are then combined in

tables 20 through 26 into average cost figures

per women with that condition for the appropriate package of services (e.g., diagnosis

of CIS, treatment of EICC, followup of CIN).

In the tables, many procedures are

prorated according to the proportion of

women in that disease state category assumed

to receive them. Thus, for example, in table

20, all women with CIN undergo colposcopy

at the diagnostic workup, so the per-patient

cost is the full amount of the procedure.

Only one-third of women are assumed to

receive a repeat Pap test, however, the attributable per-patient cost of this component

is one-third of the cost of a smear. The proportion of women receiving various services

is drawn largely from the NHDS data and

represents an approximation of the proportion

of women receiving various services under

current medical practice.
Costs and Effectiveness of Cervical Cancer Screening Ž 67

Table 19--Prices for Services Related to Cervical Cancer

Unit 1988b Where used i n estimation

Service price Sourcea

Update (see table number)

Office visit- -extended . . . . . . . . . . . . . . . . . . . .

Office visit- -intermediate.. . . . . . . . . . . . . . .

Hospital visit--initial comprehensive. . . . .

Hospital visit--subsequent brief . . . . . . . . . .

HospitaL day. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Pap test. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Colposcopy..... . . . . . . . . . . . . . . . . . . . . . . . . . . .

CoLposcopy w/biopsy . . . . . . . . . . . . . . . . . . . . . . .

weighted average . . . . . . . . . . . . . . . . . . . . . . . .

Chest X-ray . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Pelvic computed tomography scan. . . . . . . . . . .

Sigmoidoscopy. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Barium enema . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Cystoscopy... . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Intravenous pyelogram. . . . . . . . . . . . . . . . . . . . .

Complete blood count . . . . . . . . . . . . . . . . . . . . . .

Blood urea nitrogen . . . . . . . . . . . . . . . . . . . . . . .

Creatinine-blood . . . . . . . . . . . . . . . . . . . . . . . . . .

PeLvic sonogram . . . . . . . . . . . . . . . . . . . . . . . . . . .

Cervical biopsy . . . . . . . . . . . . . . . . . . . . . . . . . . .

Other biopsies:

cul de sac. . . . . . . . . . . . . . . . . . . . . . . . . . . .

uterus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

vagina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

vulva . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

weighted average . . . . . . . . . . . . . . . . . . . . . .

Dilation and curettage . . . . . . . . . . . . . . . . . . . .

Ionization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

CIN treatments:

cauterization . . . . . . . . . . . . . . . . . . . . . . . . .

cryosurgery . . . . . . . . . . . . . . . . . . . . . . . . . . .

laser surgery . . . . . . . . . . . . . . . . . . . . . . . . .

weighted average . . . . . . . . . . . . . . . . . . . . . .

Hysterectomy-totaL . . . . . . . . . . . . . . . . . . . . . . . .

Hysterectomy- radical.. . . . . . . . . . . . . . . . . . . . .

Pelvic exenteration. . . . . . . . . . . . . . . . . . . . . . .

Bilateral oophorectomy. . . . . . . . . . . . . . . . . . . .

Culdotomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Dilation of cervical canal . . . . . . . . . . . . . . . .

Excision-vagina . . . . . . . . . . . . . . . . . . . . . . . . . . .

Excision-vulva . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Hysterectomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Incision of cervix . . . . . . . . . . . . . . . . . . . . . . . .

Obliteration of vagina . . . . . . . . . . . . . . . . . . . .

Repair-cystocele . . . . . . . . . . . . . . . . . . . . . . . . . .

Repair-cystocele/rectoce[e. . . . . . . . . . . . . . . .

Unilateral oophorectomy. . . . . . . . . . . . . . . . . . .

Unilatera( salpingo-oophorectomy. . . . . . . . . .

Vaginotomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Radium implantf. . . . . . . . . . . . . . . . . . . . . . . . . . .

Teleradiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Chemotherapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

ExternaL radiation . . . . . . . . . . . . . . . . . . . . . . . .

$ 33.00

25.00

77.00

20.00

500.81

7.35

46.76

84.10

20.46

119.48

119.66

40.71

170.71

44.45

7.00

7.00

7.00

47.74

40.43

51.00

53.00

50.11

50.85

251.84

249.12

40.40

64.29

165.99

933.10

1,525.56

2,213.59

373.00

68.00

39.00

95.52

69.77

370.00

42.00

470.00

408.00

509.00

373.00

449.00

103.50

70.49

47.65

24.75

44.70

HCFA 1987

HCFA 1987

HCFA 1987

HCFA 1987

AHA 1986

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1987

HCFA 1987

HCFA 1987

HCFA 1986

HCFA 1986

HCFA 1987

HCFA 1987

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1987

HCFA 1986

HCFA 1986

HCFA 1986

HCFA 1987

HCFA 1987

HCFA 1987

HCFA 1986

HCFA 1986

HCFA 1987

HCFA 1987

HCFA 1987

HCFA 1987

HCFA 1987

HCFA 1987

HCFA 1987

HCFA 1987

HCFA 1986

HCFA 1987

HCFA 1986

HCFA 1986

$35.23

26.69

82.20

21.35

545.78

8.37

53.22

95.71

71.56

23.20

136.00

136.20

46.34

194.31

50.59

7.47

7.47

7.47

54.34

46.02

54.44

56.58

57.04

57.88

56.33d/58.33 e

286.66

283.56

45.99

73.18

177.20

58.91

1,062.03

1,729.50

2,509.51

398.39

72.59

41.63

108.73

79.42

394.99

44.84

501.75

435.56

543.38

389.19

479.33

110.49

80.23

50.84

28.17

50.87

20, 23, 25

20, 21, 23, 24, 25, 26

20, 21, 22, 23, 24, 25

20, 21, 22, 23, 24, 25

20, 21, 22, 23, 24, 25

20, 25

20, 21, 23, 24

23, 26

23

23

23

23

23, 26

23

23

23

26

20, 22

20, 22

21, 22, 23

20, 21, 22, 23, 25

23

21, 23, 25

20

21

23

24

23

23

23

23

21

23

23

21, 23

21

21

23

21

23

23

24

24

24

ABBREVIATIONS: AHA = American Hospital Association; CIN = cervical intraepithelial neoplasia;

HCFA = Health Care Financing Agency.

aAHA, 1986 data from American Hospital Association, Hospital Statistics 1987 Edition (Chicago, IL: American Hospital Association, 1989); HCFA 1986 and 1987 data from Part B Medicare Annua[ Data System provided by M. McMulLan Health Care

Financing Administration, Baltimore, MO, personal communications, 1988; and W.J. Sobaski, Health Care Financing Ackninis-

, tration, Baltimore, MD, personal communications. 1989.

‘Based on comsumer price index for professional medical services (in medical care component) from Bureau of Labor

Statistics; National Hospital Input Index from HeaLth Care Financing Administration, Office of the Actuary.

cBased on weighted average of allowed charges for the following: biopsy of uterus (l), vagina (4), CUL de sac (l), vulva

,(1), (1986 charges updated to 1988).

dUsed for diagnostic admission.

eUsed for diagnosis and treatment.

Based on 44 cases from the NationaL Hospital Discharge Survey of elderly women receiving in-hospital care for cervical cancer.

SOURCE: Office of Technology Assessment, 1990.
68 ■ Costs and Effectiveness of Cervical Cancer Screening

Table 20--Estimated Costs of Diagnosing

and Treating Cervical Intraepithelial Neoplasia

(CIN-grades 1 and 2)

$ 2.7 9

$358.44 “

Proportion Average cost

of CIN cases per person

Servic e Calculation of total cos t

a

receiving servic e with CIN

Colposcopy. . . . . . . . . . . . . . . . . $98.25 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100% $98.2 5

procedure = $71.56

physician visit =$26.6 9

Repeat Pap test. . . . . . . . . . . . $8.37 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33%

Ionization . . . . . . . . . . . . . . . . . $1,195.11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30%

procedure = $283.56

hospital stay (1.5 days) = $818.6 7

initial inpatient physician visit = $82.2 0

additional inpatient visits (.5) = $10.6 7

Cervical biopsy . . . . . . . . . . . . %6.02 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62% $28.5 3

Other biopsies . . . . . . . . . . . . . $87.50 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100% $87.5 0

(1.5 X $58.33 )

Subtotal ...-..- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $57S.51

Treatment by cautery. . . . . . . $94.14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100% $94.14

cryosurgery or procedure = $58.91

laser surger y office visit = $35.2 3

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $669.65

ABBREVIATION: CIN = cervical intraepithelial neoplasia .

a

See table 19 for sources of component costs.

SOURCE: Office of Technology Assessment, 1990.
Costs and Effectiveness of Cervical Cancer Screening • 69

Table 21--Estimated Costs of Diagnosing and Treating Carcinoma In Situ

Proportion Average cost

of CIS cases per person

Servic e Calculation of total cos t

a

receiving servic e

b with CIS

COlpOSCOpy. . . . . . . . . . . . . . . . . . . . $98.25 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100% $ 98.25

servic e = $71.56

visi t = $26.69

Total hysterectomy . . . . . . . . . . . . $1,062.03 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43% $ 456.6 7

Ionization . . . . . . . . . . . . . . . . . . . . $283.56 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35% $ 99.25

Dilation and curettage . . . . . . . . $286.66 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30% $ 86.00

Other surgery . . . . . . . . . . . . . . . . $340.44 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35% $ 119.1 5

Hospital stay. . . . . . . . . . . . . . . . . $2,892.63 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100% $2,892.6 3

(5.3 days x 545.78)

Initial physician visit . . . . . . . $82.20 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100% $ 82.20

Additional physician visits... $91.8 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100% $ 91.81

(4.3 x$21.35 )

Total--------------------- . . . . . . . . --------- ---------------- ------------ -------- --- $3,925.%

ABBREVIATION: CIS = carcinoma in situ.

aSee table 19 for sources of component costs.

All services except colposcopy are in-hospital services; proportions of cases receiving in-hospital services are based on 23 cases from the National Hospital Discharge Survey of elderly women receiving inhospital care for CIS.

cIncludes cryosurgery, excision of vulva, obliteration of vagina, repair of cystoce[e, repair of cystoce(e

and rectocele, and unilateral salpingo-oophorectomy.

SOURCE: Office of Technology Assessment, 1990.
70 Ž Costs and Effectiveness of Cervical Cancer Screening

Table 22--Estimated Costs of Diagnostic Admission

for Cervical Cancer

Proportion o f Average cos t

cervical cancer cases per person

Servic e Calculation of total cos t

a % receiving servic ecervical cance r

Dilation and curettage . . . . . . . . . . $286.6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 5 9 % $ 169.1 3

Cervical biopsy . . . . . . . . . . . . . . . . . $46.02 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 9 % $$ 27.15

Other biopsies . . . . . . . . . . . . . . . . . . $56.33 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 6 % $ 14.6 5

Ionization . . . . . . . . . . . . . . . . . . . . . . $283.56 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 5 % $ 42.53

Hospital stay. . . . . . . . . . . . . . . . . . . $3,656.73 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 % $3,656.7 3

(6.7 days x 545.78 )

Initial inpatien t

physician visit . . . . . . . . . . . . . . . . . $82.20 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 % $ 82.20

Additional inpatien t

physician visits . . . . . . . . . . . . . . . . $121.70 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 % $ 121.7 0

(5.7x $21.35 )

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -------- . . . . . . . . . . . . . . . . $4,114.09

~See table 19 for sources of component costs .

Based on 27 cases from the National Hospital Discharge Survey of elderly women with diagnostic

admissions for cervical cancer.

SOURCE: Office of Technology Assessment, 1990 .
Costs and Effectiveness of Cervical Cancer Screening Ž 71

Table 23--Estimated Costs of Diagnosing

and Treating Early Invasive Cervical Cancer

Proportion Average cost

Service of EICC cases per person

package Calculation of total cos t

a b

receiving servic e with EICC

Colposcopy:

Outpatien t service = $71.5 6

service s visi t = $26.69

$98.2 5 100% $ 98.25

Staging:

Chest X-ray = $ 23.29

Pelvic coopted tomography scan = $136.00

Sigmoidoscopy = $136.20

Barium enema = $ 46.34

Cystoscopy = $194.31

Intravenous pyelogram = $ 50.59

Extended office visit = $ 35.2 3

Complete blood count = $ 7.47

Blood urea nitrogen = $ 7.47

Creatinine-blood = $ 7.4 7

$644.3 7 100% $ 644.3 7

Sub-total ------------ . . . . . . . . . . . . . . . . . . . . . . . . . . . . ---------- ------------ . . $ 742.62

Inpatien t Diagnostic admissionc = $4,114.0 9 20% $ 822.8 2

service s Radioactive substance implant = $ 80.2 3 50% $ 40.12

Radical hysterectomy = $1,729.5 0 30% $ 518.8 5

Other surgery = $ 126.6 2 59% $ 74.71

Dilation and curettage = $ 286.6 6 11% $ 31.53

Ionizatio n = S 283.5 6 5% $ 14.1 8

Hospital stay (10.1 days) = $5,512.3 8 100% $ 5,512.38

Physician visits = $ 82.2 0 100% $ 82.20

($21.35 x 9.1 )

Additional inpatient physician visits = $ 194.2 9 100% 194.2 9

(9.1 days )

sub-total ------------------- --------- . . . . . . . . -------- --------- --------- -- $7,291.08

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . - $8,033.70

. . . .

ABBRIVIATIO N cc = early lnvasive cervical cancer.

~See table 19 for sources of cost components.

Based on 44 cases from the National Hospital Discharge Survey of elderly women receiving care for EICC.

~See table 22 for source of costs.

Includes bilateral oophorectomy, cauterization , cryosurgery, culdotomy, dilation of cervix, excision o f

lesion-vagina, hysterotomy, incision of cervix, obliteration of vagina, unilateral oo@orectw,

vaginotomy.

SOURCE: Office of Technology Assessment, 1990.
72 ■ Costs and Effectiveness of Cervical Cancer Screening

Table 24--Estimated Costs of Diagnosing

and Treating Late Invasive Cervical Cancer

ABBREVIATION: LICC = late invasive cervical cancer.

a

See table 19 for sources of cost components.

See table 20 for cost of components.

~See table 23 for cost of components.

Based on 116 cases from the National Hospital Discharge Survey of elderly women receiving inhospita[ care for late cervical cancer.

‘Based on length of stay for cases with chemotherapy and weighted average of a[lowed charges for

~ different types of chemotherapy.

Based on length of stay for cases with teleradiation.

~Based ~ length of stay for cases with other external radiation.

See table 22 for cost of components.

Source: Office of Technology Assessment, 1990.
Costs and Effectiveness of Cervical Cancer Screening • 73

Table 25--Estimated Costs of Followup Care for CIN and CIS

Proportion o f Average cos t

Service CINand CIS cases per person with

package Calculation of total cos t

a

receiving servic e CIN and CIS

Followu p 4 office visits x $ 26.6 9 100% $ 106.7 6

year 1 1 Pap smear x $ 8.3 7 100% $ 8.37

Cryosurgery :

service = $ 73.18

visi t = $ 35.23

$ 108.4 1

Ionization :

Procecdur e = $ 283.5 6

hospital stay (1.5 days) = $818.6 7

physician visits (during hospital stay) = $ 92.8 8

$1,196.1 1 5% $ 59.7 4

Subtotal --------- . . . . . . . . . . . . . . . . . . . . . . . . . ---------- . . . $ 185.71

Followup

years 2 through 5 2 office visits annually x $ 26.6 9 100% $213.5 2

1 Pap smear annually x $ 8.3 7 100% $ 33.4 8

Subtotal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $247.00

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -------- . . . . . . . . . . . . . . . . . . ------$ 432.71

ABBREVIATION: CIN = cervical intraepithelial neoplasia

a

See table 19 for sources of cost c~nents.

SOURCE: Office of Technology Assessment, 1990.

and CIS = carcinoma in situ. — —

$ 10.84
74 • Costs and Effectiveness of Cervical Cancer Screening

Table 26--Estimated Costs of Followup Care for Invasive Cervical Cancer

Proportion Average cost

Servic e of ICC cases per person

package Calculation of total cos t

a

receiving servic e with ICC

Early cancer followup 4 office visits x $26.69 = $106.76

year 1 2 intravenous pyelograms x $50.59 = $101.18

2 chest x-rays x $23.29 = $46.5 8

2 pelvic sonograms x $54.34 = $108.68

cos t . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $363.2 0 100% $ 363.2 0

Early cancer followup 2 office visits annually x $26.69 = $53.3 8

years 2 through 5 1 intravenous pyelograms x $50.59 = $ 50.59

2 chest x-rays x $23.29 = $ 46.58

1 pelvic sonogram x $54.34 = $54.34

Annual cost. . . . . . . . . . . . . . . . . . . . . . . . $204.89 100% $ 819.5 6

(x 4 years )

Total, followup care for early invasive cervical wincer ....--. . . . . . . . . ------ S1,182.76

Late cancer followup 4 office visits annually = $106.7 6

years 1 through 3 2 intravenous pyelograms = $101.18

2 chest x-rays = $ 46.58

Annual cost. . . . . . . . . . . . . . . . . . . . . . . . $254.52 100% $ 763.5 6

(x 3 years )

Late cancer followup 2 office visits annually = $ 53.3 8

years 4 through 5 1 intravenous pyelograms = $ 50.59

1 chest x-ray = $ 46.58

1 pelvic sonogram = $ 54.34

Annual cost. . . . . . . . . . . . . . . . . . . . . . . . $181.60 100% $ 363.2 0

(x 2 years )

Total, followup care for late invasive cervical cancer ------- . . . . . . . . ------- $1,126.76

ABBREVIATION: ICC = invasive cervical cancer.

a

See table 19 for sources of cost components.

SOURCE: Office of Technology Assessment, 1990.
ABBREVIATIONS

ACOG

ACS

AHA

ASCP

CIN

CIS

D&C

DHHS

DYS

EICC

HCFA

HPV

ICC

IVP

LICC

MDYS

NA

NCI

NHDS

NHIS

NIH

SEER

USPSTF

--American College of Obstetricians and Gynecologists

--American Cancer Society

--American Hospital Association

--American Society of Clinical Pathologists

--cervical intraepithelial neoplasia

--carcinoma in situ

--dilation and curettage

--U.S. Department of Health and Human Services

--dysplasia

--early invasive cervical cancer

--Health Care Financing Administration

--human papillomavirus

--invasive cervical cancer

--intravenous pyelogram

--late invasive cervical cancer

--mild dysplasia

--not available

--National Cancer Institute

--National Hospital Discharge Survey

--National Health Interview Survey

--National Institutes of Health

--surveillance, epidemiology, and end results

--United States Preventive Services Task Force

75
REFERENCES

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

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For further information on this paper or others in

OTA’s series on Preventive Health Services Under

Medicare, contact: Judith Wagner, Health Program,

Office of Technology Assessment, U.S. Congress,

Washington, D.C. 20510-8025