Literature DB >> 11830609

Cost-effectiveness of cervical cancer screening: comparison of screening policies.

M Elske van den Akker-van Marle1, Marjolein van Ballegooijen, Gerrit J van Oortmarssen, Rob Boer, J Dik F Habbema.   

Abstract

BACKGROUND: Recommended screening policies for cervical cancer differ widely among countries with respect to targeted age range, screening interval, and total number of scheduled screening examinations (i.e., Pap smears). We compared the efficiency of cervical cancer-screening programs by performing a cost-effectiveness analysis of cervical cancer-screening policies from high-income countries.
METHODS: We used the microsimulation screening analysis (MISCAN) program to model and determine the costs and effects of almost 500 screening policies, some fictitious and some actual (i.e., recommended by national guidelines). The costs (in U.S. dollars) and effects (in years of life gained) were compared for each policy to identify the most efficient policies.
RESULTS: There were 15 efficient screening policies (i.e., no alternative policy exists that results in more life-years gained for lower costs). For these policies, which considered two to 40 total scheduled examinations, the age range expanded gradually from 40-52 years to 20-80 years as the screening interval decreased from 12 to 1.5 years. For the efficient policies, the predicted gain in life expectancy ranged from 11.6 to 32.4 days, compared with a gain of 46 days if cervical cancer mortality were eliminated entirely. The average cost-effectiveness ratios increased from $6700 (for the longest screening interval) to $23 900 per life-year gained. For some countries, the recommended screening policies were close to efficient, but the cost-effectiveness could be improved by reducing the number of scheduled examinations, starting them at later ages, or lengthening the screening interval.
CONCLUSIONS: The basis for the diversity in the screening policies among high-income countries does not appear to relate to the screening policies' cost-effectiveness ratios, which are highly sensitive to the number of Pap smears offered during a lifetime.

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Year:  2002        PMID: 11830609     DOI: 10.1093/jnci/94.3.193

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   13.506


  26 in total

1.  Cost effectiveness of a program to promote screening for cervical cancer in the Vietnamese-American population.

Authors:  John F Scoggins; Scott D Ramsey; J Carey Jackson; Victoria M Taylor
Journal:  Asian Pac J Cancer Prev       Date:  2010

Review 2.  Calibration methods used in cancer simulation models and suggested reporting guidelines.

Authors:  Natasha K Stout; Amy B Knudsen; Chung Yin Kong; Pamela M McMahon; G Scott Gazelle
Journal:  Pharmacoeconomics       Date:  2009       Impact factor: 4.981

Review 3.  The value of models in informing resource allocation in colorectal cancer screening: the case of The Netherlands.

Authors:  Frank van Hees; Ann G Zauber; Harriët van Veldhuizen; Marie-Louise A Heijnen; Corine Penning; Harry J de Koning; Marjolein van Ballegooijen; Iris Lansdorp-Vogelaar
Journal:  Gut       Date:  2015-06-10       Impact factor: 23.059

4.  The impact of overdiagnosis on the selection of efficient lung cancer screening strategies.

Authors:  Summer S Han; Kevin Ten Haaf; William D Hazelton; Vidit N Munshi; Jihyoun Jeon; Saadet A Erdogan; Colden Johanson; Pamela M McMahon; Rafael Meza; Chung Yin Kong; Eric J Feuer; Harry J de Koning; Sylvia K Plevritis
Journal:  Int J Cancer       Date:  2017-06-01       Impact factor: 7.396

5.  Cervical cancer screening with AMIGAS: a cost-effectiveness analysis.

Authors:  David R Lairson; Yu-Chia Chang; Theresa L Byrd; Judith Lee Smith; Maria E Fernandez; Katherine M Wilson
Journal:  Am J Prev Med       Date:  2014-06       Impact factor: 5.043

Review 6.  Dynamic microsimulation models for health outcomes: a review.

Authors:  Carolyn M Rutter; Alan M Zaslavsky; Eric J Feuer
Journal:  Med Decis Making       Date:  2010-05-18       Impact factor: 2.583

7.  Dried cervical spots for human papillomaviruses identification.

Authors:  Valérie Charbonneau; Isabelle Garrigue; Antoine Jaquet; Apollinaire Horo; Albert Minga; Patricia Recordon-Pinson; François Dabis; Hervé Fleury
Journal:  J Med Virol       Date:  2013-04-17       Impact factor: 2.327

8.  Indirect estimation of a discrete-state discrete-time model using secondary data analysis of regression data.

Authors:  Deanna J M Isaman; Jacob Barhak; Wen Ye
Journal:  Stat Med       Date:  2009-07-20       Impact factor: 2.373

9.  Multicohort models in cost-effectiveness analysis: why aggregating estimates over multiple cohorts can hide useful information.

Authors:  James F O'Mahony; Joost van Rosmalen; Ann G Zauber; Marjolein van Ballegooijen
Journal:  Med Decis Making       Date:  2012-08-27       Impact factor: 2.583

Review 10.  Willingness to pay for cancer prevention.

Authors:  Timothy L Hunt; Bryan R Luce; Matthew J Page; Robin Pokrzywinski
Journal:  Pharmacoeconomics       Date:  2009       Impact factor: 4.981

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