Literature DB >> 25023249

Personalizing age of cancer screening cessation based on comorbid conditions: model estimates of harms and benefits.

Iris Lansdorp-Vogelaar, Roman Gulati, Angela B Mariotto, Clyde B Schechter, Tiago M de Carvalho, Amy B Knudsen, Nicolien T van Ravesteyn, Eveline A M Heijnsdijk, Chester Pabiniak, Marjolein van Ballegooijen, Carolyn M Rutter, Karen M Kuntz, Eric J Feuer, Ruth Etzioni, Harry J de Koning, Ann G Zauber, Jeanne S Mandelblatt.   

Abstract

BACKGROUND: Harms and benefits of cancer screening depend on age and comorbid conditions, but reliable estimates are lacking.
OBJECTIVE: To estimate the harms and benefits of cancer screening by age and comorbid conditions to inform decisions about screening cessation.
DESIGN: Collaborative modeling with 7 cancer simulation models and common data on average and comorbid condition level-specific life expectancy.
SETTING: U.S. population. PATIENTS: U.S. cohorts aged 66 to 90 years in 2010 with average health or 1 of 4 comorbid condition levels: none, mild, moderate, or severe. INTERVENTION: Mammography, prostate-specific antigen testing, or fecal immunochemical testing. MEASUREMENTS: Lifetime cancer deaths prevented and life-years gained (benefits); false-positive test results and overdiagnosed cancer cases (harms). For each comorbid condition level, the age at which harms and benefits of screening were similar to that for persons with average health having screening at age 74 years.
RESULTS: Screening 1000 women with average life expectancy at age 74 years for breast cancer resulted in 79 to 96 (range across models) false-positive results, 0.5 to 0.8 overdiagnosed cancer cases, and 0.7 to 0.9 prevented cancer deaths. Although absolute numbers of harms and benefits differed across cancer sites, the ages at which to cease screening were consistent across models and cancer sites. For persons with no, mild, moderate, and severe comorbid conditions, screening until ages 76, 74, 72, and 66 years, respectively, resulted in harms and benefits similar to average-health persons. LIMITATION: Comorbid conditions influenced only life expectancy.
CONCLUSION: Comorbid conditions are an important determinant of harms and benefits of screening. Estimates of screening benefits and harms by comorbid condition can inform discussions between providers and patients about personalizing screening cessation decisions. PRIMARY FUNDING SOURCE: National Cancer Institute and Centers for Disease Control and Prevention.

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Year:  2014        PMID: 25023249      PMCID: PMC4160041          DOI: 10.7326/M13-2867

Source DB:  PubMed          Journal:  Ann Intern Med        ISSN: 0003-4819            Impact factor:   25.391


  49 in total

1.  The MISCAN-COLON simulation model for the evaluation of colorectal cancer screening.

Authors:  F Loeve; R Boer; G J van Oortmarssen; M van Ballegooijen; J D Habbema
Journal:  Comput Biomed Res       Date:  1999-02

2.  Breast cancer screening for elderly women with and without comorbid conditions. A decision analysis model.

Authors:  J S Mandelblatt; M E Wheat; M Monane; R D Moshief; J P Hollenberg; J Tang
Journal:  Ann Intern Med       Date:  1992-05-01       Impact factor: 25.391

3.  Development of a comorbidity index using physician claims data.

Authors:  C N Klabunde; A L Potosky; J M Legler; J L Warren
Journal:  J Clin Epidemiol       Date:  2000-12       Impact factor: 6.437

4.  When should we stop screening?

Authors:  J S Rich; W C Black
Journal:  Eff Clin Pract       Date:  2000 Mar-Apr

5.  Cancer screening in elderly patients: a framework for individualized decision making.

Authors:  L C Walter; K E Covinsky
Journal:  JAMA       Date:  2001-06-06       Impact factor: 56.272

6.  Cost-effectiveness of screening for colorectal cancer in the general population.

Authors:  A L Frazier; G A Colditz; C S Fuchs; K M Kuntz
Journal:  JAMA       Date:  2000-10-18       Impact factor: 56.272

7.  Comparative effectiveness of alternative prostate-specific antigen--based prostate cancer screening strategies: model estimates of potential benefits and harms.

Authors:  Roman Gulati; John L Gore; Ruth Etzioni
Journal:  Ann Intern Med       Date:  2013-02-05       Impact factor: 25.391

8.  Lead times and overdetection due to prostate-specific antigen screening: estimates from the European Randomized Study of Screening for Prostate Cancer.

Authors:  Gerrit Draisma; Rob Boer; Suzie J Otto; Ingrid W van der Cruijsen; Ronald A M Damhuis; Fritz H Schröder; Harry J de Koning
Journal:  J Natl Cancer Inst       Date:  2003-06-18       Impact factor: 13.506

9.  Colonoscopy screening in the elderly: when to stop?

Authors:  Tyler Stevens; Carol A Burke
Journal:  Am J Gastroenterol       Date:  2003-08       Impact factor: 10.864

10.  Toward optimal screening strategies for older women. Costs, benefits, and harms of breast cancer screening by age, biology, and health status.

Authors:  Jeanne S Mandelblatt; Clyde B Schechter; K Robin Yabroff; William Lawrence; James Dignam; Martine Extermann; Sarah Fox; Gretchen Orosz; Rebecca Silliman; Jennifer Cullen; Lodovico Balducci
Journal:  J Gen Intern Med       Date:  2005-06       Impact factor: 5.128

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  49 in total

1.  Collaborative Modeling of the Benefits and Harms Associated With Different U.S. Breast Cancer Screening Strategies.

Authors:  Jeanne S Mandelblatt; Natasha K Stout; Clyde B Schechter; Jeroen J van den Broek; Diana L Miglioretti; Martin Krapcho; Amy Trentham-Dietz; Diego Munoz; Sandra J Lee; Donald A Berry; Nicolien T van Ravesteyn; Oguzhan Alagoz; Karla Kerlikowske; Anna N A Tosteson; Aimee M Near; Amanda Hoeffken; Yaojen Chang; Eveline A Heijnsdijk; Gary Chisholm; Xuelin Huang; Hui Huang; Mehmet Ali Ergun; Ronald Gangnon; Brian L Sprague; Sylvia Plevritis; Eric Feuer; Harry J de Koning; Kathleen A Cronin
Journal:  Ann Intern Med       Date:  2016-01-12       Impact factor: 25.391

2.  How Do Older Adults Consider Age, Life Expectancy, Quality of Life, and Physician Recommendations When Making Cancer Screening Decisions? Results from a National Survey Using a Discrete Choice Experiment.

Authors:  Ellen M Janssen; Craig E Pollack; Cynthia Boyd; John F P Bridges; Qian-Li Xue; Antonio C Wolff; Nancy L Schoenborn
Journal:  Med Decis Making       Date:  2019-06-21       Impact factor: 2.583

3.  Breast cancer screening in patients with cancers other than breast.

Authors:  Robin B Leopold; Alexander W Thomas; Kyle F Concannon; Alissa D Correll; Catherine M LaPenta; Stephen M Maurer; Brian L Sprague; Sally D Herschorn; Claire F Verschraegen
Journal:  Breast Cancer Res Treat       Date:  2017-03-06       Impact factor: 4.872

4.  Simulation of Chemotherapy Effects in Older Breast Cancer Patients With High Recurrence Scores.

Authors:  Young Chandler; Jinani C Jayasekera; Clyde B Schechter; Claudine Isaacs; Christopher J Cadham; Jeanne S Mandelblatt
Journal:  J Natl Cancer Inst       Date:  2020-06-01       Impact factor: 13.506

5.  Conditions for Valid Empirical Estimates of Cancer Overdiagnosis in Randomized Trials and Population Studies.

Authors:  Roman Gulati; Eric J Feuer; Ruth Etzioni
Journal:  Am J Epidemiol       Date:  2016-06-29       Impact factor: 4.897

6.  Examining Generalizability of Older Adults' Preferences for Discussing Cessation of Screening Colonoscopies in Older Adults with Low Health Literacy.

Authors:  Nancy L Schoenborn; Norah L Crossnohere; Ellen M Janssen; Craig E Pollack; Cynthia M Boyd; Antonio C Wolff; Qian-Li Xue; Jacqueline Massare; Marcela Blinka; John F P Bridges
Journal:  J Gen Intern Med       Date:  2019-08-26       Impact factor: 5.128

7.  Using Active Learning for Speeding up Calibration in Simulation Models.

Authors:  Mucahit Cevik; Mehmet Ali Ergun; Natasha K Stout; Amy Trentham-Dietz; Mark Craven; Oguzhan Alagoz
Journal:  Med Decis Making       Date:  2015-10-15       Impact factor: 2.583

8.  Introduction to the Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Models.

Authors:  Oguzhan Alagoz; Donald A Berry; Harry J de Koning; Eric J Feuer; Sandra J Lee; Sylvia K Plevritis; Clyde B Schechter; Natasha K Stout; Amy Trentham-Dietz; Jeanne S Mandelblatt
Journal:  Med Decis Making       Date:  2018-04       Impact factor: 2.583

9.  Structure, Function, and Applications of the Georgetown-Einstein (GE) Breast Cancer Simulation Model.

Authors:  Clyde B Schechter; Aimee M Near; Jinani Jayasekera; Young Chandler; Jeanne S Mandelblatt
Journal:  Med Decis Making       Date:  2018-04       Impact factor: 2.583

10.  Personalizing colonoscopy screening for elderly individuals based on screening history, cancer risk, and comorbidity status could increase cost effectiveness.

Authors:  Frank van Hees; Sameer D Saini; Iris Lansdorp-Vogelaar; Sandeep Vijan; Reinier G S Meester; Harry J de Koning; Ann G Zauber; Marjolein van Ballegooijen
Journal:  Gastroenterology       Date:  2015-08-04       Impact factor: 22.682

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