Reducing overtreatment associated with overdiagnosis in cervical cancer screening-A model-based benefit-harm analysis for Austria.

Publisher: Wiley-Liss Country of Publication: United States NLM ID: 0042124 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-0215 (Electronic) Linking ISSN: 00207136 NLM ISO Abbreviation: Int J Cancer Subsets: MEDLINE

Publication: 1995- : New York, NY : Wiley-Liss
Original Publication: 1966-1984 : Genève : International Union Against Cancer

Early Detection of Cancer/*methods ; Mass Screening/*methods ; Papillomavirus Infections/*diagnosis ; Uterine Cervical Neoplasms/*diagnosis ; Uterine Cervical Dysplasia/*diagnosis; Adult ; Alphapapillomavirus/physiology ; Austria ; Cyclin-Dependent Kinase Inhibitor p16/analysis ; Female ; Humans ; Ki-67 Antigen/analysis ; Markov Chains ; Medical Overuse/prevention & control ; Middle Aged ; Papanicolaou Test/methods ; Papillomavirus Infections/virology ; Uterine Cervical Neoplasms/virology ; Vaginal Smears/methods ; Young Adult ; Uterine Cervical Dysplasia/virology

A general concern exists that cervical cancer screening using human papillomavirus (HPV) testing may lead to considerable overtreatment. We evaluated the trade-off between benefits and overtreatment among different screening strategies differing by primary tests (cytology, p16/Ki-67, HPV alone or in combinations), interval, age and diagnostic follow-up algorithms. A Markov state-transition model calibrated to the Austrian epidemiological context was used to predict cervical cancer cases, deaths, overtreatments and incremental harm-benefit ratios (IHBR) for each strategy. When considering the same screening interval, HPV-based screening strategies were more effective compared to cytology or p16/Ki-67 testing (e.g., relative reduction in cervical cancer with biennial screening: 67.7% for HPV + Pap cotesting, 57.3% for cytology and 65.5% for p16/Ki-67), but were associated with increased overtreatment (e.g., 19.8% more conizations with biennial HPV + Papcotesting vs. biennial cytology). The IHBRs measured in unnecessary conizations per additional prevented cancer-related death were 31 (quinquennial Pap + p16/Ki-67-triage), 49 (triennial Pap + p16/Ki-67-triage), 58 (triennial HPV + Pap cotesting), 66 (biennial HPV + Pap cotesting), 189 (annual Pap + p16/Ki-67-triage) and 401 (annual p16/Ki-67 testing alone). The IHBRs increased significantly with increasing screening adherence rates and slightly with lower age at screening initiation, with a reduction in HPV incidence or with lower Pap-test sensitivity. Depending on the accepted IHBR threshold, biennial or triennial HPV-based screening in women as of age 30 and biennial cytology in younger women may be considered in opportunistic screening settings with low or moderate adherence such as in Austria. In organized settings with high screening adherence and in postvaccination settings with lower HPV prevalence, the interval may be prolonged.
(© 2019 UICC.)

Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68:394-424.
Arbyn M, Anttila A, Jordan J, et al. European guidelines for quality Assurance in Cervical Cancer Screening. Second edition-summary document. Ann Oncol 2010;21:448-58.
Bruni L, Barrionuevo-Rosas L, Albero G, et al. Human papillomavirus and related diseases in Austria. Summary report 2015 03-20. Wien: ICO Information Centre on HPV and Cancer (HPV information Centre), 2015.
Statistik Austria. Gebärmutterhals (C53). Available at: http://www.statistik.at/web_de/statistiken/menschen_und_gesellschaft/gesundheit/krebserkrankungen/gebaermutterhals/index.html.
Breitenecker G, Girardi F, Joura E, et al. Leitlinie für die Diagnose und Therapie von Cervikalen Intraepithelialen Neoplasien (CIN) und Mikrokarzinomen der Cervix uteri. Speculum 2005;23:20-5.
Öffentliches Gesundheitsportal Österreich. Kostenlose HPV-Impfung für Kinder startet. Available at: https://www.gesundheit.gv.at/aktuelles/archiv-2014/hpv-impfung-start, vol. 2018.
Woolf SH, Harris R. The harms of screening: new attention to an old concern. JAMA 2012;307:565-6.
Esserman LJ, Thompson IM, Reid B, et al. Addressing overdiagnosis and overtreatment in cancer: a prescription for change. Lancet Oncol 2014;15:e234-42.
Ronco GAM, Meijer CJLM, Snijders PJF, et al. Screening for cervical cancer with primary testing for human papillomavirus, 2nd edn. Luxembourg: Office for Official Publications of the European Union, 2015. 1-68.
Heleno B, Thomsen MF, Rodrigues DS, et al. Quantification of harms in cancer screening trials: literature review. BMJ 2013;347:f5334.
Trikalinos TA, Siebert U, Lau J. Decision-analytic modeling to evaluate benefits and harms of medical tests: uses and limitations. Med Decis Making 2009;29:E22-9.
Siebert U. When should decision-analytic modeling be used in the economic evaluation of health care? [editorial]. Eur J Health Econ 2003;4:143-50.
Vickers AJ, Van Calster B, Steyerberg EW. Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests. BMJ 2016;352:i6.
Caro JJ, Briggs AH, Siebert U, et al. Modeling good research practices - overview: a report of the ISPOR-SMDM modeling good research practices task force −1. Value Health 2012;15:796-803.
Siebert U, Alagoz O, Bayoumi AM, et al. State-transition modeling: a report of the ISPOR-SMDM modeling good research practices task Force-3. Value Health 2012;15:812-20.
Drummond M, Schwartz JS, Jonsson B, et al. Response from the authors of "key principles for the improved conduct of health technology assessments for resource allocation decisions". Int J Technol Assess Health Care 2008;24:367-8.
Reich OH, Hefler L, Regauer S, et al. Diagnose und Therapie von cervikalen intraepithelialen Neoplasien (CIN, SIL) und des Adenocarcinoma in situ (AIS) sowie Vorgangsweise bei zytologischen Befunden mit eingeschränkter Beurteilbarkeit. Wien: Österreichische Gesellschaft für Gynäkologie und Geburtshilfe (OEGGG), 2015.
Statistik Austria. Jährliche Sterbetafeln für Österreich Jahr 2013. Available at: http://www.statistik.at/web_de/statistiken/bevoelkerung/sterbetafeln/index.html.
Siebert U, Sroczynski G, Hillemanns P, et al. The German cervical cancer screening model: development and validation of a decision-analytic model for cervical cancer screening in Germany. Eur J Public Health 2006;16:185-92.
Sroczynski G, Schnell-Inderst P, Muhlberger N, et al. Decision-analytic modeling to evaluate the long-term effectiveness and cost-effectiveness of HPV-DNA testing in primary cervical cancer screening in Germany. GMS Health Technol Assess 2010;6:Doc05.
Sroczynski G, Schnell-Inderst P, Muhlberger N, et al. Cost-effectiveness of primary HPV screening for cervical cancer in Germany - a decision analysis. Eur J Cancer 2011;47:1633-46.
Sroczynski G, Schnell-Inderst P, Mühlberger N, et al. Decision-analytic modeling to evaluate the long-term effectiveness and cost-effectiveness of HPV-DNA testing in primary cervical cancer screening in Germany. GMS Health Technol Assess 2010;6:Doc05.
Kucera H, Michalica W. Epidemiology of cervical cancer in Austria. Onkologie 1979;2:142-7.
Borena W, Grunberger M, Widschwendter A, et al. Pre-vaccine era cervical human papillomavirus infection among screening population of women in West Austria. BMC Public Health 2016;16:889.
Zechmeister I, Freiesleben de Blasio B, Radlberger P, et al. Ökonomische Evaluation der Impfung gegen humane Papillomaviren (HPV-Impfung) in Österreich. LBI-HTA Projektbericht Nr. 9. Wien: Ludwig Boltzmann Institut für Health Technology Assessment, 2007.
Arbyn M, Ronco G, Anttila A, et al. Evidence regarding human papillomavirus testing in secondary prevention of cervical cancer. Vaccine 2012;30(Suppl 5):F88-99.
Cuzick J, Clavel C, Petry KU, et al. Overview of the European and North American studies on HPV testing in primary cervical cancer screening. Int J Cancer 2006;119:1095-101.
McCrory DC, Matchar DB. Evaluation of cervical cytology-systematic reviewed. Rockville, MD: Agency for Health Care Research and Quality (AHRQ), 1999.
Nanda K, McCrory DC, Myers ER, et al. Accuracy of the Papanicolaou test in screening for and follow-up of cervical cytologic abnormalities: a systematic review. Ann Intern Med 2000;132:810-9.
Petry KU, Schmidt D, Scherbring S, et al. Triaging pap cytology negative, HPV positive cervical cancer screening results with p16/Ki-67 dual-stained cytology. Gynecol Oncol 2011;121:505-9.
Schmidt D, Bergeron C, Denton KJ, et al. Group. ECCS. p16/ki-67 dual-stain cytology in the triage of ASCUS and LSIL papanicolaou cytology: results from the European equivocal or mildly abnormal Papanicolaou cytology study. Cancer Cytopathol 2011;119:158-66.
Bergeron C, Giorgi-Rossi P, Cas F, et al. Informed cytology for triaging HPV-positive women: substudy nested in the NTCC randomized controlled trial. J Natl Cancer Inst 2015;107:dju423.
Ouitrakul S, Udomthavornsuk B, Chumworathayi B, et al. Accuracy of colposcopically directed biopsy in diagnosis of cervical pathology at Srinagarind hospital. Asian Pac J Cancer Prev 2011;12:2451-3.
Stoler MH, Vichnin MD, Ferenczy A, et al. The accuracy of colposcopic biopsy: analyses from the placebo arm of the Gardasil clinical trials. Int J Cancer 2011;128:1354-62.
Zuchna C, Hager M, Tringler B, et al. Diagnostic accuracy of guided cervical biopsies: a prospective multicenter study comparing the histopathology of simultaneous biopsy and cone specimen. Am J Obstet Gynecol 2010;203:321.e1-6.
Cantor SB, Cardenas-Turanzas M, Cox DD, et al. Accuracy of colposcopy in the diagnostic setting compared with the screening setting. Obstet Gynecol 2008;111:7-14.
Eddy DM, Hollingworth W, Caro JJ, et al. Model transparency and validation: a report of the ISPOR-SMDM modeling good research practices task force-7. Value Health 2012;15:843-50.
Braune G, Fiedler T, Hefler L. Arbeitsgemeinschaft für Gynäkologische Onkologie: HPV Task Force der OEGGG - Positionspapier. Österreichische Gesellschaft für Gynäkologie und Geburtshilfe (OEGGG). Available from: http://www.oeggg.at/fileadmin/user_upload/HPV-Positionspapier_150915_WEB.pdf; 2015.
Mendes D, Bains I, Vanni T, et al. Systematic review of model-based cervical screening evaluations. BMC Cancer 2015;15:334.
Stout NK, Goldhaber-Fiebert JD, Ortendahl JD, et al. Trade-offs in cervical cancer prevention: balancing benefits and risks. Arch Intern Med 2008;168:1881-9.
Pedersen K, Sorbye SW, Burger EA, et al. Using decision-analytic modeling to isolate interventions that are feasible, efficient and optimal: an application from the Norwegian cervical cancer screening program. Value Health 2015;18:1088-97.
Burger EA, Pedersen K, Sy S, et al. Choosing wisely: a model-based analysis evaluating the trade-offs in cancer benefit and diagnostic referrals among alternative HPV testing strategies in Norway. Br J Cancer 2017;117:783-90.
Pedersen K, Burger EA, Nygard M, et al. Adapting cervical cancer screening for women vaccinated against human papillomavirus infections: The value of stratifying guidelines. Eur J Cancer 2018;91:68-75.
Ronco G, Dillner J, Elfström KM, et al. Efficacy of HPV-based screening for prevention of invasive cervical cancer: follow-up of four European randomised controlled trials. Lancet (London, England) 2013;383:524-32.
Kyrgiou M, Koliopoulos G, Martin-Hirsch P, et al. Obstetric outcomes after conservative treatment for intraepithelial or early invasive cervical lesions: systematic review and meta-analysis. Lancet (London, England) 2006;367:489-98.
McCaffery K, Waller J, Nazroo J, et al. Social and psychological impact of HPV testing in cervical screening: a qualitative study. Sex Transm Infect 2006;82:169-74.
Goldie SJ, Kuntz KM. A potential error in evaluating cancer screening: a comparison of 2 approaches for modeling underlying disease progression. Med Decis Making 2003;23:232-41.
Pitman R, Fisman D, Zaric GS, et al. Dynamic transmission modeling: a report of the ISPOR-SMDM modeling good research practices task force working group. Med Decis Making 2012;32:712-21.
Van den Bruel A, Jones C, Yang Y, et al. People's willingness to accept overdetection in cancer screening: population survey. BMJ 2015;350:h980.
Sicsic J, Pelletier-Fleury N, Moumjid N. Women's benefits and harms trade-offs in breast cancer screening: results from a discrete-choice experiment. Value Health 2018;21:78-88.

Keywords: Papanicolaou; benefit-harm analysis; cervical cancer; decision analysis; human papillomavirus; p16/Ki-67; screening

0 (Cyclin-Dependent Kinase Inhibitor p16)
0 (Ki-67 Antigen)

Date Created: 20191225 Date Completed: 20210405 Latest Revision: 20221207

20231215

10.1002/ijc.32849

31872420