Literature DB >> 31821501

Estimating the Natural History of Cervical Carcinogenesis Using Simulation Models: A CISNET Comparative Analysis.

Emily A Burger1,2, Inge M C M de Kok3, Emily Groene4, James Killen5, Karen Canfell5,6, Shalini Kulasingam4, Karen M Kuntz, Suzette Matthijsse3, Catherine Regan1, Kate T Simms5,6, Megan A Smith5,6, Stephen Sy1, Fernando Alarid-Escudero7, Vivek Vaidyanathan4, Marjolein van Ballegooijen3, Jane J Kim1.   

Abstract

BACKGROUND: The natural history of human papillomavirus (HPV)-induced cervical cancer (CC) is not directly observable, yet the age of HPV acquisition and duration of preclinical disease (dwell time) influences the effectiveness of alternative preventive policies. We performed a Cancer Intervention and Surveillance Modeling Network (CISNET) comparative modeling analysis to characterize the age of acquisition of cancer-causing HPV infections and implied dwell times for distinct phases of cervical carcinogenesis.
METHODS: Using four CISNET-cervical models with varying underlying structures but fit to common US epidemiological data, we estimated the age of acquisition of causal HPV infections and dwell times associated with three phases of cancer development: HPV, high-grade precancer, and cancer sojourn time. We stratified these estimates by HPV genotype under both natural history and CC screening scenarios, because screening prevents cancer development that affects the mix of detected cancers.
RESULTS: The median time from HPV acquisition to cancer detection ranged from 17.5 to 26.0 years across the four models. Three models projected that 50% of unscreened women acquired their causal HPV infection between ages 19 and 23 years, whereas one model projected these infections occurred later (age 34 years). In the context of imperfect compliance with US screening guidelines, the median age of causal infection was 4.4-15.9 years later compared with model projections in the absence of screening.
CONCLUSIONS: These validated CISNET-CC models, which reflect some uncertainty in the development of CC, elucidate important drivers of HPV vaccination and CC screening policies and emphasize the value of comparative modeling when evaluating public health policies.
© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Year:  2020        PMID: 31821501      PMCID: PMC7492768          DOI: 10.1093/jnci/djz227

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


  28 in total

1.  A population-based study of human papillomavirus genotype prevalence in the United States: baseline measures prior to mass human papillomavirus vaccination.

Authors:  Cosette M Wheeler; William C Hunt; Jack Cuzick; Erika Langsfeld; Amanda Pearse; George D Montoya; Michael Robertson; Catherine A Shearman; Philip E Castle
Journal:  Int J Cancer       Date:  2012-06-20       Impact factor: 7.396

Review 2.  Human papillomavirus infection and the multistage carcinogenesis of cervical cancer.

Authors:  Mark Schiffman; Nicolas Wentzensen
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-04       Impact factor: 4.254

3.  Non-progression of cervical intraepithelial neoplasia estimated from population-screening data.

Authors:  A B Bos; M van Ballegooijen; G J van Oortmarssen; M E van Marle; J D Habbema; E Lynge
Journal:  Br J Cancer       Date:  1997       Impact factor: 7.640

4.  Persistence of type-specific human papillomavirus infection among cytologically normal women.

Authors:  A Hildesheim; M H Schiffman; P E Gravitt; A G Glass; C E Greer; T Zhang; D R Scott; B B Rush; P Lawler; M E Sherman
Journal:  J Infect Dis       Date:  1994-02       Impact factor: 5.226

5.  Clinical progression of high-grade cervical intraepithelial neoplasia: estimating the time to preclinical cervical cancer from doubly censored national registry data.

Authors:  Margaretha A Vink; Johannes A Bogaards; Folkert J van Kemenade; Hester E de Melker; Chris J L M Meijer; Johannes Berkhof
Journal:  Am J Epidemiol       Date:  2013-07-28       Impact factor: 4.897

6.  Epidemiological evidence for age-dependent regression of pre-invasive cervical cancer.

Authors:  G J van Oortmarssen; J D Habbema
Journal:  Br J Cancer       Date:  1991-09       Impact factor: 7.640

Review 7.  Systematic review of model-based cervical screening evaluations.

Authors:  Diana Mendes; Iren Bains; Tazio Vanni; Mark Jit
Journal:  BMC Cancer       Date:  2015-05-01       Impact factor: 4.430

8.  Human papillomavirus genotype distributions: implications for vaccination and cancer screening in the United States.

Authors:  Cosette M Wheeler; William C Hunt; Nancy E Joste; Charles R Key; Wim G V Quint; Philip E Castle
Journal:  J Natl Cancer Inst       Date:  2009-03-24       Impact factor: 13.506

9.  The predicted effect of changes in cervical screening practice in the UK: results from a modelling study.

Authors:  K Canfell; R Barnabas; J Patnick; V Beral
Journal:  Br J Cancer       Date:  2004-08-02       Impact factor: 7.640

10.  High-risk HPV type-specific clearance rates in cervical screening.

Authors:  N W J Bulkmans; J Berkhof; S Bulk; M C G Bleeker; F J van Kemenade; L Rozendaal; P J F Snijders; C J L M Meijer
Journal:  Br J Cancer       Date:  2007-03-06       Impact factor: 7.640

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2.  Modeling Strategies to Optimize Cancer Screening in USPSTF Guideline-Noncompliant Women.

Authors:  Glen B Taksler; Elisabeth F P Peterse; Isarah Willems; Kevin Ten Haaf; Erik E L Jansen; Inge M C M de Kok; Nicolien T van Ravesteyn; Harry J de Koning; Iris Lansdorp-Vogelaar
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3.  Impact of disruptions and recovery for established cervical screening programs across a range of high-income country program designs, using COVID-19 as an example: A modelled analysis.

Authors:  Megan A Smith; Emily A Burger; Alejandra Castanon; Inge M C M de Kok; Sharon J B Hanley; Matejka Rebolj; Michaela T Hall; Erik E L Jansen; James Killen; Xavier O'Farrell; Jane J Kim; Karen Canfell
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4.  The Differential Risk of Cervical Cancer in HPV-Vaccinated and -Unvaccinated Women: A Mathematical Modeling Study.

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Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2021-04-09       Impact factor: 4.090

5.  Impact of COVID-19-related care disruptions on cervical cancer screening in the United States.

Authors:  Emily A Burger; Erik El Jansen; James Killen; Inge McM de Kok; Megan A Smith; Stephen Sy; Niels Dunnewind; Nicole G Campos; Jennifer S Haas; Sarah Kobrin; Aruna Kamineni; Karen Canfell; Jane J Kim
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6.  Projected time to elimination of cervical cancer in the USA: a comparative modelling study.

Authors:  Emily A Burger; Megan A Smith; James Killen; Stephen Sy; Kate T Simms; Karen Canfell; Jane J Kim
Journal:  Lancet Public Health       Date:  2020-02-10

7.  A proposed new generation of evidence-based microsimulation models to inform global control of cervical cancer.

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Journal:  Prev Med       Date:  2021-03-04       Impact factor: 4.018

8.  Risk of cervical intraepithelial neoplasia grade 3 or higher (CIN3+) among women with HPV-test in 1990-1992, a 30-year follow-up study.

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Journal:  Infect Agent Cancer       Date:  2021-06-22       Impact factor: 2.965

9.  The road to cervical cancer elimination in Malaysia: Evaluation of the impact and cost-effectiveness of human papillomavirus screening with self-collection and digital registry support.

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Journal:  Int J Cancer       Date:  2021-08-25       Impact factor: 7.316

10.  The Impact of Different Screening Model Structures on Cervical Cancer Incidence and Mortality Predictions: The Maximum Clinical Incidence Reduction (MCLIR) Methodology.

Authors:  Inge M C M de Kok; Emily A Burger; Steffie K Naber; Karen Canfell; James Killen; Kate Simms; Shalini Kulasingam; Emily Groene; Stephen Sy; Jane J Kim; Marjolein van Ballegooijen
Journal:  Med Decis Making       Date:  2020-06-03       Impact factor: 2.583

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