4.6 Article

Predicting Cohort-Specific Cervical Cancer Incidence From Population-Based Surveys of Human Papilloma Virus Prevalence: A Worldwide Study

Journal

AMERICAN JOURNAL OF EPIDEMIOLOGY
Volume 191, Issue 3, Pages 402-412

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/aje/kwab254

Keywords

forecasting; papillomavirus infections; uterine cervical neoplasms

Funding

  1. Bill & Melinda Gates Foundation [OPP 1188709, INV-005318]
  2. Canadian Institutes of Health Research
  3. Bill and Melinda Gates Foundation [INV-005318] Funding Source: Bill and Melinda Gates Foundation

Ask authors/readers for more resources

This study proposes a predictive method called PANDORA, based on HPV prevalence and CCI, to predict CCI among high-risk HPV-positive women and to predict CCI up to 14 years following high-risk HPV detection. The findings show that CCI increases during the 14 years following high-risk HPV detection in unscreened women aged <35 years, but remains mainly constant among women 35 years and older. Age at sexual debut is a significant modifier of CCI. The model accurately reproduces CCI among high-risk HPV-positive women and predicts the annual number of cervical cancer cases and CCI in locations without cancer registry.
Predictions of cervical cancer burden and the impact of measures taken to control this cancer are usually data-demanding and based on complex assumptions. We propose a predictive method (called PANDORA) based on human papillomavirus (HPV) prevalence, measured 1993-2008, and cervical cancer incidence (CCI), measured 1993-2012, in the same birth cohorts from different worldwide locations, informed by data on age at detection of high-risk HPV and sexual debut. The model can predict CCI among high-risk HPV-positive women and predict CCI up to 14 years following high-risk HPV detection. We found CCI to increase during the 14 years following high-risk HPV detection in unscreened women aged <35 years but to remain mainly constant among women 35 years. Age at sexual debut was a significant modifier of CCI. Using our model, we accurately reproduced CCI among high-risk HPV-positive women as observed in cohort studies and in the general population of multiple countries. We also predicted the annual number of cervical cancer cases and CCI in locations with HPV prevalence data but no cancer registry. These findings could inform cervical cancer control programs in settings without cancer registries, as they can be used to predict future cervical cancer burden from population-based surveys of HPV prevalence.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available