ArticleJournal of the Royal Statistical Society. Series A, (Statistics in Society)2015
A joint model of persistent human papillomavirus infection and cervical cancer risk: Implications for cervical cancer screening.
Article in Journal of the Royal Statistical Society. Series A, (Statistics in Society), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- A Comparison of Methods for Modeling Multistate Cancer Progression Using Screening Data with Censoring after Intervention.Medical decision making : an international journal of the Society for Medical Decision Making · 2026Article
- Nationwide registry-based trial of risk-stratified cervical screening.International journal of cancer · 2025Article
- A progressive three-state model to estimate time to cancer: a likelihood-based approach.BMC medical research methodology · 2022Article
- Reconstructing contact network structure and cross-immunity patterns from multiple infection histories.PLoS computational biology · 2021Article
- A study of type-specific HPV natural history and implications for contemporary cervical cancer screening programs.EClinicalMedicine · 2020Article
- Mixture models for undiagnosed prevalent disease and interval-censored incident disease: applications to a cohort assembled from electronic health records.Statistics in medicine · 2017Article
- Targeting Persistent Human Papillomavirus Infection.Viruses · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
New cervical cancer screening guidelines in the US and many European countries recommend that women get tested for human papillomavirus (HPV). To inform decisions about screening intervals, we calculate the increase in precancer/cancer risk per year of continued HPV infection. However, both time to onset of precancer/cancer and time to HPV clearance are interval-censored, and onset of precancer/cancer strongly informatively censors HPV clearance. We analyze this bivariate informatively interval-censored data by developing a novel joint model for time to clearance of HPV and time to precancer/cancer using shared random-effects, where the estimated mean duration of each woman's HPV infection is a covariate in the submodel for time to precancer/cancer. The model was fit to data on 9,553 HPV-positive/Pap-negative women undergoing cervical cancer screening at Kaiser Permanente Northern California, data that were pivotal to the development of US screening guidelines. We compare the implications for screening intervals of this joint model to those from population-average marginal models of precancer/cancer risk. In particular, after 2 years the marginal population-average precancer/cancer risk was 5%, suggesting a 2-year interval to control
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.