ArticleValue in health regional issues2022
Mathematical Models for Evaluating Effectiveness and Cost-Effectiveness of Cervical Cancer Control Policies in Populations Including Women Living With Human Immunodeficiency Virus: A Scoping Review.
Article in Value in health regional issues, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Potential Impact of Catch-Up HPV Vaccination on HPV Prevalence and Cervical Cancer Incidence Among Women Living With HIV in South Africa: Results From Two Mathematical Models.Journal of the International AIDS Society · 2026Article
- Awareness, attendance, and attitudes toward cervical cancer screening among HIV-positive Chinese women in Yunnan province: a cross-sectional study.BMC women's health · 2024Article
- Cost-effectiveness of approaches to cervical cancer screening in Malawi: comparison of frequencies, lesion treatment techniques, and risk-stratified approaches.BMC health services research · 2024Article
- Cost-effectiveness of single-visit cervical cancer screening in KwaZulu-Natal, South Africa: a model-based analysis accounting for the HIV epidemic.Frontiers in oncology · 2024Article
- Stochastic dynamics of human papillomavirus delineates cervical cancer progression.Journal of mathematical biology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 5 countries.
Funding
Abstract
objectivesMathematical modeling is increasingly used to inform cervical cancer control policies, and model-based evaluations of such policies in women living with human immunodeficiency virus (HIV) are an emerging research area. We did a scoping review of published literature to identify research gaps and inform future work in this field.
methodsWe systematically searched literature up to April 2022 and included mathematical modeling studies evaluating the effectiveness or cost-effectiveness of cervical cancer prevention strategies in populations including women living with HIV. We extracted information on prevention strategies and modeling approaches.
resultsWe screened 1504 records and included 22 studies, almost half of which focused on South Africa. We found substantial between-study heterogeneity in terms of strategies assessed and modeling approaches used. Fourteen studies evaluated cervical cancer screening strategies, 7 studies assessed human papillomavirus vaccination (with or without screening), and 1 study evaluated the impact of HIV control measures on cervical cancer incidence and mortality. Thirteen conducted cost-effectiveness analyses. Markov cohort state-transition models were used most commonly (n = 12). Most studies (n = 17) modeled the effect of HIV by creating HIV-related health states. Thirteen studies performed model calibration, but 11 did not report the calibration methods used. Only 1 study stated that model code was available upon request.
conclusionsFew model-based evaluations of cervical cancer control strategies have specifically considered women living with HIV. Improvements in model transparency, by sharing information and making model code publicly available, could facilitate the utility of these evaluations for other high disease-burden countries, where they are needed for assisting policy makers.
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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.