ArticleCancers2020
Multistate Markov Model to Predict the Prognosis of High-Risk Human Papillomavirus-Related Cervical Lesions.
Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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
10 citing papers in PubMed, 17 citations in OpenAlex.
- Predicting disease progression and mortality in prostate cancer using real-world data-driven time-inhomogeneous Markov models.iScience · 2026Article
- Cost-effectiveness analysis of 9-valent human papillomavirus vaccine combined with screening for cervical cancer in Japan.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025Article
- Carcinogenesis and management of human papillomavirus-associated cervical cancer.International journal of clinical oncology · 2023Review
- Estimating Bidirectional Transitions and Identifying Predictors of Mild Cognitive Impairment.Neurology · 2023Article
- Nucleic acids and proteins carried by exosomes of different origins as potential biomarkers for gynecologic cancers.Molecular therapy oncolytics · 2022Review
- Prognosis of high-risk human papillomavirus-related cervical lesions: A hidden Markov model analysis of a single-center cohort in Japan.Cancer medicine · 2022Article
- Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model.Diabetes, metabolic syndrome and obesity : targets and therapy · 2022Article
- Natural History of Anal Papillomavirus Infection in HIV-Negative Men Who Have Sex With Men Based on a Markov Model: A 5-Year Prospective Cohort Study.Frontiers in public health · 2022Article
- Article
- Human Papillomavirus and Cancers.Cancers · 2020Article
Corrections and comments
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Authors and funding
16 authors at 3 institutions in 1 country.
Funding
Abstract
Cervical intraepithelial neoplasia (CIN) has a natural history of bidirectional transition between different states. Therefore, conventional statistical models assuming a unidirectional disease progression may oversimplify CIN fate. We applied a continuous-time multistate Markov model to predict this CIN fate by addressing the probability of transitions between multiple states according to the genotypes of high-risk human papillomavirus (HPV). This retrospective cohort comprised 6022 observations in 737 patients (195 normal, 259 CIN1, and 283 CIN2 patients at the time of entry in the cohort). Patients were followed up or treated at the University of Tokyo Hospital between 2008 and 2015. Our model captured the prevalence trend satisfactory, particularly for up to two years. The estimated probabilities for 2-year transition to CIN3 or more were the highest in HPV 16-positive patients (13%, 30%, and 42% from normal, CIN1, and CIN2, respectively) compared with those in the other genotype-positive patients (3.1%-9.6%, 7.6%-16%, and 21%-32% from normal, CIN1, and CIN2, respectively). Approximately 40% of HPV 52- or 58-related CINs remained at CIN1 and CIN2. The Markov model highlights the differences in transition and progression patterns between high-risk HPV-related CINs. HPV genotype-based management may be desirable for patients with cervical lesions.
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Registered trials
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