ArticleCancer science2025
A population-based study using nomograms to predict overall and cancer-specific survival in HPV-associated CSCC.
Article in Cancer science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Development and verification of a competing risk model for forecasting cancer-specific survival in malignant bone tumor patients: an analysis of SEER database.Translational cancer research · 2026Article
- Risk prediction of pneumocystis jirovecii pneumonia in kidney transplant recipients using a clinical nomogram.Frontiers in cellular and infection microbiology · 2026Article
- A population-based study using nomograms to predict overall and cancer-specific survival in HPV-associated CSCC.Cancer science · 2025Article
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Authors and funding
12 authors.
Funding
Abstract
Constructing and validating two nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) in cutaneous squamous cell carcinoma (CSCC) correlated with human papillomavirus (HPV) infection was the main goal of this study. We constructed predictive models for OS and CSS incidence in HPV infection-associated CSCC using information from 2238 patients in the Surveillance, Epidemiology, and End Results (SEER) database and screened the variables by LASSO regression, Cox univariate regression, and Cox multifactorial regression models, which were calibrated and validated by internal and external cohorts. Finally, all patients were categorized into intermediate-risk, low-risk, and high-risk groups based on the optimal threshold calculated from the total score. Multivariate analysis showed that HPV infection status, marital status, tumor metastatic stage, surgical status, radiotherapy status, lymph node biopsy, local lymph node dissection, primary tumor status, and bone metastasis were risk factors for OS and CSS. The C index, the time-dependent area under the receiver-operating characteristic curve, and the column-line diagrams of the calibration plot were among the excellent-performance metrics that were effectively displayed. Moreover, the decision curve analysis of the two nomograms consistently revealed their favorable net benefits spanning 1, 2, and 3 years. In addition, the survival curves indicate that each of the two risk classification systems clearly differentiates high, medium, and low risk groups. These meticulously crafted nomograms stand poised to serve as indispensable instruments in clinical practice, empowering clinicians to adeptly communicate with patients regarding their prognostic outlook over the forthcoming 1, 2, and 3 years.
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