ArticleFrontiers in genetics2021
A New HPV score System Predicts the Survival of Patients With Cervical Cancers.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Survival prediction landscape: an in-depth systematic literature review on activities, methods, tools, diseases, and databases.Frontiers in artificial intelligence · 2024Pooled it
- Risk factors associated with overall survival in patients with cervical cancer: a prospective cohort study in Western China comparing random survival forest and Cox proportional hazards models.Journal of gynecologic oncology · 2026Article
- Article
- Cancer Stem Cells and Their Possible Implications in Cervical Cancer: A Short Review.International journal of molecular sciences · 2022Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Persistent high-risk human papillomavirus (hrHPV) infection is confirmed as the major cause of cervical cancer. According to the HPV infection status, cervical cancer could be generalized as following three subgroups: HPV-negative, pure HPV-infection, and HPV-integration. Currently, the impact of HPV status on cervical cancer prognosis remains under dispute. Therefore, we explored the potential correlation between HPV status and the clinical outcome of cervical cancer, by establishing a robust prognostic predicting model based on a cervical cancer cohort using The Cancer Genome Atlas (TCGA) database. We performed an iCluster algorithm incorporating DNA copy number variation, SNP, DNA methylation, mRNA expression, and miRNA expression profile together and classified the cohort into three clusters. According to defined clusters, we established an HPV score system by weighing resultant gene alterations through random forest and COX models. This prediction tool could help to identify cervical cancer prognosis through evaluating individual HPV infection status and subsequent genetic modification, which might provide insights into HPV-related gene driven cervical cancer treatment strategies, yet its predictive power and robustness need to be further verified with independent cohorts.
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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.