ArticleBMJ open2023
Prognostic prediction models for oropharyngeal squamous cell carcinoma (OPSCC): a protocol for systematic review, critical appraisal and meta-analysis.
Article in BMJ open, 2023. 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.
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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.
- Genetic susceptibility, risk prediction, and druggable targets for oropharyngeal cancer: a UK Biobank study.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
- A machine learning model for predicting adverse prognostic events in patients with neurosyphilis: Results from the DEFEAT-NS study.iScience · 2026Article
- Astragaloside IV represses the immune evasion and acidic microenvironment of oral squamous cell carcinoma.Cellular & molecular biology letters · 2026Article
- Article
- Identifying Data-Driven Clinical Subgroups for Cervical Cancer Prevention With Machine Learning: Population-Based, External, and Diagnostic Validation Study.JMIR public health and surveillance · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionOropharyngeal squamous cell carcinoma (OPSCC) is increasingly prevalent and has significantly heterogeneous risks of survival for diagnosed individuals due to the inter-related risk factors. Precise prediction of the risk of survival for an individual patient with OPSCC presents a useful adjunct to therapeutic decision-making regarding the management of OPSCC. The aim of this systematic review, critical appraisal and meta-analysis is to assess prognostic prediction models for OPSCC and lay a foundation for future research programmes to develop and validate prognostic prediction models for OPSCC. METHODS AND ANALYSIS: This protocol will follow the Preferred Reporting Items for Systematic Review and Meta-Analyses Protocol statement. Based on predefined criteria, electronic databases including MEDLINE, Embase, Web of Science, the Cochrane Library and China National Knowledge Infrastructure (CNKI) will be searched for relevant studies without language restrictions from inception of databases to present. This study will systematically review published prognostic prediction models for survival outcomes in patients with OPSCC, describe their characteristics, compare performance and assess risk of bias and real-world clinical utility. Selection of eligible studies, data extraction and critical appraisal will be conducted independently by two reviewers. A third reviewer will resolve any disagreements. Included studies will be systematically summarised using appropriate tools designed for prognostic prediction modelling studies. Risk of bias and quality of studies will be assessed using the Prediction Model Risk of Bias Assessment Tool and the Transparent Reporting of a multivariable prediction model for individual prognosis or diagnosis. Performance measures of these models will be pooled and analysed with meta-analyses if feasible. ETHICS AND DISSEMINATION: This review will be conducted completely based on published data, so approval from an ethics committee or written consent is not required. The results will be disseminated through a peer-reviewed publication. PROSPERO REGISTRATION NUMBER: CRD42023400272.
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