Non-Cochrane · DTA · PM42137481
Risk prediction models for oral squamous cell carcinoma and oral potentially malignant disorders in Asian populations: a systematic review and meta-analysis.
Drokow Emmanuel Kwateng, Amponsem Boateng Cecilia, Zhang Yongping, et al. · Frontiers in oral health · 2026 · PubMed · doi:10.3389/froh.2026.1779476
Findings
Population Asymptomatic adults in Asian countries (screening and community settings)
8 findings
| Multivariable risk prediction models for OSCC/OPMD | Reference standard (histopathological or clinical diagnosis) | Sensitivity Community, clinic and hospital based screening in Asia · Validation type: external (3 studies) vs internal only (4 studies) | Meta-regression coefficient (logit sensitivity) 0.982 GRADE not reported 7 studies |
| Multivariable risk prediction models for OSCC/OPMD | Reference standard (histopathological or clinical diagnosis) | Specificity Community, clinic and hospital based screening in Asia · Validation type: external (3 studies) vs internal only (4 studies) | Meta-regression coefficient (logit false positive rate) -0.421 GRADE not reported 7 studies |
| Multivariable risk prediction models for OSCC/OPMD | Reference standard (histopathological or clinical diagnosis) | Sensitivity Community, clinic and hospital based screening in Asia · Target condition: combined OPMD/OSCC (3 studies) vs OSCC only (4 studies) | Meta-regression coefficient (logit sensitivity) 1.217 GRADE not reported 7 studies |
| Multivariable risk prediction models for OSCC/OPMD | Reference standard (histopathological or clinical diagnosis) | Specificity Community, clinic and hospital based screening in Asia · Random-effects HSROC model; overall | Pooled specificity 0.8 [0.67, 0.89] GRADE not reported 7 studies |
| Multivariable risk prediction models for OSCC/OPMD | Reference standard (histopathological or clinical diagnosis) | Specificity Community, clinic and hospital based screening in Asia · Common effect model; overall | Pooled specificity 0.56 [0.56, 0.56] GRADE not reported 7 studies |
| Multivariable risk prediction models for OSCC/OPMD | Reference standard (histopathological or clinical diagnosis) | Sensitivity Community, clinic and hospital based screening in Asia · Random-effects HSROC model; overall | Pooled sensitivity 0.84 [0.78, 0.89] GRADE not reported 7 studies |
| Multivariable risk prediction models for OSCC/OPMD | Reference standard (histopathological or clinical diagnosis) | Sensitivity Community, clinic and hospital based screening in Asia · Common effect model; overall | Pooled sensitivity 0.77 [0.76, 0.78] GRADE not reported 7 studies |
| Multivariable risk prediction models for OSCC/OPMD | Reference standard (histopathological or clinical diagnosis) | Specificity Community, clinic and hospital based screening in Asia · Target condition: combined OPMD/OSCC (3 studies) vs OSCC only (4 studies) | Meta-regression coefficient (logit false positive rate) -0.503 GRADE not reported 7 studies |
Included primary studies 19
Open in Studies| Study | Year | Also included by | Outcomes it informs here | Trial data |
|---|---|---|---|---|
| Miao 2016 Association of microRNA polymorphisms with the risk of head and neck squamous cell carcinoma in a Chinese population: a case-control study. PMID:27515039 | 2016 | 1 other review | not stated | not extracted yet |
| Adeoye 2022 Performance of a simplified scoring system for risk stratification in oral cancer and oral potentially malignant disorders screening DOI:10.1111/jop.13293 | 2022 | this review only | not stated | not extracted yet |
| Adeoye 2022 Performance of a simplified scoring system for risk stratification in oral cancer and oral potentially malignant disorders screening. PMID:35312123 | 2022 | this review only | not stated | not extracted yet |
| Amarasinghe 2010 Derivation and validation of a risk-factor model for detection of oral potentially malignant disorders in populations with high prevalence DOI:10.1038/sj.bjc.6605778 | 2010 | this review only | not stated | not extracted yet |
| Amarasinghe 2010 Derivation and validation of a risk-factor model for detection of oral potentially malignant disorders in populations with high prevalence. PMID:20628386 | 2010 | this review only | not stated | not extracted yet |
| Chen F 2018 Nomograms and risk scores for predicting the risk of oral cancer in different sexes: a large-scale case-control study. PMID:30026853 | 2018 | this review only | not stated | not extracted yet |
| Chen Q 2021 Association between serum arsenic and oral cancer risk: A case‐control study in southeast China DOI:10.1111/cdoe.12633 | 2021 | this review only | not stated | not extracted yet |
| Chen Q 2022 Association between serum arsenic and oral cancer risk: A case-control study in southeast China. PMID:33748987 | 2022 | this review only | not stated | not extracted yet |
| Chiu 2002 A Scoring System for the Early Detection of Oral Submucous Fibrosis Based on a Self‐administered Questionnaire DOI:10.1111/j.1752-7325.2002.tb03417.x | 2002 | this review only | not stated | not extracted yet |
| Chiu 2002 A scoring system for the early detection of oral submucous fibrosis based on a self-administered questionnaire. PMID:14700086 | 2002 | this review only | not stated | not extracted yet |
| Chung 2017 Combined Genetic Biomarkers and Betel Quid Chewing for Identifying High-Risk Group for Oral Cancer Occurrence DOI:10.1158/1940-6207.capr-16-0259 | 2017 | this review only | not stated | not extracted yet |
| Chung 2017 Combined Genetic Biomarkers and Betel Quid Chewing for Identifying High-Risk Group for Oral Cancer Occurrence. PMID:28400480 | 2017 | this review only | not stated | not extracted yet |
| Hung 2020 Assessment of the Risk of Oral Cancer Incidence in A High-Risk Population and Establishment of A Predictive Model for Oral Cancer… DOI:10.3390/ijerph17020665 | 2020 | this review only | not stated | not extracted yet |
| Hung 2020 Assessment of the Risk of Oral Cancer Incidence in A High-Risk Population and Establishment of A Predictive Model for Oral Cancer… PMID:31968579 | 2020 | this review only | not stated | not extracted yet |
| Krishna Rao 2016 A screening model for oral cancer using risk scores: development and validation DOI:10.1111/cdoe.12192 | 2015 | this review only | not stated | not extracted yet |
| Krishna Rao 2016 A screening model for oral cancer using risk scores: development and validation. PMID:26308953 | 2016 | this review only | not stated | not extracted yet |
| Miao 2016 Association of microRNA polymorphisms with the risk of head and neck squamous cell carcinoma in a Chinese population: a case–control study DOI:10.1186/s40880-016-0136-9 | 2016 | this review only | not stated | not extracted yet |
| Wang 2019 A personalized computational model predicts cancer risk level of oral potentially malignant disorders and its web application for… DOI:10.1111/jop.12983 | 2020 | this review only | not stated | not extracted yet |
| Wang 2020 A personalized computational model predicts cancer risk level of oral potentially malignant disorders and its web application for… PMID:31823403 | 2020 | this review only | not stated | not extracted yet |
Overlap with other reviews
Reviews that include the same primary studies are not independent evidence. Shared counts match studies by PMID, DOI or NCT, and otherwise by author and year (a probable match). Only the non-Cochrane dental reviews have study lists, so overlap with Cochrane reviews is not counted yet.
| Review | Shared studies | Jaccard |
|---|---|---|
| Assessment of genetic susceptibility in patients with oral squamous cell carcinoma: a systematic review and meta-analysis. (2026) | 1 | 0.00 |
Review question
| Element | Planned (methods) | Found (results) |
|---|---|---|
| Population | Asymptomatic adults aged 18 years or older in any Asian country, no prior OSCC diagnosis | Asian community, clinic and hospital screening populations (n=171 to 1,719,191 per study) |
| Intervention | Development or validation of multivariable risk prediction models for OSCC or OPMD | Multivariable risk models: logistic regression (8), Cox regression (1), machine learning (2) (n=11) |
| Comparison | Reference standard (histopathological diagnosis for OSCC; clinical or histological diagnosis for OPMD) | Reference standard diagnosis of OSCC or OPMD |
| Outcomes | Incident OSCC or detection of OPMD; sensitivity, specificity, AUC | Pooled sensitivity 0.84, pooled specificity 0.80 (n=7 studies in meta-analysis) |
| Study designs | Cohort, cross-sectional and case-control studies, prospective or retrospective | 9 prospective and 2 retrospective studies (n=11) |
| Timing | Incident OSCC over defined follow-up or OPMD at point of screening | Not specified |