In the last 30 years, there has been an increasing incidence of oral cancer worldwide. Earlier detection of oral cancer has been shown to improve survival rates. However, given the relatively low prevalence of this disease, population-wide screening is likely to be inefficient. Risk prediction models could be used to target screening to those at highest risk or to select individuals for preventative interventions. This review (a) systematically identified published models that predict the development of oral cancer and are suitable for use in the general population and (b) described and compared the identified models, focusing on their development, including risk factors, performance and applicability to risk-stratified screening. A search was carried out in November 2022 in the Medline, Embase and Cochrane Library databases to identify primary research papers that report the development or validation of models predicting the risk of developing oral cancer (cancers of the oral cavity or oropharynx). The PROBAST tool was used to evaluate the risk of bias in the identified studies and the applicability of the models they describe. The search identified 11,222 articles, of which 14 studies (describing 23 models), satisfied the eligibility criteria of this review. The most commonly included risk factors were age (n= 20), alcohol consumption (n= 18) and smoking (n= 17). Six of the included models incorporated genetic information and three used biomarkers as predictors. Including information on human papillomavirus status was shown to improve model performance; however, this was only included in a small number of models. Most of the identified models (n= 13) showed good or excellent discrimination (AUROC > 0.7). Only fourteen models had been validated and only two of these validations were carried out in populations distinct from the model development population (external validation). Conclusions: Several risk prediction models have been identified that could be used to identify individuals at the highest risk of oral cancer within the context of screening programmes. However, external validation of these models in the target population is required, and, subsequently, an assessment of the feasibility of implementation with a risk-stratified screening programme for oral cancer.
过去30年间，全球口腔癌发病率持续上升。早期发现已被证实能有效提高患者生存率。然而鉴于该疾病患病率相对较低，开展全民筛查可能效率不足。风险预测模型可用于锁定高危人群进行针对性筛查，或筛选个体实施预防性干预。本综述（a）系统梳理了适用于普通人群的口腔癌发病风险预测模型；（b）重点从模型构建维度（包括风险因素、预测效能及风险分层筛查适用性）对现有模型进行描述与比较。研究团队于2022年11月系统检索Medline、Embase和Cochrane图书馆数据库，筛选报告口腔（腔）癌或口咽癌风险预测模型开发或验证的原始研究论文。采用PROBAST工具评估纳入研究的偏倚风险及其描述模型的适用性。最终从11,222篇文献中筛选出符合标准的14项研究（涵盖23个预测模型）。最常见的风险因素包括年龄（20个模型）、饮酒（18个模型）和吸烟（17个模型）。其中6个模型整合了遗传信息，3个模型采用生物标志物作为预测因子。纳入人乳头瘤病毒感染状态可提升模型性能，但仅有少数模型包含该指标。多数模型（13个）显示出良好或优异的区分度（AUROC > 0.7）。仅14个模型经过验证，其中仅2项验证在独立于模型开发人群的外部群体中实施。结论：现有多个风险预测模型可用于筛查项目中识别口腔癌高危人群，但需在目标人群中开展外部验证，并进一步评估口腔癌风险分层筛查方案的实施可行性。
肿瘤(癌症)患者之家