A Systematic Review of Risk Prediction Models for Esophageal Adenocarcinoma in the General Population

Background and Aims

Risk prediction models can identify individuals at high risk of esophageal adenocarcinoma. This systematic review aimed to critically appraise the available models for projecting absolute risk of esophageal adenocarcinoma in the general population.

Methods

We searched Medline, Embase, and Cochrane Library databases for studies of risk prediction models for esophageal adenocarcinoma. Data were extracted from eligible studies according to the checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies. Risk of bias and applicability were assessed using the prediction model risk of bias assessment tool.

Results

We identified 7 studies. Age, sex, gastroesophageal reflux disease, body mass index, and tobacco smoking were the most common predictors. The area under the receiver operating characteristic curve ranged between 0.76 and 0.88 in the derivation datasets. The models based on 2 cohort studies showed good agreement between observed and predicted risks. All studies had at least 1 domain with high risk of bias, primarily attributable to methodological shortcomings in the data analysis.

Conclusion

Most risk prediction models showed good performance in identifying individuals at high risk of esophageal adenocarcinoma. Validation in external populations and cost-effectiveness evaluation are needed before these models can be applied in public health and clinical practice.