Prediction models for patients with esophageal or gastric cancer: A systematic review and meta-analysis

BackgroundClinical prediction models are increasingly used to predict outcomes such as survival in cancer patients. The aim of this study was threefold. First, to perform a systematic review to identify available clinical prediction models for patients with esophageal and/or gastric cancer. Second, to evaluate sources of bias in the included studies. Third, to investigate the predictive performance of the prediction models using meta-analysis.MethodsMEDLINE, EMBASE, PsycINFO, CINAHL, and The Cochrane Library were searched for publications from the year 2000 onwards. Studies describing models predicting survival, adverse events and/or health-related quality of life (HRQoL) for esophageal or gastric cancer patients were included. Potential sources of bias were assessed and a meta-analysis, pooled per prediction model, was performed on the discriminative abilities (c-indices).ResultsA total of 61 studies were included (45 development and 16 validation studies), describing 47 prediction models. Most models predicted survival after a curative resection. Nearly 75% of the studies exhibited bias in at least 3 areas and model calibration was rarely reported. The meta-analysis showed that the averaged c-index of the models is fair (0.75) and ranges from 0.65 to 0.85.ConclusionMost available prediction models only focus on survival after a curative resection, which is only relevant to a limited patient population. Few models predicted adverse events after resection, and none focused on patient’s HRQoL, despite its relevance. Generally, the quality of reporting is poor and external model validation is limited. We conclude that there is a need for prediction models that better meet patients’ information needs, and provide information on both the benefits and harms of the various treatment options in terms of survival, adverse events and HRQoL.

背景
临床预测模型（Clinical prediction models）的应用愈发广泛，多用于预测癌症患者的生存状态等临床结局。本研究确立了三重研究目标：其一，开展系统综述，筛选针对食管及/或胃癌患者的现有临床预测模型；其二，评估纳入研究中的偏倚来源；其三，采用Meta分析（meta-analysis）考察相关预测模型的预测性能。

方法
本研究检索了MEDLINE、EMBASE、PsycINFO、CINAHL及Cochrane图书馆（The Cochrane Library）2000年以来发表的相关文献。纳入研究需针对食管或胃癌患者，且报道了可预测其生存结局、不良事件及/或健康相关生活质量（health-related quality of life, HRQoL）的预测模型。研究人员对潜在偏倚来源进行了评估，并按每一项预测模型开展合并Meta分析，以分析其判别能力（C指数（c-indices））。

结果
最终共纳入61项研究（其中45项为模型开发研究，16项为模型验证研究），共计报道了47项临床预测模型。其中多数模型用于预测患者接受根治性切除术后的生存状态。近75%的研究至少在3个领域存在偏倚，且模型校准度的相关报告极为匮乏。Meta分析结果显示，所有模型的平均C指数为0.75，处于尚可水平，取值范围介于0.65至0.85之间。

结论
现有临床预测模型大多仅聚焦于根治性切除术后的生存结局，但其仅适用于有限的患者人群。仅有极少数模型可预测术后不良事件，且尚无模型关注患者的健康相关生活质量，尽管该指标具有重要临床意义。整体而言，相关研究的报告质量欠佳，且模型的外部验证工作极为有限。综上，当前亟需开发更贴合患者信息需求的预测模型，使其能够从生存结局、不良事件及健康相关生活质量三个维度，为患者提供不同治疗方案的获益与风险相关信息。