Choi Woo Jin, Walker Richard, Rajendran Luckshi, Jones Owen, Gravely Annie, Englesakis Marina, Gallinger Steven, Hirschfield Gideon, Hansen Bettina, Sapisochin Gonzalo
From the Department of Surgery, University of Toronto, Toronto, Ontario, Canada.
Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
Ann Surg Open. 2023 Sep 1;4(3):e328. doi: 10.1097/AS9.0000000000000328. eCollection 2023 Sep.
To conduct a systematic review, critical appraisal, and external validation of survival prediction tools for patients undergoing intrahepatic cholangiocarcinoma (iCCA) resection.
Despite the development of several survival prediction tools in recent years for patients undergoing iCCA resections, there is a lack of critical appraisal and external validation of these models.
We conducted a systematic review and critical appraisal of survival and recurrence prediction models for patients undergoing curative-intent iCCA resections. Studies were evaluated based on their model design, risk of bias, reporting, performance, and validation results. We identified the best model and externally validated it using our institution's data.
This review included a total of 31 studies, consisting of 26 studies with original prediction tools and 5 studies that only conducted external validations. Among the 26, 54% of the studies conducted internal validations, 46% conducted external validations, and only 1 study scored a low risk of bias. Harrell's C-statistics ranged from 0.67 to 0.76 for internal validation and from 0.64 to 0.75 for external validation. Only 81% of the studies reported model calibration. Our external validation of the best model (Intrahepatic Cholangiocarcinoma [ICC]-Metroticket) estimated Harrell's and Uno's C-statistics of 0.67 (95% CI: 0.56-0.77) and Uno's time-dependent area under the receiver operating characteristic curve (AUC) of 0.71 (95% CI: 0.53-0.88), with a Brier score of 0.20 (95% CI: 0.15-0.26) and good calibration plots.
Many prediction models have been published in recent years, but their quality remains poor, and minimal methodological quality improvement has been observed. The ICC-Metroticket was selected as the best model (Uno's time-dependent AUC of 0.71) for 5-year overall survival prediction in patients undergoing curative-intent iCCA resection.
对接受肝内胆管癌（iCCA）切除术患者的生存预测工具进行系统评价、批判性评估和外部验证。
尽管近年来针对接受iCCA切除术的患者开发了多种生存预测工具，但这些模型缺乏批判性评估和外部验证。
我们对接受根治性iCCA切除术患者的生存和复发预测模型进行了系统评价和批判性评估。根据模型设计、偏倚风险、报告情况、性能和验证结果对研究进行评估。我们确定了最佳模型，并使用我们机构的数据对其进行外部验证。
本综述共纳入31项研究，其中26项研究有原创预测工具，5项研究仅进行了外部验证。在这26项研究中，54%的研究进行了内部验证，46%进行了外部验证，只有1项研究的偏倚风险较低。内部验证的Harrell's C统计量范围为0.67至0.76，外部验证的范围为0.64至0.75。只有81%的研究报告了模型校准情况。我们对最佳模型（肝内胆管癌[ICC]-Metroticket）的外部验证估计Harrell's和Uno's C统计量为0.67（95%置信区间：0.56 - 0.77），Uno's时间依赖性受试者工作特征曲线下面积（AUC）为0.71（95%置信区间：0.53 - 0.88），Brier评分为0.20（95%置信区间：0.15 - 0.26），校准图良好。
近年来发表了许多预测模型，但其质量仍然较差，且方法学质量的改进甚微。ICC-Metroticket被选为接受根治性iCCA切除术患者5年总生存预测的最佳模型（Uno's时间依赖性AUC为0.71）。
