Section of Thoracic Surgery, Department of Surgery, University of Chicago, Chicago, Illinois, United States of America.
Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America.
PLoS One. 2024 May 16;19(5):e0303281. doi: 10.1371/journal.pone.0303281. eCollection 2024.
The Risk Analysis Index (RAI) is a frailty assessment tool based on an accumulation of deficits model. We mapped RAI to data from the Society of Thoracic Surgeons (STS) Database to determine whether RAI correlates with postoperative outcomes following lung cancer resection.
METHODOLOGY/PRINCIPAL FINDINGS: This was a national database retrospective observational study based on data from the STS Database. Study patients underwent surgery 2018 to 2020. RAI was divided into four increasing risk categories. The associations between RAI and each of postoperative complications and administrative outcomes were examined using logistic regression models. We also compared the performance of RAI to established risk indices (American Society of Anesthesiology (ASA) and Charlson Comorbidity Index (CCI)) using areas under the Receiver Operating Characteristic (ROC) curves (AUC). Results: Of 29,420 candidate patients identified in the STS Database, RAI could be calculated for 22,848 (78%). Almost all outcome categories exhibited a progressive increase in marginal probability as RAI increased. On multivariable analyses, RAI was significantly associated with an incremental pattern with almost all outcomes. ROC analyses for RAI demonstrated "good" AUC values for mortality (0.785; 0.748) and discharge location (0.791), but only "fair" values for all other outcome categories (0.618 to 0.690). RAI performed similarly to ASA and CCI in terms of AUC score categories.
CONCLUSIONS/SIGNIFICANCE: RAI is associated with clinical and administrative outcomes following lung cancer resection. However, its overall accuracy as a surgical risk predictor is only moderate and similar to ASA and CCI. We do not recommend routine use of RAI for assessment of individual patient risk for major lung resection.
风险分析指数(RAI)是一种基于累积缺陷模型的衰弱评估工具。我们将 RAI 映射到胸外科医师学会(STS)数据库的数据中,以确定 RAI 是否与肺癌切除术后的术后结果相关。
方法/主要发现:这是一项基于 STS 数据库数据的全国性数据库回顾性观察研究。研究患者于 2018 年至 2020 年接受手术。RAI 分为四个递增风险类别。使用逻辑回归模型检查 RAI 与每种术后并发症和管理结果之间的关联。我们还使用接受者操作特征(ROC)曲线下的面积(AUC)比较了 RAI 与既定风险指数(美国麻醉医师学会(ASA)和 Charlson 合并症指数(CCI))的性能。结果:在 STS 数据库中确定的 29420 名候选患者中,可计算出 22848 名(78%)患者的 RAI。几乎所有的结果类别都表现出随着 RAI 的增加而边际概率逐渐增加。在多变量分析中,RAI 与几乎所有结果均呈显著相关的递增模式。RAI 的 ROC 分析显示,死亡率(0.785;0.748)和出院地点(0.791)的 AUC 值“良好”,但其他所有结果类别的 AUC 值均为“一般”(0.618 至 0.690)。RAI 在 AUC 评分类别方面与 ASA 和 CCI 的性能相似。
结论/意义:RAI 与肺癌切除术后的临床和管理结果相关。然而,它作为手术风险预测器的总体准确性仅为中等,与 ASA 和 CCI 相似。我们不建议常规使用 RAI 评估主要肺切除的个体患者风险。