Department of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
Department of Transfusion Medicine, West China Hospital, Sichuan University, Chengdu, China.
Cancer Med. 2023 Oct;12(20):20266-20276. doi: 10.1002/cam4.6551. Epub 2023 Oct 9.
Mean platelet volume (MPV), as a marker of platelet activity, has been shown to be an efficient prognostic biomarker in several types of cancer. Using MPV, this study aimed to create and validate a prognostic nomogram to the overall survival in esophageal squamous cell carcinoma (ESCC) patients.
The nomogram was constructed and tested using data from a retrospective study of 1893 patients who were randomly assigned to the training and testing cohorts with a 7:3 randomization. In order to screen out the optimal predictors for overall survival (OS), we conducted the LASSO-cox regression, univariate, and multivariate cox regression analyses. Subsequently, the predictive accuracy of the nomogram was validated in both the training and the testing cohorts. Finally, decision curve analysis (DCA) was used to confirm clinical validity.
Age, MPV, nerve invasion, T stage, and N stage were found as independent prognostic variables for OS and were further developed into a nomogram. The nomogram's prediction accuracy for 1-, 3-, and 5-year OS was 0.736, 0.749, 0.774, and 0.724, 0.719, 0.704 in the training and testing cohorts, respectively. Furthermore, DCA results indicated that nomograms outperformed the AJCC 8th and conventional T, N staging systems in both the training and testing cohorts.
The nomogram, in conjunction with MPV and standard clinicopathological markers, could improve the accuracy of prediction of OS in ESCC patients.
血小板平均体积（MPV）作为血小板活性的标志物，已被证明是多种癌症的有效预后生物标志物。本研究旨在利用 MPV 为食管鳞状细胞癌（ESCC）患者建立和验证一个总生存预后的列线图。
该列线图是通过对 1893 名随机分为训练和测试队列的患者的回顾性研究数据进行构建和测试的，采用 7:3 的随机化分组。为了筛选出总生存（OS）的最佳预测因素，我们进行了 LASSO-cox 回归、单因素和多因素 cox 回归分析。随后，在训练和测试队列中验证了列线图的预测准确性。最后，通过决策曲线分析（DCA）来确认临床有效性。
年龄、MPV、神经侵犯、T 分期和 N 分期是 OS 的独立预后因素，并进一步纳入列线图中。该列线图对 1、3 和 5 年 OS 的预测准确性在训练和测试队列中分别为 0.736、0.749、0.774 和 0.724、0.719、0.704。此外，DCA 结果表明，在训练和测试队列中，列线图均优于 AJCC 8 分期和传统 T、N 分期系统。
列线图结合 MPV 和标准临床病理标志物可提高 ESCC 患者 OS 预测的准确性。
