Bai Mingjian, Feng Jing, Liu Jie, Li Yunxiang, Xu Yueming, Ma Fucun, Ma Ruiqing, Liang Guowei, Liu Xuekai, Zhao Na
Department of Clinical Laboratory, Aerospace Center Hospital, Beijing, China.
Department of Literature and Science, University of Wisconsin-Madison, Madison, WI, United States.
Front Mol Biosci. 2024 Dec 23;11:1512937. doi: 10.3389/fmolb.2024.1512937. eCollection 2024.
The aim of the present study was to establish a predictive model to predict the peritoneal cancer index (PCI) preoperatively in patients with pseudomyxoma peritonei (PMP).
A total of 372 PMP patients were consecutively included from a prospective follow-up database between 1 June 2013 and 1 June 2023. Nine potential variables, namely, gender, age, Barthel Index (BAI), hemoglobin (Hb), albumin (Alb), D-dimer, carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA 125), and CA 19-9, were estimated using multiple linear regression (MLR) analysis with a stepwise selection procedure. The established MLR model was internally validated using -fold cross-validation. The agreement between the predicted and surgical PCI was assessed using Bland-Altman plots and intraclass correlation (ICC). A value of less than 0.05 was considered statistically significant.
Six independent predictors were confirmed by the stepwise MLR analysis with an value of 0.570. The predicted PCI formula was represented as follows: PCI = 19.567 + 2.091 * Gender (male = 1, female = 0) - 0.643 * Alb +4.201 * Lg (D-dimer) + 2.938 * Lg (CEA) + 5.441 * Lg (CA 125) + 1.802 * Lg (CA 19-9). The agreement between predicted and surgical PCI was assessed using Bland-Altman plots, showing a limit of agreement (LoA) between -15.847 (95%: -17.2646 to -14.4292) and +15.847 (95%: 14.4292-17.2646).
This study represents the first attempt to use an MLR model for the preoperative prediction of PCI in PMP patients. Nevertheless, the MLR model did not perform well enough in predicting preoperative PCI. In the future, more advanced statistical techniques and a radiomics-based CT-PCI-participated MLR model will be developed, which may enhance the predictive ability of PCI.
本研究的目的是建立一个预测模型，用于术前预测黏液性腹膜假瘤（PMP）患者的腹膜癌指数（PCI）。
从2013年6月1日至2023年6月1日的前瞻性随访数据库中连续纳入372例PMP患者。使用逐步选择程序的多元线性回归（MLR）分析估计九个潜在变量，即性别、年龄、Barthel指数（BAI）、血红蛋白（Hb）、白蛋白（Alb）、D-二聚体、癌胚抗原（CEA）、糖类抗原125（CA 125）和CA 19-9。使用留一法交叉验证对建立的MLR模型进行内部验证。使用Bland-Altman图和组内相关系数（ICC）评估预测的PCI与手术PCI之间的一致性。P<0.05被认为具有统计学意义。
逐步MLR分析确认了六个独立预测因子，R²值为0.570。预测PCI公式如下：PCI = 19.567 + 2.091×性别（男性=1，女性=0） - 0.643×Alb + 4.201×lg（D-二聚体） + 2.938×lg（CEA） + 5.441×lg（CA 125） + 1.802×lg（CA 19-9）。使用Bland-Altman图评估预测的PCI与手术PCI之间的一致性，显示一致性界限（LoA）在-15.847（95%：-17.2646至-14.4292）和+15.847（95%：14.4292 - 17.2646）之间。
本研究首次尝试使用MLR模型对PMP患者的术前PCI进行预测。然而，MLR模型在预测术前PCI方面表现不够理想。未来，将开发更先进的统计技术和基于放射组学的CT-PCI参与的MLR模型，这可能会提高PCI的预测能力。
