He Jiaxiang, Xiao Wei, Zhao Qian, Lin Cong, Hou Tieying, Sun Zhaohui, Cao Donglin
The Affiliated Guangdong Second Provincial General Hospital of Jinan University Guangzhou, Guangdong, China.
Department of Laboratory Medicine, General Hospital of Southern Theater Command Guangzhou, Guangdong, China.
Am J Cancer Res. 2025 May 15;15(5):2111-2126. doi: 10.62347/AAFK9855. eCollection 2025.
This study aimed to establish a short-term risk assessment model for patients with newly diagnosed multiple myeloma (NDMM), to augment the current prognosis assessments of MM patients. This model serves as a reference for evaluating the short-term remission of patients. Between January 2013 and March 2023, a total of 232 NDMM patients were enrolled in the Hematology department. The cohort between January 2013 and October 2020 was selected as the training set (n=165) and the cohort between November 2020 and March 2023 was used as the internal validation set (n=67). Using univariate and multivariate forward stepwise Cox analysis, the determined prognostic factors were urinary immunoglobulin G (IgG), carbon dioxide combining power (COCP), and total protein (TP). A 3-prognostic factor Nomogram model was established based on Cox regression. The area under the curve (AUC) of the Nomogram in 4-, 5- and 6-month complete remission (CR) was 0.777, 0.722, and 0.708, and the C index was 0.691 (0.661-0.721). Kaplan-Meier curve analysis indicated that the CR rate of the high-risk group was lower than the low-risk group (training set P<0.001, internal validation set P=0.018), which exhibited a better stratification of patients than the International Staging System (ISS, training set P=0.850, internal validation set P=0.900), Revised International Staging System (R-ISS, training set P=0.740, internal validation set P=0.720) and the Second Revision of the ISS (R2-ISS, training set P=0.480, internal validation set P=0.590). This study effectively constructed a Nomogram for short-term risk assessment of NDMM patients based on three widely used clinical markers, thereby enriching factors related to NDMM prognosis and aiding in the evaluation of the short-term complete remission.
本研究旨在建立新诊断多发性骨髓瘤（NDMM）患者的短期风险评估模型，以完善目前对MM患者的预后评估。该模型为评估患者的短期缓解情况提供参考。2013年1月至2023年3月期间，血液科共纳入232例NDMM患者。将2013年1月至2020年10月的队列作为训练集（n = 165），2020年11月至2023年3月的队列作为内部验证集（n = 67）。采用单因素和多因素向前逐步Cox分析，确定的预后因素为尿免疫球蛋白G（IgG）、二氧化碳结合力（COCP）和总蛋白（TP）。基于Cox回归建立了包含3个预后因素的列线图模型。该列线图在4个月、5个月和6个月完全缓解（CR）时的曲线下面积（AUC）分别为0.777、0.722和0.708，C指数为0.691（0.661 - 0.721）。Kaplan-Meier曲线分析表明，高风险组的CR率低于低风险组（训练集P < 0.001，内部验证集P = 0.018），与国际分期系统（ISS，训练集P = 0.850，内部验证集P = 0.900）、修订国际分期系统（R-ISS，训练集P = 0.740，内部验证集P = 0.720）和国际分期系统第二次修订版（R2-ISS，训练集P = 0.480，内部验证集P = 0.590）相比，该模型对患者的分层效果更好。本研究基于三种广泛应用的临床标志物，有效构建了NDMM患者短期风险评估的列线图，从而丰富了与NDMM预后相关的因素，并有助于评估短期完全缓解情况。
