Zhang Limei, Chen Shuzhao, Wang Weida, Wang Yun, Liang Yang
Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, China.
Front Cell Dev Biol. 2022 Nov 25;10:1021587. doi: 10.3389/fcell.2022.1021587. eCollection 2022.
Extramedullary disease is a manifestation of multiple myeloma, the prognosis of which remains poor even in the era of novel drugs. Therefore, we aimed to develop a predictive model for patients with primary extramedullary multiple myeloma (EMM). Clinical and laboratory data of patients diagnosed with primary EMM between July 2007 and July 2021 were collected and analyzed. Univariate and least absolute shrinkage and selection operation Cox regression analyses (LASSO) were used to select prognostic factors for overall survival (OS) to establish a nomogram prognostic model. The performance of the model was evaluated using concordance index which was internally validated by bootstraps with 1,000 resample, area under the curve (AUCs), and calibration curves. 217 patients were included in this retrospective study. Patients with EMM had a higher rate of belonging to the male sex, age >50 years, advanced Durie-Salmon stage III, hypercalcemia, and low hemoglobin level. Compared with patients with bone-related extramedullary disease, those with extraosseous-related extramedullary disease had a higher frequency of advanced Durie-Salmon stage III, lower rate of hypercalcemia, and elevated prothrombin time. The OS and progression-free survival (PFS) of patients with bone-related extramedullary disease were significantly higher than those of patients with extraosseous-related extramedullary disease. After the univariate and LASSO analyses, six prognostic factors, including performance status, number of extramedullary involved sites, β2-microglobulin, lactate dehydrogenase, monocyte-lymphocyte ratio, and prothrombin time, were integrated to establish a nomogram. The model showed robust discrimination with a concordance index (C-index) of 0.775 (95% confidence interval [CI], 0.713-0.836), internally validated with the corrected C-index of 0.756, and excellent performance in time-dependent AUCs compared with other staging systems. The AUCs for 1-, 3-, and 5-year OS were 0.814, 0.744, and 0.832, respectively. The calibration curves exhibited good consistency between the observed and nomogram-predicted OS. The 5-year OS of patients in the high-risk group (23.3%; 95% CI, 13.9%-39.3%) was much worse than that in the low-risk group (73.0%; 95% CI, 62.5%-85.4%; < 0.001). The nomogram predictive model based on six clinical variables showed good prognostic performance and could better predict individual survival in patients with EMM.
髓外疾病是多发性骨髓瘤的一种表现形式,即使在新型药物时代,其预后仍然很差。因此,我们旨在为原发性髓外多发性骨髓瘤(EMM)患者开发一种预测模型。收集并分析了2007年7月至2021年7月期间诊断为原发性EMM的患者的临床和实验室数据。采用单因素分析以及最小绝对收缩和选择算子Cox回归分析(LASSO)来选择总生存(OS)的预后因素,以建立列线图预后模型。使用一致性指数评估模型的性能,该指数通过1000次重采样的自举法进行内部验证,同时还采用曲线下面积(AUC)和校准曲线进行评估。这项回顾性研究纳入了217例患者。EMM患者中男性、年龄>50岁、Durie-Salmon分期晚期III期、高钙血症以及血红蛋白水平低的比例更高。与骨相关髓外疾病患者相比,骨外相关髓外疾病患者Durie-Salmon分期晚期III期的频率更高、高钙血症发生率更低且凝血酶原时间升高。骨相关髓外疾病患者的OS和无进展生存期(PFS)显著高于骨外相关髓外疾病患者。经过单因素分析和LASSO分析后,整合了六个预后因素,包括体能状态、髓外受累部位数量、β2微球蛋白、乳酸脱氢酶、单核细胞与淋巴细胞比值以及凝血酶原时间,以建立列线图。该模型显示出强大的辨别能力,一致性指数(C指数)为0.775(95%置信区间[CI],0.713 - 0.836),经校正的C指数为0.756进行内部验证,并且与其他分期系统相比,在时间依赖性AUC方面表现出色。1年、3年和5年OS的AUC分别为0.814、0.744和0.832。校准曲线显示观察到的OS与列线图预测的OS之间具有良好的一致性。高危组患者的5年OS(23.3%;95% CI,13.9% - 39.3%)远低于低危组患者(73.0%;95% CI,62.5% - 85.4%;P < 0.001)。基于六个临床变量的列线图预测模型显示出良好的预后性能,能够更好地预测EMM患者的个体生存情况。