Xu Jiaxuan, Xu Peipei, Han Qiaoyan, Sun Jingjing, Chen Bing, Dong Xiaoqing
Department of Hematology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China.
Department of Hematology, Jingjiang People's Hospital, Jingjiang, China.
Front Oncol. 2022 Aug 26;12:941714. doi: 10.3389/fonc.2022.941714. eCollection 2022.
This study aimed to comprehensively investigate the relationship between the survival differences and socioeconomic status (SES) in patients with multiple myeloma (MM) and construct a predictive nomogram to assess clinical outcomes of MM patients.
The Surveillance, Epidemiology, and End Results (SEER) census tract-level SES database provides two specialized attributes: SES index and rurality. Using this database, 37,819 patients diagnosed with MM between January 2007 and December 2016 were enrolled. We evaluated the effects of SES index on overall survival (OS) and myeloma-specific survival (MSS) using Kaplan-Meier curves and Cox regression analyses. Thereafter, we included 126 patients with MM from two independent medical centers in China and divided them into training (Center 1) and validation (Center 2) cohorts. Univariate and multivariate Cox analyses were used in the training cohort to construct a nomogram for predicting clinical outcomes. Nomogram performance was assessed using the area under the curve (AUC) and calibration curves.
In the SEER cohort, lower SES was significantly associated with worse OS rates and MSS rates (both < 0.001). Multivariate analysis confirmed SES as an independent predictor of survival. Subgroup analysis indicated an increasing linear trend in survival benefits in non-Hispanic White, married, insured, and urban populations with increasing SES (all < 0.001). In the training cohort, albumin, creatinine, rurality, and SES were confirmed as independent prognostic indicators. A nomogram for OS prediction was developed using these four factors, and it showed satisfactory discrimination and calibration. The 18- and 36-month AUC values of the nomogram were 0.79 and 0.82, respectively. Based on the total nomogram points, patients were categorized into two risk levels with good separation.
SES strongly influences survival disparities in patients with MM. Our nomogram consisting of clinical and sociodemographic characteristics can potentially predict survival outcomes.
本研究旨在全面调查多发性骨髓瘤（MM）患者生存差异与社会经济地位（SES）之间的关系，并构建一个预测列线图以评估MM患者的临床结局。
监测、流行病学和最终结果（SEER）普查区层面的SES数据库提供了两个专门属性：SES指数和乡村属性。利用该数据库，纳入了2007年1月至2016年12月期间诊断为MM的37819例患者。我们使用Kaplan-Meier曲线和Cox回归分析评估SES指数对总生存期（OS）和骨髓瘤特异性生存期（MSS）的影响。此后，我们纳入了来自中国两个独立医疗中心的126例MM患者，并将他们分为训练队列（中心1）和验证队列（中心2）。在训练队列中使用单因素和多因素Cox分析构建用于预测临床结局的列线图。使用曲线下面积（AUC）和校准曲线评估列线图性能。
在SEER队列中，较低的SES与较差的OS率和MSS率显著相关（均P<0.001）。多因素分析证实SES是生存的独立预测因素。亚组分析表明，在非西班牙裔白人、已婚、参保和城市人群中，随着SES的增加，生存获益呈线性增加趋势（均P<0.001）。在训练队列中，白蛋白、肌酐、乡村属性和SES被确认为独立预后指标。使用这四个因素开发了一个用于OS预测的列线图，它显示出令人满意的区分度和校准度。列线图的18个月和36个月AUC值分别为0.79和0.82。根据列线图总分，患者被分为两个风险水平，区分良好。
SES强烈影响MM患者的生存差异。我们由临床和社会人口学特征组成的列线图有可能预测生存结局。
