Department of Orthopaedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
Department of Rheumatology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
World J Surg Oncol. 2024 Jun 25;22(1):168. doi: 10.1186/s12957-024-03453-y.
To investigate the prognosis of patients with Multiple Myeloma (MM) after surgery, analyze the risk factors leading to adverse postoperative outcomes, and establish a nomogram.
Clinical data from 154 patients with MM who underwent surgery at our institution between 2007 and 2019 were retrospectively analyzed. Assessing and comparing patients' pain levels, quality of life, and functional status before and after surgery (P < 0.05) were considered statistically significant. The Kaplan-Meier survival curve was used to estimate the median survival time. Adverse postoperative outcomes were defined as worsened symptoms, lesion recurrence, complication grade ≥ 2, or a postoperative survival period < 1 year. Logistic regression analysis was used to determine the prognostic factors. Based on the logistic regression results, a nomogram predictive model was developed and calibrated.
Postoperative pain was significantly alleviated in patients with MM, and there were significant improvements in the quality of life and functional status (P < 0.05). The median postoperative survival was 41 months. Forty-nine patients (31.8%) experienced adverse postoperative outcomes. Multivariate logistic regression analysis identified patient age, duration of MM, International Staging System, preoperative Karnofsky Performance Status, and Hb < 90 g/L as independent factors influencing patient prognosis. Based on these results, a nomogram was constructed, with a C-index of 0.812. The calibration curve demonstrated similarity between the predicted and actual survival curves. Decision curve analysis favored the predictive value of the model at high-risk thresholds from 10% to-69%.
This study developed a nomogram risk prediction model to assist in providing quantifiable assessment indicators for preoperative evaluation of surgical risk.
为了探讨多发性骨髓瘤(MM)患者手术后的预后,分析导致不良术后结局的风险因素,并建立一个列线图。
回顾性分析了 2007 年至 2019 年期间在我院接受手术的 154 例 MM 患者的临床资料。评估并比较了患者手术前后的疼痛水平、生活质量和功能状态(P<0.05)被认为具有统计学意义。Kaplan-Meier 生存曲线用于估计中位生存时间。不良术后结局定义为症状恶化、病变复发、并发症分级≥2 或术后生存时间<1 年。采用 logistic 回归分析确定预后因素。根据 logistic 回归结果,建立并校准了列线图预测模型。
MM 患者术后疼痛明显缓解,生活质量和功能状态显著改善(P<0.05)。中位术后生存时间为 41 个月。49 例(31.8%)患者发生不良术后结局。多因素 logistic 回归分析确定患者年龄、MM 持续时间、国际分期系统、术前卡氏功能状态评分和 Hb<90 g/L 是影响患者预后的独立因素。基于这些结果,构建了一个列线图,C 指数为 0.812。校准曲线表明预测和实际生存曲线之间具有相似性。决策曲线分析表明,该模型在 10%至-69%的高危阈值下具有预测价值。
本研究建立了一个列线图风险预测模型,以协助提供术前手术风险评估的量化评估指标。