Department of Pharmacy, Huadong Hospital, Fudan University, Shanghai, China.
Department of Radiology, Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine (TCM), Shanghai, China.
Front Endocrinol (Lausanne). 2024 May 13;15:1371910. doi: 10.3389/fendo.2024.1371910. eCollection 2024.
This study represented the inaugural effort to develop predictive survival nomograms for metastatic soft tissue sarcoma (mSTS) patients in the era of immune checkpoint inhibitors.
From the Surveillance, Epidemiology, and End Results (SEER) program database, we extracted 3078 eligible patients with mSTS between 2016 and 2022. Kaplan-Meier survival analysis, univariate and multivariable Cox analyses, and univariate and multivariable logistic analyses were conducted. Subsequently, predictive nomograms were constructed. Clinical effectiveness was validated using the area under the curve (AUC), calibration curve, and decision curve analysis (DCA) methods.
We used the SEER database to include 3078 eligible patients with mSTS between 2016 and 2022. All the eligible patients were randomly allocated in a ratio of 6:4 and stratified into a training group (n = 1846) and a validation group (n = 1232). In the multivariate Cox analysis, age, race, marital status, pathological grade, histologic subtype, surgery, and chemotherapy were identified as independent prognostic factors. These factors were used to construct the nomogram to predict the 1-, 3-, and 5-year OS of mSTS patients. The C-index for the training cohort and the validation cohort was 0.722(95% confidence interval [CI]: 0.708-0.736), and 0.716(95% CI: 0.698-0.734), respectively. The calibration curves for 1-, 3-, and 5-year OS probability demonstrated excellent calibration between the predicted and the actual survival. The AUC values of the nomogram at 1-, 3-, and 5-year were 0.785, 0.767, and 0.757 in the training cohort, 0.773, 0.754, and 0.751 in the validation cohort, respectively. Furthermore, DCA indicated the favorable clinical utility of the nomogram in both cohorts. The risk stratification system was constructed using the established nomogram, which enhanced prediction accuracy, aided clinicians in identifying high-risk patients and informing treatment decisions.
This study marked the inaugural effort in constructing predictive survival nomograms mSTS patients in the era of immune checkpoint inhibitors. The robustly constructed nomograms, alongside actual outcomes, offered valuable insights to inform follow-up management strategies.
本研究旨在开发免疫检查点抑制剂时代转移性软组织肉瘤（mSTS）患者的预测生存列线图，这是首次尝试。
我们从监测、流行病学和最终结果（SEER）计划数据库中提取了 2016 年至 2022 年间 3078 例符合条件的 mSTS 患者。进行 Kaplan-Meier 生存分析、单变量和多变量 Cox 分析、单变量和多变量逻辑分析。随后，构建预测列线图。使用曲线下面积（AUC）、校准曲线和决策曲线分析（DCA）方法验证临床效果。
我们使用 SEER 数据库纳入了 2016 年至 2022 年间的 3078 例符合条件的 mSTS 患者。所有合格患者被随机分为 6:4 的比例，并分为训练组（n = 1846）和验证组（n = 1232）。在多变量 Cox 分析中，年龄、种族、婚姻状况、病理分级、组织学亚型、手术和化疗被确定为独立的预后因素。这些因素被用于构建预测 mSTS 患者 1、3 和 5 年 OS 的列线图。训练队列和验证队列的 C 指数分别为 0.722（95%置信区间[CI]：0.708-0.736）和 0.716（95%CI：0.698-0.734）。1、3 和 5 年 OS 概率的校准曲线表明，预测生存率与实际生存率之间具有极好的一致性。在训练队列中，列线图在 1、3 和 5 年的 AUC 值分别为 0.785、0.767 和 0.757，在验证队列中，分别为 0.773、0.754 和 0.751。此外，DCA 表明该列线图在两个队列中的临床实用性都很好。使用建立的列线图构建风险分层系统，提高了预测准确性，帮助临床医生识别高危患者并为治疗决策提供信息。
本研究首次构建了免疫检查点抑制剂时代 mSTS 患者的预测生存列线图。稳健构建的列线图以及实际结果为制定随访管理策略提供了有价值的见解。
