Mathematical Institute, Leiden University, Leiden, The Netherlands.
Department of Orthopaedic Surgery, Leiden University Medical Center, Leiden, The Netherlands.
J Surg Oncol. 2021 Mar;123(4):1050-1056. doi: 10.1002/jso.26337. Epub 2020 Dec 17.
A dynamic prediction model for patients with soft tissue sarcoma of the extremities was previously developed to predict updated overall survival probabilities throughout patient follow-up. This study updates and externally validates the dynamic model.
Data from 3826 patients with high-grade extremity soft tissue sarcoma, treated surgically with curative intent were used to update the dynamic PERsonalised SARcoma Care (PERSARC) model. Patients were added to the model development cohort and grade was included in the model. External validation was performed with data from 1111 patients treated at a single tertiary center.
Calibration plots show good model calibration. Dynamic C-indices suggest that the model can discriminate between high- and low-risk patients. The dynamic C-indices at 0, 1, 2, 3, 4, and 5 years after surgery were equal to 0.697, 0.790, 0.822, 0.818, 0.812, and 0.827, respectively.
Results from the external validation show that the dynamic PERSARC model is reliable in predicting the probability of surviving an additional 5 years from a specific prediction time point during follow-up. The model combines patient-, treatment-specific and time-dependent variables such as local recurrence and distant metastasis to provide accurate survival predictions throughout follow-up and is available through the PERSARC app.
先前已开发出用于预测肢体软组织肉瘤患者更新后总体生存概率的动态预测模型，用于对患者随访期间进行预测。本研究对该动态模型进行了更新和外部验证。
利用 3826 例高分级肢体软组织肉瘤患者的手术治疗数据，以明确高复发风险患者的特征，建立并验证预测模型。通过将患者纳入模型开发队列并将分级纳入模型来更新动态个体化软组织肉瘤管理（PERSARC）模型。通过单一的三级中心治疗的 1111 例患者的数据进行外部验证。
校准图显示模型具有良好的校准度。动态 C 指数表明该模型可以区分高风险和低风险患者。术后 0、1、2、3、4 和 5 年的动态 C 指数分别等于 0.697、0.790、0.822、0.818、0.812 和 0.827。
外部验证结果表明，动态 PERSARC 模型能够可靠地预测从特定随访时间点开始的 5 年内的生存概率。该模型结合了患者、治疗特异性和时间依赖性变量（如局部复发和远处转移），可在整个随访期间提供准确的生存预测，且可通过 PERSARC 应用程序获得。
