Background: The aim of the current study was to construct prognostic nomograms for individual risk prediction in elderly patients with osteosarcoma.
Methods: Data for 816 elderly patients (≥ 40 years old) with osteosarcoma between 2004 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) database were randomly assigned to training (N=573) and internal validation (N=243) sets. The essential clinical predictors were identified based on least absolute shrinkage and selection operator (Lasso) Cox regression. Nomograms were constructed to predict the 1-, 3-, and 5-year cancer-specific survival (CSS) and overall survival (OS).
Results: Our LASSO regression analyses of the training set yielded five clinicopathological features (age, chemotherapy, surgery, AJCC stage, and summary stage) in the training cohort for the prognosis of elderly patients with osteosarcoma, while grade was only associated with OS and M stage was only associated with CSS. Construction of nomograms based on these predictors was performed to evaluate the prognosis of elderly patients with osteosarcoma. The C-index, calibration and decision curve analysis also showed the satisfactory performance of these nomograms for prognosis prediction.
Conclusion: The constructed nomograms are helpful tools for exactly predicting the prognosis of elderly patients with osteosarcoma, which could enable patients to be more accurately managed in clinical practice.



中文翻译：

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老年骨肉瘤患者预后列线图的开发和验证

背景：本研究的目的是构建用于预测老年骨肉瘤患者个体风险的预后列线图。
方法：来自监测、流行病学和最终结果 (SEER) 数据库的 2004 年至 2016 年间 816 名老年骨肉瘤患者（≥ 40 岁）的数据被随机分配到培训 (N=573) 和内部验证 (N=243)套。基于最小绝对收缩和选择算子 (Lasso) Cox 回归确定了基本的临床预测因子。构建列线图以预测 1 年、3 年和 5 年癌症特异性生存期 (CSS) 和总生存期 (OS)。
结果：我们对训练集的 LASSO 回归分析在老年骨肉瘤患者预后的训练队列中产生了五个临床病理学特征（年龄、化疗、手术、AJCC 分期和总结期），而分级仅与 OS 相关，M 分期为仅与 CSS 相关联。基于这些预测因子构建列线图以评估老年骨肉瘤患者的预后。C 指数、校准和决策曲线分析也显示了这些列线图在预后预测方面的令人满意的性能。
结论：构建的列线图是准确预测老年骨肉瘤患者预后的有用工具，可以使患者在临床实践中得到更准确的管理。