Medical Oncology Department, Mohammed VI University Hospital of Marrakech, Marrakech, Morocco.
Faculty of Medicine and Pharmacy, Biosciences and Health Laboratory, Cadi Ayyad University, Marrakech, Morocco.
BMC Cancer. 2023 Oct 20;23(1):1016. doi: 10.1186/s12885-023-11355-7.
Nomogram is a graphic representation containing the expressed factor of the mathematical formula used to define a particular phenomenon. We aim to build and internally validate a nomogram to predict overall survival (OS) in patients diagnosed with lung cancer (LC).
We included 1200 LC patients from a single institution registry diagnosed from 2013 to 2021. The independent prognostic factors of LC patients were identified via cox proportional hazard regression analysis. Based on the results of multivariate cox analysis, we constructed the nomogram to predict the OS of LC patients.
We finally included a total of 1104 LC patients. Age, medical urgency at diagnosis, performance status, radiotherapy, and surgery were identified as prognostic factors, and integrated to build the nomogram. The model performance in predicting prognosis was measured by receiver operating characteristic curve. Calibration plots of 6-, 12-, and 24- months OS showed optimal agreement between observations and model predictions.
We have developed and validated a unique predictive tool that can offer patients with LC an individual OS prognosis. This useful prognostic model could aid doctors in making decisions and planning therapeutic trials.
列线图是一种图形表示，包含用于定义特定现象的数学公式的表达因素。我们旨在构建和内部验证一个列线图，以预测被诊断患有肺癌（LC）的患者的总生存期（OS）。
我们纳入了 2013 年至 2021 年期间来自单一机构登记处的 1200 名 LC 患者。通过 cox 比例风险回归分析确定 LC 患者的独立预后因素。基于多变量 cox 分析的结果，我们构建了列线图来预测 LC 患者的 OS。
我们最终纳入了总共 1104 名 LC 患者。年龄、诊断时的医疗紧急情况、表现状态、放疗和手术被确定为预后因素，并整合到列线图中。该模型在预测预后方面的性能通过接受者操作特征曲线进行测量。6、12 和 24 个月 OS 的校准图显示了观察值和模型预测之间的最佳一致性。
我们已经开发并验证了一种独特的预测工具，可以为 LC 患者提供个体 OS 预后。这个有用的预后模型可以帮助医生做出决策和规划治疗试验。
