Department of Radiation Oncology, Fudan University Shanghai Cancer Center, 270 Dong An Road, Shanghai, 200032, China.
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
Eur Arch Otorhinolaryngol. 2024 Jan;281(1):181-192. doi: 10.1007/s00405-023-08173-9. Epub 2023 Aug 8.
To assess the impact of body dose on survival outcomes in nasopharyngeal carcinoma (NPC) patients and to create novel nomograms incorporating body dose parameters for predicting survival.
594 of non-metastasis NPC patients (training group, 396; validation group, 198) received intensity-modulated radiation therapy at our institution from January 2012 to December 2016. Patient characteristics, body dose parameters in dose-volume histogram (DVH) and hematology profiles were collected for predicting overall survival (OS) and progression-free survival (PFS). Nomograms for OS and PFS were developed using the selected predictors. Each nomogram was evaluated based on its C-index and calibration curve.
Body dose-based risk score for OS (RS), N stage, age, and induction chemotherapy were independent predictors for OS, with a C-index of 0.784 (95% CI 0.749-0.819) in the training group and 0.763 (95% CI 0.715-0.810) in the validation group for the nomogram. As for PFS, the most important predictors were the body dose-based risk score for PFS (RS) N stage, and induction chemotherapy. C-index of PFS nomogram was 0.706 (95% CI 0.681-0.720) in the training group and 0.691 (95% CI 0.662-0.711) in the validation group. The two models outperformed the TNM staging system in predicting outcomes.
Body dose coverage is a useful predictor of prognosis in clinical routine patients. The novel nomograms integrating body dose parameters can precisely predict OS and PFS in NPC patients.
评估身体剂量对鼻咽癌（NPC）患者生存结果的影响，并创建包含身体剂量参数的新诺模图，以预测生存。
本研究纳入了 594 例未发生转移的 NPC 患者（训练组 396 例，验证组 198 例），他们均于 2012 年 1 月至 2016 年 12 月在我院接受调强放疗。收集患者特征、剂量体积直方图（DVH）中的身体剂量参数和血液学特征，用于预测总生存（OS）和无进展生存（PFS）。使用选定的预测因子建立 OS 和 PFS 的诺模图。每个诺模图都基于其 C 指数和校准曲线进行评估。
基于身体剂量的 OS 风险评分（RS）、N 分期、年龄和诱导化疗是 OS 的独立预测因子，在训练组中的 C 指数为 0.784（95%CI 0.749-0.819），在验证组中的 C 指数为 0.763（95%CI 0.715-0.810）。对于 PFS，最重要的预测因子是基于身体剂量的 PFS 风险评分（RS）、N 分期和诱导化疗。PFS 诺模图的 C 指数在训练组中为 0.706（95%CI 0.681-0.720），在验证组中为 0.691（95%CI 0.662-0.711）。这两个模型在预测结果方面优于 TNM 分期系统。
身体剂量覆盖是临床常规患者预后的有用预测因子。整合身体剂量参数的新诺模图可以准确预测 NPC 患者的 OS 和 PFS。
