State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, Guangzhou, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Johns Hopkins University School of Medicine, Baltimore, Maryland.
Int J Radiat Oncol Biol Phys. 2021 Jan 1;109(1):120-130. doi: 10.1016/j.ijrobp.2020.08.045. Epub 2020 Aug 24.
We aimed to develop an accurate prognostic model to identify suitable candidates for definitive radiation therapy (DRT) in addition to palliative chemotherapy (PCT) among patients with de novo metastatic nasopharyngeal carcinoma (mNPC).
Patients with de novo mNPC who received first-line PCT with or without DRT were included. Overall survival for patients who received PCT alone versus PCT plus DRT was estimated using inverse probability of treatment weighting-adjusted survival analyses. We developed and validated a prognostic model to predict survival and stratify risks in de novo mNPC. A model-based trees approach was applied to estimate stratified treatment effects using prognostic scores obtained from the prognostic model and to identify suitable DRT candidates. Dominance analysis was used to determine the relative importance of each predictor of receiving DRT.
A total of 460 patients were enrolled; 244 received PCT plus DRT and 216 received PCT alone. The 6-month conditional landmark, inverse probability of treatment weighting-adjusted Cox regression analysis showed that PCT plus DRT was associated with a significant survival benefit (hazard ratio: 0.516; 95% confidence interval, 0.403-0.660; P < .001). A prognostic model based on 5 independent prognostic factors, including serum lactate dehydrogenase, number of metastatic sites, presence of liver metastasis, posttreatment Epstein-Barr virus DNA level, and response of metastases to chemotherapy was developed and subsequently validated. Prognostic scores obtained from the prognostic model were used for risk stratification and efficacy estimation. High-risk patients identified using the proposed model would not benefit from additional DRT, whereas low-risk patients experienced significant survival benefits. Socioeconomic factors, including insurance status and education level, played an important role in receipt of DRT.
Additional DRT after PCT was associated with increased overall survival in patients with de novo mNPC, especially low-risk patients identified with a newly developed prognostic model.
我们旨在开发一种准确的预后模型,以确定初诊转移性鼻咽癌(mNPC)患者在接受姑息性化疗(PCT)之外是否适合接受根治性放疗(DRT)。
纳入接受一线 PCT 联合或不联合 DRT 的初诊 mNPC 患者。采用逆概率治疗权重调整后的生存分析估计仅接受 PCT 与接受 PCT 联合 DRT 的患者的总生存情况。我们开发并验证了一种预测生存和分层初诊 mNPC 风险的预后模型。应用基于模型的树方法,根据预后模型获得的预后评分估计分层治疗效果,并确定合适的 DRT 候选者。采用优势分析确定接受 DRT 的每个预测因素的相对重要性。
共纳入 460 例患者,244 例接受 PCT 联合 DRT,216 例接受 PCT 单药治疗。6 个月条件性 landmark 逆概率治疗权重调整后的 Cox 回归分析显示,PCT 联合 DRT 与生存显著获益相关(风险比:0.516;95%置信区间,0.403-0.660;P<0.001)。基于 5 个独立预后因素(包括血清乳酸脱氢酶、转移灶数量、肝转移存在、治疗后 EBV-DNA 水平和转移灶对化疗的反应)建立了预后模型,并随后进行了验证。从预后模型中获得的预后评分用于风险分层和疗效估计。使用所提出的模型识别的高风险患者不会从额外的 DRT 中获益,而低风险患者则显著获益。社会经济因素,包括保险状况和教育水平,在接受 DRT 方面发挥了重要作用。
PCT 后加用 DRT 可提高初诊 mNPC 患者的总生存率,特别是使用新开发的预后模型识别的低危患者。