针对化疗免疫疗法后接受局部放疗的新发转移性鼻咽癌的递归分区分析模型。

IF 7.1 2区医学 Q1 ONCOLOGY

ESMO Open Pub Date : 2024-10-18 DOI:10.1016/j.esmoop.2024.103960

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引用次数: 0

摘要

背景：化学免疫疗法是治疗新发转移性鼻咽癌（dmNPC）的一线疗法，附加的局部放射治疗（LRRT）可显著延长患者的生存期。然而，新发转移性鼻咽癌具有相当大的异质性，导致患者的预后存在很大差异。我们为接受一线化疗免疫疗法加 LRRT 的患者开发并验证了一种预后工具，并评估了不同风险水平的远处转移患者接受局部治疗（LT）的益处：我们研究了364名接受初始铂类化疗和抗程序性细胞死亡蛋白1免疫疗法，然后接受LRRT治疗的dmNPC患者。患者被随机分为训练组和验证组（比例为 7:3）。主要终点是无进展生存期（PFS）。利用递归分区分析（RPA）建立了无进展生存期预后模型：RPA模型根据转移灶数量、肝转移状态和治疗后Epstein-Barr病毒DNA水平将患者分为五个预后组。生存分析确定了三个不同的风险组。与中风险组和低风险组相比，高风险患者的 PFS 明显较差（2 年 PFS 率：训练队列：13.7% 对 69.4% 对 94.4%，P < 0.001；验证队列：7.8% 对 65.1% 对 87.3%，P < 0.001）。我们研究了LT对这些风险组远处转移的影响，发现只有中风险组患者从LT中获益（2年PFS率：77.5%对64.0%）：77.5%对64.0%；危险比=0.535，95%置信区间为0.297-0.966，P=0.035）。相反，在低风险亚组（P = 0.218）和高风险亚组（P = 0.793）中，LT治疗远处转移没有带来生存获益：我们基于RPA的预后模型综合了转移病灶数量、肝转移状态和治疗后Epstein-Barr病毒DNA水平，可预测接受化疗免疫治疗加LRRT的dmNPC患者的PFS。该模型提供了个性化的治疗指导，表明中风险组患者可能会从LT治疗远处转移中获益，而高风险和低风险组患者则可能不会。

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Recursive partitioning analysis model for de novo metastatic nasopharyngeal carcinoma treated with locoregional radiotherapy following chemoimmunotherapy

Background

Chemoimmunotherapy is the first-line treatment of de novo metastatic nasopharyngeal carcinoma (dmNPC), with additional locoregional radiotherapy (LRRT) significantly prolonging patient survival. De novo metastatic nasopharyngeal carcinoma, however, demonstrates considerable heterogeneity, resulting in significant variability in patient outcomes. We developed and validated a prognostic tool for patients undergoing first-line chemoimmunotherapy plus LRRT and to evaluate the benefit of local therapy (LT) for distant metastases across different risk levels.

Patients and methods

We studied 364 dmNPC patients receiving initial platinum-based chemotherapy and anti-programmed cell death protein 1 immunotherapy followed by LRRT. Patients were randomly divided into training and validation cohorts (7 : 3 ratio). The primary endpoint was progression-free survival (PFS). A prognostic model for PFS was developed using recursive partitioning analysis (RPA).

Results

An RPA model categorized patients into five prognostic groups based on number of metastatic lesions, liver metastasis status, and post-treatment Epstein–Barr virus DNA levels. Survival analysis identified three distinct risk groups. High-risk patients had significantly poorer PFS compared with medium- and low-risk groups (2-year PFS rate: training cohort: 13.7% versus 69.4% versus 94.4%, P < 0.001; validation cohort: 7.8% versus 65.1% versus 87.3%, P < 0.001). We investigated the impact of LT for distant metastases across these risk groups and found that only patients in the medium-risk group derived benefit from LT (2-year PFS rate: 77.5% versus 64.0%; hazard ratio = 0.535, 95% confidence interval 0.297-0.966, P = 0.035). Conversely, no survival benefit from LT for distant metastases was observed in the low-risk (P = 0.218) and high-risk subgroups (P = 0.793).

Conclusions

Our RPA-based prognostic model integrates number of metastatic lesions, liver metastasis status, and post-treatment Epstein–Barr virus DNA levels to predict PFS in dmNPC patients undergoing chemoimmunotherapy plus LRRT. This model offers personalized treatment guidance, suggesting that patients in the medium-risk group may benefit from LT for distant metastases, while those in high- and low-risk groups may not.

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来源期刊

ESMO Open Medicine-Oncology

CiteScore

11.70

自引率

2.70%

发文量

255

审稿时长

10 weeks

期刊介绍： ESMO Open is the online-only, open access journal of the European Society for Medical Oncology (ESMO). It is a peer-reviewed publication dedicated to sharing high-quality medical research and educational materials from various fields of oncology. The journal specifically focuses on showcasing innovative clinical and translational cancer research. ESMO Open aims to publish a wide range of research articles covering all aspects of oncology, including experimental studies, translational research, diagnostic advancements, and therapeutic approaches. The content of the journal includes original research articles, insightful reviews, thought-provoking editorials, and correspondence. Moreover, the journal warmly welcomes the submission of phase I trials and meta-analyses. It also showcases reviews from significant ESMO conferences and meetings, as well as publishes important position statements on behalf of ESMO. Overall, ESMO Open offers a platform for scientists, clinicians, and researchers in the field of oncology to share their valuable insights and contribute to advancing the understanding and treatment of cancer. The journal serves as a source of up-to-date information and fosters collaboration within the oncology community.