RAIRI Model-Guided Adjuvant Therapy in Nasopharyngeal Carcinoma

Recruiting now · Phase 3

Conditions studied: Nasopharyngeal Carcinoma (NPC)

In brief

This study aims to evaluate a personalized approach for treating patients with locoregionally advanced nasopharyngeal carcinoma (NPC). Currently, many high-risk patients receive additional treatment (adjuvant therapy) after standard chemoradiotherapy to prevent the cancer from returning. However, some patients may not actually need this extra treatment and could safely avoid its side effects. This trial uses a novel risk prediction model called the Response-Adapted Individualized Risk Index (RAIRI). The RAIRI model evaluates how a patient's tumor and blood markers (such as Epstein-Barr Virus DNA) respond during and immediately after their initial chemoradiotherapy. In this study, patients will be randomly assigned to one of two groups: 1. Standard Treatment Group: All patients will receive standard adjuvant therapy (either a PD-1 inhibitor or capecitabine) after completing their initial chemoradiotherapy. 2. RAIRI-Guided Group (Experimental): Patients will be evaluated using the RAIRI model after initial chemoradiotherapy. Only those identified as "high-risk" by the model will receive adjuvant therapy. Those identified as "low-risk" will be exempted from adjuvant therapy and will undergo regular observation. The main goal of this study is to determine if using the RAIRI model to exempt low-risk patients from adjuvant therapy is as safe and effective as giving adjuvant therapy to everyone, measured by how long patients live without the disease returning or progressing.

Key facts

Study ID
NCT07590024
Run by
Cancer Institute and Hospital, Chinese Academy of Medical Sciences
People needed
651
Starts
2026-05-01
Expected to finish
2030-12-31
Last updated by the study team
2026-06-04

Who can join

Age: 18 and older, up to 65. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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