Benefit of Avasopasem Manganese on Severe Oral Mucositis in Head and Neck Cancer in the ROMAN Trial: Unplanned Secondary Analysis

IF 2.2 Q3 ONCOLOGY Advances in Radiation Oncology Pub Date : 2024-11-09 DOI:10.1016/j.adro.2024.101674

Carryn Anderson MD , Samuel Salvaggio PhD , Mickaël De Backer PhD , Jean-Christophe Chiem PhD , Gary Walker MD, MPH, MS , Deborah Saunders DMD, BSc , Christopher M. Lee MD , Neal Dunlap MD , Eugene Kennedy MD , Robert Beardsley PhD , Benton Schoen BA , Marc Buyse ScD

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Abstract

Purpose

Oral mucositis (OM) is a debilitating side effect of cisplatin and intensity-modulated radiation therapy (IMRT) in patients with head and neck cancer. The phase 3 ROMAN trial showed avasopasem manganese (AVA) significantly decreased individual endpoints of incidence and duration of severe oral mucositis (SOM, World Health Organization [WHO] grade 3-4), with nominal decrease in severity (WHO grade 4) and significant increase in the delay in onset of SOM. We sought to determine the Net Treatment Benefit (NTB) of AVA versus placebo (PBO) using the generalized pairwise comparisons (GPC) method.

Methods and Materials

GPC is a statistical method that permits simultaneous analysis of several prioritized outcomes, comparing all possible pairs of a patient in the active (ie, AVA) group and a patient from the control (ie, PBO) group. NTB is the net benefit across all the outcomes for AVA compared to PBO. Key clinically relevant outcomes from ROMAN were prioritized: (1) WHO grade 4 OM incidence; (2) SOM incidence; (3) days of SOM; (4) days to SOM onset, with 7 days difference defined as the clinical relevance threshold for SOM days and SOM onset.

Results

GPC analysis of 407 patients (AVA = 241, placebo = 166) stratified by cisplatin schedule and treatment setting resulted in 13,969 pairwise comparisons. AVA showed statistically significant net benefit on all 4 key outcomes with a 53.9% probability that AVA would benefit patients versus a 35.0% probability that PBO would; the difference between these probabilities was a NTB of 18.9% (P = .0012), translating to an AVA number needed to treat of 5.3 patients. All outcomes contributed to NTB, reflecting improvements in SOM incidence, onset and duration, and in grade 4 OM incidence seen in the original ROMAN analysis.

Conclusions

This GPC analysis shows compelling evidence from the ROMAN trial of AVA's clinical benefit across key parameters of SOM burden.

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ROMAN试验中阿伐沙星锰对头颈癌严重口腔黏膜炎的益处：计划外二次分析

目的口腔黏膜炎（OM）是头颈部癌症患者接受顺铂和调强放射治疗（IMRT）后出现的一种使人衰弱的副作用。3 期 ROMAN 试验显示，阿伐帕司锰片（AVA）可显著降低严重口腔黏膜炎（SOM，世界卫生组织 [WHO] 3-4 级）的发病率和持续时间等单项终点，其严重程度（WHO 4 级）也有一定程度的降低，但 SOM 的发病延迟时间显著延长。我们试图使用广义配对比较法（GPC）确定 AVA 与安慰剂（PBO）的净治疗获益（NTB）。方法与材料GPC 是一种统计方法，它允许同时分析多个优先结果，比较活性组（即 AVA）患者与对照组（即 PBO）患者的所有可能配对。NTB 是 AVA 与 PBO 相比在所有结果中的净获益。对 ROMAN 的主要临床相关结果进行了优先排序：(1) WHO 4 级 OM 发生率；(2) SOM 发生率；(3) SOM 天数；(4) SOM 发病天数，将 7 天差异定义为 SOM 天数和 SOM 发病的临床相关阈值。AVA 在所有 4 个关键结果上都显示出统计学意义上的显著净获益，AVA 患者获益的概率为 53.9%，而 PBO 患者获益的概率为 35.0%；这两个概率之间的差异为 18.9% 的 NTB (P = .0012)，换算成 AVA 需要治疗的患者人数为 5.3 人。所有结果都对 NTB 有贡献，反映了原始 ROMAN 分析中发现的 SOM 发生率、发病率和持续时间以及 4 级 OM 发生率的改善。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Advances in Radiation Oncology Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

4.60

自引率

4.30%

发文量

208

审稿时长

98 days

期刊介绍： The purpose of Advances is to provide information for clinicians who use radiation therapy by publishing: Clinical trial reports and reanalyses. Basic science original reports. Manuscripts examining health services research, comparative and cost effectiveness research, and systematic reviews. Case reports documenting unusual problems and solutions. High quality multi and single institutional series, as well as other novel retrospective hypothesis generating series. Timely critical reviews on important topics in radiation oncology, such as side effects. Articles reporting the natural history of disease and patterns of failure, particularly as they relate to treatment volume delineation. Articles on safety and quality in radiation therapy. Essays on clinical experience. Articles on practice transformation in radiation oncology, in particular: Aspects of health policy that may impact the future practice of radiation oncology. How information technology, such as data analytics and systems innovations, will change radiation oncology practice. Articles on imaging as they relate to radiation therapy treatment.