JCO Article Insights: Nivolumab + Relatlimab v Nivolumab + Ipilimumab in Melanoma

JCO Article Insights: Nivolumab + Relatlimab v Nivolumab + Ipilimumab in Melanoma

9:42 Nov 25, 2024
About this episode
In this JCO Article Insights episode, Rohit Singh provides a summary on "First-Line Nivolumab Plus Relatlimab Versus Nivolumab Plus Ipilimumab in Advanced Melanoma: An Indirect Treatment Comparison Using RELATIVITY-047 and CheckMate 067 Trial Data", by Long et al, published in the November issue of the Journal of Clinical Oncology. The article provides insights into the use of the two dual immune checkpoint inhibitor regimens in patients with untreated advanced melanoma. TRANSCRIPT Rohit Singh: Hello and welcome to JCO Article Insights. I'm your host Rohit Singh, Assistant Professor at the University of Vermont Cancer Center and today we'll be discussing the article "First-Line Nivolumab Plus Relatlimab Versus Nivolumab Plus Ipilimumab in Advanced Melanoma: An Indirect Treatment Comparison Using RELATIVITY-047 and CheckMate 067 Trials," authored by Dr. Georgina Long from the Melanoma Institute of Australia and her colleagues. So as we know, nivolumab plus relatlimab and nivo plus ipi, I'm going to refer to as ipi-nivo moving forward, are dual immune checkpoint inhibitors regimens that are approved for treating patients with advanced melanoma based on the phase 2 and 3 RELATIVITY-047 and phase 3 CheckMate 067 trials respectively. Nivo plus relatlimab is the only dual PD-1 and LAG-3 inhibitor regimen approved for treating patients with advanced melanoma and relatlimab is the first in class human IgG4 LAG-3 blocking antibody. Ipi plus nivo is a dual PD-1 and CTLA-4 inhibitor regimen. So this paper basically is an indirect treatment comparison using a patient level database from these trials and this pretty much was conducted because of the absence of head to head trials looking at different regimens in advanced melanoma in first line setting. In this trial, the authors tried to compare these two trials. However, it's always hard to compare two different trials and we usually don't do cross trial comparisons. The problem is that the groups might be different to begin with. For example, one group might have younger patients, healthier patients, while the other might have older or sicker. These differences can make it hard to tell if the treatment caused improvement or if the groups were different to begin with. In this trial, researchers use inverse probability of treatment weighting to adjust the baseline differences between the two patient groups or between these two trials. Inverse probability of treatment weighting is a method used in research to help make a fair comparison between two groups when studying how a trea
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