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Quantification of long-term survival benefit in a comparative oncology clinical study

Cette étude met en évidence l'intérêt d'une approche pour quantifier, en termes d'évolution des taux de survie globale, le bénéfice à long terme de nouveaux traitements (tels que des immunothérapies) dont les effets cliniques sont tardifs

Novel treatments, such as immunotherapies, may have delayed clinical effect but may be associated with long-term survival benefit in some patients. The conventional procedure using the log-rank test and hazard ratio (HR) for evaluating the long-term treatment effect on overall survival (OS) can be suboptimal in terms of interpretation and power. As an example, part A of the Figure shows Kaplan-Meier curves for OS comparing chemotherapy plus cetuximab and chemotherapy plus bevacizumab using reconstructed OS data for the expanded RAS wild-type subgroup in Venook et al. The HR was 0.88 (95% CI, 0.72-1.08; P = .24) in favor of cetuximab numerically. Visually, the Kaplan-Meier curve for cetuximab is almost identical to that for bevacizumab to month 30 but superior to bevacizumab thereafter. This finding suggests that cetuximab might have a relatively long-term OS benefit that was not appropriately captured by HR. Long-term survival benefit is often quantified by comparing survival rates at a specific time point. For instance, at month 60, cetuximab and bevacizumab had observed survival rates of 27% and 17%, respectively. These summaries, however, do not include information on the temporal OS profile before or after month 60. In this study, using these data, we show an alternative, clinically interpretable approach to quantifying long-term survival benefit.

JAMA Oncology , résumé, 2017

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