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Blangero Y, Rabilloud M, Laurent-Puig P, Le Malicot K, Lepage C, Ecochard R, Taieb J, Subtil F. The area between ROC curves, a non-parametric method to evaluate a biomarker for patient treatment selection. Biom J 2020; 62:1476-1493. [PMID: 32346912 DOI: 10.1002/bimj.201900171] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 09/26/2019] [Accepted: 01/10/2020] [Indexed: 12/19/2022]
Abstract
Treatment selection markers are generally sought for when the benefit of an innovative treatment in comparison with a reference treatment is considered, and this benefit is suspected to vary according to the characteristics of the patients. Classically, such quantitative markers are detected through testing a marker-by-treatment interaction in a parametric regression model. Most alternative methods rely on modeling the risk of event occurrence in each treatment arm or the benefit of the innovative treatment over the marker values, but with assumptions that may be difficult to verify. Herein, a simple non-parametric approach is proposed to detect and assess the general capacity of a quantitative marker for treatment selection when no overall difference in efficacy could be demonstrated between two treatments in a clinical trial. This graphical method relies on the area between treatment-arm-specific receiver operating characteristic curves (ABC), which reflects the treatment selection capacity of the marker. A simulation study assessed the inference properties of the ABC estimator and compared them with other parametric and non-parametric indicators. The simulations showed that the estimate of the ABC had low bias, power comparable to parametric indicators, and that its confidence interval had a good coverage probability (better than the other non-parametric indicator in some cases). Thus, the ABC is a good alternative to parametric indicators. The ABC method was applied to data of the PETACC-8 trial that investigated FOLFOX4 versus FOLFOX4 + cetuximab in stage III colon adenocarcinoma. It enabled the detection of a treatment selection marker: the DDR2 gene.
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Affiliation(s)
- Yoann Blangero
- Service de Biostatistique, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France.,Université de Lyon, Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
| | - Muriel Rabilloud
- Service de Biostatistique, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France.,Université de Lyon, Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
| | - Pierre Laurent-Puig
- Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Service de génétique, Hôpital Européen Georges Pompidou, Paris, France.,INSERM UMR-S 1147, Paris, France
| | | | - Côme Lepage
- Fédération Francophone de Cancérologie Digestive, Dijon, France.,Hépato-gastroentérologie et cancérologie digestive, Centre hospitalier universitaire Dijon Bourgogne, Dijon, France.,INSERM U 866, Dijon, France
| | - René Ecochard
- Service de Biostatistique, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France.,Université de Lyon, Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
| | - Julien Taieb
- Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Chirurgie digestive générale et cancérologique, Hôpital Européen Georges Pompidou, Paris, France
| | - Fabien Subtil
- Service de Biostatistique, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France.,Université de Lyon, Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
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