M-K Riviere1, C Le Tourneau2, X Paoletti3, F Dubois4, S Zohar5. 1. INSERM, U1138, Team 22, Centre de Recherche des Cordeliers, Université Paris 5, Université Paris 6, Paris IRIS (Institut de Recherches Internationales Servier), Suresnes marie-karelle.riviere@crc.jussieu.fr. 2. Institut Curie INSERM, U900, Paris Department of Medical Oncology, Institut Curie, Paris, France. 3. Institut Curie INSERM, U900, Paris. 4. IRIS (Institut de Recherches Internationales Servier), Suresnes. 5. INSERM, U1138, Team 22, Centre de Recherche des Cordeliers, Université Paris 5, Université Paris 6, Paris.
Abstract
BACKGROUND: Combining several anticancer agents can increase the overall antitumor action, but at the same time, it can also increase the overall observed toxicity. Adaptive dose-escalation designs for drug combinations have recently emerged as an attractive alternative to algorithm-based designs, and they seem more effective in combination recommendations. These methods are not used in practice currently. Our aim is to describe international scientific practices in the setting of phase I drug combinations in oncology. MATERIAL AND METHODS: A bibliometric study on phase I dose-finding combination trials was conducted using the Medline(®) PubMed database between 1 January, 2011, and 31 December 2013. Sorting by abstract, we selected all papers involving a minimum of two agents and then retained only those in which at least two agents were dose-escalated. RESULTS: Among the 847 references retrieved, 162 papers reported drug-combination phase I trials in which at least two agents were dose-escalated. In 88% of trials, a traditional or modified 3 + 3 dose-escalation design was used. All except one trial used a design developed for single-agent evaluation. Our study suggests that drug-combination phase I trials in oncology are very safe, as revealed by the calculated median dose-limiting toxicity rate of 6% at the recommended dose, which is far below the target rate in these trials (33%). We also examined requirements of phase I clinical trials in oncology with drug combinations and the potential advantages of novel approaches in early phases. CONCLUSION: Efforts to promote novel and innovative approaches among statisticians and clinicians appear valuable. Adaptive designs have an important role to play in early phase development.
BACKGROUND: Combining several anticancer agents can increase the overall antitumor action, but at the same time, it can also increase the overall observed toxicity. Adaptive dose-escalation designs for drug combinations have recently emerged as an attractive alternative to algorithm-based designs, and they seem more effective in combination recommendations. These methods are not used in practice currently. Our aim is to describe international scientific practices in the setting of phase I drug combinations in oncology. MATERIAL AND METHODS: A bibliometric study on phase I dose-finding combination trials was conducted using the Medline(®) PubMed database between 1 January, 2011, and 31 December 2013. Sorting by abstract, we selected all papers involving a minimum of two agents and then retained only those in which at least two agents were dose-escalated. RESULTS: Among the 847 references retrieved, 162 papers reported drug-combination phase I trials in which at least two agents were dose-escalated. In 88% of trials, a traditional or modified 3 + 3 dose-escalation design was used. All except one trial used a design developed for single-agent evaluation. Our study suggests that drug-combination phase I trials in oncology are very safe, as revealed by the calculated median dose-limiting toxicity rate of 6% at the recommended dose, which is far below the target rate in these trials (33%). We also examined requirements of phase I clinical trials in oncology with drug combinations and the potential advantages of novel approaches in early phases. CONCLUSION: Efforts to promote novel and innovative approaches among statisticians and clinicians appear valuable. Adaptive designs have an important role to play in early phase development.
Authors: Alexander Drilon; Anne A Eaton; Katja Schindler; Mrinal M Gounder; David R Spriggs; Pamela Harris; S Percy Ivy; Alexia Iasonos; Mario E Lacouture; David M Hyman Journal: Cancer Date: 2016-02-24 Impact factor: 6.860
Authors: Cody Chiuzan; Jonathan Shtaynberger; Gulam A Manji; Jimmy K Duong; Gary K Schwartz; Anastasia Ivanova; Shing M Lee Journal: J Biopharm Stat Date: 2017-02-06 Impact factor: 1.051