BACKGROUND: Progression-free survival (PFS) is frequently used as a primary endpoint in late-phase clinical trials for anti-metastatic cancer agents. Previous studies have indicated that the frequency of tumor assessment affects the statistical power for PFS because progression dates are inaccurate; however, this finding may be difficult to generalize because of its unrealistic assumptions. Therefore, we re-examined this issue under realistic assumptions and various scenarios that approximate actual clinical trials. METHODS: Randomized clinical trials comparing two interventions against a solid tumor were simulated under conditions where progressive disease (PD)-dominant PFS or a non-negligible number of deaths (death-competitive PFS) contributed to PFS events, which are conditions that resemble clinical trials of first-line therapy and later-line therapy, respectively. We assessed the impact of tumor assessment frequency on the statistical power. RESULTS: Under the PD-dominant PFS condition, even in extreme scenarios, statistical power loss was only approximately 3%. Under the death-competitive PFS condition, tumor assessment frequency affected the statistical power of PFS if the effect of the treatment on overall survival was lower than that on time to progression. In this case, loss of statistical power was often more than 10% in some realistic scenarios. CONCLUSION: In trials investigating first-line treatments (PD-dominant PFS), tumor assessment frequency has a negligible impact on statistical power, whereas in trials investigating late-line therapies (death-competitive PFS), the potential impact of tumor assessment frequency on statistical power should be carefully evaluated at the design stage.
BACKGROUND: Progression-free survival (PFS) is frequently used as a primary endpoint in late-phase clinical trials for anti-metastatic cancer agents. Previous studies have indicated that the frequency of tumor assessment affects the statistical power for PFS because progression dates are inaccurate; however, this finding may be difficult to generalize because of its unrealistic assumptions. Therefore, we re-examined this issue under realistic assumptions and various scenarios that approximate actual clinical trials. METHODS: Randomized clinical trials comparing two interventions against a solid tumor were simulated under conditions where progressive disease (PD)-dominant PFS or a non-negligible number of deaths (death-competitive PFS) contributed to PFS events, which are conditions that resemble clinical trials of first-line therapy and later-line therapy, respectively. We assessed the impact of tumor assessment frequency on the statistical power. RESULTS: Under the PD-dominant PFS condition, even in extreme scenarios, statistical power loss was only approximately 3%. Under the death-competitive PFS condition, tumor assessment frequency affected the statistical power of PFS if the effect of the treatment on overall survival was lower than that on time to progression. In this case, loss of statistical power was often more than 10% in some realistic scenarios. CONCLUSION: In trials investigating first-line treatments (PD-dominant PFS), tumor assessment frequency has a negligible impact on statistical power, whereas in trials investigating late-line therapies (death-competitive PFS), the potential impact of tumor assessment frequency on statistical power should be carefully evaluated at the design stage.
Authors: Rafael Rosell; Enric Carcereny; Radj Gervais; Alain Vergnenegre; Bartomeu Massuti; Enriqueta Felip; Ramon Palmero; Ramon Garcia-Gomez; Cinta Pallares; Jose Miguel Sanchez; Rut Porta; Manuel Cobo; Pilar Garrido; Flavia Longo; Teresa Moran; Amelia Insa; Filippo De Marinis; Romain Corre; Isabel Bover; Alfonso Illiano; Eric Dansin; Javier de Castro; Michele Milella; Noemi Reguart; Giuseppe Altavilla; Ulpiano Jimenez; Mariano Provencio; Miguel Angel Moreno; Josefa Terrasa; Jose Muñoz-Langa; Javier Valdivia; Dolores Isla; Manuel Domine; Olivier Molinier; Julien Mazieres; Nathalie Baize; Rosario Garcia-Campelo; Gilles Robinet; Delvys Rodriguez-Abreu; Guillermo Lopez-Vivanco; Vittorio Gebbia; Lioba Ferrera-Delgado; Pierre Bombaron; Reyes Bernabe; Alessandra Bearz; Angel Artal; Enrico Cortesi; Christian Rolfo; Maria Sanchez-Ronco; Ana Drozdowskyj; Cristina Queralt; Itziar de Aguirre; Jose Luis Ramirez; Jose Javier Sanchez; Miguel Angel Molina; Miquel Taron; Luis Paz-Ares Journal: Lancet Oncol Date: 2012-01-26 Impact factor: 41.316
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Authors: E A Eisenhauer; P Therasse; J Bogaerts; L H Schwartz; D Sargent; R Ford; J Dancey; S Arbuck; S Gwyther; M Mooney; L Rubinstein; L Shankar; L Dodd; R Kaplan; D Lacombe; J Verweij Journal: Eur J Cancer Date: 2009-01 Impact factor: 9.162
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