TY  - JOUR
AB  - The one–sample log–rank test is the method of choice for single–arm Phase II trials with time–to–event endpoint. It allows to compare the survival of patients to a reference survival curve that typically represents the expected survival under standard of care. The one–sample log–rank test, however, assumes that the reference survival curve is known. This ignores that the reference curve is commonly estimated from historic data and thus prone to sampling error. Ignoring sampling variability of the reference curve results in type I error rate inflation. We study this inflation in type I error rate analytically and by simulation. Moreover we derive the actual distribution of the one–sample log–rank test statistic, when the sampling variability of the reference curve is taken into account. In particular, we provide a consistent estimate of the factor by which the true variance of the one-sample log–rank statistic is underestimated when reference curve sampling variability is ignored. Our results are further substantiated by a case study using a real world data example in which we demonstrate how to estimate the error rate inflation in the planning stage of a trial.
AU  - Danzer, Moritz Fabian
AU  - Feld, Jannik
AU  - Faldum, Andreas
AU  - Faldum, Andreas St. H.
AU  - Faldum, A.
AU  - Schmidt, René
DA  - 2022-07-21
DO  - 10.17879/52099615192
KW  - Research errors
KW  - Test statistics
KW  - Random variables
KW  - Normal distribution
KW  - Distribution curves
KW  - Statistical distributions
KW  - Stochastic processes
KW  - Probability theory
LA  - eng
N1  - PLoS ONE 17 (2022) 7, e0271094
N1  - Finanziert durch den Open-Access-Publikationsfonds der Westfälischen Wilhelms-Universität Münster (WWU Münster)
PY  - 2022-07-21
TI  - Reference curve sampling variability in one–sample log–rank tests
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:6-52099611690
Y2  - 2024-11-22T00:54:23
ER  -