Adaptive Designs for the One-sample Log-rank Test

Schmidt, René; Faldum, Andreas; Kwiecien, Robert

doi:10.1111/biom.12776

Cited by 9 publications

(12 citation statements)

References 22 publications

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“…The approaches proposed by Wu 7,11 and by Schmidt et al. 8,9 are both based on a counting process formulation of the one-sample log-rank test. Besides the form of the test statistic, a key difference between both approaches is that Wu 7,11 consider the underlying counting process in the study time scale, whereas Schmidt et al.…”

Section: Discussionmentioning

confidence: 99%

“…5 Alternative formulas have been derived based on a counting process approach. 6–9 Kwak and Jung 6 provide a sample size formula under the assumption that the survival distributions under the null and alternative are close, and Wu 7 provides a sample size formula based on the exact variance of the one-sample log-rank statistic in the large sample limit. Whereas Kwak and Jung 6 and Wu 7 consider the counting process in study time, Schmidt et al.…”

Section: Introductionmentioning

confidence: 99%

“…Whereas Kwak and Jung 6 and Wu 7 consider the counting process in study time, Schmidt et al. 8,9 describe the one-sample log-rank statistic as stochastic process in information time. From a counting process point of view, the difference between the approaches of Finkelstein et al.…”

Section: Introductionmentioning

confidence: 99%

“…5 and Schmidt et al. 8,9 is that the first use the optional variation process [M] of the compensated counting process martingale M to approximate information time, whereas the latter use the predictable variation process 〈M〉.…”

Section: Introductionmentioning

confidence: 99%

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An improved one-sample log-rank test

Kerschke¹,

Faldum²,

Schmidt³

2020

Stat Methods Med Res

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The one-sample log-rank test allows to compare the survival of a single sample with a prefixed reference survival curve. It naturally applies in single-arm phase IIa trials with time-to-event endpoint. Several authors have described that the original one-sample log-rank test is conservative when sample size is small and have proposed strategies to correct the conservativeness. Here, we propose an alternative approach to improve the one-sample log-rank test. Our new one-sample log-rank statistic is based on the unique transformation of the underlying counting process martingale such that the moments of the limiting normal distribution have no shared parameters. Simulation results show that the new one-sample log-rank test gives type I error rate and power close to the nominal levels also when sample size is small, while relevantly reducing the required sample size to achieve the desired power as compared to current approaches to design studies to compare the survival outcome of a sample with a reference.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An improved one-sample log-rank test

Kerschke¹,

Faldum²,

Schmidt³

2020

Stat Methods Med Res

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“…To construct the survival curves and the onset of a combined critical event (death or hospitalization), the Kaplan-Meier method [16] was used, the significance of the differences between the curves was determined using the log-rank criterion [17]. Differences were considered statistically significant at p<0.05.…”

Section: Methodsmentioning

confidence: 99%

Prognostic Value of Cognitive Tests and Their Combination in Patients With Chronic Heart Failure and Reduced Left Ventricular Ejection Fraction

Воронков

Solonovych

Liashenko

et al. 2018

EUREKA: Health Sciences

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Impaired cognitive function (CF) is common among patients with CHF and is an additional factor impairing the quality of life, adherence to treatment, and hence the clinical prognosis in this category of patients. The aim of this work was to study the prognostic significance of individual cognitive tests, as well as their combination in patients with CHF with a reduced left ventricular ejection fraction (LV EF). Materials and methods. The study was conducted in the Department of Heart Failure of National Scientific Center "M.D. Strazhesko Institute of Cardiology" National Academy of Medical Sciences of Ukraine, in the period from 01/01/2016 to 04/27/2018. A total of 124 patients with CHF between the ages of 18 and 75 years, II-IV functional classes by NYHA were examined. The cognitive function was assessed using the Schulte test, Mini-Mental State Examination scale (MMSE); HADS scale. Cognitive dysfunction (CD) was considered as MMSE ≤26 points. To construct the survival curves and the onset of the combined critical event (death or hospitalization), the Kaplan – Meier method was used, the significance of the differences between the curves was determined using the log-rank criterion. Differences were considered statistically significant at p <0.05. Results. The MMSE scale was highly informative regarding the prediction of survival and the onset of a combined critical event (death or hospitalization) in patients with CHF and reduced LVEF even after correction of the compared groups by age and functional class according to NYHA (p=0.025 and p=0.049, respectively). Using the same sample, Schulte showed low prognostic significance regarding survival and reliable informativeness regarding the onset of the combined critical event, which, however, was leveled after correcting the compared samples by age and functional class NYHA (p=0.798 and p=0.240, respectively). The inclusion in the prognostic algorithm of estimating the sum of points on the HADS depression scale allowed increasing the degree of reliability of differences between the compared groups of patients with CD and without CD in terms of both long-term survival and the onset of a combined critical event (death or hospitalization) (p=0.006 and p=0.001 respectively). Conclusions. The MMSE scale is informative regarding the prediction of survival and the onset of a combined critical event in patients with CHF and reduced LVEF. Schulte's test does not have the prognostic information indicated above, however, the inclusion in the algorithm of the sum of points on the HADS depression scale allows to increase the degree of statistical confidence in the compared groups.

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Confirmatory adaptive group sequential designs for single‐arm phase II studies with multiple time‐to‐event endpoints

et al. 2021

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Existing methods concerning the assessment of long‐term survival outcomes in one‐armed trials are commonly restricted to one primary endpoint. Corresponding adaptive designs suffer from limitations regarding the use of information from other endpoints in interim design changes. Here we provide adaptive group sequential one‐sample tests for testing hypotheses on the multivariate survival distribution derived from multi‐state models, while making provision for data‐dependent design modifications based on all involved time‐to‐event endpoints. We explicitly elaborate application of the methodology to one‐sample tests for the joint distribution of (i) progression‐free survival (PFS) and overall survival (OS) in the context of an illness‐death model, and (ii) time to toxicity and time to progression while accounting for death as a competing event. Large sample distributions are derived using a counting process approach. Small sample properties are studied by simulation. An already established multi‐state model for non‐small cell lung cancer is used to illustrate the adaptive procedure.

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Adaptive Designs for the One-sample Log-rank Test

Cited by 9 publications

References 22 publications

An improved one-sample log-rank test

An improved one-sample log-rank test

Prognostic Value of Cognitive Tests and Their Combination in Patients With Chronic Heart Failure and Reduced Left Ventricular Ejection Fraction

Confirmatory adaptive group sequential designs for single‐arm phase II studies with multiple time‐to‐event endpoints

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