An omnibus test for several hazard alternatives in prevention randomized controlled clinical trials

Garès, Valérie; Andrieu, Sandrine; Dupuy, Jean‐François; Savy, Nicolas

doi:10.1002/sim.6366

Cited by 20 publications

(14 citation statements)

References 42 publications

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“…Perhaps a line of future research is to construct more powerful tests adaptive to the deviation from PH assumption. There are quite a few novel statistical tests for non-proportional hazards alternatives proposed and discussed in the literature (Fleming et al, 1987;Pepe and Fleming, 1989;Kosorok and Lin, 1999;Feng and Wahed, 2008;Yang and Prentice, 2010;Garès et al, 2015;Uno et al, 2015). However, there are no coherent corresponding estimation procedures to quantify the treatment difference.…”

Section: Discussionmentioning

confidence: 99%

Efficiency of Two Sample Tests via the Restricted Mean Survival Time for Analyzing Event Time Observations

Tian

Ruberg

et al. 2017

Biometrics

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Summary In comparing two treatments with the event time observations, the hazard ratio (HR) estimate is routinely used to quantify the treatment difference. However, this model dependent estimate may be difficult to interpret clinically especially when the proportional hazards (PH) assumption is violated. An alternative estimation procedure for treatment efficacy based on the restricted means survival time or t-year mean survival time (t-MST) has been discussed extensively in the statistical and clinical literature. On the other hand, a statistical test via the HR or its asymptotically equivalent counterpart, the logrank test, is asymptotically distribution-free. In this paper, we assess the relative efficiency of the hazard ratio and t-MST tests with respect to the statistical power under various PH and non-PH models theoretically and empirically. When the PH assumption is valid, the t-MST test performs almost as well as the HR test. For non-PH models, the t-MST test can substantially outperform its HR counterpart. On the other hand, the HR test can be powerful when the true difference of two survival functions is quite large at end but not the beginning of the study. Unfortunately, for this case, the HR estimate may not have a simple clinical interpretation for the treatment effect due to the violation of the PH assumption.

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Section: Discussionmentioning

confidence: 99%

Efficiency of Two Sample Tests via the Restricted Mean Survival Time for Analyzing Event Time Observations

Tian

Ruberg

et al. 2017

Biometrics

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“…1,2 Freedom from treatment failure (FFF) was assessed at week [16][17][18][19][20] and at month 12 of therapy. The FFF rates at these 2 timepoints for ethosuximide were 53% and 45%, valproate 58% and 44%, and lamotrigine 29% and 21%.…”

mentioning

confidence: 99%

“…15 P and q equal to 0 gave the log-rank test results, and p 5 0, q 5 1 focused on later separation between curves by AED. 16 Initial monotherapy FFF was compared to second monotherapy FFF using a noninferiority analysis. A therapy was considered noninferior as second monotherapy if the second monotherapy FFF rate was no worse than 10% lower than the same therapy's initial monotherapy FFF rate.…”

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confidence: 99%

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Second monotherapy in childhood absence epilepsy

et al. 2017

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Objective: To determine optimal second monotherapy for children with childhood absence epilepsy (CAE) experiencing initial treatment failure.Methods: Children with CAE experiencing treatment failure during the double-blind phase of a randomized controlled trial comparing ethosuximide, valproic acid, and lamotrigine were randomized to open-label second monotherapy with one of the 2 other study therapies. Primary study outcome was freedom from failure proportion at week 16-20 and month 12 visits after randomization. Secondary study outcome was percentage of participants experiencing attentional dysfunction at these visits.Results: A total of 208 children were enrolled, randomized, and received second therapy. At both week 16-20 visit and month 12 visit, ethosuximide's (63%, 57%) and valproic acid's (65%, 49%) freedom from failure proportions were similar to each other and higher than lamotrigine's (45%, 36%, p 5 0.051 and p 5 0.062). At both time points, ethosuximide and valproic acid had superior seizure control compared to lamotrigine (p , 0.0001). At both the week 16-20 and month 12 visits, attentional dysfunction was numerically more common with valproic acid than with ethosuximide or lamotrigine. For each medication, second monotherapy freedom from failure proportions demonstrated noninferiority to initial monotherapy freedom from failure proportions.Conclusions: As second monotherapy, ethosuximide and valproic acid, demonstrated higher freedom from failure proportions and greater efficacy than lamotrigine; valproic acid was associated with more attentional dysfunction. Ethosuximide is the optimal second monotherapy for children with CAE not responding to initial therapy with other medications. ClinicalTrials.gov identifier: NCT00088452.Classification of evidence: This study provides Class III evidence that for children with CAE experiencing initial treatment failure, second monotherapy with ethosuximide or valproic acid is superior to lamotrigine. Neurology ® 2017;88:182-190 GLOSSARY AED 5 antiepileptic drug; CAE 5 childhood absence epilepsy; CI 5 confidence interval; CPT 5 Continuous Performance Test; FFF 5 freedom from treatment failure; GTC 5 generalized tonic-clonic; ILAE 5 International League Against Epilepsy; OR 5 odds ratio; RCT 5 randomized clinical trial.A double-blind randomized clinical trial (RCT) compared ethosuximide, lamotrigine, and valproate as initial monotherapy for children with newly diagnosed childhood absence epilepsy (CAE).1,2 Freedom from treatment failure (FFF) was assessed at week 16-20 and at month 12 of therapy. The FFF rates at these 2 timepoints for ethosuximide were 53% and 45%, valproate 58% and 44%, and lamotrigine 29% and 21%.1,2 Ethosuximide was identified as the optimal initial therapy due to superior efficacy compared with lamotrigine and similar efficacy but fewer attentional side effects when compared to valproate. However, initial monotherapy failed in a substantial proportion of children with CAE.

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“…For instance, Gillen and Emerson (2007) showed that these statistics are non-transitive under general alternatives and proposed an extension to avoid this drawback. More recently, Garès, Andrieu, Dupuy, and Savy (2015) proposed another extension which is designed to have good power against both late effects and proportional hazards alternatives.…”

Section: Right-censored Data: Counting Process Approachmentioning

confidence: 99%

FHtest: An R Package for the Comparison of Survival Curves with Censored Data

Oller¹,

Langohr²

2017

J. Stat. Soft.

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The Fleming-Harrington class for right-censored data was first introduced by Harrington and Fleming (1982). This class is widely used in survival analysis studies and it is a subset of the so-called weighted logrank test statistics. Recently, Oller and Gómez (2012) proposed an extension of this class for interval-censored data. This paper introduces the R package FHtest, which implements the Fleming-Harrington class for right-censored and interval-censored survival data. It provides an integrated approach for performing two-sample, k-sample and trend tests based on either counting process theory, likelihood theory, or permutation distributions. In this paper, we summarize the main aspects of the theory framework and present several examples with R codes to illustrate the usage of the main functions of FHtest.

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An omnibus test for several hazard alternatives in prevention randomized controlled clinical trials

Cited by 20 publications

References 42 publications

Efficiency of Two Sample Tests via the Restricted Mean Survival Time for Analyzing Event Time Observations

Efficiency of Two Sample Tests via the Restricted Mean Survival Time for Analyzing Event Time Observations

Second monotherapy in childhood absence epilepsy

FHtest: An R Package for the Comparison of Survival Curves with Censored Data

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