Testing equivalence of survival before but not after end of follow-up

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Testing equivalence of survival before but not after end of follow-up. / Furberg, Julie K; Pipper, Christian B; Scheike, Thomas.

In: Lifetime Data Analysis, Vol. 27, No. 2, 2021, p. 216-243.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Furberg, JK, Pipper, CB & Scheike, T 2021, 'Testing equivalence of survival before but not after end of follow-up', Lifetime Data Analysis, vol. 27, no. 2, pp. 216-243. https://doi.org/10.1007/s10985-021-09517-5

APA

Furberg, J. K., Pipper, C. B., & Scheike, T. (2021). Testing equivalence of survival before but not after end of follow-up. Lifetime Data Analysis, 27(2), 216-243. https://doi.org/10.1007/s10985-021-09517-5

Vancouver

Furberg JK, Pipper CB, Scheike T. Testing equivalence of survival before but not after end of follow-up. Lifetime Data Analysis. 2021;27(2):216-243. https://doi.org/10.1007/s10985-021-09517-5

Author

Furberg, Julie K ; Pipper, Christian B ; Scheike, Thomas. / Testing equivalence of survival before but not after end of follow-up. In: Lifetime Data Analysis. 2021 ; Vol. 27, No. 2. pp. 216-243.

Bibtex

@article{ef170ee37e4f4097a20390fffa9a4aa8,
title = "Testing equivalence of survival before but not after end of follow-up",
abstract = "For equivalence trials with survival outcomes, a popular testing approach is the elegant test for equivalence of two survival functions suggested by Wellek (Biometrics 49: 877-881, 1993). This test evaluates whether or not the difference between the true survival curves is practically irrelevant by specifying an equivalence margin on the hazard ratio under the proportional hazards assumption. However, this approach is based on extrapolating the behavior of the survival curves to the whole time axis, whereas in practice survival times are only observed until the end of follow-up. We propose a modification of Welleks test that only addresses equivalence until end of follow-up and derive the large sample properties of this test. Another issue is the proportional hazards assumption which may not be realistic. If this assumption is violated, one may severely misjudge the actual treatment effect with a hazard ratio quantification and wrongly declare equivalence. We suggest a non-parametric test for assessing survival equivalence within the follow-up period. We derive the large sample properties of this test and provide an approximation to the limiting distribution under some mild assumptions on the functional form of the difference between the two survival curves. Both suggestions are investigated by simulation and applied to a clinical trial on survival of gastric cancer patients.",
keywords = "Computer Simulation, Follow-Up Studies, Humans, Proportional Hazards Models",
author = "Furberg, {Julie K} and Pipper, {Christian B} and Thomas Scheike",
year = "2021",
doi = "10.1007/s10985-021-09517-5",
language = "English",
volume = "27",
pages = "216--243",
journal = "Lifetime Data Analysis",
issn = "1380-7870",
publisher = "Springer",
number = "2",

}

RIS

TY - JOUR

T1 - Testing equivalence of survival before but not after end of follow-up

AU - Furberg, Julie K

AU - Pipper, Christian B

AU - Scheike, Thomas

PY - 2021

Y1 - 2021

N2 - For equivalence trials with survival outcomes, a popular testing approach is the elegant test for equivalence of two survival functions suggested by Wellek (Biometrics 49: 877-881, 1993). This test evaluates whether or not the difference between the true survival curves is practically irrelevant by specifying an equivalence margin on the hazard ratio under the proportional hazards assumption. However, this approach is based on extrapolating the behavior of the survival curves to the whole time axis, whereas in practice survival times are only observed until the end of follow-up. We propose a modification of Welleks test that only addresses equivalence until end of follow-up and derive the large sample properties of this test. Another issue is the proportional hazards assumption which may not be realistic. If this assumption is violated, one may severely misjudge the actual treatment effect with a hazard ratio quantification and wrongly declare equivalence. We suggest a non-parametric test for assessing survival equivalence within the follow-up period. We derive the large sample properties of this test and provide an approximation to the limiting distribution under some mild assumptions on the functional form of the difference between the two survival curves. Both suggestions are investigated by simulation and applied to a clinical trial on survival of gastric cancer patients.

AB - For equivalence trials with survival outcomes, a popular testing approach is the elegant test for equivalence of two survival functions suggested by Wellek (Biometrics 49: 877-881, 1993). This test evaluates whether or not the difference between the true survival curves is practically irrelevant by specifying an equivalence margin on the hazard ratio under the proportional hazards assumption. However, this approach is based on extrapolating the behavior of the survival curves to the whole time axis, whereas in practice survival times are only observed until the end of follow-up. We propose a modification of Welleks test that only addresses equivalence until end of follow-up and derive the large sample properties of this test. Another issue is the proportional hazards assumption which may not be realistic. If this assumption is violated, one may severely misjudge the actual treatment effect with a hazard ratio quantification and wrongly declare equivalence. We suggest a non-parametric test for assessing survival equivalence within the follow-up period. We derive the large sample properties of this test and provide an approximation to the limiting distribution under some mild assumptions on the functional form of the difference between the two survival curves. Both suggestions are investigated by simulation and applied to a clinical trial on survival of gastric cancer patients.

KW - Computer Simulation

KW - Follow-Up Studies

KW - Humans

KW - Proportional Hazards Models

U2 - 10.1007/s10985-021-09517-5

DO - 10.1007/s10985-021-09517-5

M3 - Journal article

C2 - 33515387

VL - 27

SP - 216

EP - 243

JO - Lifetime Data Analysis

JF - Lifetime Data Analysis

SN - 1380-7870

IS - 2

ER -

ID: 286627162