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Two-stage phase II oncology designs using short-term endpoints for early stopping

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Two-stage phase II oncology designs using short-term endpoints for early stopping. / Kunz, Cornelia; Wason, James M. S.; Kieser, Meinhard.

In: Statistical Methods in Medical Research, Vol. 26, No. 4, 01.08.2017, p. 1671-1683.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Kunz, C, Wason, JMS & Kieser, M 2017, 'Two-stage phase II oncology designs using short-term endpoints for early stopping', Statistical Methods in Medical Research, vol. 26, no. 4, pp. 1671-1683. https://doi.org/10.1177/0962280215585819

APA

Kunz, C., Wason, J. M. S., & Kieser, M. (2017). Two-stage phase II oncology designs using short-term endpoints for early stopping. Statistical Methods in Medical Research, 26(4), 1671-1683. https://doi.org/10.1177/0962280215585819

Vancouver

Kunz C, Wason JMS, Kieser M. Two-stage phase II oncology designs using short-term endpoints for early stopping. Statistical Methods in Medical Research. 2017 Aug 1;26(4):1671-1683. https://doi.org/10.1177/0962280215585819

Author

Kunz, Cornelia ; Wason, James M. S. ; Kieser, Meinhard. / Two-stage phase II oncology designs using short-term endpoints for early stopping. In: Statistical Methods in Medical Research. 2017 ; Vol. 26, No. 4. pp. 1671-1683.

Bibtex

@article{0e30c61bfc4449a2a78d7cc442911a3b,
title = "Two-stage phase II oncology designs using short-term endpoints for early stopping",
abstract = "Phase II oncology trials are conducted to evaluate whether the tumour activity of a new treatment is promising enough to warrant further investigation. The most commonly used approach in this context is a two-stage single-arm design with binary endpoint. As for all designs with interim analysis, its efficiency strongly depends on the relation between recruitment rate and follow-up time required to measure the patients{\textquoteright} outcomes. Usually, recruitment is postponed after the sample size of the first stage is achieved up until the outcomes of all patients are available. This may lead to a considerable increase of the trial length and with it to a delay in the drug development process. We propose a design where an intermediate endpoint is used in the interim analysis to decide whether or not the study is continued with a second stage. Optimal and minimax versions of this design are derived. The characteristics of the proposed design in terms of type I error rate, power, maximum and expected sample size as well as trial duration are investigated. Guidance is given on how to select the most appropriate design. Application is illustrated by a phase II oncology trial in patients with advanced angiosarcoma, which motivated this research.",
keywords = "two-stage designs, oncology, short-term endpoint, early stopping",
author = "Cornelia Kunz and Wason, {James M. S.} and Meinhard Kieser",
note = "The final, definitive version of this article has been published in the Journal, Statistical Methods in Medical Research, 26 (4), 2017, {\textcopyright} SAGE Publications Ltd, 2017 by SAGE Publications Ltd at the Statistical Methods in Medical Research page: http://journals.sagepub.com/home/smm on SAGE Journals Online: http://journals.sagepub.com/ ",
year = "2017",
month = aug,
day = "1",
doi = "10.1177/0962280215585819",
language = "English",
volume = "26",
pages = "1671--1683",
journal = "Statistical Methods in Medical Research",
issn = "0962-2802",
publisher = "SAGE Publications Ltd",
number = "4",

}

RIS

TY - JOUR

T1 - Two-stage phase II oncology designs using short-term endpoints for early stopping

AU - Kunz, Cornelia

AU - Wason, James M. S.

AU - Kieser, Meinhard

N1 - The final, definitive version of this article has been published in the Journal, Statistical Methods in Medical Research, 26 (4), 2017, © SAGE Publications Ltd, 2017 by SAGE Publications Ltd at the Statistical Methods in Medical Research page: http://journals.sagepub.com/home/smm on SAGE Journals Online: http://journals.sagepub.com/

PY - 2017/8/1

Y1 - 2017/8/1

N2 - Phase II oncology trials are conducted to evaluate whether the tumour activity of a new treatment is promising enough to warrant further investigation. The most commonly used approach in this context is a two-stage single-arm design with binary endpoint. As for all designs with interim analysis, its efficiency strongly depends on the relation between recruitment rate and follow-up time required to measure the patients’ outcomes. Usually, recruitment is postponed after the sample size of the first stage is achieved up until the outcomes of all patients are available. This may lead to a considerable increase of the trial length and with it to a delay in the drug development process. We propose a design where an intermediate endpoint is used in the interim analysis to decide whether or not the study is continued with a second stage. Optimal and minimax versions of this design are derived. The characteristics of the proposed design in terms of type I error rate, power, maximum and expected sample size as well as trial duration are investigated. Guidance is given on how to select the most appropriate design. Application is illustrated by a phase II oncology trial in patients with advanced angiosarcoma, which motivated this research.

AB - Phase II oncology trials are conducted to evaluate whether the tumour activity of a new treatment is promising enough to warrant further investigation. The most commonly used approach in this context is a two-stage single-arm design with binary endpoint. As for all designs with interim analysis, its efficiency strongly depends on the relation between recruitment rate and follow-up time required to measure the patients’ outcomes. Usually, recruitment is postponed after the sample size of the first stage is achieved up until the outcomes of all patients are available. This may lead to a considerable increase of the trial length and with it to a delay in the drug development process. We propose a design where an intermediate endpoint is used in the interim analysis to decide whether or not the study is continued with a second stage. Optimal and minimax versions of this design are derived. The characteristics of the proposed design in terms of type I error rate, power, maximum and expected sample size as well as trial duration are investigated. Guidance is given on how to select the most appropriate design. Application is illustrated by a phase II oncology trial in patients with advanced angiosarcoma, which motivated this research.

KW - two-stage designs

KW - oncology

KW - short-term endpoint

KW - early stopping

U2 - 10.1177/0962280215585819

DO - 10.1177/0962280215585819

M3 - Journal article

VL - 26

SP - 1671

EP - 1683

JO - Statistical Methods in Medical Research

JF - Statistical Methods in Medical Research

SN - 0962-2802

IS - 4

ER -