Publication

Extrapolating Survival Data Using Historical Trial-Based a Priori Distributions

Soikkeli, F., Hashim, M., Ouwens, M., Postma, M. & Heeg, B., Sep-2019, In : Value in Health. 22, 9, p. 1012-1017 6 p.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Soikkeli, F., Hashim, M., Ouwens, M., Postma, M., & Heeg, B. (2019). Extrapolating Survival Data Using Historical Trial-Based a Priori Distributions. Value in Health, 22(9), 1012-1017. https://doi.org/10.1016/j.jval.2019.03.017

Author

Soikkeli, Fanni ; Hashim, Mahmoud ; Ouwens, Mario ; Postma, Maarten ; Heeg, Bart. / Extrapolating Survival Data Using Historical Trial-Based a Priori Distributions. In: Value in Health. 2019 ; Vol. 22, No. 9. pp. 1012-1017.

Harvard

Soikkeli, F, Hashim, M, Ouwens, M, Postma, M & Heeg, B 2019, 'Extrapolating Survival Data Using Historical Trial-Based a Priori Distributions', Value in Health, vol. 22, no. 9, pp. 1012-1017. https://doi.org/10.1016/j.jval.2019.03.017

Standard

Extrapolating Survival Data Using Historical Trial-Based a Priori Distributions. / Soikkeli, Fanni; Hashim, Mahmoud; Ouwens, Mario; Postma, Maarten; Heeg, Bart.

In: Value in Health, Vol. 22, No. 9, 09.2019, p. 1012-1017.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Soikkeli F, Hashim M, Ouwens M, Postma M, Heeg B. Extrapolating Survival Data Using Historical Trial-Based a Priori Distributions. Value in Health. 2019 Sep;22(9):1012-1017. https://doi.org/10.1016/j.jval.2019.03.017


BibTeX

@article{b35da683d74f4e99b1414af4e01b143c,
title = "Extrapolating Survival Data Using Historical Trial-Based a Priori Distributions",
abstract = "Objectives: To show how clinical trial data can be extrapolated using historical trial data-based a priori distributions.Methods: Extrapolations based on 30-month pivotal multiplemyeloma trial data were compared with 75-month data from the same trial. The 30-month data represent a typical decision-making scenario where early results from a clinical trial are extrapolated. Mature historical trial data with the same comparator as in the pivotal trial were incorporated in 2 stages. First, the parametric distribution selection was based on the historical trial data. Second, the shape parameter estimate of the historical trial was used to define an informative a priori distribution for the shape of the 30-month pivotal trial data. The method was compared with standard approaches, fitting parametric distributions to the 30-month data with noninformative prior. The predicted survival of each method was compared with the observed survival (DAUC) in the 75-month trial data.Results: The Weibull had the best fit to the historical trial and the log-normal to the 30-month pivotal trial data. The DAUC of the Weibull with informative priors was considerably smaller compared with the standard Weibull. Also, the predicted median survival based on the Weibull with informative priors was more accurate (melphalan and prednisone [MP] 40 months, and bortezomib [V] combined with MP [VMP] 62 months) than based on the standard Weibull (MP 45 months and VMP 72 months) when compared with the observed median (MP 41.3 months and VMP 56.4 months).Conclusions: Extrapolation of clinical trial data is improved by using historical trial data-based informative a priori distributions.",
keywords = "Bayesian statistics, multiple myeloma, oncology, overall survival, survival analysis, EXTERNAL DATA, PREDNISONE, MELPHALAN",
author = "Fanni Soikkeli and Mahmoud Hashim and Mario Ouwens and Maarten Postma and Bart Heeg",
year = "2019",
month = "9",
doi = "10.1016/j.jval.2019.03.017",
language = "English",
volume = "22",
pages = "1012--1017",
journal = "Value in Health",
issn = "1098-3015",
publisher = "ELSEVIER SCIENCE INC",
number = "9",

}

RIS

TY - JOUR

T1 - Extrapolating Survival Data Using Historical Trial-Based a Priori Distributions

AU - Soikkeli, Fanni

AU - Hashim, Mahmoud

AU - Ouwens, Mario

AU - Postma, Maarten

AU - Heeg, Bart

PY - 2019/9

Y1 - 2019/9

N2 - Objectives: To show how clinical trial data can be extrapolated using historical trial data-based a priori distributions.Methods: Extrapolations based on 30-month pivotal multiplemyeloma trial data were compared with 75-month data from the same trial. The 30-month data represent a typical decision-making scenario where early results from a clinical trial are extrapolated. Mature historical trial data with the same comparator as in the pivotal trial were incorporated in 2 stages. First, the parametric distribution selection was based on the historical trial data. Second, the shape parameter estimate of the historical trial was used to define an informative a priori distribution for the shape of the 30-month pivotal trial data. The method was compared with standard approaches, fitting parametric distributions to the 30-month data with noninformative prior. The predicted survival of each method was compared with the observed survival (DAUC) in the 75-month trial data.Results: The Weibull had the best fit to the historical trial and the log-normal to the 30-month pivotal trial data. The DAUC of the Weibull with informative priors was considerably smaller compared with the standard Weibull. Also, the predicted median survival based on the Weibull with informative priors was more accurate (melphalan and prednisone [MP] 40 months, and bortezomib [V] combined with MP [VMP] 62 months) than based on the standard Weibull (MP 45 months and VMP 72 months) when compared with the observed median (MP 41.3 months and VMP 56.4 months).Conclusions: Extrapolation of clinical trial data is improved by using historical trial data-based informative a priori distributions.

AB - Objectives: To show how clinical trial data can be extrapolated using historical trial data-based a priori distributions.Methods: Extrapolations based on 30-month pivotal multiplemyeloma trial data were compared with 75-month data from the same trial. The 30-month data represent a typical decision-making scenario where early results from a clinical trial are extrapolated. Mature historical trial data with the same comparator as in the pivotal trial were incorporated in 2 stages. First, the parametric distribution selection was based on the historical trial data. Second, the shape parameter estimate of the historical trial was used to define an informative a priori distribution for the shape of the 30-month pivotal trial data. The method was compared with standard approaches, fitting parametric distributions to the 30-month data with noninformative prior. The predicted survival of each method was compared with the observed survival (DAUC) in the 75-month trial data.Results: The Weibull had the best fit to the historical trial and the log-normal to the 30-month pivotal trial data. The DAUC of the Weibull with informative priors was considerably smaller compared with the standard Weibull. Also, the predicted median survival based on the Weibull with informative priors was more accurate (melphalan and prednisone [MP] 40 months, and bortezomib [V] combined with MP [VMP] 62 months) than based on the standard Weibull (MP 45 months and VMP 72 months) when compared with the observed median (MP 41.3 months and VMP 56.4 months).Conclusions: Extrapolation of clinical trial data is improved by using historical trial data-based informative a priori distributions.

KW - Bayesian statistics

KW - multiple myeloma

KW - oncology

KW - overall survival

KW - survival analysis

KW - EXTERNAL DATA

KW - PREDNISONE

KW - MELPHALAN

U2 - 10.1016/j.jval.2019.03.017

DO - 10.1016/j.jval.2019.03.017

M3 - Article

VL - 22

SP - 1012

EP - 1017

JO - Value in Health

JF - Value in Health

SN - 1098-3015

IS - 9

ER -

ID: 98081674