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A quantitative framework to inform extrapolation decisions in children

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A quantitative framework to inform extrapolation decisions in children. / Wadsworth, I.; Hampson, L.V.; Jaki, T.; Sills, G.J.; Marson, A.G.; Appleton, R.

In: Journal of the Royal Statistical Society: Series A Statistics in Society, Vol. 183, No. 2, 01.02.2020, p. 515-534.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Wadsworth, I, Hampson, LV, Jaki, T, Sills, GJ, Marson, AG & Appleton, R 2020, 'A quantitative framework to inform extrapolation decisions in children', Journal of the Royal Statistical Society: Series A Statistics in Society, vol. 183, no. 2, pp. 515-534. https://doi.org/10.1111/rssa.12532

APA

Wadsworth, I., Hampson, L. V., Jaki, T., Sills, G. J., Marson, A. G., & Appleton, R. (2020). A quantitative framework to inform extrapolation decisions in children. Journal of the Royal Statistical Society: Series A Statistics in Society, 183(2), 515-534. https://doi.org/10.1111/rssa.12532

Vancouver

Wadsworth I, Hampson LV, Jaki T, Sills GJ, Marson AG, Appleton R. A quantitative framework to inform extrapolation decisions in children. Journal of the Royal Statistical Society: Series A Statistics in Society. 2020 Feb 1;183(2):515-534. https://doi.org/10.1111/rssa.12532

Author

Wadsworth, I. ; Hampson, L.V. ; Jaki, T. ; Sills, G.J. ; Marson, A.G. ; Appleton, R. / A quantitative framework to inform extrapolation decisions in children. In: Journal of the Royal Statistical Society: Series A Statistics in Society. 2020 ; Vol. 183, No. 2. pp. 515-534.

Bibtex

@article{e42237d5f6b5493fbcbb8124d4f870aa,
title = "A quantitative framework to inform extrapolation decisions in children",
abstract = "When developing a new medicine for children, the potential to extrapolate from adult efficacy data is well recognized. However, significant assumptions about the similarity of adults and children are needed for extrapolations to be biologically plausible. One such assumption is that of similar exposure–response (E–R‐) relationships. Motivated by applications to antiepileptic drug development, we consider how data that are available from existing trials of adults and adolescents can be used to quantify prior uncertainty about whether E–R‐relationships are similar in adults and younger children. A Bayesian multivariate meta‐analytic model is fitted to existing E–R‐data and adjusted for external biases that arise because these data are not perfectly relevant to the comparison of interest. We propose a strategy for eliciting expert prior opinion on external biases. From the bias‐adjusted meta‐analysis, we derive prior distributions quantifying our uncertainty about the degree of similarity between E–R‐relationships for adults and younger children. Using these we calculate the prior probability that average pharmacodynamic responses in adults and younger children, both on placebo and at an effective concentration, are sufficiently similar to justify a complete extrapolation of efficacy data. A simulation study is performed to evaluate the operating characteristics of the approach proposed.",
keywords = "Bias, Clinical trials, Elicitation, Extrapolation, Meta-analysis, Paediatrics",
author = "I. Wadsworth and L.V. Hampson and T. Jaki and G.J. Sills and A.G. Marson and R. Appleton",
year = "2020",
month = feb,
day = "1",
doi = "10.1111/rssa.12532",
language = "English",
volume = "183",
pages = "515--534",
journal = "Journal of the Royal Statistical Society: Series A Statistics in Society",
issn = "0964-1998",
publisher = "Wiley",
number = "2",

}

RIS

TY - JOUR

T1 - A quantitative framework to inform extrapolation decisions in children

AU - Wadsworth, I.

AU - Hampson, L.V.

AU - Jaki, T.

AU - Sills, G.J.

AU - Marson, A.G.

AU - Appleton, R.

PY - 2020/2/1

Y1 - 2020/2/1

N2 - When developing a new medicine for children, the potential to extrapolate from adult efficacy data is well recognized. However, significant assumptions about the similarity of adults and children are needed for extrapolations to be biologically plausible. One such assumption is that of similar exposure–response (E–R‐) relationships. Motivated by applications to antiepileptic drug development, we consider how data that are available from existing trials of adults and adolescents can be used to quantify prior uncertainty about whether E–R‐relationships are similar in adults and younger children. A Bayesian multivariate meta‐analytic model is fitted to existing E–R‐data and adjusted for external biases that arise because these data are not perfectly relevant to the comparison of interest. We propose a strategy for eliciting expert prior opinion on external biases. From the bias‐adjusted meta‐analysis, we derive prior distributions quantifying our uncertainty about the degree of similarity between E–R‐relationships for adults and younger children. Using these we calculate the prior probability that average pharmacodynamic responses in adults and younger children, both on placebo and at an effective concentration, are sufficiently similar to justify a complete extrapolation of efficacy data. A simulation study is performed to evaluate the operating characteristics of the approach proposed.

AB - When developing a new medicine for children, the potential to extrapolate from adult efficacy data is well recognized. However, significant assumptions about the similarity of adults and children are needed for extrapolations to be biologically plausible. One such assumption is that of similar exposure–response (E–R‐) relationships. Motivated by applications to antiepileptic drug development, we consider how data that are available from existing trials of adults and adolescents can be used to quantify prior uncertainty about whether E–R‐relationships are similar in adults and younger children. A Bayesian multivariate meta‐analytic model is fitted to existing E–R‐data and adjusted for external biases that arise because these data are not perfectly relevant to the comparison of interest. We propose a strategy for eliciting expert prior opinion on external biases. From the bias‐adjusted meta‐analysis, we derive prior distributions quantifying our uncertainty about the degree of similarity between E–R‐relationships for adults and younger children. Using these we calculate the prior probability that average pharmacodynamic responses in adults and younger children, both on placebo and at an effective concentration, are sufficiently similar to justify a complete extrapolation of efficacy data. A simulation study is performed to evaluate the operating characteristics of the approach proposed.

KW - Bias

KW - Clinical trials

KW - Elicitation

KW - Extrapolation

KW - Meta-analysis

KW - Paediatrics

U2 - 10.1111/rssa.12532

DO - 10.1111/rssa.12532

M3 - Journal article

VL - 183

SP - 515

EP - 534

JO - Journal of the Royal Statistical Society: Series A Statistics in Society

JF - Journal of the Royal Statistical Society: Series A Statistics in Society

SN - 0964-1998

IS - 2

ER -