Demonstrating Contribution of Components of Fixed-Dose Drug Combinations Through Longitudinal Exposure-Response Analysis

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Demonstrating Contribution of Components of Fixed-Dose Drug Combinations Through Longitudinal Exposure-Response Analysis. / Nøhr-Nielsen, Asbjørn; Lange, Theis; Forman, Julie Lyng; Papathanasiou, Theodoros; Foster, David J R; Upton, Richard N; Bjerrum, Ole Jannik; Lund, Trine Meldgaard.

I: The AAPS Journal, Bind 22, Nr. 2, 32, 2020.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Nøhr-Nielsen, A, Lange, T, Forman, JL, Papathanasiou, T, Foster, DJR, Upton, RN, Bjerrum, OJ & Lund, TM 2020, 'Demonstrating Contribution of Components of Fixed-Dose Drug Combinations Through Longitudinal Exposure-Response Analysis', The AAPS Journal, bind 22, nr. 2, 32. https://doi.org/10.1208/s12248-020-0414-y

APA

Nøhr-Nielsen, A., Lange, T., Forman, J. L., Papathanasiou, T., Foster, D. J. R., Upton, R. N., ... Lund, T. M. (2020). Demonstrating Contribution of Components of Fixed-Dose Drug Combinations Through Longitudinal Exposure-Response Analysis. The AAPS Journal, 22(2), [32]. https://doi.org/10.1208/s12248-020-0414-y

Vancouver

Nøhr-Nielsen A, Lange T, Forman JL, Papathanasiou T, Foster DJR, Upton RN o.a. Demonstrating Contribution of Components of Fixed-Dose Drug Combinations Through Longitudinal Exposure-Response Analysis. The AAPS Journal. 2020;22(2). 32. https://doi.org/10.1208/s12248-020-0414-y

Author

Nøhr-Nielsen, Asbjørn ; Lange, Theis ; Forman, Julie Lyng ; Papathanasiou, Theodoros ; Foster, David J R ; Upton, Richard N ; Bjerrum, Ole Jannik ; Lund, Trine Meldgaard. / Demonstrating Contribution of Components of Fixed-Dose Drug Combinations Through Longitudinal Exposure-Response Analysis. I: The AAPS Journal. 2020 ; Bind 22, Nr. 2.

Bibtex

@article{8dab27488abb4b15b6b9f76477f4c8ba,
title = "Demonstrating Contribution of Components of Fixed-Dose Drug Combinations Through Longitudinal Exposure-Response Analysis",
abstract = "Exposure-response (ER) modeling for fixed-dose combinations (FDC) has previously been found to have an inflated false positive rate (FP), i.e., observing a significant effect of FDC components when no true effect exists. Longitudinal exposure-response (LER) analysis utilizes the time course of the data and is valid for several clinical endpoints for FDCs. The aim of the study was to investigate if LER is applicable for the validation of FDCs by demonstrating the contribution of each component to the overall effect without inflation of FP rates. FP and FN rates associated with ER and LER analysis were investigated using stochastic simulation and estimation. Four hundred thirty-two scenarios with varying numbers of patients, duration, sampling frequency, dose distribution, design, and drug activity were analyzed using a range of linear, log-linear, and non-linear models to asses FP and FN rates. Lastly, the impact of the clinical trial parameters was investigated. LER analyses provided well-controlled FP rates of the expected 5{\%} or less; however, in low information clinical trials consisting of 30 patients, 4 samples, and 20 days, LER analyses lead to inflated FN rates. Parameter investigation showed that when the clinical trial includes sufficient patients, duration, samples, and an appropriate trial design, the FN rates are in general below the expected 5{\%} for LER analysis. Based on the results, LER analysis can be used for the validation of FDCs and fixed ratio drug combinations. The method constitutes a new avenue for providing evidence that demonstrates the contribution of each component to the overall clinical effect.",
author = "Asbj{\o}rn N{\o}hr-Nielsen and Theis Lange and Forman, {Julie Lyng} and Theodoros Papathanasiou and Foster, {David J R} and Upton, {Richard N} and Bjerrum, {Ole Jannik} and Lund, {Trine Meldgaard}",
year = "2020",
doi = "10.1208/s12248-020-0414-y",
language = "English",
volume = "22",
journal = "A A P S Journal",
issn = "1550-7416",
publisher = "Springer",
number = "2",

}

RIS

TY - JOUR

T1 - Demonstrating Contribution of Components of Fixed-Dose Drug Combinations Through Longitudinal Exposure-Response Analysis

AU - Nøhr-Nielsen, Asbjørn

AU - Lange, Theis

AU - Forman, Julie Lyng

AU - Papathanasiou, Theodoros

AU - Foster, David J R

AU - Upton, Richard N

AU - Bjerrum, Ole Jannik

AU - Lund, Trine Meldgaard

PY - 2020

Y1 - 2020

N2 - Exposure-response (ER) modeling for fixed-dose combinations (FDC) has previously been found to have an inflated false positive rate (FP), i.e., observing a significant effect of FDC components when no true effect exists. Longitudinal exposure-response (LER) analysis utilizes the time course of the data and is valid for several clinical endpoints for FDCs. The aim of the study was to investigate if LER is applicable for the validation of FDCs by demonstrating the contribution of each component to the overall effect without inflation of FP rates. FP and FN rates associated with ER and LER analysis were investigated using stochastic simulation and estimation. Four hundred thirty-two scenarios with varying numbers of patients, duration, sampling frequency, dose distribution, design, and drug activity were analyzed using a range of linear, log-linear, and non-linear models to asses FP and FN rates. Lastly, the impact of the clinical trial parameters was investigated. LER analyses provided well-controlled FP rates of the expected 5% or less; however, in low information clinical trials consisting of 30 patients, 4 samples, and 20 days, LER analyses lead to inflated FN rates. Parameter investigation showed that when the clinical trial includes sufficient patients, duration, samples, and an appropriate trial design, the FN rates are in general below the expected 5% for LER analysis. Based on the results, LER analysis can be used for the validation of FDCs and fixed ratio drug combinations. The method constitutes a new avenue for providing evidence that demonstrates the contribution of each component to the overall clinical effect.

AB - Exposure-response (ER) modeling for fixed-dose combinations (FDC) has previously been found to have an inflated false positive rate (FP), i.e., observing a significant effect of FDC components when no true effect exists. Longitudinal exposure-response (LER) analysis utilizes the time course of the data and is valid for several clinical endpoints for FDCs. The aim of the study was to investigate if LER is applicable for the validation of FDCs by demonstrating the contribution of each component to the overall effect without inflation of FP rates. FP and FN rates associated with ER and LER analysis were investigated using stochastic simulation and estimation. Four hundred thirty-two scenarios with varying numbers of patients, duration, sampling frequency, dose distribution, design, and drug activity were analyzed using a range of linear, log-linear, and non-linear models to asses FP and FN rates. Lastly, the impact of the clinical trial parameters was investigated. LER analyses provided well-controlled FP rates of the expected 5% or less; however, in low information clinical trials consisting of 30 patients, 4 samples, and 20 days, LER analyses lead to inflated FN rates. Parameter investigation showed that when the clinical trial includes sufficient patients, duration, samples, and an appropriate trial design, the FN rates are in general below the expected 5% for LER analysis. Based on the results, LER analysis can be used for the validation of FDCs and fixed ratio drug combinations. The method constitutes a new avenue for providing evidence that demonstrates the contribution of each component to the overall clinical effect.

U2 - 10.1208/s12248-020-0414-y

DO - 10.1208/s12248-020-0414-y

M3 - Journal article

C2 - 31989328

VL - 22

JO - A A P S Journal

JF - A A P S Journal

SN - 1550-7416

IS - 2

M1 - 32

ER -

ID: 235477059