Confidence interval criteria for assessment of dose proportionality

B. P. Smith, F. R. Vandenhende, K. A. DeSante, N. A. Farid, P. A. Welch, John Callaghan, S. T. Forgue

Research output: Contribution to journalArticle

213 Citations (Scopus)

Abstract

Purpose. The aim of this work was a pragmatic, statistically sound and clinically relevant approach to dose-proportionality analyses that is compatible with common study designs. Methods. Statistical estimation is used to derive a (1-α)% confidence interval (CI) for the ratio of dose-normalized, geometric mean values (R(dnm)) of a pharmacokinetic variable (PK). An acceptance interval for R(dnm) defining the clinically relevant, dose-proportional region is established a priori. Proportionality is declared if the CI for R(dnm) is completely contained within the critical region. The approach is illustrated with mixed-effects models based on a power function of the form PK = β0 · Dose(β1); however, the logic holds for other functional forms. Results. It was observed that the dose-proportional region delineated by a power model depends only on the dose ratio. Furthermore, a dose ratio (ρ1) can be calculated such that the CI lies entirely within the pre-specified critical region. A larger ratio (ρ2) may exist such that the CI lies completely outside that region. The approach supports inferences about the PK response that are not constrained to the exact dose levels studied. Conclusion. The proposed method enhances the information from a clinical dose-proportionality study and helps to standardize decision rules.

Original languageEnglish
Pages (from-to)1278-1283
Number of pages6
JournalPharmaceutical Research
Volume17
Issue number10
StatePublished - 2000

Fingerprint

Pharmacokinetics
Confidence Intervals
Acoustic waves

Keywords

  • Bioequivalence
  • Dose proportionality
  • Mixed effects model
  • Pharmacokinetics
  • Power model

ASJC Scopus subject areas

  • Chemistry(all)
  • Pharmaceutical Science
  • Pharmacology

Cite this

Smith, B. P., Vandenhende, F. R., DeSante, K. A., Farid, N. A., Welch, P. A., Callaghan, J., & Forgue, S. T. (2000). Confidence interval criteria for assessment of dose proportionality. Pharmaceutical Research, 17(10), 1278-1283.

Confidence interval criteria for assessment of dose proportionality. / Smith, B. P.; Vandenhende, F. R.; DeSante, K. A.; Farid, N. A.; Welch, P. A.; Callaghan, John; Forgue, S. T.

In: Pharmaceutical Research, Vol. 17, No. 10, 2000, p. 1278-1283.

Research output: Contribution to journalArticle

Smith, BP, Vandenhende, FR, DeSante, KA, Farid, NA, Welch, PA, Callaghan, J & Forgue, ST 2000, 'Confidence interval criteria for assessment of dose proportionality', Pharmaceutical Research, vol. 17, no. 10, pp. 1278-1283.
Smith BP, Vandenhende FR, DeSante KA, Farid NA, Welch PA, Callaghan J et al. Confidence interval criteria for assessment of dose proportionality. Pharmaceutical Research. 2000;17(10):1278-1283.
Smith, B. P. ; Vandenhende, F. R. ; DeSante, K. A. ; Farid, N. A. ; Welch, P. A. ; Callaghan, John ; Forgue, S. T. / Confidence interval criteria for assessment of dose proportionality. In: Pharmaceutical Research. 2000 ; Vol. 17, No. 10. pp. 1278-1283.
@article{7224f6d19c454e128b57e6d397bee5f1,
title = "Confidence interval criteria for assessment of dose proportionality",
abstract = "Purpose. The aim of this work was a pragmatic, statistically sound and clinically relevant approach to dose-proportionality analyses that is compatible with common study designs. Methods. Statistical estimation is used to derive a (1-α){\%} confidence interval (CI) for the ratio of dose-normalized, geometric mean values (R(dnm)) of a pharmacokinetic variable (PK). An acceptance interval for R(dnm) defining the clinically relevant, dose-proportional region is established a priori. Proportionality is declared if the CI for R(dnm) is completely contained within the critical region. The approach is illustrated with mixed-effects models based on a power function of the form PK = β0 · Dose(β1); however, the logic holds for other functional forms. Results. It was observed that the dose-proportional region delineated by a power model depends only on the dose ratio. Furthermore, a dose ratio (ρ1) can be calculated such that the CI lies entirely within the pre-specified critical region. A larger ratio (ρ2) may exist such that the CI lies completely outside that region. The approach supports inferences about the PK response that are not constrained to the exact dose levels studied. Conclusion. The proposed method enhances the information from a clinical dose-proportionality study and helps to standardize decision rules.",
keywords = "Bioequivalence, Dose proportionality, Mixed effects model, Pharmacokinetics, Power model",
author = "Smith, {B. P.} and Vandenhende, {F. R.} and DeSante, {K. A.} and Farid, {N. A.} and Welch, {P. A.} and John Callaghan and Forgue, {S. T.}",
year = "2000",
language = "English",
volume = "17",
pages = "1278--1283",
journal = "Pharmaceutical Research",
issn = "0724-8741",
publisher = "Springer New York",
number = "10",

}

TY - JOUR

T1 - Confidence interval criteria for assessment of dose proportionality

AU - Smith, B. P.

AU - Vandenhende, F. R.

AU - DeSante, K. A.

AU - Farid, N. A.

AU - Welch, P. A.

AU - Callaghan, John

AU - Forgue, S. T.

PY - 2000

Y1 - 2000

N2 - Purpose. The aim of this work was a pragmatic, statistically sound and clinically relevant approach to dose-proportionality analyses that is compatible with common study designs. Methods. Statistical estimation is used to derive a (1-α)% confidence interval (CI) for the ratio of dose-normalized, geometric mean values (R(dnm)) of a pharmacokinetic variable (PK). An acceptance interval for R(dnm) defining the clinically relevant, dose-proportional region is established a priori. Proportionality is declared if the CI for R(dnm) is completely contained within the critical region. The approach is illustrated with mixed-effects models based on a power function of the form PK = β0 · Dose(β1); however, the logic holds for other functional forms. Results. It was observed that the dose-proportional region delineated by a power model depends only on the dose ratio. Furthermore, a dose ratio (ρ1) can be calculated such that the CI lies entirely within the pre-specified critical region. A larger ratio (ρ2) may exist such that the CI lies completely outside that region. The approach supports inferences about the PK response that are not constrained to the exact dose levels studied. Conclusion. The proposed method enhances the information from a clinical dose-proportionality study and helps to standardize decision rules.

AB - Purpose. The aim of this work was a pragmatic, statistically sound and clinically relevant approach to dose-proportionality analyses that is compatible with common study designs. Methods. Statistical estimation is used to derive a (1-α)% confidence interval (CI) for the ratio of dose-normalized, geometric mean values (R(dnm)) of a pharmacokinetic variable (PK). An acceptance interval for R(dnm) defining the clinically relevant, dose-proportional region is established a priori. Proportionality is declared if the CI for R(dnm) is completely contained within the critical region. The approach is illustrated with mixed-effects models based on a power function of the form PK = β0 · Dose(β1); however, the logic holds for other functional forms. Results. It was observed that the dose-proportional region delineated by a power model depends only on the dose ratio. Furthermore, a dose ratio (ρ1) can be calculated such that the CI lies entirely within the pre-specified critical region. A larger ratio (ρ2) may exist such that the CI lies completely outside that region. The approach supports inferences about the PK response that are not constrained to the exact dose levels studied. Conclusion. The proposed method enhances the information from a clinical dose-proportionality study and helps to standardize decision rules.

KW - Bioequivalence

KW - Dose proportionality

KW - Mixed effects model

KW - Pharmacokinetics

KW - Power model

UR - http://www.scopus.com/inward/record.url?scp=0033634992&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033634992&partnerID=8YFLogxK

M3 - Article

VL - 17

SP - 1278

EP - 1283

JO - Pharmaceutical Research

JF - Pharmaceutical Research

SN - 0724-8741

IS - 10

ER -