» Articles » PMID: 27323698

Measuring the Individual Benefit of a Medical or Behavioral Treatment Using Generalized Linear Mixed-effects Models

Overview
Journal Stat Med
Publisher Wiley
Specialty Public Health
Date 2016 Jun 22
PMID 27323698
Citations 9
Authors
Affiliations
Soon will be listed here.
Abstract

We propose statistical definitions of the individual benefit of a medical or behavioral treatment and of the severity of a chronic illness. These definitions are used to develop a graphical method that can be used by statisticians and clinicians in the data analysis of clinical trials from the perspective of personalized medicine. The method focuses on assessing and comparing individual effects of treatments rather than average effects and can be used with continuous and discrete responses, including dichotomous and count responses. The method is based on new developments in generalized linear mixed-effects models, which are introduced in this article. To illustrate, analyses of data from the Sequenced Treatment Alternatives to Relieve Depression clinical trial of sequences of treatments for depression and data from a clinical trial of respiratory treatments are presented. The estimation of individual benefits is also explained. Copyright © 2016 John Wiley & Sons, Ltd.

Citing Articles

Active Ingredients of Voice Therapy for Muscle Tension Voice Disorders: A Retrospective Data Audit.

Madill C, Chacon A, Kirby E, Novakovic D, Nguyen D J Clin Med. 2021; 10(18).

PMID: 34575246 PMC: 8469541. DOI: 10.3390/jcm10184135.


Using population crossover trials to improve the decision process regarding treatment individualization in N-of-1 trials.

Diaz F Stat Med. 2021; 40(20):4345-4361.

PMID: 34213011 PMC: 10773237. DOI: 10.1002/sim.9030.


Improvement in the long-term care burden after surgical treatment of patients with idiopathic normal pressure hydrocephalus: a supplementary study.

Ishikawa M, Yamada S, Miyajima M, Kazui H, Mori E Sci Rep. 2021; 11(1):11732.

PMID: 34083550 PMC: 8175749. DOI: 10.1038/s41598-021-90911-2.


A graphical approach to assess the goodness-of-fit of random-effects linear models when the goal is to measure individual benefits of medical treatments in severely ill patients.

Wang Z, Diaz F BMC Med Res Methodol. 2020; 20(1):193.

PMID: 32689939 PMC: 7370523. DOI: 10.1186/s12874-020-01054-3.


Measuring individual benefits of psychiatric treatment using longitudinal binary outcomes: Application to antipsychotic benefits in non-cannabis and cannabis users.

Zhang X, De Leon J, Crespo-Facorro B, Diaz F J Biopharm Stat. 2020; 30(5):916-940.

PMID: 32511941 PMC: 9030227. DOI: 10.1080/10543406.2020.1765371.


References
1.
Sharp S, Thompson S, Altman D . The relation between treatment benefit and underlying risk in meta-analysis. BMJ. 1996; 313(7059):735-8. PMC: 2352108. DOI: 10.1136/bmj.313.7059.735. View

2.
Whiting B, Kelman A, Grevel J . Population pharmacokinetics. Theory and clinical application. Clin Pharmacokinet. 1986; 11(5):387-401. DOI: 10.2165/00003088-198611050-00004. View

3.
Diaz F, Berg M, Krebill R, Welty T, Gidal B, Alloway R . Random-effects linear modeling and sample size tables for two special crossover designs of average bioequivalence studies: the four-period, two-sequence, two-formulation and six-period, three-sequence, three-formulation designs. Clin Pharmacokinet. 2013; 52(12):1033-43. DOI: 10.1007/s40262-013-0103-4. View

4.
Diaz F, Eap C, Ansermot N, Crettol S, Spina E, De Leon J . Can valproic acid be an inducer of clozapine metabolism?. Pharmacopsychiatry. 2014; 47(3):89-96. PMC: 4229130. DOI: 10.1055/s-0034-1371866. View

5.
Senn S . Mastering variation: variance components and personalised medicine. Stat Med. 2015; 35(7):966-77. PMC: 5054923. DOI: 10.1002/sim.6739. View