Using marginal structural models to analyze randomized clinical trials with non-adherence and lost to follow up

Copyright © 2021 Elsevier Inc. All rights reserved..

BACKGROUND: In the presence of non-adherence and lost to follow up, results of an Intention to Treat (ITT) analysis may be biased as it is measuring the effect of assignment rather than the effect of treatment. Given that Marginal Structural Models (MSMs) adjust for such issues, this study examines the use of MSMs to assess the validity of ITT analyses in the presence of non-adherence and lost to follow up in an existing randomized clinical trial on asthma treatment.

METHODS: Inverse probability weights were obtained from a pooled logistic regression assessing the probability of staying on assigned treatment (adherence) and of remaining uncensored (censored) for subjects at each visit by treatment arm. Weights were then pooled into a MSM analysis using a Poisson generalized estimating equation with an independent correlation matrix.

RESULTS: Out of 488 participants, 174 (36%) did not adhere to the baseline assignment and 85 (17%) were lost to follow up by the end of the study. The adjusted relative risks (RR), and 95% confidence intervals (CI), obtained from the MSMs (theophylline vs. montelukast; RR=1.24; 95% CI: 0.83,1.84; theophylline vs. placebo: RR=1.01; 95% CI: 0.70,1.48; and montelukast vs. placebo: RR=0.83; 95% CI: 0.57,1.19) were nearly identical to that of the ITT analysis (theophylline vs. montelukast: RR=1.22; 95% CI: 0.82,1.86; theophylline vs. placebo: RR=0.99; 95% CI: 0.67,1.50; and montelukast vs. placebo: RR=0.82; 95% CI: 0.55,1.21).

CONCLUSION: Concordance between the results of ITT and MSMs indicate adherence and censoring may not invalidate ITT analysis. However, no adherence or censorship thresholds currently exist to assist researchers in determining when MSMs may be superior to ITT in the analysis of clinical trials with non-adherence or censorship issues, and therefore, MSMs should be conducted as a sensitivity analysis to the ITT approach in clinical trials.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:63

Enthalten in:

Annals of epidemiology - 63(2021) vom: 15. Nov., Seite 22-28

Sprache:

Englisch

Beteiligte Personen:

Lancet, Elizabeth A [VerfasserIn]
Borrell, Luisa N [VerfasserIn]
Holbrook, Janet [VerfasserIn]
Morabia, Alfredo [VerfasserIn]

Links:

Volltext

Themen:

Causalinference
Clinical trials
Intention to treat
Inverse probability weighting
Journal Article
Marginal structural models

Anmerkungen:

Date Completed 19.10.2021

Date Revised 31.05.2022

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1016/j.annepidem.2021.07.001

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM328344311