Open AccessPopulation repeated time‐to‐event analysis of exacerbations in asthma patients: A novel approach for predicting asthma exacerbations based on biomarkers, spirometry, and diaries/questionnaires
Author(s) -
Svensson Robin J,
Ribbing Jakob,
Kotani Naoki,
Dolton Michael,
Vadhavkar Shweta,
Cheung Dorothy,
Staton Tracy,
Choy David F,
Putnam Wendy,
Jin Jin,
Budha Nageshwar,
Karlsson Mats O.,
Quartino Angelica,
Zhu Rui
Publication year - 2021
Publication title -
cpt: pharmacometrics and systems pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.53
H-Index - 37
ISSN - 2163-8306
DOI - 10.1002/psp4.12690
Subject(s) - covariate , medicine , exacerbation , spirometry , asthma , population , hazard ratio , proportional hazards model , physical therapy , statistics , confidence interval , mathematics , environmental health
Identification of covariates, including biomarkers, spirometry, and diaries/questionnaires, that predict asthma exacerbations would allow better clinical predictions, shorter phase II trials and inform decisions on phase III design, and/or initiation (go/no‐go). The objective of this work was to characterize asthma‐exacerbation hazard as a function of baseline and time‐varying covariates. A repeated time‐to‐event (RTTE) model for exacerbations was developed using data from a 52‐week phase IIb trial, including 502 patients with asthma randomized to placebo or 70 mg, 210 mg, or 490 mg astegolimab every 4 weeks. Covariate analysis was performed for 20 baseline covariates using the full random effects modeling approach, followed by time‐varying covariate analysis of nine covariates using the stepwise covariate model (SCM) building procedure. Following the SCM, an astegolimab treatment effect was explored. Diary‐based symptom score (difference in objective function value [dOFV] of −83.7) and rescue medication use (dOFV = −33.5), and forced expiratory volume in 1 s (dOFV = −14.9) were identified as significant time‐varying covariates. Of note, time‐varying covariates become more useful with more frequent measurements, which should favor the daily diary scores over others. The most influential baseline covariates were exacerbation history and diary‐based symptom score (i.e., symptom score was important as both time‐varying and baseline covariate). A (nonsignificant) astegolimab treatment effect was included in the final model because the limited data set did not allow concluding the remaining effect size as irrelevant. Without time‐varying covariates, the treatment effect was statistically significant ( p < 0.01). This work demonstrated the utility of a population RTTE approach to characterize exacerbation hazard in patients with severe asthma.