Population repeated time-to-event analysis of exacerbations in asthma patients : A novel approach for predicting asthma exacerbations based on biomarkers, spirometry, and diaries/questionnaires
| Autor: | Mats O. Karlsson, Angelica Quartino, Dorothy Cheung, Naoki Kotani, Tracy Staton, Robin J Svensson, Jakob Ribbing, Michael J. Dolton, Jin Jin, Shweta Vadhavkar, Nageshwar Budha, Rui Zhu, Wendy S. Putnam, David F. Choy |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Adult
Male Spirometry medicine.medical_specialty Time Factors Exacerbation Respiratory Medicine and Allergy Population Anti-Inflammatory Agents RM1-950 Antibodies Monoclonal Humanized Placebo Severity of Illness Index Article Double-Blind Method Surveys and Questionnaires Internal medicine Covariate medicine Humans Pharmacology (medical) education Survival analysis Proportional Hazards Models Asthma Lungmedicin och allergi education.field_of_study medicine.diagnostic_test business.industry Research Articles Middle Aged medicine.disease Random effects model Progression-Free Survival Modeling and Simulation Disease Progression Female Therapeutics. Pharmacology business Biomarkers |
| Zdroj: | CPT: Pharmacometrics & Systems Pharmacology CPT: Pharmacometrics & Systems Pharmacology, Vol 10, Iss 10, Pp 1221-1235 (2021) |
| Popis: | 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 |
| Databáze: | OpenAIRE |
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