Efficacy and safety of two doses of budesonide/formoterol fumarate metered dose inhaler in COPD

Hanania, Nicola A.; Papi, Alberto; Anzueto, Antonio; Martínez, Fernando J.; Rossman, Kimberly; Cappelletti, Christy; Duncan, Elizabeth A.; Nyberg, Jack; Dorinsky, Paul

doi:10.1183/23120541.00187-2019

Cited by 8 publications

(11 citation statements)

References 30 publications

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“…The database included pooled exacerbation data from a total of 20,054 patients from ETHOS (NCT02465567), 13 KRONOS (NCT02497001), 12 TELOS (NCT02766608), 20 SOPHOS (NCT02727660), 21 PINNACLE-1 (NCT01854645), 22 PINNACLE-2 (NCT01854658), 22 and PINNACLE-4 (NCT02343458) 24 ( Table 1 ). Data from extension studies (up to 1 year in duration) of KRONOS (NCT03262012, NCT02536508) 18 , 19 and PINNACLE-1 and PINNACLE-2 (PINNACLE-3; NCT01970878) 23 were also included.…”

Section: Methodsmentioning

confidence: 99%

Predictive modeling of COPD exacerbation rates using baseline risk factors

Singh

Hurst

Martínez

et al. 2022

Ther Adv Respir Dis

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Background: Demographic and disease characteristics have been associated with the risk of chronic obstructive pulmonary disease (COPD) exacerbations. Using previously collected multinational clinical trial data, we developed models that use baseline risk factors to predict an individual’s rate of moderate/severe exacerbations in the next year on various pharmacological treatments for COPD. Methods: Exacerbation data from 20,054 patients in the ETHOS, KRONOS, TELOS, SOPHOS, and PINNACLE-1, PINNACLE-2, and PINNACLE-4 studies were pooled. Machine learning was used to identify predictors of moderate/severe exacerbation rates. Important factors were selected for generalized linear modeling, further informed by backward variable selection. An independent test set was held back for validation. Results: Prior exacerbations, eosinophil count, forced expiratory volume in 1 s percent predicted, prior maintenance treatments, reliever medication use, sex, COPD Assessment Test score, smoking status, and region were significant predictors of exacerbation risk, with response to inhaled corticosteroids (ICSs) increasing with higher eosinophil counts, more prior exacerbations, or additional prior treatments. Model fit was similar in the training and test set. Prediction metrics were ~10% better in the full model than in a simplified model based only on eosinophil count, prior exacerbations, and ICS use. Conclusion: These models predicting rates of moderate/severe exacerbations can be applied to a broad range of patients with COPD in terms of airway obstruction, eosinophil counts, exacerbation history, symptoms, and treatment history. Understanding the relative and absolute risks related to these factors may be useful for clinicians in evaluating the benefit: risk ratio of various treatment decisions for individual patients. Clinical trials registered with www.clinicaltrials.gov (NCT02465567, NCT02497001, NCT02766608, NCT02727660, NCT01854645, NCT01854658, NCT02343458, NCT03262012, NCT02536508, and NCT01970878)

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Section: Methodsmentioning

confidence: 99%

Predictive modeling of COPD exacerbation rates using baseline risk factors

Singh

Hurst

Martínez

et al. 2022

Ther Adv Respir Dis

Self Cite

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“…Patients with COPD who experience persistent exacerbations may have elevated blood eosinophil levels compared to those who have fewer exacerbations, and ICS-containing regimens (including triple therapy) have demonstrably improved lung function in such patients. 35 , 41 Although biomarkers were not analyzed, and their influence on prescription patterns was not evaluated in our study, this could nevertheless be an area of interest in future real-world data analyses for informing optimal patient treatment and management.…”

Section: Discussionmentioning

confidence: 99%

A Real-World Analysis of Treatment Patterns and Clinical Characteristics Among Patients with COPD Who Initiated Multiple-Inhaler Triple Therapy in New Zealand

Xu¹,

Miléa²,

Rojas³

et al. 2021

COPD

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Purpose Real-world data on maintenance treatment and prescription patterns provide insights into healthcare management among patients with chronic obstructive pulmonary disease (COPD), which benefits our understanding of current COPD treatment patterns in New Zealand. Methods We retrospectively analyzed real-world data from the HealthStat general practice database to evaluate treatment patterns among patients with COPD in New Zealand who initiated multiple-inhaler triple therapy (MITT): inhaled corticosteroid (ICS) + long-acting muscarinic antagonist + long-acting β 2 -agonist (LABA). Our main objective described treatment patterns (class, duration, modification, persistence, and adherence) and characteristics of patients with COPD initiating MITT between 1 May 2016 and 30 April 2017, with 12-months’ follow-up. We also assessed the number of patients receiving MITT between 2015 and 2017, among a larger patient population receiving long-acting bronchodilator and ICS-containing therapies. Results Of 6249 eligible patients, 421 (mean age 67.3 years; mean number exacerbations at baseline 1.8) initiated MITT: 59.1% received combination ICS/LABA therapy prior to MITT initiation, and median treatment duration prior to MITT initiation was 350 days. Overall, 33.5% of patients remained on index treatment for 12 months. Of the remaining patients who modified treatment (on average at 144.4 days), those who had a direct switch (24.9%) or retreatment (13.5%) remained on MITT, 19.7% of patients stepped down to mono/dual therapy, and 8.3% discontinued treatment. Mean (standard deviation) persistence to any MITT over 12 months was 47.3 (50.0), and 53.4% of patients were considered adherent to MITT. Total proportions of patients receiving long-acting bronchodilator therapy and MITT increased between 2015 and 2017. Conclusion Most patients with COPD in New Zealand who initiated MITT had characteristics appropriate for triple therapy prescription, suggesting prescription behavior among general practitioners was largely consistent with treatment guidelines. Our findings may help optimize treatment decisions, with a focus on improving long-term triple therapy persistence and adherence.

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“…To prepare data for synthesis, some data conversions were needed. If data was reported in mL [31,32] we converted it into L. In Bafadhel et al [16], we calculated a mean based on the data provided in their supplemental material, i.e. EOS estimates ranging from 5 to 140, 150 to 300 and 310 to 2510.…”

Section: Strategy For Data Synthesismentioning

confidence: 99%