Predicting outcomes following holistic breathlessness services: A pooled analysis of individual patient data

Holistic breathlessness services have been developed for people with advanced disease and chronic breathlessness, leading to improved psychological aspects of breathlessness and health. The extent to which patient characteristics influence outcomes is unclear. To identify patient characteristics predicting outcomes of mastery and distress due to breathlessness following holistic breathlessness services. Secondary analysis of pooled individual patient data from three clinical trials. Our primary analysis assessed predictors of clinically important improvements in Chronic Respiratory Questionnaire mastery scores (+0.5 point), and our secondary analysis predictors of improvements in Numerical Rating Scale distress due to breathlessness (？1 point). Variables significantly related to improvement in univariate models were considered in separate backwards stepwise logistic regression models. The dataset comprised 259 participants (118 female; mean (standard deviation) age 69.2 (10.6)？years) with primary diagnoses of chronic obstructive pulmonary disease (49.8%), cancer (34.7%) and interstitial lung disease (10.4%). Controlling for age, sex and trial, baseline mastery remained the only significant independent predictor of improvement in mastery (odds ratio 0.57, 95% confidence intervals 0.43–0.74; p？<？0.001), and baseline distress remained the only significant predictor of improvement in distress (odds ratio 1.64; 95% confidence intervals 1.35–2.03; p？<？0.001). Baseline lung function, breathlessness severity, health status, mild anxiety and depression, and diagnosis did not predict outcomes. Outcomes of mastery and distress following holistic breathlessness services are influenced by baseline scores for these variables, and not by diagnosis, lung function or health status. Stratifying patients by levels of mastery and/or distress due to breathlessness appears appropriate for clinical trials and services