Key result
Machine learning models using brain imaging predict breathlessness improvements during pulmonary rehabilitation with ~83% accuracy.
Why the study?
Baseline patient characteristics predicting improvements in chronic breathlessness in COPD during pulmonary rehabilitation were unknown.
Does D-cycloserine improve breathlessness and do functional brain imaging markers predict therapeutic response to pulmonary rehabilitation in patients with mild-to-moderate COPD?
RCT (n=71)
Double-blind
Randomized
No
Does D-cycloserine improve breathlessness and do functional brain imaging markers predict therapeutic response to pulmonary rehabilitation in patients with mild-to-moderate COPD?
Brain activity related to breathlessness expectation is a strong predictor of clinical improvement in breathlessness during pulmonary rehabilitation in COPD patients.
Answers are grounded in this paper and cite their sources.
Brain imaging markers may identify likely responders to pulmonary rehabilitation in COPD; extends RCT evidence on breathlessness-expectation prediction.
Background Chronic breathlessness in COPD is effectively treated with pulmonary rehabilitation. However, baseline patient characteristics predicting improvements in breathlessness are unknown. This knowledge may provide better understanding of the mechanisms engaged in treating breathlessness, helping to individualise therapy. Increasing evidence supports the role of expectation (i.e. placebo and nocebo effects) in breathlessness perception. In this study, we tested functional brain imaging markers of breathlessness expectation as predictors of therapeutic response to pulmonary rehabilitation, and whether D-cycloserine, a brain-active drug known to influence expectation mechanisms, modulates any predictive model. Methods Data from 72 participants with mild-to-moderate COPD recruited to a randomised double-blind controlled experimental medicine study of D-cycloserine given during pulmonary rehabilitation was analysed (ID: NCT01985750 ). Baseline variables, including brain-activity, self-report questionnaires responses, clinical measures of respiratory function and drug allocation were used to train machine-learning models to predict the outcome, a minimally clinically relevant change in the dyspnoea-12 score. Findings Only models that included brain imaging markers of breathlessness-expectation successfully predicted improvements in dyspnoea-12 score (sensitivity 0.88, specificity 0.77). D-cycloserine was independently associated with breathlessness improvement. Models that included only questionnaires and clinical measures did not predict outcome (sensitivity 0.68, specificity 0.2). Interpretation Brain activity to breathlessness related cues is a strong predictor of clinical improvement in breathlessness over pulmonary rehabilitation. This implies that expectation is key in breathlessness perception. Manipulation of the brain’s expectation pathways (either pharmacological or non-pharmacological) merits further testing in the treatment of chronic breathlessness. Funding This work was supported by the JABBS Foundation Research in context Evidence before the study Despite considerable research we still do not know which patient characteristics predict clinical improvements in breathlessness following pulmonary rehabilitation. Recent evidence suggests that the brain processes associated with breathlessness-expectation play an important contributory role in breathlessness severity. However, this has never been examined as a predictor of pulmonary rehabilitation outcome. The ability to predict outcomes has a number of potential benefits, including identifying targets for personalised medicine and the better allocation of scare healthcare resources via parallel care pathways. Added value of the study This study analysed data from a longitudinal experimental medicine study of 71 patients with COPD over a course of pulmonary rehabilitation, that used functional magnetic resonance imaging testing breathlessness-expectation mechanisms in the brain. Participants were randomised in a double-blind procedure to receive either 250mg oral D-cycloserine or a matched placebo. Using baseline variables to train machine learning models we revealed that only models containing brain markers of breathlessness-expectation successfully predicted improvements in dyspnoea-12 score (sensitivity 0.88, specificity 0.77). D-cycloserine use was independently associated with breathlessness improvements. Models that only contained questionnaire and clinical measure did not predict outcome (sensitivity 0.68, specificity 0.2). Implications of all the available evidence These findings are the first evidence that breathlessness-expectation related brain activity is a strong predictor of clinical improvement in breathlessness over pulmonary rehabilitation. This implies that expectation is a key mechanism in breathlessness perception and that the manipulation of the brain’s expectation pathways merits further testing as a novel therapeutic approach for breathlessness.
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Finnegan et al. (2021) conducted an RCT in mild-to-moderate COPD (n=71). D-cycloserine vs. Placebo was evaluated on Prediction of minimally clinically relevant change in dyspnoea-12 score (≥3 points) (Accuracy 0.83, 95% CI 0.75-0.90, p=<0.001). Machine learning models incorporating brain imaging markers of breathlessness-expectation successfully predicted clinical improvements in breathlessness during pulmonary rehabilitation with an accuracy of 0.83.
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