ArticlesThe Acute COPD Exacerbation Prediction Tool (ACCEPT): a modelling study
Introduction
Chronic obstructive pulmonary disease (COPD) is characterised by symptoms of breathlessness and cough, which worsen acutely during exacerbations.1 COPD is known to be a heterogeneous disorder with large variations in risk of exacerbation across patients.2 In clinical practice, a history of two or more exacerbations and one severe exacerbation per year is used to guide therapeutic choices for exacerbation prevention.3 However, this approach is clinically restricted owing to substantial heterogeneity in risk even within those who frequently exacerbate.4
Prognostic clinical prediction tools enable personalised approaches to disease management. Despite potential benefits, no such tool is routinely used in clinical management of COPD. Whereas, for COPD-related mortality, clinical scoring schemes, such as the BODE index, are available and frequently used.5 A 2017 systematic review by Guerra and colleagues6 identified 27 prediction tools for COPD exacerbations. Among these tools, only two reported on model validation and none were deemed ready for personalised COPD management in clinic.6
In this study, we describe a new model, the Acute COPD Exacerbation Prediction Tool (ACCEPT), to predict, at an individual level, rate and severity of COPD exacerbation, report on its performance in an independent external cohort, and explain, using case studies, its potential clinical application. As a decision tool, ACCEPT provides a personalised risk profile that allows clinicians to tailor treatment regimens to individual needs of patients.
Section snippets
Participants and study design
In reporting our prediction model, we followed recommendations set by the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statement.7 We developed the model using data from patients with COPD, without previous or existing history of asthma, and who had at least one exacerbation over the past 12 months. We then externally validated the model in patients with COPD regardless of their exacerbation history and in a subset of patients with
Results
We excluded 96 patients who were lost to follow-up (n=33) or had missing values (n=63; figure 1). The final development dataset included 2380 patients (1107 from MACRO, 847 from STATCOPE, and 426 from OPTIMAL). Total mean age was 64·7 years (SD 8·8) and 1373 (58%) were men. Patients had a total of 3056 exacerbations, 628 of which were severe. In the external validation dataset, ECLIPSE, 109 patients had missing values. Thus, the final sample included 1819 patients with COPD (mean age was 63·3
Discussion
The most important finding of the study was the development and validation of ACCEPT that uses simple and widely available clinical and demographic variables to predict risk and severity of exacerbations over a 12-month period, enabling personalisation of care for patients with COPD. ACCEPT was superior to using an individual's history of exacerbation to predict future risk of exacerbations and, in particular, for severe exacerbations (we observed an increase in AUC of 0·11 in all patients with
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