Prognostic models for mortality and hospitalisation risk in a contemporary Australian chronic obstructive pulmonary disease cohort

TL;DR

This study developed and validated new models to predict hospitalization and mortality risks in Australian COPD patients, showing improved performance when incorporating haemoglobin-corrected DLCO.

Contribution

The study introduces locally developed models that outperform existing COPD prognostic models and demonstrates the added value of DLCOc in improving model accuracy.

Findings

Locally developed models predicted COPD-specific hospitalization and mortality with AUCs up to 0.90, outperforming DOSE and updated ADO models.

Incorporating haemoglobin-corrected DLCO significantly improved the performance of extended ADO and DOSE models.

Reduced DLCOc was strongly predictive of COPD outcomes and acted as a short-term survival risk.

Abstract

Chronic Obstructive Pulmonary Disease (COPD) poses significant public health and economic challenges and performant prognostic models may be useful to direct treatment. The purpose of this study was to develop predictive models, validate the DOSE and updated ADO predictive models, and identify predictors of future hospitalisation and mortality in contemporary Australian COPD patients.

Data from 8,578 inpatients and outpatients diagnosed with COPD (via post-bronchodilator spirometry) between 2006 and 2021 at a large South Australian tertiary public hospital were analysed. Multivariate logistic models and Cox regression, utilising penalised regularisation in multiply imputed data, were used to investigate predictors of hospitalisation due to COPD exacerbation at 1-, 3-, and 5-years post-diagnosis, and COPD-specific mortality at 3- and 5-years. Haemoglobin-corrected DLCO (DLCOc) was used to extend the DOSE and updated ADO models.

Locally developed models could predict COPD-specific 1-year hospitalisation risk with AUCs 0.80 (95% CI = [0.76, 0.83]) in males and 0.82 (95% CI = [0.78, 0.86]) in females on a temporally distinct hold-out set, with 3- and 5-year AUCs falling within this range. COPD-specific mortality was predicted with AUCs of 0.90 (95% CI = [0.85, 0.94]) and 0.89 (95% CI = [0.84, 0.92]) at 3 and 5 years in females, and 0.90 (95% CI = [0.86, 0.93]) and 0.88 (95% CI = [0.84, 0.92]) in males. Cox regression models predicted survival well in the test set for both females (C-index = 0.88, 95% CI = [0.85, 0.90]) and males (C-index = 0.86, 95% CI = [0.82, 0.88]). Local model performance was superior to that of the DOSE and updated ADO models for all outcomes, although not always significantly. Among the selected predictors, reduced DLCOc was strongly predictive of all outcomes. and acts as a short-term survival risk for follow-up durations less than 10 years. There was no significant difference in performance between sex, and there were differences in selected features and feature strength between sexes. Extending the extant clinical models with DLCOc significantly improved updated ADO and DOSE model fit and improved discriminatory performance, with the extended ADO index achieving AUC of 0.77 (95% CI = [0.75, 0.79]) and 0.87 (95% CI = [0.84, 0.89]) for predicting 5-year hospitalisation and mortality respectively across the full cohort. The extended DOSE index performed similarly with AUCs 0.77 (95% CI = [0.75, 0.79]) and 0.87 (95% CI = 0.83, 0.89)) for 5-year hospitalisation and mortality.

Ours is the only large clinical cohort and prognostic study of Australian COPD patients to date. Locally developed models achieved greater discriminative performance than the original updated ADO and DOSE models within our cohort. Extending the ADO and DOSE models with DLCOc significantly improved model fit in our cohort. We recommend further research into the use of DLCOc as a prognostic index for COPD, and its inclusion in future modelling attempts.

Retrospectively registered. Clinical trial number: Not Applicable.

The online version contains supplementary material available at 10.1186/s12931-026-03531-7.

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