Journal Article

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

Smith, Luke A., Mukherjee, Sutapa, Bird, Alix, Palmer, Lyle J., Rose, Anand, Zeng, Minyan

2026

Overview

Background 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. Methods 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. Results 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. Conclusions 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. Trial registration Retrospectively registered. Clinical trial number: Not Applicable.

• Publisher: BioMed Central,Nature Publishing Group,BMC
• Subject: Bronchodilators / Chronic obstructive / Chronic obstructive pulmonary disease / Clinical medicine / Datasets / Demographics / Demography / Dyspnea / Exacerbation / Females / Health insurance / Hemoglobin / Hospitalization / Laboratories / Logit models / Lung diseases / Males / Medicine / Medicine & Public Health / Missing data / Mortality / Patients / Pneumology/Respiratory System / Population / Prediction models / Prognosis / Public health / Pulmonary disease / Regression / Regression analysis / Regression models / Regularization / Risk / Smoking / Survival / Variables