Development of the ProPal-COPD tool to identify patients with COPD for proactive palliative care
Publication year
2017Source
International journal of COPD, 12, (2017), pp. 2121-2128ISSN
Publication type
Article / Letter to editor

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Organization
Anesthesiology
Dentistry
Health Evidence
Biochemistry (UMC)
Pulmonary Diseases
Journal title
International journal of COPD
Volume
vol. 12
Page start
p. 2121
Page end
p. 2128
Subject
Radboudumc 0: Other Research RIMLS: Radboud Institute for Molecular Life Sciences; Radboudumc 10: Reconstructive and regenerative medicine RIHS: Radboud Institute for Health Sciences; Radboudumc 18: Healthcare improvement science RIHS: Radboud Institute for Health Sciences; Radboudumc 5: Inflammatory diseases RIHS: Radboud Institute for Health SciencesAbstract
BACKGROUND: Our objective was to develop a tool to identify patients with COPD for proactive palliative care. Since palliative care needs increase during the disease course of COPD, the prediction of mortality within 1 year, measured during hospitalizations for acute exacerbation COPD (AECOPD), was used as a proxy for the need of proactive palliative care. PATIENTS AND METHODS: Patients were recruited from three general hospitals in the Netherlands in 2014. Data of 11 potential predictors, a priori selected based on literature, were collected during hospitalization for AECOPD. After 1 year, the medical files were explored for the date of death. An optimal prediction model was assessed by Lasso logistic regression, with 20-fold cross-validation for optimal shrinkage. Missing data were handled using complete case analysis. RESULTS: Of 174 patients, 155 patients were included; of those 30 (19.4%) died within 1 year. The optimal prediction model was internally validated and had good discriminating power (AUC =0.82, 95% CI 0.81-0.82). This model relied on the following seven predictors: the surprise question, Medical Research Council dyspnea questionnaire (MRC dyspnea), Clinical COPD Questionnaire (CCQ), FEV1% of predicted value, body mass index, previous hospitalizations for AECOPD and specific comorbidities. To ensure minimal miss out of patients in need of proactive palliative care, we proposed a cutoff in the model that prioritized sensitivity over specificity (0.90 over 0.73, respectively). Our model (ProPal-COPD tool) was a stronger predictor of mortality within 1 year than the CODEX (comorbidity, age, obstruction, dyspnea, and previous severe exacerbations) index. CONCLUSION: The ProPal-COPD tool is a promising multivariable prediction tool to identify patients with COPD for proactive palliative care.
This item appears in the following Collection(s)
- Academic publications [202802]
- Electronic publications [100870]
- Faculty of Medical Sciences [80020]
- Open Access publications [69592]
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