Trial reportNPJ primary care respiratory medicine2014
Development and validation of a model to predict the 10-year risk of general practitioner-recorded COPD.
Trial report in NPJ primary care respiratory medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.
- Prediction models for the development of COPD: a systematic review.International journal of chronic obstructive pulmonary disease · 2018Pooled it
- Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2017Pooled it
- Trial
- Development and Validation of an Electronic Health Record Algorithm to Predict the Presence of Chronic Obstructive Pulmonary Disease.International journal of chronic obstructive pulmonary disease · 2026Article
- Photoreceptor metabolic window unveils eye-body interactions.Nature communications · 2025Article
- Current Progress of COPD Early Detection: Key Points and Novel Strategies.International journal of chronic obstructive pulmonary disease · 2023Review
- Nomograms Using CT Morphological Features and Clinical Characteristics to Identify COPD in Patients with Lung Cancer: A Multicenter Study.International journal of chronic obstructive pulmonary disease · 2023Article
- Machine Learning Prediction of Progression in Forced Expiratory Volume in 1 Second in the COPDGene® Study.Chronic obstructive pulmonary diseases (Miami, Fla.) · 2022Article
- Development and validation of the EHS-COPD model to predict sex-specific risk of chronic obstructive pulmonary disease (COPD) in older Chinese adults: Hong Kong's Elderly Health Service Cohort.Annals of translational medicine · 2022Article
- Development and validation of a nomogram to predict pulmonary function and the presence of chronic obstructive pulmonary disease in a Korean population.BMC pulmonary medicine · 2021Article
- Lung function in adults and future burden of obstructive lung diseases in a long-term follow-up.NPJ primary care respiratory medicine · 2020Article
- Personalized medicine for patients with COPD: where are we?International journal of chronic obstructive pulmonary disease · 2019Review
- External validation of a COPD prediction model using population-based primary care data: a nested case-control study.Scientific reports · 2017Article
- Development and validation of the Salzburg COPD-screening questionnaire (SCSQ): a questionnaire development and validation study.NPJ primary care respiratory medicine · 2017Article
- Article
- Projecting the COPD population and costs in England and Scotland: 2011 to 2030.Scientific reports · 2016Article
- A retrospective study of two populations to test a simple rule for spirometry.BMC family practice · 2016Article
- Review
- Risk Prediction for Adverse Pregnancy Outcomes in a Medicaid Population.Journal of women's health (2002) · 2015Article
- Predicting risk of COPD in primary care: development and validation of a clinical risk score.BMJ open respiratory research · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundThere is increasing interest in the earlier detection of, and intervention in, patients at highest risk of developing chronic obstructive pulmonary disease (COPD).
aimsThe objective of this research was to develop and validate a risk prediction model for general practitioner (GP)-recorded diagnosis of COPD.
methodsWe used data from 239 Scottish GP practices; two-thirds were randomly allocated to a derivation cohort and the other third to a validation cohort. We included patients aged 35-74 years at the cohort entry date, and excluded patients with a recorded diagnosis of COPD prior to the entry date and with missing data on smoking status.
resultsThere were 480,903 patients in the derivation cohort and 247,755 in the validation cohort. The incidence of COPD in the total cohort was 5.53/1,000 patient-years of follow-up (95% confidence interval (CI), 5.46-5.60). In the derivation cohort, the COPD risk for ever- versus never-smokers was substantially higher in women (hazard ratio (HR)=9.61, 95% CI, 8.92-10.34) than in men (HR=6.72, 95% CI, 6.19-7.30). Other risk factors for both sexes were level of deprivation and a previously recorded asthma diagnosis. In the validation cohort, the model discriminated well between patients who did and those who did not develop COPD: area under the receiver operating characteristics curve=0.845 (95% CI, 0.840-0.850) for females and 0.832 (95% CI, 0.827-0.837) for males.
conclusionsWe have developed and validated the first risk prediction model for COPD, which has the major advantage of being populated entirely by routinely collected data and consequently may be used for clinical practice.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.