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External validation of a COPD prediction model using population-based primary care data: a nested case-control study.

ABSTRACT: Emerging models for predicting risk of chronic obstructive pulmonary disease (COPD) require external validation in order to assess their clinical value. We validated a previous model for predicting new onset COPD in a different database. We randomly drew 38,597 case-control pairs (total N?=?77,194) of individuals aged ?35 years and matched for sex, age, and general practice from the United Kingdom Clinical Practice Research Datalink database. We assessed accuracy of the model to discriminate between COPD cases and non-cases by calculating area under the receiver operator characteristic (ROC_AUC) for the prediction scores. Analogous to the development model, ever smoking (OR 6.70; 95%CI 6.41-6.99), prior asthma (OR 6.43; 95%CI 5.85-7.07), and higher socioeconomic deprivation (OR 2.90; 95%CI 2.72-3.09 for highest vs. lowest quintile) increased the risk of COPD. The validated prediction scores ranged from 0-5.71 (ROC_AUC 0.66; 95%CI 0.65-0.66) for males and 0-5.95 (ROC_AUC 0.71; 95%CI 0.70-0.71) for females. We have confirmed that smoking, prior asthma, and socioeconomic deprivation are key risk factors for new onset COPD. Our model seems externally valid at identifying patients at risk of developing COPD. An impact assessment now needs to be undertaken to assess whether this prediction model can be applied in clinical care settings.

SUBMITTER: Nwaru BI

PROVIDER: S-EPMC5356333 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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External validation of a COPD prediction model using population-based primary care data: a nested case-control study.

Nwaru Bright I BI Simpson Colin R CR Sheikh Aziz A Kotz Daniel D

Scientific reports 20170317

Emerging models for predicting risk of chronic obstructive pulmonary disease (COPD) require external validation in order to assess their clinical value. We validated a previous model for predicting new onset COPD in a different database. We randomly drew 38,597 case-control pairs (total N = 77,194) of individuals aged ≥35 years and matched for sex, age, and general practice from the United Kingdom Clinical Practice Research Datalink database. We assessed accuracy of the model to discriminate bet ...[more]

PMID: 28304375

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Project description:ObjectiveTo validate all diagnostic prediction models for ruling out pulmonary embolism that are easily applicable in primary care.DesignSystematic review followed by independent external validation study to assess transportability of retrieved models to primary care medicine.Setting300 general practices in the Netherlands.ParticipantsIndividual patient dataset of 598 patients with suspected acute pulmonary embolism in primary care.Main outcome measuresDiscriminative ability of all models retrieved by systematic literature search, assessed by calculation and comparison of C statistics. After stratification into groups with high and low probability of pulmonary embolism according to pre-specified model cut-offs combined with qualitative D-dimer test, sensitivity, specificity, efficiency (overall proportion of patients with low probability of pulmonary embolism), and failure rate (proportion of pulmonary embolism cases in group of patients with low probability) were calculated for all models.ResultsTen published prediction models for the diagnosis of pulmonary embolism were found. Five of these models could be validated in the primary care dataset: the original Wells, modified Wells, simplified Wells, revised Geneva, and simplified revised Geneva models. Discriminative ability was comparable for all models (range of C statistic 0.75-0.80). Sensitivity ranged from 88% (simplified revised Geneva) to 96% (simplified Wells) and specificity from 48% (revised Geneva) to 53% (simplified revised Geneva). Efficiency of all models was between 43% and 48%. Differences were observed between failure rates, especially between the simplified Wells and the simplified revised Geneva models (failure rates 1.2% (95% confidence interval 0.2% to 3.3%) and 3.1% (1.4% to 5.9%), respectively; absolute difference -1.98% (-3.33% to -0.74%)). Irrespective of the diagnostic prediction model used, three patients were incorrectly classified as having low probability of pulmonary embolism; pulmonary embolism was diagnosed only after referral to secondary care.ConclusionsFive diagnostic pulmonary embolism prediction models that are easily applicable in primary care were validated in this setting. Whereas efficiency was comparable for all rules, the Wells rules gave the best performance in terms of lower failure rates.

Project description:BACKGROUND: Injuries in childhood are largely preventable yet an estimated 2,400 children die every day because of injury and violence. Despite this, the factors that contribute to injury occurrence have not been quantified at the population scale using primary care data. We used The Health Improvement Network (THIN) database to identify risk factors for thermal injury, fractures and poisoning in pre-school children in order to inform the optimal delivery of preventative strategies. METHODS: We used a matched, nested case-control study design. Cases were children under 5 with a first medically recorded injury, comprising 3,649 thermal injury cases, 4,050 fracture cases and 2,193 poisoning cases, matched on general practice to 94,620 control children. RESULTS: Younger maternal age and higher birth order increased the odds of all injuries. Children's age of highest injury risk varied by injury type; compared with children under 1 year, thermal injuries were highest in those age 1-2 (OR = 2.43, 95%CI 2.23-2.65), poisonings in those age 2-3 (OR = 7.32, 95%CI 6.26-8.58) and fractures in those age 3-5 (OR = N 3.80, 95%CI 3.42-4.23). Increasing deprivation was an important modifiable risk factor for poisonings and thermal injuries (tests for trend p ≤ 0.001) as were hazardous/harmful alcohol consumption by a household adult (OR = 1.73, 95%CI 1.26-2.38 and OR = 1.39, 95%CI 1.07-1.81 respectively) and maternal diagnosis of depression (OR = 1.45, 95%CI 1.24-1.70 and OR = 1.16, 95%CI 1.02-1.32 respectively). Fracture was not associated with these factors, however, not living in single-adult household reduced the odds of fracture (OR = 0.88, 95%CI 0.82-0.95). CONCLUSIONS: Maternal depression, hazardous/harmful adult alcohol consumption and socioeconomic deprivation represent important modifiable risk factors for thermal injury and poisoning but not fractures in preschool children. Since these risk factors can be ascertained from routine primary care records, pre-school children's frequent visits to primary care present an opportunity to reduce injury risk by implementing effective preventative interventions from existing national guidelines.

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Project description:Prediction of lifetime cardiovascular disease (CVD) risk is recommended in many clinical guidelines, but lifetime risk models are rarely externally validated. The aim of this study was to externally validate the QRiskLifetime incident CVD risk prediction tool. Independent external validation of QRiskLifetime using Clinical Practice Research Datalink data, examining discrimination and calibration in the whole population and stratified by age, and reclassification compared to QRISK3. Since lifetime CVD risk is unobservable, performance was evaluated at 10-years' follow-up, and lifetime performance inferred in terms of performance for in the different age-groups from which lifetime predictions are derived. One million, two hundreds sixty thousand and three hundreds twenty nine women and 1,223,265 men were included in the analysis. Discrimination was excellent in the whole population (Harrell's-C = 0.844 in women, 0.808 in men), but moderate to poor stratified by age-group (Harrell's C in people aged 30-44 0.714 for both men and women, in people aged 75-84 0.578 in women and 0.556 in men). Ten-year CVD risk was under-predicted in the whole population, and in all age-groups except women aged 45-64, with worse under-prediction in older age-groups. Compared to those at highest QRISK3 estimated 10-year risk, those with highest lifetime risk were younger (mean age: women 50.5 vs. 71.3 years; men 46.3 vs. 63.8 years) and had lower systolic blood pressure and prevalence of treated hypertension, but had more family history of premature CVD, and were more commonly minority ethnic. Over 10-years, the estimated number needed to treat (NNT) with a statin to prevent one CVD event in people with QRISK3 ≥ 10% was 34 in women and 37 in men, compared to 99 and 100 for those at highest lifetime risk. QRiskLifetime underpredicts 10-year CVD risk in nearly all age-groups, so is likely to also underpredict lifetime risk. Treatment based on lifetime risk has considerably lower medium-term benefit than treatment based on 10-year risk.

Dataset Information

External validation of a COPD prediction model using population-based primary care data: a nested case-control study.

Publications

External validation of a COPD prediction model using population-based primary care data: a nested case-control study.

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