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Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients.

ABSTRACT: A key prerequisite for precision medicine is the estimation of disease progression from the current patient state. Disease correlations and temporal disease progression (trajectories) have mainly been analysed with focus on a small number of diseases or using large-scale approaches without time consideration, exceeding a few years. So far, no large-scale studies have focused on defining a comprehensive set of disease trajectories. Here we present a discovery-driven analysis of temporal disease progression patterns using data from an electronic health registry covering the whole population of Denmark. We use the entire spectrum of diseases and convert 14.9 years of registry data on 6.2 million patients into 1,171 significant trajectories. We group these into patterns centred on a small number of key diagnoses such as chronic obstructive pulmonary disease (COPD) and gout, which are central to disease progression and hence important to diagnose early to mitigate the risk of adverse outcomes. We suggest such trajectory analyses may be useful for predicting and preventing future diseases of individual patients.

SUBMITTER: Jensen AB

PROVIDER: S-EPMC4090719 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients.

Jensen Anders Boeck AB Moseley Pope L PL Oprea Tudor I TI Ellesøe Sabrina Gade SG Eriksson Robert R Schmock Henriette H Jensen Peter Bjødstrup PB Jensen Lars Juhl LJ Brunak Søren S

Nature communications 20140624

A key prerequisite for precision medicine is the estimation of disease progression from the current patient state. Disease correlations and temporal disease progression (trajectories) have mainly been analysed with focus on a small number of diseases or using large-scale approaches without time consideration, exceeding a few years. So far, no large-scale studies have focused on defining a comprehensive set of disease trajectories. Here we present a discovery-driven analysis of temporal disease p ...[more]

PMID: 24959948

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Project description:BackgroundThe Million Hearts Cardiovascular Disease Risk Reduction Model provides financial incentives for practices to lower 10-year atherosclerotic cardiovascular disease (ASCVD) risk for high-risk (ASCVD ≥30%) Medicare patients. To estimate average practice-level ASCVD risk reduction, we applied optimal trial outcomes to a real-world population with high ASCVD risk.MethodsThis study uses observational registry data from the National Cardiovascular Data Registry Practice Innovation and Clinical Excellence Registry from January 2013 to June 2016. We modeled ASCVD risk reductions using historical clinical trial data (reducing cholesterol by 26.5%, reducing systolic blood pressure by 10.9%, reducing smoking rates by 21.8%) the average reduction in ASCVD risk associated with individual and combined risk factor modifications, and then percentage of practices achieving the various incentive thresholds for the Million Hearts Model.ResultsThe final study population included 135 166 patients, with 16 248 (12.0%) with 10-year ASCVD risk of ≥30%, but without existing ASCVD. The mean 10-year ASCVD risk was 41.9% (±1 SD of 11.6). Using risk factor reductions from clinical trials, lowering cholesterol, blood pressure, and smoking rates reduced 10-year ASCVD risk by 3.3% (±3.1), 6.3% (±1.1) and 0.5% (±1.3), respectively. Combining all 3 reductions resulted in a 9.7% (±3.6) reduction, with 67 (27.0%) of practices achieving a patient-level average 10-year ASCVD risk reduction of ≥10%, 181 (73.0%) achieving a 2 to 10% reduction, and no practice achieving <2% reduction.ConclusionsIn cardiology practices, about 1 out of 8 patients have a 10-year ASCVD risk ≥30% and qualify as high risk in the Million Hearts Model. If practices target the three main modifiable risk factors and achieve reductions similar to clinical trial results, ASCVD risk could be substantially lowered and all practices could receive incentive payments. These findings support the potential benefit of the Million Hearts Model and provide guidance to participating practices.

Project description:BackgroundLarge-scale and contemporary population-based studies of heart failure incidence are needed to inform resource planning and research prioritisation but current evidence is scarce. We aimed to assess temporal trends in incidence and prevalence of heart failure in a large general population cohort from the UK, between 2002 and 2014.MethodsFor this population-based study, we used linked primary and secondary electronic health records of 4 million individuals from the Clinical Practice Research Datalink (CPRD), a cohort that is representative of the UK population in terms of age and sex. Eligible patients were aged 16 years and older, had contributed data between Jan 1, 2002, and Dec 31, 2014, had an acceptable record according to CPRD quality control, were approved for CPRD and Hospital Episodes Statistics linkage, and were registered with their general practice for at least 12 months. For patients with incident heart failure, we extracted the most recent measurement of baseline characteristics (within 2 years of diagnosis) from electronic health records, as well as information about comorbidities, socioeconomic status, ethnicity, and region. We calculated standardised rates by applying direct age and sex standardisation to the 2013 European Standard Population, and we inferred crude rates by applying year-specific, age-specific, and sex-specific incidence to UK census mid-year population estimates. We assumed no heart failure for patients aged 15 years or younger and report total incidence and prevalence for all ages (>0 years).FindingsFrom 2002 to 2014, heart failure incidence (standardised by age and sex) decreased, similarly for men and women, by 7% (from 358 to 332 per 100 000 person-years; adjusted incidence ratio 0·93, 95% CI 0·91-0·94). However, the estimated absolute number of individuals with newly diagnosed heart failure in the UK increased by 12% (from 170 727 in 2002 to 190 798 in 2014), largely due to an increase in population size and age. The estimated absolute number of prevalent heart failure cases in the UK increased even more, by 23% (from 750 127 to 920 616). Over the study period, patient age and multi-morbidity at first presentation of heart failure increased (mean age 76·5 years [SD 12·0] to 77·0 years [12·9], adjusted difference 0·79 years, 95% CI 0·37-1·20; mean number of comorbidities 3·4 [SD 1·9] vs 5·4 [2·5]; adjusted difference 2·0, 95% CI 1·9-2·1). Socioeconomically deprived individuals were more likely to develop heart failure than were affluent individuals (incidence rate ratio 1·61, 95% CI 1·58-1·64), and did so earlier in life than those from the most affluent group (adjusted difference -3·51 years, 95% CI -3·77 to -3·25). From 2002 to 2014, the socioeconomic gradient in age at first presentation with heart failure widened. Socioeconomically deprived individuals also had more comorbidities, despite their younger age.InterpretationDespite a moderate decline in standardised incidence of heart failure, the burden of heart failure in the UK is increasing, and is now similar to the four most common causes of cancer combined. The observed socioeconomic disparities in disease incidence and age at onset within the same nation point to a potentially preventable nature of heart failure that still needs to be tackled.FundingBritish Heart Foundation and National Institute for Health Research.

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Dataset Information

Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients.

Publications

Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients.

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