Dataset Information

Dupuytren's Disease Predicts Increased All-Cause and Cancer-Specific Mortality: Analysis of a Large Cohort from the U.K. Clinical Practice Research Datalink.

ABSTRACT:

Background

Dupuytren's disease is a common, chronic, fibroproliferative disease of the palmar fascia. The cause is unclear but includes genetic predisposition alongside environmental factors. Several studies have suggested an association between Dupuytren's disease and excess mortality. The authors aimed to evaluate this association in adult patients in the United Kingdom and identify the causes of mortality.

Methods

The authors used a large primary care database (Clinical Practice Research Datalink) linked to the Office of National Statistics to identify patients with Dupuytren's disease between January 1, 1995, and December 31, 2013. Each patient was matched by age, sex, and general practitioner to five control patients without the disease. Cox regression models were used to study the association between Dupuytren's disease and all-cause and cause-specific mortality, adjusting for confounders.

Results

A total of 41,965 Dupuytren's disease patients and 209,825 control patients were identified. The all-cause mortality rate was increased in both unadjusted (hazard ratio, 1.48; 99% CI, 1.29 to 1.70; p < 0.0001) and multivariable adjusted (hazard ratio, 1.43; 99% CI, 1.25 to 1.65; p < 0.0001) models in patients with Dupuytren's disease, 12 years after diagnosis. Excess mortality was secondary to a wide range of causes, including cancer (hazard ratio, 1.66; 99% CI, 1.27 to 2.17; p < 0.0001), an effect that persisted after adjustment for confounders.

Conclusions

There is excess mortality associated with Dupuytren's disease that can be partially explained through environmental factors. From time of diagnosis in primary care, there is a 12-year window of opportunity for intervention to reduce the impact of these factors. The authors observed an increased risk of cancer mortality independent of confounders, and hypothesize a shared genetic risk between Dupuytren's disease and cancer.

Clinical question/level of evidence

Risk, II.

SUBMITTER: Kuo RYL

PROVIDER: S-EPMC7043723 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Publications

Dupuytren's Disease Predicts Increased All-Cause and Cancer-Specific Mortality: Analysis of a Large Cohort from the U.K. Clinical Practice Research Datalink.

Kuo Rachel Yi Ling RYL Ng Michael M Prieto-Alhambra Daniel D Furniss Dominic D

Plastic and reconstructive surgery 20200301 3

<h4>Background</h4>Dupuytren's disease is a common, chronic, fibroproliferative disease of the palmar fascia. The cause is unclear but includes genetic predisposition alongside environmental factors. Several studies have suggested an association between Dupuytren's disease and excess mortality. The authors aimed to evaluate this association in adult patients in the United Kingdom and identify the causes of mortality.<h4>Methods</h4>The authors used a large primary care database (Clinical Practic ...[more]

PMID: 32097318

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Project description:ObjectivesThe optimal method of identifying people with asthma from electronic health records in primary care is not known. The aim of this study is to determine the positive predictive value (PPV) of different algorithms using clinical codes and prescription data to identify people with asthma in the United Kingdom Clinical Practice Research Datalink (CPRD).Methods684 participants registered with a general practitioner (GP) practice contributing to CPRD between 1 December 2013 and 30 November 2015 were selected according to one of eight predefined potential asthma identification algorithms. A questionnaire was sent to the GPs to confirm asthma status and provide additional information to support an asthma diagnosis. Two study physicians independently reviewed and adjudicated the questionnaires and additional information to form a gold standard for asthma diagnosis. The PPV was calculated for each algorithm.Results684 questionnaires were sent, of which 494 (72%) were returned and 475 (69%) were complete and analysed. All five algorithms including a specific Read code indicating asthma or non-specific Read code accompanied by additional conditions performed well. The PPV for asthma diagnosis using only a specific asthma code was 86.4% (95% CI 77.4% to 95.4%). Extra information on asthma medication prescription (PPV 83.3%), evidence of reversibility testing (PPV 86.0%) or a combination of all three selection criteria (PPV 86.4%) did not result in a higher PPV. The algorithm using non-specific asthma codes, information on reversibility testing and respiratory medication use scored highest (PPV 90.7%, 95% CI (82.8% to 98.7%), but had a much lower identifiable population. Algorithms based on asthma symptom codes had low PPVs (43.1% to 57.8%)%).ConclusionsPeople with asthma can be accurately identified from UK primary care records using specific Read codes. The inclusion of spirometry or asthma medications in the algorithm did not clearly improve accuracy.Ethics and disseminationThe protocol for this research was approved by the Independent Scientific Advisory Committee (ISAC) for MHRA Database Research (protocol number15_257) and the approved protocol was made available to the journal and reviewers during peer review. Generic ethical approval for observational research using the CPRD with approval from ISAC has been granted by a Health Research Authority Research Ethics Committee (East Midlands-Derby, REC reference number 05/MRE04/87).The results will be submitted for publication and will be disseminated through research conferences and peer-reviewed journals.

Project description:BackgroundExcess mortality captures the total effect of the Coronavirus Disease 2019 (COVID-19) pandemic on mortality and is not affected by misspecification of cause of death. We aimed to describe how health and demographic factors were associated with excess mortality during, compared to before, the pandemic.Methods and findingsWe analysed a time series dataset including 9,635,613 adults (≥40 years old) registered at United Kingdom general practices contributing to the Clinical Practice Research Datalink. We extracted weekly numbers of deaths and numbers at risk between March 2015 and July 2020, stratified by individual-level factors. Excess mortality during Wave 1 of the UK pandemic (5 March to 27 May 2020) compared to the prepandemic period was estimated using seasonally adjusted negative binomial regression models. Relative rates (RRs) of death for a range of factors were estimated before and during Wave 1 by including interaction terms. We found that all-cause mortality increased by 43% (95% CI 40% to 47%) during Wave 1 compared with prepandemic. Changes to the RR of death associated with most sociodemographic and clinical characteristics were small during Wave 1 compared with prepandemic. However, the mortality RR associated with dementia markedly increased (RR for dementia versus no dementia prepandemic: 3.5, 95% CI 3.4 to 3.5; RR during Wave 1: 5.1, 4.9 to 5.3); a similar pattern was seen for learning disabilities (RR prepandemic: 3.6, 3.4 to 3.5; during Wave 1: 4.8, 4.4 to 5.3), for black or South Asian ethnicity compared to white, and for London compared to other regions. Relative risks for morbidities were stable in multiple sensitivity analyses. However, a limitation of the study is that we cannot assume that the risks observed during Wave 1 would apply to other waves due to changes in population behaviour, virus transmission, and risk perception.ConclusionsThe first wave of the UK COVID-19 pandemic appeared to amplify baseline mortality risk to approximately the same relative degree for most population subgroups. However, disproportionate increases in mortality were seen for those with dementia, learning disabilities, non-white ethnicity, or living in London.

Dataset Information

Dupuytren's Disease Predicts Increased All-Cause and Cancer-Specific Mortality: Analysis of a Large Cohort from the U.K. Clinical Practice Research Datalink.

Background

Methods

Results

Conclusions

Clinical question/level of evidence

Publications

Dupuytren's Disease Predicts Increased All-Cause and Cancer-Specific Mortality: Analysis of a Large Cohort from the U.K. Clinical Practice Research Datalink.

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