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Abstract
Objective Clinically applicable diabetes severity measures are lacking, with no previous studies comparing their predictive value with glycated hemoglobin (HbA1c). We developed and validated a type 2 diabetes severity score (the DIabetes Severity SCOre, DISSCO) and evaluated its association with risks of hospitalization and mortality, assessing its additional risk information to sociodemographic factors and HbA1c.
Research design and methods We used UK primary and secondary care data for 139 626 individuals with type 2 diabetes between 2007 and 2017, aged ≥35 years, and registered in general practices in England. The study cohort was randomly divided into a training cohort (n=111 748, 80%) to develop the severity tool and a validation cohort (n=27 878). We developed baseline and longitudinal severity scores using 34 diabetes-related domains. Cox regression models (adjusted for age, gender, ethnicity, deprivation, and HbA1c) were used for primary (all-cause mortality) and secondary (hospitalization due to any cause, diabetes, hypoglycemia, or cardiovascular disease or procedures) outcomes. Likelihood ratio (LR) tests were fitted to assess the significance of adding DISSCO to the sociodemographics and HbA1c models.
Results A total of 139 626 patients registered in 400 general practices, aged 63±12 years were included, 45% of whom were women, 83% were White, and 18% were from deprived areas. The mean baseline severity score was 1.3±2.0. Overall, 27 362 (20%) people died and 99 951 (72%) had ≥1 hospitalization. In the training cohort, a one-unit increase in baseline DISSCO was associated with higher hazard of mortality (HR: 1.14, 95% CI 1.13 to 1.15, area under the receiver operating characteristics curve (AUROC)=0.76) and cardiovascular hospitalization (HR: 1.45, 95% CI 1.43 to 1.46, AUROC=0.73). The LR tests showed that adding DISSCO to sociodemographic variables significantly improved the predictive value of survival models, outperforming the added value of HbA1c for all outcomes. Findings were consistent in the validation cohort.
Conclusions Higher levels of DISSCO are associated with higher risks for hospital admissions and mortality. The new severity score had higher predictive value than the proxy used in clinical practice, HbA1c. This reproducible algorithm can help practitioners stratify clinical care of patients with type 2 diabetes.
- type 2 diabetes
- electronic patient records
- algorithms
- hospitalization
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Footnotes
Presented at Some of the findings were presented at the National Institute for Health Research School for Primary Care Research (NIHR SPCR) Showcase, November 2018, London, UK; the Diabetes UK Conference, March 2018, London, UK; and the 55th Annual Meeting for the European Association for the Study of Diabetes (EASD), September 2019, Barcelona, Spain.
Contributors EK, MAM, and SSZ designed the study. SSZ extracted and analyzed the data and drafted the manuscript. EK and MAM critically revised the initial versions. DMA, CS, CDM, CAC-G, DR, HVM, NQ, SW, TH, IB, NP, SG, and MKR contributed to interpretation of data and revised the paper for important intellectual content. All authors agreed on the final version of the paper before submission. SSZ is the guarantor. The corresponding author attests that all listed authors meet the authorship criteria and that no others meeting the criteria have been omitted.
Funding This study is funded by the NIHR SPCR (grant number 331). This report is an independent research by the NIHR. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The lead author had full access to the data in the study and had final responsibility for the decision to submit for publication. DMA is funded by the NIHR Greater Manchester Patient Safety Translational Research Centre, the NIHR School for Primary Care Research, and the NIHR Manchester Biomedical Research Centre. CDM is funded by the NIHR Collaboration for Leadership in Applied Health Research and Care West Midlands, the NIHR School for Primary Care Research and the NIHR Research Professorship in General Practice (NIHR-RP-2014-04-026). CAC-G is part funded by NIHR Applied Research Collaboration (ARC) West Midlands. NP’s time was partially funded by the NIHR Manchester Biomedical Research Centre.
Competing interests DMA reports research grants from Abbvie, Almirall, Celgene, Eli Lilly, Novartis, UCB and the Leo Foundation. CS reports grants from NIHR SPCR, during the conduct of the study and is partially supported by NHS CLAHRC West. CDM is funded by a NIHR Research ship (NIHR-RP- 2014-04- 026), the NIHR Collaborations for Leadership in Applied Health Research and Care West Midlands and the NIHR School for Primary Care Research. NQ reports grants from the NIHR SPCR and NIHR HTA, during the conduct of the study. SW reports honorarium and independent scientific donation from Amgen and serves as a member of the Clinical Practice Research Datalink Independent Scientific Committee (ISAC) at the UK Medicines and Health Regulatory Agency. IB reports indirect competing interests as Chief Data Scientist Advisor to AstraZeneca via University of Liverpool; NIHR Senior Investigator grant. MKR has received educational grant support from MSD and Novo Nordisk; has modest stock ownership in GSK; and has consulted for Roche.Other co-authors declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.
Patient consent for publication Not required.
Ethics approval The study was approved by the Independent Scientific Advisory Committee (ISAC) for MHRA Database Research (protocol number: 17_168). Generic ethical approval for observational research using CPRD with approval from ISAC has been granted by Health Research Authority (HRA) Research Ethics Committee (East Midlands—Derby, REC reference number 05/MRE04/87).
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data may be obtained from a third party and are not publicly available. All data relevant to the study are included in the article or uploaded as supplementary information. Electronic health records are, by definition, considered sensitive data in the UK by the Data Protection Act and cannot be shared via public deposition because of information governance restriction in place to protect patient confidentiality. Access to data is available only once approval has been obtained through the individual constituent entities controlling access to the data. The primary care data can be requested via application to the Clinical Practice Research Datalink, secondary care data can be requested via application to the Hospital Episode Statistics from the UK Health and Social Care Information Centre, and mortality data are available by application to the UK Office for National Statistics.