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      Examining the risk of depression or self-harm associated with incretin-based therapies used to manage hyperglycaemia in patients with type 2 diabetes: a cohort study using the UK Clinical Practice Research Datalink

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          Abstract

          Objectives

          To compare population-based incidence rates of new-onset depression or self-harm in patients initiating incretin-based therapies with that of sulfonylureas (SU) and other glucose-lowering agents.

          Design

          Population-based cohort study.

          Setting

          Patients attending primary care practices registered with the UK-based Clinical Practice Research Datalink (CPRD).

          Participants

          Using the UK-based CPRD, we identified two incretin-based therapies cohorts: (1) dipeptidyl peptidase-4 inhibitor (DPP-4i)-cohort, consisting of new users of DPP-4i and SU and (2) glucagon-like peptide-1 receptor agonists (GLP-1RA)-cohort, consisting of new users of GLP-1RA and SU, between January 2007 and January 2016. Patients with a prior history of depression, self-harm and other serious psychiatric conditions were excluded.

          Main outcome measures

          The primary study outcome comprised a composite of new-onset depression or self-harm. Unadjusted and adjusted Cox proportional hazards regression was used to quantify the association between incretin-based therapies and depression or self-harm. Deciles of High-Dimensional Propensity Scores and concurrent number of glucose-lowering agents were used to adjust for potential confounding.

          Results

          We identified new users of 6206 DPP-4i and 22 128 SU in the DPP-4i-cohort, and 501 GLP-1RA and 16 409 SU new users in the GLP-1RA-cohort. The incidence of depression or self-harm was 8.2 vs 11.7 events/1000 person-years in the DPP-4i-cohort and 18.2 vs 13.6 events/1000 person-years in the GLP-1RA-cohort for incretin-based therapies versus SU, respectively. Incretin-based therapies were not associated with an increased or decreased incidence of depression or self-harm compared with SU (DPP-4i-cohort: unadjusted HR 0.70, 95% CI 0.51 to 0.96; adjusted HR 0.80, 95% CI 0.57 to 1.13; GLP-1RA-cohort: unadjusted HR 1.36, 95% CI 0.72 to 2.58; adjusted HR 1.25, 95% CI 0.63 to 2.50). Consistent results were observed for other glucose-lowering comparators including insulin and thiazolidinediones.

          Conclusions

          Our findings suggest that the two incretin-based therapies are not associated with an increased or decreased risk of depression or self-harm.

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          Most cited references43

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          Data Resource Profile: Clinical Practice Research Datalink (CPRD)

          The Clinical Practice Research Datalink (CPRD) is an ongoing primary care database of anonymised medical records from general practitioners, with coverage of over 11.3 million patients from 674 practices in the UK. With 4.4 million active (alive, currently registered) patients meeting quality criteria, approximately 6.9% of the UK population are included and patients are broadly representative of the UK general population in terms of age, sex and ethnicity. General practitioners are the gatekeepers of primary care and specialist referrals in the UK. The CPRD primary care database is therefore a rich source of health data for research, including data on demographics, symptoms, tests, diagnoses, therapies, health-related behaviours and referrals to secondary care. For over half of patients, linkage with datasets from secondary care, disease-specific cohorts and mortality records enhance the range of data available for research. The CPRD is very widely used internationally for epidemiological research and has been used to produce over 1000 research studies, published in peer-reviewed journals across a broad range of health outcomes. However, researchers must be aware of the complexity of routinely collected electronic health records, including ways to manage variable completeness, misclassification and development of disease definitions for research.
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            Diabetes mellitus, fasting glucose, and risk of cause-specific death.

            The extent to which diabetes mellitus or hyperglycemia is related to risk of death from cancer or other nonvascular conditions is uncertain. We calculated hazard ratios for cause-specific death, according to baseline diabetes status or fasting glucose level, from individual-participant data on 123,205 deaths among 820,900 people in 97 prospective studies. After adjustment for age, sex, smoking status, and body-mass index, hazard ratios among persons with diabetes as compared with persons without diabetes were as follows: 1.80 (95% confidence interval [CI], 1.71 to 1.90) for death from any cause, 1.25 (95% CI, 1.19 to 1.31) for death from cancer, 2.32 (95% CI, 2.11 to 2.56) for death from vascular causes, and 1.73 (95% CI, 1.62 to 1.85) for death from other causes. Diabetes (vs. no diabetes) was moderately associated with death from cancers of the liver, pancreas, ovary, colorectum, lung, bladder, and breast. Aside from cancer and vascular disease, diabetes (vs. no diabetes) was also associated with death from renal disease, liver disease, pneumonia and other infectious diseases, mental disorders, nonhepatic digestive diseases, external causes, intentional self-harm, nervous-system disorders, and chronic obstructive pulmonary disease. Hazard ratios were appreciably reduced after further adjustment for glycemia measures, but not after adjustment for systolic blood pressure, lipid levels, inflammation or renal markers. Fasting glucose levels exceeding 100 mg per deciliter (5.6 mmol per liter), but not levels of 70 to 100 mg per deciliter (3.9 to 5.6 mmol per liter), were associated with death. A 50-year-old with diabetes died, on average, 6 years earlier than a counterpart without diabetes, with about 40% of the difference in survival attributable to excess nonvascular deaths. In addition to vascular disease, diabetes is associated with substantial premature death from several cancers, infectious diseases, external causes, intentional self-harm, and degenerative disorders, independent of several major risk factors. (Funded by the British Heart Foundation and others.).
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              High-dimensional propensity score adjustment in studies of treatment effects using health care claims data.

              Adjusting for large numbers of covariates ascertained from patients' health care claims data may improve control of confounding, as these variables may collectively be proxies for unobserved factors. Here, we develop and test an algorithm that empirically identifies candidate covariates, prioritizes covariates, and integrates them into a propensity-score-based confounder adjustment model. We developed a multistep algorithm to implement high-dimensional proxy adjustment in claims data. Steps include (1) identifying data dimensions, eg, diagnoses, procedures, and medications; (2) empirically identifying candidate covariates; (3) assessing recurrence of codes; (4) prioritizing covariates; (5) selecting covariates for adjustment; (6) estimating the exposure propensity score; and (7) estimating an outcome model. This algorithm was tested in Medicare claims data, including a study on the effect of Cox-2 inhibitors on reduced gastric toxicity compared with nonselective nonsteroidal anti-inflammatory drugs (NSAIDs). In a population of 49,653 new users of Cox-2 inhibitors or nonselective NSAIDs, a crude relative risk (RR) for upper GI toxicity (RR = 1.09 [95% confidence interval = 0.91-1.30]) was initially observed. Adjusting for 15 predefined covariates resulted in a possible gastroprotective effect (0.94 [0.78-1.12]). A gastroprotective effect became stronger when adjusting for an additional 500 algorithm-derived covariates (0.88 [0.73-1.06]). Results of a study on the effect of statin on reduced mortality were similar. Using the algorithm adjustment confirmed a null finding between influenza vaccination and hip fracture (1.02 [0.85-1.21]). In typical pharmacoepidemiologic studies, the proposed high-dimensional propensity score resulted in improved effect estimates compared with adjustment limited to predefined covariates, when benchmarked against results expected from randomized trials.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2018
                8 October 2018
                : 8
                : 10
                : e023830
                Affiliations
                [1 ] departmentSchool of Pharmacy, Faculty of Science , University of Waterloo , Waterloo, Ontario, Canada
                [2 ] departmentSchool of Pharmacy , Memorial University of Newfoundland , St. John’s, Newfoundland and Labrador, Canada
                [3 ] departmentFaculty of Medicine , Memorial University of Newfoundland , St. John’s, Newfoundland and Labrador, Canada
                [4 ] departmentDivision of General Internal Medicine, Department of Medicine , University of Alberta , Edmonton, Alberta, Canada
                Author notes
                [Correspondence to ] Dr John-Michael Gamble; jm.gamble@ 123456uwaterloo.ca
                Author information
                http://orcid.org/0000-0001-6891-8721
                Article
                bmjopen-2018-023830
                10.1136/bmjopen-2018-023830
                6194463
                30297350
                6e72cc76-0223-49da-b6bb-62073dd1b485
                © Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 22 June 2018
                : 27 August 2018
                : 31 August 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;
                Categories
                Diabetes and Endocrinology
                Research
                1506
                1843
                Custom metadata
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                Medicine
                cohort study,type 2 diabetes,dipeptidyl-peptidase 4 inhibitors,glucagon-like receptor 1 agonists,depression,suicide,self-harm

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