Effect of combination treatment with glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors on incidence of cardiovascular and serious renal events: population based cohort study.

OBJECTIVE: To determine whether the combined use of glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 (SGLT-2) inhibitors is associated with a decreased risk of major adverse cardiovascular events and serious renal events compared with either drug class alone among patients with type 2 diabetes, and to assess the effect of the combination on the individual components of major adverse cardiovascular events, heart failure, and all cause mortality. DESIGN: Population based cohort study using a prevalent new-user design, emulating a trial. SETTING: UK Clinical Practice Research Datalink linked to Hospital Episode Statistics Admitted Patient Care and Office for National Statistics databases. PARTICIPANTS: Two prevalent new-user cohorts were assembled between January 2013 and December 2020, with follow-up until the end of March 2021. The first cohort included 6696 patients who started GLP-1 receptor agonists and added on SGLT-2 inhibitors, and the second included 8942 patients who started SGLT-2 inhibitors and added on GLP-1 receptor agonists. Combination users were matched, in a 1:1 ratio, to patients prescribed the same background drug, duration of background drug, and time conditional propensity score. MAIN OUTCOME MEASURES: Cox proportional hazards models were fitted to estimate the hazard ratios and 95% confidence intervals of major adverse cardiovascular events and serious renal events, separately, comparing the GLP-1 receptor agonist-SGLT-2 inhibitor combination with the background drug, either GLP-1 receptor agonists or SGLT-2 inhibitors, depending on the cohort. Secondary outcomes included associations with the individual components of major adverse cardiovascular events (myocardial infarction, ischaemic stroke, cardiovascular mortality), heart failure, and all cause mortality. RESULTS: Compared with GLP-1 receptor agonists, the SGLT-2 inhibitor-GLP-1 receptor agonist combination was associated with a 30% lower risk of major adverse cardiovascular events (7.0 v 10.3 events per 1000 person years; hazard ratio 0.70, 95% confidence interval 0.49 to 0.99) and a 57% lower risk of serious renal events (2.0 v 4.6 events per 1000 person years; hazard ratio 0.43, 0.23 to 0.80). Compared with SGLT-2 inhibitors, the GLP-1 receptor agonist-SGLT-2 inhibitor combination was associated with a 29% lower risk of major adverse cardiovascular events (7.6 v 10.7 events per 1000 person years; hazard ratio 0.71, 0.52 to 0.98), whereas serious renal events generated a wide confidence interval (1.4 v 2.0 events per 1000 person years; hazard ratio 0.67, 0.32 to 1.41). Secondary outcomes generated similar results but with wider confidence intervals. CONCLUSIONS: In this cohort study, the GLP-1 receptor agonist-SGLT-2 inhibitor combination was associated with a lower risk of major adverse cardiovascular events and serious renal events compared with either drug class alone.

Glucagon like peptide-1 receptor agonists and the risk of skin cancer among patients with type 2 diabetes: Population-based cohort study.

AIMS: The objective of this study was to determine whether the use of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) is associated with an increased risk of melanoma and nonmelanoma skin cancer, separately, compared with the use of sulfonylureas among patients with type 2 diabetes. METHODS: Using the United Kingdom Clinical Practice Research Datalink (2007-2019), we assembled two new-user active comparator cohorts. In the first cohort assessing melanoma as the outcome, 11,786 new users of GLP-1 RAs were compared with 208,519 new users of sulfonylureas. In the second cohort assessing nonmelanoma skin cancer as the outcome, 11,774 new users of GLP-1 RAs were compared with 207,788 new users of sulfonylureas. Cox proportional hazards models weighted using propensity score fine stratification were fit to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of melanoma and nonmelanoma skin cancer, respectively. RESULTS: Compared with sulfonylureas, GLP-1 RAs were not associated with an increased risk of either melanoma (42.6 vs. 43.9 per 100,000 person-years, respectively; HR 0.96, 95% CI 0.53-1.75) or nonmelanoma skin cancer (243.9 vs. 229.9 per 100,000 person-years, respectively; HR 1.03, 95% CI 0.80-1.33). There was no evidence of an association between cumulative duration of use with either melanoma or nonmelanoma skin cancer. Consistent results were observed in secondary and sensitivity analyses. CONCLUSIONS: In this population-based cohort study, GLP-1 RAs were not associated with an increased risk of melanoma or nonmelanoma skin cancer, compared with sulfonylureas.

Dipeptidyl peptidase-4 inhibitors and the risk of skin cancer among patients with type 2 diabetes: a UK population-based cohort study.

INTRODUCTION: The dipeptidyl peptidase-4 (DPP-4) enzyme significantly influences carcinogenic pathways in the skin. The objective of this study was to determine whether DPP-4 inhibitors are associated with the incidence of melanoma and nonmelanoma skin cancer, compared with sulfonylureas. RESEARCH DESIGN AND METHODS: Using the United Kingdom Clinical Practice Research Datalink, we assembled two new-user active comparator cohorts for each skin cancer outcome from 2007 to 2019. For melanoma, the cohort included 96 739 DPP-4 inhibitor users and 209 341 sulfonylurea users, and 96 411 DPP-4 inhibitor users and 208 626 sulfonylurea users for non-melanoma skin cancer. Propensity score fine stratification weighted Cox proportional hazards models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs of melanoma and non-melanoma skin cancer, separately. RESULTS: Overall, DPP-4 inhibitors were associated with a 23% decreased risk of melanoma compared with sulfonylureas (49.7 vs 65.3 per 100 000 person-years, respectively; HR 0.77, 95% CI 0.61 to 0.96). The HR progressively reduced with increasing cumulative duration of use (0-2 years HR 1.14, 95% CI 0.84 to 1.54; 2.1-5 years HR 0.44, 95% CI 0.29 to 0.66; >5 years HR 0.33, 95% CI 0.14 to 0.74). In contrast, these drugs were not associated with the incidence of non-melanoma skin cancer, compared with sulfonylureas (448.1 vs 426.1 per 100 000 person-years, respectively; HR 1.06, 95% CI 0.98 to 1.15). CONCLUSIONS: In this large, population-based cohort study, DPP-4 inhibitors were associated with a reduced risk of melanoma but not non-melanoma skin cancer, compared with sulfonylureas.

Associations Between Natural Language Processing-Enriched Social Determinants of Health and Suicide Death Among US Veterans.

Importance: Social determinants of health (SDOHs) are known to be associated with increased risk of suicidal behaviors, but few studies use SDOHs from unstructured electronic health record notes. Objective: To investigate associations between veterans' death by suicide and recent SDOHs, identified using structured and unstructured data. Design, Setting, and Participants: This nested case-control study included veterans who received care under the US Veterans Health Administration from October 1, 2010, to September 30, 2015. A natural language processing (NLP) system was developed to extract SDOHs from unstructured clinical notes. Structured data yielded 6 SDOHs (ie, social or familial problems, employment or financial problems, housing instability, legal problems, violence, and nonspecific psychosocial needs), NLP on unstructured data yielded 8 SDOHs (social isolation, job or financial insecurity, housing instability, legal problems, barriers to care, violence, transition of care, and food insecurity), and combining them yielded 9 SDOHs. Data were analyzed in May 2022. Exposures: Occurrence of SDOHs over a maximum span of 2 years compared with no occurrence of SDOH. Main Outcomes and Measures: Cases of suicide death were matched with 4 controls on birth year, cohort entry date, sex, and duration of follow-up. Suicide was ascertained by National Death Index, and patients were followed up for up to 2 years after cohort entry with a study end date of September 30, 2015. Adjusted odds ratios (aORs) and 95% CIs were estimated using conditional logistic regression. Results: Of 6 122 785 veterans, 8821 committed suicide during 23 725 382 person-years of follow-up (incidence rate 37.18 per 100 000 person-years). These 8821 veterans were matched with 35 284 control participants. The cohort was mostly male (42 540 [96.45%]) and White (34 930 [79.20%]), with 6227 (14.12%) Black veterans. The mean (SD) age was 58.64 (17.41) years. Across the 5 common SDOHs, NLP-extracted SDOH, on average, retained 49.92% of structured SDOHs and covered 80.03% of all SDOH occurrences. SDOHs, obtained by structured data and/or NLP, were significantly associated with increased risk of suicide. The 3 SDOHs with the largest effect sizes were legal problems (aOR, 2.66; 95% CI, 2.46-2.89), violence (aOR, 2.12; 95% CI, 1.98-2.27), and nonspecific psychosocial needs (aOR, 2.07; 95% CI, 1.92-2.23), when obtained by combining structured data and NLP. Conclusions and Relevance: In this study, NLP-extracted SDOHs, with and without structured SDOHs, were associated with increased risk of suicide among veterans, suggesting the potential utility of NLP in public health studies.

Proton pump inhibitors and the risk of inflammatory bowel disease: population-based cohort study.

OBJECTIVE: To determine whether the use of proton pump inhibitors (PPIs) compared with the use of histamine-2 receptor antagonists (H2RAs) is associated with an increased risk of inflammatory bowel disease (IBD). DESIGN: Population-based cohort study designed to address the impact of protopathic bias. SETTING: General practices contributing data to the UK Clinical Practice Research Datalink GOLD. PARTICIPANTS: 1 498 416 initiators of PPIs and 322 474 initiators of H2RAs from 1 January 1990 to 31 December 2018, with follow-up until 31 December 2019. Patients were analysed according to the timing of the IBD diagnosis after treatment initiation (early vs late). MAIN OUTCOME MEASURES: Standardised morbidity ratio weighted Cox proportional hazards models were used to estimate marginal HRs and 95% CIs. In the early-event analysis, IBD diagnoses were assessed within the first 2 years of treatment initiation, an analysis subject to potential protopathic bias. In the late-event analysis, all exposures were lagged by 2 years to account for latency and minimise protopathic bias. RESULTS: In the early-event analysis, the use of PPIs was associated with an increased risk of IBD within the first 2 years of treatment initiation, compared with H2RAs (HR 1.39, 95% CI 1.14 to 1.69). In contrast, the use of PPIs was not associated with an increased risk of IBD in the late-event analysis (HR 1.05, 95% CI 0.90 to 1.22). The results remained consistent in several sensitivity analyses. CONCLUSIONS: Compared with H2RAs, PPIs were not associated with an increased risk of IBD, after accounting for protopathic bias.

Novel antihyperglycaemic drugs and prevention of chronic obstructive pulmonary disease exacerbations among patients with type 2 diabetes: population based cohort study.

OBJECTIVE: To determine whether the use of glucagon-like peptide 1 (GLP-1) receptor agonists, dipeptidyl peptidase 4 (DPP-4) inhibitors, and sodium-glucose co-transporter-2 (SGLT-2) inhibitors, separately, is associated with a decreased risk of exacerbations of chronic obstructive pulmonary disease among patients with chronic obstructive pulmonary disease and type 2 diabetes. DESIGN: Population based cohort study using an active comparator, new user design. SETTING: The United Kingdom Clinical Practice Research Datalink linked with the Hospital Episode Statistics Admitted Patient Care and Office for National Statistics databases. PARTICIPANTS: Three active comparator, new user cohorts of patients starting the study drugs (GLP-1 receptor agonists, DPP-4 inhibitors, or SGLT-2 inhibitors) or sulfonylureas with a history of chronic obstructive pulmonary disease. The first cohort included 1252 patients starting GLP-1 receptor agonists and 14 259 starting sulfonylureas, the second cohort included 8731 patients starting DPP-4 inhibitors and 18 204 starting sulfonylureas, and the third cohort included 2956 patients starting SGLT-2 inhibitors and 10 841 starting sulfonylureas. MAIN OUTCOME MEASURES: Cox proportional hazards models with propensity score fine stratification weighting were fitted to estimate hazard ratios and 95% confidence intervals of severe exacerbation of chronic obstructive pulmonary disease (defined as hospital admission for chronic obstructive pulmonary disease), separately for GLP-1 receptor agonists, DPP-4 inhibitors, and SGLT-2 inhibitors. Whether these drugs were associated with a decreased risk of moderate exacerbation (defined as a co-prescription of an oral corticosteroid and an antibiotic along with an outpatient diagnosis of acute chronic obstructive pulmonary disease exacerbation on the same day) was also assessed. RESULTS: Compared with sulfonylureas, GLP-1 receptor agonists were associated with a 30% decreased risk of severe exacerbation (3.5 v 5.0 events per 100 person years; hazard ratio 0.70, 95% confidence interval 0.49 to 0.99) and moderate exacerbation (0.63, 0.43 to 0.94). DPP-4 inhibitors were associated with a modestly decreased incidence of severe exacerbation (4.6 v. 5.1 events per 100 person years; hazard ratio 0.91, 0.82 to 1.02) and moderate exacerbation (0.93, 0.82 to 1.07), with confidence intervals including the null value. Finally, SGLT-2 inhibitors were associated with a 38% decreased risk of severe exacerbation (2.4 v 3.9 events per 100 person years; hazard ratio 0.62, 0.48 to 0.81) but not moderate exacerbation (1.02, 0.83 to 1.27). CONCLUSIONS: In this population based study, GLP-1 receptor agonists and SGLT-2 inhibitors were associated with a reduced risk of severe exacerbations compared with sulfonylureas in patients with chronic obstructive pulmonary disease and type 2 diabetes. DPP-4 inhibitors were not clearly associated with a decreased risk of chronic obstructive pulmonary disease exacerbations.

Incretin-Based Drugs and the Risk of Acute Liver Injury Among Patients With Type 2 Diabetes.

OBJECTIVE: To determine whether the use of dipeptidyl peptidase 4 (DPP-4) inhibitors and glucagon-like peptide 1 receptor agonists (GLP-1 RAs), separately, is associated with an increased risk of acute liver injury compared with the use of sodium-glucose cotransporter 2 (SGLT-2) inhibitors. RESEARCH DESIGN AND METHODS: We used the U.K. Clinical Practice Research Datalink linked with the Hospital Episode Statistics Admitted Patient Care and the Office for National Statistics databases to assemble two new-user, active-comparator cohorts. The first included 106,310 initiators of DPP-4 inhibitors and 27,277 initiators of SGLT-2 inhibitors, while the second included 9,470 initiators of GLP-1 RAs and 26,936 initiators of SGLT-2 inhibitors. Cox proportional hazards models with propensity score fine stratification weighting were used to estimate hazard ratios (HRs) and 95% CIs of acute liver injury. RESULTS: Compared with SGLT-2 inhibitors, DPP-4 inhibitors were associated with a 53% increased risk of acute liver injury (HR 1.53, 95% CI 1.02-2.30). In contrast, GLP-1 RAs were not associated with an overall increased risk of acute liver injury (HR 1.11, 95% CI 0.57-2.16). However, an increased risk was observed among female users of both DPP-4 inhibitors (HR 3.22, 95% CI 1.67-6.21) and GLP-1 RAs (HR 3.23, 95% CI 1.44-7.25). CONCLUSIONS: In this population-based study, DPP-4 inhibitors were associated with an increased risk of acute liver injury compared with SGLT-2 inhibitors in patients with type 2 diabetes. In contrast, an increased risk of acute liver injury was observed only among female GLP-1 RA users.

India's ban on antimicrobial fixed-dose combinations: winning the battle, losing the war?

BACKGROUND AND OBJECTIVES: India, the country with the largest market availability of antimicrobial fixed-dose combinations (FDCs), banned certain antimicrobial FDCs in September 2018. Our objective was to examine the impact of Government ban on the sales of antimicrobial FDCs. METHODS: The sales patterns of 14 of the 26 banned antimicrobial FDCs were analyzed using monthly private sector drug sales data from IQVIA (a comprehensive and nationally representative drug sales database) between January 2018 and December 2019. We carried out descriptive analyses to evaluate the trend in sales over time for banned and non-banned antimicrobial FDCs using cumulative sales volumes. RESULTS: Overall, the cumulative sales volume of banned antimicrobial FDCs declined by 75% between January and September 2018 and the same months of 2019, although some banned FDCs continued to be available in significant volumes. The effectiveness of the ban was offset by several pathways. First, the sales of combinations containing moieties belonging to the same drug-classes as the antimicrobials in the banned FDCs increased after the ban. Second, while certain formulations of particular combinations were banned, the sales of other non-banned formulation of these combinations increased. Third, in some cases, products containing new non-antimicrobial components added to the banned combinations remained available. INTERPRETATION AND CONCLUSIONS: While sales of the banned antimicrobial FDCs decreased in 2019, we identified several mechanisms that counterbalanced the ban, including implementation failure, rising sales of congeners, and products with additional non-antimicrobial components.

Glucagon-Like Peptide 1 Receptor Agonists and Sodium-Glucose Cotransporter 2 Inhibitors and Risk of Nonalcoholic Fatty Liver Disease Among Patients With Type 2 Diabetes.

OBJECTIVE: To determine whether glucagon-like peptide 1 receptor agonists (GLP-1 RA) and sodium-glucose cotransporter 2 (SGLT-2) inhibitors, separately, are associated with a decreased risk of nonalcoholic fatty liver disease (NAFLD) compared with dipeptidyl peptidase 4 (DPP-4) inhibitors among patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: We assembled two new-user, active comparator cohorts using the U.K. Clinical Practice Research Datalink. The first included 30,291 and 225,320 new users of GLP-1 RA and DPP-4 inhibitors, respectively. The second included 41,184 and 148,421 new users of SGLT-2 inhibitors and DPP-4 inhibitors, respectively. Cox proportional hazards models weighted using propensity score fine stratification were fit to estimate hazard ratios (HRs) with 95% CIs of NAFLD. We also determined whether the study drugs were associated with a decreased risk of hepatic transaminase elevation within restricted subcohorts. RESULTS: GLP-1 RA were associated with a lower incidence of NAFLD with a wide CI compared with DPP-4 inhibitors (3.9 vs. 4.6 per 1,000 person-years, respectively; HR 0.86, 95% CI 0.73-1.01). SGLT-2 inhibitors were associated with a decreased risk of NAFLD (5.4 vs. 7.0 per 1,000 person-years, respectively; HR 0.78, 95% CI 0.68-0.89). In the restricted subcohorts, both GLP-1 RA and SGLT-2 inhibitors were associated with a decreased risk of hepatic transaminase elevation (HR 0.89, 95% CI 0.83-0.95, and HR 0.66, 95% CI 0.61-0.71). CONCLUSIONS: SGLT-2 inhibitors, and possibly GLP-1 RA, may be associated with a decreased incidence of NAFLD and hepatic transaminase elevation among patients with type 2 diabetes.

Glucagon-Like Peptide 1 Receptor Agonists and Risk of Anaphylactic Reaction Among Patients With Type 2 Diabetes: A Multisite Population-Based Cohort Study.

Case reports and a pharmacovigilance analysis have linked glucagon-like peptide 1 receptor agonists (GLP-1 RAs) with anaphylactic reactions, but real-world evidence for this possible association is lacking. Using databases from the United Kingdom (Clinical Practice Research Datalink) and the United States (Medicare, Optum (Optum, Inc., Eden Prairie, Minnesota), and IBM MarketScan (IBM, Armonk, New York)), we employed a new-user, active comparator study design wherein initiators of GLP-1 RAs were compared with 2 different active comparator groups (initiators of dipeptidyl peptidase 4 (DPP-4) inhibitors and initiators of sodium-glucose cotransporter 2 (SGLT-2) inhibitors) between 2007 and 2019. Propensity score fine stratification weighted Cox proportional hazards models were fitted to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for an anaphylactic reaction. Database-specific HRs were pooled using random-effects models. Compared with the use of DPP-4 inhibitors (n = 1,641,520), use of GLP-1 RAs (n = 324,098) generated a modest increase in the HR for anaphylactic reaction, with a wide 95% CI (36.9 per 100,000 person-years vs. 32.1 per 100,000 person-years, respectively; HR = 1.15, 95% CI: 0.94, 1.42). Compared with SGLT-2 inhibitors (n = 366,067), GLP-1 RAs (n = 259,929) were associated with a 38% increased risk of anaphylactic reaction (40.7 per 100,000 person-years vs. 29.4 per 100,000 person-years, respectively; HR = 1.38, 95% CI: 1.02, 1.87). In this large, multisite population-based cohort study, GLP-1 RAs were associated with a modestly increased risk of anaphylactic reaction when compared with DPP-4 inhibitors and SGLT-2 inhibitors.

Long-Term patterns of cancer incidence among patients with and without type 2 diabetes in the United Kingdom.

AIMS: Studies using contemporary cohorts are needed to assess the association between type 2 diabetes and cancer. METHODS: Using the United Kingdom Clinical Practice Research Datalink, we matched patients with type 2 diabetes between 1988 and 2019 to patients without type 2 diabetes. Poisson regression models were fit to estimate incidence rate ratios (IRRs) with 95% confidence intervals (CIs) for cancer. In secondary analyses, we determined whether the strength of the association varied with calendar time and whether patients with type 2 diabetes had a higher incidence of being diagnosed with multiple cancers during the follow-up period. RESULTS: 890,214 patients with type 2 diabetes were matched to an equal number of patients without type 2 diabetes. Patients with type 2 diabetes had a higher cancer incidence than patients without type 2 diabetes (IRR 1.19, 95% CI 1.18-1.21). The IRR was higher 2010 onwards (IRR: 1.25, 95% CI: 1.23-1.28) compared with the association in previous years. Overall, patients with type 2 diabetes had a 5% higher incidence of being diagnosed with multiple cancers (IRR: 1.05, 95% CI: 1.04-1.07). CONCLUSIONS: The results of this large population-based study indicate that type 2 diabetes is associated with an increased risk of several cancers.

Defining Clinically Relevant Target Populations Using Real-World Data to Guide the Design of Representative Antidiabetic Drug Trials.

The US Food and Drug Administration is considering replacing cardiovascular outcome trials of antidiabetic drugs with trials that better represent patients with type 2 diabetes. However, designing such representative trials requires understanding the underlying target populations (i.e., populations intended to receive the drug in the real-world setting). Thus, we used the Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results (LEADER) trial as a motivating example to illustrate how different target populations impact trial representativeness. Using the United Kingdom Clinical Practice Research Datalink, we identified three target populations: (i) all patients with type 2 diabetes; (ii) patients prescribed liraglutide; and (iii) patients who would have been eligible to receive liraglutide based on treatment stage (i.e., patients with poorly controlled diabetes eligible to receive a second-to-fifth line antidiabetic drug). We then examined the representativeness of the LEADER trial by applying its eligibility criteria to each target population. The target populations of patients with type 2 diabetes (n = 279,763), those prescribed liraglutide (n = 14,421), and those eligible to receive liraglutide based on the treatment stage (n = 85,610) differed substantially in terms of hemoglobin A1c, body mass index, prevalence of heart failure, and chronic kidney disease. Applying the LEADER trial eligibility criteria to these target populations resulted in the inclusion of 19.1%, 20.7%, and 34.8% patients, respectively. This study highlights how real-world data can be used to define different target populations. Explicitly defining these target populations can help in the design of future trials of antidiabetic drugs.

Use of Real-World Data to Emulate a Clinical Trial and Support Regulatory Decision Making: Assessing the Impact of Temporality, Comparator Choice, and Method of Adjustment.

External controls have been primarily used in the setting of single-arm trials of rare diseases; their use in common diseases has not been readily investigated, nor is there guidance on how to best select comparators. Thus, the objective of this study was to emulate a large cardiovascular outcome trial of type 2 diabetes to compare associations of effectiveness with different comparator groups to those reported in the trial. Using the Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results (LEADER) trial, we investigated six comparator groups using three calendar time periods (Early: 1999-2003; Later: 2004-2008, and Contemporaneous: 2009-2013) and two comparators (sulfonylureas and other second-to-third-line antidiabetic drugs). Hazard ratios (HRs) of the three-point composite cardiovascular outcome were estimated using four variations of the propensity score (adjustment, stratification, fine stratification, and matching) and compared with the LEADER trial (HR, 0.87; 95% confidence interval, 0.78-0.97). When comparing users of liraglutide with users of sulfonylureas, the HRs ranged from 0.57 to 1.03, with estimates in the early period most closely reflecting the LEADER trial (HR, 0.57-0.88). In contrast, the HRs ranged from 0.73 to 0.97 when comparing liraglutide users with users of any second-to-third-line antidiabetic drugs, although the later period generated estimates closest to the LEADER trial (HR, 0.77-0.84). Different methods of adjustment led to generally consistent HRs, aside from the fine stratification in the early period. This study highlights the complex interplay between comparator, temporality, and method of adjustment when selecting comparators using real-word data. These design choices must be considered in the design of trial emulation studies.

The Use of Long-Acting Insulin Analogs and the Risk of Colorectal Cancer Among Patients with Type 2 Diabetes: A Population-Based Cohort Study.

INTRODUCTION: The association between long-acting insulin analogs and colorectal cancer is uncertain, with previous studies reporting discrepant findings. OBJECTIVE: To determine whether the use of long-acting insulin analogs is associated with an increased risk of colorectal cancer, when compared with use of intermediate-acting human insulins among patients with type 2 diabetes. METHODS: We conducted a population-based study using the United Kingdom Clinical Practice Research Datalink (CPRD). We identified patients newly treated with either a long-acting insulin analog or an intermediate-acting human insulin between September 1, 2002 and January 31, 2018, with follow-up until January 31, 2019. Each long-acting insulin analog user was propensity score-matched to one intermediate-acting human insulin user, and a lag of 1 year was imposed. Cox proportional hazards models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs) of colorectal cancer, comparing long-acting insulin analogs with intermediate-acting human insulin. Secondary analysis was conducted to assess whether there was a duration-response relationship. RESULTS: A total of 10,734 new long-acting insulin analog users were matched to 10,734 new intermediate-acting human insulin users. After a median follow-up of 2.8 years, the use of long-acting insulin analogs was not associated with an increased risk of colorectal cancer, compared with intermediate-acting human insulin (1.80 vs. 1.87 per 1000 person-years, respectively; HR 0.96, 95% CI 0.70-1.34). There was no evidence of a duration-response relationship. CONCLUSIONS: The results of this population-based study indicate that use of long-acting insulin analogs is not associated with an overall increased risk of colorectal cancer.

Diagnosis of immune checkpoint inhibitor-associated myocarditis: A systematic review.

BACKGROUND: Myocarditis is a rare but severe adverse event associated with immune checkpoint inhibitors, its diagnosis depending on a high index of suspicion and appropriate investigations. Our objective was to systematically review the diagnostic approaches to myocarditis associated with immune checkpoint inhibitors. METHODS: The systematic review was conducted according to the PRISMA guidelines (PROSPERO Registration: CRD42018097247). We searched Medline and Embase for case reports, case series, and observational studies published in journal articles or presented as conference abstracts that describe patients who developed myocarditis after immune checkpoint inhibitor therapy. RESULTS: After a review of 2326 citations, we included 88 cases (53 case reports/series published in journal articles and 35 cases in the observational study). Serum troponin was elevated in 98% of the case reports and 94% of participants in the observational study. ST changes including ST elevation were present in almost a third of case reports. Echocardiography revealed preserved left ventricular ejection fraction in 32% of case reports and 51% of cases in the observational study; however, preserved systolic function did not predict greater survival. Patients who suffered poorer prognosis tended to have major conduction defects or ventricular arrhythmias more frequently than patients who did not. Acute myocardial ischemia was ruled out in all cases (n = 31) when the diagnostic workup included coronary angiography. CONCLUSIONS: Immune checkpoint inhibitor-associated myocarditis is characterized by elevation of cardiac troponin levels and non-specific electrocardiographic changes. Early coronary angiography may distinguish it from myocardial ischemia or myocardial infarction.

Learning to detect and understand drug discontinuation events from clinical narratives.

OBJECTIVE: Identifying drug discontinuation (DDC) events and understanding their reasons are important for medication management and drug safety surveillance. Structured data resources are often incomplete and lack reason information. In this article, we assessed the ability of natural language processing (NLP) systems to unlock DDC information from clinical narratives automatically. MATERIALS AND METHODS: We collected 1867 de-identified providers' notes from the University of Massachusetts Medical School hospital electronic health record system. Then 2 human experts chart reviewed those clinical notes to annotate DDC events and their reasons. Using the annotated data, we developed and evaluated NLP systems to automatically identify drug discontinuations and reasons at the sentence level using a novel semantic enrichment-based vector representation (SEVR) method for enhanced feature representation. RESULTS: Our SEVR-based NLP system achieved the best performance of 0.785 (AUC-ROC) for detecting discontinuation events and 0.745 (AUC-ROC) for identifying reasons when testing this highly imbalanced data, outperforming 2 state-of-the-art non-SEVR-based models. Compared with a rule-based baseline system for discontinuation detection, our system improved the sensitivity significantly (57.75% vs 18.31%, absolute value) while retaining a high specificity of 99.25%, leading to a significant improvement in AUC-ROC by 32.83% (absolute value). CONCLUSION: Experiments have shown that a high-performance NLP system can be developed to automatically identify DDCs and their reasons from providers' notes. The SEVR model effectively improved the system performance showing better generalization and robustness on unseen test data. Our work is an important step toward identifying reasons for drug discontinuation that will inform drug safety surveillance and pharmacovigilance.

Automatic extraction of quantitative data from ClinicalTrials.gov to conduct meta-analyses.

OBJECTIVES: Systematic reviews and meta-analyses are labor-intensive and time-consuming. Automated extraction of quantitative data from primary studies can accelerate this process. ClinicalTrials.gov, launched in 2000, is the world's largest trial repository of results data from clinical trials; it has been used as a source instead of journal articles. We have developed a Web application called EXACT (EXtracting Accurate efficacy and safety information from ClinicalTrials.gov) that allows users without advanced programming skills to automatically extract data from ClinicalTrials.gov in analysis-ready format. We have also used the automatically extracted data to examine the reproducibility of meta-analyses in three published systematic reviews. STUDY DESIGN AND SETTING: We developed a Python-based software application (EXACT) that automatically extracts data required for meta-analysis from the ClinicalTrials.gov database in a spreadsheet format. We confirmed the accuracy of the extracted data and then used those data to repeat meta-analyses in three published systematic reviews. To ensure that we used the same statistical methods and outcomes as the published systematic reviews, we repeated the meta-analyses using data manually extracted from the relevant journal articles. For the outcomes whose results we were able to reproduce using those journal article data, we examined the usability of ClinicalTrials.gov data. RESULTS: EXACT extracted data at ClincalTrials.gov with 100% accuracy, and it required 60% less time than the usual practice of manually extracting data from journal articles. We found that 87% of the data elements extracted using EXACT matched those extracted manually from the journal articles. We were able to reproduce 24 of 28 outcomes using the journal article data. Of these 24 outcomes, we were able to reproduce 83.3% of the published estimates using data at ClinicalTrials.gov. CONCLUSION: EXACT (http://bio-nlp.org/EXACT) automatically and accurately extracted data elements from ClinicalTrials.gov and thus reduced time in data extraction. The ClinicalTrials.gov data reproduced most meta-analysis results in our study, but this conclusion needs further validation.