Patient stratification for determining optimal second-line and third-line therapy for type 2 diabetes: the TriMaster study.

Precision medicine aims to treat an individual based on their clinical characteristics. A differential drug response, critical to using these features for therapy selection, has never been examined directly in type 2 diabetes. In this study, we tested two hypotheses: (1) individuals with body mass index (BMI) > 30 kg/m2, compared to BMI ≤ 30 kg/m2, have greater glucose lowering with thiazolidinediones than with DPP4 inhibitors, and (2) individuals with estimated glomerular filtration rate (eGFR) 60-90 ml/min/1.73 m2, compared to eGFR >90 ml/min/1.73 m2, have greater glucose lowering with DPP4 inhibitors than with SGLT2 inhibitors. The primary endpoint for both hypotheses was the achieved HbA1c difference between strata for the two drugs. In total, 525 people with type 2 diabetes participated in this UK-based randomized, double-blind, three-way crossover trial of 16 weeks of treatment with each of sitagliptin 100 mg once daily, canagliflozin 100 mg once daily and pioglitazone 30 mg once daily added to metformin alone or metformin plus sulfonylurea. Overall, the achieved HbA1c was similar for the three drugs: pioglitazone 59.6 mmol/mol, sitagliptin 60.0 mmol/mol and canagliflozin 60.6 mmol/mol (P = 0.2). Participants with BMI > 30 kg/m2, compared to BMI ≤ 30 kg/m2, had a 2.88 mmol/mol (95% confidence interval (CI): 0.98, 4.79) lower HbA1c on pioglitazone than on sitagliptin (n = 356, P = 0.003). Participants with eGFR 60-90 ml/min/1.73 m2, compared to eGFR >90 ml/min/1.73 m2, had a 2.90 mmol/mol (95% CI: 1.19, 4.61) lower HbA1c on sitagliptin than on canagliflozin (n = 342, P = 0.001). There were 2,201 adverse events reported, and 447/525 (85%) randomized participants experienced an adverse event on at least one of the study drugs. In this precision medicine trial in type 2 diabetes, our findings support the use of simple, routinely available clinical measures to identify the drug class most likely to deliver the greatest glycemic reduction for a given patient. (ClinicalTrials.gov registration: NCT02653209 ; ISRCTN registration: 12039221 .).

Development of a treatment selection algorithm for SGLT2 and DPP-4 inhibitor therapies in people with type 2 diabetes: a retrospective cohort study.

BACKGROUND: Current treatment guidelines do not provide recommendations to support the selection of treatment for most people with type 2 diabetes. We aimed to develop and validate an algorithm to allow selection of optimal treatment based on glycaemic response, weight change, and tolerability outcomes when choosing between SGLT2 inhibitor or DPP-4 inhibitor therapies. METHODS: In this retrospective cohort study, we identified patients initiating SGLT2 and DPP-4 inhibitor therapies after Jan 1, 2013, from the UK Clinical Practice Research Datalink (CPRD). We excluded those who received SGLT2 or DPP-4 inhibitors as first-line treatment or insulin at the same time, had estimated glomerular filtration rate (eGFR) of less than 45 mL/min per 1·73 m2, or did not have a valid baseline glycated haemoglobin (HbA1c) measure (<53 or ≥120 mmol/mol). The primary efficacy outcome was the HbA1c value reached 6 months after drug initiation, adjusted for baseline HbA1c. Clinical features associated with differential HbA1c outcome on the two therapies were identified in CPRD (n=26 877), and replicated in reanalysis of 14 clinical trials (n=10 414). An algorithm to predict individual-level differential HbA1c outcome on the two therapies was developed in CPRD (derivation; n=14 069) and validated in head-to-head trials (n=2499) and CPRD (independent validation; n=9376). In CPRD, we further explored heterogeneity in 6-month weight change and treatment discontinuation. FINDINGS: Among 10 253 patients initiating SGLT2 inhibitors and 16 624 patients initiating DPP-4 inhibitors in CPRD, baseline HbA1c, age, BMI, eGFR, and alanine aminotransferase were associated with differential HbA1c outcome with SGLT2 inhibitor and DPP-4 inhibitor therapies. The median age of participants was 62·0 years (IQR 55·0-70·0). 10 016 (37·3%) were women and 16 861 (62·7%) were men. An algorithm based on these five features identified a subgroup, representing around four in ten CPRD patients, with a 5 mmol/mol or greater observed benefit with SGLT2 inhibitors in all validation cohorts (CPRD 8·8 mmol/mol [95% CI 7·8-9·8]; CANTATA-D and CANTATA-D2 trials 5·8 mmol/mol [3·9-7·7]; BI1245.20 trial 6·6 mmol/mol [2·2-11·0]). In CPRD, predicted differential HbA1c response with SGLT2 inhibitor and DPP-4 inhibitor therapies was not associated with weight change. Overall treatment discontinuation within 6 months was similar in patients predicted to have an HbA1c benefit with SGLT2 inhibitors over DPP-4 inhibitors (median 15·2% [13·2-20·3] vs 14·4% [12·9-16·7]). A smaller subgroup predicted to have greater HbA1c reduction with DPP-4 inhibitors were twice as likely to discontinue SGLT2 inhibitors than DPP-4 inhibitors (median 26·8% [23·4-31·0] vs 14·8% [12·9-16·8]). INTERPRETATION: A validated treatment selection algorithm for SGLT2 inhibitor and DPP-4 inhibitor therapies can support decisions on optimal treatment for people with type 2 diabetes. FUNDING: BHF-Turing Cardiovascular Data Science Award and the UK Medical Research Council.

Real-world effectiveness of pneumococcal vaccination in older adults: Cohort study using the UK Clinical Practice Research Datalink.

BACKGROUND: The 23-valent pneumococcal polysaccharide vaccine (PPV23) is recommended for UK older adults, but how age moderates effectiveness is unclear. METHODS: Three annual cohorts of primary-care patients aged≥65y from the Clinical Practice Research Datalink selected from 2003-5 created a natural experiment (n = 324,804), reflecting the staged introduction of the vaccine. The outcome was symptoms consistent with community-acquired pneumococcal pneumonia (CAP) requiring antibiotics or hospitalisation. We used the prior event rate ratio (PERR) approach to address bias from unmeasured confounders. RESULTS: Vaccinated patients had higher rates of CAP in the year before vaccination than their controls, indicating the potential for confounding bias. After adjustment for confounding using the prior event rate ratio (PERR) method, PPV23 was estimated to be effective against CAP for two years after vaccination in all age sub-groups with hazard ratios (95% confidence intervals) of 0.86 (0.80 to 0.93), 0.74 (0.65 to 0.85) and 0.65 (0.57 to 0.74) in patients aged 65-74, 75-79 and 80+ respectively in the 2005 cohort. Age moderated the effect of vaccination with predicted risk reductions of 8% at 65y and 29% at 80y. CONCLUSIONS: PPV23 is moderately effective at reducing CAP among UK patients aged≥65y, in the two years after vaccination. Vaccine effectiveness is maintained, and may increase, in the oldest age groups in step with increasing susceptibility to CAP.

Influenza vaccination reduced myocardial infarctions in United Kingdom older adults: a prior event rate ratio study.

OBJECTIVES: We aimed to estimate the real-world effectiveness of the influenza vaccine against myocardial infarction (MI) and influenza in the decade since adults aged ≥ 65 years were first recommended the vaccine. STUDY DESIGN AND SETTING: We identified annual cohorts, 1997 to 2011, of adults aged ≥ 65 years, without previous influenza vaccination, from UK general practices, registered with the Clinical Practice Research Datalink. Using a quasi-experimental study design to control for confounding bias, we estimated influenza vaccine effectiveness on hospitalization for MI, influenza, and antibiotic prescriptions for lower respiratory tract infections. RESULTS: Vaccination was moderately effective against influenza, the prior event rate ratio-adjusted hazard ratios ranging from 0.70 in 1999 to 0.99 in 2001. Prior event rate ratio-adjusted hazard ratios demonstrated a protective effect against MIs, varying between 0.40 in 2010 and 0.89 in 2001. Aggregated across the cohorts, influenza vaccination reduced the risk of MIs by 39% (95% confidence interval: 34%, 44%). CONCLUSION: Effectiveness of the flu vaccine in preventing MIs in older UK adults is consistent with the limited evidence from clinical trials. Similar trends in effectiveness against influenza and against MIs suggest the risk of influenza mediates the effectiveness against MIs, although divergence in some years implies the mechanism may be complex.

Uptake and impact of the English National Health Service digital diabetes prevention programme: observational study.

INTRODUCTION: 'Healthier You', the National Health Service (NHS) diabetes prevention programme (DPP) offers adults in England at high risk of type 2 diabetes (T2DM) an evidence-based behavioral intervention to prevent or delay T2DM onset. This study assesses the impact of a pilot digital stream of the DPP (DDPP) on glycated hemoglobin (HbA1c) and weight. RESEARCH DESIGN AND METHODS: A service evaluation employing prospectively collected data in a prospective cohort design in nine NHS local pilot areas across England. Participants were adults with non-diabetic hyperglycemia (NDH) (HbA1c 42-47 mmol/mol or fasting plasma glucose 5.5-6.9 mmol/L) in the 12 months prior to referral. The DDPP comprised five digital health interventions (DHI). Joint primary outcomes were changes in HbA1c and weight between baseline and 12 months. HbA1c and weight readings were recorded at referral (baseline) by general practices, and then at 12-month postregistration. Demographic data and service variables were collected from the DHI providers. RESULTS: 3623 participants with NDH registered for the DDPP and of these, 2734 (75%) were eligible for inclusion in the analyses. Final (12-month) follow-up data for HbA1c were available for 1799 (50%) and for weight 1817 (50%) of registered participants. Mean change at 12 months was -3.1 (-3.4 to -2.8) kg, p<0.001 for weight and -1.6 (-1.8 to -1.4) mmol/mol, p<0.001 for HbA1c. Access to peer support and a website and telephone service was associated with significantly greater reductions in HbA1c and weight. CONCLUSIONS: Participation in the DDPP was associated with clinically significant reductions in weight and HbA1c. Digital diabetes prevention can be an effective and wide-reaching component of a population-based approach to addressing type 2 diabetes prevention.

Impact of influenza vaccination on amoxicillin prescriptions in older adults: A retrospective cohort study using primary care data.

BACKGROUND: Bacterial infections of the upper and lower respiratory tract are a frequent complication of influenza and contribute to the widespread use of antibiotics. Influenza vaccination may help reduce both appropriate and inappropriate prescribing of antibiotics. Electronic health records provide a rich source of information for assessing secondary effects of influenza vaccination. METHODS: We conducted a retrospective study to estimate effects of influenza vaccine on antibiotic (amoxicillin) prescription in the elderly based on data from the Clinical Practice Research Datalink. The introduction of UK policy to recommend the influenza vaccine to older adults in 2000 led to a substantial increase in uptake, creating a natural experiment. Of 259,753 eligible patients that were unvaccinated in 1999 and aged≥65y by January 2000, 88,519 patients received influenza vaccination in 2000. These were propensity score matched 1:1 to unvaccinated patients. Time-to-amoxicillin was analysed using the Prior Event Rate Ratio (PERR) Pairwise method to address bias from time-invariant measured and unmeasured confounders. A simulation study and negative control outcome were used to help strengthen the validity of results. RESULTS: Compared to unvaccinated patients, those from the vaccinated group were more likely to be prescribed amoxicillin in the year prior to vaccination: hazard ratio (HR) 1.90 (95% confidence interval 1.83, 1.98). Following vaccination, the vaccinated group were again more likely to be prescribed amoxicillin, HR 1.64 (1.58,1.71). After adjusting for prior differences between the two groups using PERR Pairwise, overall vaccine effectiveness was 0.86 (0.81, 0.92). Additional analyses suggested that provided data meet the PERR assumptions, these estimates were robust. CONCLUSIONS: Once differences between groups were taken into account, influenza vaccine had a beneficial effect, lowering the frequency of amoxicillin prescribing in the vaccinated group. Ensuring successful implementation of national programmes of vaccinating older adults against influenza may help contribute to reducing antibiotic resistance.

Prior event rate ratio adjustment produced estimates consistent with randomized trial: a diabetes case study.

OBJECTIVES: Electronic health records (EHR) provide a valuable resource for assessing drug side-effects, but treatments are not randomly allocated in routine care creating the potential for bias. We conduct a case study using the Prior Event Rate Ratio (PERR) Pairwise method to reduce unmeasured confounding bias in side-effect estimates for two second-line therapies for type 2 diabetes, thiazolidinediones, and sulfonylureas. STUDY DESIGN AND SETTINGS: Primary care data were extracted from the Clinical Practice Research Datalink (n = 41,871). We utilized outcomes from the period when patients took first-line metformin to adjust for unmeasured confounding. Estimates for known side-effects and a negative control outcome were compared with the A Diabetes Outcome Progression Trial (ADOPT) trial (n = 2,545). RESULTS: When on metformin, patients later prescribed thiazolidinediones had greater risks of edema, HR 95% CI 1.38 (1.13, 1.68) and gastrointestinal side-effects (GI) 1.47 (1.28, 1.68), suggesting the presence of unmeasured confounding. Conventional Cox regression overestimated the risk of edema on thiazolidinediones and identified a false association with GI. The PERR Pairwise estimates were consistent with ADOPT: 1.43 (1.10, 1.83) vs. 1.39 (1.04, 1.86), respectively, for edema, and 0.91 (0.79, 1.05) vs. 0.94 (0.80, 1.10) for GI. CONCLUSION: The PERR Pairwise approach offers potential for enhancing postmarketing surveillance of side-effects from EHRs but requires careful consideration of assumptions.

Disease progression and treatment response in data-driven subgroups of type 2 diabetes compared with models based on simple clinical features: an analysis using clinical trial data.

BACKGROUND: Research using data-driven cluster analysis has proposed five subgroups of diabetes with differences in diabetes progression and risk of complications. We aimed to compare the clinical utility of this subgroup-based approach for predicting patient outcomes with an alternative strategy of developing models for each outcome using simple patient characteristics. METHODS: We identified five clusters in the ADOPT trial (n=4351) using the same data-driven cluster analysis as reported by Ahlqvist and colleagues. Differences between clusters in glycaemic and renal progression were investigated and contrasted with stratification using simple continuous clinical features (age at diagnosis for glycaemic progression and baseline renal function for renal progression). We compared the effectiveness of a strategy of selecting glucose-lowering therapy using clusters with one combining simple clinical features (sex, BMI, age at diagnosis, baseline HbA1c) in an independent trial cohort (RECORD [n=4447]). FINDINGS: Clusters identified in trial data were similar to those described in the original study by Ahlqvist and colleagues. Clusters showed differences in glycaemic progression, but a model using age at diagnosis alone explained a similar amount of variation in progression. We found differences in incidence of chronic kidney disease between clusters; however, estimated glomerular filtration rate at baseline was a better predictor of time to chronic kidney disease. Clusters differed in glycaemic response, with a particular benefit for thiazolidinediones in patients in the severe insulin-resistant diabetes cluster and for sulfonylureas in patients in the mild age-related diabetes cluster. However, simple clinical features outperformed clusters to select therapy for individual patients. INTERPRETATION: The proposed data-driven clusters differ in diabetes progression and treatment response, but models that are based on simple continuous clinical features are more useful to stratify patients. This finding suggests that precision medicine in type 2 diabetes is likely to have most clinical utility if it is based on an approach of using specific phenotypic measures to predict specific outcomes, rather than assigning patients to subgroups. FUNDING: UK Medical Research Council.

Time trends in prescribing of type 2 diabetes drugs, glycaemic response and risk factors: A retrospective analysis of primary care data, 2010-2017.

AIM: To describe population-level time trends in prescribing patterns of type 2 diabetes therapy, and in short-term clinical outcomes (glycated haemoglobin [HbA1c], weight, blood pressure, hypoglycaemia and treatment discontinuation) after initiating new therapy. MATERIALS AND METHODS: We studied 81 532 people with type 2 diabetes initiating a first- to fourth-line drug in primary care between 2010 and 2017 inclusive in United Kingdom electronic health records (Clinical Practice Research Datalink). Trends in new prescriptions and subsequent 6- and 12-month adjusted changes in glycaemic response (reduction in HbA1c), weight, blood pressure and rates of hypoglycaemia and treatment discontinuation were examined. RESULTS: Use of dipeptidyl peptidase-4 inhibitors as second-line therapy near doubled (41% of new prescriptions in 2017 vs. 22% in 2010), replacing sulphonylureas as the most common second-line drug (29% in 2017 vs. 53% in 2010). Sodium-glucose co-transporter-2 inhibitors, introduced in 2013, comprised 17% of new first- to fourth-line prescriptions by 2017. First-line use of metformin remained stable (91% of new prescriptions in 2017 vs. 91% in 2010). Over the study period there was little change in average glycaemic response and in the proportion of people discontinuing treatment. There was a modest reduction in weight after initiating second- and third-line therapy (improvement in weight change 2017 vs. 2010 for second-line therapy: -1.5 kg, 95% confidence interval [CI] -1.9, -1.1; P < 0.001), and a slight reduction in systolic blood pressure after initiating first-, second- and third-line therapy (improvement in systolic blood pressure change 2017 vs. 2010 range: -1.7 to -2.1 mmHg; all P < 0.001). Hypoglycaemia rates decreased over time with second-line therapy (incidence rate ratio 0.94 per year, 95% CI 0.88, 1.00; P = 0.04), mirroring the decline in use of sulphonylureas. CONCLUSIONS: Recent changes in prescribing of therapy for people with type 2 diabetes have not led to a change in glycaemic response and have resulted in modest improvements in other population-level short-term clinical outcomes.

Evaluating associations between the benefits and risks of drug therapy in type 2 diabetes: a joint modeling approach.

OBJECTIVE: Precision medicine drug therapy seeks to maximize efficacy and minimize harm for individual patients. This will be difficult if drug response and side effects are positively associated, meaning that patients likely to respond best are at increased risk of side effects. We applied joint longitudinal-survival models to evaluate associations between drug response (longitudinal outcome) and the risk of side effects (survival outcome) for patients initiating type 2 diabetes therapy. STUDY DESIGN AND SETTING: Participants were randomized to metformin (MFN), sulfonylurea (SU), or thiazolidinedione (TZD) therapy in the A Diabetes Outcome Progression Trial (ADOPT) drug efficacy trial (n=4,351). Joint models were parameterized for 1) current HbA1c response (change from baseline in HbA1c) and 2) cumulative HbA1c response (total HbA1c change). RESULTS: With MFN, greater HbA1c response did not increase the risk of gastrointestinal events (HR per 1% absolute greater current response 0.82 [95% CI 0.67, 1.01]; HR per 1% higher cumulative response 0.90 [95% CI 0.81, 1.00]). With SU, greater current response was associated with an increased risk of hypoglycemia (HR 1.41 [95% CI 1.04, 1.91]). With TZD, greater response was associated with an increased risk of edema (current HR 1.45 [95% CI 1.05, 2.01]; cumulative 1.22 [95% CI 1.07, 1.38]) but not fracture. CONCLUSION: Joint modeling provides a useful framework to evaluate the association between response to a drug and the risk of developing side effects. There may be great potential for widespread application of joint modeling to evaluate the risks and benefits of both new and established medications.

Sex and BMI Alter the Benefits and Risks of Sulfonylureas and Thiazolidinediones in Type 2 Diabetes: A Framework for Evaluating Stratification Using Routine Clinical and Individual Trial Data.

OBJECTIVE: The choice of therapy for type 2 diabetes after metformin is guided by overall estimates of glycemic response and side effects seen in large cohorts. A stratified approach to therapy would aim to improve on this by identifying subgroups of patients whose glycemic response or risk of side effects differs markedly. We assessed whether simple clinical characteristics could identify patients with differing glycemic response and side effects with sulfonylureas and thiazolidinediones. RESEARCH DESIGN AND METHODS: We studied 22,379 patients starting sulfonylurea or thiazolidinedione therapy in the U.K. Clinical Practice Research Datalink (CPRD) to identify features associated with increased 1-year HbA1c fall with one therapy class and reduced fall with the second. We then assessed whether prespecified patient subgroups defined by the differential clinical factors showed differing 5-year glycemic response and side effects with sulfonylureas and thiazolidinediones using individual randomized trial data from ADOPT (A Diabetes Outcome Progression Trial) (first-line therapy, n = 2,725) and RECORD (Rosiglitazone Evaluated for Cardiovascular Outcomes and Regulation of Glycemia in Diabetes) (second-line therapy, n = 2,222). Further replication was conducted using routine clinical data from GoDARTS (Genetics of Diabetes Audit and Research in Tayside Scotland) (n = 1,977). RESULTS: In CPRD, male sex and lower BMI were associated with greater glycemic response with sulfonylureas and a lesser response with thiazolidinediones (both P < 0.001). In ADOPT and RECORD, nonobese males had a greater overall HbA1c reduction with sulfonylureas than with thiazolidinediones (P < 0.001); in contrast, obese females had a greater HbA1c reduction with thiazolidinediones than with sulfonylureas (P < 0.001). Weight gain and edema risk with thiazolidinediones were greatest in obese females; however, hypoglycemia risk with sulfonylureas was similar across all subgroups. CONCLUSIONS: Patient subgroups defined by sex and BMI have different patterns of benefits and risks on thiazolidinedione and sulfonylurea therapy. Subgroup-specific estimates can inform discussion about the choice of therapy after metformin for an individual patient. Our approach using routine and shared trial data provides a framework for future stratification research in type 2 diabetes.

Predicting Incident Multimorbidity.

PURPOSE: Multimorbidity is associated with adverse outcomes, yet research on the determinants of its incidence is lacking. We investigated which sociodemographic, health, and individual lifestyle (eg, physical activity, smoking behavior, body mass index) characteristics predict new cases of multimorbidity. METHODS: We used data from 4,564 participants aged 50 years and older in the English Longitudinal Study of Aging that included a 10-year follow-up period. Discrete time-to-event (complementary log-log) models were constructed for exploring the associations of baseline characteristics with outcomes between 2002-2003 and 2012-2013 separately for participants with no initial conditions (n = 1,377) developing multimorbidity, any increase in conditions within 10 years regardless of initial conditions, and the impact of individual conditions on incident multimorbidity. RESULTS: The risks of developing multimorbidity were positively associated with age, and they were greater for the least wealthy, for participants who were obese, and for those who reported the lowest levels of physical activity or an external locus of control (believing that life events are outside of one's control) for all groups regardless of baseline conditions (all linear trends <.05). No significant associations were observed for sex, educational attainment, or social detachment. For participants with any increase in conditions (n = 4,564), a history of smoking was the only additional predictor. For participants with a single baseline condition (n = 1,534), chronic obstructive pulmonary disease (COPD), asthma, and arrhythmia showed the strongest associations with subsequent multimorbidity. CONCLUSIONS: Our findings support the development and implementation of a strategy targeting the prevention of multimorbidity for susceptible groups. This approach should incorporate behavior change addressing lifestyle factors and target health-related locus of control.

Precision Medicine in Type 2 Diabetes: Clinical Markers of Insulin Resistance Are Associated With Altered Short- and Long-term Glycemic Response to DPP-4 Inhibitor Therapy.

OBJECTIVE: A precision approach to type 2 diabetes therapy would aim to target treatment according to patient characteristics. We examined if measures of insulin resistance and secretion were associated with glycemic response to dipeptidyl peptidase 4 (DPP-4) inhibitor therapy. RESEARCH DESIGN AND METHODS: We evaluated whether markers of insulin resistance and insulin secretion were associated with 6-month glycemic response in a prospective study of noninsulin-treated participants starting DPP-4 inhibitor therapy (Predicting Response to Incretin Based Agents [PRIBA] study; n = 254), with replication for routinely available markers in U.K. electronic health care records (Clinical Practice Research Datalink [CPRD]; n = 23,001). In CPRD, we evaluated associations between baseline markers and 3-year durability of response. To test the specificity of findings, we repeated analyses for glucagon-like peptide 1 (GLP-1) receptor agonists (PRIBA, n = 339; CPRD, n = 4,464). RESULTS: In PRIBA, markers of higher insulin resistance (higher fasting C-peptide [P = 0.03], HOMA2 insulin resistance [P = 0.01], and triglycerides [P < 0.01]) were associated with reduced 6-month HbA1c response to DPP-4 inhibitors. In CPRD, higher triglycerides and BMI were associated with reduced HbA1c response (both P < 0.01). A subgroup defined by obesity (BMI ≥30 kg/m2) and high triglycerides (≥2.3 mmol/L) had reduced 6-month response in both data sets (PRIBA HbA1c reduction 5.3 [95% CI 1.8, 8.6] mmol/mol [0.5%] [obese and high triglycerides] vs. 11.3 [8.4, 14.1] mmol/mol [1.0%] [nonobese and normal triglycerides]; P = 0.01). In CPRD, the obese, high- triglycerides subgroup also had less durable response (hazard ratio 1.28 [1.16, 1.41]; P < 0.001). There was no association between markers of insulin resistance and response to GLP-1 receptor agonists. CONCLUSIONS: Markers of higher insulin resistance are consistently associated with reduced glycemic response to DPP-4 inhibitors. This finding provides a starting point for the application of a precision diabetes approach to DPP-4 inhibitor therapy.

Cohort profile for the MASTERMIND study: using the Clinical Practice Research Datalink (CPRD) to investigate stratification of response to treatment in patients with type 2 diabetes.

PURPOSE: This is a retrospective cohort study using observational data from anonymised primary care records. We identify and extract all patients with type 2 diabetes and associated clinical data from the Clinical Practice Research Datalink (CPRD) to inform models of disease progression and stratification of treatment. PARTICIPANTS: Data were extracted from CPRD on 8 August 2016. The initial data set contained all patients (n=313 485) in the database who had received a type 2 diabetes medication. Criteria were applied to identify and exclude those with type 1 diabetes, polycystic ovarian syndrome or other forms of diabetes (n=40 204), and for data quality control (n=12). We identified 251 338 patients for inclusion in future analyses of diabetes progression and treatment response. FINDINGS TO DATE: For 6-month response to treatment, measured by change in glycated haemoglobin (HbA1c), we have 91 765 patients with 119 785 treatment response episodes. The greatest impact on reduction of HbA1c occurs with first-line and second-line treatments, metformin and sulfonylurea. Patients moving to third-line treatments tend to have greater weights and higher body mass index. We have investigated the impact of non-adherence to commonly used glucose-lowering medications on HbA1c. For baseline-adjusted HbA1c change over 1 year, non-adherent patients had lower HbA1c reductions than adherent patients, with mean and 95% CI of -4.4 (-4.7 to -4.0) mmol/mol (-0.40 (-0.43 to -0.37) %). FUTURE PLANS: Findings from studies using these data will help inform future treatment plans and guidelines. Additional data are added with updates from CPRD. This will increase the numbers of patients on newer medications and add more data on those already receiving treatment. There are several ongoing studies investigating different hypotheses regarding differential response to treatment and progression of diabetes. For side effects, links to Hospital Episode Statistics data, where severe events such as hypoglycaemia will be recorded, will also be explored.

Adjusting for unmeasured confounding in nonrandomized longitudinal studies: a methodological review.

OBJECTIVES: Motivated by recent calls to use electronic health records for research, we reviewed the application and development of methods for addressing the bias from unmeasured confounding in longitudinal data. STUDY DESIGN AND SETTING: Methodological review of existing literature. We searched MEDLINE and EMBASE for articles addressing the threat to causal inference from unmeasured confounding in nonrandomized longitudinal health data through quasi-experimental analysis. RESULTS: Among the 121 studies included for review, 84 used instrumental variable analysis (IVA), of which 36 used lagged or historical instruments. Difference-in-differences (DiD) and fixed effects (FE) models were found in 29 studies. Five of these combined IVA with DiD or FE to try to mitigate for time-dependent confounding. Other less frequently used methods included prior event rate ratio adjustment, regression discontinuity nested within pre-post studies, propensity score calibration, perturbation analysis, and negative control outcomes. CONCLUSION: Well-established econometric methods such as DiD and IVA are commonly used to address unmeasured confounding in nonrandomized longitudinal studies, but researchers often fail to take full advantage of available longitudinal information. A range of promising new methods have been developed, but further studies are needed to understand their relative performance in different contexts before they can be recommended for widespread use.

Safety and Effectiveness of Statins for Prevention of Recurrent Myocardial Infarction in 12 156 Typical Older Patients: A Quasi-Experimental Study.

BACKGROUND: There is limited evidence on statin risk and effectiveness for patients aged 80+. We estimated risk of recurrent myocardial infarction, muscle-related and other adverse events, and statin-related incremental costs in "real-world" older patients treated with statins versus no statins. METHODS: We used primary care electronic medical records from the UK Clinical Practice Research Datalink. Subhazard ratios (competing risk of death) for myocardial infarction recurrence (primary end point), falls, fractures, ischemic stroke, and dementia, and hazard ratios (Cox) for all-cause mortality were used to compare older (60+) statin users and 1:1 propensity-score-matched controls (n = 12,156). Participants were followed-up for 10 years. RESULTS: Mean age was 76.5±9.2 years; 45.5% were women. Statins were associated with near significant reduction in myocardial infarction recurrence (subhazard ratio = 0.84, 0.69-1.02, p = .073), with protective effect in the 60-79 age group (0.73, 0.57-0.94) but a nonsignificant result in the 80+ group (1.06, 0.78-1.44; age interaction p = .094). No significant associations were found for stroke or dementia. Data suggest an increased risk of falls (1.36, 1.17-1.60) and fractures (1.33, 1.04-1.69) in the first 2 years of treatment, particularly in the 80+ group. Treatment was associated with lower all-cause mortality. Statin use was associated with health care cost savings in the 60-79 group but higher costs in the 80+ group. CONCLUSIONS: Estimates of statin effectiveness for the prevention of recurrent myocardial infarction in patients aged 60-79 years were similar to trial results, but more evidence is needed in the older group. There may be an excess of falls and fractures in very old patients, which deserves further investigation.

Obesity in Older People With and Without Conditions Associated With Weight Loss: Follow-up of 955,000 Primary Care Patients.

BACKGROUND: Moderate obesity in later life may improve survival, prompting calls to revise obesity control policies. However, this obesity paradox may be due to confounding from smoking, diseases causing weight-loss, plus varying follow-up periods. We aimed to estimate body mass index (BMI) associations with mortality, incident type 2 diabetes, and coronary heart disease in older people with and without the above confounders. METHODS: Cohort analysis in Clinical Practice Research Datalink primary care, hospital and death certificate electronic medical records in England for ages 60 to more than 85 years. Models were adjusted for age, gender, alcohol use, smoking, calendar year, and socioeconomic status. RESULTS: Overall, BMI 30-34.9 (obesity class 1) was associated with lower overall death rates in all age groups. However, after excluding the specific confounders and follow-up less than 4 years, BMI mortality risk curves at age 65-69 were U-shaped, with raised risks at lower BMIs, a nadir between 23 and 26.9 and steeply rising risks above. In older age groups, mortality nadirs were at modestly higher BMIs (all <30) and risk slopes at higher BMIs were less marked, becoming nonsignificant at age 85 and older. Incidence of diabetes was raised for obesity-1 at all ages and for coronary heart disease to age 84. CONCLUSIONS: Obesity is associated with shorter survival plus higher incidence of coronary heart disease and type 2 diabetes in older populations after accounting for the studied confounders, at least to age 84. These results cast doubt on calls to revise obesity control policies based on the claimed risk paradox at older ages.

Vitamin D and Risk of Neuroimaging Abnormalities.

Vitamin D deficiency has been linked with an increased risk of incident all-cause dementia and Alzheimer's disease. The aim of the current study was to explore the potential mechanisms underlying these associations by determining whether low vitamin D concentrations are associated with the development of incident cerebrovascular and neurodegenerative neuroimaging abnormalities. The population consisted of 1,658 participants aged ≥65 years from the US-based Cardiovascular Health Study who were free from prevalent cardiovascular disease, stroke and dementia at baseline in 1992-93. Serum 25-hydroxyvitamin D (25(OH)D) concentrations were determined by liquid chromatography-tandem mass spectrometry from blood samples collected at baseline. The first MRI scan was conducted between 1991-1994 and the second MRI scan was conducted between 1997-1999. Change in white matter grade, ventricular grade and presence of infarcts between MRI scan one and two were used to define neuroimaging abnormalities. During a mean follow-up of 5.0 years, serum 25(OH)D status was not significantly associated with the development of any neuroimaging abnormalities. Using logistic regression models, the multivariate adjusted odds ratios (95% confidence interval) for worsening white matter grade in participants who were severely 25(OH)D deficient (<25 nmol/L) and deficient (≥25-50 nmol/L) were 0.76 (0.35-1.66) and 1.09 (0.76-1.55) compared to participants with sufficient concentrations (≥50 nmol/L). The multivariate adjusted odds ratios for ventricular grade in participants who were severely 25(OH)D deficient and deficient were 0.49 (0.20-1.19) and 1.12 (0.79-1.59) compared to those sufficient. The multivariate adjusted odds ratios for incident infarcts in participants who were severely 25(OH)D deficient and deficient were 1.95 (0.84-4.54) and 0.73 (0.47-1.95) compared to those sufficient. Overall, serum vitamin D concentrations could not be shown to be associated with the development of cerebrovascular or neurodegenerative neuroimaging abnormalities in Cardiovascular Health Study participants.

Should Studies of Diabetes Treatment Stratification Correct for Baseline HbA1c?

AIMS: Baseline HbA1c is a major predictor of response to glucose lowering therapy and therefore a potential confounder in studies aiming to identify other predictors. However, baseline adjustment may introduce error if the association between baseline HbA1c and response is substantially due to measurement error and regression to the mean. We aimed to determine whether studies of predictors of response should adjust for baseline HbA1c. METHODS: We assessed the relationship between baseline HbA1c and glycaemic response in 257 participants treated with GLP-1R agonists and assessed whether it reflected measurement error and regression to the mean using duplicate 'pre-baseline' HbA1c measurements not included in the response variable. In this cohort and an additional 2659 participants treated with sulfonylureas we assessed the relationship between covariates associated with baseline HbA1c and treatment response with and without baseline adjustment, and with a bias correction using pre-baseline HbA1c to adjust for the effects of error in baseline HbA1c. RESULTS: Baseline HbA1c was a major predictor of response (R2 = 0.19,ß = -0.44,p<0.001).The association between pre-baseline and response was similar suggesting the greater response at higher baseline HbA1cs is not mainly due to measurement error and subsequent regression to the mean. In unadjusted analysis in both cohorts, factors associated with baseline HbA1c were associated with response, however these associations were weak or absent after adjustment for baseline HbA1c. Bias correction did not substantially alter associations. CONCLUSIONS: Adjustment for the baseline HbA1c measurement is a simple and effective way to reduce bias in studies of predictors of response to glucose lowering therapy.