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Abstract Background The handling of missing data is a challenge for inference and regression modelling. A particular challenge is dealing with missing predictor information, particularly when trying to build and make predictions from models for use in clinical practice. Methods We utilise a flexible Bayesian approach for handling missing predictor information in regression models. This provides practitioners with full posterior predictive distributions for both the missing predictor information (conditional on the observed predictors) and the outcome-of-interest. We apply this approach to a previously proposed counterfactual treatment selection model for type 2 diabetes second-line therapies. Our approach combines a regression model and a Dirichlet process mixture model (DPMM), where the former defines the treatment selection model, and the latter provides a flexible way to model the joint distribution of the predictors. Results We show that DPMMs can model complex relationships between predictor variables and can provide powerful means of fitting models to incomplete data (under missing-completely-at-random and missing-at-random assumptions). This framework ensures that the posterior distribution for the parameters and the conditional average treatment effect estimates automatically reflect the additional uncertainties associated with missing data due to the hierarchical model structure. We also demonstrate that in the presence of multiple missing predictors, the DPMM model can be used to explore which variable(s), if collected, could provide the most additional information about the likely outcome. Conclusions When developing clinical prediction models, DPMMs offer a flexible way to model complex covariate structures and handle missing predictor information. DPMM-based counterfactual prediction models can also provide additional information to support clinical decision-making, including allowing predictions with appropriate uncertainty to be made for individuals with incomplete predictor data.

Abstract Recent type 2 diabetes guidance from the UK’s National Institute for Health and Care Excellence (NICE) proposes offering SGLT2-inhibitor therapy to people with established atherosclerotic cardiovascular disease (ASCVD) or heart failure, and considering SGLT2-inhibitor therapy for those at high-risk of cardiovascular disease defined as a 10-year cardiovascular risk of > 10% using the QRISK2 algorithm. We used a contemporary population-representative UK cohort of people with type 2 diabetes to assess the implications of this guidance. 93.1% of people currently on anti-hyperglycaemic treatment are now recommended or considered for SGLT2-inhibitor therapy under the new guidance, with the majority (59.6%) eligible on the basis of QRISK2 rather than established ASCVD or heart failure (33.6%). Applying these results to the approximately 2.20 million people in England currently on anti-hyperglycaemic medication suggests 1.75 million people will now be considered for additional SGLT2-inhibitor therapy, taking the total cost of SGLT2-inhibitor therapy in England to over £1 billion per year. Given that older people, those of non-white ethnic groups, and those at lower cardiovascular disease risk were underrepresented in the clinical trials which were used to inform this guidance, careful evaluation of the impact and safety of increased SGLT2-inhibitor prescribing across different populations is urgently required. Evidence of benefit should be weighed against the major cost implications for the UK National Health Service.

Abstract Background Internet-based Cognitive Behaviour Therapy (iCBT) for depression have been implemented in routine care across Europe in varying ways, at various scales and with varying success. This study aimed to advance our understanding of organisational implementation climate from the perspectives of implementers and mental health service deliverers. Methods Qualitative and quantitative methods were combined to study the concept of organisational implementation climate in mental health care settings. Based on concept mapping, a qualitative workshop with implementers was used to conceptualise organisational implementation climate for optimizing iCBT use in routine practice. Service deliverers involved in the provision of iCBT were invited to participate in an explorative cross-sectional survey assessing levels of satisfaction and usability of iCBT, and organisational implementation climate in implementing iCBT. The two methods were applied independently to study viewpoints of implementers as well as service deliverers. Corresponding to the explorative nature of the study, inductive reasoning was applied to identify patterns and develop a reasonable explanation of the observations made. Correlative associations between satisfaction, usability and implementation climate were explored. Results Sixteen implementers representing fourteen service delivery organisations across Europe participated in the workshop. The top-three characteristics of a supportive organisational implementation climate included: (1) clear roles and skills of implementers, (2) feasible implementation targets, and (3) a dedicated implementation team. The top-three tools for creating a supportive implementation climate included: (1) feedback on job performance, (2) progress monitoring in achieving implementation targets, and (3) guidelines for assessing the impact of iCBT. The survey (n=111) indicated that service providers generally regarded their organisational implementation climate as supportive in implementing iCBT services. Organisational implementation climate was weakly associated with perceived usability and moderately with satisfaction with iCBT services. Conclusions Organisational implementation climate is a relevant factor to implementers and service deliverers in implementing iCBT in routine care. It is not only an inherent characteristic of the context in which implementation takes place, it can also be shaped to improve implementation of iCBT services. Future research should further theorise organisational implementation climate and empirically validate the measurement instruments such as used in this study.

Abstract Background It is unclear what to do when people with type 2 diabetes have had no or a limited glycemic response to a recently introduced medication. Intra-individual HbA1c variability can obscure true response. Some guidelines suggest stopping apparently ineffective therapy, but no studies have addressed this issue. Methods In a retrospective cohort analysis using the UK Clinical Practice Research Datalink (CPRD), we assessed the outcome of 55,530 patients with type 2 diabetes starting their second or third non-insulin glucose-lowering medication, with a baseline HbA1c > 58 mmol/mol (7.5%). For those with no HbA1c improvement or a limited response at 6 months (HbA1c fall

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: The impact of taking oral glucose-lowering medicines intermittently, rather than as recommended, is unclear. We conducted a retrospective cohort study using community-acquired U.K. clinical data (Clinical Practice Research Database [CPRD] and GoDARTS database) to examine the prevalence of nonadherence to treatment for type 2 diabetes and investigate its potential impact on HbA1c reduction stratified by type of glucose-lowering medication.Research Design and Methods: Data were extracted for patients treated between 2004 and 2014 who were newly prescribed metformin, sulfonylurea, thiazolidinedione, or dipeptidyl peptidase 4 inhibitors and who continued to obtain prescriptions over 1 year. Cohorts were defined by prescribed medication type, and good adherence was defined as a medication possession ratio ≥0.8. Linear regression was used to determine potential associations between adherence and 1-year baseline-adjusted HbA1c reduction.Results: In CPRD and GoDARTS, 13% and 15% of patients, respectively, were nonadherent. Proportions of nonadherent patients varied by the oral glucose-lowering treatment prescribed (range 8.6% [thiazolidinedione] to 18.8% [metformin]). Nonadherent, compared with adherent, patients had a smaller HbA1c reduction (0.4% [4.4 mmol/mol] and 0.46% [5.0 mmol/mol] for CPRD and GoDARTs, respectively). Difference in HbA1c response for adherent compared with nonadherent patients varied by drug (range 0.38% [4.1 mmol/mol] to 0.75% [8.2 mmol/mol] lower in adherent group). Decreasing levels of adherence were consistently associated with a smaller reduction in HbA1c.Conclusions: Reduced medication adherence for commonly used glucose-lowering therapies among patients persisting with treatment is associated with smaller HbA1c reductions compared with those taking treatment as recommended. Differences observed in HbA1c responses to glucose-lowering treatments may be explained in part by their intermittent use. [ABSTRACT FROM AUTHOR]

Aims: Predicting likely durability of glucose-lowering therapies for people with type 2 diabetes (T2D) could help inform individualised therapeutic choices.Methods: We used data from UKPDS patients with newly-diagnosed T2D randomised to first-line glucose-lowering monotherapy with chlorpropamide-glibenclamide-basal insulin or metformin. In 2339 participants who achieved one-year HbA1c values <7.5% (<59 mmol/mol)-we assessed relationships between one-year characteristics and time to monotherapy-failure (HbA1c ≥ 7.5% or requiring second-line therapy). Model validation was performed using bootstrap sampling.Results: Follow-up was median (IQR) 11.0 (8.0-14.0) years. Monotherapy-failure occurred in 72%-82%-75% and 79% for those randomised to chlorpropamide-glibenclamide-basal insulin or metformin respectively-after median 4.5 (3.0-6.6)-3.7 (2.6-5.6)-4.2 (2.7-6.5) and 3.8 (2.6- 5.2) years. Time-to-monotherapy-failure was predicted primarily by HbA1c and BMI values-with other risk factors varying by type of monotherapy-with predictions to within ±2.5 years for 55%-60%-56% and 57% of the chlorpropamide-glibenclamide-basal insulin and metformin monotherapy cohorts respectively.Conclusions: Post one-year glycaemic durability can be predicted robustly in individuals with newly-diagnosed T2D who achieve HbA1c values < 7.5% one year after commencing traditional monotherapies. Such information could be used to help guide glycaemic management for individual patients. [ABSTRACT FROM AUTHOR]