Design of the SALT Osteoporosis Study: a randomised pragmatic trial, to study a primary care screening and treatment program for the prevention of fractures in women aged 65 years or older.

BACKGROUND: Several drugs have become available for the treatment of osteoporosis. However, screening and treatment of patients with a high fracture risk is currently not recommended in the Netherlands, because the effectiveness of bone sparing drugs has not been demonstrated in the general primary care population. Here we describe the design of the SALT Osteoporosis study, which aims to examine whether the screening and treatment of older, female patients in primary care can reduce fractures, in comparison to usual care. METHODS: A randomised pragmatic trial has been designed using a stepwise approach in general care practices in the Netherlands. Women aged ≥65 years, who are not prescribed bone sparing drugs or corticosteroids are eligible for the study. First, women with at least one clinical risk factor for fractures, as determined by questionnaires, are randomly assigned to the intervention or control group. Second, women in the intervention group having a high fracture risk according to our screening program, including an adapted fracture risk assessment (FRAX) tool, combined with dual-energy x-ray absorptiometry (DXA), and instant vertebral assessment (IVA), are offered a structured treatment program. The women in the control group receive care as usual and will undergo the same screening as the intervention group at the end of the trial. The follow-up duration will be three years and the primary outcome is time to first incident fracture and the total number of fractures. DISCUSSION: The results of the current study will be very important for underpinnings of the prevention strategy of the osteoporosis guidelines. TRIAL REGISTRATION: ID NTR2430 . Registered 26 July 2010.

The Use of Antidepressants, Anxiolytics, and Hypnotics in People with Type 2 Diabetes and Patterns Associated with Use: The Hoorn Diabetes Care System Cohort.

Objective. With depression being present in approximately 20% of people with type 2 diabetes mellitus (T2DM), we expect equally frequent prescription of antidepressants, anxiolytics, and hypnotics. Nevertheless, prescription data in people with T2DM is missing and the effect of depression on glycaemic control is contradictory. The aim of this study was to assess the prevalence of antidepressants, anxiolytics, and/or hypnotics use in a large, managed, primary care system cohort of people with T2DM and to determine the sociodemographic characteristics, comorbidities, T2DM medication, and metabolic control associated with its use. Method. The prevalence of antidepressants, anxiolytics, and/or hypnotics use in the years 2007-2012 was assessed in the Hoorn Diabetes Care System Cohort from the Netherlands. Results. From the 7016 people with T2DM, 500 people (7.1%) used antidepressants only, 456 people (6.5%) used anxiolytics and/or hypnotics only, and 254 people (3.6%) used a combination. Conclusion. We conclude that in our managed, primary care system 17% of all people with T2DM used antidepressants, anxiolytics, and/or hypnotics. Users of antidepressants, anxiolytics, and/or hypnotics were more often female, non-Caucasian, lower educated, and more often treated with insulin.

Variants in Pharmacokinetic Transporters and Glycemic Response to Metformin: A Metgen Meta-Analysis.

Therapeutic response to metformin, a first-line drug for type 2 diabetes (T2D), is highly variable, in part likely due to genetic factors. To date, metformin pharmacogenetic studies have mainly focused on the impact of variants in metformin transporter genes, with inconsistent results. To clarify the significance of these variants in glycemic response to metformin in T2D, we performed a large-scale meta-analysis across the cohorts of the Metformin Genetics Consortium (MetGen). Nine candidate polymorphisms in five transporter genes (organic cation transporter [OCT]1, OCT2, multidrug and toxin extrusion transporter [MATE]1, MATE2-K, and OCTN1) were analyzed in up to 7,968 individuals. None of the variants showed a significant effect on metformin response in the primary analysis, or in the exploratory secondary analyses, when patients were stratified according to possible confounding genotypes or prescribed a daily dose of metformin. Our results suggest that candidate transporter gene variants have little contribution to variability in glycemic response to metformin in T2D.

Effectiveness of insulin therapy in people with Type 2 diabetes in the Hoorn Diabetes Care System.

AIMS: To identify HbA1c trajectories after the start of insulin treatment and to identify clinically applicable predictors of the response to insulin therapy. METHODS: The study population comprised 1203 people with Type 2 diabetes included in the Hoorn Diabetes Care System (n = 9849). Inclusion criteria were: age ≥ 40 years; initiation of insulin during follow-up after failure to reach HbA1c levels ≤ 53 mmol/mol (7%) with oral glucose-lowering agents; and a follow up ≥ 2 years after initiating insulin. Latent class growth modelling was used to identify trajectories of HbA1c . Subjects considered to be 'off target' had HbA1c levels ≥ 53 mmol/mol (7.0%) during one-third or more of the follow-up time, and those considered to be 'on target' had HbA1c levels ≥ 53 mmol/mol (7.0%) during less than one-third of the follow-up time. RESULTS: Four HbA1c trajectories were identified. Most people (88.7%) were classified as having a stable HbA1c trajectory of ~57 mmol/mol (7.4%). Only 24.4% of the people were on target in response to insulin; this was associated with lower HbA1c levels and a higher age at the start of insulin treatment. CONCLUSIONS: Using latent class growth modelling, four HbA1c trajectories were identified. A quarter of the people starting insulin were on target. Low HbA1c levels and advanced age at the start of insulin therapy were associated with better response to insulin therapy. Initiating insulin earlier improves the likelihood of achieving and sustaining glycaemic control.

Policy evaluation in diabetes prevention and treatment using a population-based macro simulation model: the MICADO model.

AIMS: To test a simulation model, the MICADO model, for estimating the long-term effects of interventions in people with and without diabetes. METHODS: The MICADO model includes micro- and macrovascular diseases in relation to their risk factors. The strengths of this model are its population scope and the possibility to assess parameter uncertainty using probabilistic sensitivity analyses. Outcomes include incidence and prevalence of complications, quality of life, costs and cost-effectiveness. We externally validated MICADO's estimates of micro- and macrovascular complications in a Dutch cohort with diabetes (n = 498,400) by comparing these estimates with national and international empirical data. RESULTS: For the annual number of people undergoing amputations, MICADO's estimate was 592 (95% interquantile range 291-842), which compared well with the registered number of people with diabetes-related amputations in the Netherlands (728). The incidence of end-stage renal disease estimated using the MICADO model was 247 people (95% interquartile range 120-363), which was also similar to the registered incidence in the Netherlands (277 people). MICADO performed well in the validation of macrovascular outcomes of population-based cohorts, while it had more difficulty in reflecting a highly selected trial population. CONCLUSIONS: Validation by comparison with independent empirical data showed that the MICADO model simulates the natural course of diabetes and its micro- and macrovascular complications well. As a population-based model, MICADO can be applied for projections as well as scenario analyses to evaluate the long-term (cost-)effectiveness of population-level interventions targeting diabetes and its complications in the Netherlands or similar countries.