Glycaemic, weight, and blood pressure changes associated with early versus later treatment intensification with dapagliflozin in United Kingdom primary care patients with type 2 diabetes mellitus

AIMS

Early treatment intensification for type 2 diabetes mellitus (T2DM) is often required to achieve glycaemic control and avoid longer-term complications. We assessed associations between early versus later dapagliflozin initiation with changes in glucose control, weight, and blood pressure using UK Clinical Practice Research Datalink (CPRD) data.

METHODS

People with T2DM aged ≥18 years, initiating dapagliflozin between November 2012 and August 2016 and with prior oral T2DM therapy (N = 3774), were included. The relationship between early (first intensification after metformin or sulfonylurea monotherapy) and later (second or higher-order intensification) dapagliflozin use and baseline changes in glycated haemoglobin A1c (HbA1c; ≥1.0% absolute reduction), weight (≥5.0% relative loss), and systolic blood pressure (SBP; ≥2 mmHg absolute reduction) after 6-12 months were assessed.

RESULTS

Overall, 25% of patients (951 of 3774) were early users and 75% (2823 of 3774) were later users. Later users were older, more likely to be men, and had longer disease duration. Early and later users had similar baseline mean HbA1c levels. For early versus later users, respectively, baseline-adjusted mean (95% confidence interval [CI]) reductions were 1.54% (-1.65, -1.44) versus 1.02% (-1.08, -0.97) in HbA1c, 3.31% (-4.37, -2.25) versus 4.06% (-5.05, -3.07) in weight, and 2.50 mm Hg (-3.89, -1.11) versus 2.84 mm Hg (-3.67, -2.01) in SBP. Early versus later use was associated with a greater likelihood of adjusted HbA1c reduction of ≥1% (odds ratio: 1.68, 95% CI: 1.15-2.45).

CONCLUSIONS

Glycaemic benefits were greater with early versus later dapagliflozin intensification. These results support broader and earlier dapagliflozin use.

Concordance of hospitalizations between Clinical Practice Research Datalink and linked Hospital Episode Statistics among patients treated with oral antidiabetic therapies

PURPOSE

The ability of the Clinical Practice Research Datalink (CPRD) to ascertain all-cause hospitalizations remains unknown. We determined the proportion of hospitalizations in CPRD that were also recorded in Hospital Episode Statistics (HES), and vice versa, among patients initiating oral antidiabetic (OAD) therapy.

METHODS

We conducted a retrospective cohort study from October 2009 to September 2012 among OAD-treated patients registered with general practitioners who contribute to CPRD and consent to HES linkage. In CPRD, we identified initial hospitalizations for each calendar year by an Inpatient Referral, Consultation Type code, or Read code indicating an inpatient episode and determined if an admission date was recorded in HES within ±30 days. We then identified initial HES admission dates and determined if a hospitalization was documented in CPRD within ±30 days. Sensitivity analyses were conducted utilizing HES discharge, rather than admission, dates.

RESULTS

Among 8574 OAD-treated HES-linked patients in CPRD, 6574 initial hospitalizations across the study period were identified in CPRD, and 5188 (78.9% [95% CI, 77.9%-79.9%]) were confirmed by a HES admission date within ±30 days (median difference, ±3 days [IQR, 1-7 days]). Among 8609 initial hospital admissions in HES, 4803 (55.7% [95% CI, 54.7%-56.8%]) hospitalizations were recorded in CPRD within ±30 days (median difference, ±4 days [IQR, 1-9 days]). Similar results were observed using HES discharge dates.

CONCLUSION

A substantial minority of patient-level hospitalization data are nonconcordant between HES and CPRD. Pharmacoepidemiologic studies within CPRD that seek to identify hospitalizations should consider linkage with HES to ensure adequate ascertainment of inpatient events.

Impact of increased influenza vaccination in 2-3-year-old children on disease burden within the general population: A Bayesian model-based approach

Introduction

During the 2013–2014 influenza season, Public Health England extended routine influenza vaccination to all 2- and 3-year-old children in England. To estimate the impact of this change in policy on influenza-related morbidity and mortality, we developed a disease transmission and surveillance model informed by real-world data.

Methods

We combined real-world and literature data sources to construct a model of influenza transmission and surveillance in England. Data were obtained for four influenza seasons, starting with the 2010–2011 season. Bayesian inference was used to estimate model parameters on a season-by-season basis to assess the impact of targeting 2- and 3-year-old children for influenza vaccination. This provided the basis for the construction of counterfactual scenarios comparing vaccination rates of ~2% and ~35% in the 2- and 3- year-old population to estimate reductions in general practitioner (GP) influenza-like-illness (ILI) consultations, respiratory hospitalizations and deaths in the overall population.

Results

Our model was able to replicate the main patterns of influenza across the four seasons as observed through laboratory surveillance data. Targeting 2- and 3-year-old children for influenza vaccination resulted in reductions in the general population of between 6.2–9.9% in influenza-attributable GP ILI consultations, 6.1–10.7% in influenza-attributable respiratory hospitalizations, and 5.7–9.4% in influenza-attributable deaths. The decrease in influenza-attributable ILI consultations represents a reduction of between 4.5% and 7.3% across all ILI consultations. The reduction in influenza-attributable respiratory hospitalizations represents a reduction of between 1.2% and 2.3% across all respiratory hospitalizations. Reductions in influenza-attributable respiratory deaths represent a reduction of between 0.9% and 2.4% in overall respiratory deaths.

Conclusion

This study has provided evidence that extending routine influenza vaccination to all healthy children aged 2 and 3 years old leads to benefits in terms of reduced utilization of healthcare resources and fewer respiratory health outcomes and deaths.

Weight change and healthcare resource use in English patients with type 2 diabetes mellitus initiating a new diabetes medication class

AIMS

The aim of this study was to investigate the association between weight change and healthcare resource use (HCRU) and costs in English primary care patients with type 2 diabetes mellitus (T2DM) initiating treatment with a new diabetes medication class.

METHODS

Patients diagnosed with T2DM initiating a new diabetes medication class (first-line, switch or add-on treatment) were selected from Clinical Practice Research Datalink. Weight change (index date) was measured 6 months after initiating new treatment. HCRU was derived up to 1 year after index. Adjusted analyses evaluated the association between weight change and HCRU and costs (GBP, 2013 prices).

RESULTS

Of 9031 patients, about half (n = 4901) experienced < 3% weight change (weight neutral); the proportions gaining or losing weight were similar. Compared with the weight neutral group, weight gain was associated with significantly increased total costs within a year (3.0-5.4% weight gain: £58.9; p = 0.01, ≥ 5.5% weight gain: £52.9; p = 0.04) and diabetes primary care costs (3.0-5.4% weight gain: £29.2; p < 0.001, ≥ 5.5% weight gain: £34.2; p < 0.001). This included increased rates of prescribing drugs for diabetes and, in ≥ 5.5% weight gain, increased primary care contacts. A ≥ 5.5% weight loss was associated with increased hospital admissions (odds ratio = 1.4; p < 0.0001) and total costs (£126.3; p < 0.001).

CONCLUSION

Weight gain after initiating a new glucose-lowering medication is associated with increased prescribing and contact with primary care clinicians, with increased costs in primary care and total spending. This study supports that weight gain in diabetes is associated with increased healthcare costs.

Generalisability of The Health Improvement Network (THIN) database: demographics, chronic disease prevalence and mortality rates

INTRODUCTION

The degree of generalisability of patient databases to the general population is important for interpreting database research. This report describes the representativeness of The Health Improvement Network (THIN), a UK primary care database, of the UK population.

METHODS

Demographics, deprivation (Townsend), Quality and Outcomes Framework (QOF) condition prevalence and deaths from THIN were compared with national statistical and QOF 2006/2007 data.

RESULTS

Demographics were similar although THIN contained fewer people aged under 25 years. Condition prevalence was comparable, e.g. 3.5% diabetes prevalence in THIN, 3.7% nationally. More THIN patients lived in the most affluent areas (23.5% in THIN, 20% nationally). Between 1990 and 2009, standardised mortality ratio ranged from 0.81 (95% CI: 0.39-1.49; 1990) to 0.93 (95% CI: 0.48-1.64; 1995). Adjusting for demographics/deprivation, the 2006 THIN death rate was 9.08/1000 population close to the national death rate of 9.4/1000 population.

CONCLUSION

THIN is generalisable to the UK for demographics, major condition prevalence and death rates adjusted for demographics and deprivation.

A retrospective database study of insulin initiation in patients with Type 2 diabetes in UK primary care

AIMS

This study characterized UK primary care patients with Type 2 diabetes who initiated insulin treatment, and described the initial insulin regimens used, overall metabolic changes and health-care resource usage.

METHODS

A retrospective cohort study was performed using quality-checked patient data from The Health Improvement Network database. Eligible patients who initiated insulin for the first time between 2004 and 2006 were grouped into four cohorts according to the type of insulin regimen initiated. Data on patient characteristics, metabolic and clinical outcomes and health-care resource use were collected at baseline and during 6 months of follow-up.

RESULTS

In total, 4045 eligible adults [2269 male, 1776 female; mean age 62.6 ± 13.3 years; mean baseline HbA(1c) 82 ± 22 mmol/mol (9.6% ± 2.0%)] initiated insulin. Approximately half (52.4%) initiated insulin as basal insulin only, 41.6% as premixed only, 4.0% as basal-bolus and 2.1% as prandial insulin only. Among patients with ≥ 180 days follow-up (n=3815), the initial insulin regimen was not changed during follow-up in 75.1% of patients, while 13.7% discontinued, 7.0% switched and 4.7% intensified insulin therapy. The mean change in HbA(1c) was -14 mmol/mol (-1.3%, n=2881), with 17.3% of patients achieving an HbA(1c) of <53 mmol/mol (7%, n=3024). The mean weight change was +0.9 kg (n=2345).

CONCLUSIONS

Basal and premixed insulin were the most common types of insulin initiated and in most patients no changes were made to the initial regimen over 6 months. However, few patients achieved glycemic control targets.

Optimization of insulin therapy in patients with type 2 diabetes mellitus: beyond basal insulin

AIMS

To describe patients with Type 2 diabetes mellitus treated with basal insulin, with or without oral antidiabetics in UK primary care, and evaluate insulin treatment patterns and factors explaining changes in therapy.

METHODS

Retrospective analysis of patients with Type 2 diabetes within The Health Improvement Network UK primary care database. Patients receiving basal insulin between January and June 2006 were followed until July 2009.

RESULTS

Analysis included 3185 patients, mean age 65.6 years [standard deviation (SD) 12.4], 50.9% men, median diabetes duration 9.6 years, median basal insulin use 1.3 years, 86.5% had received oral antidiabetics in the previous 12 months. Mean follow-up was 2.9 years (SD 1.0), 59.8% patients maintained basal insulin throughout follow-up with a mean HbA(1C) of 69 mmol/mol (SD 19; 8.4%, SD 1.7) at baseline and 65 mmol/mol (SD 17; 8.1%, SD 1.6) during follow-up. During follow-up, 6.9% of patients discontinued, 19.3% intensified with and 14.1% switched to prandial or premixed insulin. Patients who intensified (prandial) had a mean HbA(1c) of 77 mmol/mol (SD 18; 9.2%, SD 1.6) before change and a mean HbA(1c) of 71 mmol/mol (SD 21; 8.6%, SD 2.0) at the end of the study. Those switching to premixed insulin had a mean HbA(1c) of 80 mmol/mol (SD 18; 9.5%, SD 1.7) before change and a mean HbA(1c) of 69 mmol/mol (SD 17; 8.5%, SD 1.5) at the end of the study. Increasing HbA(1c) and longer diabetes duration explained intensification and switch.

CONCLUSIONS

The majority of patients had HbA(1c) above the 53 mmol/mol (< 7%) target at baseline and post-intensification/switch. The HbA(1c) levels were reduced by intensification/switch suggesting that insulin changes did have some impact. Most patients did not change insulin treatment despite having higher than recommended HbA(1c) levels. Reasons for not changing treatment in face of unsatisfactory clinical outcomes are unclear. Further research is warranted to explore barriers towards therapy change.

Evaluation of varenicline as an aid to smoking cessation in UK general practice - a THIN database study

OBJECTIVES

Varenicline is a licensed smoking cessation medication in the EU, USA and many other countries worldwide. This study was designed to assess its effectiveness in a UK general practice setting.

METHODS

The main outcome measure was the rate of smoking cessation, defined as the seven-day point prevalence after six months from starting varenicline. Varenicline users were identified from records in The Health Improvement Network (THIN) database. A questionnaire on smoking cessation was sent to patients who commenced treatment close to the selection date (six months prior to the date of questionnaire dispatch).

RESULTS

The response rate was 26.4%: 193 responses were received. Ninety percent had previously attempted to stop smoking and 87.4% had used nicotine replacement therapy during the previous attempt to stop smoking. The overall smoking cessation rate was 49.5%. There was a strong association between the duration of varenicline treatment and smoking cessation. Patients who reported using varenicline for 9-12 weeks were 11 times more likely to stop smoking than those who completed less than two weeks of treatment. There was some evidence that patients with a longer history of smoking were less likely to stop. No association was observed between smoking cessation and: previous number of cigarettes smoked per day; number of previous attempts to stop smoking; or motivations for stopping.

CONCLUSIONS

Varenicline appeared to be a useful pharmacological aid to smoking cessation in a general practice setting. The observed effectiveness was similar to the efficacy estimates from previously reported clinical trials. However, the response rate was lower than expected and responders tended to be older, more likely to suffer from chronic obstructive pulmonary disease and to live in more affluent areas than non-responders. Responses were self-reported and not clinically validated therefore recall bias may be an issue.

Prescribing trends and drug budget impact of the ARBs in the UK

OBJECTIVES

Angiotensin II receptor blockers (ARBs) were introduced into the UK antihypertensive drug market at a premium price relative to other antihypertensives during a period of evolving evidence about hypertension treatment. This study aimed to determine the UK antihypertensive drug budget impact as the first ARB market launched in December 1994 and what proportion of the increase was directly attributable to ARBs.

METHODS

Prescriptions for oral antihypertensives were identified from The Health Improvement Network database. Drug prices were based on the Chemist & Druggist January 2005 pricelist estimating real expenditure growth. Expenditure increases were disaggregated into the number of patients receiving antihypertensive drug prescriptions, the number of antihypertensive prescriptions per patient treated, and the average drug expenditure per antihypertensive prescription.

RESULTS

The annual ARB prescription frequency increased from 0.04% in 1995 to 6.57% in 2004. Expenditure for antihypertensive drugs was estimated at pound465,862,416 in 1995 and pound1,458,268,104 in 2004 (2005 values), reflecting a 213% real rate of increase. Use of ARBs accounted for only 9.3% (range: 5.8%-12.5%) of the average drug expenditure. Treatment prevalence rose from 11.30% in 1995 to 16.90% in 2004, while the average number of antihypertensive drug prescriptions per patient increased from 9.34 to 13.46 per year. The average expenditure per antihypertensive drug prescription increased over time reflecting a product shift toward more expensive therapies.

CONCLUSIONS

ARBs accounted for only 9.3% of the 213% increase in antihypertensive drug expenditure after their introduction. A substantial portion of the impact reflected increases in treatment prevalence and in the number of prescriptions per patient.

The importance of defining periods of complete mortality reporting for research using automated data from primary care

PURPOSE

To define periods of acceptable mortality reporting in primary care and to demonstrate through examples the implication for research using automated medical data.

METHODS

Annual death counts were obtained for each primary care practice participating in The Health Improvement Network "THIN" (UK). Expected counts were calculated from national death rates, accounting for the practice's age/sex structure. The standardized mortality ratio (SMR) was calculated with 95% confidence intervals (CI). A visual review process was undertaken to assign the year from which the practice had acceptable mortality reporting (AMR). The process involved reviewer pairs who were blinded to each other's decisions. Patterns of death reporting were checked. The AMR year was applied as a filter to THIN data to assess its impact on the SMR.

RESULTS

For most practices the SMR was relatively stable and the AMR year was easily identified with 86% agreement between the blinded reviewer pairs. Applying the AMR to THIN removed under-reporting of death. However, the total computerized follow-up reduced from 37 to 32 million patient-years. Problematic death recording patterns included some practices keeping only live patient records when converting their software systems thereby creating 'immortal periods' prior to this moment, and peaks occurring when practices updated the vital status of their patients' records.

CONCLUSIONS

This is the first time that an external standard has been used to assess completeness of mortality in automated primary care data. The resulting AMR year provides a natural filter for research and avoids biases associated with 'immortal periods', record updating and under-reporting.

Comparing cost-effectiveness analyses of anti-hypertensive drug therapy for decision making: mission impossible?

The purpose of this literature review was to compare the methodology used in the most recently published cost-effectiveness studies of antihypertensive treatments, and to identify methodological strengths and weaknesses that indicate the study's potential as a useful, decision-making tool. Based on the results of a search of several databases, spanning the years 1995 to 2000, 10 cost-effectiveness studies were identified. Although the majority of the studies reported their cost-effectiveness ratio in "costs per year of life gained," the studies also considered a varying range of components including additional end points. The methodology used to measure effectiveness, the cost variables included, and the characteristics of the patient population varied significantly across studies. Due to this lack of conformity, it would be difficult, if not impossible, to compare the results and draw conclusions about the relative cost-effectiveness of different types of antihypertensive drug therapies. This lack of uniform comparison across studies is likely to draw criticism from both the clinical and health-care decision-making communities. Future studies within this field should be thorough and useful for decision making. It is suggested that short-term outcomes should include systolic and diastolic blood pressure measurements and long-term outcomes should include end points such as myocardial infarction, stroke, congestive heart failure and renal events. Other positive outcomes such as a more favorable side-effect profile, should be used to enhance the primary outcomes. Additionally, when subpopulations are considered in submodels, studies should address the issue of generalizability. Cost calculations should be transparent and related to the perspective of the study. Modeling the cost-effectiveness of a drug may be an acceptable method provided that data sources and assumptions are valid and transparent.