Assessment of Unmet Clinical Need in Type 2 Diabetic Patients on Conventional Therapy in the UK

Psychological interventions to improve self-management of type 1 and type 2 diabetes: a systematic review

BACKGROUND

For people with diabetes mellitus to achieve optimal glycaemic control, motivation to perform self-management is important. The research team wanted to determine whether or not psychological interventions are clinically effective and cost-effective in increasing self-management and improving glycaemic control.

OBJECTIVES

The first objective was to determine the clinical effectiveness of psychological interventions for people with type 1 diabetes mellitus and people with type 2 diabetes mellitus so that they have improved (1) glycated haemoglobin levels, (2) diabetes self-management and (3) quality of life, and fewer depressive symptoms. The second objective was to determine the cost-effectiveness of psychological interventions.

DATA SOURCES

The following databases were accessed (searches took place between 2003 and 2016): MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, PsycINFO, EMBASE, Cochrane Controlled Trials Register, Web of Science, and Dissertation Abstracts International. Diabetes conference abstracts, reference lists of included studies and Clinicaltrials.gov trial registry were also searched.

REVIEW METHODS

Systematic review, aggregate meta-analysis, network meta-analysis, individual patient data meta-analysis and cost-effectiveness modelling were all used. Risk of bias of randomised and non-randomised controlled trials was assessed using the Cochrane Handbook (Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ 2011;343:d5928).

DESIGN

Systematic review, meta-analysis, cost-effectiveness analysis and patient and public consultation were all used.

SETTING

Settings in primary or secondary care were included.

PARTICIPANTS

Adolescents and children with type 1 diabetes mellitus and adults with types 1 and 2 diabetes mellitus were included.

INTERVENTIONS

The interventions used were psychological treatments, including and not restricted to cognitive-behavioural therapy, counselling, family therapy and psychotherapy.

MAIN OUTCOME MEASURES

Glycated haemoglobin levels, self-management behaviours, body mass index, blood pressure levels, depressive symptoms and quality of life were all used as outcome measures.

RESULTS

A total of 96 studies were included in the systematic review (n = 18,659 participants). In random-effects meta-analysis, data on glycated haemoglobin levels were available for seven studies conducted in adults with type 1 diabetes mellitus (n = 851 participants) that demonstrated a pooled mean difference of -0.13 (95% confidence interval -0.33 to 0.07), a non-significant decrease in favour of psychological treatment; 18 studies conducted in adolescents/children with type 1 diabetes mellitus (n = 2583 participants) that demonstrated a pooled mean difference of 0.00 (95% confidence interval -0.18 to 0.18), indicating no change; and 49 studies conducted in adults with type 2 diabetes mellitus (n = 12,009 participants) that demonstrated a pooled mean difference of -0.21 (95% confidence interval -0.31 to -0.10), equivalent to reduction in glycated haemoglobin levels of -0.33% or ≈3.5 mmol/mol. For type 2 diabetes mellitus, there was evidence that psychological interventions improved dietary behaviour and quality of life but not blood pressure, body mass index or depressive symptoms. The results of the network meta-analysis, which considers direct and indirect effects of multiple treatment comparisons, suggest that, for adults with type 1 diabetes mellitus (7 studies; 968 participants), attention control and cognitive-behavioural therapy are clinically effective and cognitive-behavioural therapy is cost-effective. For adults with type 2 diabetes mellitus (49 studies; 12,409 participants), cognitive-behavioural therapy and counselling are effective and cognitive-behavioural therapy is potentially cost-effective. The results of the individual patient data meta-analysis for adolescents/children with type 1 diabetes mellitus (9 studies; 1392 participants) suggest that there were main effects for age and diabetes duration. For adults with type 2 diabetes mellitus (19 studies; 3639 participants), baseline glycated haemoglobin levels moderated treatment outcome.

LIMITATIONS

Aggregate meta-analysis was limited to glycaemic control for type 1 diabetes mellitus. It was not possible to model cost-effectiveness for adolescents/children with type 1 diabetes mellitus and modelling for type 2 diabetes mellitus involved substantial uncertainty. The individual patient data meta-analysis included only 40-50% of studies.

CONCLUSIONS

This review suggests that psychological treatments offer minimal clinical benefit in improving glycated haemoglobin levels for adults with type 2 diabetes mellitus. However, there was no evidence of benefit compared with control interventions in improving glycated haemoglobin levels for people with type 1 diabetes mellitus.

FUTURE WORK

Future work should consider the competency of the interventionists delivering a therapy and psychological approaches that are matched to a person and their life course.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016033619.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 28. See the NIHR Journals Library website for further project information.

Evaluating glycaemic control in patients poorly controlled on oral antidiabetic drugs in real-world setting: Results from assessing the Appropriate Timing of Type 2 diAbetes INtensification (ATTAIN)

INTRODUCTION

Many patients with type 2 diabetes mellitus (DM) fail to achieve glycaemic control despite recommended treatment strategies to reduce glycated haemoglobin (HbA1c). This real-world retrospective cohort study compared HbA1c change and treatment patterns between those intensifying and not intensifying therapy with oral antidiabetic drugs (OADs).

MATERIALS AND METHODS

Patients suboptimally controlled on OADs (>58 mmol/mol [>7.5%] or >64 mmol/mol [>8.0%] for high risk, index 1) were included from IQVIA Medical Research Data. Intensifiers within 12 months of index 1 were matched (1:1) to nonintensifiers. Primary outcomes were HbA1c change and proportion of participants achieving HbA1c targets 6 and 12 months post-index 2 (date of intensification [intensifiers] or pseudodate [nonintensifiers]). Therapy adherence was also assessed.

RESULTS

A total of 10 832 participants (5539 intensifiers and 5293 nonintensifiers) were included. Mean HbA1c decrease from baseline to 6 months was -1.13% (intensifiers) vs -0.75% (nonintensifiers), with no substantial further change at 12 months. Cox proportional hazards (PH) analysis suggested a nearly 20% greater chance of target achievement at 6 months for intensifiers vs nonintensifiers (hazard ratio [HR]: 0.79 [95% confidence interval [CI]: 0.73-0.86]), which was similar at 12 months (HR: 0.80 [95% CI: 0.74-0.86]). Intensifiers tended towards greater adherence to baseline therapy (90% [standard deviation (SD): 14.9] vs nonintensifiers 87% [SD: 16.0]), which decreased following intensification.

CONCLUSIONS

Significant reductions in HbA1c were evident at 6 months and were greater in intensifiers vs nonintensifiers. Little additional clinical benefit was seen 12 months postintensification. Despite good treatment adherence, many participants failed to achieve target HbA1c; actions beyond improved adherence are needed to improve suboptimal HbA1c.

Insights for Care: The Healthcare Utilisation and Cost Impact of Managing Type 2 Diabetes-Associated Microvascular Complications

INTRODUCTION

The increasing prevalence of type 2 diabetes (T2DM) in the UK imposes a significant burden on the National Health Service (NHS). Despite the availability of effective treatments, the loss of glycaemic control over time results in significant comorbidities, including nephropathy, neuropathy and retinopathy. The cost of treating these microvascular complications has not been well documented, and this study aimed to provide an accurate assessment of the healthcare resource utilisation (HCRU) associated with managing T2DM and its complications.

METHODS

This retrospective cohort study utilised electronic medical records from patients with T2DM from the Heart of England Foundation Trust (HEFT), which captures data from patients using secondary care services. Patients were diagnosed with microvascular complications based on ICD-10 or OPCS codes. HCRU over a 2-year period was based on NHS Tariffs for healthcare services for inpatient, accident and emergency, and dialysis clinic usage.

RESULTS

The study cohort comprised 26,629 patients with T2DM who used HEFT services during the study period, 22.6%, 20.8% and 3.1% of whom had comorbid nephropathy, retinopathy or neuropathy, respectively. While the prevalence of diabetes in the overall HEFT population was reported to be 7% in 2012, diabetes and its associated complications accounted for more than 30% of secondary care costs. Furthermore, while patients with diabetes represent only 17% of HEFT inpatients, they account for more than 20% of service usage. The economic burden of microvascular complications increased substantially with the severity of the condition, with the overall cost exceeding £70 million over the 2-year period.

CONCLUSION

This study of patients with T2DM in a typical secondary care provider in the UK showed that avoiding the progression of microvascular complications could provide substantial cost savings through targeted interventions that improve outcomes and lower resource use.

FUNDING

Merck Sharp & Dohme Limited.

The New Paradigms in Clinical Research: From Early Access Programs to the Novel Therapeutic Approaches for Unmet Medical Needs

Despite several innovative medicines gaining worldwide approval in recent years, there are still therapeutic areas for which unsatisfied therapeutic needs persist. For example, high unmet clinical need was observed in patients diagnosed with type 2 diabetes mellitus and hemophilia, as well as in specific age groups, such as the pediatric population. Given the urgent need to improve the therapy of clinical conditions for which unmet clinical need is established, clinical testing, and approval of new medicines are increasingly being carried out through accelerated authorization procedures. Starting from 1992, the Food and Drug Administration and the European Medicines Agency have supported the so-called Early Access Programs (EAPs). Such procedures, which can be based on incomplete clinical data, allow an accelerated marketing authorization for innovative medicines. The growth in pharmaceutical research has also resulted in the development of novel therapeutic approaches, such as biotech drugs and advanced therapy medicinal products, including new monoclonal antibodies for the treatment of asthma, antisense oligonucleotides for the treatment of Duchenne muscular dystrophy and spinal muscular atrophy, and new anticancer drugs that act on genetic biomarkers rather than any specific type of cancer. Even though EAPs and novel therapeutic approaches have brought huge benefits for public health, their implementation is limited by several challenges, including the high risk of safety-related label changes for medicines authorized through the accelerated procedure, the high costs, and the reimbursement and access concerns. In this context, regulatory agencies should provide the best conditions for the implementation of the described new tools.

An empirical tool for estimating the share of unmet need due to healthcare inefficiencies, suboptimal access, and lack of effective technologies

Background

Although there has been growing attention to the measurement of unmet need, which is the overall epidemiological burden of disease, current measures ignore the burden that could be eliminated from technological advances or more effective use of current technologies.

Methods

We developed a conceptual framework and empirical tool that separates unmet need from met need and subcategorizes the causes of unmet need into suboptimal access to and ineffective use of current technologies and lack of current technologies. Statistical models were used to model the relationship between health-related quality of life (HR-QOL) and treatment utilization using data from the National Health and Wellness Survey (NHWS). Predicted HR-QOL was combined with prevalence data from the Global Burden of Disease Study (GBD) to estimate met need and the causes of unmet need due to morbidity in the US and EU5 for five diseases: rheumatoid arthritis, breast cancer, Parkinson’s disease, hepatitis C, and chronic obstructive pulmonary disease (COPD).

Results

HR-QOL was positively correlated with adherence to medication and patient-perceived quality and negatively correlated with financial barriers. Met need was substantial across all disease and regions, although significant unmet need remains. While the majority of unmet need was driven by lack of technologies rather than ineffective use of current technologies, there was considerable variation across diseases and regions. Overall unmet need was largest for COPD, which had the highest prevalence of all diseases in this study.

Conclusion

We developed a methodology that can inform decisions about which diseases to invest in and whether those investments should focus on improving access to currently available technologies or inventing new technologies.

Electronic supplementary material

The online version of this article (10.1186/s12913-019-3914-7) contains supplementary material, which is available to authorized users.

Insights into optimal basal insulin titration in type 2 diabetes: Results of a quantitative survey

AIMS

Basal insulin (BI) treatment initiation and dose titration in type 2 diabetes (T2DM) are often delayed. Such "clinical inertia" results in poor glycaemic control and high risk of long-term complications. This survey aimed to determine healthcare professional (HCP) and patient attitudes to BI initiation and titration.

METHODS

An online survey (July-August 2015) including HCPs and patients with T2DM in the USA, France and Germany. Patients were ≥18 years old and had been on BI for 6 to 36 months, or discontinued BI within the previous 12 months.

RESULTS

Participants comprised 386 HCPs and 318 people with T2DM. While >75% of HCPs reported discussing titration at the initiation visit, only 16% to 28% of patients remembered such discussions, many (32%-42%) were unaware of the need to titrate BI, and only 28% to 39% recalled mention of the time needed to reach glycaemic goals. Most HCPs and patients agreed that more effective support tools to assist BI initiation/titration are needed; patients indicated that provision of such tools would increase confidence in self-titration. HCPs identified fear of hypoglycaemia, failure to titrate in the absence of symptoms, and low patient motivation as important titration barriers. In contrast, patients identified weight gain, the perception that titration meant worsening disease, frustration over the time to reach HbA1c goals and fear of hypoglycaemia as major factors.

CONCLUSION

A disconnect exists between HCP- and patient-perceived barriers to effective BI titration. To optimize titration, strategies should be targeted to improve HCP-patient communication, and provide support and educational tools.

Costs and Treatment Pathways for Type 2 Diabetes in the UK: A Mastermind Cohort Study

INTRODUCTION

Medication therapy for type 2 diabetes has become increasingly complex, and there are few reliable data on the current state of clinical practice. We report treatment pathways and associated costs of medication therapy for people with type 2 diabetes in the UK, their variability and changes over time.

METHODS

Prescription and biomarker data for 7159 people with type 2 diabetes were extracted from the GoDARTS cohort study, covering the period 1989-2013. Average follow-up was 10 years. Individuals were prescribed on average 2.4 (SD: 1.2) drugs with average annual costs of £241. We calculated summary statistics for first- and second-line therapies. Linear regression models were used to estimate associations between therapy characteristics and baseline patient characteristics.

RESULTS

Average time from diagnosis to first prescription was 3 years (SD: 4.0 years). Almost all first-line therapy (98%) was monotherapy, with average annual cost of £83 (SD: £204) for 3.8 (SD: 3.5) years. Second-line therapy was initiated in 73% of all individuals, at an average annual cost of £219 (SD: £305). Therapies involving insulin were markedly more expensive than other common therapies. Baseline HbA1c was unrelated to future therapy costs, but higher average HbA1c levels over time were associated with higher costs.

CONCLUSIONS

Medication therapy has undergone substantial changes during the period covered in this study. For example, therapy is initiated earlier and is less expensive than in the past. The data provided in this study will prove useful for future modelling studies, e.g. of stratified treatment approaches.

Glycaemic control and hypoglycaemia burden in patients with type 2 diabetes initiating basal insulin in Europe and the USA

AIMS

To evaluate short- and long-term glycaemic control and hypoglycaemia incidence in insulin-naïve patients ≥30 years of age with type 2 diabetes (T2DM) initiating basal insulin (BI) with or without oral anti-hyperglycaemic drugs (OADs).

METHODS

This was an observational, retrospective longitudinal analysis of electronic medical records from 5 European countries and the USA. A multivariable logistic regression model assessed baseline and short-term (0-3 months post BI initiation) factors associated with long-term (3-24 months) glycaemic control and hypoglycaemia.

RESULTS

Overall, 40 627 patients were included; 20.9% and 27.8% achieved the general HbA1c target of ≤7% at 3 and 24 months post BI initiation, respectively. Failure to achieve HbA1c ≤7% at 3 months was associated with increased risk of failing to achieve target at 24 months (odds ratio [OR], 3.70 [95% CI, 3.41-4.00]). Over 24 months, 8.9% of patients experienced a recorded hypoglycaemic event. Hypoglycaemia during the initial 3-month period was associated with longer-term risk of these events over the ensuing 3 to 24 months (OR, 5.71 [95% CI, 4.67-6.99]).

CONCLUSIONS

Initiating BI with or without OADs is associated with short- and long-term suboptimal glycaemic control; the majority of patients fail to achieve HbA1c target ≤7% in the first 3 months, or after 2 years of BI treatment. Treatment response and hypoglycaemia incidence by 3 months post BI initiation are associated with longer-term glycaemic control and hypoglycaemic risk, respectively. These results support the need for early anti-hyperglycaemic interventions that more effectively control blood glucose levels without increasing the risk of hypoglycaemia.

An alternative approach to modelling HbA1c trajectories in patients with type 2 diabetes mellitus

AIMS

Time-dependent HbA1c trajectories in health economic models of type 2 diabetes mellitus (T2DM) are typically informed by the UK Prospective Diabetes Study (UKPDS). However, this approach may not accurately predict HbA1c progression in patients who do not conform to the demographic profile of the original UKPDS cohort. This study aimed to develop an alternative mathematical model (MM) to simulate HbA1c progression in T2DM.

MATERIALS AND METHODS

A systematic literature review identified studies, published between 2005 and 2015, that reported HbA1c in adult T2DM patients over a minimum duration of 18 months. Pooled data from eligible studies were used to develop an alternative MM equation for HbA1c progression, which was then contrasted with the UKPDS 68 progression equation in illustrative scenarios.

RESULTS

A total of 68 studies were eligible for data extraction (mean follow-up time 4.1 years). HbA1c progression was highly heterogeneous across studies, varying with baseline HbA1c, treatment group and patient age. The MM equation was fitted with parameters for mean baseline HbA1c (8.3%), initial change in HbA1c (-0.62%) and upper quartile of maximum observed HbA1c (9.3%). Differences in HbA1c trajectories between the MM and UKPDS approaches altered the timing of therapy escalation in illustrative scenarios.

CONCLUSIONS

The MM represents an alternative approach to simulate HbA1c trajectories in T2DM models, as UKPDS data may not adequately reflect the heterogeneity of HbA1c profiles observed in clinical studies. However, the choice of approach should ultimately be determined by the characteristics of individual patients under consideration and the clinical face validity of the modelled trajectories.