A Real-World Observational Study of Time to Treatment Intensification Among Elderly Patients with Inadequately Controlled Type 2 Diabetes Mellitus

A machine learning model to predict therapeutic inertia in type 2 diabetes using electronic health record data

OBJECTIVE

To estimate the therapeutic inertia prevalence for patients with type 2 diabetes, develop and validate a machine learning model predicting therapeutic inertia, and determine the added predictive value of area-level social determinants of health (SDOH).

METHODS

This prognostic study with a retrospective cohort design used OneFlorida data (linked electronic health records (EHRs) from 1240 practices/clinics in Florida). The study cohort included adults (aged ≥ 18) with type 2 diabetes, HbA1C ≥ 7% (53 mmol/mol), ≥one ambulatory visit, and ≥one antihyperglycemic medication prescribed (excluded patients prescribed insulin before HbA1C). The outcome was therapeutic inertia, defined as absence of treatment intensification within six months after HbA1C ≥ 7% (53 mmol/mol). The predictors were patient, provider, and healthcare system factors. Machine learning methods included gradient boosting machines (GBM), random forests (RF), elastic net (EN), and least absolute shrinkage and selection operator (LASSO). The DeLong test compared the discriminative ability (represented by C-statistics) between models.

RESULTS

The cohort included 31,087 patients with type 2 diabetes (mean age = 58.89 (SD = 13.27) years, 50.50% male, 58.89% White). The therapeutic inertia prevalence was 39.80% among the 68,445 records. GBM outperformed (C-statistic from testing sample = 0.84, 95% CI = 0.83-0.84) RF (C-statistic = 0.80, 95% CI = 0.79-0.80), EN (C-statistic = 0.80, 95% CI = 0.80-0.81), and LASSO (C-statistic = 0.80, 95% CI = 0.80-0.81), p < 0.05. Area-level SDOH significantly increased the discriminative ability versus models without SDOH (C-statistic for GBM = 0.84, 95% CI = 0.84-0.85 vs. 0.84, 95% CI = 0.83-0.84), p < 0.05.

CONCLUSIONS

Using EHRs of patients with type 2 diabetes from a large state, machine learning predicted therapeutic inertia (prevalence = 40%). The model's ability to predict patients at high risk of therapeutic inertia is clinically applicable to diabetes care.

Metformin dosage patterns in type 2 diabetes patients in a real-world setting in the United States

AIM

To examine metformin dosage patterns among adults with type 2 diabetes in an integrated healthcare system in the US.

METHODS

Using electronic medical records, the proportions of patients receiving different initial metformin doses were reported. Proportion of patients receiving ≥1500 mg metformin daily at initiation or within six months after initiation and the associated sociodemographic and clincal factors were examined.

RESULTS

The cohort included 715 patients (52.6% female, 64.1% white, and mean age = 57.0 ± 12.7 years). Of these, 31.3% received an initial daily metformin dose of <850 mg, 46.9% received 850-1499 mg, and 21.8% received ≥1500 mg and 244 (34.1%) patients received ≥1500 mg metformin daily at initiation or within six months after initiation. Patients aged 65-79 years (vs. those aged <50 years) and blacks (vs. whites) were less likely and Hispanics (vs. whites) and patients with higher HbA1c before metformin initiation were more likely to receive ≥1500 mg metformin daily at initiation or within six months after initiation.

CONCLUSIONS

Study findings suggest a need for efforts to maximize the proportion of eligible patients receiving a recommended metformin dose. Factors impacting metformin dosage identified in the study could be a useful guidance.

The impact of phenotype, ethnicity and genotype on progression of type 2 diabetes mellitus

AIM

To conduct a comprehensive review of studies of glycaemic deterioration in type 2 diabetes and identify the major factors influencing progression.

METHODS

We conducted a systematic literature search with terms linked to type 2 diabetes progression. All the included studies were summarized based upon the factors associated with diabetes progression and how the diabetes progression was defined.

RESULTS

Our search yielded 2785 articles; based on title, abstract and full-text review, we included 61 studies in the review. We identified seven criteria for diabetes progression: 'Initiation of insulin', 'Initiation of oral antidiabetic drug', 'treatment intensification', 'antidiabetic therapy failure', 'glycaemic deterioration', 'decline in beta-cell function' and 'change in insulin dose'. The determinants of diabetes progression were grouped into phenotypic, ethnicity and genotypic factors. Younger age, poorer glycaemia and higher body mass index at diabetes diagnosis were the main phenotypic factors associated with rapid progression. The effect of genotypic factors on progression was assessed using polygenic risk scores (PRS); a PRS constructed from the genetic variants linked to insulin resistance was associated with rapid glycaemic deterioration. The evidence of impact of ethnicity on progression was inconclusive due to the small number of multi-ethnic studies.

CONCLUSION

We have identified the major determinants of diabetes progression-younger age, higher BMI, higher HbA1c and genetic insulin resistance. The impact of ethnicity is uncertain; there is a clear need for more large-scale studies of diabetes progression in different ethnic groups.

Clinical Inertia in Poorly Controlled Type 2 Diabetes Mellitus Patients with Obesity: An Observational Retrospective Study

INTRODUCTION

To evaluate clinical inertia in patients with type 2 diabetes mellitus (T2DM), obesity and poor glycaemic control in routine clinical practice.

METHODS

This was a retrospective, observational study based on the analysis of medical records from the BIG-PAC® database. Subjects who required medical care in 2013 with the following characteristics were enrolled in the study: age ≥ 30 years, diagnosis of T2DM, glycosylated haemoglobin (HbA1c) ≥ 8%, obesity (body mass index [BMI] ≥ 30 kg/m²) and treatment with ≥ 2 oral antidiabetic drugs (OADs). Inertia was evaluated by time (days) to the first intensification during the period while HbA1c levels were ≥ 8% and percentage of patients whose treatment was not intensified at 6 months, 1, 2 and 3 years and the end of follow-up. The minimum length of follow-up was 4 years. Descriptive analyses and Kaplan-Meier survival curves were performed.

RESULTS

A total of 13,824 patients with T2DM receiving ≥ 2 OADs were identified; of these 2709 (19.6%) had HbA1c ≥ 8% and BMI ≥ 30 kg/m², thus fulfilling the inclusion criteria. Of these 2709 patients, the mean age was 65.5 (standard deviation [SD] 12.0) years; 54.9% were male, mean HbA1c level was 9.2% (SD 1.3%); mean BMI was 32.1 (SD 0.9) kg/m²; and mean time from diagnosis was 8.2 (SD 3.0) years. HbA1c remained ≥ 8% for a median of 440 (95% confidence interval [CI] 421-459) days. The median time to first intensification was 456 (95% CI 429-483) days. No intensification had occurred in 77.8, 59.5, 41.5, 28.1 and 22.4% of patients at 6 months, 1, 2, 3 years and the end of follow-up, respectively.

CONCLUSIONS

The patients with T2DM analysed in this study had a mean HbA1c of 9.2% at baseline, and this remained at ≥ 8% for > 1 year. The time to the first treatment intensification was longer than that recommended by guidelines. Treatment was not intensified in a large percentage of patients, with almost 60% of patients not receiving intensification at 1 year of follow-up.

Efficacy and safety of lixisenatide as add-on therapy to basal insulin in older adults with type 2 diabetes in the GetGoal-O Study

BACKGROUND

This study compared the efficacy and safety of lixisenatide with placebo as add-on therapy to basal insulin (BI) in adults aged ≥70 years with type 2 diabetes (T2D), with or without moderate renal insufficiency.

METHODS

This post hoc analysis evaluated data from non-frail patients with T2D inadequately controlled on BI with or without oral antidiabetic drugs (n = 108), randomized to once-daily lixisenatide 20 μg or placebo for 24 weeks (GetGoal-O Study). The primary endpoint was the change in HbA1c from baseline to Week 24. Secondary endpoints included changes from baseline in fasting plasma glucose, 2-hour postprandial plasma glucose (PPG), average seven-point self-monitored plasma glucose (SMPG), area under the curve for SMPG, daily BI dose, body weight, proportion of patients achieving HbA1c > 0.5%, and composite endpoints. Safety outcomes included the incidence of documented symptomatic hypoglycemia (plasma glucose <60 mg/dL) and gastrointestinal treatment-emergent adverse events (TEAEs). Outcomes were also analyzed by the occurrence of moderate renal insufficiency.

RESULTS

Compared with placebo, lixisenatide-treated patients had significantly greater reductions in HbA1c, 2-hour PPG, average seven-point SMPG, and body weight. Documented symptomatic hypoglycemia was approximately two-fold higher in patients treated with placebo than lixisenatide (12.7% vs 5.7%). GI TEAEs occurred more frequently in the lixisenatide- than placebo-treated group (34% vs 9.1%). Moderate renal insufficiency (estimated glomerular filtration rate between ≥30 and <60 mL/min/1.73 m² ) did not negatively affect lixisenatide efficacy or safety. A greater proportion of patients treated with lixisenatide than placebo achieved composite endpoints.

CONCLUSIONS

Add-on therapy with lixisenatide in non-frail patients aged ≥70 years with T2D uncontrolled with BI is effective, safe, and well tolerated and should be considered in this population.

The association between polypharmacy and adverse health consequences in elderly type 2 diabetes mellitus patients; a systematic review and meta-analysis

AIM

To summarize the existing literature concerning the association between polypharmacy and adverse health consequences in elderly patients with type 2 diabetes mellitus.

METHODS

We searched four literature databases (PubMed/Medline, ScienceDirect and Web of Science) through April 2019. We included all studies that addressed the association between polypharmacy and all-cause of mortality, glycemic control, macrovacular complications, hospitalization, potentially inappropriate medicines, drug-drug interactions and fall. A statistical program OpenMeta [Analyst] was used. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated with a random effects model. I² statistics was performed to assess heterogeneity.

RESULTS

Out of sixteen studies, three studies were used for meta-analysis. A statistically significant association was found between polypharmacy and all-cause mortality (OR = 1.622, 95% CI (1.606-1.637) P < 0.001), and myocardial infarction (OR = 1.962, 95% CI (1.942-1.982), P < 0.001. Non-statistically significant association with evidence of moderate heterogeneity was found between polypharmacy and stroke (OR = 1.335; 95% CI (0.532-3.346), P = 0.538, I² = 45%), and hospitalization (OR = 1.723; 95% CI (0.983-3.021), P = 0.057, I² = 57%).

CONCLUSIONS

Pooled risk estimates reveal that polypharmacy is associated with increased all-cause mortality, macrovacular complications and hospitalization using categorical definitions. These findings assert the need for interventions that optimize the balance of benefits and harms in medicines prescribing.

Drug utilization and factors associated with polypharmacy in individuals with diabetes mellitus in Minas Gerais, Brazil

The objective of this study was to evaluate the use of drugs and the factors associated with polypharmacy in patients with diabetes mellitus (DM) in Minas Gerais. Descriptive analysis of drugs in use and logistic regression to estimate the association between socio-demographic and clinical characteristics with polypharmacy were performed. Of the 2619 respondents, 56.5% were in polypharmacy. Drugs for DM, agent in renin-angiotensin system, and diuretics are the most frequently used. Factors such as age, comorbidities and increased access to health services were associated with polypharmacy. It was observed high prevalence of polypharmacy, which requires a suitable care and better quality of drug use in this population.

Treatment Intensification in Type 2 Diabetes: A Real-World Study of 2-OAD Regimens, GLP-1 RAs, or Basal Insulin

INTRODUCTION

Treatment guidelines recommend a stepwise approach to glycemia management in patients with type 2 diabetes (T2D), but this may result in uncontrolled glycated hemoglobin A1c (HbA1c) between steps. This retrospective analysis compared clinical and economic outcomes among patients with uncontrolled T2D initiating two oral antidiabetes drugs (OADs), glucagon-like peptide-1 receptor agonists (GLP-1 RAs), or basal insulin in a real-world setting.

METHODS

Adults with T2D on OAD monotherapy were identified in the MarketScan claims database (2007-2014). Those initiating two OADs (simultaneously or sequentially), GLP-1 RAs, or basal insulin were selected (date of initiation was termed the 'index date'); patients were required to have HbA1c > 7.0% in the 6 months pre-index date. HbA1c was compared from 6 months pre- to 1-year post-index. Annual all-cause healthcare utilization and costs were reported over the 1-year follow-up period.

RESULTS

Data for 6054 patients were analyzed (2-OAD, n = 4442; GLP-1 RA, n = 361; basal insulin, n = 1251). Baseline HbA1c was high in all cohorts, but highest in the basal-insulin cohort. Treatment initiation resulted in reductions in HbA1c in all cohorts, which was generally maintained throughout the follow-up period. Average HbA1c reductions from the 6 months pre- to 1 year post-index date were -1.2% for GLP-1 RA, -1.6% for OADs, and -1.8% for basal insulin. HbA1c < 7.0% at 1 year occurred in 32.6%, 47.5%, and 41.1% of patients, respectively. Annual healthcare costs (mean [SD]) were lowest for OAD (US$10,074 [$22,276]) followed by GLP-1 RA (US$14,052 [$23,829]) and basal insulin (US$18,813 [$37,332]).

CONCLUSION

Despite robust HbA1c lowering following treatment initiation, many patients did not achieve HbA1c < 7.0%. Basal insulin, generally prescribed for patients with high baseline HbA1c, was associated with a large reduction in HbA1c and with higher costs. Therapy intensification at an appropriate time could lead to clinical and economic benefits and should be investigated further.

FUNDING

Sanofi U.S., Inc.

Therapeutic inertia in the treatment of hyperglycaemia in patients with type 2 diabetes: A systematic review

AIMS

Therapeutic inertia, defined as the failure to initiate or intensify therapy in a timely manner according to evidence-based clinical guidelines, is a key reason for uncontrolled hyperglycaemia in patients with type 2 diabetes. The aims of this systematic review were to identify how therapeutic inertia in the management of hyperglycaemia was measured and to assess its extent over the past decade.

MATERIALS AND METHODS

Systematic searches for articles published from January 1, 2004 to August 1, 2016 were conducted in MEDLINE and Embase. Two researchers independently screened all of the titles and abstracts, and the full texts of publications deemed relevant. Data were extracted by a single researcher using a standardized data extraction form.

RESULTS

The final selection for the review included 53 articles. Measurements used to assess therapeutic inertia varied across studies, making comparisons difficult. Data from low- to middle-income countries were scarce. In most studies, the median time to treatment intensification after a glycated haemoglobin (HbA1c) measurement above target was more than 1 year (range 0.3 to >7.2 years). Therapeutic inertia increased as the number of antidiabetic drugs rose and decreased with increasing HbA1c levels. Data were mainly available from Western countries. Diversity of inertia measures precluded meta-analysis.

CONCLUSIONS

Therapeutic inertia in the management of hyperglycaemia in patients with type 2 diabetes is a major concern. This is well documented in Western countries, but corresponding data are urgently needed in low- and middle-income countries, in view of their high prevalence of type 2 diabetes.

Overtreatment and Deintensification of Diabetic Therapy among Medicare Beneficiaries

BACKGROUND

Deintensification of diabetic therapy is often clinically appropriate for older adults, because the benefit of aggressive diabetes treatment declines with age, while the risks increase.

OBJECTIVE

We examined rates of overtreatment and deintensification of therapy for older adults with diabetes, and whether these rates differed by medical, demographic, and socioeconomic characteristics.

DESIGN, SUBJECTS, AND MAIN MEASURES

We analyzed Medicare claims data from 10 states, linked to outpatient laboratory values to identify patients potentially overtreated for diabetes (HbA1c < 6.5% with fills for any diabetes medications beyond metformin, 1/1/2011-6/30/2011). We examined characteristics associated with deintensification for potentially overtreated diabetic patients. We used multinomial logistic regression to examine whether patient characteristics associated with overtreatment of diabetes differed from those associated with undertreatment (i.e. HbA1c > 9.0%).

KEY RESULTS

Of 78,792 Medicare recipients with diabetes, 8560 (10.9%) were potentially overtreated. Overtreatment of diabetes was more common among those who were over 75 years of age and enrolled in Medicaid (p < 0.001), and was less common among Hispanics (p = 0.009). Therapy was deintensified for 14% of overtreated diabetics. Appropriate deintensification of diabetic therapy was more common for patients with six or more chronic conditions, more outpatient visits, or living in urban areas; deintensification was less common for those over age 75. Only 6.9% of Medicare recipients with diabetes were potentially undertreated. Variables associated with overtreatment of diabetes differed from those associated with undertreatment.

CONCLUSIONS

Medicare recipients are more frequently overtreated than undertreated for diabetes. Medicare recipients who are overtreated for diabetes rarely have their regimens deintensified.

Therapeutic inertia in patients treated with two or more antidiabetics in primary care: Factors predicting intensification of treatment

AIMS

To determine the patterns and predictors of treatment intensification in patients with type 2 diabetes on ≥2 non-insulin antidiabetic drugs (NIADs) and inadequate glycaemic control in primary care in Catalonia, Spain.

MATERIAL AND METHODS

This was a retrospective analysis using electronic medical records from patients with HbA1c ≥ 7% and a first prescription for a new NIAD or insulin recorded from January 2010 to December 2014. Therapeutic inertia was defined as no intensification if HbA1c was ≥8% at baseline or during follow-up. Time to first intensification was evaluated by time-to-event analysis, and factors predicting intensification through a competing-risk regression model.

RESULTS

Among 23 678 patients with HbA1c ≥ 7%, 26.2% were censored without treatment intensification after a median follow up of 4.2 years. Among the 12 730 patients in the subgroup with HbA1c ≥ 8% at baseline or during follow-up, therapeutic inertia was present in 18.1% of cases. In the overall cohort, mean HbA1c at initiation of insulin and NIAD were 9.4% ± 1.5% and 8.7% ± 1.3%, respectively. Median time to first intensification was 17.1 months in patients with HbA1c 8.0% to 9.9%, and 10.1 months in those with HbA1c > 10%. Variables strongly associated with intensification were HbA1c values 8.0% to 9.9% (subhazard ratio [SHR], 1.7; 95% CI, 1.65-1.78) and >10% (SHR, 2.5; 95% CI, 2.37-2.68); diabetes duration ≥20 years (SHR, 1.25; 95% CI, 1.11-1.41) and, to a lesser extent, female gender, presence of comorbidities, chronic kidney disease and microvascular complications.

CONCLUSIONS

Intensification was not undertaken in 1 in 5 patients. Both HbA1c thresholds and time until therapy intensification exceeded current recommendations.

Implementation of integrated geriatric care at a German hospital: a case study to understand when and why beneficial outcomes can be achieved

BACKGROUND

Many health systems have implemented integrated care as an alternative approach to health care delivery that is more appropriate for patients with complex, long-term needs. The objective of this article was to analyse the implementation of integrated care at a German geriatric hospital and explore whether the use of a "context-mechanisms-outcomes"-based model provides insights into when and why beneficial outcomes can be achieved.

METHODS

We conducted 15 semi-structured interviews with health professionals employed at the hospital. The data were qualitatively analysed using a "context-mechanisms-outcomes"-based model. Specifically, mechanisms were defined as the different components of the integrated care intervention and categorised according to Wagner's Chronic Care Model (CCM). Context was understood as the setting in which the mechanisms are brought into practice and described by the barriers and facilitators encountered in the implementation process. These were categorised according to the six levels of Grol and Wensing's Implementation Model (IM): innovation, individual professional, patient, social context, organisational context and economic and political context. Outcomes were defined as the effects triggered by mechanisms and context, and categorised according to the six dimensions of quality of care as defined by the World Health Organization, namely effectiveness, efficiency, accessibility, patient-centeredness, equity and safety.

RESULTS

The integrated care intervention consisted of three main components: a specific reimbursement system ("early complex geriatric rehabilitation"), multidisciplinary cooperation, and comprehensive geriatric assessments. The inflexibility of the reimbursement system regarding the obligatory number of treatment sessions contributed to over-, under- and misuse of services. Multidisciplinary cooperation was impeded by a high workload, which contributed to waste in workflows. The comprehensive geriatric assessments were complemented with information provided by family members, which contributed to decreased likelihood of adverse events.

CONCLUSIONS

We recommend an increased focus on trying to understand how intervention components interact with context factors and, combined, lead to positive and/or negative outcomes.