Tolerability and Effectiveness of Exenatide Once Weekly Relative to Basal Insulin Among Type 2 Diabetes Patients of Different Races in Routine Care

Treatment effect heterogeneity following type 2 diabetes treatment with GLP1-receptor agonists and SGLT2-inhibitors: a systematic review

BACKGROUND

A precision medicine approach in type 2 diabetes requires the identification of clinical and biological features that are reproducibly associated with differences in clinical outcomes with specific anti-hyperglycaemic therapies. Robust evidence of such treatment effect heterogeneity could support more individualized clinical decisions on optimal type 2 diabetes therapy.

METHODS

We performed a pre-registered systematic review of meta-analysis studies, randomized control trials, and observational studies evaluating clinical and biological features associated with heterogenous treatment effects for SGLT2-inhibitor and GLP1-receptor agonist therapies, considering glycaemic, cardiovascular, and renal outcomes. After screening 5,686 studies, we included 101 studies of SGLT2-inhibitors and 75 studies of GLP1-receptor agonists in the final systematic review.

RESULTS

Here we show that the majority of included papers have methodological limitations precluding robust assessment of treatment effect heterogeneity. For SGLT2-inhibitors, multiple observational studies suggest lower renal function as a predictor of lesser glycaemic response, while markers of reduced insulin secretion predict lesser glycaemic response with GLP1-receptor agonists. For both therapies, multiple post-hoc analyses of randomized control trials (including trial meta-analysis) identify minimal clinically relevant treatment effect heterogeneity for cardiovascular and renal outcomes.

CONCLUSIONS

Current evidence on treatment effect heterogeneity for SGLT2-inhibitor and GLP1-receptor agonist therapies is limited, likely reflecting the methodological limitations of published studies. Robust and appropriately powered studies are required to understand type 2 diabetes treatment effect heterogeneity and evaluate the potential for precision medicine to inform future clinical care.

Precision medicine in type 2 diabetes: A systematic review of treatment effect heterogeneity for GLP1-receptor agonists and SGLT2-inhibitors

Background

A precision medicine approach in type 2 diabetes requires identification of clinical and biological features that are reproducibly associated with differences in clinical outcomes with specific anti-hyperglycaemic therapies. Robust evidence of such treatment effect heterogeneity could support more individualized clinical decisions on optimal type 2 diabetes therapy.

Methods

We performed a pre-registered systematic review of meta-analysis studies, randomized control trials, and observational studies evaluating clinical and biological features associated with heterogenous treatment effects for SGLT2-inhibitor and GLP1-receptor agonist therapies, considering glycaemic, cardiovascular, and renal outcomes.

Results

After screening 5,686 studies, we included 101 studies of SGLT2-inhibitors and 75 studies of GLP1-receptor agonists in the final systematic review. The majority of papers had methodological limitations precluding robust assessment of treatment effect heterogeneity. For glycaemic outcomes, most cohorts were observational, with multiple analyses identifying lower renal function as a predictor of lesser glycaemic response with SGLT2-inhibitors and markers of reduced insulin secretion as predictors of lesser response with GLP1-receptor agonists. For cardiovascular and renal outcomes, the majority of included studies were post-hoc analyses of randomized control trials (including meta-analysis studies) which identified limited clinically relevant treatment effect heterogeneity.

Conclusions

Current evidence on treatment effect heterogeneity for SGLT2-inhibitor and GLP1-receptor agonist therapies is limited, likely reflecting the methodological limitations of published studies. Robust and appropriately powered studies are required to understand type 2 diabetes treatment effect heterogeneity and evaluate the potential for precision medicine to inform future clinical care.

Plain language summary

This review identifies research that helps understand which clinical and biological factors that are associated with different outcomes for specific type 2 diabetes treatments. This information could help clinical providers and patients make better informed personalized decisions about type 2 diabetes treatments. We focused on two common type 2 diabetes treatments: SGLT2-inhibitors and GLP1-receptor agonists, and three outcomes: blood glucose control, heart disease, and kidney disease. We identified some potential factors that are likely to lessen blood glucose control including lower kidney function for SGLT2-inhibitors and lower insulin secretion for GLP1-receptor agonists. We did not identify clear factors that alter heart and renal disease outcomes for either treatment. Most of the studies had limitations, meaning more research is needed to fully understand the factors that influence treatment outcomes in type 2 diabetes.

Novel methodology for the evaluation of symptoms reported by patients with newly diagnosed atrial fibrillation: Application of natural language processing to electronic medical records data

INTRODUCTION

Understanding symptom patterns in atrial fibrillation (AF) can help in disease management. We report on the application of natural language processing (NLP) to electronic medical records (EMRs) to capture symptom reports in patients with newly diagnosed (incident) AF.

METHODS AND RESULTS

This observational retrospective study included adult patients with an index diagnosis of incident AF during January 1, 2016 through June 30, 2018, in the Optum datasets. The baseline and follow-up periods were 1 year before/after the index date, respectively. The primary objective was identification of the following predefined symptom reports: dyspnea or shortness of breath; syncope, presyncope, lightheadedness, or dizziness; chest pain; fatigue; and palpitations. In an exploratory analysis, the incidence rates of symptom reports and cardiovascular hospitalization were assessed in propensity-matched patient cohorts with incident AF receiving first-line dronedarone or sotalol. Among 30 447 patients with an index AF diagnosis, the NLP algorithm identified at least 1 predefined symptom in 9734 (31.9%) patients. The incidence rate of symptom reports was highest at 0-3 months post-diagnosis and lower at >3-6 and >6-12 months (pre-defined timepoints). Across all time periods, the most common symptoms were dyspnea or shortness of breath, followed by syncope, presyncope, lightheadedness, or dizziness. Similar temporal patterns of symptom reports were observed among patients with prescriptions for dronedarone or sotalol as first-line treatment.

CONCLUSION

This study illustrates that NLP can be applied to EMR data to characterize symptom reports in patients with incident AF, and the potential for these methods to inform comparative effectiveness.

Retrospective Observational Real-World Outcome Study to Evaluate Safety Among Patients With Erectile Dysfunction (ED) With Co-Possession of Tadalafil and Anti-Hypertensive Medications (anti-HTN)

BACKGROUND

Erectile dysfunction (ED) is a common condition affecting male adults and may be associated with hypertension, diabetes, hyperlipidemia, and obesity. Phosphodiesterase type 5 (PDE5) inhibitors, such as tadalafil, are the first-line drug therapy for ED. Studies and the current prescribing information of these PDE5 inhibitors indicate they are mechanistic mild vasodilators and, as such, concomitant use of a PDE5 inhibitor with anti-hypertensive medication may lead to drops in blood pressure due to possible drug-drug interaction.

AIM

Evaluate risks of hypotensive/cardiovascular outcomes in a large cohort of patients with ED that have co-possession of prescriptions for tadalafil and hypertensive medications versus either medication/s alone.

METHODS

A cohort study conducted within an electronic health record database (Optum) representing hospitals across the US. Adult male patients prescribed tadalafil and/or anti-hypertensive medications from January 2012 to December 2017 were eligible. Possession periods were defined by the time patients likely had possession of medication, with propensity score-matched groups used for comparison.

OUTCOMES

Risk of hypotensive/cardiovascular outcomes were measured using diagnostic codes and NLP algorithms during possession periods of tadalafil + anti-hypertensive versus either medication/s alone.

RESULTS

In total there were 127,849 tadalafil + anti-hypertensive medication possession periods, 821,359 anti-hypertensive only medication possession periods, and 98,638 tadalafil only medication possession periods during the study; 126,120 were successfully matched. Adjusted-matched incidence rate ratios (IRRs) for the anti-hypertensive only possession periods compared with tadalafil + anti-hypertensive periods of diagnosed outcomes were all below 1. Two outcomes had a 95% confidence interval (CI) that did not include 1.0: ventricular arrhythmia (IRR 0.79; 95% CI 0.66, 0.94) and diagnosis of hypotension (IRR 0.79; 95% CI 0.71, 0.89).

CLINICAL IMPLICATIONS

Provides real world evidence that co-possession of tadalafil and anti-hypertensive medications does not increase risk of hypotensive/cardiovascular outcomes beyond that observed for patients in possession of anti-hypertensive medications only.

STRENGTHS AND LIMITATIONS

EHR data are valuable for the evaluation of real world outcomes, however, the data are retrospective and collected for clinical patient management rather than research. Prescription data represent the intent of the prescriber and not use by the patient. Residual bias cannot be ruled out, despite propensity score matching, due to unobserved patient characteristics and severity that are not fully reflected in the EHR database.

CONCLUSION

In the studied real world patients, this study did not demonstrate an increased risk of hypotensive or cardiovascular outcomes associated with co-possession of tadalafil and anti-hypertensive medications beyond that observed for patients in possession of anti-hypertensive medications only. Nunes AP, Seeger JD, Stewart A, et al., Retrospective Observational Real-World Outcome Study to Evaluate Safety Among Patients With Erectile Dysfunction (ED) With Co-Possession of Tadalafil and Anti-Hypertensive Medications (anti-HTN). J Sex Med 2022;19:74-82.

Non-specific pain and 30-day readmission in acute coronary syndromes: findings from the TRACE-CORE prospective cohort

Background

Patients with acute coronary syndromes often experience non-specific (generic) pain after hospital discharge. However, evidence about the association between post-discharge non-specific pain and rehospitalization remains limited.

Methods

We analyzed data from the Transitions, Risks, and Actions in Coronary Events Center for Outcomes Research and Education (TRACE-CORE) prospective cohort. TRACE-CORE followed patients with acute coronary syndromes for 24 months post-discharge from the index hospitalization, collected patient-reported generic pain (using SF-36) and chest pain (using the Seattle Angina Questionnaire) and rehospitalization events. We assessed the association between generic pain and 30-day rehospitalization using multivariable logistic regression (N = 787). We also examined the associations among patient-reported pain, pain documentation identified by natural language processing (NLP) from electronic health record (EHR) notes, and the outcome.

Results

Patients were 62 years old (SD = 11.4), with 5.1% Black or Hispanic individuals and 29.9% women. Within 30 days post-discharge, 87 (11.1%) patients were re-hospitalized. Patient-reported mild-to-moderate pain, without EHR documentation, was associated with 30-day rehospitalization (odds ratio [OR]: 2.03, 95% confidence interval [CI]: 1.14–3.62, reference: no pain) after adjusting for baseline characteristics; while patient-reported mild-to-moderate pain with EHR documentation (presumably addressed) was not (OR: 1.23, 95% CI: 0.52–2.90). Severe pain was also associated with 30-day rehospitalization (OR: 3.16, 95% CI: 1.32–7.54), even after further adjusting for chest pain (OR: 2.59, 95% CI: 1.06–6.35).

Conclusions

Patient-reported post-discharge generic pain was positively associated with 30-day rehospitalization. Future studies should further disentangle the impact of cardiac and non-cardiac pain on rehospitalization and develop strategies to support the timely management of post-discharge pain by healthcare providers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-02195-z.

Method used to identify adenomyosis and potentially undiagnosed adenomyosis in a large, U.S. electronic health record database

BACKGROUND

The prevalence of adenomyosis is underestimated due to lack of a specific diagnostic code and diagnostic delays given most diagnoses occur at hysterectomy.

OBJECTIVES

To identify women with adenomyosis using indicators derived from natural language processing (NLP) of clinical notes in the Optum Electronic Health Record database (2014-2018), and to estimate the prevalence of potentially undiagnosed adenomyosis.

METHODS

An NLP algorithm identified mentions of adenomyosis in clinical notes that were highly likely to represent a diagnosis. The anchor date was date of first affirmed adenomyosis mention; baseline characteristics were assessed in the 12 months prior to this date. Characteristics common to adenomyosis cases were used to select a suitable pool of women from the underlying population, among whom undiagnosed adenomyosis might exist. A random sample of this pool was selected to form the comparator cohort. Logistic regression was used to compare adenomyosis cases to comparators; the predictive probability (PP) of being an adenomyosis case was assessed. Comparators having a PP ≥ 0.1 were considered potentially undiagnosed adenomyosis and were used to calculate the prevalence of potentially undiagnosed adenomyosis in the underlying population.

RESULTS

Among 11 456 347 women aged 18-55 years in the underlying population, 19 503 were adenomyosis cases. Among 332 583 comparators, 22 696 women were potentially undiagnosed adenomyosis cases. The prevalence of adenomyosis and potentially undiagnosed adenomyosis was 1.70 and 19.1 per 1000 women aged 18-55 years, respectively.

CONCLUSIONS

Considering potentially undiagnosed adenomyosis, the prevalence of adenomyosis may be 10x higher than prior estimates based on histologically confirmed adenomyosis cases only.

Identifying Symptom Information in Clinical Notes Using Natural Language Processing

BACKGROUND

Symptoms are a core concept of nursing interest. Large-scale secondary data reuse of notes in electronic health records (EHRs) has the potential to increase the quantity and quality of symptom research. However, the symptom language used in clinical notes is complex. A need exists for methods designed specifically to identify and study symptom information from EHR notes.

OBJECTIVES

We aim to describe a method that combines standardized vocabularies, clinical expertise, and natural language processing to generate comprehensive symptom vocabularies and identify symptom information in EHR notes. We piloted this method with five diverse symptom concepts: constipation, depressed mood, disturbed sleep, fatigue, and palpitations.

METHODS

First, we obtained synonym lists for each pilot symptom concept from the Unified Medical Language System. Then, we used two large bodies of text (clinical notes from Columbia University Irving Medical Center and PubMed abstracts containing Medical Subject Headings or key words related to the pilot symptoms) to further expand our initial vocabulary of synonyms for each pilot symptom concept. We used NimbleMiner, an open-source natural language processing tool, to accomplish these tasks and evaluated NimbleMiner symptom identification performance by comparison to a manually annotated set of nurse- and physician-authored common EHR note types.

RESULTS

Compared to the baseline Unified Medical Language System synonym lists, we identified up to 11 times more additional synonym words or expressions, including abbreviations, misspellings, and unique multiword combinations, for each symptom concept. Natural language processing system symptom identification performance was excellent.

DISCUSSION

Using our comprehensive symptom vocabularies and NimbleMiner to label symptoms in clinical notes produced excellent performance metrics. The ability to extract symptom information from EHR notes in an accurate and scalable manner has the potential to greatly facilitate symptom science research.

Glucagon-Like Peptide 1 Receptor Agonist (GLP1RA) Exposure and Outcomes in Type 2 Diabetes: A Systematic Review of Population-Based Observational Studies

INTRODUCTION

Glucagon-like peptide 1 receptor agonists (GLP1RAs) are licensed for the treatment of type 2 diabetes (T2D). They have been shown to be safe (from the cardiovascular (CV) perspective) and effective (in terms of glycaemia, and in some cases, reducing CV events) in extensive randomised controlled trials (RCTs). However, there remain concerns regarding the generalisability of these findings (to those ineligible for RCT participation) and about non-CV safety. For effectiveness, population-based pharmacoepidemiology studies can confirm and extend the findings of RCTs findings to broader populations and explore safety, for which RCTs are not usually powered, in more detail.

METHOD

We did a pre-planned and registered (PROSPERO registration CRD42020165720) systematic review of population-based studies investigating GLP1RA effectiveness and safety, following Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines.

RESULTS

A total of 22 studies were identified (including 200,148 participants and 396,457 person-years of follow-up) exploring exposure to GLP1RA class, exenatide and liraglutide (the only individual drugs with treatment effect estimates identified) on mortality, cardiovascular disease (CVD), acute pancreatitis (AP), pancreatic cancer (PC), thyroid cancer (TC), acute renal failure (ARF), diabetic retinopathy (DR), breast cancer (BC) and hypoglycaemia. For CV and mortality outcomes, studies confirmed the associated safety of these drugs. For liraglutide, point estimate (PE) range (PER) major adverse cardiovascular events (MACE) (0.53-0.95) and PER heart failure (0.34-1.22) were similar in direction to the beneficial effect observed in RCTs for MACE but varied widely for heart failure. For safety outcomes, exposure was not associated with AP (PER 0.50-1.17), PC (PER 0.40-1.54), BC (PER 0.90-1.51) or hypoglycaemia (PER 0.59-1.06). Only one study was identified exploring each of TC (no evidence of association, hazard ratio (HR) 1.46, 95% confidence interval (CI) 0.98-2.19), renal outcomes (no evidence of association, HR 0.77, 95% CI 0.42-1.41) and DR (no evidence of association, HR 0.67, 95% CI 0.51-0.90).

CONCLUSION

In T2D, GLP1RAs appear safe from the CV perspective and (for liraglutide) may have associated benefit in primary as well as secondary CVD prevention. For non-CV safety, GLP1RA exposure was not associated with an increased risk of AP, PC, BC or hypoglycaemia; the other outcomes had too few studies to draw firm conclusions and should be explored further.

Safety, Pharmacokinetics and Pharmacodynamics of Multiple Escalating Doses of PEGylated Exenatide (PB-119) in Healthy Volunteers

BACKGROUND AND OBJECTIVE

At present, the deficiency of β-cell function is progressive in patients with type 2 diabetes mellitus. Exenatide cannot only control blood glucose well, but also promotes the regeneration and proliferation of islet β-cells and improves the function of β cells. However, it needs to be given twice a day, and there are many adverse reactions such as nausea. PEGylated exenatide (study code: PB-119) needs to be administered only once a week. The purpose of this experiment was to evaluate the safety, pharmacokinetics and pharmacodynamics of an escalating dose regimen of subcutaneous PEGylated exenatide injections in healthy subjects.

METHODS

Twelve healthy young adult subjects in each group received once-weekly subcutaneous injections of 165 μg, 330 μg, and 660 μg PEGylated exenatide for 6 weeks. Plasma drug concentration was determined in venous blood collected across selected time points. Safety and tolerability were evaluated by monitoring adverse events, laboratory parameters, and electrocardiogram. Blood glucose, insulin,  glucagon and C peptide were monitored at different time points to evaluate the pharmacodynamics of PEGylated exenatide.

RESULTS

A total of 11, 10, and 12 subjects completed the study in 165 µg, 330 µg, and 660 µg dose groups, respectively. After 6 consecutive weeks of administration, the t_1/2 in the 165 μg, 330 μg, and 660 µg dose groups was 55.67 ± 11.03 h, 56.99 ± 21.37 h, and 54.81 ± 13.87 h, respectively. The C_avg was 4.22 ± 0.78 ng/ml, 6.03 ± 1.43 ng/ml, and 10.50 ± 3.06 ng/ml, respectively. AUCss was 708.59 ± 131.87 h•ng/ml, 1012.63 ± 240.79 h•ng/ml, and 1763.81 ± 514.50 h•ng/ml, respectively. The accumulation index was 1.15 ± 0.07, 1.17 ± 0.11, and 1.14 ± 0.07. The CLss/F was 241.25 ± 51.13 ml/h, 341.53 ± 73.62 ml/h, and 450.06 ± 313.76 ml/h, respectively. A total of 10 of 36 (27.78%) subjects in the three dose groups developed specific antibodies after consecutive subcutaneous injections of PEGylated exenatide. The C_avg and C_max were higher than those of antibody-negative subjects. Furthermore, in antibody-positive subjects, CLss/F, t_1/2, AUC_τ, accumulation index, MRT_(0-inf) and other parameters were lower than those of antibody-negative subjects. In the 165 μg dose group, two subjects (16.67%) experienced 4 adverse events. In the 330 μg dose group, no subjects reported adverse events. In the 660 μg dose group, 8 subjects (66.67%) reported 16 adverse events, which were mostly gastrointestinal. There were no significant changes in the pharmacodynamic parameters except the glucagon level at day 36 in the 660 µg dose group, the 2h postprandial insulin and C peptide levels at day 36 and day 50 in the 165 μg dose group compared with baseline (- 1 day).

CONCLUSION

A once-weekly subcutaneous injection of 165 µg and 330 µg PEGylated exenatide is safe. No significant effects on blood glucose or pancreatic hormone levels were observed in the subjects within these dose groups. The pharmacokinetic parameters of PEGylated exenatide may be affected by immunogenicity.

CLINICAL TRIALS REGISTRATION

The study is registered at clinicaltrials.gov (No. NCT03062774).

Using RWE research to extend clinical trials in diabetes: An example with implications for the future

BACKGROUND

Although randomized, controlled trials (RCTs) are seen as the gold standard for evidence in clinical medicine, a number of considerations are increasing the use of real-world data (RWD) to generate evidence. A series of methodological challenges must be overcome in order for such real-world evidence (RWE) to gain acceptance. In diabetes, RWE faces some particular issues that have limited its development. As the natural history of diabetes progresses, patients' disease changes over time and treatments will be modified as a result. This evolving disease and treatment pattern requires application of methods that account for such changes over time. Research developing RWE in diabetes and other conditions has sometimes been subject to important biases, and researchers should be aware of, and take steps to mitigate potential for bias in order to enhance the evidence produced.

RESULTS

We review a RWE study that replicated and extended evidence provided by a RCT regarding the effects of weekly exenatide relative to basal insulin (glargine or detemir) to illustrate a potential application of RWE. This study observed a 0.7% decrease in HbA1C for weekly exenatide relative to a 0.5% decrease in HbA1C for the comparator along with a 2 kg weight loss for weekly exenatide relative to a 0.25 kg weight gain, effects that were close to those from the RCT. Further, the RWE study was able to extend results to patient populations that were not well represented in the RCT.

CONCLUSION

Despite numerous challenges, RWE can be used to complement evidence from RCTs.

Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review

OBJECTIVE

Natural language processing (NLP) of symptoms from electronic health records (EHRs) could contribute to the advancement of symptom science. We aim to synthesize the literature on the use of NLP to process or analyze symptom information documented in EHR free-text narratives.

MATERIALS AND METHODS

Our search of 1964 records from PubMed and EMBASE was narrowed to 27 eligible articles. Data related to the purpose, free-text corpus, patients, symptoms, NLP methodology, evaluation metrics, and quality indicators were extracted for each study.

RESULTS

Symptom-related information was presented as a primary outcome in 14 studies. EHR narratives represented various inpatient and outpatient clinical specialties, with general, cardiology, and mental health occurring most frequently. Studies encompassed a wide variety of symptoms, including shortness of breath, pain, nausea, dizziness, disturbed sleep, constipation, and depressed mood. NLP approaches included previously developed NLP tools, classification methods, and manually curated rule-based processing. Only one-third (n = 9) of studies reported patient demographic characteristics.

DISCUSSION

NLP is used to extract information from EHR free-text narratives written by a variety of healthcare providers on an expansive range of symptoms across diverse clinical specialties. The current focus of this field is on the development of methods to extract symptom information and the use of symptom information for disease classification tasks rather than the examination of symptoms themselves.

CONCLUSION

Future NLP studies should concentrate on the investigation of symptoms and symptom documentation in EHR free-text narratives. Efforts should be undertaken to examine patient characteristics and make symptom-related NLP algorithms or pipelines and vocabularies openly available.

Tardive dyskinesia among patients using antipsychotic medications in customary clinical care in the United States

Background

Tardive dyskinesia (TD) is a movement disorder resulting from treatment with typical and atypical antipsychotics. An estimated 16–50% of patients treated with antipsychotics have TD, but this number may be underestimated. The objectives of this study were to build an algorithm for use in electronic health records (EHRs) for the detection and characterization of TD patients, and to estimate the prevalence of TD in a population of patients exposed to antipsychotic medications.

Methods

This retrospective observational study included patients identified in the Optum EHR Database who received a new or refill prescription for an antipsychotic medication between January 2011 and December 2015 (follow-up through June 2016). TD mentions were identified in the natural language–processed clinical notes, and an algorithm was built to classify the likelihood that the mention represented documentation of a TD diagnosis as probable, possible, unlikely, or negative. The final TD population comprised a subgroup identified using this algorithm, with ≥1 probable TD mention (highly likely TD).

Results

164,417 patients were identified for the antipsychotic population, with1,314 comprising the final TD population. Conservatively, the estimated average annual prevalence of TD in patients receiving antipsychotics was 0.8% of the antipsychotic user population. The average annual prevalence may be as high as 1.9% per antipsychotic user per year, allowing for a more-inclusive algorithm using both probable and possible TD. Most TD patients were prescribed atypical antipsychotics (1049/1314, 79.8%). Schizophrenia (601/1314, 45.7%), and paranoid and schizophrenia‐like disorders (277/1314, 21.1%) were more prevalent in the TD population compared with the entire antipsychotic drug cohort (13,308/164,417; 8.1% and 19,359/164,417; 11.8%, respectively).

Conclusions

Despite a lower TD prevalence than previously estimated and the predominant use of atypical antipsychotics, identified TD patients appear to have a substantial comorbidity burden that requires special treatment and management consideration.