Objective measures of non-adherence in cardiometabolic diseases: a review focused on urine biochemical screening

Cardiovascular medication adherence testing in patients living with HIV: A single-centre observational study

INTRODUCTION

People with HIV (PWH) are at an increased risk of developing cardiovascular disease (CVD) compared to HIV-negative individuals. We sought to evaluate the adherence to medications for CVD in PWH and identify factors associated with non-adherence to these medications.

METHODS

We conducted a cross-sectional study at the University Hospitals of Leicester NHS Trust between 16 April 2019 and 8 November 2022. We recruited consecutive PWH, who were attending a routine follow-up outpatient appointment and were prescribed at least one medication for CVD. In addition, we included urinary adherence results of patients with samples collected as part of routine clinical care. We used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to assess if their prescribed medications (antihypertensives, diuretics, beta-blockers, lipid-lowering agents, antiplatelets, anticoagulants, antidiabetic medications) were present in the participant's urine sample. Multivariable models were used to identify demographic or clinical features that were associated with non-adherence.

RESULTS

A total of 162 PWH were included in the analysis. Median age was 55 [interquartile range (IQR): 50-61] years, 63% were male, average time living with HIV was 15 years (IQR: 11-19) and the majority (98%) had an undetectable HIV viral load. In approximately one-third of patients (59/162), at least one prescribed medication of interest was not detected in urine. Non-adherence to lipid-lowering agents was common (35/88, 40%). On multivariable logistic regression, the number of prescribed cardiovascular medications, was associated with medication non-adherence [medication non-adherence, per one medication increase: adjusted odds ratio (95% confidence interval) = 1.78 (1.34-2.36); p < 0.001].

CONCLUSION

We found sub-optimal adherence to medications for CVD in PWH. In order to maximize the clinical benefit of statin therapy in PWH, factors requiring consideration include: improved medication adherence, awareness of polypharmacy, educational interventions and quantitative assessment of sub-optimal adherence through chemical adherence testing.

Non-adherence to cardiometabolic medication as assessed by LC-MS/MS in urine and its association with kidney and cardiovascular outcomes in type 2 diabetes mellitus

AIMS/HYPOTHESIS

Non-adherence to medication is a frequent barrier in the treatment of patients with type 2 diabetes mellitus, potentially limiting the effectiveness of evidence-based treatments. Previous studies have mostly relied on indirect adherence measures to analyse outcomes based on adherence. The aim of this study was to use LC-MS/MS in urine-a non-invasive, direct and objective measure-to assess non-adherence to cardiometabolic drugs and analyse its association with kidney and cardiovascular outcomes.

METHODS

This cohort study includes 1125 participants from the PROVALID study, which follows patients with type 2 diabetes mellitus at the primary care level. Baseline urine samples were tested for 79 cardiometabolic drugs and metabolites thereof via LC-MS/MS. An individual was classified as totally adherent if markers for all drugs were detected, partially non-adherent when at least one marker for one drug was detected, and totally non-adherent if no markers for any drugs were detected. Non-adherence was then analysed in the context of cardiovascular (composite of myocardial infarction, stroke and cardiovascular death) and kidney (composite of sustained 40% decline in eGFR, sustained progression of albuminuria, kidney replacement therapy and death from kidney failure) outcomes.

RESULTS

Of the participants, 56.3% were totally adherent, 42.0% were partially non-adherent, and 1.7% were totally non-adherent to screened cardiometabolic drugs. Adherence was highest to antiplatelet and glucose-lowering agents and lowest to lipid-lowering agents. Over a median (IQR) follow-up time of 5.10 (4.12-6.12) years, worse cardiovascular outcomes were observed with non-adherence to antiplatelet drugs (HR 10.13 [95% CI 3.06, 33.56]) and worse kidney outcomes were observed with non-adherence to antihypertensive drugs (HR 1.98 [95% CI 1.37, 2.86]).

CONCLUSIONS/INTERPRETATION

This analysis shows that non-adherence to cardiometabolic drug regimens is common in type 2 diabetes mellitus and negatively affects kidney and cardiovascular outcomes.

Improving medication adherence in cardiovascular disease

Non-adherence to medication is a global health problem with far-reaching individual-level and population-level consequences but remains unappreciated and under-addressed in the clinical setting. With increasing comorbidity and polypharmacy as well as an ageing population, cardiovascular disease and medication non-adherence are likely to become increasingly prevalent. Multiple methods for detecting non-adherence exist but are imperfect, and, despite emerging technology, a gold standard remains elusive. Non-adherence to medication is dynamic and often has multiple causes, particularly in the context of cardiovascular disease, which tends to require lifelong medication to control symptoms and risk factors in order to prevent disease progression. In this Review, we identify the causes of medication non-adherence and summarize interventions that have been proven in randomized clinical trials to be effective in improving adherence. Practical solutions and areas for future research are also proposed.

Measuring adherence to antihypertensive medication using an objective test in older adults attending primary care: cross-sectional study

Analysis of urine samples using liquid chromatography-tandem mass spectrometry (LC-MS/MS) has previously revealed high rates of non-adherence to antihypertensive medication. It is unclear whether these rates represent those in the general population. This study aimed to investigate whether it is feasible to collect urine samples in a primary care setting and analyse them using LC-MS/MS to detect non-adherence to antihypertensive medication. This study used a prospective, observational cohort design. Consecutive patients were recruited opportunistically from five general practices in UK primary care. They were aged ≥65 years with hypertension and had at least one antihypertensive prescription. Participants were asked to provide a urine sample for analysis of medication adherence. Samples were sent to a laboratory via post and analysed using LC-MS/MS. Predictors of adherence to medication were explored with multivariable logistic regression. Of 349 consecutive patients approached for the study, 214 (61.3%) gave informed consent and 191 (54.7%) provided a valid urine sample for analysis. Participants were aged 76.2 ± 6.6 years and taking a median of 2 antihypertensive medications (IQR 1-3). A total of 27/191 participants (14.2%) reported not taking all of their medications on the day of urine sample collection. However, LC-MS/MS analysis of samples revealed only 4/27 (9/191 in total; 4.7%) were non-adherent to some of their medications. Patients prescribed more antihypertensive medications were less likely to be adherent (OR 0.24, 95%CI 0.09-0.65). Biochemical testing for antihypertensive medication adherence is feasible in routine primary care, although non-adherence to medication is generally low, and therefore widespread testing is not indicated.

Clinical Variation in the Treatment Practices for Medication Nonadherence, Drug-Drug Interactions, and Recognition of Disease Progression in Patients with Chronic Cardiometabolic Diseases: A Cross-Sectional Patient Simulation Study among Primary Care Physicians

Background

Medication nonadherence in patients with chronic diseases is common, costly, and often underdiagnosed. In the United States, approximately 40-50% of patients with cardiometabolic conditions are not adherent to long-term medications. Drug-drug interactions (DDI) are also underrecognized and may lead to medication nonadherence in this patient population. Treatment complexity associated with cardiometabolic conditions contributes to increased risk for adverse drug events and DDIs.

Methods

We recruited a nationally representative sample of 246 board-certified family and internal medicine physicians to evaluate how they assessed, identified, and treated medication nonadherence, DDIs, and worsening disease. Participating physicians were asked to care for three online simulated patients, each with at least one chronic cardiometabolic disease, including atrial fibrillation, heart failure, diabetes mellitus, or hypertension, and who were taking prescription medications for their disease. Physicians' scores were based on evidence-based care recommendation criteria, including overall care quality and treatment for medication nonadherence and DDIs.

Results

Overall, quality-of-care scores across all cases ranged from 13% to 87% with an average of 50.8% ± 12.1%. The average overall diagnostic plus treatment score was 21.9% ± 13.6%. Participants identified nonadherence in just 3.6% of cases, DDIs in 8.9% of cases, and disease progression in 30.3% of cases.

Conclusions

Based on these study results, primary care physicians were unable to adequately diagnose and treat patients with chronic cardiometabolic diseases who either suffered from medication nonadherence, DDIs, or progression of the disease. Improved standardization and technique in identifying these diagnoses is needed in primary care. Trial Registration. This trial is registered with clinicaltrials.gov, NCT05192590.

Depression and the risk of hospitalization in type 2 diabetes patients: A nested case-control study accounting for non-persistence to antidiabetic treatment

INTRODUCTION

Depression is one of the most common comorbidities of type 2 diabetes. The relationship between these two diseases seems to be bidirectional. Both conditions separately lead to significant morbidity and mortality, including hospitalization. Moreover, depression is associated with non-persistence with antidiabetic drugs.

OBJECTIVES

To measure the effect of depression on morbidity and particularly on all-cause, diabetes-related, cardiovascular-related and major cardiovascular events-related hospitalization, adjusting for non-persistence to antidiabetic drugs and other confounders.

METHODS

We performed a nested case-control study within a cohort of type 2 diabetic individuals initiating antidiabetic drugs. Using the health administrative data of the province of Quebec, Canada, we identified all-cause, diabetes-related, cardiovascular-related and major cardiovascular hospitalizations during a maximum follow-up of eight years after the initiation of antidiabetic drug treatment. A density sampling method matched all cases with up to 10 controls by age, sex, and the Elixhauser comorbidity index. The effect of depression on hospitalization was estimated using conditional logistic regressions adjusting for non-persistence to antidiabetic drug treatment and other variables.

RESULTS

We identified 41,550 all-cause hospitalized cases, of which 34,437 were related to cardiovascular (CV) diseases, 29,584 to diabetes, and 13,867 to major CV events. Depression was diagnosed in 2.51% of all-cause hospitalizations and 1.16% of matched controls. 69.11% of cases and 72.59% of controls were on metformin monotherapy. The majority (71.62% vs 75.02%, respectively) stayed on metformin monotherapy without adding or switching drugs during follow-up. Non-persistence was at similar rates (about 30%) in both groups. In the multivariable analyses, depression was associated with an increased risk for all-cause hospitalizations, with odds ratios (ORs) ranging from 2.21 (95% CI: 2.07-2.37) to 1.32 (95% CI: 1.22-1.44) according to the model adjustment (from the univariate to the fully adhjusted).

CONCLUSION

Depression increased the risk of all-cause hospitalizations among patients treated for diabetes, even after accounting for non-persistence and other potentially confounding factors. These results stress the impact of depression on diabetic patients' use of health care resources.

Associations of Plasma Concentration Profiles of Dapagliflozin, a Selective Inhibitor of Sodium–Glucose Co-Transporter Type 2, with Its Effects in Japanese Patients with Type 2 Diabetes Mellitus

This study was conducted to evaluate the long-term plasma concentration profiles of dapagliflozin and its effects on the glycated hemoglobin (HbA1c) level, body weight, and estimated glomerular filtration rate (eGFR) in 72 Japanese outpatients with type 2 diabetes mellitus (T2DM) receiving metformin and a dipeptidyl peptidase-4 inhibitor. At baseline, HbA1c level, body weight, and eGFR were 6.9 ± 0.6%, 77.9 ± 13.5 kg, and 78.8 ± 20.7 mL/min/1.73 m², respectively. A once-daily oral dose of 5 mg dapagliflozin was administered, and its trough plasma concentrations were evaluated at 1, 3, 6, 9, and 12 months. In this study, the patients with stable dapagliflozin concentrations were defined, based on a well-organized clinical trial, as those with average plasma concentrations of 2–5 ng/mL with a coefficient of variation <30%; these values were achieved if patients complied with their once-daily dosage. Multivariate analysis showed a significant decrease in the HbA1c levels among patients with stable concentrations (−0.6 ± 0.4%, p < 0.01), which was greater than the mean change among all 72 patients (−0.2 ± 0.5%, p < 0.01). The patients’ mean body weight also decreased (−2.3 ± 4.0 kg, p = 0.060). Average plasma concentrations ranged from 1.6 to 11.8 ng/mL; however, multivariate analysis indicated it was unrelated to the HbA1c-lowering effect. In conclusion, the long-term stability of plasma dapagliflozin concentration was important in lowering HbA1c level, and a once-daily oral dose of 5 mg was sufficient in achieving this effect.

Nonadherence in Hypertension: How to Develop and Implement Chemical Adherence Testing

Nonadherence to antihypertensive medication is common, especially in those with apparent treatment-resistant hypertension (true treatment-resistant hypertension requires exclusion of nonadherence), and its routine detection is supported by clinical guidelines. Chemical adherence testing is a reliable and valid method to detect adherence, yet methods are unstandardized and are not ubiquitous. This article describes the principles of chemical adherence testing for hypertensive patients and provides a set of recommendations for centers wishing to develop the test. We recommend testing should be done in either of two instances: (1) in those who have resistant hypertension or (2) in those on 2 antihypertensives who have a less than 10 mm Hg drop in systolic blood pressure on addition of the second antihypertensive medication. Furthermore, we recommend that verbal consent is secured before undertaking the test, and the results should be discussed with the patient. Based on medications prescribed in United Kingdom, European Union, and United States, we list top 20 to 24 drugs that cover >95% of hypertension prescriptions which may be included in the testing panel. Information required to identify these medications on mass spectrometry platforms is likewise provided. We discuss issues related to ethics, sample collection, transport, stability, urine versus blood samples, qualitative versus quantitative testing, pharmacokinetics, instrumentation, validation, quality assurance, and gaps in knowledge. We consider how to best present, interpret, and discuss chemical adherence test results with the patient. In summary, this guidance should help clinicians and their laboratories in the development of chemical adherence testing of prescribed antihypertensive drugs.

Comparison of measures of medication adherence from pharmacy dispensing and insurer claims data

OBJECTIVE

Medication nonadherence is linked to worsened clinical outcomes and increased costs. Existing system-level adherence interventions rely on insurer claims for patient identification and outcome measurement, yet suffer from incomplete capture and lags in data acquisition. Data from pharmacies regarding prescription filling, captured in retail dispensing, may be more efficient.

DATA SOURCES

Pharmacy fill and insurer claims data.

STUDY DESIGN

We compared adherence measured using pharmacy fill data to adherence using insurer claims data, expressed as proportion of days covered (PDC) over 12 months. Agreement was evaluated using correlation/validation metrics. We also explored the relationship between adherence in both sources and disease control using prediction modeling.

DATA EXTRACTION METHODS

Large pragmatic trial of cardiometabolic disease in an integrated delivery network.

PRINCIPAL FINDINGS

Among 1113 patients, adherence was higher in pharmacy fill (mean = 50.0%) versus claims data (mean = 47.4%), although they had moderately high correlation (R = 0.57, 95% CI: 0.53-0.61) with most patients (86.9%) being similarly classified as adherent or nonadherent. Sensitivity and specificity of pharmacy fill versus claims data were high (0.89, 95% CI: 0.86-0.91 and 0.80, 95% CI: 0.75-0.85). Pharmacy fill-based PDC predicted better disease control slightly more than claims-based PDC, although the difference was nonsignificant.

CONCLUSIONS

Pharmacy fill data may be an alternative to insurer claims for adherence measurement.

Non-adherence to antidiabetic and cardiovascular drugs in type 2 diabetes mellitus and its association with renal and cardiovascular outcomes: A narrative review

Cardiovascular and renal complications are a major burden for individuals with type 2 diabetes mellitus (T2DM). Besides lifestyle interventions, current guidelines recommend combination drug therapy to prevent or delay the incidence and progression of comorbidities. However, non-adherence to pharmacotherapy is common in chronic conditions such as T2DM and a barrier to successful disease management. Numerous studies have associated medication non-adherence with worse outcome as well as higher health care costs. This narrative review provides (i) an overview on adherence measures used within and outside research settings, (ii) an estimate on the prevalence of non-adherence to antidiabetic and cardiovascular drugs in T2DM, and (iii) specifically focuses on the association of non-adherence to these drugs with renal and cardiovascular outcomes.

Adherence to cardiovascular pharmacotherapy by patients in Iraq: A mixed methods assessment using quantitative dried blood spot analysis and the 8-item Morisky Medication Adherence Scale

This study evaluated the adherence to prescribed cardiovascular therapy medications among cardiovascular disease patients attending clinics in Misan, Amara, Iraq. Mixed methods were used to assess medication adherence comprising the Arabic version of the eight-item Morisky Medication Adherence Scale (MMAS-8) and determination of drug concentrations in patient dried blood spot (DBS) samples by liquid chromatography-high resolution mass spectrometry. Three hundred and three Iraqi patients (median age 53 years, 50.5% female) who had been taking one or more of the nine commonly prescribed cardiovascular medications (amlodipine, atenolol, atorvastatin, bisoprolol, diltiazem, lisinopril, losartan, simvastatin and valsartan) for at least six months were enrolled. For each patient MMAS-8 scores were determined alongside drug concentrations in their dried blood spot samples. Results from the standardized questionnaire showed that adherence was 81.8% in comparison with 50.8% obtained using the laboratory-based microsample analysis. The agreement between the indirect (MMAS-8) and direct (DBS analysis) assessment approaches to assessing medication adherence showed significantly poor agreement (kappa = 0.28, P = 0.001). The indirect and direct assessment approaches showed no significant correlation between nonadherence to prescribed cardiovascular pharmacotherapy and age and gender, but were significantly associated with the number of medications in the patient's treatment regimen (MMAS-8: Odds Ratio (OR) 1.947, 95% CI, P = 0.001; DBS analysis: OR 2.164, 95% CI, P = 0.001). The MMAS-8 results highlighted reasons for nonadherence to prescribed cardiovascular pharmacotherapy in this patient population whilst the objective DBS analysis approach gave valuable information about nonadherence to each medication in the patient's treatment regimen. DBS sampling, due its minimally invasive nature, convenience and ease of transport is a useful alternative matrix to monitor adherence objectively in Iraq to cardiovascular pharmacotherapy. This information combined with MMAS-8 can provide clinicians with an evidence-based novel approach to implement intervention strategies to optimise and personalise cardiovascular pharmacotherapy in the Iraqi population and thereby improve patient health outcomes.

Community pharmacist interventions to improve adherence to lipid lowering medication and their influence on clinical outcomes: A systematic review and meta-analysis

INTRODUCTION

Non-adherence is a major problem among patients with chronic diseases. Community pharmacists are ideally positioned to detect non-adherence and to provide patient-centred interventions.

OBJECTIVE

To conduct a systematic review of the impact of community pharmacist interventions on patient adherence to lipid lowering medication (LLM) prescriptions and clinical outcomes.

SEARCH METHOD

Five databases (MEDLINE, Cochrane Library, Science Direct, Scopus, and Web of Knowledge) were searched systematically to identify relevant reports published by December 2019. Study quality was assessed with the Cochrane risk of bias (RoB 2.0) tool.

SELECTION CRITERIA

Controlled trials in which community pharmacists conducted an intervention to improve patient adherence to LLM and clinical outcomes were evaluated.

MAIN RESULTS

Five studies (2408 participants) were included in the qualitative analysis. Four studies (n = 2266) were pooled in the meta-analysis. Participants in the intervention group (IG) had better adherence than those in the control group (CG) [odds ratio (OR) = 1.67; 95% confidence interval (CI) 1.38-2.02; P < 0.001; I² = 54%]. Better adherence rates were obtained when adherence was measured with validated questionnaires than when medication-possession ratio (MPR) measurements were used. Total cholesterol (TC) levels were not included in the meta-analysis due to data variability among the studies.

CONCLUSIONS

Pharmacist-led intervention can improve LLM adherence, but its influence on clinical outcomes, including lipid level control, remains to be clarified.