Statin adherence is lower in primary than secondary prevention: A national follow-up study of new users

Cost-utility analysis of using high-intensity statin among post-hospitalized acute coronary syndrome patients

BACKGROUND

Post-hospitalized acute coronary syndrome (ACS) patients in Indonesia National Insurance does not pay for the use of high-intensity statin (HIS) for secondary prevention after ACS hospitalization. Moreover, a cost-utility analysis needs to be conducted to evaluate the cost-effectiveness of prescribing HIS and low-to-moderate-intensity statin (LMIS) per quality-adjusted life year (QALY). This study aimed to estimate the cost-utility of long-term HIS treatment in post-hospitalized ACS patients in Indonesia compared to current practice.

RESULTS

This study compared the economic outcomes of long-term HIS and LMIS in Indonesian post-hospitalized ACS patients. A lifetime Markov model predicted ACS-related events, costs, and QALY from a payer perspective. A systematic review estimated treatment-specific event probabilities, post-event survival, health-related quality of life, and Indonesia medical-care expenses from published sources. This study conducted probabilistic sensitivity analysis (PSA) using 1000 independent Monte Carlo simulations and a series of one-way deterministic sensitivity analyses utilizing a tornado diagram. The economic evaluation model proved that intensive HIS treatment can increase per-patient QALYs and care expenditures compared to LMIS. The use of HIS among post-hospitalized ACS patients had ICER 31.843.492 IDR per QALY gained, below the Indonesia willingness-to-pay (WTP) for terminal disease and life-saving treatment.

CONCLUSION

From the Indonesia payer perspective, using HIS for post-hospitalized ACS patients in Indonesia is cost-effective at 31.843.492 IDR per QALY gained.

Assessment of internet-based information on statin therapy

AIMS

The use of statin therapy is deemed to be controversial by mainstream media. Patients increasingly source medical information from the internet, and the use of statins is no exception. This study aims to determine the quality and educational content of statin-focused information on the internet and YouTube.

METHODS AND RESULTS

'Statin' was searched on Google, Yahoo!, Bing, and YouTube. The first 50 results obtained from each search engine and the first 20 YouTube videos were screened by two assessors. Websites were assessed using the Flesch Reading Ease (FRE) score, University of Michigan Consumer Health Website Evaluation Checklist, and a customized scoring system evaluating statin-focused content for quality. Videos were scored using the Journal of the American Medical Association (JAMA) benchmark criteria, Global Quality Score (GQS), and the customized scoring system. Websites scored a median FRE score of 57.5 [interquartile range (IQR) 52.1-62.3], median Michigan score of 36 (IQR 32-41.5), and median content score of 5 (IQR 3.75-7). Good interobserver agreement was demonstrated [Michigan score interobserver coefficient correlation (ICC) = 0.968; content score ICC = 0.944]. Videos scored a median JAMA score of 2, median GQS score of 2.5, and median content score of 2.5. Good interobserver agreement was demonstrated (JAMA ICC = 0.746; GQS ICC = 0.874; content score ICC = 0.946).

CONCLUSION

Quality and readability of statin-focused online information are poor. Healthcare professionals should be aware of the limitations of the current available sources and design online resources that are accurate and patient-friendly.

The Association between Deductibles and Cardiovascular Medication Adherence: A Retrospective Inception Cohort Study

OBJECTIVE

Drug non-adherence in primary preventive cardiovascular therapy is one of the most important modifiable drivers of cardiovascular events. The effect of deductibles in healthcare cost-sharing plans (the amount that has to be paid for healthcare services before the insurance company starts to pay) on such non-adherence in a European setting is unknown. Therefore, we estimated the association between deductibles and the adherence to primary preventive antihypertensive and antihyperlipidemic medication.

METHODS

Using the claims database of Menzis Health Insurer in the Netherlands, we applied ordered beta regression mixed modelling to estimate the association between deductibles and adherence taking several demographic and social-economic factors, repeated measurements and within-patient variation into account.

RESULTS

All in all, 106,316 patients starting primary preventive antihypertensive or antihyperlipidemic monotherapy were eligible for analysis. At index date, mean age of the study population was 58 years and 52% were male. Reaching the deductible limit and no need to pay for medication anymore increased the adherence [relative adherence ratio (RAR) 1.03, 95% confidence interval (95% CI): 1.00-1.05] for antihyperlipidemic therapy and 1.02 (95% CI: 1.00-1.04) for antihypertensive therapy. A larger deductible amount decreases the adherence of antihyperlipidemic and antihypertensive therapy (RAR 0.83; 95% CI: 0.69-1.00 and RAR 0.85, 95% CI: 0.74-0.98, respectively).

CONCLUSION

Independent of other risk factors for non-adherence, presence of deductibles in health insurance is associated with a small negative effect on the adherence to both primary preventive antihypertensive as well as antihyperlipidemic therapy. Further study is needed on the potential health-economic consequences.

Are statins making older persons weaker? A discontinuation study of muscular side effects

Thirteen percent of the Danish population are treated with a statin-half of these are in primary prevention, and most are > 65 years old. Statins have known muscular side effects (i.e., myalgia) correlated to reduced muscle performance. This study examines if years of statin treatment in older people introduce subclinical muscle discomfort and loss of muscle mass and strength. In total, 98 participants (71.1 ± 3.6 years (mean ± SD)), who were in primary prevention treatment for elevated plasma cholesterol with a statin, were included in this study. Statin treatment was discontinued for 2 months and then re-introduced for 2 months. Primary outcomes included muscle performance and myalgia. Secondary outcomes included lean mass and plasma cholesterol. Functional muscle capacity measured as a 6-min walk test increased after discontinuation (from 542 ± 88 to 555 ± 91 m, P < 0.05) and remained increased after re-introduction (557 ± 94 m). Similar significant results were found with a chair stand test (15.7 ± 4.3 to 16.3 ± 4.9 repetitions/30 s) and a quadriceps muscle test. Muscle discomfort during rest did not change significantly with discontinuation (visual analog scale from 0.9 ± 1.7 to 0.6 ± 1.4) but increased (P < 0.05) with the re-introduction (to 1.2 ± 2.0) and muscle discomfort during activity decreased (P < 0.05) with discontinuation (from 2.5 ± 2.6 to 1.9 ± 2.3). After 2 weeks of discontinuation, low-density lipoprotein cholesterol increased from 2.2 ± 0.5 to 3.9 ± 0.8 mM and remained elevated until the re-introduction of statins (P < 0.05). Significant and lasting improvements in muscle performance and myalgia were found at the discontinuation and re-introduction of statins. The results indicate a possible statin-related loss of muscle performance in older persons that needs further examination.

Clinical Characteristics of Patients With Statin Discontinuation in Korea: A Nationwide Population-Based Study

Objective

To investigate the clinical characteristics of patients with statin discontinuation in Korea, using a nationwide database.

Methods

We analyzed 1,308,390 patients treated with statin for the first time in their life between 2016 and 2017 using the Korean National Health Information Database. The patients participated in the Korean National Health Screening Program within two years before taking statin. Patients with statin discontinuation were defined as those who were not prescribed statin between 365 days and 730 days after the initial statin prescription.

Results

The overall prevalence of statin discontinuation was 39.44%. Patients with statin discontinuation were younger, had lower body mass index (BMI), included a higher number of smokers and drinkers, did not exercise regularly, with fewer cases of hypertension and diabetes mellitus than those without statin discontinuation (p<0.001). Compared with patients aged 20-29 years, the risk of statin discontinuation showed a U-shaped relationship with age (odds ratios [ORs]: 0.619 in 30-39 years; 0.454 in 40-49 years; 0.345 in 50-59 years; 0.307 in 60-69 years; 0.324 in 70-79 years; and 0.415 in ≥80 years). In addition, increased BMI was associated with decreased risk of statin discontinuation (ORs: 0.969 with 25.0-29.9 kg/m2, and 0.890 with ≥30.0 kg/m2). Patients with hypertension and diabetes mellitus were at a lower risk of statin discontinuation (OR: 0.414 for hypertension; 0.416 for diabetes mellitus).

Conclusion

The prevalence of patients with statin discontinuation in Korea was 39.44% at 1 to 2 years after initial statin treatment.

Direct oral anticoagulant concentrations and adherence in stroke patients

No therapeutic ranges linking drug concentrations of apixaban and rivaroxaban to clinical outcomes have been defined. We investigated whether direct oral anticoagulant (DOAC) concentrations among patients admitted to hospital with symptoms of stroke differed between those later verified to suffer an ischaemic cerebrovascular event (stroke or transient ischaemic attack) and those having other diagnoses (control group). Serum concentrations in 102 patients on DOAC for atrial fibrillation (84%) and thromboembolic disease (16%) were measured within 24 h of the acute event, employing ultra-high performance liquid chromatography with tandem mass spectrometry. We converted all concentrations to standardized trough levels. DOAC concentrations were lower in the 64 patients with verified ischaemic cerebrovascular event than in the 30 controls, 255 ± 155 versus 329 ± 144 nmol/L (p = 0.029), despite no statistically significant difference in self-reported adherence and daily dosages. Calculated concentrations were 5.4-596 nmol/L (median = 229 nmol/L) in the ischaemic stroke group and 41-602 nmol/L (median = 316 nmol/L) in controls. CHA2 DS2 -VASc score was significantly higher in the ischaemic stroke group than in controls (4.9 ± 1.6 versus 4.1 ± 1.7; p = 0.007). These results may suggest that patients with high cerebrovascular risk might benefit from higher DOAC levels than those with a lower risk.

Don't Judge a Book by Its Cover: The Role of Statins in Liver Cancer

Statins, which are inhibitors of 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, are an effective pharmacological tool for lowering blood cholesterol levels. This property makes statins one of the most popular drugs used primarily to prevent cardiovascular diseases, where hyperlipidemia is a significant risk factor that increases mortality. Nevertheless, studies conducted mainly in the last decade have shown that statins might prevent and treat liver cancer, one of the leading causes of cancer-related mortality worldwide. This narrative review summarizes the scientific achievements to date regarding the role of statins in liver tumors. Molecular biology tools have revealed that cell growth and proliferation can be inhibited by statins, which further inhibit angiogenesis. Clinical studies, supported by meta-analysis, confirm that statins are highly effective in preventing and treating hepatocellular carcinoma and cholangiocarcinoma. However, this effect may depend on the statin's type and dose, and more clinical trials are required to evaluate clinical effects. Moreover, their potential hepatotoxicity is a significant caveat for using statins in clinical practice. Nevertheless, this group of drugs, initially developed to prevent cardiovascular diseases, is now a key candidate in hepato-oncology patient management. The description of new drug-statin-like structures, e.g., with low toxicity to liver cells, may bring another clinically significant improvement to current cancer therapies.

Multivariate Sequential Analytics for Cardiovascular Disease Event Prediction

BACKGROUND

 Automated clinical decision support for risk assessment is a powerful tool in combating cardiovascular disease (CVD), enabling targeted early intervention that could avoid issues of overtreatment or undertreatment. However, current CVD risk prediction models use observations at baseline without explicitly representing patient history as a time series.

OBJECTIVE

 The aim of this study is to examine whether by explicitly modelling the temporal dimension of patient history event prediction may be improved.

METHODS

 This study investigates methods for multivariate sequential modelling with a particular emphasis on long short-term memory (LSTM) recurrent neural networks. Data from a CVD decision support tool is linked to routinely collected national datasets including pharmaceutical dispensing, hospitalization, laboratory test results, and deaths. The study uses a 2-year observation and a 5-year prediction window. Selected methods are applied to the linked dataset. The experiments performed focus on CVD event prediction. CVD death or hospitalization in a 5-year interval was predicted for patients with history of lipid-lowering therapy.

RESULTS

 The results of the experiments showed temporal models are valuable for CVD event prediction over a 5-year interval. This is especially the case for LSTM, which produced the best predictive performance among all models compared achieving AUROC of 0.801 and average precision of 0.425. The non-temporal model comparator ridge classifier (RC) trained using all quarterly data or by aggregating quarterly data (averaging time-varying features) was highly competitive achieving AUROC of 0.799 and average precision of 0.420 and AUROC of 0.800 and average precision of 0.421, respectively.

CONCLUSION

 This study provides evidence that the use of deep temporal models particularly LSTM in clinical decision support for chronic disease would be advantageous with LSTM significantly improving on commonly used regression models such as logistic regression and Cox proportional hazards on the task of CVD event prediction.

Medication adherence prediction through temporal modelling in cardiovascular disease management

Background

Chronic conditions place a considerable burden on modern healthcare systems. Within New Zealand and worldwide cardiovascular disease (CVD) affects a significant proportion of the population and it is the leading cause of death. Like other chronic diseases, the course of cardiovascular disease is usually prolonged and its management necessarily long-term. Despite being highly effective in reducing CVD risk, non-adherence to long-term medication continues to be a longstanding challenge in healthcare delivery. The study investigates the benefits of integrating patient history and assesses the contribution of explicitly temporal models to medication adherence prediction in the context of lipid-lowering therapy.

Methods

Data from a CVD risk assessment tool is linked to routinely collected national and regional data sets including pharmaceutical dispensing, hospitalisation, lab test results and deaths. The study extracts a sub-cohort from 564,180 patients who had primary CVD risk assessment for analysis. Based on community pharmaceutical dispensing record, proportion of days covered (PDC) $$\ge$$ ≥  80 is used as the threshold for adherence. Two years (8 quarters) of patient history before their CVD risk assessment is used as the observation window to predict patient adherence in the subsequent 5 years (20 quarters). The predictive performance of temporal deep learning models long short-term memory (LSTM) and simple recurrent neural networks (Simple RNN) are compared against non-temporal models multilayer perceptron (MLP), ridge classifier (RC) and logistic regression (LR). Further, the study investigates the effect of lengthening the observation window on the task of adherence prediction.

Results

Temporal models that use sequential data outperform non-temporal models, with LSTM producing the best predictive performance achieving a ROC AUC of 0.805. A performance gap is observed between models that can discover non-linear interactions between predictor variables and their linear counter parts, with neural network (NN) based models significantly outperforming linear models. Additionally, the predictive advantage of temporal models become more pronounced when the length of the observation window is increased.

Conclusion

The findings of the study provide evidence that using deep temporal models to integrate patient history in adherence prediction is advantageous. In particular, the RNN architecture LSTM significantly outperforms all other model comparators.

Attainment of low-density lipoprotein cholesterol goals in statin treated patients: real-world evidence from Australia

OBJECTIVE

Little is known about the attainment of low-density lipoprotein cholesterol (LDL-C) targets in patients treated with statins in Australian primary healthcare setting that are at increased risk of cardiovascular disease.

METHODS

A retrospective cohort study was conducted using data from electronic medical records of patients treated by general practitioners across Australia. LDL-C target attainment was defined as LDL-C levels ≤ 2 mmol/L for all risk groups, in line with Australian guidelines. Multivariable logistic regression was used to identify the factors associated with LDL-C target attainment.

RESULTS

Overall, 61,407 patients were included in the analysis. The mean age was 65 years (± standard deviation [SD] 12.1); 52.0% were males.. Overall, the median LDL-C level was 2.3 mmol/L (IQR = 1.8 - 2.8) and 36.0% of the study population met therapeutic targets. Increased likelihood to achieve LDL-C targets was observed in patients diagnosed with type 2 diabetes (OR 2.07, 95% CI 1.92 - 2.24), stroke (OR = 1.58, 95% CI 1.39 - 1.79, p< 0.001) or chronic heart disease (OR = 1.67, 95% CI 1.55 - 1.81, p<0.001). Patients diagnosed with dyslipidaemia (OR = 0.59, 95% CI 0.55 - 0.64, p < 0.001), hypertension (OR = 0.91, 95% CI 0.83 - 1.00, p< 0.05) and current smokers (OR = 0.71, 95% CI 0.71 - 1.00, p <0.05), were less likely to attain LDL-C targets, regardless of the type, intensity and length of use of the prescribed statin.

CONCLUSION

Longer duration and higher intensity statin were associated with more patients achieving targeted LDL-C goal, however nearly two thirds of Australians still failed to achieve targeted outcome even after 24 months of statin therapy.

A Novel Statin Compound from Monacolin J Produced Using CYP102A1-Catalyzed Regioselective C-Hydroxylation

Statins inhibit the 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMG-CoA reductase), which is the rate-limiting enzyme in cholesterol biosynthesis. Statin therapy reduces morbidity and mortality in those who are at high risk of cardiovascular disease. Monacolin J is a statin compound, which is an intermediate in the lovastatin biosynthesis pathway, in the fungus Aspergillus terreus. It is also found in red yeast rice, which is made by culturing rice with the yeast Monascus purpureus. Monacolin J has a hydroxyl substituent at position C’-8 of monacolin L. Here, a new statin derivative from monacolin J was made through the catalysis of CYP102A1 from Bacillus megaterium. A set of CYP102A1 mutants of monacolin J hydroxylation with high catalytic activity was screened. The major hydroxylated product was C-6′a-hydroxymethyl monacolin J, whose structure was confirmed using LC–MS and NMR analysis. The C-6′a-hydroxymethyl monacolin J has never been reported before. It showed a greater ability to inhibit HMG-CoA reductase than the monacolin J substrate itself. Human liver microsomes and human CYP3A4 also showed the ability to catalyze monacolin J in producing the same product of the CYP102A1-catalyzed reaction. This result motivates a new strategy for the development of a lead for the enzymatic and chemical processes to develop statin drug candidates.

Using group-based trajectory modeling to characterize the association of past ACEIs/ARBs adherence with subsequent statin adherence patterns among new statin users

BACKGROUND

Despite well-documented benefits, statin adherence remains suboptimal. Studies have suggested that previous adherence to other chronic medications is a strong predictor of future adherence to newly initiated statins. Group-based trajectory modeling (GBTM) has been applied as a method to longitudinally depict the dynamic nature of adherence.

OBJECTIVES

This study aimed to examine the association between patients' adherence patterns to newly initiated statins and previous adherence trajectories of angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) using GBTM.

METHODS

This retrospective cohort study was conducted among continuously enrolled statin initiators using claims data. Patients were included if they had ACEI/ARB use within 1 year before statin initiation (preindex period). Monthly adherence to ACEIs/ARBs was calculated during the preindex period and monthly adherence to statins was assessed 1 year after statin initiation using proportion of days covered (PDC). The monthly PDCs were modeled as a longitudinal response in a logistic GBTM to provide distinct patterns of adherence for ACEIs/ARBs and statins, separately. A multinomial logistic regression was conducted to determine an association between ACEI/ARB adherence trajectories and future statin trajectories, controlling for patient characteristics.

RESULTS

A total of 1078 patients were categorized into 4 distinct statin adherence trajectories: adherent (40.8%), gradual decline (37.4%), gaps in adherence (13.9%), and rapid decline (7.9%). Patients were further categorized into 4 groups on the basis of their distinct past ACEIs/ARBs trajectories: adherent (43%), gaps in adherence (29%), delayed nonadherence (15.2%), and gradual decline (12.8%). In the multinomial logistic regression, patients in the gaps in adherence or gradual decline groups were more likely to follow similar trajectories for future statin use than the adherent trajectory.

CONCLUSION

Previous adherence trajectories of ACEIs/ARBs may predict future adherence patterns for newly initiated statins. Knowledge of past medication-taking behavior could provide valuable information for developing tailored interventions to improve adherence.

Association between CVDs and initiation and adherence to statin treatment in patients with newly diagnosed hypercholesterolaemia: a retrospective cohort study

OBJECTIVES

To evaluate the association between incident cardiovascular disease (CVD) and initiation and adherence to statin treatment for primary prevention of CVD in patients with newly diagnosed hypercholesterolaemia.

DESIGN

A population-based retrospective cohort study.

SETTING

This study used National Health Insurance Service-Health Screening Cohort (NHIS-HEALS) from Republic of Korea.

PARTICIPANTS

This study included 11 320 participants without previous history of CVD aged between 40 and 79 years who had elevated total cholesterol level (more than 240 mg/dL) and had initiated statin treatment within 24 months of the national health screening from 2004 to 2012 identified in the NHIS-HEALS.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome, CVD, was defined as first-ever admission or death due to ischaemic heart disease, acute myocardial infarction, revascularisation or stroke, or December 31 2013. The HRs of CVD according to statin adherence were calculated according to stratification by Systematic COronary Risk Evaluation.

RESULTS

Early statin initiation significantly lowered risk of CVD outcomes compared with late initiation (HR of late statin user, 1.24; 95% CI 1.02 to 2.51). Among early initiators, statin discontinuers had a significantly higher risk for CVD compared with persistent users (HR, 1.71; 95% CI 1.10 to 2.67), while statin reinitiators had an attenuated risk increase (HR 1.34, 95% CI 0.79 to 2.30).

CONCLUSIONS

Among statin users with newly diagnosed hypercholesterolaemia, early statin initiation is associated with lower CVD risk compared with late initiation. Furthermore, statin discontinuation is associated with increased risk of CVD, but reinitiation attenuated the risk.