Improve Statin Adherence Research Articles

Strategies aiming to improve statin therapy adherence in older adults: a systematic review

BackgroundRandomized clinical trials have shown that, under optimal conditions, statins reduce the risk of cardiovascular events in older adults. Given the prevalence and consequences of suboptimal adherence to statin among older adults, it is essential to document strategies designed to increase statin adherence in this population. The objective of this systematic review is to describe and summarize the effectiveness of interventions to improve statin adherence in older adults (≥ 65 years old).MethodsThis review followed PRISMA guidelines. Studies were identified from PubMed, PsycINFO, Embase, CINAHL and Web of Science. Study selection was conducted independently by four reviewers working in pairs. Included studies reported data on interventions designed to increase adherence to statin therapy in older adults and were original trials or observational studies. Interventions were pragmatically regrouped into 8 different categories going from patient to administrative level. Two reviewers extracted study data and assessed study quality independently. Given the heterogeneity between the included studies, a narrative critique and summary was conducted.ResultsTwelve out of the 2889 identified articles were included in the review. Our review showed that simplifying patients’ drug regimen, administrative improvements and large-scale pharmacy-led automated telephone interventions show positive effects on patient adherence to statin therapy, with odds ratios between > 1.0 and 3.0, while education-based strategies and intensified patient care showed mixed results.ConclusionsCurrent evidence suggests that some interventions can increase statin adherence in older adults, which could help in the reduction of the risk of a cardiovascular event in this population.

Telephone-based social health screening by pharmacists in the nonadherent Medicare population.

BACKGROUND: Unmet social health needs are associated with medication nonadherence. Although pharmacists are well positioned to address medication nonadherence, there is limited experience with screening for and addressing social health needs. OBJECTIVES: To compare the prevalence of social health needs among Medicare patients with higher vs lower social health risk using a predictive model. To also evaluate pre-post changes in medication adherence and health care use following a pharmacist-initiated social health screening. METHODS: A social health screening workflow was implemented into a routine pharmacist adherence program at an integrated health care delivery system. The social health screening was conducted during medication adherence outreach phone calls with Medicare members who were overdue for statin, blood pressure, or diabetes medications. We developed a social health need predictive algorithm to flag higher-risk patients and tested this algorithm against a random subset of lower-risk patients. Screening conversations were guided by a focus group that developed open-ended questions to identify social health needs. Comparisons in social health needs were made between higher- and lower-risk patients. Use and adherence outcomes were compared pre and post for patients who accepted a referral to social health resources and patients who declined a referral. RESULTS: 1,217 patients were contacted and screened for social health needs by pharmacists. Patients flagged by the social risk algorithm were more likely to report social health needs (28.7% vs 12.7% in the unflagged group; P < 0.01). Commonly reported needs included transportation (43%), finances (34%), caregiving (22%), mental health (11%), and food access (10%). 221 patients accepted a referral to a central resource website and call center that connected patients to local services. One year after screening dates, patients who did not accept a referral spent more time in the hospital (mean change +0.7 days, SD = 7.3, P < 0.01), had fewer primary care visits (mean change -0.5 visits, SD = 6.5, P < 0.01), and had a shorter length of membership (mean change -0.4 months, SD = 1.9, P < 0.01). Patients who accepted a referral had increased statin adherence (62.3% adherent pre vs 74.7% post, P = 0.02). CONCLUSIONS: We implemented a workflow for pharmacists to screen for social health needs. The social health need prediction model doubled the identification rate of patients who have needs. Intervening on social health needs during these calls may improve statin adherence and may have no adverse effect on health care utilization or health plan membership. DISCLOSURES: Social health risk predictive model development and validation was funded by the Agency for Healthcare Research and Quality (AHRQ R18HS027343).

What is the Statin Possession Ratio Cut-Off Which Identifies Those at Increased Risk Following Acute Coronary Syndrome (ANZACS-QI 68)?

More optimal dispensing of statins is associated with greater cholesterol lowering; however, it is not known whether this translates to improved outcomes following acute coronary syndrome (ACS). The aim of this study was to assess the association between various levels of statin adherence and outcomes following ACS. Patients hospitalised with ACS who underwent coronary angiography between 2014-2018 were identified from the All New Zealand ACS Quality Improvement (ANZACS-QI) registry. Medication possession ratio (MPR) was used to assess statin adherence and calculated over 1 year post-discharge using linked pharmaceutical dispensing datasets. Optimal, adequate and suboptimal adherence was defined as an MPR of ≥1.0, 0.8-0.99 and 0-0.79, respectively. A combined outcome of all-cause mortality and rehospitalisation for atherosclerotic disease was identified from 1 year post-discharge through September 2021. Cox proportional hazard models were used to adjust for confounding variables. Of the 30,452 patients, 68% had optimal adherence, 15% adequate adherence and 16% had suboptimal adherence to statins. Mean follow-up was 3.6 years. Those with suboptimal adherence had a higher adjusted risk of the combined outcome compared with those with optimal adherence (HR 1.18, 95% CI 1.11-1.26). There was no significant difference in adjusted outcome between those with optimal and adequate adherence (HR 0.99, 95% CI 0.92-1.06). Suboptimal statin adherence following ACS is associated with an increased risk of mortality and rehospitalisation. An MPR cut-off of 0.8 seems reasonable to identify those at higher risk of cardiovascular events that could benefit the most from interventions to improve statin adherence and is appropriate as a target for quality improvement programs.

318 Optimizing the Identification and Prediction of Statin Intolerance to Improve Statin Adherence Using Natural Language Processing and Machine Learning

OBJECTIVES/GOALS: Aim1: To develop a natural language processing (NLP) algorithm to effectively identify statin associated muscle symptoms (SAMS) in patients’electronic health records (EHRs). Aim2: To develop a machine learning model based on clinical features within EHRs that predict the likelihood of SAMS occurrences. METHODS/STUDY POPULATION: A retrospective cohort of adult patients initiated on statins within the Minnesota Fairview Healthcare System EHRs from 2010 to 2020 will be analyzed. NLP-PIER (Patient Information Extraction for Research) platform will be used to search and identify patients who developed SAMS after statin initiation. Manual annotation of clinical notes will be completed to validate the accuracy of identified SAMS cases. Then, a selection of clinical features within the EHRs will be input as predictors for machine learning algorithms development. Select machine learning classifiers will be deployed to generate models for the prediction of SAMS and the best-performing model will be selected based on model performance. RESULTS/ANTICIPATED RESULTS: The expected outcomes include generation of a fine-tuned NLP algorithm that can rigorously identify SAMS occurrences within EHRs. Further, we anticipate having a practical risk model that accurately predicts patients’risks of developing SAMS when taking statins. DISCUSSION/SIGNIFICANCE: The positive and translational impact of our research will be to equip healthcare providers with such informatics tools to improve statin adherence, ultimately promoting patient optimal health and outcomes by maximizing the tolerance and thus realizing the therapeutic benefits of statins.

A shared decision‐making intervention by pharmacy students to improve statin adherence

AbstractIntroductionDespite the well‐established value of statins in reducing cardiovascular events, nearly half of patients fail to receive maximum benefit due to nonadherence. Studies indicate that motivational interviewing (MI) by pharmacy students can improve statin adherence. The benefit of incorporating an individualized approach, including shared‐decision making (SDM), is unknown, as is the student‐perceived value of this activity in their professional development.ObjectivesTo (a) measure the effect of an individualized telephone intervention conducted by pharmacy students in improving statin adherence and (b) assess the self‐reported value of intervention participation to guide continual quality improvement.MethodsA prospective, quality‐improvement project was conducted among patients receiving care at a university‐based healthcare system through a commercial or Medicare Advantage plan. Pharmacy claims data identified nonadherent patients based on a six‐month proportion of days covered (PDC) &lt;0.80 for statin prescriptions. A sample of these patients was randomly selected to receive the intervention from July 2019 to April 2020, while remaining patients served as controls. The intervention included 1‐2 telephone calls by pharmacy students to deliver individualized evidence‐based education, including SDM and MI strategies. Mean PDC change and proportion of patients converted to adherent (PDC≥0.80) were evaluated 6 months post‐intervention using the intention‐to‐treat principle.ResultsThere were 58 patients in the intervention group, 52 of whom (90%) received at least one telephone call, and 82 controls. Six months post‐intervention mean PDC increased significantly in the intervention vs control group (12.8% vs 0.7%, P = .004), and 66% of the intervention group were adherent compared to 41% of controls [P = .005, adjusted OR = 2.46 (1.20‐5.05)]. Seven students participated in the intervention, with 83% of survey responders reporting positive professional development value during the experience.ConclusionPharmacy trainees may successfully deliver individualized interventions capable of improving statin adherence while positively contributing to their professional development.

Systematic Review of RCTs Assessing the Effectiveness of mHealth Interventions to Improve Statin Medication Adherence: Using the Behaviour-Change Technique Taxonomy to Identify the Techniques That Improve Adherence.

Statin non-adherence is a common problem in the management of cardiovascular disease (CVD), increasing patient morbidity and mortality. Mobile health (mHealth) interventions may be a scalable way to improve medication adherence. The objectives of this review were to assess the literature testing mHealth interventions for statin adherence and to identify the Behaviour-Change Techniques (BCTs) employed by effective and ineffective interventions. A systematic search was conducted of randomised controlled trials (RCTs) measuring the effectiveness of mHealth interventions to improve statin adherence against standard of care in those who had been prescribed statins for the primary or secondary prevention of CVD, published in English (1 January 2000–17 July 2020). For included studies, relevant data were extracted, the BCTs used in the trial arms were coded, and a quality assessment made using the Risk of Bias 2 (RoB2) questionnaire. The search identified 17 relevant studies. Twelve studies demonstrated a significant improvement in adherence in the mHealth intervention trial arm, and five reported no impact on adherence. Automated phone messages were the mHealth delivery method most frequently used in effective interventions. Studies including more BCTs were more effective. The BCTs most frequently associated with effective interventions were “Goal setting (behaviour)”, “Instruction on how to perform a behaviour”, and “Credible source”. Other effective techniques were “Information about health consequences”, “Feedback on behaviour”, and “Social support (unspecified)”. This review found moderate, positive evidence of the effect of mHealth interventions on statin adherence. There are four primary recommendations for practitioners using mHealth interventions to improve statin adherence: use multifaceted interventions using multiple BCTs, consider automated messages as a digital delivery method from a credible source, provide instructions on taking statins, and set adherence goals with patients. Further research should assess the optimal frequency of intervention delivery and investigate the generalisability of these interventions across settings and demographics.

Interventions to Improve Statin Tolerance and Adherence in Patients at Risk for Cardiovascular Disease : A Systematic Review for the 2020 U.S. Department of Veterans Affairs and U.S. Department of Defense Guidelines for Management of Dyslipidemia.

Strategies to improve patients' tolerance of and adherence to statins may enhance the effectiveness of dyslipidemia treatment in those at risk for cardiovascular disease (CVD). To assess the benefits and harms of interventions to improve statin adherence in patients at risk for CVD. MEDLINE, EMBASE, PubMed, and the Cochrane Library from December 2013 through May 2019 (English language only). Systematic reviews (SRs), randomized controlled trials (RCTs), and cohort studies that addressed interventions for improving statin tolerance and adherence. One investigator abstracted data and assessed study quality, and a second investigator checked abstractions and assessments for accuracy. One SR, 1 RCT, and 4 cohort studies were included. The SR found that intensified patient care improved adherence and decreased levels of total serum cholesterol and low-density lipoprotein cholesterol (LDL-C) at 6 months or more of follow-up. Compared with statin treatment discontinuation, nondaily statin dosing lowered total cholesterol and LDL-C levels. One large cohort study suggested that more than 90% of patients who discontinued statin treatment could be rechallenged with the same or a different statin and be adherent 1 year after a statin-related adverse event led to discontinuation. Two small cohort studies reported that more than 90% of patients who were previously intolerant to statins and who had low baseline levels of vitamin D were able to adhere to statins 1 year after vitamin D supplementation. This is a qualitative synthesis of new evidence with existing meta-analyses, and studies had several methodological shortcomings. Although the strength of evidence for most interventions was low or very low, intensified patient care and rechallenge with the same or a different statin (or a lower dose) seem to be favorable options for improving statin adherence. U.S. Department of Veterans Affairs.

Evaluating trajectories of statin adherence after a motivational interviewing intervention

ObjectiveThe objective of the current study was to compare postintervention adherence trajectories with preintervention trajectories for those receiving a telephonic motivational interviewing (MoI) intervention to determine predictors associated with each distinct postintervention trajectory and any association between pre- and postintervention trajectories. DesignRetrospective study design using group-based trajectory modeling. Settings and participantsA telephonic MoI intervention was conducted by trained student pharmacists to improve statin adherence in a Medicare Advantage plan. Four preintervention adherence trajectories were previously identified: rapid decline (RD), gradual decline (GD), gaps in adherence (GA), and adherent and were used to customize the MoI intervention. Patients from the 3 nonadherent preintervention trajectories were randomized to control or intervention groups and were followed for 6 months from the date of MoI intervention. Outcome measuresGroup-based trajectory modeling was performed to identify 3 relevant postintervention trajectories. Descriptive statistics were used to assess differences in pre- and postintervention adherence trajectories. Multinomial logistic regression was conducted to determine predictors associated with each identified postintervention trajectory. ResultsThere were 152 intervention patients and 304 randomly selected controls. The prominent postintervention trajectories that were identified differed from the preintervention trajectories and were (1) GD (17.2%), (2) adherent (61.9%), and (3) discontinuation (20.9%). Among the intervention group, more patients in the GA preintervention trajectory (58.65%) moved to the adherent trajectory postintervention than those in the RD and GD preintervention trajectories. Furthermore, the predictors associated with the postintervention trajectories included MoI intervention, prescriber specialty, presence of diabetes, presence of congestive heart failure, Centers for Medicare & Medicaid Services risk score, and preintervention trajectories. ConclusionThe postintervention adherence trajectory patterns differed from the preintervention trajectory patterns with many patients moving into an adherent trajectory especially among those receiving the intervention.

Risk factors affecting the failed low-density lipoprotein level achievement rate in working-age male population at high cardiovascular risk.

The aim of this study was to clarify the low-density lipoprotein (LDL)-C level achievement rate and detect factors affecting the failed LDL-C achievement rate in patients treated with statins and anti-platelet agents using a large insurance claim database and health check-up data. Access to a large health insurance claims database, and health check-up data were obtained from Japan Medical Data Center (JMDC) Co. Ltd., Tokyo. The database was searched to identify employed working-age male patients who had started treatment with statin and anti-platelet drugs for the secondary prevention of cardiovascular events. These patients were enrolled in the retrospective cohort study, which included screening at 3months and observation for 3years. LDL-C levels were obtained from the annual health check-up data. The achievement rate for LDL-C<100 was assessed for three consecutive years. Adherence was assessed using the proportion of days covered (PDC) for the statin, which was calculated from prescription data over a 3-year period. Overall, 294 patients (male/female, 294/0; age, 47.8±6.0years; body mass index, 24.8±4.2kg/m2 ; hypertension, 76.2%; and diabetes mellitus, 20.4%) were included. The LDL-C achievement rate for three consecutive years after starting treatment with statin and aspirin was 49.7%, 51.4% and 45.9%, respectively. Factors affecting failed LDL-C on adjusted odds were lower adherence to PDC [0.96 (0.94-0.99), P<0.001, 1% increase] and higher baseline LDL-C [1.01 (1.00-1.02), P=0.037, 1mg/dL increase]. Our results suggest that in the working-age male population need to improve statin adherence, especially those with higher baseline LDL-C levels.

PDB121 EVALUATING INTERVENTION TRAJECTORIES OF STATIN ADHERENCE FOLLOWING A MOTIVATIONAL-INTERVIEWING INTERVENTION CUSTOMIZED BY PAST ADHERENCE TRAJECTORIES TO IMPROVE STATIN ADHERENCE

Group-based trajectory modeling depicts longitudinal adherence over time, overcoming some limitations of proportion of days covered (PDC). Adherence to statins remains sub-optimal despite its effectiveness in improving cardiovascular outcomes. A telephonic Motivational Interviewing Intervention (MoI) was conducted by trained pharmacy students to improve statin adherence in a Medicare Advantage Plan. Four adherence trajectories were identified in the one-year pre-intervention period including: rapid decline (RD), gradual decline (GD), gaps in adherence (GA) and adherent. These trajectories were used to customize the MoI intervention. The objective was to evaluate post-intervention adherence trajectories as compared to pre-intervention trajectories for those receiving the MoI. Patients from the 3 non-adherent pre-intervention trajectories were randomized to control or intervention. Patients who received the intervention and randomly selected controls were followed for six months from the date of the initial counseling. Monthly PDCs were calculated during the 6-month follow-up and dichotomized with PDC ≥ 0.8 considered as adherent. Logistic group-based trajectory modeling on PDC was performed on the intervention and controls to identify three relevant post-intervention trajectories. Descriptive statistics were performed to assess differences in pre and post-intervention adherence trajectories. There were 151 intervention patients and 310 randomly selected controls. Post-intervention trajectories identified were, (1) GD (24.3%) (2) adherent (58.3%) and (3) discontinuation (17.57%) respectively. More patients in the intervention group as compared to the control group were in the adherent trajectory post-intervention (66.89% vs 53.87%) (p= 0.007). Similarly, fewer discontinuations were observed with the intervention group (11.92% vs 20.32%) (p= 0.02). Further, more patients in the GA pre-intervention trajectory (75.6% intervention, 68.9% controls) moved to the adherent trajectory post-intervention indicating greater benefits of intervention to this patient subgroup. The post-intervention adherence trajectory patterns were simpler than the pre-intervention trajectory patterns with many patients moving into an adherent trajectory especially among those receiving the intervention.

It's Not Too Late to Improve Statin Adherence: Association Between Changes in Statin Adherence from Before to After Acute Myocardial Infarction and All-Cause Mortality.

BackgroundMany older patients have a change in statin adherence—either an increase or a decrease—from before to after an acute myocardial infarction (AMI), but its association with mortality is unknown.Methods and ResultsUsing Medicare administrative claims, a cohort of patients ≥66 years old with an AMI hospitalization from 2008 to 2010 was assembled. Statin adherence was measured for 180 days pre‐AMI and 180 days post‐AMI and categorized as severely nonadherent, moderately nonadherent, or adherent. Categorical change in statin adherence from pre‐ to post‐AMI was assessed. Patients were then followed for up to 18 months for all‐cause mortality. A Cox proportional hazards model was applied to estimate the effects of statin adherence change on all‐cause mortality, adjusted for patient baseline characteristics. Of 101 011 eligible patients, 20% had a categorical increase in adherence, 16% decreased, and 14% remained nonadherent both pre‐ and post‐AMI. Compared with patients who were always severely nonadherent (both pre‐ and post‐AMI), patients whose adherence increased from severely nonadherent to adherent (hazard ratio=0.83; 95% CI: 0.75–0.92) and patients who were always adherent (hazard ratio=0.88; 95% CI: 0.82–0.94) were less likely to die; patients whose adherence decreased from moderately nonadherent to severely nonadherent were more likely to die (hazard ratio=1.11; 95% CI: 1.01–1.22).ConclusionsAfter an AMI, patients with decreased statin adherence had the worst mortality outcomes. However, patients with increased statin adherence had a similar risk of mortality compared with continuously adherent patients, suggesting that, even after an AMI, it is not too late to improve statin adherence.

Predictors of first-year nonadherence and discontinuation of statins among older adults: a retrospective cohort study.

The aim of this study was to examine the level of and predictors of statin nonadherence and discontinuation among older adults. Among 22 340 Australians aged ≥65 years who initiated statin therapy from January 2014 to December 2015, we estimated the first-year nonadherence (proportion of days covered [PDC] <0.80) and discontinuation (≥90 days without statin coverage) rates. Predictors of nonadherence and discontinuation were examined via multivariable logistic regression. Analyses were performed separately for general beneficiaries (with a higher co-payment; n=4841) and concessional beneficiaries (with a lower co-payment; n=17 499). During the one-year follow-up, 55.1% were nonadherent (concessional 52.6%; general beneficiaries 64.2%) and 44.7% discontinued statins (concessional 43.1%; general beneficiaries 50.4%). Among concessional beneficiaries, those aged 75-84 years and ≥85 years were more likely to discontinue than people aged 65-74 years (odds ratio 1.11, 95% confidence interval 1.04-1.19 and 1.38, 1.23-1.54, respectively). Diabetes was associated with an increased likelihood of nonadherence and discontinuation, while hypertension, angina and congestive heart failure were associated with a lower likelihood of nonadherence and discontinuation. Anxiety was associated with an increased likelihood of discontinuation, but polypharmacy (concurrent use of five or more drugs) was associated with a lower likelihood of nonadherence and discontinuation. Statin initiation by a general medical practitioner was associated with both increased likelihood of nonadherence and discontinuation. Similar predictors of nonadherence and discontinuation were identified for the general beneficiaries. Among older adults prescribed statins, first-year nonadherence and discontinuation are high. Specific population subgroups such as people aged ≥85 years, those with diabetes or anxiety may require additional attention to improve statin adherence.

What are the effective strategies to improve statin adherence in patients with post–myocardial infarction?

Long, Jackson MD; Patel, Achint MD; Lake, Christopher MD; Nymberg, Jerome MD Author Information

Preventable statin adverse reactions and therapy discontinuation. What can we learn from the spontaneous reporting system?

ABSTRACTBackground: Statin treatment is often associated with poor adherence, which may be due to the onset of adverse drug reactions (ADRs). We investigated on potential risk factors related to preventable cases of statin-induced ADRs and to the discontinuation of statin therapy.Methods: We performed a study using the database of Italian spontaneous reporting. The target population for the preventability assessment was all patients with suspected statin-induced ADRs deriving from Campania Region (a territory of Southern Italy) between 2012 and 2017. Additionally, a local sentinel surveillance site involving General Practitioners was selected to countercheck in routine clinical practice the role of ADRs for statin discontinuation.Results: In total, 34 of 655 (5.19%) regional cases were preventable and among detected risk factors 90.0% was related to healthcare professionals’ practices and 10.0% to patient behaviour. In 81.4% (533/655) of cases, statin therapy was discontinued due to ADRs, mainly classified as not serious and associated with a positive prognosis. These results were also confirmed in the active sentinel site.Conclusions: Our findings suggest an inappropriate use of statins among the identified preventable cases and a potential inappropriate statin discontinuation due to ADRs. These factors may be useful for targeting interventions to improve statin adherence.

Abstract MP74: It's Not Too Late to Improve Adherence: Association Between All-Cause Mortality and Statin Adherence Change After Acute Myocardial Infarction

Introduction: Hospitalization for acute myocardial infarction (AMI) affects medication adherence in prevalent statin users. Our objective was to estimate the association between changes in statin adherence and all-cause mortality after AMI discharge. Hypothesis: Patients who are adherent both pre- and post-AMI have the lowest risk of all-cause mortality. Methods: Medicare administrative claims were used to identify AMI hospitalizations in 2008-2010. Patients were ≥66 years old, continuously enrolled ≥360 days pre-AMI with a statin prescription claim, discharged to home/self-care, and survived ≥180 days post-AMI with continuous enrollment. Statin adherence was measured in the 180 days pre- and post-AMI hospitalization using proportion of days covered and categorized as severely nonadherent, moderately nonadherent, and adherent. The exposure was categorical change in statin adherence from pre- to post-AMI (9 categories, see Figure); adherent/adherent was the reference group. Patients were followed for all-cause mortality from 180 days post-discharge for up to 18 months. A multivariable Cox proportional hazards model estimated hazard ratios (HRs). Results: Of 101,011 eligible patients, 15% decreased, 20% increased, and 64% did not change statin adherence categories. Compared to patients who were adherent pre- and post-AMI, the adjusted HR (95% confidence intervals [CIs]) for patients who increased from severely nonadherent to adherent was 0.93 (95% CI: 0.85-1.02); other increases in adherence had similar HRs (see Figure). Compared to patients who were adherent pre- and post-AMI, the adjusted HR for patients who decreased from adherent to severely nonadherent was 1.22 (95% CI: 1.13-1.33); other decreases in adherence had similar HRs. Conclusions: Although patients with decreased statin adherence had the worst mortality outcomes, those with increased adherence had similar or better outcomes than continuously adherent patients, showing that, even after an AMI, it is not too late to improve statin adherence.

Evaluation of the Effectiveness of a Patient-Centered Educational Mailer Designed to Improve Statin Adherence: A Pragmatic Trial.

Background:Patients with high total cholesterol have increased risk of cardiovascular disease. National Cholesterol Education Program (NCEP) and American Heart Association (AHA) guidelines recommend cholesterol lowering with statin medications; however, statin adherence remains poor. We hypothesized that patient-centered education on the 10-year risk for each of the major constituents of cardiovascular disease would increase statin adherence and achievement of the low-density lipoprotein cholesterol (LDL-C) goal.Methods:Veterans within the Salt Lake City Veterans Affairs (VA) Medical Center initiating statin therapy from October 2008 to December 2011 were randomized in a pragmatic design to receive either an educational mailer or usual care. The mailer outlined their 10-year global cardiovascular risk, separated into coronary heart disease, stroke, and congestive heart failure. The study was unblinded and followed an intention-to-treat analysis where outcome measures were obtained during normal care process. The primary outcome measure was the achievement of the LDL-C goal during the 12-month follow-up.Results:Two hundred and seven patients were randomly assigned to either the intervention arm (95) or the control arm (112). No differences in the proportion of patients meeting the LDL-C goal were detected during 12-months [Relative Risk (RR): 0.95 (95 percent confidence interval (CI): 0.77–1.17)] or 18-months [RR: 1.03 (95 percent CI: 0.84, 1.25)]. Patients in the intervention arm had higher adherence on average, e.g., intervention patients were more likely to have 70 percent or more days of statin therapy compared to patients who received standard care—though this did not reach statistical significance—RR: 1.33 (95 percent CI: 1.00, 1.78). There were no statistical differences in cardiovascular outcomes or mortality.Conclusion:Patient education mailers sent to patients starting statin treatment did not have a clear impact on LDL-C goal achievement or adherence to statin therapy.

Comprehensive efforts to increase adherence to statin therapy.

Previous work from the European Society of Cardiology (ESC), the European Atherosclerosis Society (EAS) and from other groups has addressed the benefits of statin treatment in different patient populations.1–4 Unfortunately, adherence to guideline-recommended statin therapy is suboptimal: Statins are underused and LDL cholesterol targets are not met in up to 80% of high-risk patients.5–7 Excellent reviews have recently been published on the issue of statin intolerance and some lay media as well strongly emphasize this issue.8 True and verified statin intolerance, however, is uncommon and is not the main reason for poor adherence to statin treatment. Because poor adherence to statin treatment in turn is extremely common, it appears necessary to discuss the problem of statin adherence in a broader context and to develop strategies to overcome it. This clinically important task has not yet been the focus of a review or practice recommendation and therefore is the aim of the present position paper from the ESC working group on Cardiovascular Pharmacotherapy. This work takes the position that statin therapy is underutilized because of non-adherence not solely related to statin side effects and proposes steps to be taken in cardiovascular practice to improve statin adherence and thus cardiovascular outcomes. Our article aims to highlight the scientific background that helps to (i) overcome statin non-adherence by definition and description of true adverse statin effects, (ii) increase statin adherence by changing reservation against lipid lowering in media and the public, and (iii) guide efforts in the scientific community to close the gap between knowledge and practice of lipid management. Although statins are generally well-tolerated, statin adherence is poor in clinical practice: A survey of statin prescription claims showed a 30% discontinuation rate within the first year following initial prescription for primary prevention in USA.9 Data from the Danish …

Abstract 12183: SLCO1B1 Genotype-Guided Statin Therapy Lowers LDL Cholesterol in Patients With Statin-Intolerance- A Randomized Controlled Trial

Introduction: Statin-intolerance is a barrier to reducing cardiovascular disease risk. A genetic variant (*5, rs4149056) in the SLCO1B1 statin hepatic transporter gene is well characterized and linked to higher statin concentrations, statin-intolerance, and statin non-adherence. SLCO1B1*5 has a high negative predictive value for severe simvastatin myopathy; Pravastatin[P]/ fluvastatin[F]/ rosuvastatin[R] are preferred statins in *5 carriers to minimize side effects. The effects of SLCO1B1 genotype-guided statin therapy or delivery of SLCO1B1 genetic risk information are unknown. Hypothesis: Genotype-guided statin therapy (GGST) is superior to usual care in patients with statin-intolerance for statin-related outcomes. Methods: We randomly assigned 159 primary care patients with statin intolerance not prescribed statins to either GGST vs. usual care. GGST patients and their providers received *5 genetic risk information about statin side effects and genotype-specific statin prescription recommendations. Patients in the usual care arm received general information regarding statin risk and prescriptions. The outcomes measured at 3 and 8 months were statin re-initiation, LDL cholesterol (LDLc), and statin adherence using the validated Morisky Medication Adherence Survey. Results: The median age was 64.0 years, 57% were female, 41% reported intolerance to &gt; 1 statin, 75% reported myalgia with statins, and 25% were *5 carriers. Follow up was complete for 144 patients (91%) at 3-months and 118 (74%) at 8-months. At 3-months, GGST was associated with a higher proportion of patients who restarted statin therapy (55.4% vs. 38.0%, p=0.037), and lower LDLc (131.9±42.0 vs. 144.4±43.0, p=0.041), but similar statin adherence scores (p=0.96). Effects at 8-months were consistent with 3-month results for statin prescriptions (54% vs. 37%, p=0.07) and LDLc (128.6±37.9 vs. 141.0±44.4, p=0.07). Use of P/F/R was higher in *5 carriers assigned to GGST versus usual care (92% vs. 67%, p=0.24). Conclusion: In primary care patients with statin-intolerance, SLCO1B1 genotype guided statin therapy is effective in lowering LDLc compared to usual care. GGST, however, did not improve statin adherence in those who re-initiated statin therapy.

Statin Adherence: Does Gender Matter?

Cardiovascular disease (CVD) continues to be the leading cause of death for men and women in the USA. Statins have contributed significantly to noted declines in cardiovascular-related mortality in the last decade; however, the benefit of statins is inequitable across genders. Women continue to be less likely to take statins and to meet target LDL goals than men. As a possible contributing factor to this disparity, we explore the evidence for gender-based differences in provision of, and adherence to statins. Compared with men, women are less likely to adhere to statins. Potential reasons for this gender difference in use of statins can be observed across all phases of adherence including both intentional and unintentional non-adherence. Notable gender-specific contributing factors for statin non-adherence include decreased provider and patient awareness of CVD risk among women, higher risk of statin intolerance among women, and competing demands associated with family caregiving responsibilities. Similar to limitations in the broader CVD literature, there is inadequate inclusion of gender-specific analyses in statin-related trials. Gender-based disparities in statin adherence can be linked to both provider level, psychosocial, and medication intolerance factors. Interventions designed to improve statin adherence should take gender-specific challenges into consideration such as women being older at the time of increased CVD risk, higher rates of statin intolerance, and potentially greater caregiving responsibilities.

Patient-Centered Interventions to Improve Adherence to Statins: A Narrative Synthesis of Systematically Identified Studies

Poor adherence to statins increases cardiovascular disease risk. We systematically identified 32 controlled studies that assessed patient-centered interventions designed to improve statin adherence. The limited number of studies and variation in study characteristics precluded strict quality criteria or meta-analysis. Cognitive education or behavioural counselling delivered face-to-face multiple times consistently improved statin adherence compared with control groups (7/8 and 3/3 studies, respectively). None of four studies using medication reminders and/or adherence feedback alone reported significantly improved statin adherence. Single interventions that improved statin adherence but were not conducted face-to-face included cognitive education in the form of genetic test results (two studies) and cognitive education via a website (one study). Similar mean adherence measures were reported for 17 intervention arms and were thus compared in a sub-analysis: 8 showed significantly improved statin adherence, but effect sizes were modest (+7 to +22 % points). In three of these studies, statin adherence improved despite already being high in the control group (82–89 vs. 57–69 % in the other studies). These three studies were the only studies in this sub-analysis to include cognitive education delivered face-to-face multiple times (plus other interventions). In summary, the most consistently effective interventions for improving adherence to statins have modest effects and are resource-intensive. Research is needed to determine whether modern communications, particularly mobile health platforms (recently shown to improve medication adherence in other chronic diseases), can replicate or even enhance the successful elements of these interventions while using less time and fewer resources.Electronic supplementary materialThe online version of this article (doi:10.1007/s40265-016-0640-x) contains supplementary material, which is available to authorized users.