Communicating personalised statin therapy-effects as 10-year CVD-risk or CVD-free life-expectancy: does it improve decisional conflict? Three-armed, blinded, randomised controlled trial.

OBJECTIVE: To determine whether communicating personalised statin therapy-effects obtained by prognostic algorithm leads to lower decisional conflict associated with statin use in patients with stable cardiovascular disease (CVD) compared with standard (non-personalised) therapy-effects. DESIGN: Hypothesis-blinded, three-armed randomised controlled trial SETTING AND PARTICIPANTS: 303 statin users with stable CVD enrolled in a cohort INTERVENTION: Participants were randomised in a 1:1:1 ratio to standard practice (control-group) or one of two intervention arms. Intervention arms received standard practice plus (1) a personalised health profile, (2) educational videos and (3) a structured telephone consultation. Intervention arms received personalised estimates of prognostic changes associated with both discontinuation of current statin and intensification to the most potent statin type and dose (ie, atorvastatin 80 mg). Intervention arms differed in how these changes were expressed: either change in individual 10-year absolute CVD risk (iAR-group) or CVD-free life-expectancy (iLE-group) calculated with the SMART-REACH model (http://U-Prevent.com). OUTCOME: Primary outcome was patient decisional conflict score (DCS) after 1 month. The score varies from 0 (no conflict) to 100 (high conflict). Secondary outcomes were collected at 1 or 6 months: DCS, quality of life, illness perception, patient activation, patient perception of statin efficacy and shared decision-making, self-reported statin adherence, understanding of statin-therapy, post-randomisation low-density lipoprotein cholesterol level and physician opinion of the intervention. Outcomes are reported as median (25th- 75th percentile). RESULTS: Decisional conflict differed between the intervention arms: median control 27 (20-43), iAR-group 22 (11-30; p-value vs control 0.001) and iLE-group 25 (10-31; p-value vs control 0.021). No differences in secondary outcomes were observed. CONCLUSION: In patients with clinically manifest CVD, providing personalised estimations of treatment-effects resulted in a small but significant decrease in decisional conflict after 1 month. The results support the use of personalised predictions for supporting decision-making. TRIAL REGISTRATION: NTR6227/NL6080.

Prediction of individualized lifetime benefit from cholesterol lowering, blood pressure lowering, antithrombotic therapy, and smoking cessation in apparently healthy people.

AIMS: The benefit an individual can expect from preventive therapy varies based on risk-factor burden, competing risks, and treatment duration. We developed and validated the LIFEtime-perspective CardioVascular Disease (LIFE-CVD) model for the estimation of individual-level 10 years and lifetime treatment-effects of cholesterol lowering, blood pressure lowering, antithrombotic therapy, and smoking cessation in apparently healthy people. METHODS AND RESULTS: Model development was conducted in the Multi-Ethnic Study of Atherosclerosis (n = 6715) using clinical predictors. The model consists of two complementary Fine and Gray competing-risk adjusted left-truncated subdistribution hazard functions: one for hard cardiovascular disease (CVD)-events, and one for non-CVD mortality. Therapy-effects were estimated by combining the functions with hazard ratios from preventive therapy trials. External validation was performed in the Atherosclerosis Risk in Communities (n = 9250), Heinz Nixdorf Recall (n = 4177), and the European Prospective Investigation into Cancer and Nutrition-Netherlands (n = 25 833), and Norfolk (n = 23 548) studies. Calibration of the LIFE-CVD model was good and c-statistics were 0.67-0.76. The output enables the comparison of short-term vs. long-term therapy-benefit. In two people aged 45 and 70 with otherwise identical risk-factors, the older patient has a greater 10-year absolute risk reduction (11.3% vs. 1.0%) but a smaller gain in life-years free of CVD (3.4 vs. 4.5 years) from the same therapy. The model was developed into an interactive online calculator available via www.U-Prevent.com. CONCLUSION: The model can accurately estimate individual-level prognosis and treatment-effects in terms of improved 10-year risk, lifetime risk, and life-expectancy free of CVD. The model is easily accessible and can be used to facilitate personalized-medicine and doctor-patient communication.

The prediction of therapy-benefit for individual cardiovascular disease prevention: rationale, implications, and implementation.

PURPOSE OF REVIEW: We aim to outline the importance and the clinical implications of using predicted individual therapy-benefit in making patient-centered treatment decisions in cardiovascular disease (CVD) prevention. Therapy-benefit concepts will be illustrated with examples of patients undergoing lipid management. RECENT FINDINGS: In both primary and secondary CVD prevention, the degree of variation in individual therapy-benefit is large. An individual's therapy-benefit can be estimated by combining prediction algorithms and clinical trial data. Measures of therapy-benefit can be easily integrated into clinical practice via a variety of online calculators. Lifetime estimates (e.g., gain in healthy life expectancy) look at therapy-benefit over the course of an individual's life, and are less influenced by age than short-term estimates (e.g., 10-year absolute risk reduction). Lifetime estimates can thus identify people who could substantially benefit from early initiation of CVD prevention. Compared with current guidelines, treatment based on predicted therapy-benefit would increase eligibility for therapy among young people with a moderate risk-factor burden and individuals with a high residual risk. SUMMARY: The estimation of individual therapy-benefit is an important part of individualized medicine. Implementation tools allow for clinicians to readily estimate both short-term and lifetime therapy-benefit.

Variation in minimum desired cardiovascular disease-free longevity benefit from statin and antihypertensive medications: a cross-sectional study of patient and primary care physician perspectives.

OBJECTIVE: Expressing therapy benefit from a lifetime perspective, instead of only a 10-year perspective, is both more intuitive and of growing importance in doctor-patient communication. In cardiovascular disease (CVD) prevention, lifetime estimates are increasingly accessible via online decision tools. However, it is unclear what gain in life expectancy is considered meaningful by those who would use the estimates in clinical practice. We therefore quantified lifetime and 10-year benefit thresholds at which physicians and patients perceive statin and antihypertensive therapy as meaningful, and compared the thresholds with clinically attainable benefit. DESIGN: Cross-sectional study. SETTINGS: (1) continuing medical education conference in December 2016 for primary care physicians;(2) information session in April 2017 for patients. PARTICIPANTS: 400 primary care physicians and 523 patients in the Netherlands. OUTCOME: Months gain of CVD-free life expectancy at which lifelong statin therapy is perceived as meaningful, and months gain at which 10 years of statin and antihypertensive therapy is perceived as meaningful. Physicians were framed as users for lifelong and prescribers for 10-year therapy. RESULTS: Meaningful benefit was reported as median (IQR). Meaningful lifetime statin benefit was 24 months (IQR 23-36) in physicians (as users) and 42 months (IQR 12-42) in patients willing to consider therapy. Meaningful 10-year statin benefit was 12 months (IQR 10-12) for prescribing (physicians) and 14 months (IQR 10-14) for using (patients). Meaningful 10-year antihypertensive benefit was 12 months (IQR 8-12) for prescribing (physicians) and 14 months (IQR 10-14) for using (patients). Women desired greater benefit than men. Age, CVD status and co-medication had minimal effects on outcomes. CONCLUSION: Both physicians and patients report a large variation in meaningful longevity benefit. Desired benefit differs between physicians and patients and exceeds what is clinically attainable. Clinicians should recognise these discrepancies when prescribing therapy and implement individualised medicine and shared decision-making. Decision tools could provide information on realistic therapy benefit.