Multiple Risk Factor Intervention Research Articles

Do meta-analyses of randomized controlled trials estimate the true population effects of multiple risk factor interventions?

Do meta-analyses of randomized controlled trials estimate the true population effects of multiple risk factor interventions?

Estimating the average treatment effect in randomized clinical trials with all-or-none compliance

Noncompliance is a common intercurrent event in randomized clinical trials that raises important questions about analytical objectives and approaches. Motivated by the Multiple Risk Factor Intervention Trial (MRFIT), we consider how to estimate the average treatment effect (ATE) in randomized trials with all-or-none compliance. Confounding is a major challenge in estimating the ATE, and conventional methods for confounding adjustment typically require the assumption of no unmeasured confounders which may be difficult to justify. Using randomized treatment assignment as an instrumental variable, the ATE can be identified in the presence of unmeasured confounders under suitable assumptions, including an assumption that limits the effect-modifying activities of unmeasured confounders. We describe and compare several estimation methods based on different modeling assumptions. Some of these methods are able to incorporate information from auxiliary covariates for improved efficiency without introducing bias. The different methods are compared in a simulation study and applied to the MRFIT.

In Memoriam: Richard H. Grimm, Jr, MD, MPH, PhD (August 22, 1946-September 8, 2022).

In Memoriam: Richard H. Grimm, Jr, MD, MPH, PhD (August 22, 1946-September 8, 2022).

The Impact of Health on Labor Market Outcomes: Evidence from a Large-Scale Health Experiment

While economists have posited that health investments increase earnings, isolating the causal effect of health is challenging due to reverse causality and unobserved heterogeneity. We examine the labor market effects of a randomized controlled trial, the Multiple Risk Factor Intervention Trial (MRFIT), which monitored nearly 13,000 men for over six years. We find that this intervention, which provided a bundle of treatments to reduce coronary heart disease mortality, increased earnings and family income. We find few differences in estimated gains by baseline health and occupation characteristics. (JEL I12, J24, J31)

What are the effects of multiple risk factor interventions for primary prevention of coronary heart disease (CHD)?

What are the effects of multiple risk factor interventions for primary prevention of coronary heart disease (CHD)?

ASIAN PACIFIC SOCIETY OF NEPHROLOGY CLINICAL PRACTICE GUIDELINE ON DIABETIC KIDNEY DISEASE.

ASIAN PACIFIC SOCIETY OF NEPHROLOGY CLINICAL PRACTICE GUIDELINE ON DIABETIC KIDNEY DISEASE.

Invited Commentary: Learning From Our Past to Build on Our Future- Lessons Learned From MRFIT and JUMBO.

We propose that Blackburn (Am J Epidemiol. 2020;189(6):491-498) ignores several important issues that need to be considered in the context of a historical reflection of the National Heart Institute's landmark study, the Multiple Risk Factor Intervention Trial (MRFIT), and the alternative proposal, the "JUMBO" trial, submitted to the National Heart Institute by an experienced team of extramural investigators but never funded. A key focus of this commentary is to offer an alternative perspective on both studies using our current understanding of the impact of social and structural determinants of health; evidence that policy, systems, and environmental interventions are needed to support behavior change at the individual level; and the significance of examining research from a racial/socioeconomic equity lens. While we strongly agree with Blackburn's conclusion urging the National Institutes of Health to invest in prevention research at a level consistent with its social and economic impact, we encourage the author to move beyond simply underscoring the methodological limitations and failure of the findings of MRFIT compared with the potential of the proposed JUMBO trial to consider the contribution of MRFIT to our current understanding of chronic disease prevention and treatment.

The National Cooperative Trial on Multifactorial Prevention of First Heart Attacks and Coronary Mortality in Free-Living, High-Risk, Middle-Aged American Men, Also Known as JUMBO: A Short Story.

The concept of a multiple risk-factor intervention trial (MRFIT) originated in mid-20th century efforts to determine whether modifying the "risk factors" established by cardiovascular disease epidemiology would prevent heart attacks. The term "MRFIT" probably first appeared in the 1968 report to the National Heart Institute from investigators of the National Diet-Heart Feasibility Study. Based on their pilot experience, they recommended a trial of diet alone. Aware, however, that authorities might agree with the rationale but not the implementation of such a massive and risky undertaking, they also proposed an alternative: whether coronary heart disease was preventable at all by simultaneous intervention on several risk factors; that is, a multiple risk-factor intervention trial. After some years agonizing by serial expert committees, the National Heart Institute opted against an explanatory diet trial and for a pragmatic multiple risk-factor intervention, one designed by Institute staff and operated under contract. Meanwhile, an impatient community of investigators met together in the Makarska Conference, outlined a broad cardiovascular disease prevention policy, and submitted their idealized version of a multiple risk-factor trial, called JUMBO. But the National Heart Institute, because of the plan for its own trial, had no funds left for an investigator-initiated proposal. Hence, this background and story of the MRFIT that wasn't.

Invited Commentary: Can You Do Trials of Behavioral Modification, Such as Diet or Exercise Intervention, With Hard Endpoints?

Blackburn (Am J Epidemiol. 2020;189(6):491-498) describes the evolution from the Makarska Conference in 1968 to the planning of the JUMBO trial and the decision by the National Institutes of Health (NIH) to do the Multiple Risk Factor Intervention Trial. He attributes the failure of the Multiple Risk Factor Intervention Trial to show a significant reduction in coronary heart disease or total mortality to the design of the trial, the multiple centers involved, and continued bureaucracy. The paper is important in raising 3 issues of continued relevance: 1) What is the relationship of the NIH staff in both development and monitoring of large cooperative studies, especially clinical trials, outside of the walls of the NIH? 2) Can clinical trials that utilize individual randomization to intervention and comparison be successful in evaluating a common-source epidemic, such as diet and coronary heart disease, especially in populations with readily available foods and competing advertising, etc.? 3) How much information obtained from, e.g., observational studies, animal models, and genetic studies, is necessary given limits of human population clinical trials of behavioral intervention to develop recommendations for strong public health programs to reduce morbidity and mortality, and what is the measure of successful intervention?

The rising burden of non-communicable diseases in sub-Saharan Africa

The rising burden of non-communicable diseases in sub-Saharan Africa

A win ratio approach to the re-analysis of Multiple Risk Factor Intervention Trial.

Composite outcomes, which combine multiple types of clinical events into a single outcome, are common in clinical trials. The usual analysis considers the time to first occurrence of any event in the composite. The major criticisms of such an approach are (1) this implicitly treats the outcomes as if they were of equal importance, but they often vary in terms of clinical relevance and severity, (2) study participants often experience more than one type of event, and (3) often less severe events occur before more severe ones, but the usual analysis disregards any information beyond that first event. A novel approach, referred to as the win ratio, which addresses the aforementioned criticisms of composite outcomes, is illustrated with a re-analysis of data on fatal and non-fatal cardiovascular disease time-to-event outcomes reported for the Multiple Risk Factor Intervention Trial. In this trial, 12,866 participants were randomized to a special intervention group (n = 6428) or a usual care (n = 6438) group. Non-fatal outcomes were ranked by risk of cardiovascular disease death up to 20 years after trial. In one approach, participants in the special intervention and usual care groups were first matched on coronary heart disease risk at baseline and time of enrollment. Each matched pair was categorized as a winner or loser depending on which one experienced a cardiovascular disease death first. If neither died of cardiovascular disease causes, they were evaluated on the most severe non-fatal outcome. This process continued for all the non-fatal outcomes. A second win ratio statistic, obtained from Cox partial likelihood, was also estimated. This statistic provides a valid estimate of the win ratio using multiple events if the marginal and conditional survivor functions of each outcome satisfy proportional hazards. Loss ratio statistics (inverse of win ratios) are compared to hazard ratios from the usual first event analysis. A larger 11-event composite was also considered. For the 7-event cardiovascular disease composite, the previously reported first event analysis based on 581 events in the special intervention group and 652 events in the usual care group yielded a hazard ratio (95% confidence interval) of 0.89 (0.79-0.99), compared to 0.86 (0.77-0.97) and 0.91 (0.81-1.02) for the severity ranked estimates. Results for the 11-event composite also confirmed the findings of the first event analysis. The win ratio analysis was able to leverage information collected past the first experienced event and rank events by severity. The results were similar to and confirmed previously reported traditional first event analysis. The win ratio statistic is a useful adjunct to the traditional first event analysis for trials with composite outcomes.

237-OR: Beneficial Impact of Intensified Multifactorial Intervention on Stroke—The Steno-2 Study

Epidemiological studies have shown that diabetes is a well-established independent but modifiable risk factor for stroke. In the Steno-2 Study 160 patients with T2DM and microalbuminuria were randomised to intensified or conventional multiple risk factor intervention targeting classical CVD risk factors for a mean of 7.8 years and then followed for up to 21.9 years. The primary endpoint in this post hoc analysis was time to first stroke (Cox regression adjusted for age and sex). Baseline predictors were examined using backwards regression elimination (threshold of α = 0.10) of the following variables: age, sex, known diabetes duration, smoking status, left ventricular ejection fraction, heart rate variability, atrial fibrillation, BMI, systolic BP, GFR, retinopathy, HbA1c, proBNP and total cholesterol, and urinary albumin excretion rate. During follow-up 30 participants experienced a total of 39 strokes. More patients randomised to conventional therapy experienced a stroke with 21 participants (26%) with 29 strokes in the conventional-therapy group vs. 9 participants (11%) with a total of 10 strokes in the intensive therapy group. Baseline systolic BP and GFR were significant risk factors for stroke. In conclusion, intensified multiple risk factor intervention in patients with type 2 diabetes and microalbuminuria reduces the risk for strokes as well as the number of recurrent cerebrovascular events. Disclosure P. Gæde: None. J. Oellgaard: Employee; Self; Novo Nordisk A/S. C. Kruuse: Speaker's Bureau; Self; Novo Nordisk A/S. P. Rossing: Advisory Panel; Self; AstraZeneca, Bayer AG, Boehringer Ingelheim Pharmaceuticals, Inc. Speaker's Bureau; Self; Eli Lilly and Company, Merck Sharp & Dohme Corp. Other Relationship; Self; Novartis AG, Novo Nordisk A/S. H.D. Parving: None. O. Pedersen: None.

Liberation From the P Value's Tyranny.

> P-values, next to nuclear weapons, are the worst invention of the 20th century . > > —Herman Rubin, Purdue University, 1981 More than a half century ago, the P value was selected as the measuring tool for health care research by administrators. The difficulties generated by statistical hypothesis testing in addition to the constraints it places on cardiovascular trial researchers must now be declared unacceptable by the cardiology research community. Developed >90 years ago by statistician, Ronald Fisher, while working on a manure experiment in England,1,2 P values have risen to dominate the field of cardiovascular investigation for no other reasons than those of custom and habit. The abuse of P values has become so rampant that the American Statistical Association in 2016 was compelled to provide a consensus statement decrying their misuse.3 Counterpoint, see p 1049 Statistical hypothesis testing and P values were criticized by scientists from the beginning. They thought that its reverse logic—embracing a null hypothesis that one did not think, only to have the data reject it compelling the scientist to accept what one did think—was tortured and unnecessarily complex. P values rose to prominence in health care when grant administrators, journal editors, and Food and Drug Administration officials, overwhelmed by the post–World War II explosion in research, chose the P value instrument to help identify worthy research.4 The P value was not chosen because it had any basis in epidemiology, biology, pathophysiology, or cardiovascular medicine. It was selected because these administrators needed a metric to help them to separate the research wheat from the chaff, and they could see no alternative. The fledgling clinical trial research community accepted this P value imprimatur, not realizing that this nonmalicious selection portended pernicious consequences. Even though the P value’s sole, small role was to …

Who Resembles a Scientific Leader-Jack or Jill? How Implicit Bias Could Influence Research Grant Funding.

When women advance in medicine, so does women’s health. In cardiology, women have led major research studies examining and confirming sex differences in cardiovascular disease risk factors, manifestations, and outcomes, providing essential data for evidence-based approaches to women’s heart health. The inclusion of women in cardiovascular research studies paralleled the entry of women physicians into cardiology. When women were absent as principal investigators, women were also missing from the tens of thousands of participants in the early cardiovascular prevention trials, including the Coronary Drug Project, Physicians Health Study, Lipid Research Clinics Coronary Primary Prevention Trial, and Multiple Risk Factors Intervention Trial (so-called MR FIT). Given the association between women entering cardiology and research in women’s heart health, it is worrisome that women comprise <20% of cardiologists (the lowest percentage among internal medicine subspecialties).1 Furthermore, although female cardiologists are more likely than their male peers to practice in academic settings where most research is conducted (43% versus 34%), they are less likely in these settings to be involved in research2 or achieve the rank of full professor,1 and more likely to report lower levels of career attainment.2 Because conducting research as an independent investigator is …

Multiple Risk Factor Interventions for Primary Prevention of CVD in LMIC: A Cochrane Review.

This study sought to determine the effectiveness of multiple risk factor interventions aimed at modifying major cardiovascular risk factors for the primary prevention of cardiovascular disease in low- and middle-income countries (LMIC). We searched electronic databases for randomized controlled trials of health promotion interventions to achieve behavior change. The pooled effect indicated a reduction in systolic blood pressure (-6.72 mm Hg; 95% confidence interval [CI]: -9.82 to -3.61; I2 = 91%), diastolic blood pressure (-4.40 mm Hg; 95% CI: -6.47 to -2.34; I2 = 92%), body mass index (-0.76 kg/m2; 95% CI: -1.29 to -0.22; I2 = 80%), and waist circumference (-3.31 cm; 95% CI: -4.77 to -1.86; I2 = 55%) in favor of multiple risk factor interventions. There is some evidence that multiple risk factor interventions may lower blood pressure levels and anthropometrics in populations in LMIC settings at high risk of hypertension and diabetes.

Can Cardiovascular Epidemiology and Clinical Trials Close the Risk Management Gap Between Diabetes and Prediabetes?

We reviewed published literature to determine the relationship between A1c and cardiovascular disease (CVD) and summarize the need and implications for CVD risk reduction with interventions, focusing in the prediabetic A1c range (<6.5%). Strong evidence supports a continuous relationship between A1c and CVD-even below the current levels of A1c-defined prediabetes and after adjustment for known risk factors for CVD. Clinical trials have demonstrated a reduction in CV morbidity and/or mortality when interventions are invoked in the prediabetic A1c range. Guidelines advocating CV risk factor management in prediabetes have not been widely adopted, subsequently leading to comparable coronary heart disease risk between people with prediabetes (HR=1.9, 95% CI 1.7-2.1 vs normoglycemia) and diabetes itself (HR=2.0, 95% CI 1.8-2.2 vs no diabetes). This review highlights the missed opportunity to utilize multiple risk factor interventions to reduce CVD in high-risk people with prediabetes.

Multiple Risk Factor Counseling to Promote Heart-healthy Lifestyles in the Chest Pain Observation Unit: Pilot Randomized Controlled Trial.

Admission to the chest pain observation unit (CPOU) may be an advantageous time for patients to consider heart-healthy lifestyle changes while undergoing diagnostic evaluation to rule out myocardial ischemia. The aim of this pragmatic trial was to assess the effectiveness of a multiple risk factor intervention in changing CPOU patients' health beliefs and readiness to change health behaviors. A secondary aim was to obtain preliminary estimates of the intervention's effect on diet, physical activity, and smoking. We conducted a pilot randomized controlled trial of a moderate-intensity counseling intervention that aimed to build motivation to change and problem-solving skills in 140 adult patients with at least one modifiable cardiovascular risk factor (CRF) who were admitted to the CPOU of an academic emergency department (ED) with symptoms of possible acute coronary syndrome. Study patients were randomly assigned to full counseling (face-to-face cardiovascular risk assessment and personalized counseling on nutrition, physical activity, and smoking cessation in the ED, plus two telephone follow-up sessions) or minimal counseling (brief instruction [<5 minutes] on benefits of modifying cardiovascular risk factors) by a cardiac rehabilitation specialist. We measured Health Belief Model constructs for ischemic heart disease, stage of change, and self-reported CRF-related behaviors (diet, exercise, and smoking) during 6-month follow-up using previously validated measures. We used linear mixed models and logistic regression (with generalized estimating equations) to compare continuous and dichotomous behavioral outcomes across treatment arms, respectively. Approximately 20% more patients in the full counseling arm reported having received counseling on diet and physical activity during CPOU admission, compared to the minimal counseling arm; a similar proportion of patients in both counseling arms reported having received advice or assistance in quitting smoking. There were no significant differences between treatment arms for any cardiovascular health beliefs, readiness to change, or CRF-related behaviors during longitudinal follow-up. In secondary analyses in both treatment arms combined, however, patients showed significant differences between follow-up and baseline measurements: increases in the perceived benefits of improving CRF-related behaviors (27.7 vs. 26.6 on a scale from 7 to 35, p = 0.0001) and increased readiness to change dietary behavior and physical activity during follow-up-intake of saturated fat (83% vs. 49%), readiness to change fruit and vegetable consumption (83% vs 56%), and readiness to perform regular exercise (34% vs. 14%) at 6 months and baseline, respectively (p < 0.0001 for all comparisons in both treatment arms combined). A multiple risk factor intervention that focused on increasing motivation to change and problem-solving skills did not significantly improve behavioral outcomes, compared to minimal counseling. Patients admitted to the CPOU demonstrated sustained changes in several cardiovascular health beliefs and risk-related behaviors during follow-up; this provides further evidence that the CPOU visit is a "teachable moment" for cardiovascular risk reduction. Future studies should evaluate the effectiveness of ED-initiated counseling interventions to engage patients in changing cardiovascular risk behaviors, in coordination with primary care.

Atherosclerosis associated with dynamic inflammation changes after multifactorial intervention in short-duration type 2 diabetes: A randomized, controlled, 10-year follow-up trial

PurposeTo analyze the impact of dynamic changes in inflammation on atherosclerosis in short-duration type 2 diabetes after multifactorial intervention. MethodsIn this randomized controlled study, a total of 150 type 2 diabetes patients who had a mean age of 49.8±7.3years, 51% male, with disease duration <1year and without evidence of atherosclerosis were randomized into an intensive intervention group (IG), in which patients received multiple risk factors intervention by the special project team and tried to reach the pre-determined intervention goals, and a conventional group (CG), in which patients received standard diabetes care by the clinic doctor. All patients recieved intervention study for 7 years, then underwent a 3-year observational follow-up study. The primary endpoints were occurrence of subclinical atherosclerosis, defined as the intima–media thickness of the common carotid artery (CC-IMT)≥1.0mm or formation of atherosclerosis plaques, and the occurrence of cardiovascular events. Results68 patients in IG and 65 patients in CG completed the 10-year study. The cumulative incidence of subclinical atherosclerosis was 30.7% vs 57.3% (IG vs CG, HR 0.36, 95% CI 0.22–0.60, P<0.0001) and that of cardiovascular events was 12.0% vs 22.7% (IG vs CG, HR 0.46, 95% CI 0.21–0.98, P=0.0516). High sensitivity C-reactive protein (hs-CRP) reduction from baseline to the 10-year follow-up was −1.54mg/L (IG) and −0.67mg/L (CG) with difference (IG minus CG) of −0.87mg/L(95% CI −0.72 to −1.02, P=0.008) and the natural logarithm of serum amyloid A (SAA) reduction was −4.04 (IG) and −1.44 (CG) with difference (IG minus CG) of −2.60 (95% CI −2.30 to −2.90, P=0.002). The decrease in general score of inflammatory markers (combination of hs-CRP and SAA) was independently associated with subclinical atherosclerosis (OR=0.65, P=0.045) and cardiovascular events (OR=0.60, P=0.042). ConclusionsDynamic changes in inflammation act as an important factor that affects the occurrence of atherosclerosis in type 2 diabetes patients. Multifactorial intensive intervention can reduce systemic low-grade inflammation and delay the occurrence of atherosclerosis in short-duration type 2 diabetes.

Obesity Paradox in Recurrent Attacks of Gout in Observational Studies: Clarification and Remedy.

Obesity is strongly associated with incident gout risk, but its association with the risk of recurrent gout attacks has been null or weak, constituting an obesity paradox. We sought to demonstrate and overcome the methodologic issues associated with the obesity paradox for risk of recurrent gout attacks. Using the Multiple Risk Factor Intervention Trial database, we decomposed the total effect of obesity into its direct and indirect (i.e., mediated) effects using marginal structural models. We also estimated the total effect of body mass index (BMI) change from baseline among incident gout patients. Of 11,816 gout-free subjects at baseline, we documented 408 incident gout cases, with 132 developing recurrent gout attacks over a 7-year followup period. The adjusted odds ratio (OR) for incident gout among obese individuals was 2.6, whereas that for recurrent gout attacks among gout patients was 0.98 (i.e., the obesity paradox). These ORs correlated well with the ORs for the indirect and direct effects of obesity on the risk of recurrent gout attacks (2.83 and 0.98, respectively). Compared with no BMI change, the OR of increasing versus decreasing >5% of baseline BMI was 0.61 and 1.60 for recurrent gout attacks, respectively (P for trend < 0.01), suggesting a dose-response association. The obesity paradox for the risk of recurrent gout attacks is explained by the absence of the direct effect, which is often measured in conventional analyses and misinterpreted as the intended total effect of interest. In contrast, the BMI change analysis correctly estimated the intended total effect of BMI, and revealed a dose-response relationship.

Lifestyle Factors Associated With Sunscreen Use Among Young Adults.

Background. Skin cancer is the most common cancer in the United States with melanoma rates increasing. Sunscreen use is an effective way to protect the skin and reduce skin cancer risk. Limited research has been conducted examining the relationship between sunscreen use and other lifestyle factors. Interventions aimed at multiple lifestyle factors have shown promise for prevention and reduced health care costs. Objective. This study explores the relationship between sunscreen use and lifestyle factors associated with mortality and morbidity among young adults. Lifestyle factors examined included physical activity, substance abuse, smoking, sexual behavior, unintentional injury, and mental well-being. Methods. A convenience sample of 747 college students was surveyed about sunscreen use and other health risks. Data were analyzed using SPSS 19. Results. White, female students older than 21 years were more likely to use sunscreen. Texting while driving, low life satisfaction, and binge drinking were associated with inadequate sunscreen use. Limitations. Convenience sampling limits generalizability and surveys are subject to recall, self-report, and self-selection bias. Conclusions. The findings provide the framework to develop multiple risk factor interventions.