Cardiovascular and Cancer Risk with Tofacitinib in Rheumatoid Arthritis.

BACKGROUND: Increases in lipid levels and cancers with tofacitinib prompted a trial of major adverse cardiovascular events (MACE) and cancers in patients with rheumatoid arthritis receiving tofacitinib as compared with a tumor necrosis factor (TNF) inhibitor. METHODS: We conducted a randomized, open-label, noninferiority, postauthorization, safety end-point trial involving patients with active rheumatoid arthritis despite methotrexate treatment who were 50 years of age or older and had at least one additional cardiovascular risk factor. Patients were randomly assigned in a 1:1:1 ratio to receive tofacitinib at a dose of 5 mg or 10 mg twice daily or a TNF inhibitor. The coprimary end points were adjudicated MACE and cancers, excluding nonmelanoma skin cancer. The noninferiority of tofacitinib would be shown if the upper boundary of the two-sided 95% confidence interval for the hazard ratio was less than 1.8 for the combined tofacitinib doses as compared with a TNF inhibitor. RESULTS: A total of 1455 patients received tofacitinib at a dose of 5 mg twice daily, 1456 received tofacitinib at a dose of 10 mg twice daily, and 1451 received a TNF inhibitor. During a median follow-up of 4.0 years, the incidences of MACE and cancer were higher with the combined tofacitinib doses (3.4% [98 patients] and 4.2% [122 patients], respectively) than with a TNF inhibitor (2.5% [37 patients] and 2.9% [42 patients]). The hazard ratios were 1.33 (95% confidence interval [CI], 0.91 to 1.94) for MACE and 1.48 (95% CI, 1.04 to 2.09) for cancers; the noninferiority of tofacitinib was not shown. The incidences of adjudicated opportunistic infections (including herpes zoster and tuberculosis), all herpes zoster (nonserious and serious), and adjudicated nonmelanoma skin cancer were higher with tofacitinib than with a TNF inhibitor. Efficacy was similar in all three groups, with improvements from month 2 that were sustained through trial completion. CONCLUSIONS: In this trial comparing the combined tofacitinib doses with a TNF inhibitor in a cardiovascular risk-enriched population, risks of MACE and cancers were higher with tofacitinib and did not meet noninferiority criteria. Several adverse events were more common with tofacitinib. (Funded by Pfizer; ORAL Surveillance ClinicalTrials.gov number, NCT02092467.).

Risk of major adverse cardiovascular events with tofacitinib versus tumour necrosis factor inhibitors in patients with rheumatoid arthritis with or without a history of atherosclerotic cardiovascular disease: a post hoc analysis from ORAL Surveillance.

OBJECTIVES: Evaluate risk of major adverse cardiovascular events (MACE) with tofacitinib versus tumour necrosis factor inhibitors (TNFi) in patients with rheumatoid arthritis (RA) with or without a history of atherosclerotic cardiovascular disease (ASCVD) in ORAL Surveillance. METHODS: Patients with RA aged ≥50 years with ≥1 additional CV risk factor received tofacitinib 5 mg or 10 mg two times per day or TNFi. Hazard rations (HRs) were evaluated for the overall population and by history of ASCVD (exploratory analysis). RESULTS: Risk of MACE, myocardial infarction and sudden cardiac death were increased with tofacitinib versus TNFi in ORAL Surveillance. In patients with history of ASCVD (14.7%; 640/4362), MACE incidence was higher with tofacitinib 5 mg two times per day (8.3%; 17/204) and 10 mg two times per day (7.7%; 17/222) versus TNFi (4.2%; 9/214). HR (combined tofacitinib doses vs TNFi) was 1.98 (95% confidence interval (CI) 0.95 to 4.14; interaction p values: 0.196 (for HR)/0.059 (for incidence rate difference)). In patients without history of ASCVD, MACE HRs for tofacitinib 5 mg two times per day (2.4%; 30/1251) and 10 mg two times per day (2.8%; 34/1234) versus TNFi (2.3%; 28/1237) were, respectively, 1.03 (0.62 to 1.73) and 1.25 (0.76 to 2.07). CONCLUSIONS: This post hoc analysis observed higher MACE risk with tofacitinib versus TNFi in patients with RA and history of ASCVD. Among patients without history of ASCVD, all with prevalent CV risk factors, MACE risk did not appear different with tofacitinib 5 mg two times per day versus TNFi. Due to the exploratory nature of this analysis and low statistical power, we cannot exclude differential MACE risk for tofacitinib 5 mg two times per day versus TNFi among patients without history of ASCVD, but any absolute risk excess is likely low. TRIAL REGISTRATION NUMBER: NCT02092467.

Effects of dapagliflozin on prevention of major clinical events and recovery in patients with respiratory failure because of COVID-19: Design and rationale for the DARE-19 study.

AIMS: Coronavirus disease 2019 (COVID-19) is caused by a novel severe acute respiratory syndrome coronavirus 2. It can lead to multiorgan failure, including respiratory and cardiovascular decompensation, and kidney injury, with significant associated morbidity and mortality, particularly in patients with underlying metabolic, cardiovascular, respiratory or kidney disease. Dapagliflozin, a sodium-glucose cotransporter-2 inhibitor, has shown significant cardio- and renoprotective benefits in patients with type 2 diabetes (with and without atherosclerotic cardiovascular disease), heart failure and chronic kidney disease, and may provide similar organ protection in high-risk patients with COVID-19. MATERIALS AND METHODS: DARE-19 (NCT04350593) is an investigator-initiated, collaborative, international, multicentre, randomized, double-blind, placebo-controlled study testing the dual hypotheses that dapagliflozin can reduce the incidence of cardiovascular, kidney and/or respiratory complications or all-cause mortality, or improve clinical recovery, in adult patients hospitalized with COVID-19 but not critically ill on admission. Eligible patients will have ≥1 cardiometabolic risk factor for COVID-19 complications. Patients will be randomized 1:1 to dapagliflozin 10 mg or placebo. Primary efficacy endpoints are time to development of new or worsened organ dysfunction during index hospitalization, or all-cause mortality, and the hierarchical composite endpoint of change in clinical status through day 30 of treatment. Safety of dapagliflozin in individuals with COVID-19 will be assessed. CONCLUSIONS: DARE-19 will evaluate whether dapagliflozin can prevent COVID-19-related complications and all-cause mortality, or improve clinical recovery, and assess the safety profile of dapagliflozin in this patient population. Currently, DARE-19 is the first large randomized controlled trial investigating use of sodium-glucose cotransporter 2 inhibitors in patients with COVID-19.

Power and sample size calculation for the win odds test: application to an ordinal endpoint in COVID-19 trials.

The win odds is a distribution-free method of comparing locations of distributions of two independent random variables. Introduced as a method for analyzing hierarchical composite endpoints, it is well suited to be used in the analysis of ordinal scale endpoints in COVID-19 clinical trials. For a single outcome, we provide power and sample size calculation formulas for the win odds test. We also provide an implementation of the win odds analysis method for a single ordinal outcome in a commonly used statistical software to make the win odds analysis fully reproducible.

Evaluation of alternative confidence intervals to address non-inferiority through the stratified difference between proportions.

The confidence interval (CI) for the difference between two proportions has been an important and active research topic, especially in the context of non-inferiority hypothesis testing. Issues concerning the Type 1 error rate, power, coverage rate and aberrations have been extensively studied for non-stratified cases. However, stratified confidence intervals are frequently used in non-inferiority trials and similar settings. In this paper, several methods for stratified confidence intervals for the difference between two proportions, including existing methods and novel extensions from unstratified CIs, are evaluated across different scenarios. When sparsity across the strata is not a concern, adding imputed observations to the stratification analysis can strengthen Type-1 error control without substantial loss of power. When sparseness of data is a concern, most of the evaluated methods fail to control Type-1 error; the modified stratified t-test CI is an exception. We recommend the modified stratified t-test CI as the most useful and flexible method across the respective scenarios; the modified stratified Wald CI may be useful in settings where sparsity is unlikely. These findings substantially contribute to the application of stratified CIs for non-inferiority testing of differences between two proportions.

On kernel machine learning for propensity score estimation under complex confounding structures.

Post marketing data offer rich information and cost-effective resources for physicians and policy-makers to address some critical scientific questions in clinical practice. However, the complex confounding structures (e.g., nonlinear and nonadditive interactions) embedded in these observational data often pose major analytical challenges for proper analysis to draw valid conclusions. Furthermore, often made available as electronic health records (EHRs), these data are usually massive with hundreds of thousands observational records, which introduce additional computational challenges. In this paper, for comparative effectiveness analysis, we propose a statistically robust yet computationally efficient propensity score (PS) approach to adjust for the complex confounding structures. Specifically, we propose a kernel-based machine learning method for flexibly and robustly PS modeling to obtain valid PS estimation from observational data with complex confounding structures. The estimated propensity score is then used in the second stage analysis to obtain the consistent average treatment effect estimate. An empirical variance estimator based on the bootstrap is adopted. A split-and-merge algorithm is further developed to reduce the computational workload of the proposed method for big data, and to obtain a valid variance estimator of the average treatment effect estimate as a by-product. As shown by extensive numerical studies and an application to postoperative pain EHR data comparative effectiveness analysis, the proposed approach consistently outperforms other competing methods, demonstrating its practical utility.

Suboptimal reliability of liver biopsy evaluation has implications for randomized clinical trials.

BACKGROUND & AIMS: Liver biopsies are a critical component of pivotal studies in non-alcoholic steatohepatitis (NASH), constituting inclusion criteria, risk stratification factors and endpoints. We evaluated the reliability of NASH Clinical Research Network scoring of liver biopsies in a NASH clinical trial. METHODS: Digitized slides of 678 biopsies from 339 patients with paired biopsies randomized into the EMMINENCE study - examining a novel insulin sensitizer (MSDC-0602K) in NASH - were read independently by 3 hepatopathologists blinded to treatment code and scored using the NASH CRN histological scoring system. Various endpoints were computed from these scores. RESULTS: Inter-reader linearly weighted kappas were 0.609, 0.484, 0.328, and 0.517 for steatosis, fibrosis, lobular inflammation, and ballooning, respectively. Inter-reader unweighted kappas were 0.400 for the diagnosis of NASH, 0.396 for NASH resolution without worsening fibrosis, and 0.366 for fibrosis improvement without worsening NASH. In the current study, 46.3% of the patients included in the study based on 1 hepatopathologist's qualifying reading were deemed not to meet the study's histologic inclusion criteria by at least 1 of the 3 hepatopathologists. The MSDC-0602K treatment effect was lowest for those histologic features with lower inter-reader reliability. Simulations show that the lack of reliability of endpoints and inclusion criteria can drastically reduce study power - from >90% in a well-powered study to as low as 40%. CONCLUSIONS: The reliability of hepatopathologists' liver biopsy evaluation using currently accepted criteria is suboptimal. This lack of reliability may affect NASH pivotal studies by introducing patients who do not meet NASH study entry criteria, misclassifying fibrosis subgroups, and attenuating apparent treatment effects. LAY SUMMARY: Since liver biopsy analysis plays such an important role in clinical studies of non-alcoholic steatohepatitis, it is important to understand the reliability of hepato-pathologist readings. We examined both inter- and intra-reader variability in a large data set of paired liver biopsies from a clinical trial. We found very poor inter-reader and modest intra-reader variability. This result has important implications for entry criteria, fibrosis stratification, and the ability to measure a treatment effect in clinical trials.

Tolvaptan in Later-Stage Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND: In a previous trial involving patients with early autosomal dominant polycystic kidney disease (ADPKD; estimated creatinine clearance, ≥60 ml per minute), the vasopressin V2-receptor antagonist tolvaptan slowed the growth in total kidney volume and the decline in the estimated glomerular filtration rate (GFR) but also caused more elevations in aminotransferase and bilirubin levels. The efficacy and safety of tolvaptan in patients with later-stage ADPKD are unknown. METHODS: We conducted a phase 3, randomized withdrawal, multicenter, placebo-controlled, double-blind trial. After an 8-week prerandomization period that included sequential placebo and tolvaptan run-in phases, during which each patient's ability to take tolvaptan without dose-limiting side effects was assessed, 1370 patients with ADPKD who were either 18 to 55 years of age with an estimated GFR of 25 to 65 ml per minute per 1.73 m2 of body-surface area or 56 to 65 years of age with an estimated GFR of 25 to 44 ml per minute per 1.73 m2 were randomly assigned in a 1:1 ratio to receive tolvaptan or placebo for 12 months. The primary end point was the change in the estimated GFR from baseline to follow-up, with adjustment for the exact duration that each patient participated (interpolated to 1 year). Safety assessments were conducted monthly. RESULTS: The change from baseline in the estimated GFR was -2.34 ml per minute per 1.73 m2 (95% confidence interval [CI], -2.81 to -1.87) in the tolvaptan group, as compared with -3.61 ml per minute per 1.73 m2 (95% CI, -4.08 to -3.14) in the placebo group (difference, 1.27 ml per minute per 1.73 m2; 95% CI, 0.86 to 1.68; P<0.001). Elevations in the alanine aminotransferase level (to >3 times the upper limit of the normal range) occurred in 38 of 681 patients (5.6%) in the tolvaptan group and in 8 of 685 (1.2%) in the placebo group. Elevations in the aminotransferase level were reversible after stopping tolvaptan. No elevations in the bilirubin level of more than twice the upper limit of the normal range were detected. CONCLUSIONS: Tolvaptan resulted in a slower decline than placebo in the estimated GFR over a 1-year period in patients with later-stage ADPKD. (Funded by Otsuka Pharmaceuticals and Otsuka Pharmaceutical Development and Commercialization; REPRISE ClinicalTrials.gov number, NCT02160145 .).

Intent-to-treat analysis of cluster randomized trials when clusters report unidentifiable outcome proportions.

BACKGROUND: Cluster randomized trials are designed to evaluate interventions at the cluster or group level. When clusters are randomized but some clusters report no or non-analyzable data, intent-to-treat analysis, the gold standard for the analysis of randomized controlled trials, can be compromised. This article presents a very flexible statistical methodology for cluster randomized trials whose outcome is a cluster-level proportion (e.g. proportion from a cluster reporting an event) in the setting where clusters report non-analyzable data (which in general could be due to nonadherence, dropout, missingness, etc.). The approach is motivated by a previously published stratified randomized controlled trial called, "The Randomized Recruitment Intervention Trial (RECRUIT)," designed to examine the effectiveness of a trust-based continuous quality improvement intervention on increasing minority recruitment into clinical trials (ClinicalTrials.gov Identifier: NCT01911208). METHODS: The novel approach exploits the use of generalized estimating equations for cluster-level reports, such that all clusters randomized at baseline are able to be analyzed, and intervention effects are presented as risk ratios. Simulation studies under different outcome missingness scenarios and a variety of intra-cluster correlations are conducted. A comparative analysis of the method with imputation and per protocol approaches for RECRUIT is presented. RESULTS: Simulation results show the novel approach produces unbiased and efficient estimates of the intervention effect that maintain the nominal type I error rate. Application to RECRUIT shows similar effect sizes when compared to the imputation and per protocol approach. CONCLUSION: The article demonstrates that an innovative bivariate generalized estimating equations framework allows one to implement an intent-to-treat analysis to obtain risk ratios or odds ratios, for a variety of cluster randomized designs.

Comparisons of global tests on intersection hypotheses and their application in matched parallel gatekeeping procedures.

A clinical trial often has primary and secondary endpoints and comparisons of high and low doses of a study drug to a control. Multiplicity is not only caused by the multiple comparisons of study drugs versus the control, but also from the hierarchical structure of the hypotheses. Closed test procedures were proposed as general methods to address multiplicity. Two commonly used tests for intersection hypotheses in closed test procedures are the Simes test and the average method. When the treatment effect of a less efficacious dose is not much smaller than the treatment effect of a more efficacious dose for a specific endpoint, the average method has better power than the Simes test for the comparison of two doses versus control. Accordingly, for inferences for primary and secondary endpoints, the matched parallel gatekeeping procedure based on the Simes test for testing intersection hypotheses is extended here to allow the average method for such testing. This procedure is further extended to clinical trials with more than two endpoints as well as to clinical trials with more than two active doses and a control.

Methods for clarifying criteria for study continuation at interim analysis.

In monitoring clinical trials, the question of futility, or whether the data thus far suggest that the results at the final analysis are unlikely to be statistically successful, is regularly of interest over the course of a study. However, the opposite viewpoint of whether the study is sufficiently demonstrating proof of concept (POC) and should continue is a valuable consideration and ultimately should be addressed with high POC power so that a promising study is not prematurely terminated. Conditional power is often used to assess futility, and this article interconnects the ideas of assessing POC for the purpose of study continuation with conditional power, while highlighting the importance of the POC type I error and the POC type II error for study continuation or not at the interim analysis. Methods for analyzing subgroups motivate the interim analyses to maintain high POC power via an adjusted interim POC significance level criterion for study continuation or testing against an inferiority margin. Furthermore, two versions of conditional power based on the assumed effect size or the observed interim effect size are considered. Graphical displays illustrate the relationship of the POC type II error for premature study termination to the POC type I error for study continuation and the associated conditional power criteria.

Randomization-based analysis of covariance for inference in the sequential parallel comparison design.

The sequential parallel comparison design (SPCD), with sequence groups P:P, P:T, and T:T, together with the exclusion of the second-period information from placebo responders in the first period, can serve usefully for studies with highly favorable placebo response, for example, psychiatric clinical trials. This paper presents a methodology for the first-period treatment difference in the overall population and the second-period treatment difference in the placebo nonresponders for the first period, as well as other available sources of information that could be of potential interest. Without any assumptions, a hypothesis testing method is proposed based on the randomization distribution of comparisons using the covariance structure for the randomized population under the null hypothesis to control type I error. Randomization-based analysis of covariance (ANCOVA) is introduced to adjust for baseline and for the observations that serve as baselines for the second period. Related methods are proposed for the study population as a simple random sample of an almost infinite population. The statistical properties of the proposed methods are described with simulation studies; and the use of the methods is illustrated for an example based on the data from the ADAPT-A clinical trial.

Cardiovascular Outcome Trials in Type 2 Diabetes: What Do They Mean for Clinical Practice?

IN BRIEF Cardiovascular disease is the leading cause of morbidity and mortality in people with diabetes, and deaths from heart disease are two to four times higher among adults with type 2 diabetes. Trials such as the U.K. Prospective Diabetes Study, ACCORD (Action to Control Cardiovascular Risk in Diabetes), ADVANCE (Action in Diabetes and Vascular Disease: Preterax and Diamicron MR Controlled Evaluation), and VADT (Veteran's Affairs Diabetes Trial) produced mixed findings regarding whether intensive glycemic control results in improved cardiovascular (CV) outcomes for patients with diabetes. In response to concerns, including the CV safety of the thiazolidinedione rosiglitazone, the U.S. Food and Drug Administration and subsequently the European Medicines Agency issued guidance that trials should be conducted to prove that antihyperglycemic agents have acceptable CV risk profiles. In this article, the authors review the study designs and results of CV outcomes trials conducted with sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide 1 receptor agonists and discuss how these may affect clinical practice.

Statistical considerations in a delayed-start design to demonstrate disease modification effect in neurodegenerative disorders.

There has been a paradigm shift in diagnostic conceptualization of Alzheimer's disease (AD) based on the current evidence suggesting that structure and biology changes start to occur before clinical symptoms emerge. Consequently, therapeutic drug development is also shifting to treat early AD patients using biomarkers for enrichment in clinical trials. A similar paradigm shift is occurring for Parkinson disease. In the absence of acceptable biomarkers that could be combined with a clinical endpoint to demonstrate a disease modification (DM) effect in neurodegenerative disorders, a delayed-start design can be applied to demonstrate a lasting effect on the disease course. The delayed-start design includes two treatment periods, where in period 1, patients are randomized to receive an active treatment or placebo, and in period 2, placebo patients are switched to the active treatment while patients in the active treatment arm will continue the same treatment. The hypothesis is that patients who start the active treatment later will fail to catch up to the treatment benefit achieved by patients who receive the active treatment in both periods. A usual analytical approach has sought to demonstrate the divergence of slope during period 1 and the parallelism of slopes during period 2 as the DM effect. However, due to heterogeneity in timing and the magnitude of maximal effect among patients, nonlinear response over time could be observed within the two treatment arms in both periods. We propose an approach to evaluate the DM effect with the linearity assumption for treatment differences, but not for each arm separately.

Performance of intraclass correlation coefficient (ICC) as a reliability index under various distributions in scale reliability studies.

Many published scale validation studies determine inter-rater reliability using the intra-class correlation coefficient (ICC). However, the use of this statistic must consider its advantages, limitations, and applicability. This paper evaluates how interaction of subject distribution, sample size, and levels of rater disagreement affects ICC and provides an approach for obtaining relevant ICC estimates under suboptimal conditions. Simulation results suggest that for a fixed number of subjects, ICC from the convex distribution is smaller than ICC for the uniform distribution, which in turn is smaller than ICC for the concave distribution. The variance component estimates also show that the dissimilarity of ICC among distributions is attributed to the study design (ie, distribution of subjects) component of subject variability and not the scale quality component of rater error variability. The dependency of ICC on the distribution of subjects makes it difficult to compare results across reliability studies. Hence, it is proposed that reliability studies should be designed using a uniform distribution of subjects because of the standardization it provides for representing objective disagreement. In the absence of uniform distribution, a sampling method is proposed to reduce the non-uniformity. In addition, as expected, high levels of disagreement result in low ICC, and when the type of distribution is fixed, any increase in the number of subjects beyond a moderately large specification such as n = 80 does not have a major impact on ICC.

Statistical planning in confirmatory clinical trials with multiple treatment groups, multiple visits, and multiple endpoints.

Multiplicity issues can be multidimensional: A confirmatory clinical trial may be designed to have efficacy assessed with two or more primary endpoints, for multiple dose groups, and at several post-baseline visits. Controlling for multiplicity in this situation is challenging because there can be a hierarchy with respect to some but not all measurements. If the higher dose is considered more efficacious, multiplicity approach may evaluate the higher dose with higher priority through a fixed sequential testing framework for dose assessments in combination with a Hochberg approach for endpoints. The lower dose is only assessed when the higher dose has significant results, which reduces the power for detecting signals in the lower dose group. However, in some instances the higher dose may associate with tolerability or safety concerns that preclude regulatory approval. A real confirmatory clinical trial with such challenges is provided as an illustrative example. We discuss closed testing procedures based on multi-way averages of comparisons for this complex multiplicity situation through illustrative case analyses and a simulation study. Such strategies manage the higher dose and the lower dose with equal priority, and they enable evaluation of the multiple endpoints at multiple visits collectively with power being reasonably high.

A case study in identifying targeted patients population in major depressive disorder by enhanced enrichment design.

Despite advances in clinical trial design, failure rates near 80% in phase 2 and 50% in phase 3 have recently been reported. The challenges to successful drug development are particularly acute in central nervous system trials such as for pain, schizophrenia, mania, and depression because high-placebo response rates lessen assay sensitivity, diminish estimated treatment effect sizes, and thereby decrease statistical power. This paper addresses the importance of rigorous patient selection in major depressive disorder trials through an enhanced enrichment paradigm. This approach led to a redefinition of an ongoing, blinded phase 3 trial algorithm for patient inclusion (1) to eliminate further randomization of transient placebo responders and (2) to exclude previously randomized transient responders from the primary analysis of the double blind phase of the trial. It is illustrated for a case study for the comparison between brexpiprazole + antidepressant therapy and placebo + antidepressant therapy. Analysis of the primary endpoint showed that efficacy of brexpiprazole versus placebo could not be established statistically if the original algorithm for identification of placebo responders was used, but the enhanced enrichment approach did statistically demonstrate efficacy. Additionally, the enhanced enrichment approach identified a target population with a clinically meaningful treatment effect. Through its successful identification of a target population, the innovative enhanced enrichment approach enabled the demonstration of a positive treatment effect in a very challenging area of depression research.

Genetic association analysis under complex survey sampling: the Hispanic Community Health Study/Study of Latinos.

The cohort design allows investigators to explore the genetic basis of a variety of diseases and traits in a single study while avoiding major weaknesses of the case-control design. Most cohort studies employ multistage cluster sampling with unequal probabilities to conveniently select participants with desired characteristics, and participants from different clusters might be genetically related. Analysis that ignores the complex sampling design can yield biased estimation of the genetic association and inflation of the type I error. Herein, we develop weighted estimators that reflect unequal selection probabilities and differential nonresponse rates, and we derive variance estimators that properly account for the sampling design and the potential relatedness of participants in different sampling units. We compare, both analytically and numerically, the performance of the proposed weighted estimators with unweighted estimators that disregard the sampling design. We demonstrate the usefulness of the proposed methods through analysis of MetaboChip data in the Hispanic Community Health Study/Study of Latinos, which is the largest health study of the Hispanic/Latino population in the United States aimed at identifying risk factors for various diseases and determining the role of genes and environment in the occurrence of diseases. We provide guidelines on the use of weighted and unweighted estimators, as well as the relevant software.

Blood pressure reactivity to psychological stress is associated with clinical outcomes in patients with heart failure.

INTRODUCTION: Cardiovascular (CV) reactivity to psychological stress has been implicated in the development and exacerbation of cardiovascular disease (CVD). Although high CV reactivity traditionally is thought to convey greater risk of CVD, the relationship between reactivity and clinical outcomes is inconsistent and may depend on the patient population under investigation. The present study examined CV reactivity in patients with heart failure (HF) and its potential association with long-term clinical outcomes. METHODS: One hundred ninety-nine outpatients diagnosed with HF, with ejection fraction ≤40%, underwent an evaluation of blood pressure (BP) and heart rate reactivity to a laboratory-based simulated public-speaking stressor. Cox proportional hazards regression models were used to examine the prospective association between BP and heart rate reactivity on a combined end point of death or CV hospitalization over a 5-year median follow-up period. RESULTS: Both systolic blood pressure (SBP) and diastolic blood pressure (DBP) reactivity, quantified as continuous variables, were inversely related to risk of death or CV hospitalization (Ps < .01) after controlling for established risk factors, including HF disease severity and etiology. In similar models, heart rate reactivity was unrelated to outcome (P = .12). In models with tertiles of reactivity, high SBP reactivity, compared with intermediate SBP reactivity, was associated with lower risk (hazard ratio [HR] = .498, 95% CI .335-.742, P =.001), whereas low SBP reactivity did not differ from intermediate reactivity. For DBP, high reactivity was marginally associated with lower risk compared with intermediate DBP reactivity (HR = .767, 95% CI .515-1.14, P =.193), whereas low DBP reactivity was associated with greater risk (HR = 1.49, 95% CI 1.027-2.155, P =.0359). No relationship of heart rate reactivity to outcome was identified. CONCLUSIONS: For HF patients with reduced ejection fraction, a robust increase in BP evoked by a laboratory-based psychological challenge was associated with lower risk for adverse CVD events and may be a novel and unique marker of left ventricular systolic reserve that is accompanied by a more favorable long-term prognosis.