Wearable Sensors to Monitor Physical Activity in Heart Failure Clinical Trials: State-of-the-Art Review.

BACKGROUND: Estimation of the effects that drugs or other interventions have on patients' symptoms and functions is crucial in heart failure trials. Traditional symptoms and functions clinical outcome assessments have important limitations. Actigraphy may help to overcome these limitations due to its objective nature and the potential for continuous recording of data. However, actigraphy is not currently accepted as clinically relevant by key stakeholders. METHODS AND RESULTS: In this state-of-the-art study, the key aspects to consider when implementing actigraphy in heart failure trials are discussed. They include which actigraphy-derived measures should be considered, how to build endpoints using them, how to measure and analyze them, and how to handle the patients' and sites' logistics of integrating devices into trials. A comprehensive recommendation based on the current evidence is provided. CONCLUSION: Actigraphy is technically feasible in clinical trials involving heart failure, but successful implementation and use to demonstrate clinically important differences in physical functioning with drug or other interventions require careful consideration of many design choices.

Development and Validation of a New Hierarchical Composite End Point for Clinical Trials of Kidney Disease Progression.

SIGNIFICANCE STATEMENT: The established composite kidney end point in clinical trials combines clinical events with sustained large changes in GFR but does not weigh the relative clinical importance of the end point components. By contrast, a hierarchical composite end point (HCE) accounts for the clinical importance of the end point components. The authors developed and validated a kidney HCE that combines clinical kidney outcomes with longitudinal GFR changes (GFR slope). They demonstrate that in seven major placebo-controlled kidney outcome trials with different medications, treatment effect estimates on the HCE were consistently in similar directions and of similar magnitudes compared with treatment effects on the established kidney end point. The HCE's prioritization of clinical outcomes and ability to combine dichotomous outcomes with GFR slope make it an attractive alternative to the established kidney end point. BACKGROUND: The established composite kidney end point in clinical trials combines clinical events with sustained large changes in GFR. However, the statistical method does not weigh the relative clinical importance of the end point components. A HCE accounts for the clinical importance of the end point components and enables combining dichotomous outcomes with continuous measures. METHODS: We developed and validated a new HCE for kidney disease progression, performing post hoc analyses of seven major Phase 3 placebo-controlled trials that assessed the effects of canagliflozin, dapagliflozin, finerenone, atrasentan, losartan, irbesartan, and aliskiren in patients with CKD. We calculated the win odds (WOs) for treatment effects on a kidney HCE, defined as a hierarchical composite of all-cause mortality; kidney failure; sustained 57%, 50%, and 40% GFR declines from baseline; and GFR slope. The WO describes the odds of a more favorable outcome for receiving the active compared with the control. We compared the WO with the hazard ratio (HR) of the primary kidney outcome of the original trials. RESULTS: In all trials, treatment effects calculated with the WO reflected a similar direction and magnitude of the treatment effect compared with the HR. Clinical trials incorporating the HCE would achieve increased statistical power compared with the established composite end point at equivalent sample sizes. CONCLUSIONS: In seven major kidney clinical trials, the WO and HR provided similar direction of treatment effect estimates with smaller HRs associated with larger WOs. The prioritization of clinical outcomes and inclusion of broader composite end points makes the HCE an attractive alternative to the established kidney end point.

Validity and Utility of a Hierarchical Composite End Point for Clinical Trials of Kidney Disease Progression: A Review.

Clinical trials in nephrology often use composite end points comprising clinical events, such as onset of ESKD and initiation of kidney function replacement therapy, along with a sustained large ( e.g. , ≥50%) decrease in GFR. Such events typically occur late in the disease course, resulting in large trials in which most participants do not contribute clinical events. In addition, components of the end point are considered of equal importance; however, their clinical significance varies. For example, kidney function replacement therapy initiation is likely to be clinically more meaningful than GFR decline of ≥50%. By contrast, hierarchical composite end points (HCEs) combine multiple outcomes and prioritize each patient's most clinically relevant outcome for inclusion in analysis. In this review, we consider the use of HCEs in clinical trials of CKD progression, emphasizing the potential to combine dichotomous clinical events such as those typically used in CKD progression trials, with the continuous variable of GFR over time, while ranking all components according to clinical significance. We consider maraca plots to visualize overall treatment effects and the contributions of individual components, discuss the application of win odds in kidney HCE trials, and review general design considerations for clinical trials for CKD progression with kidney HCE as an efficacy end point.

The maraca plot: A novel visualization of hierarchical composite endpoints.

BACKGROUND: Hierarchical composite endpoints are complex endpoints combining outcomes of different types and different clinical importance into an ordinal outcome that prioritizes the clinically most important (e.g. most severe) event of a patient. Hierarchical composite endpoint can be analysed with the win odds, an adaptation of win ratio to include ties. One of the difficulties in interpreting hierarchical composite endpoint is the lack of proper tools for visualizing the treatment effect captured by hierarchical composite endpoint, given the complex nature of the endpoint which combines events of different types. METHODS: Hierarchical composite endpoints usually combine time-to-event outcomes and continuous outcomes into a composite; hence, it is important to capture not only the shift from more severe categories to less severe categories in the active group in comparison to the control group (as in any ordinal endpoint), but also changes occurring within each category. We introduce the novel maraca plot which combines violin plots (with nested box plots) to visualize the density of the distribution of the continuous outcome and Kaplan-Meier plots for time-to-event outcomes into a comprehensive visualization. CONCLUSION: The novel maraca plot is suggested for visualization of hierarchical composite endpoints consisting of several time-to-event outcomes and a continuous outcome. It has a very simple structure and therefore easily communicates both the overall treatment effect and the effect on individual components.

Tezepelumab Reduces Exacerbations Across All Seasons in Patients with Severe, Uncontrolled Asthma: A Post Hoc Analysis of the PATHWAY Phase 2b Study.

INTRODUCTION: Tezepelumab is a human monoclonal antibody that blocks thymic stromal lymphopoietin (TSLP), an epithelial cytokine implicated in airway inflammation in asthma, from binding to its heterodimeric receptor. In the PATHWAY phase 2b study, tezepelumab significantly reduced exacerbation rates compared with placebo in adults with severe, uncontrolled asthma, irrespective of baseline disease characteristics. OBJECTIVE: To evaluate the effect of tezepelumab on asthma exacerbations on a seasonal basis. METHODS: This was a post hoc analysis of the PATHWAY study (NCT02054130). Adults (N=550) with severe, uncontrolled asthma were randomized 1:1:1:1 to receive subcutaneous tezepelumab 70 mg every 4 weeks (Q4W), 210 mg Q4W or 280 mg every 2 weeks (Q2W), or placebo Q2W, for 52 weeks. The annualized asthma exacerbation rate (AAER), total number of days with an exacerbation, proportion of patients with at least one exacerbation or 0, 1 or ≥2 exacerbations, and proportion of patients experiencing an exacerbation per day were evaluated by season and over the year, by treatment in the overall study population and in subgroups according to baseline blood eosinophil count (≥300 cells/µL or <300 cells/µL) or atopic asthma status (fluoro-enzyme immunoassay [FEIA]+ or FEIA-). RESULTS: Seasonal variations in exacerbation rates were found, with peaks observed in fall and winter, and greater variations in patients with high blood eosinophil counts (≥300 cells/µL). Tezepelumab treatment consistently reduced exacerbation rates across all seasons compared with placebo. Furthermore, there was a trend, which was not significant, toward a reduction in the total number of days with exacerbations and in the proportion of patients with exacerbations during each season in patients treated with tezepelumab compared with those who received placebo, irrespective of blood eosinophil count or atopic asthma status. CONCLUSION: Tezepelumab reduced exacerbations across all seasons, irrespective of evaluated baseline disease characteristics. These data support the efficacy of tezepelumab in a broad population of patients with severe, uncontrolled asthma.

The Tendril Plot-a novel visual summary of the incidence, significance and temporal aspects of adverse events in clinical trials.

Background: In contrast to efficacy, safety hypotheses of clinical trials are not always pre-specified, and therefore, the safety interpretation work of a trial tends to be more exploratory, often reactive, and the analysis more statistically and graphically challenging. Methods: We introduce a new means of visualizing the adverse event data across an entire clinical trial. Results: The approach overcomes some of the current limitations of adverse event analysis and streamlines the way safety data can be explored, interpreted and analyzed. Using a phase II study, we describe and exemplify how the tendril plot effectively summarizes the time-resolved safety profile of two treatment arms in a single plot and how that can provide scientists with a trial safety overview that can support medical decision making. Conclusion: To our knowledge, the tendril plot is the only way to graphically show important treatment differences with preserved temporal information, across an entire clinical trial, in a single view.

Effect of weight reduction on glycated haemoglobin in weight loss trials in patients with type 2 diabetes.

AIM: To quantify the effect of weight loss on glycated haemoglobin (HbA1c) at group level, based on data from published weight loss trials in overweight and obese patients with type 2 diabetes (T2D). METHODS: A systematic literature search in MEDLINE, EMBASE and Cochrane CENTRAL (January 1990 through December 2012) was conducted to identify prospective trials of energy-reduced diets, obesity drugs or bariatric surgery in adult, overweight and obese patients with T2D. Based on clinical data with follow-up from 3 to 24 months, a linear model was developed to describe the effect of weight reduction on HbA1c. RESULTS: The literature search identified 58 eligible articles consisting of 124 treatment groups and 17 204 subjects, yielding a total of 250 data points with concurrent mean changes from baseline in weight and HbA1c. The model-based analyses indicated a linear relationship between weight loss and HbA1c reduction, with an estimated mean HbA1c reduction of 0.1 percentage points for each 1 kg of reduced body weight for the overall population. Baseline HbA1c was a significant covariate for the relationship between weight loss and HbA1c: high HbA1c at baseline was associated with a greater reduction in HbA1c for the same degree of weight loss. The collected trial data also indicated weight-loss-dependent reductions in antidiabetic medication. CONCLUSIONS: At group level, weight loss in obese and overweight patients with T2D was consistently accompanied by HbA1c reduction in a dose-dependent manner. The model developed in the present study estimates that for each kg of mean weight loss, there is a mean HbA1c reduction of 0.1 percentage points. HbA1c-lowering is greater in populations with poor glycaemic control than in well controlled populations with the same degree of weight loss. This summary of data from previous trials regarding the effect of weight reduction on HbA1c may be used to support the design and interpretation of future studies that aim to demonstrate the efficacy of weight loss interventions for T2D treatment.

Baseline anandamide levels and body weight impact the weight loss effect of CB1 receptor antagonism in male rats.

The individual weight loss response to obesity treatment is diverse. Here we test the hypothesis that the weight loss response to the CB1 receptor antagonist rimonabant is influenced by endogenous levels of receptor agonists. We show that baseline anandamide levels and body weight independently contribute to predict the treatment response to rimonabant in rodents, demonstrating that addition of biomarkers related to mode of action is relevant for a personalized health care approach to obesity treatment.

Patient Characteristics are not Associated with Clinically Important Differential Response to Dapagliflozin: a Staged Analysis of Phase 3 Data.

INTRODUCTION: This study aimed to determine if data mining methodologies could identify reproducible predictors of dapagliflozin-specific treatment response in the phase 3 clinical program dataset. METHODS: Baseline and early treatment response variables were selected and data mining used to identify/rank all variables associated with reduction in glycated hemoglobin (HbA1c) at week 26. Generalized linear modeling was then employed using an independent dataset to identify which (if any) variables were predictive of dapagliflozin-specific treatment response as compared with treatment response in the study's control arm. The most parsimonious (i.e., simplest) model was validated by meta-analysis of nine other trials. This staged approach was used to minimize risk of type I errors. RESULTS: From the large dataset, 22 variables were selected for model generation as potentially predictive for dapagliflozin-specific reduction in HbA1c. Although baseline HbA1c was the variable most strongly associated with reduction in HbA1c at study end (i.e., the best prognostic variable), baseline fasting plasma glucose (FPG) was the only predictive dapagliflozin-specific variable in the model. Placebo-adjusted treatment effect of dapagliflozin plus metformin vs. metformin alone for change in HbA1c from baseline was -0.65% at the average baseline FPG of 192.3 mg/dL (10.7 mmol/L). This response changed by -0.32% for every SD [57.2 mg/dL (3.2 mmol/L)] increase in baseline FPG. Effect of baseline FPG was confirmed in the meta-analysis of nine studies, but the magnitude was smaller. No other variable was independently predictive of a dapagliflozin-specific reduction in HbA1c. CONCLUSIONS: This methodology successfully identified a reproducible baseline predictor of differential response to dapagliflozin. Although baseline FPG was shown to be a predictor, the effect size was not of sufficient magnitude to suggest clinical usefulness in identifying patients who would uniquely benefit from dapagliflozin treatment. The findings do support potential benefit for dapagliflozin treatment that is consistent with current recommended use.