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Aims: To develop a clinical risk model to identify individuals at higher risk of developing new‐onset diabetes and who might benefit more from weight loss pharmacotherapy. Materials and Methods: A total of 21 143 patients without type 2 diabetes at baseline from two TIMI clinical trials of stable cardiovascular patients were divided into a derivation (~2/3) and validation (~1/3) cohort. The primary outcome was new‐onset diabetes. Twenty‐seven candidate risk variables were considered, and variable selection was performed using multivariable Cox regression. The final model was evaluated for discrimination and calibration, and for its ability to identify patients who experienced a larger benefit from the weight loss medication lorcaserin in terms of risk of new‐onset diabetes. Results: During a median (interquartile range) follow‐up of 2.3 (1.8–2.7) years, new‐onset diabetes occurred in 1013 patients (7.7%). The final model included five independent predictors (glycated haemoglobin, fasting glucose, age, body mass index, and triglycerides/high‐density lipoprotein). The clinical risk model showed good discrimination (Harrell's C‐indices 0.802, 95% confidence interval [CI] 0.788–0.817 and 0.807, 95% CI 0.788–0.826) in the derivation and validation cohorts. The calibration plot demonstrated adequate calibration (2.5‐year area under the curve was 81.2 [79.1–83.5]). While hazard ratios for new‐onset diabetes with a weight‐loss therapy were comparable across risk groups (annual risks of <1%, 1%–5%, and >5%), there was a sixfold gradient in absolute risk reduction from lowest to highest risk group (p = 0.027). Conclusions: The developed clinical risk model effectively predicts new‐onset diabetes, with potential implications for personalized patient care and therapeutic decision making. [ABSTRACT FROM AUTHOR]

Interaction analysis is a critical component of clinical and public health research and represents a key topic in precision health and medicine. In applied settings, however, interaction assessment is usually limited to the test of a product term in a regression model and to the presentation of results stratified by levels of additional covariates. Stratification of results often relies on categorizing or making linearity assumptions for continuous covariates, with substantial loss of precision and of relevant information. In time-to-event analysis, moreover, interaction assessment is often limited to the multiplicative hazard scale by inclusion of a product term in a Cox regression model, disregarding the clinically relevant information that is captured by the absolute risk scale. In this paper we present a user-friendly procedure, based on the prediction of individual absolute risks from the Cox model, for the estimation and presentation of interactive effects on both the multiplicative and additive scales in survival analysis. We describe how to flexibly incorporate interactions with continuous covariates, which potentially operate in a nonlinear fashion, provide software for replicating our procedure, and discuss different approaches to deriving CIs. The presented approach will allow clinical and public health researchers to assess complex relationships between multiple covariates as they relate to a clinical endpoint, and to provide a more intuitive and precise depiction of the results in applied research papers focusing on interaction and effect stratification. [ABSTRACT FROM AUTHOR]

BACKGROUND: Cardiovascular trials often use a composite end point and a time-to-first event model. We sought to compare edoxaban versus warfarin using the win ratio, which offers data complementary to time-to-first event analysis, emphasizing the most severe clinical events. METHODS: ENGAGE AF-TIMI 48 (Effective Anticoagulation With Factor Xa Next Generation in Atrial Fibrillation-Thrombolysis in Myocardial Infarction 48) was a double-blind, randomized trial in which patients with atrial fibrillation were assigned 1:1:1 to a higher dose edoxaban regimen (60/30 mg daily), a lower dose edoxaban regimen (30/15 mg daily), or warfarin. In an exploratory analysis, we analyzed the trial outcomes using an unmatched win ratio approach. The win ratio for each edoxaban regimen was the total number of edoxaban wins divided by the number of warfarin wins for the following ranked clinical outcomes: 1: death; 2: hemorrhagic stroke; 3: ischemic stroke/systemic embolic event/epidural or subdural bleeding; 4: noncerebral International Society on Thrombosis and Haemostasis major bleeding; and 5: cardiovascular hospitalization. RESULTS: 21 105 patients were randomized to higher dose edoxaban regimen (N=7035), lower dose edoxaban regimen (N=7034), or warfarin (N=7046), yielding >49 million pairs for each treatment comparison. The median age was 72 years, 38% were women, and 59% had prior vitamin K antagonist use. The win ratio was 1.11 (95% CI, 1.05-1.18) for higher dose edoxaban regimen versus warfarin and 1.11 (95% CI, 1.05-1.18) for lower dose edoxaban regimen versus warfarin. The favorable impacts of edoxaban on death (34% of wins) and cardiovascular hospitalization (41% of wins) were the major contributors to the win ratio. Results consistently favored edoxaban in subgroups based on creatine clearance and dose reduction at baseline, with heightened benefit among those without prior vitamin K antagonist use. CONCLUSIONS: In a win ratio analysis of the ENGAGE AF-TIMI 48 trial, both dose regimens of edoxaban were superior to warfarin for the net clinical outcome incorporating ischemic and bleeding events. As the win ratio emphasizes the most severe clinical events, this analysis supports the superiority of edoxaban over warfarin in patients with atrial fibrillation. [ABSTRACT FROM AUTHOR]

Importance: Elevated lipoprotein(a) (Lp[a]) is a putative causal risk factor for atherosclerotic cardiovascular disease (ASCVD). There are conflicting data as to whether Lp(a) may increase cardiovascular risk only in the presence of concomitant inflammation., Objective: To investigate whether Lp(a) is associated with cardiovascular risk independent of high-sensitivity C-reactive protein (hs-CRP) in both primary and secondary prevention populations., Design, Setting, and Participants: This cohort study uses data from 3 distinct cohorts, 1 population-based cohort and 2 randomized clinical trials. Participants included individuals from the UK Biobank (data from 2006-2010) without prevalent ASCVD, participants in the FOURIER (TIMI 59) trial (data from 2013-2017) who had baseline Lp(a) and hs-CRP data, and participants in the SAVOR-TIMI 53 trial (data from 2010-2013) who had prevalent ASCVD and baseline values for Lp(a) and hs-CRP. The data analysis took place from November 2022 to November 2023., Exposure: Baseline plasma Lp(a), considered either as a continuous variable or dichotomized at 125 nmol/L., Main Outcomes and Measures: Risk of major adverse cardiovascular events (MACE) (composite of cardiovascular death, myocardial infarction [MI], or ischemic stroke), the individual MACE components, and peripheral artery disease (PAD)., Results: Among 357 220 individuals in the UK Biobank without prevalent ASCVD, 232 699 (65%) had low hs-CRP (<2 mg/L), and 124 521 (35%) had high hs-CRP (≥2 mg/L) values. In a Cox proportional hazard model adjusted for ASCVD risk factors, higher Lp(a) was associated with increased cardiovascular risk regardless of baseline hs-CRP value for MACE (hs-CRP ≥2 mg/L: hazard ratio [HR] per 50-nmol/L higher Lp[a], 1.05; 95% CI, 1.04-1.07; P < .001; for hs-CRP <2 mg/L: HR, 1.05; 95% CI, 1.04-1.07; P < .001; P = .80 for interaction), as well as MI, ischemic stroke, and PAD individually. Among 34 020 individuals in the FOURIER and SAVOR trials with baseline cardiometabolic disease, there were 17 643 (52%) with low and 16 377 (48%) with high baseline hs-CRP values. In Cox proportional hazard models using aggregated data from FOURIER and SAVOR, higher baseline Lp(a) was associated with increased cardiovascular risk regardless of baseline hs-CRP for MACE (hs-CRP ≥2 mg/L: HR per 50-nmol/L higher Lp[a], 1.02; 95% CI, 1.00-1.05; P = .04; hs-CRP <2 mg/L: HR, 1.05; 95% CI, 1.02-1.08; P < .001; P = .16 for interaction), MI, and PAD., Conclusions and Relevance: In this study, higher levels of Lp(a) were associated with MACE, MI, and PAD in both primary and secondary prevention populations regardless of baseline hs-CRP value.