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Prediction and validation of exenatide risk marker effects on progression of renal disease: Insights from EXSCEL.

ABSTRACT: AIM:To assess whether the previously developed multivariable risk prediction framework (PRE score) could predict the renal effects observed in the EXSCEL cardiovascular outcomes trial using short-term changes in cardio-renal risk markers. MATERIALS AND METHODS:Changes from baseline to 6?months in HbA1c, systolic blood pressure (SBP), body mass index (BMI), haemoglobin, total cholesterol, and new micro- or macroalbuminuria were evaluated. The renal outcomes were defined as a composite of a sustained 30% or 40% decline in estimated glomerular filtration rate (eGFR) or end-stage renal disease (ESRD). Relationships between risk markers and long-term renal outcomes were determined in patients with type 2 diabetes from the ALTITUDE study using multivariable Cox regression analysis, and then applied to short-term changes in risk markers observed in EXSCEL to predict the exenatide-induced impact on renal outcomes. RESULTS:Compared with placebo, mean HbA1c, BMI, SBP and total cholesterol were lower at 6?months with exenatide, as was the incidence of new microalbuminuria. The PRE score predicted a relative risk reduction for the 30% eGFR decline + ESRD endpoint of 11.3% (HR 0.89; 95% CI 0.83-0.94), compared with 12.7% (HR 0.87; 0.77-0.99) observed risk reduction. For the 40% eGFR decline + ESRD endpoint, the predicted and observed risk reductions were 11.0% (HR 0.89; 0.82-0.97) and 13.7% (HR 0.86, 0.72-1.04), respectively. CONCLUSIONS:Integrating short-term risk marker changes into a multivariable risk score predicted the magnitude of renal risk reduction observed in EXSCEL.

SUBMITTER: Idzerda NMA

PROVIDER: S-EPMC7187441 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Prediction and validation of exenatide risk marker effects on progression of renal disease: Insights from EXSCEL.

Idzerda Nienke M A NMA Clegg Lindsay E LE Hernandez Adrian F AF Bakris George G Penland Robert C RC Boulton David W DW Bethel M Angelyn MA Holman Rury R RR Heerspink Hiddo J L HJL

Diabetes, obesity & metabolism 20200203 5

<h4>Aim</h4>To assess whether the previously developed multivariable risk prediction framework (PRE score) could predict the renal effects observed in the EXSCEL cardiovascular outcomes trial using short-term changes in cardio-renal risk markers.<h4>Materials and methods</h4>Changes from baseline to 6 months in HbA1c, systolic blood pressure (SBP), body mass index (BMI), haemoglobin, total cholesterol, and new micro- or macroalbuminuria were evaluated. The renal outcomes were defined as a compos ...[more]

PMID: 31912603

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Project description:BackgroundTo determine whether there were racial differences in short-term cardiometabolic responses to once-weekly exenatide (EQW) in the Exenatide Study of Cardiovascular Event Lowering (EXSCEL).MethodsEXSCEL enrolled 14,752 patients with type 2 diabetes (hemoglobin A1c (HbA1c) 6.5-10.0% [48-86 mmol/mol]) with or without cardiovascular disease who were randomized double-blind to EQW or placebo. Background glucose-lowering/other cardiovascular therapies were unaltered for 6 months post-randomization unless clinically essential, facilitating comparison of EQW-associated effects in 14,665 evaluable participants self-identifying as White (n = 11,113), Asian (n = 1444), Black (n = 870), or Other Race (n = 1,238. Placebo-adjusted 6 month absolute changes in cardiometabolic variables were assessed using generalized linear models.ResultsMean 6-month placebo-adjusted HbA1c reductions were similar in the four groups (range 0.54-0.67% [5.9 to 7.3 mmol/mol], P = 0.11 for race×treatment interaction), with no significant difference in Asians (reference) versus other groups after covariate adjustment (all P ≥ 0.10). Six-month placebo-adjusted mean changes in systolic (-1.8 to 0.0 mmHg) and diastolic (0.2 to 1.2 mmHg) blood pressure, serum LDL (- 0.06 to 0.02 mmol/L) and HDL (0.00 to 0.01 mmol/L) cholesterol, and serum triglycerides (-0.1 to 0.0 mmol/L) were similar in the racial groups (P ≥ 0.19 for race×treatment interaction and all P ≥ 0.13 for comparisons of Asians with other races). Resting pulse rate increased more in Asians (4 beats/min) than in other groups (≤ 3 beats/min, P = 0.016 for race×treatment interaction and all P ≤ 0.050 for comparisons of Asians with other races).ConclusionsShort-term cardiometabolic responses to EQW were similar in the main racial groups in EXSCEL, apart from a greater pulse rate increase in Asians.Trial registration https://clinicaltrials.gov NCT01144338.

Project description:Background In the EXSCEL (Exenatide Study of Cardiovascular Event Lowering), exenatide once-weekly resulted in a nonsignificant reduction in major adverse cardiovascular events ( MACEs ) and a nominal 14% reduction in all-cause mortality in 14 752 patients with type 2 diabetes mellitus (T2 DM ) with and without cardiovascular disease. Whether patients at increased risk for events experienced a comparatively greater treatment benefit with exenatide is unknown. Methods and Results In the EXSCEL population, we created risk scores for MACEs and all-cause mortality using step-wise selection of baseline characteristics. A risk score was calculated for each patient, and a time-to-event model for each end point was developed including the risk score, treatment assignment, and risk-treatment interaction. Interaction P values evaluating for a differential treatment effect by baseline risk were reported. Over a median follow-up of 3.2 years (interquartile range, 2.2, 4.4), 1091 (7.4%) patients died and 1744 (11.8%) experienced a MACE . Independent predictors of MACEs and all-cause mortality included age, sex, comorbidities (eg, previous cardiovascular event), body mass index, blood pressure, hemoglobin A1c, and estimated glomerular filtration rate. The all-cause mortality and MACE risk models had modest discrimination with optimism-corrected c-indices of 0.73 and 0.71, respectively. No interaction was observed between treatment effect and risk profile for either end point (both interactions, P>0.1). Conclusions Baseline characteristics (eg, age, previous cardiovascular events) and routine laboratory values (eg, hemoglobin A1c, estimated glomerular filtration rate) provided modest prognostic value for mortality and MACEs in a broad population of patients with type 2 diabetes mellitus. Exenatide's effects on mortality and MACEs were consistent across the spectrum of baseline risk. Clinical Trial Registration URL: https://www.clinicaltrials.gov . Unique identifier: NCT 01144338.

Project description:BACKGROUND:Once-weekly exenatide (EQW) had a neutral effect on hospitalization for heart failure (HHF) in the EXSCEL study (Exenatide Study of Cardiovascular Event Lowering), with no differential treatment effect on major adverse cardiac events by baseline heart failure (HF) status. EQW's effects on secondary end points based on HHF status have not been reported. The objective was to explore the effects of EQW on secondary end points in patients with and without baseline HF and test the effects of EQW on recurrent HHF events. METHODS:The prespecified analysis of the randomized controlled EXSCEL trial, which enrolled patients with type 2 diabetes mellitus with and without additional cardiovascular disease, analyzed EQW effects on all-cause death, each major adverse cardiac event component, first HHF, and repeat HHF, by baseline HF status (regardless of ejection fraction). A subgroup analysis of the population stratified by preserved or reduced baseline ejection fraction was performed. RESULTS:Of 14 752 EXSCEL participants, 2389 (16.2%) had HF at baseline. Compared with those without HF at baseline, patients with preexisting HF were older, and more likely to be male and white, with a higher burden of other cardiovascular diseases. Overall, those assigned to EQW had a lower incidence of all-cause death (hazard ratio [HR], 0.86 [95% CI, 0.77-0.97]) and the composite outcome of all-cause death or HHF (HR, 0.89 [95% CI, 0.80-0.99]). When stratified by presence or absence of baseline HF, there was no observed reduction in all-cause death with EQW with baseline HF (HR, 1.05 [95% CI, 0.85-1.29]), while the risk of mortality was reduced with EQW in the no-HF group (HR, 0.79 [95% CI, 0.68-0.92]) with an interaction P value of 0.031. The reduction in all-cause death or HHF seen with EQW in patients without baseline HF (HR, 0.81 [95% CI, 0.71-0.93]) was not seen in patients with baseline HF (HR, 1.07 [95% CI, 0.89-1.29]; interaction P=0.015). First, plus recurrent, HHF was reduced in the exenatide group versus placebo (HR, 0.82 [95% CI, 0.68-0.99]; P=0.038). CONCLUSIONS:In EXSCEL, the use of EQW in patients with or without HF was well tolerated, but benefits of EQW on reduction in all-cause death and first hospitalization for HF were attenuated in patients with baseline HF. CLINICAL TRIAL REGISTRATION:https://www.clinicaltrials.gov. Unique identifier: NCT01144338.

Project description:Ductal carcinoma in situ (DCIS) is a preinvasive form of breast cancer with a highly variable potential of becoming invasive and affecting mortality of the patients. Due to the lack of accurate markers of disease progression, many women with detected DCIS are currently overtreated. To distinguish those DCIS cases who are likely to require therapy from those who should be left untreated, there is a need for robust and predictive biomarkers extracted from molecular or genetic profiles. We developed a supervised machine learning approach that implements multi-omics feature selection and model regularization for the identification of biomarker combinations that could be used to distinguish low-risk DCIS lesions from those with a higher likelihood of progression. To investigate the genetic heterogeneity of disease progression, we applied this approach to 40 pure DCIS and 259 invasive breast cancer (IBC) samples profiled with genome-wide transcriptomics, DNA methylation, and DNA copy number variation. Feature selection using the multi-omics Lasso-regularized algorithm identified both known genes involved in breast cancer development, as well as novel markers for early detection. Even though the gene expression-based model features led to the highest classification accuracy alone, methylation data provided a complementary source of features and improved especially the sensitivity of correctly classifying DCIS cases. We also identified a number of repeatedly misclassified DCIS cases when using either the expression or methylation markers. A small panel of 10 gene markers was able to distinguish DCIS and IBC cases with high accuracy in nested cross-validation (AU-ROC = 0.99). The marker panel was not specific to any of the established breast cancer subtypes, suggesting that the 10-gene signature may provide a subtype-agnostic and cost-effective approach for breast cancer detection and patient stratification. We further confirmed high accuracy of the 10-gene signature in an external validation cohort (AU-ROC = 0.95), profiled using distinct transcriptomic assay, hence demonstrating robustness of the risk signature.

Dataset Information

Prediction and validation of exenatide risk marker effects on progression of renal disease: Insights from EXSCEL.

Publications

Prediction and validation of exenatide risk marker effects on progression of renal disease: Insights from EXSCEL.

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