Association of Cardiac Biomarkers With Major Adverse Cardiovascular Events in High-risk Patients With Diabetes: A Secondary Analysis of the DECLARE-TIMI 58 Trial

Thomas A Zelniker; Stephen D Wiviott; Ofri Mosenzon; Erica L Goodrich; Petr Jarolim; Avivit Cahn; Deepak L Bhatt; Lawrence A Leiter; Darren K McGuire; John Wilding; Oleg Averkov; Andrzej Budaj; Alexander Parkhomenko; Kausik K Ray; Ingrid Gause-Nilsson; Anna Maria Langkilde; Martin Fredriksson; Itamar Raz; Marc S Sabatine; David A Morrow

doi:10.1001/jamacardio.2023.0019

. 2023 Mar 1;8(5):503–509. doi: 10.1001/jamacardio.2023.0019

Association of Cardiac Biomarkers With Major Adverse Cardiovascular Events in High-risk Patients With Diabetes

A Secondary Analysis of the DECLARE-TIMI 58 Trial

Thomas A Zelniker ¹, Stephen D Wiviott ², Ofri Mosenzon ³, Erica L Goodrich ², Petr Jarolim ⁴, Avivit Cahn ³, Deepak L Bhatt ⁵, Lawrence A Leiter ⁶, Darren K McGuire ⁷, John Wilding ⁸, Oleg Averkov ⁹, Andrzej Budaj ¹⁰, Alexander Parkhomenko ¹¹, Kausik K Ray ¹², Ingrid Gause-Nilsson ¹³, Anna Maria Langkilde ¹³, Martin Fredriksson ¹³, Itamar Raz ³, Marc S Sabatine ^2,¹⁴, David A Morrow ^2,^✉

¹Division of Cardiology, Medical University of Vienna, Vienna, Austria

²TIMI Study Group, Cardiovascular Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts

³The Diabetes Unit, Department of Endocrinology and Metabolism, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel

⁴Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts

⁵Mount Sinai Heart, Icahn School of Medicine at Mount Sinai Health System, New York, New York

⁶Li Ka Shing Knowledge Institute, St Michael’s Hospital, University of Toronto, Toronto, Ontario, Canada

⁷Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, Texas

⁸Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, United Kingdom

⁹Pirogov Russian National Research Medical University, Moscow, Russia

¹⁰Centre of Postgraduate Medical Education, Grochowski Hospital, Warsaw, Poland

¹¹Institute of Cardiology, Kyiv, Ukraine

¹²Imperial Centre for Cardiovascular Disease Prevention and Imperial Clinical Trials Unit, Imperial College London, London, United Kingdom

¹³BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

¹⁴Deputy Editor, JAMA Cardiology

Accepted for Publication: January 3, 2023.

Published Online: March 1, 2023. doi:10.1001/jamacardio.2023.0019

^✉

Corresponding Author: David A. Morrow, MD, MPH, TIMI Study Group, Cardiovascular Division, Brigham and Women’s Hospital, Harvard Medical School, 60 Fenwood Rd, Ste 7022-7024W, Boston, MA 02115 (dmorrow@partners.org).

Author Contributions: Drs Zelniker and Morrow had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Zelniker, Bhatt, McGuire, Averkov, Gause-Nilsson, Langkilde, Sabatine, Morrow.

Acquisition, analysis, or interpretation of data: Zelniker, Wiviott, Mosenzon, Goodrich, Jarolim, Cahn, Bhatt, Leiter, McGuire, Wilding, Budaj, Parkhomenko, Ray, Gause-Nilsson, Langkilde, Fredriksson, Raz, Sabatine, Morrow.

Drafting of the manuscript: Zelniker, Raz, Morrow.

Critical revision of the manuscript for important intellectual content: Zelniker, Wiviott, Mosenzon, Goodrich, Jarolim, Cahn, Bhatt, Leiter, McGuire, Wilding, Averkov, Budaj, Parkhomenko, Ray, Gause-Nilsson, Langkilde, Fredriksson, Sabatine, Morrow.

Statistical analysis: Zelniker, Goodrich.

Obtained funding: Jarolim, Sabatine, Morrow.

Administrative, technical, or material support: Jarolim.

Study supervision: Cahn, McGuire, Averkov, Parkhomenko, Gause-Nilsson, Langkilde, Fredriksson, Raz, Sabatine, Morrow.

Conflict of Interest Disclosures: Dr Zelniker reported grants from AstraZeneca during the conduct of the study; grants from Austrian Science Funds, German Research Foundation, and Eli Lilly and Co; and personal fees from AstraZeneca, Boehringer Ingelheim, Alkem Lab, Bayer AG, and Sun Pharmaceuticals outside the submitted work. Dr Wiviott reported grants from AstraZeneca during the conduct of the study; grants from Amgen, AstraZeneca, Daiichi Sankyo, Eisai, Janssen, Merck, and Pfizer; and personal fees from AstraZeneca, Boston Clinical Research Institute, Icon Clinical, and Novo Nordisk outside the submitted work; and his spouse is an employee of Merck. Dr Mosenzon reported grants from AstraZeneca and personal fees from AstraZeneca during the conduct of the study; grants from Novo Nordisk; and personal fees from Novo Nordisk, Boehringer Ingelheim, Eli Lilly, Sanofi, and Merck Sharp & Dohme outside the submitted work. Dr Goodrich reported grants from AstraZeneca during the conduct of the study. Dr Jarolim reported grants from AstraZeneca, Abbott Laboratories, Amgen, Roche Diagnostics, Siemens Healthineers, and Merck during the conduct of the study. Dr Cahn reported grants and personal fees from AstraZeneca during the conduct of the study as well as personal fees from Novo Nordisk, Eli Lilly, Sanofi, Boehringer Ingelheim, and Medial EarlySign outside the submitted work. Dr Bhatt reported grants from AstraZeneca during the conduct of the study; grants from Boehringer Ingelheim, Lexicon, and Sanofi outside the submitted work; research funding from Abbott, Acesion Pharma, Afimmune, Aker Biomarine, Amarin, Amgen, AstraZeneca, Bayer, Beren, Boehringer Ingelheim, Boston Scientific, Bristol Myers Squibb, Cardax, CellProthera, Cereno Scientific, Chiesi, CinCor, CSL Behring, Eisai, Ethicon, Faraday Pharmaceuticals, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, Garmin, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Javelin, Lexicon, Lilly, Medtronic, Merck, Moderna, MyoKardia, NirvaMed, Novartis, Novo Nordisk, Owkin, Pfizer, PhaseBio, PLx Pharma, Recardio, Regeneron, Reid Hoffman Foundation, Roche, Sanofi, Stasys, Synaptic, The Medicines Company, Youngene, and 89Bio; honoraria from American College of Cardiology, Arnold and Porter Law Firm, Baim Institute for Clinical Research, Belvoir Publications, Canadian Medical and Surgical Knowledge Translation Research Group, Cowen and Company, Duke Clinical Research Institute, HMP Global, Journal of the American College of Cardiology, Clinical Cardiology, K2P, Level Ex, Medtelligence/ReachMD, MJH Life Sciences, Oakstone CME, Piper Sandler, Population Health Research Institute, Slack Publications, Society of Cardiovascular Patient Care, WebMD, and Wiley; royalties from Elsevier; unfunded research support from FlowCo and Takeda; has consulted for Broadview Ventures; serves on an advisory board for AngioWave, Bayer, Boehringer Ingelheim, Cardax, CellProthera, Cereno Scientific, Elsevier Practice Update Cardiology, High Enroll, Janssen, Level Ex, McKinsey, Medscape Cardiology, Merck, MyoKardia, NirvaMed, Novo Nordisk, PhaseBio, PLx Pharma, Regado Biosciences, and Stasys; serves on a board of directors for AngioWave, Boston VA Research Institute, Bristol Myers Squibb, DRS.LINQ, High Enroll, Society of Cardiovascular Patient Care, and TobeSoft; serves on data monitoring committees for Acesion Pharma, Assistance Publique-Hôpitaux de Paris, Baim Institute for Clinical Research, Boston Scientific, Cleveland Clinic, Contego Medical, Duke Clinical Research Institute, Mayo Clinic, Mount Sinai School of Medicine, Novartis, Population Health Research Institute, and Rutgers University; is chair for the American Heart Association Quality Oversight Committee, NCDR-ACTION Registry Steering Committee, and VA CART Research and Publications Committee; is a site coinvestigator for Abbott, Biotronik, Boston Scientific, CSI, Endotronix, St Jude Medical, Philips, SpectraWAVE, Svelte, and Vascular Solutions; and has a patent for Lexicon pending. Dr Leiter reported personal fees from AstraZeneca during the conduct of the study as well as personal fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Lexicon, Merck, Novo Nordisk, Pfizer, Sanofi, and Servier outside the submitted work. Dr McGuire reported personal fees from AstraZeneca during the conduct of the study as well as personal fees from AstraZeneca, Boehringer Ingelheim, Merck, Pfizer, Novo Nordisk, Esperion, Lilly, CSL Behring, Applied Therapeutics, Metavant, Sanofi, Afimmune, Bayer, GlaxoSmithKline, Lexicon, Altimmune, Intercept Pharmaceuticals, and Kirkland & Ellis outside the submitted work. Dr Wilding reported institutional fees from AstraZeneca during the conduct of the study; personal fees from Boehringer Ingelheim, Novo Nordisk, AstraZeneca, and Sanofi; and institutional fees from AstraZeneca, Boehringer Ingelheim, Novo Nordisk, Lilly, Mundipharma, Pfizer, Rhythm, Saniona, and Ysopia outside the submitted work. Dr Averkov reported personal fees from AstraZeneca, Sanofi-Aventis, Bayer, Bristol Myers Squibb, Pfizer, Aspen, and Servier outside the submitted work. Dr Budaj reported personal fees from AstraZeneca during the conduct of the study as well as personal fees from Bristol Myers Squibb/Pfizer, Sanofi-Aventis, GlaxoSmithKline, Eisai, Bayer, Amgen, Novartis, and Novo Nordisk outside the submitted work. Dr Parkhomenko reported grants and personal fees from AstraZeneca as well as personal fees from Sanofi-Aventis, Novo Nordisk, Boehringer Ingelheim, Novartis, ACINO, Bayer, and Amgen outside the submitted work. Dr Ray reported personal fees from AstraZeneca during the conduct of the study; grants from Sanofi, Daiichi Sankyo, Regeneron, and Amgen; personal fees from AstraZeneca, Boehringer Ingelheim, Novo Nordisk, Novartis, Esperion, Eli Lilly, Silence Therapeutics, Kowa, Bayer, Amgen, Sanofi, Cargene, New Amsterdam, Daiichi Sankyo, Vaxxinity, Scribe Therapeutics, Abbott, and Pemi31 outside the submitted work. Dr Sabatine reported grants and personal fees from AstraZeneca during the conduct of the study; grants from Abbott, Amgen, Pfizer, Novartis, Ionis, Merck, Intarcia, Daiichi Sankyo, Eisai, and Anthos Therapeutics; and personal fees from Althera, Amgen, Anthos Therapeutics, Beren Therapeutics, Boehringer Ingelheim, Bristol Myers Squibb, Fibrogen, Intarcia, Merck, Moderna, Novo Nordisk, and Silence Therapeutics outside the submitted work. Dr Morrow reported grants from AstraZeneca and Roche Diagnostics during the conduct of the study; grants from Abbott Laboratories, Anthos Therapeutics, ARCA Biopharma, AstraZeneca, Merck, Novartis, Pfizer, Regeneron, and Siemens; and personal fees from Abbott Laboratories, ARCA Biopharma, InCarda Therapeutics, Inflammatix, Merck, Novartis, and Roche Diagnostics outside the submitted work. No other disclosures were reported.

Funding/Support: The DECLARE-TIMI 58 trial was funded by AstraZeneca. Drs Wiviott, Sabatine, and Morrow were supported by grants from the American Heart Association Strategically-Focused Research Network.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: Dr Sabatine is Deputy Editor of JAMA Cardiology, but he was not involved in any of the decisions regarding review of the manuscript or its acceptance.

Data Sharing Statement: See Supplement 2.

^✉

Corresponding author.

PMCID: PMC9979005 PMID: 36857035

Key Points

Question

Can cardiac biomarkers identify patients with type 2 diabetes (T2D) at higher risk and who benefit more from dapagliflozin for atherosclerotic events?

Findings

In this substudy of the DECLARE-TIMI 58 trial including 14 565 patients, baseline N-terminal pro–B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hsTnT) concentrations did not modify the relative treatment effect of dapagliflozin vs placebo on major adverse cardiovascular events (MACE). However, event rates were lower in dapagliflozin-treated vs placebo-treated patients with biomarker levels in the top quartile, whereas event rates did not differ between treatment groups in patients with biomarkers levels in quartiles 1 to 3.

Meaning

In this study, NT-proBNP and hsTnT were associated with MACE in patients with T2D at high risk of atherosclerotic events, and in individuals with high levels of both biomarkers, dapagliflozin was associated with reduced MACE event rates.

This secondary analysis of the DECLARE-TIMI 58 trial evaluates whether N-terminal pro–B-type natriuretic peptide and high-sensitivity cardiac troponin T levels can identify a subset of patients with type 2 diabetes at higher risk and who might benefit more from dapagliflozin with regard to atherosclerotic events.

Abstract

Importance

Dapagliflozin reduces the risk of hospitalizations for heart failure and the progression of chronic kidney disease in patients with and without type 2 diabetes (T2D), whereas the effects on reducing atherosclerotic events appear less clear.

Objective

To explore whether N-terminal pro–B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hsTnT) levels can identify a subset of patients with T2D at higher risk and who might benefit more from dapagliflozin with regard to atherosclerotic events.

Design, Setting, and Participants

This was a secondary analysis of the DECLARE-TIMI 58 trial, a randomized clinical trial of dapagliflozin in patients with T2D and either multiple risk factors for atherosclerotic cardiovascular disease (ASCVD; approximately 60%) or established ASCVD (approximately 40%). All patients with available blood samples at randomization were included in these analyses. Data were collected from May 2013 to September 2018, and data were analyzed from May 2019 to June 2022.

Interventions

Dapagliflozin vs placebo.

Main Outcomes and Measures

Major adverse cardiovascular events (MACE), the composite of myocardial infarction, ischemic stroke, or cardiovascular death, which was one of dual primary outcomes of the main trial.

Results

Of 14 565 included patients, 9143 (62.8%) were male, and the mean (SD) age was 63.9 (6.8) years. When tested individually in a multivariable model for MACE risk, NT-proBNP and hsTnT were each significantly associated with the risk of MACE (adjusted hazard ratio [aHR] per 1 SD in log-transformed biomarker: NT-proBNP, 1.62; 95% CI, 1.49-1.76; hsTnT: 1.59; 95% CI, 1.46-1.74). The magnitude of the association was similar in patients with ASCVD (NT-proBNP: aHR, 1.60; 95% CI, 1.45-1.77; hsTnT: aHR, 1.62; 95% CI, 1.45-1.81) and multiple risk factors for ASCVD (NT-proBNP: aHR, 1.62; 95% CI, 1.40-1.88; hsTnT: aHR, 1.51; 95% CI, 1.29-1.77). Moreover, both biomarkers remained independently associated with MACE when both were included in the multivariable model (NT-proBNP: aHR, 1.46; 95% CI, 1.34-1.60; hsTnT: aHR, 1.39; 95% CI, 1.26-1.53). Modeled as a continuous variable, baseline biomarker levels did not modify the relative treatment effect of dapagliflozin vs placebo with MACE. However, the relative risk reduction numerically grew with higher biomarker levels, as did the baseline risk. Thus, MACE event rates were nominally lower in dapagliflozin-treated vs placebo-treated patients with biomarker concentrations in the top quartile (NT-proBNP: HR, 0.83; 95% CI, 0.71-0.97; absolute risk reduction [ARR], 2.4%; hsTnT: HR, 0.85; 95% CI, 0.72-0.99; ARR, 2.7%), whereas there was no significant treatment effect in patients with biomarkers levels in quartiles 1 to 3 (NT-proBNP: HR, 1.02; 95% CI, 0.88-1.18; ARR, 0%; hsTnT: HR, 0.97; 95% CI, 0.84-1.13; ARR, 0.2%).

Conclusions and Relevance

In this study, NT-proBNP and hsTnT levels were associated with the risk for future cardiovascular events in both primary and secondary prevention patients with T2D. Both cardiac biomarkers were helpful to identify patients at very high risk for atherosclerotic events that may derive reduction in risk of MACE with dapagliflozin.

Trial Registration

ClinicalTrials.gov Identifier: NCT01730534

Introduction

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) reduce hospitalizations for heart failure (HF) and progression of chronic kidney disease (CKD) in patients with and without type 2 diabetes (T2D).^1,2 However, their effects on reducing atherosclerotic events appear modest across the population of patients with T2D with heterogeneity observed among studied populations.^3,4,5,6,7

The Dapagliflozin Effect on Cardiovascular Events—Thrombolysis in Myocardial Infarction 58 (DECLARE-TIMI 58) trial tested the SGLT2i dapagliflozin in 17 160 patients with T2D with preserved kidney function and either multiple risk factors (ie, men 55 years and older or women 60 years and older who had at least 1 of the following risk factors: hypertension, dyslipidemia, or smoking) or established atherosclerotic cardiovascular disease (ASCVD; defined as clinically evident ischemic heart disease, cerebrovascular disease, or peripheral artery disease) over a median follow-up of 4.2 years. Dapagliflozin reduced the risk of cardiovascular death and hospitalization for HF (HHF) but, in the overall population, did not reduce the risk of major adverse cardiovascular events (MACE; hazard ratio [HR], 0.93; 95% CI, 0.84-1.03).⁸ This finding was consistent in patients with multiple risk factors and ASCVD, although a nominally significant reduction of MACE was observed in patients with prior myocardial infarction (MI) and those with long-standing diabetes.^9,10

We previously reported the association of cardiac biomarkers and the risk of cardiovascular death and HHF.¹¹ Treatment with dapagliflozin reduced the risk of cardiovascular death and HHF irrespective of baseline N-terminal pro–B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hsTnT) concentrations, but NT-proBNP and hsTnT identified cohorts with higher biomarker concentrations who derived greater absolute risk reductions. Here, we assessed the association between NT-proBNP and hsTnT and ASCVD outcomes and whether these biomarkers identified a subset of patients with T2D who benefit from SGLT2i with regard to atherosclerotic events.

Methods

Study Population

This was a nested biomarker study from DECLARE-TIMI 58.^8,12,13 As described previously,¹¹ NT-proBNP (n = 14 562) and hsTnT (n = 14 551) were measured among all patients with available randomization blood samples in the TIMI Clinical Trials Laboratory, Boston, Massachusetts. The trial and this analysis were approved by the institutional review boards of all participating sites, including at Brigham and Women’s Hospital as the supervising coordinating center. Written informed consent was obtained from all trial participants.

Outcomes of Interest

The primary outcome of interest for these analyses was MACE, the composite of MI, ischemic stroke, and cardiovascular death, which was one of the dual primary outcomes of the trial. We previously reported the relationship of cardiac biomarkers and the other dual primary outcome, the risk for cardiovascular death and HHF.¹¹ All outcome events were adjudicated by a masked clinical events committee.

Biomarker Levels

Serum NT-proBNP concentrations were measured at the first thaw using an electrochemiluminescent immunoassay on the cobas e601 analyzer (proBNP II; Roche Diagnostics). This assay has a measuring range of 10 to 35 000 pg/mL. Reference limits for NT-proBNP levels are less than 125 pg/mL in people younger than 75 years and less than 450 pg/mL in people 75 years and older. hsTnT was measured with a high-sensitivity electrochemiluminescent immunoassay on the Roche cobas 601 analyzer (Elecsys Troponin T Gen 5 STAT; Roche Diagnostics). The limit of quantitation of the assay is 6 ng/L. We applied a 99th percentile upper reference limit for hsTnT of 14 ng/L.

Statistical Analysis

Kaplan-Meier event rates at 4 years are reported and illustrated using cumulative incidence curves. Log-rank tests for trend were used to compare event rates across biomarker quartiles. We used Cox models adjusted for age, sex, race, smoking, estimated glomerular filtration rate, body mass index, diabetes duration, insulin use, prior coronary artery disease, MI, ischemic stroke, peripheral artery disease, HF, dyslipidemia, and hypertension to assess the association between baseline biomarker concentrations and incident MACE. We added an interaction term along with the main effects for each biomarker and the treatment effect of dapagliflozin to test for treatment effect modification by biomarker values. To explore a nonlinear association between biomarker concentrations and the treatment effect of dapagliflozin, we further fitted adjusted Cox models with biomarker concentrations as cubic splines. All analyses were performed using R version 3.6.0 (The R Foundation) or SAS version 9.4 (SAS Institute). Two-sided P values < .05 were considered to indicate nominal statistical significance.

Results

Study Population

Among 14 565 included patients, 9143 patients (62.8%) were male, the mean (SD) age was 63.9 (6.8) years, and the median (IQR) duration of diabetes was 11 (6-16) years. A total of 5974 (41.0%) had established ASCVD, and 3101 (21.3%) had a prior MI. The median (IQR) NT-proBNP and hsTnT levels were 75 (35-165) pg/mL and 10.2 (6.9-15.5) ng/L, respectively. The baseline characteristics by biomarker quartile are shown in eTables 1 and 2 in Supplement 2.

Association Between Baseline Cardiac Biomarkers and MACE Within the Placebo Arm

Among those allocated to placebo, patients with higher baseline biomarker concentrations had higher rates of MACE (Figure 1). A stepwise gradient of risk from quartiles 1 to 3 with a steep increase in quartile 4 was observed in both patients with established ASCVD (quartile 4 vs quartile 1: NT-proBNP, 22.9% vs 8.5%; P for trend < .001; hsTnT, 24.2% vs 7.2%; P for trend < .001) as well as multiple risk factors (quartile 4 vs quartile 1: NT-proBNP, 11.4% vs 3.0%; P for trend < .001; hsTnT, 10.1% vs 3.1%; P for trend < .001) (Figure 1). Patients with multiple risk factors and biomarker levels in quartile 4 had similar event rates compared with patients with ASCVD with low biomarker concentrations.

This association remained apparent after multivariable adjustment (adjusted HR [aHR] per 1 SD in log-transformed biomarker: NT-proBNP, 1.62; 95% CI, 1.49-1.76; hsTnT: 1.59; 95% CI, 1.46-1.74) (Figure 2). The magnitude of the association was similar in patients with ASCVD (aHR per 1 SD in log-transformed biomarker: NT-proBNP: aHR, 1.60; 95% CI, 1.45-1.77; hsTnT: aHR, 1.62; 95% CI, 1.45-1.81) and patients with multiple risk factors (adjusted HR [aHR] per 1 SD in log-transformed biomarker: NT-proBNP: aHR, 1.62; 95% CI, 1.40-1.88; hsTnT: aHR, 1.51; 95% CI, 1.29-1.77). Moreover, both biomarkers remained independently associated with MACE (and the individual components) when combined in the multivariable model in the total patient population (adjusted HR [aHR] per 1 SD in log-transformed biomarker: NT-proBNP: aHR, 1.46; 95% CI, 1.34-1.60; hsTnT: aHR, 1.39; 95% CI, 1.26-1.53) as well as in patients with ASCVD and multiple risk factors (Figure 2; eFigure 1 in Supplement 1).

Figure 2. — Adjusted for age, sex, race, smoking, baseline estimated glomerular filtration rate, body mass index, diabetes duration, insulin use, history of coronary artery disease, myocardial infarction, ischemic stroke, peripheral artery disease, heart failure, dyslipidemia, and hypertension. HR indicates hazard ratio; hsTnT, high-sensitivity cardiac troponin T; MACE, major adverse cardiovascular events; NT-proBNP, N-terminal pro–B-type natriuretic peptide.

Treatment Effect of Dapagliflozin According to Baseline Biomarker Levels

Consistent with the results of the main trial, the HR for MACE with dapagliflozin in the present biomarker cohort was 0.92 (95% CI, 0.83-1.03). The probabilities of MACE stratified by baseline biomarker concentrations and treatment arm in ASCVD and multiple risk factors are shown in Figure 3A and B. In patients with NT-proBNP and hsTnT concentrations in quartile 4, dapagliflozin-treated patients had lower MACE rates than those taking placebo, yielding 17% (95% CI, 3-29) and 15% (95% CI, 1-28) relative reductions in the hazard of MACE, respectively. The absolute risk reductions observed in patients with NT-proBNP and hsTnT in the top quartiles were 2.4% and 2.7%, respectively, at 4 years. In contrast, there was no nominally significant association in patients with quartile 1 to quartile 3 levels of NT-proBNP (HR, 1.02; 95% CI, 0.88-1.18) or hsTnT (HR, 0.97; 95% CI, 0.84-1.13) (eFigure 2 in Supplement 1). However, formal interaction testing did not reveal significant heterogeneity of the association of dapagliflozin based on either baseline biomarker (Figure 3C and D; eFigures 2-6 in Supplement 1).

Figure 3. — A and B, Probability of the composite of myocardial infarction, ischemic stroke, or cardiovascular death by treatment arm and N-terminal pro–B-type natriuretic peptide (NT-ProBNP) and high-sensitivity cardiac troponin T (hsTnT) levels. C and D, Hazard ratio of dapagliflozin vs placebo for the composite of myocardial infarction, ischemic stroke, or cardiovascular death by treatment arm and NT-proBNP and hsTnT levels. The dashed vertical lines indicate the median and IQR of the biomarker levels, and the shaded area indicates 95% CIs. ASCVD indicates atherosclerotic cardiovascular disease; MACE, major adverse cardiovascular events.

Discussion

The main findings of the present study are that both NT-proBNP and hsTnT stratify (individually and complementarily) risk for future atherosclerotic events in both patients with and without established ASCVD. Moreover, in patients at high risk identified by biomarker concentrations in the top quartile (ie, NT-proBNP greater than 165 pg/mL and hsTnT greater than 15.5 ng/L), we observed lower rates of MACE with dapagliflozin than placebo. Our findings suggest the possibility that these cardiovascular biomarkers identify patients with T2D among whom treatment with dapagliflozin may confer a benefit with respect to MACE in addition to the established reductions in future HF and kidney events that are conferred irrespective of cardiac biomarker levels. In light of the global burden of T2D, these smaller effects on MACE may have clinical and public health implications (particularly in those with ASCVD and higher biomarker levels).

Results from the present study expand on findings from biomarker analyses of the CANVAS trial.¹⁴ That study of 3503 patients with baseline hsTnT levels measured, which had a higher proportion of patients with hsTnT concentrations of 14 ng/L or higher (38% vs 30%) and a longer follow-up (6 vs 4.2 years), indicated that patients with hsTnT concentrations of 14 ng/L or higher derived greater benefit from treatment with canagliflozin for MACE.

Limitations

These analyses are subject to the known limitations of subgroup analyses, including their exploratory nature and limited statistical power. As reflected in the distribution of the baseline concentrations with only approximately one-third of the patient population having either hsTnT concentrations of 14 ng/L or greater or NT-proBNP levels of 450 pg/mL or greater, the included patient population represents a lower-risk patient cohort compared with other SGLT2i cardiovascular outcomes trials in patients with T2D.^3,5

Conclusions

In this study, NT-proBNP and hsTnT levels had unique, independent prognostic value and were associated with the risk for future cardiovascular events in both primary and secondary prevention patients with T2D. Both cardiac biomarkers are helpful to identify patients at very high risk of atherosclerotic events who may derive clinical benefit from dapagliflozin with regard to MACE.

Supplement 1.

eTable 1. Baseline Characteristics According to NT-proBNP Quartiles

eTable 2. Baseline Characteristics According to hsTnT Quartiles

eFigure 1. Relationship Between Cardiac Biomarkers and Cardiovascular Events in Patients With Multiple Risk Factors for or Established Atherosclerotic Cardiovascular Disease Within the Placebo Arm

eFigure 2. Effect of Dapagliflozin vs Placebo on the Composite of Myocardial Infarction, Ischemic Stroke, and Cardiovascular Death by Biomarker Q1-3 vs Q4

eFigure 3. Effect of Dapagliflozin vs Placebo on Myocardial Infarction by Baseline Biomarker Quartiles

eFigure 4. Effect of Dapagliflozin vs Placebo on Ischemic Stroke by Baseline Biomarker Quartiles

eFigure 5. Effect of Dapagliflozin vs Placebo on Cardiovascular Death by Baseline Biomarker Quartiles

eFigure 6. Effect of Dapagliflozin vs Placebo on the Composite of Myocardial Infarction, Ischemic Stroke, and Cardiovascular Death by Biomarker Quartiles

Click here for additional data file.^{(2.3MB, pdf)}

Supplement 2.

Data Sharing Statement

Click here for additional data file.^{(14.7KB, pdf)}

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13.Raz I, Mosenzon O, Bonaca MP, et al. DECLARE-TIMI 58: participants’ baseline characteristics. Diabetes Obes Metab. 2018;20(5):1102-1110. doi: 10.1111/dom.13217 [DOI] [PubMed] [Google Scholar]
14.Vaduganathan M, Sattar N, Xu J, et al. Stress cardiac biomarkers, cardiovascular and renal outcomes, and response to canagliflozin. J Am Coll Cardiol. 2022;79(5):432-444. doi: 10.1016/j.jacc.2021.11.027 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

eTable 1. Baseline Characteristics According to NT-proBNP Quartiles

eTable 2. Baseline Characteristics According to hsTnT Quartiles

eFigure 2. Effect of Dapagliflozin vs Placebo on the Composite of Myocardial Infarction, Ischemic Stroke, and Cardiovascular Death by Biomarker Q1-3 vs Q4

eFigure 3. Effect of Dapagliflozin vs Placebo on Myocardial Infarction by Baseline Biomarker Quartiles

eFigure 4. Effect of Dapagliflozin vs Placebo on Ischemic Stroke by Baseline Biomarker Quartiles

eFigure 5. Effect of Dapagliflozin vs Placebo on Cardiovascular Death by Baseline Biomarker Quartiles

eFigure 6. Effect of Dapagliflozin vs Placebo on the Composite of Myocardial Infarction, Ischemic Stroke, and Cardiovascular Death by Biomarker Quartiles

Click here for additional data file.^{(2.3MB, pdf)}

Supplement 2.

Data Sharing Statement

Click here for additional data file.^{(14.7KB, pdf)}

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[hbr230001r14] 14.Vaduganathan M, Sattar N, Xu J, et al. Stress cardiac biomarkers, cardiovascular and renal outcomes, and response to canagliflozin. J Am Coll Cardiol. 2022;79(5):432-444. doi: 10.1016/j.jacc.2021.11.027 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Association of Cardiac Biomarkers With Major Adverse Cardiovascular Events in High-risk Patients With Diabetes

Thomas A Zelniker, MD, MSc

Stephen D Wiviott, MD

Ofri Mosenzon, MD, MSc

Erica L Goodrich, MS

Petr Jarolim, MD, PhD

Avivit Cahn, MD

Deepak L Bhatt, MD, MPH

Lawrence A Leiter, MD

Darren K McGuire, MD, MHSc

John Wilding, MD

Oleg Averkov, MD

Andrzej Budaj, MD

Alexander Parkhomenko, MD

Kausik K Ray, MBChB

Ingrid Gause-Nilsson, MD, PhD

Anna Maria Langkilde, MD, PhD

Martin Fredriksson, PhD

Itamar Raz, MD

Marc S Sabatine, MD, MPH

David A Morrow, MD, MPH

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Interventions

Main Outcomes and Measures

Results

Conclusions and Relevance

Trial Registration

Introduction

Methods

Study Population

Outcomes of Interest

Biomarker Levels

Statistical Analysis

Results

Study Population

Association Between Baseline Cardiac Biomarkers and MACE Within the Placebo Arm

Figure 1. Kaplan-Meier (KM) Event Rates of the Composite of Myocardial Infarction, Ischemic Stroke, or Cardiovascular Death by Baseline Biomarker Quartiles.

Figure 2. Association Between Cardiac Biomarkers and the Composite of Myocardial Infarction, Ischemic Stroke, or Cardiovascular Death in Placebo-Treated Patients With Multiple Risk Factors for or Established Atherosclerotic Cardiovascular Disease (ASCVD).

Treatment Effect of Dapagliflozin According to Baseline Biomarker Levels

Figure 3. Outcomes of Dapagliflozin vs Placebo According to Baseline Biomarker Level.

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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