Literature DB >> 27681000

Prognostic Implications of Biomarker Assessments in Patients With Type 2 Diabetes at High Cardiovascular Risk: A Secondary Analysis of a Randomized Clinical Trial.

Benjamin M Scirica1, Deepak L Bhatt1, Eugene Braunwald1, Itamar Raz2, Matthew A Cavender1, KyungAh Im1, Ofri Mosenzon2, Jacob A Udell3, Boaz Hirshberg4, Pia S Pollack4, Ph Gabriel Steg5, Petr Jarolim6, David A Morrow1.   

Abstract

IMPORTANCE: Cardiac biomarkers provide insights into pathophysiologic processes and offer an attractive strategy for the assessment of cardiovascular risk.
OBJECTIVE: To assess the incremental prognostic value of biomarkers that reflect different pathophysiologic processes in patients with type 2 diabetes. DESIGN, SETTING, AND PARTICIPANTS: The Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus (SAVOR)-Thrombolysis in Myocardial Infarction (TIMI) 53 is a randomized, double-blind, placebo-controlled clinical trial that evaluated the safety of saxagliptin vs placebo in 16 492 outpatients with type 2 diabetes with overt cardiovascular disease (CVD) or multiple risk factors. In this secondary analysis, widely used biomarkers were evaluated to ascertain whether they would provide incremental prognostic value in the risk stratification. Median follow-up was 2.1 years (interquartile range, 1.8-2.3 years). The study was performed from May 10, 2010, to June 15, 2013.
INTERVENTIONS: Randomization to saxagliptin vs placebo in addition to standard care. MAIN OUTCOMES AND MEASURES: Concentrations of high-sensitivity troponin T, N-terminal pro-B-type natriuretic peptide, and high-sensitivity C-reactive protein were analyzed continuously and by established cut points. Cardiovascular death, myocardial infarction, ischemic stroke, and hospitalization for heart failure (HF) were adjudicated by a blinded events committee.
RESULTS: Of the 16 492 patients, 5455 (33.1%) were female and 11 037 (66.9%) were male. Mean (SD) age was 65.0 (8.5) years (range, 39-99 years). Baseline biomarkers were measured in 12 310 patients. Elevated levels of each biomarker were associated significantly with increased risk for all cardiovascular end points. When added to clinical variables, biomarkers significantly improved the discrimination and appropriate reclassification of risk. Elevated high-sensitivity troponin T was associated with an increased risk of cardiovascular death (adjusted hazard ratio [AHR], 3.07; 95% CI, 2.35-4.02; P < .001), myocardial infarction (AHR, 2.13; 95% CI, 1.69-2.67; P < .001), and hospitalization for HF (AHR, 3.85; 95% CI, 2.82-5.27; P < .001). Elevated N-terminal pro-B-type natriuretic peptide was also associated with an increased risk of cardiovascular death (AHR, 3.09; 95% CI, 2.46-3.89; P < .001), myocardial infarction (AHR, 1.95; 95% CI, 1.51-2.53; P < .001), and hospitalization for HF (AHR, 3.92; 95% CI, 3.11-4.92; P < .001). Elevated high-sensitivity C-reactive protein was more weakly associated with an increased risk of cardiovascular death (AHR, 1.49; 95% CI, 1.22-1.82; P < .001) and hospitalization for HF (AHR, 1.47; 95% CI, 1.20-1.81; P < .001). Consistent results were seen in patients with or without established CVD. CONCLUSIONS AND RELEVANCE: A substantial proportion of patients with stable type 2 diabetes with established CVD or multiple clinical risk factors have evidence of ongoing myocardial injury, hemodynamic stress, or systemic inflammation. Biomarker risk stratification thus challenges the traditional differentiation between primary and secondary prevention based simply on clinical history. Strategies to improve risk stratification in patients with type 2 diabetes, with or without CVD, should consider incorporation of biomarker data into standard risk algorithms. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01107886.

Entities:  

Year:  2016        PMID: 27681000     DOI: 10.1001/jamacardio.2016.3030

Source DB:  PubMed          Journal:  JAMA Cardiol            Impact factor:   14.676


  26 in total

Review 1.  Biomarkers of cardiovascular disease: contributions to risk prediction in individuals with diabetes.

Authors:  Katherine N Bachmann; Thomas J Wang
Journal:  Diabetologia       Date:  2017-09-28       Impact factor: 10.122

2.  Machine Learning Methods to Predict Diabetes Complications.

Authors:  Arianna Dagliati; Simone Marini; Lucia Sacchi; Giulia Cogni; Marsida Teliti; Valentina Tibollo; Pasquale De Cata; Luca Chiovato; Riccardo Bellazzi
Journal:  J Diabetes Sci Technol       Date:  2017-05-12

3.  High-Sensitivity Cardiac Troponin-T and N-Terminal Prohormone of B-Type Natriuretic Peptide in Relation to Cardiovascular Outcomes in Type 1 Diabetes.

Authors:  Tina Costacou; Amy K Saenger; Trevor J Orchard
Journal:  Diabetes Care       Date:  2020-07-02       Impact factor: 19.112

Review 4.  Interpreting Absolute and Relative Risk Reduction in the Context of Recent Cardiovascular Outcome Trials in Patients with Type 2 Diabetes.

Authors:  David D Berg; Ahmed A Kolkailah; Ashish Sarraju; Anne Marie Kerchberger; Mahmoud Eljalby; Darren K McGuire
Journal:  Curr Diab Rep       Date:  2021-11-06       Impact factor: 4.810

5.  Cardiovascular Outcomes According to Urinary Albumin and Kidney Disease in Patients With Type 2 Diabetes at High Cardiovascular Risk: Observations From the SAVOR-TIMI 53 Trial.

Authors:  Benjamin M Scirica; Ofri Mosenzon; Deepak L Bhatt; Jacob A Udell; Ph Gabriel Steg; Darren K McGuire; KyungAh Im; Estella Kanevsky; Christina Stahre; Mikaela Sjöstrand; Itamar Raz; Eugene Braunwald
Journal:  JAMA Cardiol       Date:  2018-02-01       Impact factor: 14.676

6.  Blood pressure and cardiovascular outcomes in patients with diabetes and high cardiovascular risk.

Authors:  Brian A Bergmark; Benjamin M Scirica; Ph Gabriel Steg; Christina L Fanola; Yared Gurmu; Ofri Mosenzon; Avivit Cahn; Itamar Raz; Deepak L Bhatt
Journal:  Eur Heart J       Date:  2018-06-21       Impact factor: 29.983

7.  Cardiac Biomarkers in Youth with Type 2 Diabetes Mellitus: Results from the TODAY Study.

Authors:  Samuel S Gidding; Fida Bacha; Petter Bjornstad; Lorraine E Levitt Katz; Lynne L Levitsky; Jane Lynch; Jeanie B Tryggestad; Ruth S Weinstock; Laure El Ghormli; Joao A C Lima
Journal:  J Pediatr       Date:  2018-01       Impact factor: 4.406

8.  Causes of Troponin Elevation and Associated Mortality in Young Patients.

Authors:  Candace Wu; Avinainder Singh; Bradley Collins; Amber Fatima; Arman Qamar; Ankur Gupta; Jon Hainer; Josh Klein; Petr Jarolim; Marcelo Di Carli; Khurram Nasir; Deepak L Bhatt; Ron Blankstein
Journal:  Am J Med       Date:  2018-01-10       Impact factor: 4.965

9.  Machine Learning to Predict the Risk of Incident Heart Failure Hospitalization Among Patients With Diabetes: The WATCH-DM Risk Score.

Authors:  Matthew W Segar; Muthiah Vaduganathan; Kershaw V Patel; Darren K McGuire; Javed Butler; Gregg C Fonarow; Mujeeb Basit; Vaishnavi Kannan; Justin L Grodin; Brendan Everett; Duwayne Willett; Jarett Berry; Ambarish Pandey
Journal:  Diabetes Care       Date:  2019-09-13       Impact factor: 19.112

10.  Novel Urinary Glycan Biomarkers Predict Cardiovascular Events in Patients With Type 2 Diabetes: A Multicenter Prospective Study With 5-Year Follow Up (U-CARE Study 2).

Authors:  Koki Mise; Mariko Imamura; Satoshi Yamaguchi; Mayu Watanabe; Chigusa Higuchi; Akihiro Katayama; Satoshi Miyamoto; Haruhito A Uchida; Atsuko Nakatsuka; Jun Eguchi; Kazuyuki Hida; Tatsuaki Nakato; Atsuhito Tone; Sanae Teshigawara; Takashi Matsuoka; Shinji Kamei; Kazutoshi Murakami; Ikki Shimizu; Katsuhiro Miyashita; Shinichiro Ando; Tomokazu Nunoue; Michihiro Yoshida; Masao Yamada; Kenichi Shikata; Jun Wada
Journal:  Front Cardiovasc Med       Date:  2021-05-24
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