Novel and Conventional Biomarkers for Prediction of Myocardial Infarction and Cardiovascular Death Público

Abstract

Background: Cardiovascular diseases (CVD) are the leading causes of morbidity and mortality in the United States. Types of CVD include coronary heart disease (CHD), stroke, hypertensive heart disease, inflammatory heart disease, rheumatic heart disease, and other cardiovascular diseases. In literature, scientists have used biomarkers to estimate risk of CVD and risk of CHD, including MI or cardiovascular death. Results from these studies are varied with regards to which biomarkers are associated with an increased risk of CHD. Studies first create a biomarker score from the best biomarkers.

Methods: This analysis is based on 202 enrolled patients who have either a clinical history of angina symptoms, a positive stress test, or have in-stent restenosis (ISR). Patients are enrolled if they have an angiographic ≥ 70 percent, coronary artery or graft stenosis that will be treated with coronary angioplasty and/or stenting procedure. Prior to the interventional procedure, baseline clinical data, including participant's cardiovascular symptom status will be recorded. At the beginning of the angioplasty procedure a blood sample was taken. Blood sampling is repeated in all participants 24 hours post-procedure, one-week post-procedure, and four-weeks post-procedure. Then, the association between the biomarkers and the risk of cardiovascular mortality and myocardial infraction using multivariable Cox Proportional-Hazards Regression models. Then, clinical and multimarker score models with "best-fit" clinical models were compared, based on models containing the clinical risk factors and use of CHD therapies.

Results: During a mean follow up of 6.3 years, 49 (24%) participants had a MI or died from cardiovascular diseases. Using backwards elimination with retention p-value=0.20, these remained in the model: triglycerides, serum creatinine, and biomarkers, SDF-1, TNF, and CRP. For the endpoint of a MI or cardiovascular death the multimarker score with biomarkers SDF-1, TNF, and CRP is: =(3.668*SDF-1)+(0.345*TNF)+(0.314*CRP).

Conclusions: Concentrations of SDF-1, TNF, and CRP help to predict the future risk of MI or CV death still in the context of robust clinical risk models. Addition of these biomarkers improves discrimination. These biomarkers can assist with prognostic value for identifying death or MI after undergoing angioplasty.

Table of Contents

Table of Contents

Page

List of Tables……………………………………………..………………………………1

List of Figures………………………………………………..…………………………..2

1. Introduction……………………………………………..….……………………....3

1.1. Clinical Risk Factors of CHD………………………..………………..….4

1.2. Inflammation and CVD……………………..……………….……………..4

1.3. Biomarkers and CVD Risk……………………..………….….………..…4

1.4. Study Purpose……….…….…………………..………………………..…....6

1.5. Treatment and Interventions……………………….………..………….7

2. Methods……………………………………….…………………………………......8

2.1. Study Sample……………………..…………...….………………………....8

2.2. Biomarker Measurements……………….....………………………....9

2.3. Outcomes……………………….………….…………………………….........9

2.4. Statistical Analyses……………………….….…………………………...…9

3. Results………………………………………………………………………..….....14

3.1. Participant Characteristics……………….…………………………....14

3.2. Baseline Biomarkers and Clinical Characteristics…………..14

3.3. Prediction of MI and death with new biomarkers…………..15

3.4. Multimarker Score……………………………………...…………….…..15

3.5. IDI and NRI…………………………………………………………….........16

4. Conclusions, Implications, and Recommendations…………….17

4.1. Summary of Findings………………………………..…………………...17

4.2. Clinical Significance………………….……………..…………………...17

4.3. Study Strengths………………….…...………..……….………………..18

4.4. Study Limitations.………………….…...………..……….…….……..18

4.5. Future Studies………………….…...…………………….………….…...18

4.6. Conclusion………………….…...…………………….…………….........19

References……………………………….….…...…………………….….……….20

Appendix……………………………….….…...…………………….…….……….22

About this Master's Thesis

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School	Rollins School of Public Health
Department	Biostatistics and Bioinformatics
Subfield / Discipline	Biostatistics - MPH & MSPH
Degree	MSPH
Submission	Master's Thesis
Language	English
Research Field	Biology, Biostatistics Health Sciences, Public Health Health Sciences, Medicine and Surgery
Palabra Clave	Biomarkers
Committee Chair / Thesis Advisor	Binongo, Jose N, Emory University
Committee Members	Cotsonis, George A, Emory University
Partnering Agencies	Does not apply (no collaborating organization)

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