Profile

Hi I'm Rik (Rikuta Hamaya), MD, PhD, MS.

Instructor, Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School

Adjunct Instructor, Department of Cardiology, Tokyo University of Science

 

Thank you for viewing my profile!

 

 

Contents

Research Interests + representative work

1: Causal Inference using RCTs

One of my major research interests is about causal inference using RCTs. Often intention-to-treat effect is deemed as gold-standard evidence, which I do not necessarily agree. My work focuses on interpreting RCTs from various perspectives, including Bayesian analysis, individualized treatment rule, per-protocol effect, and combination of external data.

 

Hamaya R, Hara K, Manson J, et al. Machine-learning approaches to predict individualized treatment effect using a randomized controlled trial. European Journal of Epidemiology. 2025. In press.

Hamaya R, Cook N, Sesso H, et al. Identification of individuals who benefit from omega-3 fatty acid supplementation to prevent coronary heart disease: A machine-learning analysis of the VITAL. Under review. (Paper for Elizabeth Barrett-Connor Research Award, AHA 2024)

Hamaya R, Manson J, Wu S, et al. Re-examining the COSMOS Trial Results Using a Bayesian approach: Effects of Cocoa Extract Supplementation on Cardiovascular Events. Under review.

Hamaya R, Cook N, Sesso H, et al. A Bayesian Analysis of the VITAL Trial: Effects of Omega-3 Fatty Acid Supplementation on Cardiovascular Events. Under review.

 

2: Physical Activity

Step count is an emerging biomarker of physical activity, to which I am working on making evidence.

 

Hamaya R, Shiroma E, Moore C, et al. Time- vs Step-Based Physical Activity Metrics for Health. JAMA: Intern Med. 2024. doi:10.1001/jamainternmed.2024.0892

Hamaya R, Mori M, Miyake K, Lee IM. Association of Smartphone-Recorded Steps Over Years and Change in Cardiovascular Risk Factors Among Working-Age Adults. J Am Heart Assoc. 2022;11(14):e025689.

Hamaya R, Fukuda H, Takebayashi M, et al. Effects of an mHealth App (Kencom) With Integrated Functions for Healthy Lifestyles on Physical Activity Levels and Cardiovascular Risk Biomarkers: Observational Study of 12,602 Users. J Med Internet Res. 2021;23(4):e21622.

 

3: Hypertension prevention

Nutritional and other interventions to prevent hypertension. Greater focuses on the epidemiological methods to provide better evidence.

 

Hamaya R, Wang M, Hertzmark E, et al. Modifiable lifestyle factors in the primordial prevention of hypertension in three US cohorts. Eur J Intern Med. 2024. doi:10.1016/j.ejim.2024.10.028

Hamaya R, Sun Q, Li J et al. 24-hour urinary sodium and potassium excretions, plasma metabolomic profiles, and cardiometabolic biomarkers in US adults: A cross-sectional study. Am J Clin Nutr. 2024; DOI: 10.1016/j.ajcnut.2024.05.010.

Hamaya R, Wang M, Juraschek S, et al. Prediction of 24-hour urinary sodium excretion using machine-learning algorithms. J Am Heart Assoc. 2024; 10:e034310.

Haghayegh S, Strohmaier S, Hamaya R, et al. Sleeping Difficulties, Sleep Duration, and Risk of Hypertension in Women. Hypertension. 2023;80(11):2407-2414.

 

4: Coronary blood flow circulation 

Providing insights onto coronary physiology to guide intravascular treatment for coronary artery disease.

 

Hamaya R, Goto S, Hwang D, et al. Machine-learning-based prediction of fractional flow reserve after percutaneous coronary intervention. Atherosclerosis. 2023;383:117310.

Hamaya R, van de Hoef TP, Lee JM, et al. Differential Impact of Coronary Revascularization on Long-Term Clinical Outcome According to Coronary Flow Characteristics: Analysis of the International ILIAS Registry. Circ Cardiovasc Interv. 2022;15(6):e011948.

Hamaya R, Mittleman MA, Hoshino M, et al. Prognostic Value of Prerevascularization Fractional Flow Reserve Mediated by the Postrevascularization Level. JAMA Netw Open. 2020;3(9):e2018162.

Hamaya R, Yonetsu T, Kanaji Y, et al. Diagnostic and Prognostic Efficacy of Coronary Flow Capacity Obtained Using Pressure-Temperature Sensor-Tipped Wire-Derived Physiological Indices. JACC Cardiovasc Interv. 2018;11(8):728-737.

 

 

Education & Training

PhD in Population Health Science – Cardiovascular Epidemiology. Harvard University, 2023

MS in Biostatistics. Harvard University, 2023

MS in Epidemiology. Harvard T.H. Chan School of Public Health, 2019

MD & BSc. Tokyo Medical and Dental University, 2013

Completed internal medicine residency: Tokyo Medical and Dental University Hospital

Completed cardiology fellowship: Tsuchiura Kyodo General Hospital

 

 

Awards & Grants

Finalist, Elizabeth Barrett-Connor Research Award, American Heart Association Scientific Session, 2024

Research Award, Fuji Foundation for Protein Research, 2022

Certificate of Distinction, Harvard T.H. Chan School of Public Health, 2021

Research Fellowship, The Uehara Memorial Foundation, 2019

Research award, Tokyo Medical and Dental University, 2018 & 2019

Best Presentation Award, Functional Revascularization Encouraged by Optimal Diagnostic Strategy Live, 2018

Overseas Scholarship, The Nakajima Foundation, 2017

Best Poster Award, European Society of Cardiology Congress, 2017

Platinum Award, Beyond Angiography Japan XXI, 2016

 

 

Teaching

Clinical Data Science: Design and Analytics, Harvard Medical School: 2024-present

Introduction to Machine Learning and Risk Prediction, Harvard T.H. Chan School of Public Health: 2022-present

Research Synthesis & Meta-Analysis, Harvard T.H. Chan School of Public Health: 2020-2024

Cardiovascular Epidemiology, Tokyo University of Science: 2020-present

 

 

Publications

Please see here in Pubmed

 

 

This website

The other contents in this website are written in Japanese - about causal inference methods, nutrition evidence, etc.

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