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.