Dr. John O. Parker Lectureship: Using Big Data to Improve the Primary Prevention of Cardiovascular Disease (Presented By: Dr. Dennis Ko)

TMED Blog

| 22 November 2022

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By Isaac Emon, MSc Candidate and TMED 801 Student

On Thursday, November 17th, the Department of Medicine had the privilege of hearing from Dr. Dennis T Ko, MD, MSc, during the Dr. John O. Parker Distinguished Lectureship. Dr. Ko is a Full Professor in the Department of Medicine at the University of Toronto and a senior scientist and interventional cardiologist at Sunnybrook Hospital.

Dr. Ko’s presentation discussed the use of big data in improving the primary prevention of atherosclerotic cardiovascular disease (ASCVD), focusing on calibrating traditional cardiovascular risk scores. He began by discussing the heterogeneity of treatment efficacy, explaining how not all patients respond equally to treatment. While some patients may benefit greatly, others may experience a negative effect, emphasizing the importance of developing accurate risk scores to ensure the appropriate use of therapies. He also described the relationship between relative and absolute risk reduction, demonstrating that those with higher risk should receive the greatest benefit from treatment. Dr. Ko discussed the “Treatment Risk Paradox,” describing that treatment should align with the magnitude of benefit patients will receive but that treatment patterns are often the opposite in that lower-risk patients are more likely to receive treatment (1).

This is mind, we shifted to discuss the guidelines for primary prevention of ASCVD in Canada. We reviewed the steps for calculating the Framingham Risk Score (FRS) and examined deficiencies in this approach (2). In 2020, Dr. Ko and colleagues assessed the calibration and discrimination of the FRS and the Pooled Cohort Equations (PCE) in Ontario to uncover the validity of these risk scores in different subgroups (3). They found a substantial overestimation of the FRS in Ontario, with the overall predicted rate [of developing ASCVD within 5 years] being 5.8%, while the observed rate was found to be only 2.9% (3). An overestimation was also found using the PCE in Ontario (3). This overestimation of risk has substantial consequences including unnecessary expenditure of resources and harmful side effects and toxicities in patients treated inappropriately, reminding us to be mindful when creating management plans. Dr. Ko has worked to calibrate these risk scores using more up-to-date statistics regarding outcomes with smoking, diabetes, and other risk factors. He demonstrated that a recalibrated FRS was more accurate but still overestimated risk (4).

Dr. Ko also reviewed the difficulties of using these risk scores in a clinical setting. To adequately calculate a risk score, the physician needs to understand a detailed history, measure accurate vitals, obtain blood tests, then use a calculator to determine the level of risk. Though these may sound like routine practices, the COVID pandemic and the strict time schedules clinicians follow decrease the simplicity of calculating these scores. In fact, Dr. Ko mentions that only 50% of clinicians in the U.S. use these risk scores. Ultimately, Dr. Ko aims to reduce the physician’s role in obtaining data and is working to find ways to provide already-calculated risk scores to them directly. He describes that by using big data from the Ontario Laboratory Information System (OLIS), relative ASCVD rate can be compared to a variety of clinical and laboratory measures to help predict 5-year risk. This method shows promising accuracy in aligning with observed risk and having clinical utility. Future research should continue using large data sets like OLIS to further our translational research into clinical prevention for ASCVD, but it is important to realize that the use of big data extends far beyond cardiology and its application has value in improving patient care in all disciplines.

After the MGR, Dr. Ko offered his time to the TMED 801 class where students were able to ask questions about how his research directly impacts patients and how the topic of ASCVD prevention is often represented in the lay press. We further discussed the use of big data sets in research to improve primary prevention of ASCVD, considered how geographical and socio-economic barriers can impact patients at risk, and contemplated the pros and cons of social media in promoting cardiovascular health. The latter end of the discussion focused on Dr. Ko’s career path and how his medical and educational journey has unfolded thus far. He highlighted how helping patients has driven his passion for furthering the field of ASCVD prevention, emphasized the value in doing what you love, and stressed the importance of always ensuring you find time for yourself and your family.

On behalf of the Department of Medicine and the TMED 801 class, I would like to thank Dr. Ko for taking the time to teach and inspire us.

References:

Ko, Dennis T., Muhammad Mamdani, and David A. Alter. "Lipid-lowering therapy with statins in high-risk elderly patients: the treatment-risk paradox." Jama 291.15 (2004): 1864-1870.
Pearson, Glen J., et al. "2021 Canadian Cardiovascular Society Guidelines for the management of dyslipidemia for the prevention of cardiovascular disease in adults." Canadian journal of cardiology 37.8 (2021): 1129-1150.
Ko, D. T., Sivaswamy, A., Sud, M., Kotrri, G., Azizi, P., Koh, M., ... & Anderson, T. J. (2020). Calibration and discrimination of the Framingham Risk Score and the pooled cohort equations. CMAJ, 192(17), E442-E449.
Sud, Maneesh, et al. "Population-based recalibration of the Framingham risk score and pooled cohort equations." Journal of the American College of Cardiology 80.14 (2022): 1330-1342.

Dr. John O. Parker Lectureship: Using Big Data to Improve the Primary Prevention of Cardiovascular Disease (Presented By: Dr. Dennis Ko)

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Dr. John O. Parker Lectureship: Using Big Data to Improve the Primary Prevention of Cardiovascular Disease (Presented By: Dr. Dennis Ko)