Clinicians’ Perceptions towards Precision Medicine Tools for Cardiovascular Disease Risk Stratification in South Africa

Michelle Kamp, Oliver Pain, Andrew May, Cathryn M. Lewis, Michèle Ramsay*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Cardiovascular diseases (CVDs) are a leading cause of mortality and morbidity in South Africa. Risk stratification is the preferred approach to disease prevention, but identifying patients at high risk for CVD remains challenging. Assessing genetic risk could improve stratification and inform a clinically relevant precision medicine (PM) approach. Clinicians are critical to PM adoption, thus, this study explores practicing clinicians’ perceptions of PM-based CVD risk stratification in South Africa’s public health setting. Practicing clinicians (n = 109) at four teaching hospitals in Johannesburg, South Africa, completed an electronic self-administered survey. The effect of demographic and professional characteristics on PM-based CVD risk stratification perceptions was assessed. Fewer than 25% of respondents used clinical genetic testing, and 14% had formal genetics training. 78% had a low mean knowledge score, with higher scores associated with genetic training (p < 0.0005) and research involvement (p < 0.05). Despite limited knowledge and resources, 84% perceived PM approaches positively. 57% felt confident in applying the PM-based approach, with those already undertaking CVD risk stratification more confident (p < 0.001). High cost and limited access to genetics services are key barriers. Integrating genetic information into established clinical tools will likely increase confidence in using PM approaches. Addressing the genetics training gap and investment into the country’s genomics capacity is needed to advance PM in South Africa.

Original languageEnglish
Article number1360
JournalJournal of Personalized Medicine
Issue number9
Publication statusPublished - Sept 2022


  • cardiovascular disease
  • clinical implementation
  • clinical utility
  • clinician attitudes
  • polygenic risk scores
  • precision medicine


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