Development and Use of Prediction Models for Classification of Cardiovascular Risk of Remote Indigenous Australians

Abstract

Background Cardiovascular disease (CVD) is the leading cause of death for Indigenous Australians. There is widespread belief that current tools have deficiencies for assessing CVD risk in this high-risk population. We sought to develop a 5-year CVD risk score using a wide range of known risk factors to further improve CVD risk prediction in this population. Methods We used clinical and demographic information on Indigenous people aged between 30 and 74 years without a history of CVD events who participated in the Well Person's Health Check (WPHC), a community-based survey. Baseline assessments were conducted between 1998 and 2000, and data were linked to administrative hospitalisation and death records for identification of CVD events. We used Cox proportional hazard models to estimate the 5-year CVD risk, and the Harrell's c-statistic and the modified Hosmer-Lemeshow (mH-L) x 2 statistic to assess the model discrimination and calibration, respectively. Results The study sample consisted of 1,583 individuals (48.1% male; mean age 45.0 year). The risk score consisted of sex, age, systolic blood pressure, diabetes mellitus, waist circumference, triglycerides, and albumin creatinine ratio. The bias-corrected c-statistic was 0.72 and the bias-corrected mH-L x2 statistic was 12.01 (p-value, 0.212), indicating good discrimination and calibration, respectively. Using our risk score, the CVD risk of the Indigenous Australians could be stratified to a greater degree compared to a recalibrated Framingham risk score. Conclusions A seven-factor risk score could satisfactorily stratify 5-year risk of CVD in an Indigenous Australian cohort. These findings inform future research targeting CVD risk in Indigenous Australians.

Performance of cardiovascular risk prediction equations in Indigenous Australians

“…Thus, current CVD risk guidelines for Indigenous Australians attempt to capture the CVD risk associated with CKD by automatically classifying individuals with diabetes and microalbuminuria or those with at least moderate to severe CKD as high risk for CVD. Albuminuria is included in a coronary heart disease risk prediction score for Native Americans, who have similar risk profiles with regards to diabetes and CKD as Indigenous Australians,20 and findings from one cohort of CRISP has shown that a CVD risk score that includes albuminuria demonstrated better performance than a FHS risk equation 21. We found that when risk equations and clinical criteria were used as outlined in current clinical guidelines to define high-risk groups, a greater proportion of individuals who had CVD events were captured by the CVD risk algorithm, but this improvement was somewhat off-set by reduced specificity.…”

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“…Likewise, and after discussions with ACC, we are currently developing a potential intervention intended to help identify injured people who may benefit from additional/earlier ACC support. Interventions and risk models developed in Europe, or with non-Indigenous populations, have been found to be less effective for other groups, sometimes exacerbating inequities (Wang and Hoy, 2005 ; Kirmayer and Brass, 2016 ; Tran-Duy et al, 2020 ). Therefore, we are developing a tool to support interventions from a Māori perspective and with a principled approach that what is good, or works well, for Māori, should work well for others.…”

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“…Tran-Duy et al. received a High Impact Award for most downloads—they developed a seven-factor risk score that could stratify 5-year risk of cardiovascular disease in an Indigenous Australian cohort to a greater degree compared to a recalibrated Framingham risk score [ 28 ].…”