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. 2018 Feb;49(2):363-369.
doi: 10.1161/STROKEAHA.117.018928. Epub 2018 Jan 8.

Revised Framingham Stroke Risk Score, Nontraditional Risk Markers, and Incident Stroke in a Multiethnic Cohort

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Revised Framingham Stroke Risk Score, Nontraditional Risk Markers, and Incident Stroke in a Multiethnic Cohort

Peter Flueckiger et al. Stroke. 2018 Feb.

Abstract

Background and purpose: Limited data exist on the performance of the revised Framingham Stroke Risk Score (R-FSRS) and the R-FSRS in conjunction with nontraditional risk markers. We compared the R-FSRS, original FSRS, and the Pooled Cohort Equation for stroke prediction and assessed the improvement in discrimination by nontraditional risk markers.

Methods: Six thousand seven hundred twelve of 6814 participants of the MESA (Multi-Ethnic Study of Atherosclerosis) were included. Cox proportional hazard, area under the curve, net reclassification improvement, and integrated discrimination increment analysis were used to assess and compare each stroke prediction risk score. Stroke was defined as fatal/nonfatal strokes (hemorrhagic or ischemic).

Results: After mean follow-up of 10.7 years, 231 of 6712 (3.4%) strokes were adjudicated (2.7% ischemic strokes). Mean stroke risks using the R-FSRS, original FSRS, and Pooled Cohort Equation were 4.7%, 5.9%, and 13.5%. The R-FSRS had the best calibration (Hosmer-Lemeshow goodness-of-fit, χ2=6.55; P=0.59). All risk scores were predictive of incident stroke. C statistics of R-FSRS (0.716) was similar to Pooled Cohort Equation (0.716), but significantly higher than the original FSRS (0.653; P=0.01 for comparison with R-FSRS). Adding nontraditional risk markers individually to the R-FSRS did not improve discrimination of the R-FSRS in the area under the curve analysis, but did improve category-less net reclassification improvement and integrated discrimination increment for incident stroke. The addition of coronary artery calcium to R-FSRS produced the highest category-less net reclassification improvement (0.36) and integrated discrimination increment (0.0027). Similar results were obtained when ischemic strokes were used as the outcome.

Conclusions: The R-FSRS downgraded stroke risk but had better calibration and discriminative ability for incident stroke compared with the original FSRS. Nontraditional risk markers modestly improved the discriminative ability of the R-FSRS, with coronary artery calcium performing the best.

Keywords: atherosclerosis; epidemiology; risk factors; stroke.

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Figures

Figure 1
Figure 1
Comparing the mean calculated risk using the original Framingham Stroke Risk Scores (FSRS), Revised FSRS, and Pooled Cohort Equation (PCE) with observed stroke rate in the Multi Ethnic Study of Atherosclerosis (MESA).
Figure 2
Figure 2
Receiver operator curves (ROC) assessing the discrimination for incident stroke of the Original FSRS (O-FSRS), Revised FSRS (R-FSRS), and Pooled Cohort Equation (PCE)
Figure 3
Figure 3
Receiver operator curves (ROC) assessing the improvement in discrimination afforded by the addition of coronary artery calcium (CAC), carotid intima media thickness (CIMT), high sensitivity C-reactive protein (CRP), ankle brachial index (ABI) and family history of stroke (FHS) to the (a) Original Framingham Stroke Risk Score (O-FSRS) and (b) Revised FSRS (R-FSRS) for incident stroke events in MESA. * indicates reference
Figure 4
Figure 4
Reclassification plot of the predicted probabilities of the Original and Revised Framingham Stroke Risk Score for incident stroke events in MESA. (Both axes truncated at 0.2 to eliminate outliers)

References

    1. Benjamin EJ, Blaha MJ, Chiuve SE, Cushman M, Das SR, Deo R, et al. American Heart Association Statistics C and Stroke Statistics S. Heart Disease and Stroke Statistics-2017 Update: A Report From the American Heart Association. Circulation. 2017;135:e146–e603. - PMC - PubMed
    1. Parmar P, Krishnamurthi R, Ikram MA, Hofman A, Mirza SS, Varakin Y, et al. and Stroke Riskometer TMCWG. The Stroke Riskometer(TM) App: validation of a data collection tool and stroke risk predictor. Int J Stroke. 2015;10:231–44. - PMC - PubMed
    1. Wolf PA, D'Agostino RB, Belanger AJ, Kannel WB. Probability of stroke: a risk profile from the Framingham Study. Stroke; a journal of cerebral circulation. 1991;22:312–8. - PubMed
    1. Manolio TA, Kronmal RA, Burke GL, O'Leary DH, Price TR. Short-term predictors of incident stroke in older adults. The Cardiovascular Health Study. Stroke; a journal of cerebral circulation. 1996;27:1479–86. - PubMed
    1. Chambless LE, Heiss G, Shahar E, Earp MJ, Toole J. Prediction of ischemic stroke risk in the Atherosclerosis Risk in Communities Study. American journal of epidemiology. 2004;160:259–69. - PubMed

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