Key result
GARFIELD-AF model outperforms CHA2DS2VASc for 1-year stroke risk discrimination but consistently underpredicts absolute risk.
Why the study?
The study aimed to validate the GARFIELD-AF tool, which simultaneously predicts mortality, stroke or systemic embolism, and major bleeding, using UK primary care electronic records.
Does the GARFIELD-AF tool improve risk prediction for mortality, stroke, and major bleeding compared to CHA2DS2-VASc and HAS-BLED in patients with non-valvular AF?
Cohort (n=486,818)
Yes
Does the GARFIELD-AF tool improve risk prediction for mortality, stroke, and major bleeding compared to CHA2DS2-VASc and HAS-BLED in patients with non-valvular AF?
Absolute Event Rate: 0.666% vs 0.625%
p-value: p=<0.0001
The GARFIELD-AF tool provides superior discrimination for death, stroke, and major bleeding compared to CHA2DS2-VASc and HAS-BLED in UK primary care, but requires recalibration due to risk underprediction.
May enhance AF stroke stratification in primary care; leaves open recalibration and prospective validation before adoption.
Background The GARFIELD-AF tool is a novel risk tool that simultaneously assesses the risk of all-cause mortality, stroke or systemic embolism, and major bleeding in patients with atrial fibrillation (AF). Aim To validate the GARFIELD-AF tool using UK primary care electronic records. Design and setting A retrospective cohort study using the Clinical Practice Research Datalink (CPRD) linked with Hospital Episode Statistics data and Office for National Statistics mortality data. Method Discrimination was evaluated using the area under the curve (AUC) and calibration was evaluated using calibration-in-the-large regression and calibration plots. Results A total of 486 818 patients aged ≥18 years with incident diagnosis of non-valvular AF between 2 January 1998 and 31 July 2020 were included; 50.6% ( n = 246 425/486 818) received anticoagulation at diagnosis The GARFIELD- AF models outperformed the CHA 2 DS 2 VASc and HAS-BLED scores in discrimination ability of death, stroke, and major bleeding at all the time points. The AUC for events at 1 year for the 2017 models were: death 0.747 (95% confidence interval [CI] = 0.744 to 0.751) versus 0.635 (95% CI = 0.631 to 0.639) for CHA 2 DS 2 VASc; stroke 0.666 (95% CI = 0.663 to 0.669) versus 0.625 (95% CI = 0.622 to 0.628) for CHA 2 DS 2 VASc; and major bleeding 0.602 (95% CI = 0.598 to 0.606) versus 0.558 (95% CI = 0.554 to 0.562) for HAS- BLED. Calibration between predicted and Kaplan– Meier observed events was inadequate with the GARFIELD-AF models. Conclusion The GARFIELD-AF models were superior to the CHA 2 DS 2 VASc score for discriminating stroke and death and superior to the HAS-BLED score for discriminating major bleeding. The models consistently underpredicted the level of risk, suggesting that a recalibration is needed to optimise its use in the UK population.
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Apenteng et al. (2023) conducted a cohort in Non-valvular atrial fibrillation (n=486,818). GARFIELD-AF risk tool vs. CHA2DS2VASc and HAS-BLED scores was evaluated on Discrimination (AUC) for stroke at 1 year (2017 model) (95% CI 0.663 to 0.669, p=<0.0001). The GARFIELD-AF 2017 model demonstrated superior discrimination for 1-year stroke risk compared to the CHA2DS2VASc score (AUC 0.666 vs 0.625), though it consistently underpredicted absolute risk.
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