Clinical prediction models of fractional flow reserve: an exploration of the current evidence and appraisal of model performance

Wenjie Zuo; Rui Zhang; Mingming Yang; Zhenjun Ji; Yanru He; Yamin Su; Yangyang Qu; Zaixiao Tao; Genshan Ma

doi:10.21037/qims-20-1274

Clinical prediction models of fractional flow reserve: an exploration of the current evidence and appraisal of model performance

Quant Imaging Med Surg. 2021 Jun;11(6):2642-2657. doi: 10.21037/qims-20-1274.

Authors

Wenjie Zuo¹, Rui Zhang¹, Mingming Yang¹, Zhenjun Ji¹, Yanru He¹, Yamin Su¹, Yangyang Qu¹, Zaixiao Tao¹, Genshan Ma¹

Affiliation

¹ Department of Cardiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China.

Abstract

Background: Invasive fractional flow reserve (FFR) is a standard indicator of coronary stenoses' hemodynamic severity. Clinical prediction models (CPMs) may help differentiate ischemic from non-ischemic lesions without using a pressure wire but by integrating related variables. This approach differs from that of physics-based models. However, it is not yet known which CPMs are the most reliable at detecting hemodynamic significance.

Methods: A systematic review was performed of relevant publications that developed or validated any FFR CPMs from inception to April 2019 in the PubMed, EMBASE, and Cochrane Library databases by two independent authors. The risk of bias and applicability were assessed using the prediction model risk of the bias assessment tool (PROBAST).

Results: A total of 11 unique CPMs and 5 subsequent external validation studies were identified. The prevalence of hemodynamically significant lesions (FFR ≤0.80) across the studies had a median of 37.1% (range: 20.7-68.0%). Lesion length, percent diameter stenosis, and minimal lumen diameter were the three most frequently used variables in the CPMs. Of the 11 FFR CPMs, 9 (82%) exhibited strong discrimination [area under the curve (AUC) >0.75], and 5 (45%) had been subject to external validation; however, calibration was only available for 3 models (27%). There was a high degree of applicability; however, none of the studies was assessed as having a low risk of bias. A CPM was identified that had undergone rigorous validation and calibration: the DILEMMA score (three validations; median AUC, 0.83).

Conclusions: Almost half of the existing FFR CPMs had been externally validated. Due to their good discrimination abilities, these FFR CPMs are useful tools that could reduce the need for invasive hemodynamic measurements. Future research that adheres to methodological guidelines should be undertaken to develop high-quality models in this setting. (PROSPERO registration number: CRD42019125011).

Keywords: Fractional flow reserve (FFR); clinical prediction models (CPMs); risk; systematic review.