Diagnostic performance of quantitative flow ratio in prospectively enrolled patients : An individual patient‐data meta‐analysis
ABSTRACT Objectives We aimed to provide robust performance estimates for quantitative flow ratio (QFR) in assessment of intermediary coronary lesions. Background Angiography‐based functional lesion assessment by QFR may appear as a cost saving and safe approach to expand the use of physiology‐guided percutaneous coronary interventions. QFR was proven feasible and showed good diagnostic performance in mid‐sized off‐line and on‐line studies with fractional flow reserve (FFR) as reference standard. Methods We performed a collaborative individual patient‐data meta‐analysis of all available prospective studies with paired assessment of QFR and FFR using the CE‐marked QFR application. The main outcome was agreement of QFR and FFR using a two‐step analysis strategy with a multilevel mixed model accounting for study and center level variation. Results Of 16 studies identified, four studies had prospective enrollment and provided patient level data reaching a total of 819 patients and 969 vessels with paired FFR and QFR: FAVOR Pilot ( n = 73); WIFI II ( n = 170); FAVOR II China ( n = 304) and FAVOR II Europe‐Japan ( n = 272). We found an overall agreement (mean difference 0.009 ± 0.068, I2= 39.6) of QFR with FFR. The diagnostic performance was sensitivity 84% (95%CI: 77–90, I2= 70.1), specificity 88% (95%CI: 84–91, I2= 60.1); positive predictive value 80% (95%CI: 76–85, I2= 33.4), and negative predictive value 95% (95%CI: 93–96, I2= 75.9). Conclusions Diagnostic performance of QFR was good with FFR as reference in this meta‐analysis of high quality studies. QFR could provide an easy, safe, and cost‐effective solution for functional evaluation of coronary artery stenosis..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2019 |
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| Erschienen: |
2019 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:94 |
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| Enthalten in: |
Catheterization and Cardiovascular Interventions - 94(2019), 5, Seite 693-701 |
| Beteiligte Personen: |
Westra, Jelmer [VerfasserIn] |
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| BKL: |
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| Anmerkungen: |
© 2019 Wiley Periodicals, Inc. |
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| Umfang: |
9 |
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| doi: |
10.1002/ccd.28283 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
WLY003168387 |
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| 520 | |a ABSTRACT Objectives We aimed to provide robust performance estimates for quantitative flow ratio (QFR) in assessment of intermediary coronary lesions. Background Angiography‐based functional lesion assessment by QFR may appear as a cost saving and safe approach to expand the use of physiology‐guided percutaneous coronary interventions. QFR was proven feasible and showed good diagnostic performance in mid‐sized off‐line and on‐line studies with fractional flow reserve (FFR) as reference standard. Methods We performed a collaborative individual patient‐data meta‐analysis of all available prospective studies with paired assessment of QFR and FFR using the CE‐marked QFR application. The main outcome was agreement of QFR and FFR using a two‐step analysis strategy with a multilevel mixed model accounting for study and center level variation. Results Of 16 studies identified, four studies had prospective enrollment and provided patient level data reaching a total of 819 patients and 969 vessels with paired FFR and QFR: FAVOR Pilot ( n = 73); WIFI II ( n = 170); FAVOR II China ( n = 304) and FAVOR II Europe‐Japan ( n = 272). We found an overall agreement (mean difference 0.009 ± 0.068, I2= 39.6) of QFR with FFR. The diagnostic performance was sensitivity 84% (95%CI: 77–90, I2= 70.1), specificity 88% (95%CI: 84–91, I2= 60.1); positive predictive value 80% (95%CI: 76–85, I2= 33.4), and negative predictive value 95% (95%CI: 93–96, I2= 75.9). Conclusions Diagnostic performance of QFR was good with FFR as reference in this meta‐analysis of high quality studies. QFR could provide an easy, safe, and cost‐effective solution for functional evaluation of coronary artery stenosis. | ||
| 700 | 1 | |a Tu, Shengxian |4 aut | |
| 700 | 1 | |a Campo, Gianluca |4 aut | |
| 700 | 1 | |a Qiao, Shubin |4 aut | |
| 700 | 1 | |a Matsuo, Hitoshi |4 aut | |
| 700 | 1 | |a Qu, Xinkai |4 aut | |
| 700 | 1 | |a Koltowski, Lukasz |4 aut | |
| 700 | 1 | |a Chang, Yunxiao |4 aut | |
| 700 | 1 | |a Liu, Tommy |4 aut | |
| 700 | 1 | |a Yang, Junqing |4 aut | |
| 700 | 1 | |a Andersen, Birgitte Krogsgaard |4 aut | |
| 700 | 1 | |a Eftekhari, Ashkan |4 aut | |
| 700 | 1 | |a Christiansen, Evald Høj |4 aut | |
| 700 | 1 | |a Escaned, Javier |4 aut | |
| 700 | 1 | |a Wijns, William |4 aut | |
| 700 | 1 | |a Xu, Bo |4 aut | |
| 700 | 1 | |a Holm, Niels Ramsing |4 aut | |
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