Table 3.
The diagnostic performance in each independent cohort and in meta-analysis.
| Pittsburgh (n = 59) |
Incheon (n = 82) |
Yokohama (n = 142) |
Rochester (n = 58) |
Seville (n = 61) |
Los Angeles (n = 101) |
San Diego (n = 233) |
Uppsala (n = 62) |
Meta-analysis (95% CI) |
I2 | |
|---|---|---|---|---|---|---|---|---|---|---|
| ≥F1 | ||||||||||
| Prevalence | 98.0% | 70.7% | 90.1% | 50% | 78.7% | 81.2% | 57.0% | 93.5% | 74.6% | |
| Cut-off, kPa | ND | 2.50 (2.20–2.80) | 2.40 (2.20–3.60) | 2.98 (2.5–3.17) | 2.72 (2.66–3.63) | 2.74 (2.7–3.23) | 2.66 (2.28–3.22) | 2.47 (2.25–2.82) | 2.65 (2.52–2.78) | 17.05% |
| AUROC | ND | 0.65 (0.53–0.77) | 0.85 (0.78–0.91) | 0.88 (0.79–0.96) | 0.87 (0.76–0.97) | 0.84 (0.75–0.91) | 0.81 (0.75–0.86) | 0.58 (0.34–0.81) | 0.82 (0.79–0.85) | |
| Sensitivity | ND | 47% (33–60%) | 77% (68–84%) | 83% (64–94%) | 85% (72–94%) | 71% (60–80%) | 61% (52–70%) | 57% (43–70%) | 69% (59–78%) | 81.84% |
| Specificity | ND | 88% (68–97%) | 86% (64–100%) | 77% (58–90%) | 85% (55–98%) | 95% (74–100%) | 80% (69–86%) | 75% (19–99%) | 82% (76–87%) | 0.00% |
| PLR | ND | 3.72 (1.2–11.1) | 5.46 (1.51–19.75) | 4.00 (1.9–8.3) | 5.55 (1.5–20.0) | 13.44 (2.0–91.0) | 3.86 (2.4–6.2) | 2.28 (0.4–12.6) | 3.8 (2.70–5.30) | |
| NLR | ND | 0.61 (0.5–0.8) | 0.26 (0.17–0.38) | 0.22 (0.10–0.5) | 0.17 (0.08–0.4) | 0.31 (0.2–0.4) | 0.46 (04–0.6) | 0.57 (0.3–1.1) | 0.38 (0.27–0.52) | |
| DOR | ND | 6.1 (1.6–22.7) | 21.49 (4.5–101.4) | 18.4 (4.9–68.7) | 32.2 (5.8–177.5) | 43.5 (5.5–344.4) | 7.6 (4.1–14.2) | 4.0 (0.4–40.4) | 10.0 (6.0–18.0) | |
| ≥F2 | ||||||||||
| Prevalence | 71.2% | 15.9% | 54.2% | 24.1% | 50.8% | 42.6% | 27.7% | 43.5% | 39.4% | |
| Cut-off, kPa | 3.03 (2.35–3.4) | 2.80 (2.3–4.0) | 3.20 (2.80–3.60) | 3.17 (2.90–3.95) | 3.47 (2.72–3.72) | 2.86 (2.5–3.25) | 3.34 (3.31–3.73) | 2.82 (2.40–2.99) | 3.14 (3.01–3.24) | 44.88% |
| AUROC | 0.85 (0.74–0.95) | 0.74 (0.57–0.91) | 0.92 (0.86–0.96) | 0.94 (0.84–0.98) | 0.88 (0.79–0.97) | 0.91 (0.83–0.96) | 0.93 (0.89–0.97) | 0.74 (0.61–0.87) | 0.92 (0.90–0.94) | |
| Sensitivity | 69% (55–81%) | 54% (25–81%) | 86% (78–94%) | 100% (77–100%) | 81% (63–93%) | 93% (81–98%) | 76% (63–85%) | 52% (32–71%) | 79% (67–88%) | 75.00% |
| Specificity | 88% (64–98%) | 91% (82–97%) | 87% (78–95%) | 73% (57–85%) | 83% (65–94%) | 79% (67–89%) | 95% (91–98%) | 91% (77–98%) | 89% (82–94%) | 67.64% |
| PLR | 4.94 (1.54–15.88) | 6.20 (2.5–15.5) | 6.72 (3.57–12.64) | 3.67 (2.3–5.9) | 4.84 (2.1–11.0) | 4.50 (2.7–7.5) | 26.15 (10.9–62.7) | 6.05 (1.9–18.9) | 7.30 (4.90–10.80) | |
| NLR | 0.37 (0.23–0.59) | 0.51 (0.3–0.9) | 0.14 (0.077–0.256) | 0.05 (0.00–0.71) | 0.23 (0.1–0.5) | 0.09 (0.03–0.3) | 0.24 (0.2–0.4) | 0.53 (0.4–0.8) | 0.22 (0.13–0.36) | |
| DOR | 16.7 (3.3–84.0) | 12.3 (3.1–48.4) | 53.8 (19.5–148.6) | 75.4 (4.2–136.7) | 20.8 (5.6–77.2) | 51.1 (13.5–194.1) | 110.0 (38.1–317.6) | 11.5 (2.8–46.8) | 33.0 (20.0–56.0) | |
| ≥F3 | ||||||||||
| Prevalence | 39.0% | 8.5% | 31.7% | 20.9% | 39.3% | 35.6% | 16.2% | 11.3% | 24.1% | |
| Cut-off, kPa | 3.40 (3.25–3.8) | 3.10 (2.3–4.0) | 4.10 (3.20–4.50) | 3.95 (3.19–5.81) | 3.72 (3.62–4.08) | 3.06 (2.7–4.19) | 3.60 (3.22–3.86) | 3.31 (3.24–3.80) | 3.53 (3.40–3.66) | 41.15% |
| AUROC | 0.95 (0.89–0.99) | 0.88 (0.74–0.99) | 0.905 (0.84–0.95) | 0.92 (0.85–0.99) | 0.88 (0.78–0.97) | 0.90 (0.84–0.97) | 0.95 (0.92–0.98) | 0.99 (0.94–0.99) | 0.92 (0.90–0.94) | |
| Sensitivity | 87% (67–95%) | 71% (29–96%) | 91% (82–98%) | 82% (48–98%) | 75% (53–90%) | 92% (78–98%) | 87% (72–96%) | 100% (47–100%) | 87% (80–92%) | 24.42% |
| Specificity | 94% (81–99%) | 96% (89–99%) | 78% (70–86%) | 89% (77–96%) | 86% (71–95%) | 77% (65–86%) | 94% (90–97%) | 94% (85–99%) | 88% (81–94%) | 82.98% |
| PLR | 31.3 (4.5–217.6) | 17.86 (5.4–59.5) | 3.74 (2.43–5.76) | 3.54 (2.2–5.6) | 9.25 (3.1–28.0) | 3.97 (2.5–6.3) | 14.26 (8.1–25.0) | 23.6 (5.8–95.0) | 7.8 (4.7–13.0) | |
| NLR | 0.13 (0.05–0.40) | 0.30 (0.09–1.0) | 0.12 (0.04–0.33) | 0.05 (0.004–0.82) | 0.27 (0.1–0.5) | 0.11 (0.04–0.33) | 0.14 (0.06–0.3) | 0.15 (0.02–0.9) | 0.14 (0.09–0.22) | |
| DOR | 233.3 (22.7–2,395.6) | 60.0 (8.1–445.9) | 37.1 (11.9–115.4) | 62.0 (3.4–1123.5) | 34.0 (7.6–152.2) | 36.7 (9.8–136.6) | 10.9 (4.1–28.7) | 315.0 (13.8–7,214.5) | 55.0 (31.0–98.0) | |
| F4 | ||||||||||
| Prevalence | 15.3% | 1.2% | 7.7% | 12.1% | 11.5% | 17.8% | 6.4% | 4.8% | 8.7% | |
| Cut-off, kPa | 3.46 (3.13–4.45) | ND | 6.40 (5.40–7.20) | 4.73 (3.33–5.81) | 3.82 (3.72–5.00) | 4.39 (3.98–5.51) | 4.14 (3.22–4.58) | ND | 4.45 (3.67–5.22) | 85.24% |
| AUROC | 0.95 (0.85–0.99) | ND | 0.95 (0.92–0.98) | 0.94 (0.86–1.00) | 0.90 (0.81–0.99) | 0.87 (0.80–0.95) | 0.95 (0.92–0.98) | ND | 0.94 (0.92–0.96) | |
| Sensitivity | 100% (66–100%) | ND | 82% (48–98%) | 86% (42–100%) | 100% (59–100%) | 72% (47–90%) | 87% (60–98%) | ND | 88% (71–96%) | 5.82% |
| Specificity | 76% (62–87%) | ND | 95% (89–97%) | 90% (79–97%) | 78% (64–88%) | 89% (80–95%) | 93% (89–96%) | ND | 89% (82–93%) | 77.68% |
| PLR | 4.05 (2.39–6.84) | ND | 16.50 (7.1–32.6) | 8.74 (3.6–21.2) | 4.08 (2.3–7.2) | 6.66 (3.4–13.1) | 12.83 (7.9–21.0) | ND | 7.8 (5.1–11.9) | |
| NLR | 0.07 (0.004–0.98) | ND | 0.10 (0.03–0.59) | 0.16 (0.03–1.00) | 0.16 (0.03–1.0) | 0.31 (0.1–0.7) | 0.07 (0.01–0.5) | ND | 0.13 (0.05–0.36) | |
| DOR | 65.3 (3.5–1,208.4) | ND | 165.1 (17.6–1,344.2) | 55.2 (5.5–555.8) | 51.0 (2.7–956.4) | 21.4 (6.2–74.0) | 189.5 (23.3–118.2) | ND | 59.0 (21.0–169.0) | |
The bootstrap method and maximum Youden index were applied to estimate the optimal cut-off and 95% CI. In each cohort, ROC analysis was used to estimate AUROC, sensitivity, specificity, PLR, NLR, and DOR. The bivariate random-effects model was used for the computation. Heterogeneity was assessed using the Higgins inconsistency index test.
AUROC, area under the ROC curve; DOR, diagnostic odds ratio; ND, not determined (the calculation was not possible owing to the low prevalence); NLR, negative likelihood ratio; PLR, positive likelihood ratio; ROC, receiver operating curve.