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. 2025 Aug 26;9:300. doi: 10.1038/s41698-025-01095-1

Table 4.

Summary estimate of pooled performance of artificial intelligence in image-based lung cancer prognosis prediction

Subgroup No. of studies (datasets) Tau2 Sensitivity Specificity P valueb
Sensitivity P valuea I2 (95%CI) Specificity P valuea I2 (95%CI)
Overall 58 (78) 0.022 0.83 (0.81–0.86) < 0.05 64.97 (56.60–73.35) 0.83 (0.80–0.86) < 0.05 76.96 (72.04–81.87)
Cohort 0.0237
Internal validation cohort (52) 0.0139 0.85 (0.82–0.88) < 0.05 70.12 (61.72–78.51) 0.84 (0.81–0.87) < 0.05 73.18 (65.87–80.50)
External validation cohort (26) 0.0560 0.79 (0.75–0.82) < 0.05 36.62 (6.51–66.72) 0.81 (0.75–0.85) < 0.05 78.45 (70.57–86.32)
Algorithm 0.9761
Machine learning 45 (57) 0.0083 0.84 (0.81–0.86) < 0.05 60.56 (49.18–71.95) 0.82 (0.79–0.85) < 0.05 66.31 (56.98–75.65)
Deep learning 13 (21) 0.0669 0.82 (0.77–0.86) < 0.05 74.29 (63.29–85.28) 0.87 (0.80–0.92) < 0.05 88.72 (84.89–92.56)
Imaging variable only 0.0876
Yes 32 (46) 0.0229 0.84 (0.80–0.87) < 0.05 61.30 (55.90–76.70) 0.86 (0.82–0.89) < 0.05 76.86 (70.40–83.31)
No 26 (32) 0.0231 0.83 (0.79–0.86) < 0.05 61.09 (46.13–76.04) 0.79 (0.75–0.83) < 0.05 73.46 (64.23–82.69)
Nodule segmentation 0.6671
Manual 30 (35) 0.0125 0.83 (0.79–0.87) < 0.05 71.34 (61.61–81.06) 0.83 (0.78–0.86) < 0.05 71.04 (61.19–80.89)
Algorithm 28 (43) 0.0332 0.83 (0.80–0.85) < 0.05 59.36 (45.74–72.98) 0.84 (0.80–0.87) < 0.05 80.52 (75.16–85.88)
Image quality control 0.2975
Yes 13 (15) 0.0196 0.86 (0.80–0.91) < 0.05 71.47 (56.58–86.36) 0.85 (0.79–0.90) < 0.05 61.31 (39.57–83.06)
No 45 (63) 0.023 0.83 (0.80–0.85) < 0.05 62.19 (51.92–72.46) 0.83 (0.79–0.85) < 0.05 78.64 (73.67–83.61)
Imaging modality 0.7405
CT 40 (57) 0.0300 0.84 (0.81–0.86) < 0.05 63.36 (52.98–73.74) 0.83 (0.79–0.86) < 0.05 77.46 (71.87–83.06)
CECT 7 (9) 0.0000 0.83 (0.75–0.89) < 0.05 66.60 (43.05–90.15) 0.90 (0.75–0.97) < 0.05 85.03 (76.42–93.65)
PET/CT 11 (12) 0.0184 0.82 (0.75–0.88) < 0.05 75.36 (61.45–89.26) 0.83 (0.78–0.87) < 0.05 62.78 (39.56–85.99)

aP-Value for heterogeneity within each subgroup.

bP-Value for heterogeneity between subgroups with multivariable meta-regression analysis.