Table 1.
Number of reviews | Comparison of DORs at mean thresholda |
|
---|---|---|
E-ML model vs. HSROC model |
W-ML model vs. HSROC model |
|
Median ROR [IQR] | Median ROR [IQR] | |
Overall (n = 26) | 0.94 [0.68, 1.04] | 0.59 [0.46, 0.78] |
By size of DORb | ||
DOR < 35, n = 9 | 0.99 [0.88, 1.16] | 0.78 [0.60, 0.95] |
DOR 35–100, n = 10 | 1.00 [0.83, 1.05] | 0.53 [0.42, 0.69] |
DOR > 100, n = 7 | 0.62 [0.30, 0.75] | 0.42 [0.16, 0.59] |
By % zero cellsc | ||
<5%, n = 10 | 1.01 [0.88, 1.05] | 0.79 [0.53, 0.88] |
5–10%, n = 8 | 1.02 [0.94, 1.11] | 0.63 [0.50, 0.74] |
>10%, n = 8 | 0.62 [0.30, 0.72] | 0.42 [0.16, 0.63] |
By range in ‘S’d | ||
3 to <6, n = 7 | 0.82 [0.48, 1.03] | 0.75 [0.37, 0.79] |
6 to <8, n = 14 | 0.90 [0.68, 1.00] | 0.53 [0.49, 0.75] |
≥8, n = 5 | 1.05 [0.99, 1.16] | 0.57 [0.42, 0.73] |
Abbreviations: E-ML, equal-weight Moses–Littenberg; W-ML, weighted Moses–Littenberg; HSROC, hierarchical summary receiver operating characteristic; ROR, ratio of DORs between models; median ROR, ROR at the median; IQR, interquartile range in ROR from 25th to 75th percentile; DOR, diagnostic odds ratio.
Each Moses–Littenberg model is compared to the HSROC model (denominator).
The stratification by DOR is based on the HSROC overall pooled estimate at mean threshold.
Number of zero false-positive and false-negative cells as a percentage of the total number of cells per analysis.
Based on values for ‘S’ from Moses–Littenberg model, where S = logit(sensitivity) + logit(1 − specificity).