TABLE 3.
Logistic regression model | AUC (95% C.I., P) a | NRI (95% C.I., P) b | Cohen’s κ (95% C.I.) |
---|---|---|---|
1) Epidemiologic: age, sex, pack-years (PY) | |||
Binomial | 0.607 (0.577–0.637) | 0.172 (0.120–0.224) | |
Multinomial | 0.608 (0.577–0.638) | 0.081 (0.037–0.125) | |
2) Epidemiologic + top independently associated SNPs c | |||
Binomial | 0.617 (0.587–0.647, ref.) | (ref.) | 0.194 (0.141–0.246) |
Multinomial | 0.617 (0.587–0.647, 0.618) | 3.6% (0.9–6.4, 0.0104) | 0.095 (0.047–0.144) |
3) Epidemiologic + top independently associated SNPs c and their interactions with PY | |||
Binomial | 0.619 (0.589–0.650, 0.598) | 2.9% (0.7–5.1, 0.0097) | 0.195 (0.143–0.247) |
Multinomial | 0.620 (0.590–0.650, 0.586) | 2.2% (0.1–4.3, 0.0438) | 0.101 (0.052–0.150) |
4) Epidemiologic + PCs of top overall pathways | |||
Binomial | 0.621 (0.591–0.651, 0.568) | 5.3% (1.8–8.8, 0.0027) | 0.200 (0.146–0.253) |
Multinomial | 0.621 (0.591–0.651, 0.582) | 5.0% (1.7–8.4, 0.0033) | 0.105 (0.058–0.152) |
5) Epidemiologic + PCs of top overall pathways and their interactions with PY | |||
Binomial | 0.630 (0.600–0.660, 3.28 × 10−2) | 4.9% (2.5–7.4, 0.0002) | 0.207 (0.154–0.261) |
Multinomial | 0.631 (0.600–0.661, 2.94 × 10−2) | 5.0% (2.4–7.6, 0.0002) | 0.125 (0.077–0.173) |
6) Epidemiologic + PCs of top subtype-specific pathways and their interactions with PY | |||
Binomial | 0.651 (0.621–0.681, 8.78 × 10−4) | 8.9% (5.7–12.1, <0.0001) | 0.226 (0.171–0.281) |
Multinomial | 0.656 (0.626–0.685, 6.11 × 10−5) | 11.7% (7.3–16.0, <0.0001) | 0.152 (0.108–0.195) |
Changes in AUC were computed relative to the #2 binomial model as reference.
Net reclassification improvement values (%) were computed relative to the #2 binomial model as reference. Classification was determined based on choosing a risk prediction score cutoff for each model that corresponds to the ROC curve point with minimum Euclidean distance to coordinate (0, 1).
Three hundred and one independently associated SNPs were identified by stepwise-selection conditional analysis of the TRICL overall lung cancer GWAS meta-analysis. Logistic regression models that include the top n SNPs were tested, for 1 ≤ n ≤ 301. Optimal n yielding the highest AUC were 30 and 39 for models 2 and 3, respectively.