TABLE 3.
Performance of lung cancer prediction models
| 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) |
a
Changes in AUC were computed relative to the #2 binomial model as reference.
b
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).
c
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.