Article Figures & Data
Figures
- FIGURE 1.
(A) Estimates of survival function for patients who were 18F-FDG PET–evaluable at day 14. Solid line represents Kaplan–Meier estimate, with thin dashed lines denoting 95% pointwise confidence limits. Smooth, dash-dotted line is estimated survival function based on AFT-model. (B) Estimates of survival function by PS values (0, 1, and 2). Solid lines give Kaplan–Meier estimates, and smooth lines depict corresponding estimates based on AFT model.
- FIGURE 2.
Percentage change in SUVmax between baseline and week 2 vs. survival duration (mo). Censored observations are denoted by triangles, and Xs denote actual event times. (A) Best-fitting linear AFT model. Patients with new lesions are overlaid by red circle. (B) Data subset with known mutation status. Patients with EGFR mutations are overlaid by blue box.
- FIGURE 3.
Estimated survival functions (smooth curves) for EGFR wild-type patients with PS = 0 (A) and PS = 1 (B), with and without new lesions (red and black curves, respectively). For lognormal AFT model, dotted lines show approximate 95% pointwise confidence intervals. Step functions give corresponding Kaplan–Meier estimates.
Tables
Characteristic OSI3926g (n = 65) OAM4558g (n = 60) Age (y) Mean 62.7 62.1 SD 9.2 10.6 Women 43.1% 39.7% Race or ethnic group Asian 4.6% 0% Other 95.4% 100% Smoking status Never 20.0% 19.0% Previous 12.3% 12.7% Current 67.7% 68.3% Baseline ECOG status 0 24.6% 30.2% 1 61.5% 66.7% 2 13.8% 3.2% EGFR mutation 6.2% 9.5% Viable tissue sample 69.2% 88.9% Histologic type Adenocarcinoma 69.2% 63.2% Squamous cell carcinoma 18.5% 25.5% Median time since initial diagnosis (mo) 10.3 11.8 Median survival (mo) 7.2 7.8 Except for available tumor tissue, no baseline variable is statistically significantly different between the 2 studies at 0.05 level.
- TABLE 2.
Maximum-Likelihood Parameter Estimates Along with R2 Values for Fitted AFT Models
Model E(log T) σ^ 
R2 Population 2.02 0.947 Not applicable Prognostic (PS, SUV) 2.91 − 0.47 PS* − 0.19 − SUV†base 0.855 16.4 Predictive (δSUV) 2.86 − 0.46 PS* − 0.19 SUV†base − 0.67 δSUV‡wk2 0.840 19.7 Predictive (NL) 3.02 − 0.45 PS* − 0.18 SUV†base − 0.75 NLPET¶wk2 0.792 27.0 Predictive (NL, EGFR) 2.75 − 0.40 PS‡ − 0.12 SUV‡base − 0.71 NLPET†wk2 + 0.95 EGFR† 0.800 30.6 * P < 0.0001.
† P < 0.001.
‡ P < 0.01.
¶ P < 0.05.
Prognostic model includes PS and SUVbase. Additionally, the 3 predictive models include, respectively, δSUVwk2, NLPET, and NLPET and EGFR.
