Table 1.

Multivariate regression models to predict clinical benefit and survival following immune checkpoint blockade therapy. Multivariate logistic and Cox proportional hazards regression models for the anti-PD-L1, anti-PD-1, and anti-CTLA-4 datasets. Logistic regression in the anti-PD-L1 and anti-PD-1 datasets classified patients experiencing clinical benefit or no clinical benefit. Logistic regression in anti-CTLA-4 dataset classified patients with no clinical benefit from those with either clinical benefit within 6 months or long-term survival with no clinical benefit. Sample sizes for the anti-PD-L1, anti-PD-1, and anti-CTLA-4 datasets vary between the logistic regression (n = 21, 28, and 40, respectively) and Cox proportional hazards models (n = 25, 28, and 40, respectively) depending on available variables, with some samples having survival data with no response data.

	Logistic regression		Cox proportional hazards regression
Covariate	Estimate (SE)	P-value	Hazard ratio (95% CI)	P-value
anti-PD-L1
Intercept	−3.89 (2.98)	0.19
MBL score	1.12 (0.55)	0.04	0.79 (0.66–0.94)	0.01
TMB	0.00 (0.00)	0.94	1.00 (1.00–1.00)	0.85
CTLA-4	−5.72 (3.29)	0.08	2.10 (0.41–10.79)	0.38
PD-1	1.95 (1.76)	0.27	0.72 (0.27–1.91)	0.51
PD-L1	4.45 (3.10)	0.15	0.35 (0.05–2.30)	0.28
anti-PD-1
Intercept	0.53 (1.49)	0.72
MBL score	0.26 (0.12)	0.03	0.91 (0.81 – 1.03)	0.14
TMB	0.00 (0.00)	0.41	1.00 (1.00 – 1.00)	0.14
CTLA-4	−0.79 (1.20)	0.51	0.55 (0.10 – 2.94)	0.48
PD-1	−0.99 (1.51)	0.51	1.66 (0.21 – 13.29)	0.63
PD-L1	−0.13 (1.70)	0.94	1.56 (0.08 – 30.92)	0.77
anti-CTLA-4
Intercept	−0.84 (1.28)	0.51
MBL score	0.33 (0.14)	0.02	0.82 (0.70 – 0.96)	0.01
TMB	0.00 (0.00)	0.08	1.00 (1.00 – 1.00)	0.73
SCNA level	−0.46 (0.65)	0.48	1.30 (0.68 – 2.48)	0.43
CTLA-4	1.77 (1.10)	0.11	0.27 (0.07 – 1.03)	0.06
PD-1	−1.54 (1.44)	0.28	1.56 (0.40 – 6.04)	0.52
PD-L1	−0.55 (1.70)	0.75	0.92 (0.15 – 5.58)	0.93