Extended Data Table 4. Predictive model and validation.

a, ROC curve analysis for clinical response based on pre-treatment CD8+, PD-1+, PD-L1+, and CD4+ cells. The area under the ROC curve (AUC) was used to measure response prediction performance for pre-treatment CD8+, PD-1+, PD-L1+, and CD4+ cell densities (cells/mm²). P-values were computed on the basis of the Wilcoxon rank sum statistic. b, Performance of a model for clinical response using CD8+ (cells/mm²). A logistic regression model was constructed using pre-treatment CD8+ (cells/mm²) versus the outcome of clinical response (PR+SD vs PD) using the study cohort. This fixed model was then applied to the CD8+ density measurements in the validation cohort to compute predicted probabilities of response to treatment.

a
Variable	AUC (95% Cl)*	P-value**
Tumour
CD8+ Density	.91 (0.81, 1.00)	<0.001
PD-1+ Density	.80 (0.67, 0.94)	0.001
PD-L1+ Density	.71 (0.54, 0.88)	0.026
CD4+ Density	.66 (0.48, 0.84)	0.095
Invasive Margin
CD8+ Density	.94 (0.88, 1.00)	<0.001
PD-1 + Density	.80 (0.66, 0.94)	0.001
PD-L1+ Density	.79 (0.64, 0.95)	0.002
CD4+ Density	.66 (0.48, 0.84)	0.095

b
Patient ID	CD8+ Density, Before Tx (Invasive Margin)	Predicted Probability of Response (Logistic Model)	Blinded Prediction	True Clinical Response (RECIST 1.1)
IGR-A	58	0.35	Progression	Progression
IGR-B	159	0.37	Progression	Progression
IGR-C	329	0.40	Progression	Progression
IGR-D	341	0.41	Progression	Progression
IGR-E	2120	0.75	Response	Stable
IGR-F	5466	0.98	Response	Progression
IGR-G	2211	0.76	Response	Response
IGR-H	3810	0.92	Response	Response
IGR-I	4294	0.95	Response	Response
IGR-J	4948	0.97	Response	Response
IGR-K	5565	0.98	Response	Response
IGR-L	6004	0.99	Response	Response
IGR-M	5951	0.99	Response	Complete Response
IGR-N	7230	0.99	Response	Complete Response
IGR-O	6320	0.99	Response	Complete Response