Fig. 4: In silico clinical trials can predict immunotherapy-specific survival patterns based on biological assumptions. | Nature Communications

Fig. 4: In silico clinical trials can predict immunotherapy-specific survival patterns based on biological assumptions.

From: In silico cancer immunotherapy trials uncover the consequences of therapy-specific response patterns for clinical trial design and outcome

Fig. 4

A–F Examples of 1:1 randomized trials with various (treatment) regimens (n=600 simulated patients per arm). A–C A traditional chemotherapy trial (vs. placebo) only shows a proportional hazard ratio when the biological treatment effect targets the tumor directly and remains constant over time (compare to Supplementary Fig. 2). D An in silico immunotherapy trial elicits typical immunotherapy-induced survival curve shapes (i.e., delayed curve separation) and violates the proportional hazard assumption. E, F More intricate treatment or control regimens – (D) immunotherapy+chemotherapy-placebo vs. chemotherapy + immunotherapy-placebo, or (E) induction chemotherapy followed by immunotherapy vs. immunotherapy – induce more complex survival patterns, including (E) crossing survival curves or (F) only a temporary separation of the survival curves. Horizontal bars underneath the survival curves indicate the duration of the treatment effect (T=treatment, C=control). The red dot in column three indicates the hazard ratio averaged over the entire trial. Lines and shading in middle column: estimated hazards and 95% CIs (see Methods). Source data are provided as a Source Data file.

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