Fig. 5: Machine learning model may be useful for detecting differences between treatment arms in early phase 2 clinical trial scenarios.

a, KM curve showing OS in the test dataset for the three arms in the IMpower150 trial including ABCP (brown) versus ACP (orange) versus the control arm of BCP (black, control arm). b, Bar plot showing the rate of radiographic response at the week 6 tumor assessment for each treatment arm (left panel, CR/PR by RECIST criteria), and the rate of ctDNA molecular response for each treatment arm (right panel, mResp by C3D1 OS ctDNA model). c, Bar plot showing results from simulations of early phase 2 clinical trial scenario utilizing test data, where an early endpoint based on ctDNA (mResp by C3D1 OS model) is compared to early radiographic endpoints (week 6 RECIST response, week 6 PFS). Bar height corresponds to the proportion of simulations in which the active arm had higher rates of treatment response compared to control arm (‘true go rate’) for each early endpoint (x axis), where the left panel shows simulations comparing active ABCP arm to control BCP arm (left panel, brown colors), and right panel shows simulations comparing active ACP arm to control BCP arm (right panel, orange colors). X axis corresponds to which early endpoint is used in the simulation, comparing ctDNA criteria alone (mResp by C3D1 OS model), radiographic response alone (CR/PR by RECIST), PFS alone, or ctDNA added to radiographic response or PFS response.