Mathematical prognostic model utilizing multi-platform dynamics in patients with metastatic urothelial carcinoma receiving post-platinum immune checkpoint inhibitors

Lay summary:
Bladder cancer affects ~80,000 individuals every year in the USA. Approximately 1 in 4 patients have aggressive cancer that is not always curable. Patients with bladder cancer that has spread outside the bladder (metastatic or stage-4 bladder cancer) receiving immunotherapy have different responses and outcomes. Only 1 in 5 patients have shrinkage of the cancer, while the remaining have no change or growth of cancer on immunotherapy. Patients who receive chemotherapy typically have more brief benefits compared to immunotherapy. A large number of patients are not fit for further treatment when the cancer grows. Hence, it would be useful to be able to discriminate at an early time point between those who have growth and those who have benefit for a long time on immunotherapy. A user-friendly model that discriminates outcomes of these patients with high accuracy can be exploited to improve therapeutic strategies. For those predicted to have poor long term outcomes on immunotherapy, earlier switch to other new treatments or intensification of therapy by combinations of new agents with immunotherapy may improve outcomes. This study proposes to construct a mathematical model utilizing early changes in readily available clinical (e.g. organs of spread of cancer, fitness of patient, age, weight, gender, side effects) and laboratory variables (blood cell counts, blood albumin, cancer size measurement). We will analyze 931 patients with metastatic bladder cancer who were enrolled in the IMvigor211 trial, which was a phase 3 clinical trial comparing atezolizumab immunotherapy versus chemotherapy in those who had cancer growing after previous chemotherapy.