Early dynamics of clinical and laboratory parameters predict primary refractory disease in patients with metastatic urothelial carcinoma receiving atezolizumab.

Background: In patients with metastatic urothelial carcinoma (mUC) receiving programmed cell death ligand 1 (PD-L1) inhibitors, it is critically important to identify primary refractory patients very early to enable modification of therapy before clinical progression and decline of performance status. We hypothesized that baseline and early-on-treatment (EOT) parameters may help identify patients likely to have primary refractory disease.

Methods: We considered baseline and EOT variables measured up to 5 weeks after initiating therapy in the phase 3 clinical trial IMvigor211, which compared atezolizumab versus chemotherapy, in muC patients who had progressed on platinum-based chemotherapy. We used least absolute shrinkage and selection operator-regularized logistic regression models to predict the risk of primary refractory disease employing clinical and laboratory variables.

Results: 902 patients were evaluable for analysis. Our baseline model achieves an area under the curve (AUC) of 0.730, 0.717 for the atezolizumab group and 0.696 for the chemotherapy group. The AUC increases to 0.848 overall with EOT parameters, 0.871 for the atezolizumab group and 0.788 for the chemotherapy group. The EOT model suggests that 33.7% of patients receiving atezolizumab may benefit from switching to chemotherapy, reducing their risk of primary refractoriness from 67.1% to 51.5%.

Conclusions: Our prediction model employs readily available and routinely measured clinical and laboratory factors, such as urine-specific gravity, presence of liver metastases, and total protein and erythrocyte counts. It robustly identifies patients with early primary refractory disease to atezolizumab before clinical progression and may inform therapeutic decisions. Validation in larger independent cohorts and other treatments is required.