Sandy T. Liu, Vadim S. Koshkin, Jayanshu Jain, Monika Joshi, Matthew D. Galsky, Noah M. Hahn, Lucia Alonso Buznego, Marcus Marie Moses, Jure Murgic, Ali Raza Khaki, Tyler F. Stewart, Aristotelis Bamias, Guru Sonpavde, Daniel Castellano, Evan Shreck, Joseph J. Park, Ajjai Alva, Mehmet Asim Bilen, Alexandra Drakaki, Yousef Zakharia, Mark P. Lythgoe, Ariel Ann Nelson, Roubini Zakopoulou, Ang Li, Ivan de Kouchkovsky, Rafael Morales-Barrera, Petros Grivas, Veena Shankaran, Christopher J. Hoimes, Vivek Kumar, Pedro Isaacsson Velho, Ignacio Duran, Abhishek Tripathi, Leonidas Nikolaos Diamantopoulos, Michael Edward Devitt, Pedro C. Barata, Ana Fröbe, Lucia Carril-Ajuria, Evan Y. Yu, Alejo Rodriguez-Vida, Victor Sacristan Santos, Neeraj Agarwal, Alexander Sankin, Benjamin A. Gartrell, Gary H. Lyman, David J. Pinato, and Natalie J. Miller
Background: While immune checkpoint inhibitors (ICIs) are approved in the first-line (1L) setting for cisplatin-unfit patients with programmed death-ligand 1 (PD-L1)-high tumors or for platinum (cisplatin/carboplatin)-unfit patients, response rates remain modest and outcomes vary with no clinically useful biomarkers (except for PD-L1). Objective: We aimed to develop a prognostic model for overall survival (OS) in patients receiving 1L ICIs for advanced urothelial cancer (aUC) in a multicenter cohort study. Design, setting, and participants: Patients treated with 1L ICIs for aUC across 24 institutions and five countries (in the USA and Europe) outside clinical trials were included in this study. Outcome measurements and statistical analysis: We used a stepwise, hypothesis-driven approach using clinician- selected covariates to develop a new risk score for patients receiving ICIs in the 1L setting. Demographics, clinicopathologic data, treatment patterns, and OS were collected uniformly. Univariate Cox regression was performed on 18 covariates hypothesized to be associated with OS based on published data. Variables were retained for multivariate analysis (MVA) if they correlated with OS (p < 0.2) and were included in the final model if p < 0.05 on MVA. Retained covariates were assigned points based on the beta coefficient to create a risk score. Stratified median OS and C- statistic were calculated. Results and limitations: Among 984 patients, 357 with a mean age of 71 yr were included in the analysis, 27% were female, 68% had pure UC, and 13% had upper tract UC. Eastern Cooperative Oncology Group performance status ≥2, albumin 5, and liver metastases were significant prognostic factors on MVA and were included in the risk score. C index for new 1L risk score was 0.68 (95% confidence interval 0.65-0.71). Limitations include retrospective nature and lack of external validation. Conclusions: We developed a new 1L ICI risk score for OS based on data from patients with aUC treated with ICIs in the USA and Europe outside of clinical trials. The score components highlight readily available factors related to tumor biology and treatment response. External validation is being pursued. Patient summary: With multiple new treatments under development and approved for advanced urothelial carcinoma, it can be difficult to identify the best treatment sequence for each patient. The risk score may help inform treatment discussions and estimate outcomes in patients treated with first-line immune checkpoint inhibitors, while it can also impact clinical trial design and endpoints. TAKE HOME MESSAGE: A new risk score was developed for advanced urothelial carcinoma treated with first- line immune checkpoint inhibitors. The score assigned Eastern Cooperative Oncology Group performance status ≥2, albumin 5, and liver metastases each one point, with a higher score being associated with worse overall survival.