A New Prognostic Model in Patients with Advanced Urothelial Carcinoma Treated with First-line Immune Checkpoint Inhibitors

Ali Raza Khaki, Ang Li, Leonidas N. Diamantopoulos, Natalie J. Miller, Lucia Carril-Ajuria, Daniel Castellano, Ivan De Kouchkovsky, Vadim Koshkin, Joseph Park, Ajjai Alva, Mehmet A. Bilen, Tyler Stewart, Victor Santos, Neeraj Agarwal, Jayanshu Jain, Yousef Zakharia, Rafael Morales-Barrera, Michael Devitt, Ariel Nelson, Christopher J. HoimesEvan Shreck, Benjamin A. Gartrell, Alex Sankin, Abhishek Tripathi, Roubini Zakopoulou, Aristotelis Bamias, Alejo Rodriguez-Vida, Alexandra Drakaki, Sandy Liu, Vivek Kumar, Mark P. Lythgoe, David J. Pinato, Jure Murgic, Ana Fröbe, Monika Joshi, Pedro Isaacsson Velho, Noah Hahn, Lucia Alonso Buznego, Ignacio Duran, Marcus Moses, Pedro Barata, Matthew D. Galsky, Guru Sonpavde, Evan Y. Yu, Veena Shankaran, Gary H. Lyman, Petros Grivas

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

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 <3.5 g/dl, neutrophil:lymphocyte ratio >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 <3.5 g/dl, neutrophil:lymphocyte ratio >5, and liver metastases each one point, with a higher score being associated with worse overall survival.

Original languageEnglish (US)
Pages (from-to)464-472
Number of pages9
JournalEuropean Urology Oncology
Volume4
Issue number3
DOIs
StatePublished - Jun 1 2021

All Science Journal Classification (ASJC) codes

  • Medicine(all)

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