A new model based on 6 clinical factors may be able to predict overall survival for patients with advanced urothelial cancers being treated with the PD-L1 inhibitor atezolizumab.
Gregory Pond, PhD
A new model based on 6 clinical factors may be able to predict overall survival (OS) for patients with advanced urothelial cancers (UC) being treated with the PD-L1 inhibitor atezolizumab (Tecentriq).
Urothelial cancer is the fifth leading cancer in the United States. The American Cancer Society estimates there will be more than 81,000 new diagnoses and more than 17,000 deaths associated with the disease this year. Mortality rates have remained largely stable for the past 30 years, but the FDA has recently approved 5 new immunotherapies for patients with advanced UC receiving post-platinum chemotherapy, offering the hope of improved survival.
To date, however, there has not been a prognostic model that could identify the patients most likely to derive the most benefit from a given treatment. Gregory Pond, PhD, associate professor, McMaster University, Hamilton, Ontario, Canada, and his colleagues believe they have built a model that can identify the patients most likely to benefit from treatment with atezolizumab.
Pond discussed the findings Monday in a press conference ahead of the 2018 ASCO Genitourinary Cancers Symposium. The data are scheduled to be presented Friday, February 9, during the meeting in San Francisco.
“We’ve developed a prognostic model for overall survival which is now proposed for patients with advanced urothelial carcinoma receiving post-platinum atezolizumab,” he said. “The initial results of our study are very promising in both the training and validation datasets.”
To develop the model, Pond and colleagues analyzed data from patients (n = 310) in the pivotal, single-arm, phase II IMvigor210. That study assessed the efficacy of atezolizumab in cisplatin-ineligible patients with locally advanced or metastatic UC as a frontline therapy or following progression occurring ≥12 months after neoadjuvant or adjuvant chemotherapy.
The research team then validated the model based on data from the phase I PCD4989g trial (n = 95), and identified 6 prognostic factors:
Pond and his team determined that patient survival was associated with a patient’s total number of prognostic factors. In the Imvigor210 trial, the median OS was 19.6 months for those with 0 to 1 factors, 5.9 months for those with 2 to 3 factors, and 2.8 months for those with 4 or more factors. For patients in the PC4989g study, those numbers were 19.4, 7.2, and 2.6 months, respectively.
Other factors including stage at diagnosis, smoking, number of prior therapies, and immune cell PD-L1 status by immunohistochemistry were considered, but those were not significant following multivariate Cox regression analysis.
“The model does require further evaluation and further refinements,” Pond said. “For example, we need to look at how the model performs in datasets of larger sample size and we also want to see how it works with other checkpoint inhibitors.”
Sumanta K. Pal, MD, co-director of the City of Hope Kidney Cancer Program and moderator of the presscast, said that immunotherapy “represents a major breakthrough in bladder cancer management.” However, he said it’s important to remember that as little as one-quarter of patients experience substantial tumor shrinkage while on immunotherapy.
“Until the results of this study, there was no way to easily discern prognosis and identify who might stand to benefit most,” Pal said. “This easily-applied score developed by Dr Pond and colleagues, based on parameters readily available on the patient’s chart, provides tremendous input.
“While I would not necessarily withhold therapy on the basis of an anticipated poor prognosis, I would consider using this information in counseling patients who want to be better informed of potential outcomes with immunotherapy.”
Pond GR, Niegisch G, Rosenberg JE, et al. New 6-factor prognostic model for patients (pts) with advanced urothelial carcinoma (UC) receiving post-platinum atezolizumab. J Clin Oncol. 2018;36 (suppl 6S; abstr 413).