Population Modeling of Tumor Kinetics and Overall Survival to Identify Prognostic and Predictive Biomarkers of Efficacy for Durvalumab in Patients With Urothelial Carcinoma
| Autor: | Rajesh Narwal, Brandon W. Higgs, Yanan Zheng, Bing Wang, Ashok Kumar Gupta, Xiaoping Jin, Pralay Mukhopadhyay, Chaoyu Jin, Paul Baverel, Lorin Roskos, Yong Ben |
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| Rok vydání: | 2018 |
| Předmět: |
Male
Oncology Urologic Neoplasms medicine.medical_specialty Durvalumab Metastatic Urothelial Carcinoma medicine.medical_treatment Population Models Biological 030226 pharmacology & pharmacy B7-H1 Antigen Metastasis 03 medical and health sciences Antineoplastic Agents Immunological 0302 clinical medicine Predictive Value of Tests Internal medicine Outcome Assessment Health Care Biomarkers Tumor medicine Humans Neoplasm Invasiveness Pharmacology (medical) education Survival analysis Aged Neoplasm Staging Pharmacology education.field_of_study Chemotherapy business.industry Research Carcinoma Liver Neoplasms Antibodies Monoclonal Cancer Articles Prognosis medicine.disease Survival Analysis Tumor Burden 030220 oncology & carcinogenesis Predictive value of tests Female Urothelium business |
| Zdroj: | Clinical Pharmacology and Therapeutics |
| ISSN: | 1532-6535 0009-9236 |
| Popis: | Durvalumab is an anti-PD-L1 monoclonal antibody approved for patients with locally advanced or metastatic urothelial carcinoma (UC) that has progressed after platinum-containing chemotherapy. A population tumor kinetic model, coupled with dropout and survival models, was developed to describe longitudinal tumor size data and predict overall survival in UC patients treated with durvalumab (NCT01693562) and to identify prognostic and predictive biomarkers of clinical outcomes. Model-based covariate analysis identified liver metastasis as the most influential factor for tumor growth and immune-cell PD-L1 expression and baseline tumor burden as predictive factors for tumor killing. Tumor or immune-cell PD-L1 expression, liver metastasis, baseline hemoglobin, and albumin levels were identified as significant covariates for overall survival. These model simulations provided further insights into the impact of PD-L1 cutoff values on treatment outcomes. The modeling framework can be a useful tool to guide patient selection and enrichment strategies for immunotherapies across various cancer indications. |
| Databáze: | OpenAIRE |
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