Sylvester Researchers Develop Predictive Model to Guide Immunotherapy for Lung Cancer Patients

Researchers at Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine have developed a predictive model that can help guide immunotherapy for patients with advanced non-small cell lung cancer.

The new predictive model can help guide immunotherapy for patients with advanced non-small cell lung cancer.

“Over the last few years, we have developed new medications to help the body’s immune system fight lung cancer,” said Gilberto de Lima Lopes, Jr., M.D., associate professor of clinical medicine, medical director for international programs, associate director for global oncology, and co-leader of the Lung Cancer Site Disease Group.

“However, not all patients benefit from immunotherapy, and some experience side effects that can be severe,” added Lopes, who was co-author of a recent study published online by the journal Clinical Lung Cancer that examined clinical outcomes of lung cancer patients who were given the drug nivolumab after failing chemotherapy.

Wungki Park, M.D., an oncology fellow who works closely with Lopes, was the lead author of the study, “Developing an Algorithmic Model to Predict Clinical Outcomes of Advanced Non-Small Cell Lung Cancer Patients Treated with Nivolumab.” He presented the study at a lung cancer conference in Tokyo prior to its publication.

“We retrospectively evaluated 159 Sylvester patients with advanced non-small cell lung cancer who were treated with nivolumab after progression on platinum-based chemotherapy,” said Park. “We developed a simple, easy-to-use model called iSEND that can help clinicians predict which patients are likely to benefit from immunotherapy.”

Mohammad Jahanzeb, M.D., medical director of Sylvester Comprehensive Cancer Center at Deerfield Beach, was the senior author of the study, and co-authors were Miller School faculty and trainees Deukwoo Kwon, Ph.D., Diana Saravia, M.D., Amrita Desai, M.D., Fernando Vargas, M.D., Mohamed El Dinali, M.D., Jessica Warsch, M.D., Roy Elias, M.D., Sean Warsch, M.D., Adrian Ishkanian, M.D., Chukwuemeka Ikpeazu, M.D., Ph.D., M.B.A., and Raja Mudad, M.D.

“Dr. Park has analyzed the relationship of various elements easily available from the patients’ medical record to propose a predictive model for response to immunotherapy that is both innovative and practical,” Jahanzeb said. “This will, of course, need prospective validation in larger cohorts of patients, but it is particularly relevant given the cost of immunotherapy agents that, to date, work in a minority of patients.”

The model incorporates cellular information from a blood sample, as well as the patient’s overall physical condition and medical history.

“We found that patients with a low ratio of neutrophils to lymphocytes — two types of immune cells that can fight infection and cancer — had better outcomes than those with a high ratio,” Lopes said. “The neutrophils may suppress the cancer-fighting action of the lymphocytes, so a lower ratio would enable a more robust response.”

Another predictive indicator was the change in the ratio of neutrophils to lymphocytes after one dose of nivolumab, Lopes added. Patients whose ratios did not decrease significantly were less likely to improve from further immunotherapy treatments.

“This new iSEND model is designed to help clinicians make informed decisions about individual patient treatment,” Lopes said. “It’s another step toward the delivery of personalized medicine for cancer patients.”

Tags: immunotherapy, iSEND predictive model, Miller School of Medicine, non-small cell lung cancer, Sylvester Comprehensive Cancer Center, University of Miami