Advance-CTR

Investigator Spotlight: Boris Gershman, MD

Congratulations, Dr. Gershman! 

Boris Gershman, MD
Boris Gershman, MD

Boris Gershman, MD, was recently published in Urology for his research on a novel methodological framework to emulate two target clinical trials for renal cell carcinoma. Dr. Gershman is an assistant professor of surgery at the Beth Israel Deaconess Medical Center. He previously served as an assistant professor of surgery at the Alpert Medical School of Brown University. 

Dr. Gershman consulted with Advance-CTR's Research Design, Epidemiology, and Biostatistics Core throughout all phases of the study, from study design through to drafting and revising his manuscript for publication.

The Study 

"Emulating Target Clinical Trials of Radical Nephrectomy with or without Lymph Node Dissection for Renal Cell Carcinoma" (Urology, 2020)

Randomized clinical trials of competing surgical interventions are difficult to conduct. As a result, randomized evidence is often limited or lacking to support the comparative effectiveness of surgical interventions. This is particularly true for the study of kidney cancer, where only one randomized trial has examined the oncologic role of lymph node dissection in patients undergoing radical nephrectomy.

To address this important evidence gap, we utilized a novel methodological framework to emulate two target clinical trials of radical nephrectomy with or without lymph node dissection in the management of renal cell carcinoma. In this study, which was recently accepted in Urology, lymph node dissection as not associated with an improvement in overall survival in an emulation of a completed randomized clinical trial (EORTC 30881) or in an emulation of a hypothetical target trial of high-risk patients.

Looking ahead, we will continue to work to extend the emulation approach to other settings within urologic oncology.

"The Biostatistics Core was instrumental to the success of this study. We worked with them throughout all phases of the study, and received help with study design, conduction, drafting/revision of the manuscript, and advanced biostatistical support that allowed for the implementation of robust statistical methodology to optimize causal inference."