Forough Farrokhyar

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About

Forough Farrokhyar is a leading biostatistician and clinical epidemiologist whose work centers on advancing evidence-based surgical practice, particularly in thoracic and minimally invasive procedures. Her research focuses on learning curve methodologies, comparative effectiveness of surgical techniques, and the integration of novel technologies like near-infrared fluorescence (NIF) imaging. Farrokhyar’s major contributions include pioneering the use of propensity-adjusted analyses to compare robotic versus thoracoscopic lung resection in obese patients, a study that has garnered 26 citations and informed surgical decision-making. She also led a scoping review of learning curve methods in minimally invasive thoracic surgery, providing a critical framework for evaluating surgeon proficiency. Her work on NIF-guided segmentectomy, though early-stage with 4 citations, highlights her role in refining intraoperative guidance to improve oncological outcomes. With a career dedicated to rigorous methodology, Farrokhyar’s research has shaped how surgeons assess new technologies and techniques, ensuring patient safety and efficacy. Her studies are widely referenced by clinicians and researchers seeking to optimize surgical training and outcomes, cementing her reputation as a key contributor to the field of surgical evidence synthesis.