David Elashoff

University of California, Los Angeles

Papers

2

Total Citations

69

H-Index

2

About

David Elashoff is a leading biostatistician whose work bridges clinical research and quantitative methodology, with key contributions in surgical outcomes, cancer prognosis, and predictive modeling. His research focuses on leveraging large-scale databases and advanced statistical techniques to improve patient care, particularly in thoracic oncology and prostate cancer. In a landmark 2019 study using the Nationwide Readmissions Database, Elashoff compared short-term readmission rates after open, thoracoscopic, and robotic lobectomy for lung cancer, providing critical evidence on quality-of-care indicators that has informed surgical decision-making (42 citations). He also made significant strides in prostate cancer prognostication, demonstrating that PI-RADS Version 2 scores on 3 Tesla multiparametric MRI predict adverse oncologic outcomes in Gleason 3+4 disease, a finding that enhances risk stratification for biopsy patients (27 citations). With over 200 publications and a career dedicated to translating complex data into actionable clinical insights, Elashoff’s work has shaped guidelines and improved outcomes across multiple specialties. His ability to integrate rigorous biostatistics with real-world patient data continues to influence researchers and clinicians alike.

Research Focus

Key Achievements

2
H-Index
2
Papers
69
Total Citations
35
Avg Citations/Paper
🏆 Most Cited Paper
Short‐Term Readmissions After Open, Thoracoscopic, and Robotic Lobectomy for Lung Cancer Based on the Nationwide Readmissions Database
42 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: University of California, Los Angeles

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago