Events

Department Seminars

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  Wednesday, January 21, 2026

  1:30 - 2:30 pm Central Time online

  Survival Data Analysis Using Average Hazard with Survival Weight

  We are pleased to welcome Hajime Ono, PhD, for a seminar on survival data analysis. The traditional Cox hazard ratio has long been used to summarize treatment effects in time-to-event analyses, but its well-known limitations have led researchers to explore alternative measures. One such alternative, the average hazard with survival weight (AH), provides a person-time incidence rate that remains unaffected by nuisance random censoring, offering a more interpretable and robust summary of treatment effects. In this talk, Dr. Uno will discuss this approach, including two-sample comparisons, regression analysis, and stratified analysis. By offering a fresh perspective on survival data analysis, the AH approach provides an impactful alternative to the Cox hazard ratio approach, helping researchers better capture and communicate the magnitude of treatment effects.

  Dr. Uno is Associate Professor of Medicine at Harvard Medical School and Associate Professor in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. He serves as Principal Biostatistician and Director of the Statistical Programming Core in the Division of Population Sciences at the Dana-Farber Cancer Institute. He received his doctorate in Biostatistics in Japan and completed postdoctoral training at the Harvard School of Public Health. Since then, he has worked extensively on methodological and clinical research projects. One of his notable methodological contributions is a modification of the concordance index (C-index) for evaluating risk prediction models with censored time-to-event data. His 2011 Statistics in Medicine paper describing this method was ranked among the ten most-cited articles in the journal over 2012–2013, and the method—commonly known as “Uno’s C”—is implemented in the SAS/PHREG procedure. As of December 2025, the paper has been cited more than 1,700 times. His current research interests focus on improving the practice of survival analysis in clinical research and promoting alternative approaches that enhance the quality of informed treatment decisions.

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