Strategies to address non-proportional hazards between survival curves - Lessons from phase III trials in hepatocellular carcinoma
Ezequiel Mauro; Tiago de Castro; Marcus Zeitlhoefler; Allan Hackshaw; MinJae Lee; Tim Meyer; Amit G. Singal; Josep M. Llovet · 2025 · Journal of Hepatology
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
BACKGROUND & AIMS: Non-proportional hazards (NPH) can lead to discrepancies between interim (IA) and final analyses (FA) in randomized controlled trials (RCTs) of hepatocellular carcinoma (HCC). We assessed the impact of NPH in pivotal HCC…
Excerpt shown for reference under fair use — read the full paper at the publisher.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results*
Negative / Null Result ReportThe harmonic mean p -value for combining dependent tests
Negative / Null Result ReportGeneralizability of heterogeneous treatment effect estimates across samples
Negative / Null Result ReportNumerical predictors of arithmetic success in grades 1–6
Negative / Null Result ReportMethods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics
Negative / Null Result ReportShould multiple imputation be the method of choice for handling missing data in randomized trials?
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.1016/j.jhep.2025.08.042