{"doi":"10.3390/cancers17233750","title":"An Alternative Treatment Effect Measure for Time-to-Event Oncology Randomized Trials","abstract":"Background/Objectives: Time-to-event endpoints such as Overall Survival (OS), Progression-Free Survival (PFS), and Event-Free Survival (EFS) are central in phase III oncology trials. Hazard ratios from Cox proportional hazards models and log-rank tests are the standard analytic tools, supplemented by Kaplan–Meier estimates. However, these methods depend on proportional hazards to deliver unbiased estimates of treatment effects and large-sample assumptions, and may perform poorly under heavy censoring or non-proportional hazards. We introduce the univariate martingale residual (UMR) as a new endpoint and summary measure that enables exact inference through randomization testing. Methods: The UMR reflects the difference between observed and expected events at the subject level. Average UMRs per treatment arm provide an absolute measure of excess events. A randomization-based testing framework is used to compare treatment arms and compute exact p-values without proportional hazards or asymptotic assumptions. Performance is assessed through simulations and demonstrated using real oncology trial data. Results: UMRs offered robust and interpretable treatment summaries under heavy censoring, non-proportional hazards, and quasi-complete separation, where Cox-based estimates were unstable or undefined. The exact UMR-based randomization test maintained Type I error control and was competitive or more powerful than the log-rank test when proportional hazards were violated. Conclusions: The UMR provides an intuitive, assumption-free summary of treatment effects and supports exact inference. It represents a practical and robust alternative to hazard-ratio-based methods in phase III oncology trials, especially in complex survival settings.","journal":"Cancers","year":2025,"id":582943,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9507,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":483541,"name":"Han Yu","orcid":"0000-0001-6160-173X","position":1,"is_corresponding":false},{"id":328926,"name":"Alan D. Hutson","orcid":"0000-0002-7353-5650","position":0,"is_corresponding":true}],"reference_count":39,"raw_metadata":null,"created_at":"2026-07-19T02:58:59.653747Z","pmid":"41374954","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}