{"doi":"10.3390/cancers17152570","title":"Optimizing One-Sample Tests for Proportions in Single- and Two-Stage Oncology Trials","abstract":"BACKGROUND/OBJECTIVES: Phase II oncology trials often rely on single-arm designs to test H0:π=π0 versus Ha:π>π0, especially when randomized trials are infeasible due to cost or disease rarity. Traditional approaches, such as the exact binomial test and Simon's two-stage design, tend to be conservative, with actual Type I error rates falling below the nominal α due to the discreteness of the underlying binomial distribution. This study aims to develop a more efficient and flexible method that maintains accurate Type I error control in such settings. METHODS: We propose a convolution-based method that combines the binomial distribution with a simulated normal variable to construct an unbiased estimator of π. This method is designed to precisely control the Type I error rate while enabling more efficient trial designs. We derive its theoretical properties and assess its performance against traditional exact tests in both one-stage and two-stage trial designs. RESULTS: The proposed method results in more efficient designs with reduced sample sizes compared to standard approaches, without compromising the control of Type I error rates. We introduce a new two-stage design incorporating interim futility analysis and compare it with Simon's design. Simulations and real-world examples demonstrate that the proposed approach can significantly lower trial cost and duration. CONCLUSIONS: This convolution-based approach offers a flexible and efficient alternative to traditional methods for early-phase oncology trial design. It addresses the conservativeness of existing designs and provides practical benefits in terms of resource use and study timelines.","journal":"Cancers","year":2025,"id":571631,"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":0.9575,"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":328926,"name":"Alan D. Hutson","orcid":"0000-0002-7353-5650","position":0,"is_corresponding":true}],"reference_count":14,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:57:19.669553Z","pmid":"40805264","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":[]}