{"doi":"10.1186/s13063-024-08400-6","title":"Design considerations for Factorial Adaptive Multi-Arm Multi-Stage (FAST) clinical trials","abstract":"BACKGROUND: Multi-Arm, Multi-Stage (MAMS) clinical trial designs allow for multiple therapies to be compared across a spectrum of clinical trial phases. MAMS designs fall under several overarching design groups, including adaptive designs (AD) and multi-arm (MA) designs. Factorial clinical trials designs represent a combination of factorial and MAMS trial designs and can provide increased efficiency relative to fixed, traditional designs. We explore design choices associated with Factorial Adaptive Multi-Arm Multi-Stage (FAST) designs, which represent the combination of factorial and MAMS designs. METHODS: Simulation studies were conducted to assess the impact of the type of analyses, the timing of analyses, and the effect size observed across multiple outcomes on trial operating characteristics for a FAST design. Given multiple outcomes types assessed within the hypothetical trial, the primary analysis approach for each assessment varied depending on data type. RESULTS: The simulation studies demonstrate that the proposed class of FAST trial designs can offer a framework to potentially provide improvements relative to other trial designs, such as a MAMS or factorial trial. Further, we note that the design implementation decisions, such as the timing and type of analyses conducted throughout trial, can have a great impact on trial operating characteristics. CONCLUSIONS: Motivated by a trial currently under design, our work shows that the FAST category of trial can potentially offer benefits similar to both MAMS and factorial designs; however, the chosen design aspects which can be included in a FAST trial need to be thoroughly explored during the planning phase.","journal":"Trials","year":2024,"id":469139,"datarank":0.20794415416798362,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.0,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9595,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":398231,"name":"Jordan Elm","orcid":"0000-0002-4893-8474","position":1,"is_corresponding":false},{"id":264405,"name":"Matthew W. Semler","orcid":"0000-0002-7664-8263","position":2,"is_corresponding":false},{"id":1194087,"name":"Li Wang","orcid":"0000-0002-5205-7290","position":3,"is_corresponding":false},{"id":105997,"name":"Todd W. Rice","orcid":"0000-0002-7136-5408","position":4,"is_corresponding":false},{"id":109055,"name":"Hooman Kamel","orcid":"0000-0002-5745-0307","position":5,"is_corresponding":false},{"id":299190,"name":"William J. Mack","orcid":"0000-0003-0970-2546","position":6,"is_corresponding":false},{"id":353771,"name":"Akshitkumar M. Mistry","orcid":"0000-0002-7918-5153","position":7,"is_corresponding":false},{"id":975902,"name":"Jonathan Beall","orcid":"0000-0003-2135-2606","position":0,"is_corresponding":true}],"reference_count":7,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:05:28.027781Z","pmid":"39261887","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":[]}