{"doi":"10.1093/annonc/mdx795","title":"Phase I–II clinical trial design: a state-of-the-art paradigm for dose finding","abstract":null,"journal":"Annals of Oncology","year":2018,"id":622836,"datarank":0.6766289259775276,"base_score":4.51085950651685,"endowment":4.51085950651685,"self_citation_contribution":0.6766289259775276,"citation_network_contribution":0.0,"self_endowment_contribution":0.6766289259775276,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":90,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1609450,"name":"P.F. Thall","orcid":null,"position":1,"is_corresponding":false},{"id":1609451,"name":"K.H. Lu","orcid":null,"position":2,"is_corresponding":false},{"id":1609452,"name":"M.R. Gilbert","orcid":null,"position":3,"is_corresponding":false},{"id":268557,"name":"Ying Yuan","orcid":"0000-0003-3163-480X","position":4,"is_corresponding":false},{"id":610267,"name":"F. Yan","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Phase I–II clinical trial design: a state-of-the-art paradigm for dose finding","abstract":"Background: Conventional phase I algorithms for finding a phase-2 recommended dose (P2RD) based on toxicity alone is problematic because the maximum tolerated dose (MTD) is not necessarily the optimal dose with the most desirable risk-benefit trade-off. Moreover, the increasingly common practice of treating an expansion cohort at a chosen MTD has undesirable consequences that may not be obvious. Patients and methods: We review the phase I-II paradigm and the EffTox design, which utilizes both efficacy and toxicity to choose optimal doses for successive patient cohorts and find the optimal P2RD. We conduct a computer simulation study to compare the performance of the EffTox design with the traditional 3 + 3 design and the continuous reassessment method. Results: By accounting for the risk-benefit trade-off, the EffTox phase I-II design overcomes the limitations of conventional toxicity-based phase I designs. Numerical simulations show that the EffTox design has higher probabilities of identifying the optimal dose and treats more patients at the optimal dose. Conclusions: Phase I-II designs, such as the EffTox design, provide a coherent and efficient approach to finding the optimal P2RD by explicitly accounting for risk-benefit trade-offs underlying medical decisions.","is_dataset_classified":null,"base_score":4.51085950651685,"endowment":4.51085950651685,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"29267863","pmcid":"PMC5888967","openalex_id":"https://openalex.org/W2781164451","authors":[],"funders":[{"funder_name":"National Institutes of Health","grant_id":"R01 CA83932","title":null},{"funder_name":"National Institutes of Health","grant_id":"P50CA098258","title":null}],"total_grants":2,"fwci":2.7589,"citation_percentile":0.93022942,"influential_citations":0,"citation_trend":[{"year":2018,"count":1},{"year":2019,"count":5},{"year":2020,"count":7},{"year":2021,"count":12},{"year":2022,"count":9},{"year":2023,"count":15},{"year":2024,"count":19},{"year":2025,"count":18},{"year":2026,"count":4}],"oa_status":"hybrid","license":"cc-by-nc-nd","oa_locations":[{"url":"https://doi.org/10.1093/annonc/mdx795","host_type":"journal"},{"url":"https://doi.org/10.1093/annonc/mdx795","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S0923753419355061?httpAccept=text/xml","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S0923753419355061?httpAccept=text/plain","host_type":"publisher"},{"url":"http://academic.oup.com/annonc/article-pdf/29/3/694/24530907/mdx795.pdf","host_type":"publisher"},{"url":"https://pubmed.ncbi.nlm.nih.gov/29267863","host_type":"repository"},{"url":"http://europepmc.org/pmc/articles/PMC5888967","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5888967","host_type":"repository"}],"fields_of_study":["Statistical Methods in Clinical Trials","Advanced Causal Inference Techniques","Optimal Experimental Design Methods","Algorithms","Antineoplastic Agents","Clinical Trials, Phase I as Topic","Clinical Trials, Phase II as Topic","Computer Simulation","Humans","Maximum Tolerated Dose","Research Design","Risk Assessment"],"mesh_terms":["Algorithms","Antineoplastic Agents","Computer Simulation","Humans","Research Design","Clinical Trials, Phase I as Topic","Clinical Trials, Phase II as Topic","Risk Assessment","Maximum Tolerated Dose"],"keywords":["Medicine","Clinical trial","Medical physics","Oncology","Internal medicine"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Partnerships for the goals"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-03T21:14:35.530551Z","pmid":null,"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":[]}