Biomaterial Database

A Bayesian seamless phase I-II trial design with two stages for cancer clinical trials with drug combinations. 2020

José L Jiménez, and Sungjin Kim, and Mourad Tighiouart

Biostatistical Sciences and Pharmacometrics, Novartis Pharma A.G., Basel, Switzerland.

The use of drug combinations in clinical trials is increasingly common during the last years since a more favorable therapeutic response may be obtained by combining drugs. In phase I clinical trials, most of the existing methodology recommends a one unique dose combination as "optimal," which may result in a subsequent failed phase II clinical trial since other dose combinations may present higher treatment efficacy for the same level of toxicity. We are particularly interested in the setting where it is necessary to wait a few cycles of therapy to observe an efficacy outcome and the phase I and II population of patients are different with respect to treatment efficacy. Under these circumstances, it is common practice to implement two-stage designs where a set of maximum tolerated dose combinations is selected in a first stage, and then studied in a second stage for treatment efficacy. In this article we present a new two-stage design for early phase clinical trials with drug combinations. In the first stage, binary toxicity data is used to guide the dose escalation and set the maximum tolerated dose combinations. In the second stage, we take the set of maximum tolerated dose combinations recommended from the first stage, which remains fixed along the entire second stage, and through adaptive randomization, we allocate subsequent cohorts of patients in dose combinations that are likely to have high posterior median time to progression. The methodology is assessed with extensive simulations and exemplified with a real trial.

UI	MeSH Term	Description	Entries
D009369	Neoplasms	New abnormal growth of tissue. Malignant neoplasms show a greater degree of anaplasia and have the properties of invasion and metastasis, compared to benign neoplasms.	Benign Neoplasm,Cancer,Malignant Neoplasm,Tumor,Tumors,Benign Neoplasms,Malignancy,Malignant Neoplasms,Neoplasia,Neoplasm,Neoplasms, Benign,Cancers,Malignancies,Neoplasias,Neoplasm, Benign,Neoplasm, Malignant,Neoplasms, Malignant
D012107	Research Design	A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly.	Experimental Design,Data Adjustment,Data Reporting,Design, Experimental,Designs, Experimental,Error Sources,Experimental Designs,Matched Groups,Methodology, Research,Problem Formulation,Research Methodology,Research Proposal,Research Strategy,Research Technics,Research Techniques,Scoring Methods,Adjustment, Data,Adjustments, Data,Data Adjustments,Design, Research,Designs, Research,Error Source,Formulation, Problem,Formulations, Problem,Group, Matched,Groups, Matched,Matched Group,Method, Scoring,Methods, Scoring,Problem Formulations,Proposal, Research,Proposals, Research,Reporting, Data,Research Designs,Research Proposals,Research Strategies,Research Technic,Research Technique,Scoring Method,Source, Error,Sources, Error,Strategies, Research,Strategy, Research,Technic, Research,Technics, Research,Technique, Research,Techniques, Research
D003198	Computer Simulation	Computer-based representation of physical systems and phenomena such as chemical processes.	Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D004305	Dose-Response Relationship, Drug	The relationship between the dose of an administered drug and the response of the organism to the drug.	Dose Response Relationship, Drug,Dose-Response Relationships, Drug,Drug Dose-Response Relationship,Drug Dose-Response Relationships,Relationship, Drug Dose-Response,Relationships, Drug Dose-Response
D004338	Drug Combinations	Single preparations containing two or more active agents, for the purpose of their concurrent administration as a fixed dose mixture.	Drug Combination,Combination, Drug,Combinations, Drug
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000970	Antineoplastic Agents	Substances that inhibit or prevent the proliferation of NEOPLASMS.	Anticancer Agent,Antineoplastic,Antineoplastic Agent,Antineoplastic Drug,Antitumor Agent,Antitumor Drug,Cancer Chemotherapy Agent,Cancer Chemotherapy Drug,Anticancer Agents,Antineoplastic Drugs,Antineoplastics,Antitumor Agents,Antitumor Drugs,Cancer Chemotherapy Agents,Cancer Chemotherapy Drugs,Chemotherapeutic Anticancer Agents,Chemotherapeutic Anticancer Drug,Agent, Anticancer,Agent, Antineoplastic,Agent, Antitumor,Agent, Cancer Chemotherapy,Agents, Anticancer,Agents, Antineoplastic,Agents, Antitumor,Agents, Cancer Chemotherapy,Agents, Chemotherapeutic Anticancer,Chemotherapy Agent, Cancer,Chemotherapy Agents, Cancer,Chemotherapy Drug, Cancer,Chemotherapy Drugs, Cancer,Drug, Antineoplastic,Drug, Antitumor,Drug, Cancer Chemotherapy,Drug, Chemotherapeutic Anticancer,Drugs, Antineoplastic,Drugs, Antitumor,Drugs, Cancer Chemotherapy
D001499	Bayes Theorem	A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.	Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D017321	Clinical Trials, Phase I as Topic	Works about studies performed to evaluate the safety of diagnostic, therapeutic, or prophylactic drugs, devices, or techniques in healthy subjects and to determine the safe dosage range (if appropriate). These tests also are used to determine pharmacologic and pharmacokinetic properties (toxicity, metabolism, absorption, elimination, and preferred route of administration). They involve a small number of persons and usually last about 1 year. This concept includes phase I studies conducted both in the U.S. and in other countries.	Clinical Trials, Phase I,Drug Evaluation, FDA Phase I,Evaluation Studies, FDA Phase I,Human Microdosing Trial,Phase 1 Clinical Trial,Phase I Clinical Trial,Phase I Clinical Trials,Clinical Trials, Phase 1,Drug Evaluation, FDA Phase 1,Drug Evaluation, FDA Phase I as Topic,Evaluation Studies, FDA Phase 1,Human Microdosing Trials,Microdosing Trials, Human,Phase 1 Clinical Trials,Microdosing Trial, Human,Trial, Human Microdosing,Trials, Human Microdosing
D017322	Clinical Trials, Phase II as Topic	Works about studies that are usually controlled to assess the effectiveness and dosage (if appropriate) of diagnostic, therapeutic, or prophylactic drugs, devices, or techniques. These studies are performed on several hundred volunteers, including a limited number of patients with the target disease or disorder, and last about two years. This concept includes phase II studies conducted in both the U.S. and in other countries.	Drug Evaluation, FDA Phase 2 as Topic,Drug Evaluation, FDA Phase II as Topic,Evaluation Studies, FDA Phase 2 as Topic,Evaluation Studies, FDA Phase II as Topic