Dataset Information

How to Balance Prognostic Factors in Controlled Phase II Trials: Stratified Permuted Block Randomization or Minimization? An Analysis of Clinical Trials in Digestive Oncology.

ABSTRACT: In controlled phase II trials, major prognostic factors need to be well balanced between arms. The main procedures used are SPBR (Stratified Permuted Block Randomization) and minimization. First, we provide a systematic review of the treatment allocation procedure used in gastrointestinal oncology controlled phase II trials published in 2019. Second, we performed simulations using data from six phase II studies to measure the impacts of imbalances and bias on the efficacy estimations. From the 40 articles analyzed, all mentioned randomization in both the title and abstract, the median number of patients included was 109, and 77.5% were multicenter. Of the 27 studies that reported at least one stratification variable, 10 included the center as a stratification variable, 10 used minimization, 9 used SBR, and 8 were unspecified. In real data studies, the imbalance increased with the number of centers. The total and marginal imbalances were higher with SBR than with minimization, and the difference increased with the number of centers. The efficiency estimates per arm were close to the original trial estimate in both procedures. Minimization is often used in cases of numerous centers and guarantees better similarity between arms for stratification variables for total and marginal imbalances in phase II trials.

SUBMITTER: Martin E

PROVIDER: S-EPMC11202503 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

How to Balance Prognostic Factors in Controlled Phase II Trials: Stratified Permuted Block Randomization or Minimization? An Analysis of Clinical Trials in Digestive Oncology.

Martin Elodie E Le Malicot Karine K Guérin-Charbonnel Catherine C Bocquet François F Bouché Olivier O Turpin Anthony A Aparicio Thomas T Legoux Jean-Louis JL Dahan Laetitia L Taieb Julien J Lepage Côme C Dourthe Louis-Marie LM Pétorin Caroline C Bourgeois Vincent V Raoul Jean-Luc JL Seegers Valérie V

Current oncology (Toronto, Ont.) 20240617 6

In controlled phase II trials, major prognostic factors need to be well balanced between arms. The main procedures used are SPBR (Stratified Permuted Block Randomization) and minimization. First, we provide a systematic review of the treatment allocation procedure used in gastrointestinal oncology controlled phase II trials published in 2019. Second, we performed simulations using data from six phase II studies to measure the impacts of imbalances and bias on the efficacy estimations. From the 4 ...[more]

PMID: 38920742

Similar Datasets

Project description:Minimizing the imbalance of key baseline covariates between treatments is known to be very important to the precision of the estimate of treatment effect in clinical research. Dynamic randomization allocation techniques have been used to achieve balance across multiple baseline characteristics. However, empirical data are limited on how these techniques compare in terms of balance and efficiency. We are motivated by a newly funded randomized controlled trial, in which we have the option of choosing between two methods of randomization at the subject level: (1) randomizing individual subjects consecutively as they are enrolled, using Pocock and Simon's minimization method, and (2) simultaneously randomizing blocks of subjects once all subjects in a block have been enrolled, using a balance algorithm originally developed for cluster randomized trials.To compare dynamic block randomization and minimization in terms of balance on baseline covariates and statistical efficiency. Simple randomization was included as a reference.A simulation study using data from a previous randomized controlled trial was conducted to compare balance statistics and the accuracy and power of hypothesis testing among the randomization methods.Dynamic block randomization consistently produced the best balance and highest power for various sample and treatment effect sizes, even after post-adjustment of the pre-specified baseline covariates in all three methods. Consistent with previous reports, minimization performed better in balance and power than simple randomization; however, the differences were noticeably smaller compared to those between dynamic block randomization and simple randomization.In this simulation study, we considered three sample sizes and two block sizes for a two-arm randomized trial. We assumed no interactions among the multiple baseline covariates. It is necessary to evaluate how the results may vary when the simulation conditions are changed before drawing broader conclusions regarding comparisons between the randomization methods.This study demonstrates that dynamic block randomization outperforms minimization with regard to achieving balance and maximizing efficiency. Nevertheless, the differences across the three randomization strategies are modest. The statistical advantages associated with dynamic block randomization need to be considered in relation to the planned sample size and the practical issues for its implementation in deciding the preferred method of randomization for a given trial (e.g., the time required to accrue blocks of subjects of adequate size as balanced against the need to commence intervention/treatment immediately in those randomized to that experimental condition).

Project description:BackgroundGiven the inherent challenges of conducting randomized phase III trials in older cancer patients, single-arm phase II trials which assess the feasibility of a treatment that has already been shown to be effective in a younger population may provide a compelling alternative. Such an approach would need to evaluate treatment feasibility based on a composite endpoint that combines multiple clinical dimensions and to stratify older patients as fit or frail to account for the heterogeneity of the study population to recommend an appropriate treatment approach. In this context, stratified adaptive two-stage designs for binary or composite endpoints, initially developed for biomarker studies, allow to include two subgroups whilst maintaining competitive statistical performances. In practice, heterogeneity may indeed affect more than one dimension and incorporating co-primary endpoints, which independently assess each individual clinical dimension, would therefore appear quite pertinent. The current paper presents a novel phase II design for co-primary endpoints which takes into account the heterogeneity of a population. METHODS: We developed a stratified adaptive Bryant & Day design based on the Jones et al. and Parashar et al. algorithm. This two-stage design allows to jointly assess two dimensions (e.g. activity and toxicity) in two different subgroups. The operating characteristics of this new design were evaluated using examples and simulation comparisons with the Bryant & Day design in the context where the study population is stratified according to a pre-defined criterion.ResultsSimulation results demonstrated that the new design minimized the expected and maximum sample sizes as compared to parallel Bryant & Day designs (one in each subgroup), whilst controlling type I error rates and maintaining a competitive statistical power as well as a high probability of detecting heterogeneity.ConclusionsIn a heterogeneous population, this two-stage stratified adaptive phase II design provides a useful alternative to classical one and allows to identify a subgroup of interest without dramatically increasing sample size. As heterogeneity is not limited to older populations, this new design may also be relevant to other study populations such as children or adolescents and young adults or the development of targeted therapies based on a biomarker.

Project description:BackgroundOverall survival (OS) is the gold standard for the demonstration of a clinical benefit in cancer trials. Replacement of OS by a surrogate endpoint allows to reduce trial duration. To date, few surrogate endpoints have been validated in digestive oncology. The aim of this study was to draw up an ordered list of potential surrogate endpoints for OS in digestive cancer trials, by way of a survey among clinicians and methodologists. Secondary objective was to obtain their opinion on surrogacy and quality of life (QoL).MethodsIn 2007 and 2008, self administered sequential questionnaires were sent to a panel of French clinicians and methodologists involved in the conduct of cancer clinical trials. In the first questionnaire, panellists were asked to choose the most important characteristics defining a surrogate among six proposals, to give advantages and drawbacks of the surrogates, and to answer questions about their validation and use. Then they had to suggest potential surrogate endpoints for OS in each of the following tumour sites: oesophagus, stomach, liver, pancreas, biliary tract, lymphoma, colon, rectum, and anus. They finally gave their opinion on QoL as surrogate endpoint. In the second questionnaire, they had to classify the previously proposed candidate surrogates from the most (position #1) to the least relevant in their opinion.Frequency at which the endpoints were chosen as first, second or third most relevant surrogates was calculated and served as final ranking.ResultsResponse rate was 30% (24/80) in the first round and 20% (16/80) in the second one. Participants highlighted key points concerning surrogacy. In particular, they reminded that a surrogate endpoint is expected to predict clinical benefit in a well-defined therapeutic situation. Half of them thought it was not relevant to study QoL as surrogate for OS.DFS, in the neoadjuvant settings or early stages, and PFS, in the non operable or metastatic settings, were ranked first, with a frequency of more than 69% in 20 out of 22 settings. PFS was proposed in association with QoL in metastatic primary liver and stomach cancers (both 81%). This composite endpoint was ranked second in metastatic oesophageal (69%), colorectal (56%) and anal (56%) cancers, whereas QoL alone was also suggested in most metastatic situations.Other endpoints frequently suggested were R0 resection in the neoadjuvant settings (oesophagus (69%), stomach (56%), pancreas (75%) and biliary tract (63%)) and response. An unexpected endpoint was metastatic PFS in non operable oesophageal (31%) and pancreatic (44%) cancers. Quality and results of surgical procedures like sphincter preservation were also cited as eligible surrogate endpoints in rectal (19%) and anal (50% in case of localized disease) cancers. Except for alpha-FP kinetic in hepatocellular carcinoma (13%) and CA19-9 decline (6%) in pancreas, few endpoints based on biological or tumour markers were proposed.ConclusionThe overall results should help prioritise the endpoints to be statistically evaluated as surrogate for OS, so that trialists and clinicians can rely on endpoints that ensure relevant clinical benefit to the patient.

Project description:BackgroundImmuno-oncology (IO) is rapidly evolving in early drug development. We aimed to develop and prospectively validate a prognostic index for patients treated in IO phase I trials to assist with patient selection.MethodsThe development cohort included 192 advanced solid tumor patients treated in 13 IO phase I trials, targeting immune checkpoint and/or co-stimulatory molecules. A prognostic scoring system was developed from multivariate survival analysis of 10 clinical factors, and subsequently validated in two independent validation cohorts (n = 152 and n = 80).ResultsIn the development cohort, median age was 57.5 years (range = 20.4-84.8 years). Median progression-free survival and overall survival (OS) were 13.4 and 73.6 weeks, respectively, 90-day mortality was 16%, and overall response rate was 20%. In multivariate analysis, Eastern Cooperative Oncology Group performance status greater than or equal to 1 (hazard ratio [HR] = 3.2, 95% confidence interval [CI] = 1.8 to 5.7; P < .001), number of metastatic sites greater than 2 (HR = 2.0, 95% CI = 1.3 to 3.1; P = .003), and albumin less than the lower limit of normal (HR = 1.8, 95% CI = 1.2 to 2.7; P = .007) were independent prognostic factors; comprising the Princess Margaret Immuno-oncology Prognostic Index (PM-IPI). Patients with a score of 2-3 compared with patients with a score of 0-1 had shorter OS (HR = 3.4, 95% CI = 1.9 to 6.1; P < .001), progression-free survival (HR = 2.3, 95% CI = 1.7 to 3.2; P < .001), higher 90-day mortality (odds ratio = 8.1, 95% CI = 3.0 to 35.4; P < .001), and lower overall response rate (odds ratio = 0.4, 95% CI = 0.2 to 0.8; P = .019). The PM-IPI retained prognostic ability in both validation cohorts and performed better than previously published phase I prognostic scores for predicting OS in all three cohorts.ConclusionsThe PM-IPI is a validated prognostic score for patients treated in phase I IO trials and may aid in improving patient selection.

Dataset Information

How to Balance Prognostic Factors in Controlled Phase II Trials: Stratified Permuted Block Randomization or Minimization? An Analysis of Clinical Trials in Digestive Oncology.

Publications

How to Balance Prognostic Factors in Controlled Phase II Trials: Stratified Permuted Block Randomization or Minimization? An Analysis of Clinical Trials in Digestive Oncology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets