Assessment of tumour-agnostic therapies in basket trials

2022 ◽  
Vol 23 (1) ◽  
pp. e7
Author(s):  
Sanjay Popat ◽  
Sreeram V Ramagopalan ◽  
Joshua Ray ◽  
Stéphane Roze ◽  
Vivek Subbiah
Keyword(s):  
Basket Trials

scholarly journals Tumour-Agnostic Therapy for Pancreatic Cancer and Biliary Tract Cancer

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 252
Author(s):  
Shunsuke Kato
Keyword(s):  
Pancreatic Cancer ◽  
Biliary Tract ◽  
Biliary Tract Cancer ◽  
Cancer Genome ◽  
Current Status ◽  
Driver Mutations ◽  
Hereditary Cancer Syndrome ◽  
Routine Practice ◽  
Tract Cancer ◽  
Basket Trials

The prognosis of patients with solid tumours has remarkably improved with the development of molecular-targeted drugs and immune checkpoint inhibitors. However, the improvements in the prognosis of pancreatic cancer and biliary tract cancer is delayed compared to other carcinomas, and the 5-year survival rates of distal-stage disease are approximately 10 and 20%, respectively. However, a comprehensive analysis of tumour cells using The Cancer Genome Atlas (TCGA) project has led to the identification of various driver mutations. Evidently, few mutations exist across organs, and basket trials targeting driver mutations regardless of the primary organ are being actively conducted. Such basket trials not only focus on the gate keeper-type oncogene mutations, such as HER2 and BRAF, but also focus on the caretaker-type tumour suppressor genes, such as BRCA1/2, mismatch repair-related genes, which cause hereditary cancer syndrome. As oncogene panel testing is a vital approach in routine practice, clinicians should devise a strategy for improved understanding of the cancer genome. Here, the gene mutation profiles of pancreatic cancer and biliary tract cancer have been outlined and the current status of tumour-agnostic therapy in these cancers has been reported.

scholarly journals Variance prior specification for a basket trial design using Bayesian hierarchical modeling

2018 ◽  
Vol 16 (2) ◽  
pp. 142-153 ◽  
Author(s):  
Kristen M Cunanan ◽  
Alexia Iasonos ◽  
Ronglai Shen ◽  
Mithat Gönen
Keyword(s):  
Standard Deviation ◽  
Prior Distribution ◽  
Hierarchical Modeling ◽  
Bayesian Hierarchical Modeling ◽  
Bayesian Hierarchical ◽  
Inverse Gamma ◽  
Wide Range ◽  
Basket Trial ◽  
Basket Trials ◽  
Variance Parameter

Background: In the era of targeted therapies, clinical trials in oncology are rapidly evolving, wherein patients from multiple diseases are now enrolled and treated according to their genomic mutation(s). In such trials, known as basket trials, the different disease cohorts form the different baskets for inference. Several approaches have been proposed in the literature to efficiently use information from all baskets while simultaneously screening to find individual baskets where the drug works. Most proposed methods are developed in a Bayesian paradigm that requires specifying a prior distribution for a variance parameter, which controls the degree to which information is shared across baskets. Methods: A common approach used to capture the correlated binary endpoints across baskets is Bayesian hierarchical modeling. We evaluate a Bayesian adaptive design in the context of a non-randomized basket trial and investigate three popular prior specifications: an inverse-gamma prior on the basket-level variance, a uniform prior and half-t prior on the basket-level standard deviation. Results: From our simulation study, we can see that the inverse-gamma prior is highly sensitive to the input hyperparameters. When the prior mean value of the variance parameter is set to be near zero [Formula: see text], this can lead to unacceptably high false-positive rates [Formula: see text] in some scenarios. Thus, use of this prior requires a fully comprehensive sensitivity analysis before implementation. Alternatively, we see that a prior that places sufficient mass in the tail, such as the uniform or half-t prior, displays desirable and robust operating characteristics over a wide range of prior specifications, with the caveat that the upper bound of the uniform prior and the scale parameter of the half-t prior must be larger than 1. Conclusion: Based on the simulation results, we recommend that those involved in designing basket trials that implement hierarchical modeling avoid using a prior distribution that places a majority of the density mass near zero for the variance parameter. Priors with this property force the model to share information regardless of the true efficacy configuration of the baskets. Many commonly used inverse-gamma prior specifications have this undesirable property. We recommend to instead consider the more robust uniform prior or half-t prior on the standard deviation.

scholarly journals Efficiency of a Randomized Confirmatory Basket Trial Design Constrained to Control the False Positive Rate by Indication

2020 ◽  
Author(s):  
Linchen He ◽  
Yuru Ren ◽  
Han Chen ◽  
Daphne Guinn ◽  
Deepak Parashar ◽  
...  
Keyword(s):  
False Positive ◽  
Power Efficiency ◽  
Statistical Significance ◽  
False Positive Rate ◽  
Pooled Analysis ◽  
Positive Control ◽  
Design Parameters ◽  
Molecular Oncology ◽  
Basket Trial ◽  
Basket Trials

PURPOSEMolecular oncology determines biomarker-defined niche indications. Basket trials pool histologic indications sharing molecular pathophysiology, potentially improving development efficiency. Currently basket trials have been confirmatory only for exceptional therapies. Our previous randomized basket design may be generally suitable in the resource-intensive confirmatory phase, maintains high power, and provides nearly k-fold increased efficiency for k indications, but controls false positives for the pooled result only. Since false positive control by indications (FWER) may sometimes be required, we now simulate a variant of this basket design controlling FWER at 0.025k, the total FWER of k separate randomized trials.METHODSThe previous design eliminated indications at an interim analysis, conducting a final pooled analysis of remaining indications. To control FWER, we rechecked individual indications at a prospectively defined level of statistical significance after any positive pooled result. We simulated this modified design under numerous scenarios varying design parameters. Only designs controlling FWER and minimizing estimation bias were allowable.RESULTSSequential analyses (interim, pooled, and post-individual tests)) result in cumulative power losses. Optimal performance results when k = 3,4. We report efficiency (expected # true positives/expected sample size) relative to k parallel studies, at 90% power (“uncorrected”) or at the power achieved in the basket trial (“corrected”, because conventional designs could also increase efficiency by sacrificing power). Efficiency and power (percentage active indications identified) improve with higher percentage of initial indications active. Up to 92% uncorrected and 38% corrected efficiency improvement is possible, with power ≈ 60%.CONCLUSIONSEven under FWER control, randomized confirmatory basket trials substantially improve development efficiency. Initial indication selection is critical. The design is particularly attractive when enrollment challenges preclude full powering of individual indications.

scholarly journals Challenges and approaches to implementing master/basket trials in oncology

2019 ◽  
Vol 3 (14) ◽  
pp. 2237-2243 ◽  
Author(s):  
Amy Burd ◽  
Richard L. Schilsky ◽  
John C. Byrd ◽  
Ross L. Levine ◽  
Vassiliki A. Papadimitrakopoulou ◽  
...  
Keyword(s):  
Health Care Providers ◽  
Therapeutic Option ◽  
Clinical Trial Design ◽  
Care Providers ◽  
Rare Mutation ◽  
Medical Institutions ◽  
Number Of Patients ◽  
The Right ◽  
Tumor Types ◽  
Basket Trials

Abstract The appetite for cutting-edge cancer research, across medical institutions, scientific researchers, and health care providers, is increasing based on the promise of true breakthroughs and cures with new therapeutics available for investigation. At the same time, the barriers for advancing clinical research are impacting how quickly drug development efforts are conducted. For example, we know now that under a microscope, patients with the same type of cancer and histology might look the same; however, the reality is that most cancers are driven by genomic, transcriptional, and epigenetic changes that make each patient unique. Additionally, the immunologic reaction to different tumor types is distinct among patients. The challenge for researchers developing new therapies today is vastly different than it was in the era of cytotoxics. Today, we must identify a sufficient number of patients harboring a rare mutation or other characteristic and match this to the right therapeutic option. This summary provides a guide to help inform the scientific cancer community about the benefits and challenges of conducting umbrella or basket trials (master trials), and to create a roadmap to help make this new and evolving form of clinical trial design as effective as possible.

scholarly journals Comparing the Efficacy of Cancer Therapies between Subgroups in Basket Trials

Cell Systems ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 449-460.e2
Author(s):  
Adam C. Palmer ◽  
Deborah Plana ◽  
Peter K. Sorger
Keyword(s):  
Cancer Therapies ◽  
Basket Trials

Basket Trials: Just the End of the First Quarter

2015 ◽  
Vol 33 (25) ◽  
pp. 2823-2824 ◽  
Author(s):  
Albrecht Stenzinger ◽  
Wilko Weichert ◽  
Jochen K. Lennerz ◽  
Frederick Klauschen
Keyword(s):  
Basket Trials

Using real world data (RWD) analytics to drive operational efficiencies in basket trials.

2018 ◽  
Vol 36 (15_suppl) ◽  
pp. e14517-e14517
Author(s):  
Stelios Tzellos ◽  
Jamie Adams ◽  
Anika Arora ◽  
Steffen Brehmer ◽  
Niranjan Grandhi ◽  
...  
Keyword(s):  
Real World ◽  
Real World Data ◽  
World Data ◽  
Basket Trials

scholarly journals A Pilot Study of Comprehensive Genomic Profiling for Pediatric and Adolescent and Young Adult Solid Tumor Patients in Japan

2021 ◽  
Author(s):  
Shotaro Matsudera ◽  
Yoshihito Kano ◽  
Yasuko Aoyagi ◽  
Kohki Tohyama ◽  
Kei Ogino ◽  
...  
Keyword(s):  
Solid Tumor ◽  
Wilms Tumor ◽  
Adolescent And Young Adult ◽  
Genomic Alteration ◽  
Genomic Profiling ◽  
Tumor Patients ◽  
Comprehensive Genomic Profiling ◽  
Healthcare Insurance ◽  
Tumor Types ◽  
Basket Trials

Background: Comprehensive genomic profiling (CGP) was widely adopted in Japan after its coverage by national healthcare insurance began in June 2019. We investigated the clinical utility of CGP in pediatric and adolescent young adults (AYA) solid tumor patients. Procedure: Between November 2017 and December 2019, 13 patients who progressed with or who were likely to progress with standard therapies were recruited to the PROFILE-F study to undergo CGP using either FoundationOne® CDx or FoundationOne® Heme. Results: The median age was 28 years old. Tumor types were as follows: neuroblastoma (n=1), Wilms’ tumor (n=1), rhabdomyosarcoma (n=2), Ewing sarcoma (n=1), gastric cancer (n=1), rectal cancer (n=1), osteosarcoma (n=1), neuroendocrine tumor (n=2), salivary gland carcinoma (n=1), tracheal adenoid cystic carcinoma (n=1), and thymic cancer (n=1). In 92% of cases, at least one genomic alteration was identified, including CDKN2A (four cases), TP53 (three cases), and MYC (two cases). Actionable aberrations were found in 10 cases (77%), and a clinical trial candidate was found in seven cases (54%). However, no patients were able to receive biomarker-matched therapy according to their genomic alterations. Conclusions: Further efforts to increase basket trials and collection of clinical genomic data to predict response are necessary to advance precision cancer medicine in pediatric and AYA populations.

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