Combining immunotherapy with an epidrug in squamous cell carcinomas of different locations: rationale and design of the PEVO basket trial.
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ABSTRACT:
SUBMITTER: de Guillebon E
PROVIDER: S-EPMC8066350 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The landscape for early phase cancer clinical trials is changing dramatically because of the advent of targeted therapy. Increasingly, new drugs are designed to work against a target such as the presence of a specific tumor mutation. Because typically only a small proportion of cancer patients will possess the mutational target, but the mutation is present in many different cancers, a new class of basket trials is emerging, whereby the drug is tested simultaneously in different baskets, that is, subgroups of different tumor types. Investigators desire not only to test whether the drug works but also to determine which types of tumors are sensitive to the drug. A natural strategy is to conduct parallel trials, with the drug 's effectiveness being tested separately, using for example, the popular Simon two-stage design independently in each basket. The work presented is motivated by the premise that the efficiency of this strategy can be improved by assessing the homogeneity of the baskets ' response rates at an interim analysis and aggregating the baskets in the second stage if the results suggest the drug might be effective in all or most baskets. Via simulations, we assess the relative efficiencies of the two strategies. Because the operating characteristics depend on how many tumor types are sensitive to the drug, there is no uniformly efficient strategy. However, our investigation demonstrates that substantial efficiencies are possible if the drug works in most or all baskets, at the cost of modest losses of power if the drug works in only a single basket. Copyright © 2017 John Wiley & Sons, Ltd.
| S-EPMC5380524 | biostudies-literature
Project description:Targeted therapies on the basis of genomic aberrations analysis of the tumor have shown promising results in cancer prognosis and treatment. Regardless of tumor type, trials that match patients to targeted therapies for their particular genomic aberrations have become a mainstream direction of therapeutic management of patients with cancer. Therefore, finding the subpopulation of patients who can most benefit from an aberration-specific targeted therapy across multiple cancer types is important. We propose an adaptive Bayesian clinical trial design for patient allocation and subpopulation identification. We start with a decision theoretic approach, including a utility function and a probability model across all possible subpopulation models. The main features of the proposed design and population finding methods are the use of a flexible nonparametric Bayesian survival regression based on a random covariate-dependent partition of patients, and decisions based on a flexible utility function that reflects the requirement of the clinicians appropriately and realistically, and the adaptive allocation of patients to their superior treatments. Through extensive simulation studies, the new method is demonstrated to achieve desirable operating characteristics and compares favorably against the alternatives.
| S-EPMC6261711 | biostudies-literature
Project description:In this article, we develop a Bayesian adaptive design methodology for oncology basket trials with binary endpoints using a Bayesian model averaging framework. Most existing methods seek to borrow information based on the degree of homogeneity of estimated response rates across all baskets. In reality, an investigational product may only demonstrate activity for a subset of baskets, and the degree of activity may vary across the subset. A key benefit of our Bayesian model averaging approach is that it explicitly accounts for the possibility that any subset of baskets may have similar activity and that some may not. Our proposed approach performs inference on the basket-specific response rates by averaging over the complete model space for the response rates, which can include thousands of models. We present results that demonstrate that this computationally feasible Bayesian approach performs favorably compared to existing state-of-the-art approaches, even when held to stringent requirements regarding false positive rates.
| S-EPMC7846150 | biostudies-literature
Project description:Innovative trial designs are sought to streamline drug development in rare diseases. Basket- and integrated protocol designs are two of these new strategies and have been applied in a handful oncologic trials. We have taken the concept outside the realm of oncology and report about a first-in-human integrated protocol design that facilitates the transition from phase Ia in healthy volunteers to phase Ib in patients with rare complement-mediated disorders driven by the classical pathway.We have been conducting a prospective, double-blind, randomized, placebo-controlled first-in-human study with TNT009, which is a humanized monoclonal antibody directed against the C1s subunit of human complement component C1. The trial consisted of three subparts, including normal healthy volunteers (part one and two) and a single cohort of patients in part three. Patients suffered from various complement-mediated diseases sharing the same pathophysiological mechanism, i.e. bullous pemphigoid, antibody-mediated rejection of organ transplants, cold agglutinin disease and warm autoimmune hemolytic anemia. Primary objective of the trial has been to evaluate the safety and tolerability of TNT009 in humans.This trial provides probably the first example that basket trials may not be limited to single genetic aberrations, which is overly restrictive, but our trial design demonstrates that pathway specificity is a viable paradigm for defining baskets. This will hopefully serve as a role model that could benefit other innovative drug development programs targeting rare diseases.
| S-EPMC5050564 | biostudies-literature
Project description:An increasing appreciation for the role of the immune system in targeting cancer cells over the last decade has led to the development of several immunomodulatory agents aimed at enhancing the systemic antitumor immune response. One such method is the use of T cells that are genetically engineered to express chimeric antigen receptors (CARs). The remarkable success of this approach in advanced hematologic malignancies has garnered much enthusiasm for using this novel tool in treating other cancers. However, multiple challenges have hampered the application of this therapy to a broader set of solid tumors, most notably lung cancer. Immunotherapy has already shown great success in lung cancer, and is now the first-line treatment in PD-L1 expressing metastatic disease. Given the mounting evidence that radiation therapy plays a crucial role in amplifying the immune response elicited by immunomodulatory agents, there is potential for radiation to help in overcoming some of these challenges. In this review, we describe the basic principles of CAR T cell therapy and examine its successes and challenges to date. We then discuss the preclinical and clinical data supporting the use of radiation with immunomodulatory agents with a focus on preclinical rationale for combining CAR T cells and radiation therapy in future experiments with a focus on lung cancer.
| S-EPMC5420544 | biostudies-literature
Project description:BACKGROUND:The basket trial evaluates the treatment effect of a targeted therapy in patients with the same genetic or molecular aberration, regardless of their cancer types. Bayesian hierarchical modeling has been proposed to adaptively borrow information across cancer types to improve the statistical power of basket trials. Although conceptually attractive, research has shown that Bayesian hierarchical models cannot appropriately determine the degree of information borrowing and may lead to substantially inflated type I error rates. METHODS:We propose a novel calibrated Bayesian hierarchical model approach to evaluate the treatment effect in basket trials. In our approach, the shrinkage parameter that controls information borrowing is not regarded as an unknown parameter. Instead, it is defined as a function of a similarity measure of the treatment effect across tumor subgroups. The key is that the function is calibrated using simulation such that information is strongly borrowed across subgroups if their treatment effects are similar and barely borrowed if the treatment effects are heterogeneous. RESULTS:The simulation study shows that our method has substantially better controlled type I error rates than the Bayesian hierarchical model. In some scenarios, for example, when the true response rate is between the null and alternative, the type I error rate of the proposed method can be inflated from 10% up to 20%, but is still better than that of the Bayesian hierarchical model. LIMITATION:The proposed design assumes a binary endpoint. Extension of the proposed design to ordinal and time-to-event endpoints is worthy of further investigation. CONCLUSION:The calibrated Bayesian hierarchical model provides a practical approach to design basket trials with more flexibility and better controlled type I error rates than the Bayesian hierarchical model. The software for implementing the proposed design is available at http://odin.mdacc.tmc.edu/~yyuan/index_code.html.
| S-EPMC5891374 | biostudies-literature
Project description:BackgroundImmune checkpoint inhibitors (ICI) have revolutionised treating advanced cancers. ICI are administered intravenously every 2-6 weeks for up to 2 years, until cancer progression/unacceptable toxicity. Physiological efficacy is observed at lower doses than those used as standard of care (SOC). Pharmacodynamic studies indicate sustained target occupancy, despite a pharmacological half-life of 2-3 weeks. Reducing frequency of administration may be possible without compromising outcomes. The REFINE trial aims to limit individual patient exposure to ICI whilst maintaining efficacy, with potential benefits in quality of life and reduced drug treatment/attendance costs.Methods/designREFINE is a randomised phase II, multi-arm, multi-stage (MAMS) adaptive basket trial investigating extended interval administration of ICIs. Eligible patients are those responding to conventionally dosed ICI at 12 weeks. In stage I, patients (n = 160 per tumour-specific cohort) will be randomly allocated (1:1) to receive maintenance ICI at SOC vs extended dose interval. REFINE is currently recruiting UK patients with locally advanced or metastatic renal cell carcinoma (RCC) who have tolerated and responded to initial nivolumab/ipilimumab, randomised to receive maintenance nivolumab SOC (480 mg 4 weekly) vs extended interval (480 mg 8 weekly). Additional tumour cohorts are planned. Subject to satisfactory outcomes (progression-free survival) stage II will investigate up to 5 different treatment intervals. Secondary outcome measures include overall survival, quality-of-life, treatment-related toxicity, mean incremental pathway costs and quality-adjusted life-years per patient. REFINE is funded by the Jon Moulton Charity Trust and Medical Research Council, sponsored by University College London (UCL), and coordinated by the MRC CTU at UCL. Trial Registration ISRCTN79455488. NCT04913025 EUDRACT #: 2021-002060-47. CTA 31330/0008/001-0001; MREC approval: 21/LO/0593. REFINE Protocol version 4.0.
| S-EPMC7614585 | biostudies-literature
Project description:The treatment of coronary small vessel disease (SVD) remains an unresolved issue. Drug-eluting stents (DES) have limited efficacy due to increased rates of instent-restenosis, mainly caused by late lumen loss. Drug-coated balloons (DCB) are a promising technique because native vessels remain structurally unchanged. Basel Stent Kosten-Effektivitäts Trial: Drug-Coated Balloons vs. Drug-Eluting Stents in Small Vessel Interventions (BASKET-SMALL 2) is a multicenter, randomized, controlled, noninferiority trial of DCB vs DES in native SVD for clinical endpoints. Seven hundred fifty-eight patients with de novo lesions in vessels <3 mm in diameter and an indication for percutaneous coronary intervention such as stable angina pectoris, silent ischemia, or acute coronary syndromes are randomized 1:1 to angioplasty with DCB vs implantation of a DES after successful initial balloon angioplasty. The primary endpoint is the combination of cardiac death, nonfatal myocardial infarction, and target-vessel revascularization up to 1 year. Secondary endpoints include stent thrombosis, Bleeding Academic Research Consortium (BARC) type 3 to 5 bleeding, and long-term outcome up to 3 years. Based on clinical endpoints after 1 year, we plan to assess the noninferiority of DCB compared to DES in patients undergoing primary percutaneous coronary intervention for SVD. Results will be available in the second half of 2018. This study will compare DCB and DES regarding long-term safety and efficacy for the treatment of SVD in a large all-comer population.
| S-EPMC6001703 | biostudies-literature
Project description:BackgroundCutaneous squamous cell carcinoma (CSCC) has a propensity for perineural spread (PNS) which is associated with poorer treatment outcomes. Immunotherapy is the new standard of care treatment for advanced CSCC resulting in durable responses. PNS is not captured by traditional response assessment criteria used in clinical trials, e.g. RECIST 1.1, and there is limited literature documenting radiological PNS responses to immunotherapy. In this study we assess PNS responses to immunotherapy using a modified grading system.MethodsThis is an Australian single-center retrospective review of patients with advanced CSCC who were treated with immunotherapy between April 2018 and February 2022 who had evidence of PNS on pre-treatment magnetic-resonance imaging (MRI). The primary outcome was blinded overall radiological response in PNS using graded radiological criteria, post-commencement of immunotherapy. Three defined timepoints (< 5 months, 5-10 months, > 10 months) were reviewed. Secondary outcomes included a correlation between RECIST 1.1 and PNS assessments and the assessment of PNS on fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT).ResultsTwenty CSCC patients treated with immunotherapy were identified. Median age was 75.7 years and 75% (n = 15) were male. All patients had locoregionally advanced disease and no distant metastases. Median follow-up was 18.5 months (range: 2-59). 70% (n = 14) demonstrated a PNS response by 5 months. Three patients experienced pseudoprogression. One patient had PNS progression by the end of study follow up. RECIST 1.1 and PNS responses were largely concordant at > 10 months (Cohen's Kappa 0.62). 5/14 cases had features suspicious for PNS on FDG-PET/CT.ConclusionsPNS response to immunotherapy can be documented on MRI using graded radiological criteria. High response rates were seen in PNS with the use of immunotherapy in this cohort and these responses were largely concordant with RECIST 1.1 assessments. FDG-PET/CT demonstrated limited sensitivity in the detection of PNS.
| S-EPMC10949695 | biostudies-literature
Project description: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 (?0.5) , this can lead to unacceptably high false-positive rates (?40%) 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.
| S-EPMC6822679 | biostudies-literature