Basket Trials: Review of Current Practice and Innovations for Future Trials

Target-Driven Tissue-Agnostic Drug Approvals-A New Path of Drug Development

The regulatory approvals of tumor-agnostic therapies have led to the re-evaluation of the drug development process. The conventional models of drug development are histology-based. On the other hand, the tumor-agnostic drug development of a new drug (or combination) focuses on targeting a common genomic biomarker in multiple cancers, regardless of histology. The basket-like clinical trials with multiple cohorts allow clinicians to evaluate pan-cancer efficacy and toxicity. There are currently eight tumor agnostic approvals granted by the Food and Drug Administration (FDA). This includes two immune checkpoint inhibitors, and five targeted therapy agents. Pembrolizumab is an anti-programmed cell death protein-1 (PD-1) antibody that was the first FDA-approved tumor-agnostic treatment for unresectable or metastatic microsatellite instability-high (MSI-H) or deficient mismatch repair (dMMR) solid tumors in 2017. It was later approved for tumor mutational burden-high (TMB-H) solid tumors, although the TMB cut-off used is still debated. Subsequently, in 2021, another anti-PD-1 antibody, dostarlimab, was also approved for dMMR solid tumors in the refractory setting. Patients with fusion-positive cancers are typically difficult to treat due to their rare prevalence and distribution. Gene rearrangements or fusions are present in a variety of tumors. Neurotrophic tyrosine kinase (NTRK) fusions are present in a range of pediatric and adult solid tumors in varying frequency. Larotrectinib and entrectinib were approved for neurotrophic tyrosine kinase (NTRK) fusion-positive cancers. Similarly, selpercatinib was approved for rearranged during transfection (RET) fusion-positive solid tumors. The FDA approved the first combination therapy of dabrafenib, a B-Raf proto-oncogene serine/threonine kinase (BRAF) inhibitor, plus trametinib, a mitogen-activated protein kinase (MEK) inhibitor for patients 6 months or older with unresectable or metastatic tumors (except colorectal cancer) carrying a BRAFV600E mutation. The most recent FDA tumor-agnostic approval is of fam-trastuzumab deruxtecan-nxki (T-Dxd) for HER2-positive solid tumors. It is important to identify and expeditiously develop drugs that have the potential to provide clinical benefit across tumor types.

Bayesian Methods for Information Borrowing in Basket Trials: An Overview

Basket trials allow simultaneous evaluation of a single therapy across multiple cancer types or subtypes of the same cancer. Since the same treatment is tested across all baskets, it may be desirable to borrow information across them to improve the statistical precision and power in estimating and detecting the treatment effects in different baskets. We review recent developments in Bayesian methods for the design and analysis of basket trials, focusing on the mechanism of information borrowing. We explain the common components of these methods, such as a prior model for the treatment effects that embodies an assumption of exchangeability. We also discuss the distinct features of these methods that lead to different degrees of borrowing. Through simulation studies, we demonstrate the impact of information borrowing on the operating characteristics of these methods and discuss its broader implications for drug development. Examples of basket trials are presented in both phase I and phase II settings.

Integrated budget impact model to estimate the impact of introducing selpercatinib as a tumor-agnostic treatment option for patients with RET-altered solid tumors in the US

OBJECTIVE

To estimate the potential budget impact on US third party payers (commercial or Medicare) associated with addition of selpercatinib as a tumor-agnostic treatment for patients with Rearranged during Transfection (RET)-altered solid tumors.

METHODS

An integrated budget impact model (iBIM) with 3-year (Y) time horizon was developed for 19 RET-altered tumors. It is referred to as an integrated model because it is a single model that integrated results across multiple tumor types (as opposed to tumor-specific models developed traditionally). The model estimated eligible patient populations and included tumor-specific comparator treatments for each tumor type. Estimated annual total costs (2022USD, $) included costs of drug, administration, supportive care, and toxicity. For a one-million-member plan, the number of patients with RET-altered tumors eligible for treatment, incremental total costs, and incremental per-member per-month (PMPM) costs associated with introduction of selpercatinib treatment were estimated. Uncertainty associated with model parameters was assessed using various sensitivity analyses.

RESULTS

Commercial perspective estimated 11.68 patients/million with RET-altered tumors as treatment-eligible annually, of which 7.59 (Y1), 8.17 (Y2), and 8.76 (Y3) patients would be selpercatinib-treated (based on forecasted market share). The associated incremental total and PMPM costs (commercial) were estimated to be: $873,099 and $0.073 (Y1), $2,160,525 and $0.180 (Y2), and $2,561,281 and $0.213 (Y3), respectively. The Medicare perspective estimated 55.82 patients/million with RET-altered tumors as treatment-eligible annually, of which 36.29 (Y1), 39.08 (Y2), and 41.87 (Y3) patients would be selpercatinib-treated. The associated incremental total and PMPM costs (Medicare) were estimated to be: $4,447,832 and $0.371 (Y1), $11,076,422 and $0.923 (Y2), and $12,637,458 and $1.053 (Y3), respectively. One-way sensitivity analyses across both perspectives identified drug costs, selpercatinib market share, incidence of RET, and treatment duration as significant drivers of incremental costs.

CONCLUSIONS

Three-year incremental PMPM cost estimates suggest a modest impact on payer-budgets associated with introduction of tumor-agnostic selpercatinib treatment.

Basket trials in oncology: a systematic review of practices and methods, comparative analysis of innovative methods, and an appraisal of a missed opportunity

Background

Basket trials are increasingly used in oncology drug development for early signal detection, accelerated tumor-agnostic approvals, and prioritization of promising tumor types in selected patients with the same mutation or biomarker. Participants are grouped into so-called baskets according to tumor type, allowing investigators to identify tumors with promising responses to treatment for further study. However, it remains a question as to whether and how much the adoption of basket trial designs in oncology have translated into patient benefits, increased pace and scale of clinical development, and de-risking of downstream confirmatory trials.

Methods

Innovation in basket trial design and analysis includes methods that borrow information across tumor types to increase the quality of statistical inference within each tumor type. We build on the existing systematic reviews of basket trials in oncology to discuss the current practices and landscape. We conceptually illustrate recent innovative methods for basket trials, with application to actual data from recently completed basket trials. We explore and discuss the extent to which innovative basket trials can be used to de-risk future trials through their ability to aid prioritization of promising tumor types for subsequent clinical development.

Results

We found increasing adoption of basket trial design in oncology, but largely in the design of single-arm phase II trials with a very low adoption of innovative statistical methods. Furthermore, the current practice of basket trial design, which does not consider its impact on the clinical development plan, may lead to a missed opportunity in improving the probability of success of a future trial. Gating phase II with a phase Ib basket trial reduced the size of phase II trials, and losses in the probability of success as a result of not using innovative methods may not be recoverable by running a larger phase II trial.

Conclusion

Innovative basket trial methods can reduce the size of early phase clinical trials, with sustained improvement in the probability of success of the clinical development plan. We need to do more as a community to improve the adoption of these methods.

Anaesthesia, analgesia, and cancer outcomes: time to think like oncologists?

Cao and colleagues present a follow-up analysis of a previous RCT among >1200 older adults (mean age 72 yr) undergoing cancer surgery, originally designed to evaluate the effect of propofol or sevoflurane general anaesthesia on delirium, here to evaluate the effect of anaesthetic technique on overall survival and recurrence-free survival. Neither anaesthetic technique conferred an advantage on oncological outcomes. We suggest that although it is entirely plausible that the observed results are truly robust neutral findings, the present study could be limited, like most published studies in the field, by its heterogeneity and understandable absence of underlying individual patient-specific tumour genomic data. We argue for a precision oncology approach to onco-anaesthesiology research that recognises that cancer is not one but rather many diseases and that tumour genomics (and multi-omics) is a fundamental determinant relating drugs to longer-term outcomes.

Umbrella review of basket trials testing a drug in tumors with actionable genetic biomarkers

BACKGROUND

The utilization of basket trials in oncology has gained popularity because of the drive for precision medicine and the increasing ease of genetically profiling tumors. However, it is unknown if this has translated into patient benefit, either through higher response rates because of precision treatment or because of increasing options for less-common tumor types that are less represented in oncology drug trials. We sought to characterize basket studies for oncology drugs targeting a genetic biomarker, determine the responses for various tumor types and genetic biomarkers, and test for correlation between the number of participants in each tumor basket and the incidence of the respective tumor.

METHODS

We conducted a retrospective cross-sectional review of oncology basket trials on Embase or clinicaltrials.gov with published data. We included studies that reported on oncology drugs that target a genetic biomarker. We examined the response for basket trial participants, stratified by tumor type and genetic biomarker and the correlation between the number of participants in each tumor basket and the incidence of the respective tumor.

RESULTS

The overall response rate for all 25 included trials was 23%. The response for each genetic biomarker ranged from 0 to 69%, and for half of the genetic biomarkers, the response rate ranged from 0 to 100%, depending on tumor type. There is low correlation between the number of participants in each tumor basket and the incidence of the respective tumor (66.41 + -0.20x, R² = 0.003, p = 0.75).

CONCLUSION

While there has been an increase in the number of published basket trials and individuals included in these trials, the response rate is low, but varies widely, depending on tumor type and genetic biomarker.