Justifying the source of external comparators in single-arm oncology health technology submissions: a review of NICE and PBAC assessments

Background: The drive to expedite patient access for diseases with high unmet treatment needs has come with an increasing use of single-arm trials (SATs), especially in oncology. However, the lack of control arms in such trials creates challenges to assess and demonstrate comparative efficacy. External control (EC) arms can be used to bridge this gap, with various types of sources available to obtain relevant data. Objective: To examine the source of ECs in single-arm oncology health technology assessment (HTA) submissions to the National Institute for Health and Care Excellence (NICE) and the Pharmaceutical Benefits Advisory Committee (PBAC) and how this selection was justified by manufacturers and assessed by the respective HTA body. Methods: Single-arm oncology HTA submission reports published by NICE (England) and PBAC (Australia) from January 2011 to August 2021 were reviewed, with data qualitatively synthesized to identify themes. Results: Forty-eight oncology submissions using EC arms between 2011 and 2021 were identified, with most submissions encompassing blood and bone marrow cancers (52%). In HTA submissions to NICE and PBAC, the EC arm was typically constructed from a combination of data sources, with the company's justification in data source selection infrequently provided (PBAC [2 out of 19]; NICE [6 out of 29]), although this lack of justification was not heavily criticized by either HTA body. Conclusion: Although HTA bodies such as NICE and PBAC encourage that EC source justification should be provided in submissions, this review found that this is not typically implemented in practice. Guidance is needed to establish best practices as to how EC selection should be documented in HTA submissions.

Eribulin for patients with metastatic extramammary Paget disease: Study protocol for a single-arm phase II trial

Extramammary Paget disease (EMPD) is a rare cutaneous malignancy that predominantly affects the anogenital areas of the elderly. Although the efficacy of docetaxel and other cytotoxic agents for advanced EMPD has been reported in small retrospective case studies, no treatment has been proven effective in prospective clinical trials. We established the world's first in vivo EMPD experimental model (a patient-derived xenograft model). In our treatment experiment, xenograft tumours showed a remarkable response to eribulin. This study evaluates the efficacy of eribulin for patients with advanced EMPD. In October 2022, we started a single-arm phase II trial to evaluate the efficacy of eribulin as a treatment for adult patients with unresectable EMPD with measurable lesions. Enrolment in this clinical trial is open to patients with any prior treatment for EMPD. The primary endpoint is overall response rate; the secondary endpoints include disease control rate, overall survival, progression-free survival and adverse events. The study protocol was approved by the Ethics Committee of Hokkaido University and the other collaborating institutions. If the primary endpoint is met, it is our hope that eribulin will be regarded as a standard medication for patients with advanced EMPD.

Data Challenges for Externally Controlled Trials: Viewpoint

The preferred evidence of a large randomized controlled trial is difficult to adopt in scenarios, such as rare conditions or clinical subgroups with high unmet needs, and evidence from external sources, including real-world data, is being increasingly considered by decision makers. Real-world data originate from many sources, and identifying suitable real-world data that can be used to contextualize a single-arm trial, as an external control arm, has several challenges. In this viewpoint article, we provide an overview of the technical challenges raised by regulatory and health reimbursement agencies when evaluating comparative efficacy, such as identification, outcome, and time selection challenges. By breaking down these challenges, we provide practical solutions for researchers to consider through the approaches of detailed planning, collection, and record linkage to analyze external data for comparative efficacy.

BRIDGING RANDOMIZED CONTROLLED TRIALS AND SINGLE-ARM TRIALS USING COMMENSURATE PRIORS IN ARM-BASED NETWORK META-ANALYSIS

Network meta-analysis (NMA) is a powerful tool to compare multiple treatments directly and indirectly by combining and contrasting multiple independent clinical trials. Because many NMAs collect only a few eligible randomized controlled trials (RCTs), there is an urgent need to synthesize different sources of information, e.g., from both RCTs and single-arm trials. However, single-arm trials and RCTs may have different populations and quality, so that assuming they are exchangeable may be inappropriate. This article presents a novel method using a commensurate prior on variance (CPV) to borrow variance (rather than mean) information from single-arm trials in an arm-based (AB) Bayesian NMA. We illustrate the advantages of this CPV method by reanalyzing an NMA of immune checkpoint inhibitors in cancer patients. Comprehensive simulations investigate the impact on statistical inference of including single-arm trials. The simulation results show that the CPV method provides efficient and robust estimation even when the two sources of information are moderately inconsistent.

Detecting deviations from the efficacy and safety results of single-arm trials using real-world data: The case of a CAR-T cell therapy in B-cell lymphoma

PURPOSE

Personalized therapies are leading to an increasing number of marketing authorizations based on single-arm trials, which increases the demand for better post-authorization monitoring strategies. The aim of the present study was to estimate the power over time as data accrue in population-based registries for detecting deviations from the expected efficacy/safety of chimeric antigen receptor T cell (CAR-T) therapy approved for relapsed/refractory large B-cell lymphoma (RR-LBCL).

METHODS

The number of real-world RR-LBCL patients was projected over time in a general population of 5, 15, and 25 million citizens using lymphoma registry data. For each scenario, we computed the power over time for detecting significant deviations in efficacy (1-year overall survival [1yOS]) when comparing to historical controls (SCHOLAR-1 study; 1yOS, 28%) and RR-LBCL patients treated with CAR-T cell therapy in a single-arm trial (ZUMA-1; 1yOS, 59%) as well as deviations in selected adverse events (grade ≥3 aphasia) from the ZUMA-1 trial. We assumed a 10% absolute deviation in 1yOS (efficacy) and a relative increase of 50% in grade ≥3 aphasia (safety).

RESULTS

Assuming a general population of 5, 15, and 25 million, the accrual time needed to achieve 80% power for detecting a significant increase over the 1yOS reported in SCHOLAR-1 was 9, 4, and 3 years, respectively, while 80% power for detecting a significant decrease in 1yOS compared to ZUMA-1 required 10.5, 4.5, and 3 years of data accrual, respectively. However, corresponding estimates for aphasia were >20, 8, and 5 years, respectively.

CONCLUSIONS

Projections of the statistical power for detecting important deviations in efficacy/safety from that reported in pivotal clinical trials(s) provide critical information about the expected performance of post-authorization monitoring programs.

The response rate of alternative treatments for drugs approved on the basis of response rate

We assessed the frequency that oncology drugs approved by the U.S. Food and Drug Administration (FDA) based on a single-arm study when there is already evidence of existing and available treatments. For this, we conducted a retrospective cross-sectional analysis of FDA-approved oncology drugs based on a single-arm study. All FDA announcements for all oncology drugs approved from May 2014 through June 2019 on a single-arm trial were included. We then performed a systematic search in PubMed, looking for studies on other drugs for the same indication as the FDA drug approval. For the 60 indications, we found 38 instances (63%) of existing therapies being used for the same indication. Of those, we found that 20 drugs were approved based upon a response rate lower than response rates of existing therapies in the same indication. Among oncology drugs that were FDA-approved based on a single-arm study, we found evidence of existing, available therapies being used for the same indication as the FDA-approved drug in the majority of indications (63%), and in one-third of all indications, the response rates for existing therapies were numerically better than the FDA-approved drug. These results suggest that there are inconsistencies in the standards set for oncology drug approvals, and many uncontrolled trials leading to drug approvals could have contemporary controls for which equipoise exists.

The Effects of Model Misspecification in Unanchored Matching-Adjusted Indirect Comparison: Results of a Simulation Study

OBJECTIVES

To assess the performance of unanchored matching-adjusted indirect comparison (MAIC) by matching on first moments or higher moments in a cross-study comparisons under a variety of conditions. A secondary objective was to gauge the performance of the method relative to propensity score weighting (PSW).

METHODS

A simulation study was designed based on an oncology example, where MAIC was used to account for differences between a contemporary trial in which patients had more favorable characteristics and a historical control. A variety of scenarios were then tested varying the setup of the simulation study, including violating the implicit or explicit assumptions of MAIC.

RESULTS

Under ideal conditions and under a variety of scenarios, MAIC performed well (shown by a low mean absolute error [MAE]) and was unbiased (shown by a mean error [ME] of about zero). The performance of the method deteriorated where the matched characteristics had low explanatory power or there was poor overlap between studies. Only when important characteristics are not included in the matching did the method become biased (nonzero ME). Where the method showed poor performance, this was exaggerated if matching was also performed on the variance (ie, higher moments). Relative to PSW, MAIC provided similar results in most circumstances, although it exhibited slightly higher MAE and a higher chance of exaggerating bias.

CONCLUSIONS

MAIC appears well suited to adjust for cross-trial comparisons provided the assumptions underpinning the model are met, with relatively little efficiency loss compared with PSW.

High-dose Dexamethasone Therapy as the Initial Treatment for Idiopathic Thrombocytopenic Purpura: Protocol for a Multicenter, Open-label, Single Arm Trial

Standard therapy for idiopathic thrombocytopenic purpura (ITP) has not been established. We are conducting a multicenter, prospective trial to determine the efficacy and safety of short-term, high-dose dexamethasone therapy in ITP patients aged 18-80 years with platelet counts of <20, 000 /μL, or with <50, 000/ μL and bleeding symptoms. The primary endpoints of this trial are the proportion of responses (complete plus partial response) on day 180 (day 46+180) after the completion of the 46-day high-dose dexamethasone therapy. The results of this investigation of the effectiveness and safety of this regimen will be essential for the establishment of standard therapy for ITP.

Utility of Bayesian Single-Arm Design in New Drug Application for Rare Cancers in Japan: A Case Study of Phase 2 Trial for Sarcoma

Investigational drugs for rare cancers are often approved based solely on a single-arm phase II trial that primarily evaluates response rate in Japan. Such trials typically use a fixed sample size determined on the basis of the frequentist manner. However, since predicting the speed of patient enrollment is challenging because of the disease rarity, the time needed to complete the enrollment of the fixed number of patients is prolonged in some cases. A Bayesian design without fixing the sample size is useful for single-arm phase II trials of rare cancers. However, the arbitrariness of prior distribution specifications and the frequentist operating characteristics are regulatory issues. We recently started a Bayesian single-arm phase II trial of nivolumab in patients with sarcoma for new drug application in Japan and examined the statistical rationale and design consideration. In the Bayesian design, we specify the minimum and maximum numbers of enrolled patients during the enrollment period and the prior distributions of response rates. Considering these parameters, we obtain the minimum number of responders needed for the positive conclusion of the efficacy of nivolumab for each sample size. Simulation studies demonstrated that the operating characteristics of this design would be acceptable from the frequentist view. The Bayesian design provided an adaptive decision rule for efficacy conclusion for the drug without fixing the sample size. We hope our trial's success will provide a new drug development option for rare cancers in Japan.