AMEERA-4: a randomized, preoperative window-of-opportunity study of amcenestrant versus letrozole in early breast cancer.

BACKGROUND: Window-of-opportunity (WOO) studies provide insights into the clinical activity of new drugs in breast cancer. METHODS: AMEERA-4 (NCT04191382) was a WOO study undertaken to compare the pharmacodynamic effects of amcenestrant, a selective estrogen receptor degrader, with those of letrozole in postmenopausal women with newly diagnosed, operable estrogen receptor-positive, human epidermal growth factor receptor 2-negative (ER+/HER2-) breast cancer. Women were randomized (1:1:1) to receive amcenestrant 400 mg, amcenestrant 200 mg, or letrozole 2.5 mg once daily for 14 days before breast surgery. The primary endpoint was change in Ki67 between baseline and Day 15 (i.e., day of surgery). RESULTS: Enrollment was stopped early because of slow recruitment, in the context of the COVID-19 pandemic. The modified intent-to-treat population consisted of 95 study participants with baseline and post-treatment Ki67 values, whereas the safety population included 104 participants who had received at least one dose of study medication. Relative change from baseline in Ki67 was - 75.9% (95% confidence interval [CI] - 81.9 to - 67.9) for amcenestrant 400 mg, - 68.2% (- 75.7 to - 58.4) for amcenestrant 200 mg, and - 77.7% (- 83.4 to - 70.0) for letrozole (geometric least-squares mean [LSM] estimates). Absolute change in ER H-score from baseline (LSM estimate) was - 176.7 in the amcenestrant 400 mg arm, - 202.9 in the amcenestrant 200 mg arm, and - 32.5 in the letrozole arm. There were no Grade ≥ 3 treatment-related adverse events. CONCLUSIONS: Both amcenestrant and letrozole demonstrated antiproliferative activity in postmenopausal women with previously untreated, operable ER+/HER2- breast cancer and had good overall tolerability. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04191382 https://clinicaltrials.gov/ct2/show/NCT04191382 . Registered 9 December 2019.

Utilization of treatment effect on a surrogate endpoint for planning a study to evaluate treatment effect on a final endpoint.

To design a phase III study with a final endpoint and calculate the required sample size for the desired probability of success, we need a good estimate of the treatment effect on the endpoint. It is prudent to fully utilize all available information including the historical and phase II information of the treatment as well as external data of the other treatments. It is not uncommon that a phase II study may use a surrogate endpoint as the primary endpoint and has no or limited data for the final endpoint. On the other hand, external information from the other studies for the other treatments on the surrogate and final endpoints may be available to establish a relationship between the treatment effects on the two endpoints. Through this relationship, making full use of the surrogate information may enhance the estimate of the treatment effect on the final endpoint. In this research, we propose a bivariate Bayesian analysis approach to comprehensively deal with the problem. A dynamic borrowing approach is considered to regulate the amount of historical data and surrogate information borrowing based on the level of consistency. A much simpler frequentist method is also discussed. Simulations are conducted to compare the performances of different approaches. An example is used to illustrate the applications of the methods.

Applications of Bayesian analysis to proof-of-concept trial planning and decision making.

Decision making is a critical component of a new drug development process. Based on results from an early clinical trial such as a proof of concept trial, the sponsor can decide whether to continue, stop, or defer the development of the drug. To simplify and harmonize the decision-making process, decision criteria have been proposed in the literature. One of them is to exam the location of a confidence bar relative to the target value and lower reference value of the treatment effect. In this research, we modify an existing approach by moving some of the "stop" decision to "consider" decision so that the chance of directly terminating the development of a potentially valuable drug can be reduced. As Bayesian analysis has certain flexibilities and can borrow historical information through an inferential prior, we apply the Bayesian analysis to the trial planning and decision making. Via a design prior, we can also calculate the probabilities of various decision outcomes in relationship with the sample size and the other parameters to help the study design. An example and a series of computations are used to illustrate the applications, assess the operating characteristics, and compare the performances of different approaches.

Penalty-based approaches to evaluating multiplicity adjustments in clinical trials: Advanced multiplicity problems.

Given the importance of addressing multiplicity issues in confirmatory clinical trials, several recent publications focused on the general goal of identifying most appropriate methods for multiplicity adjustment in each individual setting. This goal can be accomplished using the Clinical Scenario Evaluation approach. This approach encourages trial sponsors to perform comprehensive assessments of applicable analysis strategies such as multiplicity adjustments under all plausible sets of statistical assumptions using relevant evaluation criteria. This two-part paper applies a novel class of criteria, known as criteria based on multiplicity penalties, to the problem of evaluating the performance of several candidate multiplicity adjustments. The ultimate goal of this evaluation is to identify efficient and robust adjustments for each individual trial and optimally select parameters of these adjustments. Part II focuses on advanced settings with several sources of multiplicity, for example, clinical trials with several endpoints evaluated at two or more doses of an experimental treatment. A case study is given to illustrate a penalty-based approach to evaluating candidate multiple testing procedures in advanced multiplicity problems.

Penalty-based approaches to evaluating multiplicity adjustments in clinical trials: Traditional multiplicity problems.

Given the importance of addressing multiplicity issues in confirmatory clinical trials, several recent publications focused on the general goal of identifying most appropriate methods for multiplicity adjustment in each individual setting. This goal can be accomplished using the Clinical Scenario Evaluation approach. This approach encourages trial sponsors to perform comprehensive assessments of applicable analysis strategies such as multiplicity adjustments under all plausible sets of statistical assumptions using relevant evaluation criteria. This two-part paper applies a novel class of criteria, known as criteria based on multiplicity penalties, to the problem of evaluating the performance of several candidate multiplicity adjustments. The ultimate goal of this evaluation is to identify efficient and robust adjustments for each individual trial and optimally select parameters of these adjustments. Part I deals with traditional problems with a single source of multiplicity. Two case studies based on recently conducted Phase III trials are used to illustrate penalty-based approaches to evaluating candidate multiple testing methods and constructing optimization algorithms.

Implementation of adaptive methods in early-phase clinical trials.

There has been constant development of novel statistical methods in the design of early-phase clinical trials since the introduction of model-based designs, yet the traditional or modified 3+3 algorithmic design remains the most widely used approach in dose-finding studies. Research has shown the limitations of this traditional design compared with more innovative approaches yet the use of these model-based designs remains infrequent. This can be attributed to several causes including a poor understanding from clinicians and reviewers into how the designs work, and how best to evaluate the appropriateness of a proposed design. These barriers are likely to be enhanced in the coming years as the recent paradigm of drug development involves a shift to more complex dose-finding problems. This article reviews relevant information that should be included in clinical trial protocols to aid in the acceptance and approval of novel methods. We provide practical guidance for implementing these efficient designs with the aim of augmenting a broader transition from algorithmic to adaptive model-guided designs. In addition we highlight issues to consider in the actual implementation of a trial once approval is obtained. Copyright © 2016 John Wiley & Sons, Ltd.

Tradeoff-based optimization criteria in clinical trials with multiple objectives and adaptive designs.

The article discusses clinical trial optimization problems in the context of mid- to late-stage drug development. Using the Clinical Scenario Evaluation approach, main objectives of clinical trial optimization are formulated, including selection of clinically relevant optimization criteria, identification of sets of optimal and nearly optimal values of the parameters of interest, and sensitivity assessments. The paper focuses on a class of optimization criteria arising in clinical trials with several competing goals, termed tradeoff-based optimization criteria, and discusses key considerations in constructing and applying tradeoff-based criteria. The clinical trial optimization framework considered in the paper is illustrated using two case studies based on a clinical trial with multiple objectives and a two-stage clinical trial which utilizes adaptive decision rules.

Use of Seamless Study Designs in Oncology Clinical Development- A Survey Conducted by IDSWG Oncology Sub-team.

Seamless study designs have the potential to accelerate clinical development. The use of innovative seamless designs has been increasing in the oncology area; however, while the concept of seamless designs becomes more popular and accepted, many challenges remain in both the design and conduct of these trials. This may be especially true when seamless designs are used in late phase development supporting regulatory decision-making. The Innovative Design Scientific Working Group (IDSWG) Oncology team conducted a survey to understand the current use of seamless study designs for registration purposes in oncology clinical development. The survey was designed to provide insights into the benefits and to identify the roadblocks. A total of 16 questions were included in the survey that was distributed using the ASA Biopharmaceutical Section and IDSWG email listings from August to September 2022. A total of 51 responses were received, with 39 (76%) respondents indicating that their organizations had seamless oncology studies in planning or implementation for registration purposes. Detailed survey results are presented in the manuscript. Overall, while seamless designs offer advantages in terms of timeline reduction and cost saving, they also present challenges related to additional complexity and the need for efficient surrogate clinical endpoints in oncology drug development.

Randomized Phase III Study of Amcenestrant Plus Palbociclib Versus Letrozole Plus Palbociclib in Estrogen Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer: Primary Results From AMEERA-5.

PURPOSE: AMEERA-5 investigated amcenestrant (oral selective estrogen receptor [ER] degrader) plus palbociclib versus letrozole plus palbociclib as first-line treatment for ER-positive/human epidermal growth factor receptor 2-negative (ER+/HER2-) advanced/metastatic breast cancer (aBC). MATERIALS AND METHODS: In AMEERA-5 (ClinicalTrials.gov identifier: NCT04478266), a double-blind, double-dummy, international phase III trial, adult pre-/post-menopausal women and men without previous systemic therapy for ER+/HER2- aBC were randomly assigned 1:1 to amcenestrant 200 mg once daily + standard palbociclib dosage (125 mg once daily, 21 days on/7 days off) or letrozole 2.5 mg once daily + standard palbociclib dosage, stratified by de novo metastatic disease, postmenopausal women, and visceral metastasis. The primary end point was progression-free survival (PFS), compared using a stratified log-rank test with one-sided type I error rate of 2.5%. Secondary end points included overall survival (key secondary), pharmacokinetics, and safety. RESULTS: Between October 14, 2020, and December 2, 2021, 1,068 patients were randomly assigned to amcenestrant + palbociclib (N = 534) or letrozole + palbociclib (N = 534). At the interim analysis (median follow-up 8.4 months), the stratified hazard ratio for PFS was 1.209 (95% CI, 0.939 to 1.557; one-sided P value = .9304); therefore, the study was stopped for futility. The 6-month PFS rate was 82.7% (95% CI, 79.0 to 85.8) with amcenestrant + palbociclib versus 86.9% (95% CI, 83.5 to 89.6) with letrozole + palbociclib. In the amcenestrant + palbociclib versus letrozole + palbociclib groups, treatment-emergent adverse events (any grade) occurred in 85.6% versus 85.4% of patients and grade ≥3 events in 46.3% versus 60.8%, respectively. CONCLUSION: The AMEERA-5 study was discontinued on the basis of the recommendation of the data monitoring committee at the interim futility analysis. No new safety signals were identified.

AMEERA-3: Randomized Phase II Study of Amcenestrant (Oral Selective Estrogen Receptor Degrader) Versus Standard Endocrine Monotherapy in Estrogen Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer.

PURPOSE: Amcenestrant (oral selective estrogen receptor degrader) demonstrated promising safety and efficacy in earlier clinical studies for endocrine-resistant, estrogen receptor-positive/human epidermal growth factor receptor 2-negative (ER+/HER2-) advanced breast cancer (aBC). PATIENTS AND METHODS: In AMEERA-3 (ClinicalTrials.gov identifier: NCT04059484), an open-label, worldwide phase II trial, patients with ER+/HER2- aBC who progressed in the (neo)adjuvant or advanced settings after not more than two previous lines of endocrine therapy (ET) were randomly assigned 1:1 to amcenestrant or single-agent endocrine treatment of physician's choice (TPC), stratified by the presence/absence of visceral metastases, previous/no treatment with cyclin-dependent kinase 4/6 inhibitor, and Eastern Cooperative Oncology Group performance status (0/1). The primary end point was progression-free survival (PFS) by independent central review, compared using a stratified log-rank test (one-sided type I error rate of 2.5%). RESULTS: Between October 22, 2019, and February 15, 2021, 290 patients were randomly assigned to amcenestrant (n = 143) or TPC (n = 147). PFS was numerically similar between amcenestrant and TPC (median PFS [mPFS], 3.6 v 3.7 months; stratified hazard ratio [HR], 1.051 [95% CI, 0.789 to 1.4]; one-sided P = .643). Among patients with baseline mutated ESR1; (n = 120 of 280), amcenestrant numerically prolonged PFS versus TPC (mPFS, 3.7 v 2.0 months; stratified HR, 0.9 [95% CI, 0.565 to 1.435]). Overall survival data were immature but numerically similar between groups (HR, 0.913; 95% CI, 0.595 to 1.403). In amcenestrant versus TPC groups, treatment-emergent adverse events (any grade) occurred in 82.5% versus 76.2% of patients and grade ≥3 events occurred in 21.7% versus 15.6%. CONCLUSION: AMEERA-3 did not meet its primary objective of improved PFS with amcenestrant versus TPC although a numerical improvement in PFS was observed in patients with baseline ESR1 mutation. Efficacy and safety with amcenestrant were consistent with the standard of care for second-/third-line ET for ER+/HER2- aBC.

Adjuvant endocrine therapy uptake, toxicity, quality of life, and prediction of early discontinuation.

BACKGROUND: Many patients receiving adjuvant endocrine therapy (ET) for breast cancer experience side effects and reduced quality of life (QoL) and discontinue ET. We sought to describe these issues and develop a prediction model of early discontinuation of ET. METHODS: Among patients with hormone receptor-positive and HER2-negative stage I-III breast cancer of the Cancer Toxicities cohort (NCT01993498) who were prescribed adjuvant ET between 2012 and 2017, upon stratification by menopausal status, we evaluated adjuvant ET patterns including treatment change and patient-reported discontinuation and ET-associated toxicities and impact on QoL. Independent variables included clinical and demographic features, toxicities, and patient-reported outcomes. A machine-learning model to predict time to early discontinuation was trained and evaluated on a held-out validation set. RESULTS: Patient-reported discontinuation rate of the first prescribed ET at 4 years was 30% and 35% in 4122 postmenopausal and 2087 premenopausal patients, respectively. Switching to a new ET was associated with higher symptom burden, poorer QoL, and higher discontinuation rate. Early discontinuation rate of adjuvant ET before treatment completion was 13% in postmenopausal and 15% in premenopausal patients. The early discontinuation model obtained a C index of 0.62 in the held-out validation set. Many aspects of QoL, most importantly fatigue and insomnia (European Organization for Research and Treatment of Cancer QoL questionnaire 30), were associated with early discontinuation. CONCLUSION: Tolerability and adherence to ET remains a challenge for patients who switch to a second ET. An early discontinuation model using patient-reported outcomes identifies patients likely to discontinue their adjuvant ET. Improved management of toxicities and novel more tolerable adjuvant ETs are needed for maintaining patients on treatment.

AMEERA-1 phase 1/2 study of amcenestrant, SAR439859, in postmenopausal women with ER-positive/HER2-negative advanced breast cancer.

AMEERA-1 is a Phase 1/2 open-label single-arm study evaluating once-daily (QD) amcenestrant, an orally bioavailable selective estrogen receptor (ER) degrader, in postmenopausal women with ER+/HER2- advanced breast cancer (NCT03284957), who were mostly heavily pretreated (including targeted therapies and fulvestrant). In the dose escalation phase (Part A: n = 16), patients received amcenestrant 20-600 mg QD. Based on absence of dose-limiting toxicities, paired functional 18F-fluoroestradiol positron emission tomography, and pharmacokinetics, 400 mg QD was selected as recommended Phase 2 dose (RP2D) for the dose expansion phase (Part B: n = 49). No Grade ≥3 treatment-related adverse events or clinically significant cardiac/eye toxicities were reported. The Part B primary endpoint, confirmed objective response rate (ORR) was 3/45 at the interim analysis and 5/46 (10.9%) at the final analysis. The overall clinical benefit rate (CBR) was 13/46 (28.3%). CBRs among patients with baseline wild-type and mutated ESR1 were 9/26 (34.6%) and 4/19 (21.1%), respectively. Paired tumor biopsy and cell-free DNA analyses revealed ER inhibition and degradation, and a reduction in detectable ESR1 mutations, including Y537S. In conclusion, amcenestrant at RP2D of 400 mg QD for monotherapy is well-tolerated with no dose-limiting toxicities, and demonstrates preliminary antitumor activity irrespective of baseline ESR1 mutation status.

Development of gatekeeping strategies in confirmatory clinical trials.

This paper discusses multiplicity issues arising in confirmatory clinical trials with hierarchically ordered multiple objectives. In order to protect the overall type I error rate, multiple objectives are analyzed using multiple testing procedures. When the objectives are ordered and grouped in multiple families (e.g. families of primary and secondary endpoints), gatekeeping procedures are employed to account for this hierarchical structure. We discuss considerations arising in the process of building gatekeeping procedures, including proper use of relevant trial-specific information and criteria for selecting gatekeeping procedures. The methods and principles discussed in this paper are illustrated using a clinical trial in patients with type II diabetes mellitus.