Design and Conduct of Early Clinical Studies of Immunotherapy: Recommendations from the Task Force on Methodology for the Development of Innovative Cancer Therapies 2019 (MDICT)

A conceptual framework for cautious escalation of anticancer treatment: How to optimize overall benefit and obviate the need for de-escalation trials

BACKGROUND

The developmental workflow of the currently performed phase 1, 2 and 3 cancer trial stages lacks essential information required for the determination of the optimal efficacy threshold of new anticancer regimens. Due to this there is a serious risk of overdosing and/or treating for an unnecessary long time, leading to excess toxicity and a higher financial burden for society. But often post-approval de-escalation trials for dose-optimization and treatment de-intensification are not performed due to failing resources and time. Therefore, the developmental workflow needs to be restructured toward cautious systemic cancer treatment escalation, in order to guarantee optimal efficacy and sustainability.

METHODS

In this manuscript we discuss opportunities to produce the information needed for cautious escalation, based on models of cancer growth and cancer kill kinetics as well as exploratory biomarkers, for the purpose of designing the optimal phase 3 superiority trial. Subsequently, we compare the sample size needed for a phase 3 superiority trial, followed by a necessary de-escalation trial with the sample size needed for a multi-arm phase 3 trial with intervention arms of differing intensity. All essential items are structured within a Framework for Cautious Escalation (FCE). The discussion uses illustrations from the breast cancer setting, but aims to be applicable for all cancers.

RESULTS

The FCE is a promising model of clinical development in oncology to prevent overtreatment and associated issues, especially with regard to the number of repetitive treatment cycles. It will hopefully increase the relevance and success rate of clinical trials, to deliver improved patient-centric outcomes.

Trial Design for Cancer Immunotherapy: A Methodological Toolkit

Immunotherapy with checkpoint inhibitors (CPIs) and cell-based products has revolutionized the treatment of various solid tumors and hematologic malignancies. These agents have shown unprecedented response rates and long-term benefits in various settings. These clinical advances have also pointed to the need for new or adapted approaches to trial design and assessment of efficacy and safety, both in the early and late phases of drug development. Some of the conventional statistical methods and endpoints used in other areas of oncology appear to be less appropriate in immuno-oncology. Conversely, other methods and endpoints have emerged as alternatives. In this article, we discuss issues related to trial design in the early and late phases of drug development in immuno-oncology, with a focus on CPIs. For early trials, we review the most salient issues related to dose escalation, use and limitations of tumor response and progression criteria for immunotherapy, the role of duration of response as an endpoint in and of itself, and the need to conduct randomized trials as early as possible in the development of new therapies. For late phases, we discuss the choice of primary endpoints for randomized trials, review the current status of surrogate endpoints, and discuss specific statistical issues related to immunotherapy, including non-proportional hazards in the assessment of time-to-event endpoints, alternatives to the Cox model in these settings, and the method of generalized pairwise comparisons, which can provide a patient-centric assessment of clinical benefit and be used to design randomized trials.

Oncology phase I trial design and conduct: time for a change - MDICT Guidelines 2022

In 2021, the Food and Drug Administration Oncology Center of Excellence announced Project Optimus focusing on dose optimization for oncology drugs. The Methodology for the Development of Innovative Cancer Therapies (MDICT) Taskforce met to review and discuss the optimization of dosage for oncology trials and to develop a practical guide for oncology phase I trials. Defining a single recommended phase II dose based on toxicity may define doses that are neither the most effective nor the best tolerated. MDICT recommendations address the need for robust non-clinical data which are needed to inform trial design, as well as an expert team including statisticians and pharmacologists. The protocol must be flexible and adaptive, with clear definition of all endpoints. Health authorities should be consulted early and regularly. Strategies such as randomization, intrapatient dose escalation, and real-world eligibility criteria are encouraged whereas serial tumor sampling is discouraged in the absence of a strong rationale and appropriately validated assay. Endpoints should include consideration of all longitudinal toxicity. The phase I dose escalation trial should define the recommended dose range for later testing in randomized phase II trials, rather than a single recommended phase II dose, and consider scenarios where different populations may require different dosages. The adoption of these recommendations will improve dosage selection in early clinical trials of new anticancer treatments and ultimately, outcomes for patients.

A systematic review of phase II trials exploring anti-PD-1/PD-L1 combinations in patients with solid tumors

BACKGROUND

A high number of combinations of PD-1/PD-L1 inhibitors with other anti-cancer therapies are in clinical development. The usefulness of phase II trials in evaluating their efficacy and safety is unclear.

MATERIALS AND METHODS

We performed a systematic search on PubMed and Cochrane Library for phase II trials of PD-1/PD-L1 inhibitors in combination with other anti-cancer therapies (systemic therapy and/or radiotherapy) published between January 1st 2018 and December 31st 2020. Study design, primary endpoint and main outcomes were registered for each paper.

RESULTS

119 articles reporting on 65 regimens were included in our analysis. Backbone agents were more frequently PD-1 inhibitors (pembrolizumab = 47, nivolumab = 41, camrelizumab = 3) followed by anti-PD-L1 (durvalumab = 19, atezolizumab = 6, avelumab = 3). Therapeutic partners were other immunotherapeutic agents (n = 46), targeted therapies (n = 40), chemotherapy (n = 22) or radiotherapy (n = 11). The majority of articles reported on single-arm trials (n = 87, 73%) and response rate was the most frequent primary endpoint (n = 69, 58%). Objective responses, registered in 109 (92%) articles, ranged between 0% and 91%. The incidence of grade 3 or higher treatment-related adverse events, clearly reported in 97 (82%) articles, spanned from 0 to 100%. Five combinations received regulatory approval by Food and Drug Administration or European Medicine Agency for 9 different indications, based on the results of a phase II trial (n = 3) or on a confirmatory phase III trial (n = 6).

CONCLUSIONS

The landscape of phase II trials evaluating PD-1/PD-L1 inhibitors with other anticancer therapies is heterogeneous. Combinations of two immunotherapeutic agents have been the most investigated. Only a minority of indications (8%) granted regulatory approval.

Comparison of Various Phase I Combination Therapy Designs in Oncology for Evaluation of Early Tumor Shrinkage Using Simulations

There is still a lack of efficient designs for identifying the dose response in oncology combination therapies in early clinical trials. The concentration response relationship can be identified using the early tumor shrinkage time course, which has been shown to be a good early response marker of clinical efficacy. The performance of various designs using an exposure–tumor growth inhibition model was explored using simulations. Different combination effects of new drug M and cetuximab (reference therapy) were explored first assuming no effect of M on cetuximab (to investigate the type I error (α)), and subsequently assuming additivity or synergy between cetuximab and M. One‐arm, two‐arm, and four‐arm designs were evaluated. In the one‐arm design, 60 patients received cetuximab + M. In the two‐arm design, 30 patients received cetuximab and 30 received cetuximab + M. In the four‐arm design, in addition to cetuximab and cetuximab + M as standard doses, combination arms with lower doses of cetuximab were evaluated (15 patients/arm). Model‐based predictions or “simulated observations” of early tumor shrinkage at week 8 (ETS8) were compared between the different arms. With the same number of individuals, the one‐arm design showed better statistical power than other designs but led to strong inflation of α in case of misestimated reference for ETS8 value. The two‐arm design protected against this misestimation and, with the same total number of subjects, would provide higher statistical power than a four‐arm design. However, a four‐arm design would be helpful for exploring more doses of cetuximab in combination with M to better understand the interaction.