The search for surrogate endpoints for immunotherapy trials

How Does Target Lesion Selection Affect RECIST? A Computer Simulation Study

OBJECTIVES

Response Evaluation Criteria in Solid Tumors (RECIST) is grounded on the assumption that target lesion selection is objective and representative of the change in total tumor burden (TTB) during therapy. A computer simulation model was designed to challenge this assumption, focusing on a particular aspect of subjectivity: target lesion selection.

MATERIALS AND METHODS

Disagreement among readers and the disagreement between individual reader measurements and TTB were analyzed as a function of the total number of lesions, affected organs, and lesion growth.

RESULTS

Disagreement rises when the number of lesions increases, when lesions are concentrated on a few organs, and when lesion growth borders the thresholds of progressive disease and partial response. There is an intrinsic methodological error in the estimation of TTB via RECIST 1.1, which depends on the number of lesions and their distributions. For example, for a fixed number of lesions at 5 and 15, distributed over a maximum of 4 organs, the error rates are observed to be 7.8% and 17.3%, respectively.

CONCLUSIONS

Our results demonstrate that RECIST can deliver an accurate estimate of TTB in localized disease, but fails in cases of distal metastases and multiple organ involvement. This is worsened by the "selection of the largest lesions," which introduces a bias that makes it hardly possible to perform an accurate estimate of the TTB. Including more (if not all) lesions in the quantitative analysis of tumor burden is desirable.

Adapting Health Technology Assessment agency standards for surrogate outcomes in early stage cancer trials: what needs to happen?

INTRODUCTION

An avalanche of early stage cancer clinical trials is coming. The majority of these solely use surrogate outcomes that have not been validated against a target outcome of interest (e.g. overall survival). Current HTA guidance on surrogate outcome validation are not methodologically or practically conducive to this scenario.

AREAS COVERED

We provide a high-level overview of methods, approaches, and conceptual thinking for making better use of limited evidence within early stage cancer HTA submissions. We outline regulatory and HTA issues and emphasize how evidence transitions from one to another, what major gaps currently exist, and how these may be bridged. We summarize current methodologies and practices, their pros and cons. We outline how complementary measurements strengthen evaluations and address fallacies and biases of conventional statistical methods for surrogate outcomes validation. The value of real-world data to support some of the necessary validity components is discussed. Lastly, we address the importance of the patient voice for better understanding which surrogate outcomes may appropriately inform HTA.

EXPERT OPINION

Conventional surrogate outcome validation represents a fraught and sub-optimal framework for HTA purposes, particularly for early stage cancer. Tools for optimizing use of limited evidence exist. Education of stakeholders is highly needed.

Improving patient selection for immuno-oncology phase 1 trials: External validation of six prognostic scores in a French Cancer Center

We compared the performance of six prognostic scores (Royal Marsden Hospital, MDACC: MD Anderson Clinical Center and MDACC + NLR: neutrophil-to-lymphocyte ratio, MD Anderson - immune checkpoint inhibitors (MDA-ICI), GRIm: Gustave Roussy Immune Score and LIPI: Lung Immune Prognostic Index) in predicting overall survival (OS) in phase I trial patients treated with immune checkpoint inhibitors (ICI). Medical records of patients with advanced solid tumors enrolled in ICI phase I trials between 2015 and 2018 at Institut Universitaire du Cancer de Toulouse-Oncopole were reviewed. The performance of prognostic scores on OS was compared using different criteria. A total of 259 patients were included. Median age was 63 years (range: 18-83). Main primary cancers were melanoma (19%), head and neck (16%), lung (13%) and bladder (10%). With a median follow-up of 15 months (95% confidence interval [CI] = [11.6;17.5]), median OS was 12.5 months (95% CI = [10.3;16.0]). All scores were associated with OS. The MDACC, LIPI and GRIm scores performed better than the others. Concordance of risk group assignment between the scoring systems was poor. According to our results, the MDACC, GRIm and LIPI scores better suited to ICI phase I settings. Adequate scoring would allow better patient selection in early ICI trials, especially during the critical period of dose escalation, and in proof-of-concept expansion cohorts.

Characterizing Exposure-Response Relationship for Therapeutic Monoclonal Antibodies in Immuno-Oncology and Beyond: Challenges, Perspectives, and Prospects

Recent data from immuno-oncology clinical studies have shown the exposure-response (E-R) relationship for therapeutic monoclonal antibodies (mAbs) was often confounded by various factors due to the complex interplay of patient characteristics, disease, drug exposure, clearance, and treatment response and presented challenges in characterization and interpretation of E-R analysis. To tackle the challenges, exposure relationships for therapeutic mAbs in immuno-oncology and oncology are reviewed, and a general framework for an integrative understanding of E-R relationship is proposed. In this framework, baseline factors, drug exposure, and treatment response are envisioned to form an interconnected triangle, driving the E-R relationship and underlying three components that compose the apparent relationship: exposure-driven E-R, baseline-driven E-R, and response-driven E-R. Various strategies in data analysis and study design to decouple those components and mitigate the confounding effect are reviewed for their merits and limitations, and a potential roadmap for selection of these strategies is proposed. Specifically, exposure metrics based on a single-dose pharmacokinetic model can be used to mitigate response-driven E-R, while multivariable analysis and/or case control analysis of data obtained from multiple dose levels in a randomized study may be used to account for the baseline-driven E-R. In this context, the importance of collecting data from multiple dose levels, the role of prognostic factors and predictive factors, the potential utility of clearance at baseline and its change over time, and future directions are discussed.

Current challenges for assessing the long-term clinical benefit of cancer immunotherapy: a multi-stakeholder perspective

Immuno-oncologics (IOs) differ from chemotherapies as they prime the patient's immune system to attack the tumor, rather than directly destroying cancer cells. The IO mechanism of action leads to durable responses and prolonged survival in some patients. However, providing robust evidence of the long-term benefits of IOs at health technology assessment (HTA) submission presents several challenges for manufacturers. The aim of this article was to identify, analyze, categorize, and further explore the key challenges that regulators, HTA agencies, and payers commonly encounter when assessing the long-term benefits of IO therapies. Insights were obtained from an international, multi-stakeholder steering committee (SC) and expert panels comprising of payers, economists, and clinicians. The selected individuals were tasked with developing a summary of challenges specific to IOs in demonstrating their long-term benefits at HTA submission. The SC and expert panels agreed that standard methods used to assess the long-term benefit of anticancer drugs may have limitations for IO therapies. Three key areas of challenges were identified: (1) lack of a disease model that fully captures the mechanism of action and subsequent patient responses; (2) estimation of longer-term outcomes, including a lack of agreement on ideal methods of survival analyses and extrapolation of survival curves; and (3) data limitations at the time of HTA submission, for which surrogate survival end points and real-world evidence could prove useful. A summary of the key challenges facing manufacturers when submitting evidence at HTA submission was developed, along with further recommendations for manufacturers in what evidence to produce. Despite almost a decade of use, there remain significant challenges around how best to demonstrate the long-term benefit of checkpoint inhibitor-based IOs to HTA agencies, clinicians, and payers. Manufacturers can potentially meet or mitigate these challenges with a focus on strengthening survival analysis methodology. Approaches to doing this include identifying reliable biomarkers, intermediate and surrogate end points, and the use of real-world data to inform and validate long-term survival projections. Wider education across all stakeholders-manufacturers, payers, and clinicians-in considering the long-term survival benefit with IOs is also important.

Chemoradiation phase II trials: re-exploring a world of missed opportunities

Background: Phase II trials are designed to assess the efficacy/toxicity ratio of experimental treatments and select those worth being tested in phase III trials. Although crucial limitations were identified when concurrent chemoradiation (cCRT) phase III trials characteristics were assessed, features of cCRT phase II trials have never been reported. The objective was to describe features of all cCRT phase II trials. Methods and material: Requests were performed in the Medline database (via PubMed). The latest update was performed in April 2016, using the following MESH terms: 'clinical trials: phase II as topic', 'chemoradiotherapy'. Results: Four hundred and fifty-eight cCRT phase II trials were identified. They were mainly multicenter (51.5%), single arm studies (77.7%) published after 2011 (55.0%). The median number of included patients was 52. Primary endpoints were mainly response rate (20.5%), pathological complete response (14.4%) and overall survival (12.6%). The primary endpoint was not defined in 22% of studies. Tumors were mostly lung (23.1%), head and neck (20.3%), colorectal (16.6%) and esophagogastric cancer (14.6%) treated at a locally advanced setting (81.7%). 55.2% of trials used 3D-conformal radiotherapy and 9.1% intensity-modulated radiotherapy, mainly with normo-fractionation (82.0% of the 573 arms with radiotherapy). Radiation technique was not reported in 19.9% of studies. Associated anticancer drugs (563 arms) were mainly conventional chemotherapies (559 arms): cisplatin (46.2%) and 5-fluorouracil (28.3%). Non cytotoxic agents (targeted therapies, immunotherapies) were tested in 97 arms (17%). With a median follow-up of 31 months, acute grades 3-5 were reported in 98.5% of studies and late toxicities in 44.5%. Follow-up was not reported in 17% of studies. Conclusions: cCRT phase II trials featured severe limitations, with outdated radiation techniques, insufficient reporting of crucial data and a small number of included patients. This certainly limited the impact of conclusions and hindered the development of successful phase III trials.

The Statistical Evaluation of Treatment and Outcomes in Head and Neck Squamous Cell Carcinoma Clinical Trials

The purpose of this article is two-fold: to help statisticians confronted with the design, implementation and analysis of clinical trials and new to the field of head and neck cancer; but also to sensitize research physicians with the role, the tasks and the challenges faced by the medical statisticians. These two purposes altogether will hopefully encourage and enable fluid communication between the research physician and the medical statistician and the understanding of each other's field and concerns. In particular, the methodological challenges resulting from the heterogeneity of the head and neck cancer, the complexity of the treatments and the associated comorbidities are presented with examples borrowed from medical literature and from the practical experience of the authors in this field.