Is local review of positron emission tomography scans sufficient in diffuse large B-cell lymphoma clinical trials? A CALGB 50303 analysis.

BACKGROUND: Quantitative methods of Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) interpretation, including the percent change in FDG uptake from baseline (ΔSUV), are under investigation in lymphoma to overcome challenges associated with visual scoring systems (VSS) such as the Deauville 5-point scale (5-PS). METHODS: In CALGB 50303, patients with DLBCL received frontline R-CHOP or DA-EPOCH-R, and although there were no significant associations between interim PET responses assessed centrally after cycle 2 (iPET) using 5-PS with progression-free survival (PFS) or overall survival (OS), there were significant associations between central determinations of iPET ∆SUV with PFS/OS. In this patient cohort, we retrospectively compared local vs central iPET readings and evaluated associations between local imaging data and survival outcomes. RESULTS: Agreement between local and central review was moderate (kappa = 0.53) for VSS and high (kappa = 0.81) for ∆SUV categories (<66% vs. ≥66%). ∆SUV ≥66% at iPET was significantly associated with PFS (p = 0.03) and OS (p = 0.002), but VSS was not. Associations with PFS/OS when applying local review vs central review were comparable. CONCLUSIONS: These data suggest that local PET interpretation for response determination may be acceptable in clinical trials. Our findings also highlight limitations of VSS and call for incorporation of more objective measures of response assessment in clinical trials.

Challenges to Using Big Data in Cancer.

Big data in healthcare can enable unprecedented understanding of diseases and their treatment, particularly in oncology. These data may include electronic health records, medical imaging, genomic sequencing, payor records, and data from pharmaceutical research, wearables, and medical devices. The ability to combine datasets and use data across many analyses is critical to the successful use of big data and is a concern for those who generate and use the data. Interoperability and data quality continue to be major challenges when working with different healthcare datasets. Mapping terminology across datasets, missing and incorrect data, and varying data structures make combining data an onerous and largely manual undertaking. Data privacy is another concern addressed by the Health Insurance Portability and Accountability Act, the Common Rule, and the General Data Protection Regulation. The use of big data is now included in the planning and activities of the FDA and the European Medicines Agency. The willingness of organizations to share data in a precompetitive fashion, agreements on data quality standards, and institution of universal and practical tenets on data privacy will be crucial to fully realizing the potential for big data in medicine.

Case Studies for Overcoming Challenges in Using Big Data in Cancer.

The analysis of big healthcare data has enormous potential as a tool for advancing oncology drug development and patient treatment, particularly in the context of precision medicine. However, there are challenges in organizing, sharing, integrating, and making these data readily accessible to the research community. This review presents five case studies illustrating various successful approaches to addressing such challenges. These efforts are CancerLinQ, the American Association for Cancer Research Project GENIE, Project Data Sphere, the National Cancer Institute Genomic Data Commons, and the Veterans Health Administration Clinical Data Initiative. Critical factors in the development of these systems include attention to the use of robust pipelines for data aggregation, common data models, data deidentification to enable multiple uses, integration of data collection into physician workflows, terminology standardization and attention to interoperability, extensive quality assurance and quality control activity, incorporation of multiple data types, and understanding how data resources can be best applied. By describing some of the emerging resources, we hope to inspire consideration of the secondary use of such data at the earliest possible step to ensure the proper sharing of data in order to generate insights that advance the understanding and the treatment of cancer.

Validation of ctDNA Quality Control Materials Through a Precompetitive Collaboration of the Foundation for the National Institutes of Health.

We report the results from a Foundation for the National Institutes of Health Biomarkers Consortium project to address the absence of well-validated quality control materials (QCMs) for circulating tumor DNA (ctDNA) testing. This absence is considered a cause of variance and inconsistencies in translating ctDNA results into clinical actions. METHODS: In this phase I study, QCMs with 14 clinically relevant mutations representing single nucleotide variants, insertions or deletions (indels), translocations, and copy number variants were sourced from three commercial manufacturers with variant allele frequencies (VAFs) of 5%, 2.5%, 1%, 0.1%, and 0%. Four laboratories tested samples in quadruplicate using two allele-specific droplet digital polymerase chain reaction and three (amplicon and hybrid capture) next-generation sequencing (NGS) panels. RESULTS: The two droplet digital polymerase chain reaction assays reported VAF values very close to the manufacturers' claimed concentrations for all QCMs. NGS assays reported most single nucleotide variants and indels, but not translocations, close to the expected VAF values. Notably, two NGS assays reported lower VAF than expected for all translocations in all QCM mixtures, possibly related to technical challenges detecting these variants. The ability to call ERBB2 copy number amplifications varied across assays. All three QCMs provided valuable insight into assay precision. Each assay across all variant types demonstrated dropouts at 0.1%, suggesting that the QCM can serve for testing of an assay's limit of detection with confidence claims for specific variants. CONCLUSION: These results support the utility of the QCM in testing ctDNA assay analytical performance. However, unique designs and manufacturing methods for the QCM, and variations in a laboratory's testing configuration, may require testing of multiple QCMs to find the best reagents for accurate result interpretation.

Minimal Residual Disease in Myeloma: Application for Clinical Care and New Drug Registration.

The development of novel agents has transformed the treatment paradigm for multiple myeloma, with minimal residual disease (MRD) negativity now achievable across the entire disease spectrum. Bone marrow-based technologies to assess MRD, including approaches using next-generation flow and next-generation sequencing, have provided real-time clinical tools for the sensitive detection and monitoring of MRD in patients with multiple myeloma. Complementary liquid biopsy-based assays are now quickly progressing with some, such as mass spectrometry methods, being very close to clinical use, while others utilizing nucleic acid-based technologies are still developing and will prove important to further our understanding of the biology of MRD. On the regulatory front, multiple retrospective individual patient and clinical trial level meta-analyses have already shown and will continue to assess the potential of MRD as a surrogate for patient outcome. Given all this progress, it is not surprising that a number of clinicians are now considering using MRD to inform real-world clinical care of patients across the spectrum from smoldering myeloma to relapsed refractory multiple myeloma, with each disease setting presenting key challenges and questions that will need to be addressed through clinical trials. The pace of advances in targeted and immune therapies in multiple myeloma is unprecedented, and novel MRD-driven biomarker strategies are essential to accelerate innovative clinical trials leading to regulatory approval of novel treatments and continued improvement in patient outcomes.

International liquid biopsy standardization alliance white paper.

The promise of precision medicine as a model to customize health care to the individual patient is heavily dependent upon new genetic tools to classify and characterize diseases and their hosts. Liquid biopsies serve as a safe alternative to solid biopsies and are thus a useful and critical component to fully realizing personalized medicine. The International Liquid Biopsy Standardization Alliance (ILSA) comprises organizations and foundations that recognize the importance of working towards the global use of liquid biopsy in oncology practice to support clinical decision making and regulatory considerations and seek to promote it in their communities. This manuscript provides an overview of the independent liquid biopsy- and standardization-based programs engaged with ILSA, their objectives and progress to date, and the tools and resources each is developing to contribute to the field. It also describes the unique areas of effort as well as synergy found within the group.

Enhanced Detection of Treatment Effects on Metastatic Colorectal Cancer with Volumetric CT Measurements for Tumor Burden Growth Rate Evaluation.

PURPOSE: Mathematical models combined with new imaging technologies could improve clinical oncology studies. To improve detection of therapeutic effect in patients with cancer, we assessed volumetric measurement of target lesions to estimate the rates of exponential tumor growth and regression as treatment is administered. EXPERIMENTAL DESIGN: Two completed phase III trials were studied (988 patients) of aflibercept or panitumumab added to standard chemotherapy for advanced colorectal cancer. Retrospectively, radiologists performed semiautomated measurements of all metastatic lesions on CT images. Using exponential growth modeling, tumor regression (d) and growth (g) rates were estimated for each patient's unidimensional and volumetric measurements. RESULTS: Exponential growth modeling of volumetric measurements detected different empiric mechanisms of effect for each drug: panitumumab marginally augmented the decay rate [tumor half-life; d [IQR]: 36.5 days (56.3, 29.0)] of chemotherapy [d: 44.5 days (67.2, 32.1), two-sided Wilcoxon P = 0.016], whereas aflibercept more significantly slowed the growth rate [doubling time; g = 300.8 days (154.0, 572.3)] compared with chemotherapy alone [g = 155.9 days (82.2, 347.0), P ≤ 0.0001]. An association of g with overall survival (OS) was observed. Simulating clinical trials using volumetric or unidimensional tumor measurements, fewer patients were required to detect a treatment effect using a volumetric measurement-based strategy (32-60 patients) than for unidimensional measurement-based strategies (124-184 patients). CONCLUSIONS: Combined tumor volume measurement and estimation of tumor regression and growth rate has potential to enhance assessment of treatment effects in clinical studies of colorectal cancer that would not be achieved with conventional, RECIST-based unidimensional measurements.

Prognostic value of interim FDG-PET in diffuse large cell lymphoma: results from the CALGB 50303 Clinical Trial.

As part of a randomized, prospective clinical trial in large cell lymphoma, we conducted serial fluorodeoxyglucose positron emission tomography (FDG-PET) at baseline, after 2 cycles of chemotherapy (interim PET [i-PET]), and at end of treatment (EoT) to identify biomarkers of response that are predictive of remission and survival. Scans were interpreted in a core laboratory by 2 imaging experts, using the visual Deauville 5-point scale (5-PS), and by calculating percent change in FDG uptake (change in standardized uptake value [ΔSUV]). Visual scores of 1 through 3 and ΔSUV ≥66% were prospectively defined as negative. Of 524 patients enrolled in the parent trial, 169 agreed to enroll in the PET substudy and 158 were eligible for final analysis. In this selected population, all had FDG-avid disease at baseline; by 5-PS, 55 (35%) remained positive on i-PET and 28 (18%) on EoT PET. Median ΔSUV on i-PET was 86.2%. With a median follow-up of 5 years, ΔSUV, as continuous variable, was associated with progression-free survival (PFS) (hazard ratio [HR] = 0.99; 95% confidence interval [CI], 0.97-1.00; P = .02) and overall survival (OS) (HR, 0.98; 95% CI, 0.97-0.99; P = .03). ΔSUV ≥66% was predictive of OS (HR, 0.31; 95% CI, 0.11-0.85; P = .02) but not PFS (HR, 0.47; 95% CI, 0.19-1.13; P = .09). Visual 5-PS on i-PET did not predict outcome. ΔSUV, but not visual analysis, on i-PET predicted OS in DLBCL, although the low number of events limited the statistical analysis. These data may help guide future clinical trials using PET response-adapted therapy. This trial was registered at www.clinicaltrials.gov as #NCT00118209.

Opportunities and Challenges in Implementation of Multiparameter Single Cell Analysis Platforms for Clinical Translation.

The high-content interrogation of single cells with platforms optimized for the multiparameter characterization of cells in liquid and solid biopsy samples can enable characterization of heterogeneous populations of cells ex vivo. Doing so will advance the diagnosis, prognosis, and treatment of cancer and other diseases. However, it is important to understand the unique issues in resolving heterogeneity and variability at the single cell level before navigating the validation and regulatory requirements in order for these technologies to impact patient care. Since 2013, leading experts representing industry, academia, and government have been brought together as part of the Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium to foster the potential of high-content data integration for clinical translation.

A QA Program for MRD Testing Demonstrates That Systematic Education Can Reduce Discordance Among Experienced Interpreters.

BACKGROUND: Minimal residual disease (MRD) in B lymphoblastic leukemia (B-ALL) by flow cytometry is an established prognostic factor used to adjust treatment in most pediatric therapeutic protocols. MRD in B-ALL has been standardized by the Children's Oncology Group (COG) in North America, but not routine clinical labs. The Foundation for National Institutes of Health sought to harmonize MRD measurement among COG, oncology groups, academic, community and government, laboratories. METHODS: Listmode data from post-induction marrows were distributed from a reference lab to seven different clinical FCM labs with variable experience in B-ALL MRD. Labs were provided with the COG protocol. Files from 15 cases were distributed to the seven labs. Educational sessions were implemented, and 10 more listmode file cases analyzed. RESULTS: Among 105 initial challenges, the overall discordance rate was 26%. In the final round, performance improved considerably; out of 70 challenges, there were five false positives and one false negative (9% discordance), and no quantitative discordance. Four of six deviations occurred in a single lab. Three samples with hematogones were still misclassified as MRD. CONCLUSIONS: Despite the provision of the COG standardized analysis protocol, even experienced laboratories require an educational component for B-ALL MRD analysis by FCM. Recognition of hematogones remains challenging for some labs when using the COG protocol. The results from this study suggest that dissemination of MRD testing to other North American laboratories as part of routine clinical management of B-ALL is possible but requires additional educational components to complement standardized methodology. © 2017 International Clinical Cytometry Society.

Vol-PACT: A Foundation for the NIH Public-Private Partnership That Supports Sharing of Clinical Trial Data for the Development of Improved Imaging Biomarkers in Oncology.

PURPOSE: To develop a public-private partnership to study the feasibility of a new approach in collecting and analyzing clinically annotated imaging data from landmark phase III trials in advanced solid tumors. PATIENTS AND METHODS: The collection of clinical trials fulfilled the following inclusion criteria: completed randomized trials of > 300 patients, highly measurable solid tumors (non-small-cell lung cancer, colorectal cancer, renal cell cancer, and melanoma), and required sponsor and institutional review board sign-offs. The new approach in analyzing computed tomography scans was to transfer to an academic image analysis laboratory, draw contours semi-automatically by using in-house-developed algorithms integrated into the open source imaging platform Weasis, and perform serial volumetric measurement. RESULTS: The median duration of contracting with five sponsors was 12 months. Ten trials in 7,085 patients that covered 12 treatment regimens across 20 trial arms were collected. To date, four trials in 3,954 patients were analyzed. Source imaging data were transferred to the academic core from 97% of trial patients (n = 3,837). Tumor imaging measurements were extracted from 82% of transferred computed tomography scans (n = 3,162). Causes of extraction failure were nonmeasurable disease (n = 392), single imaging time point (n = 224), and secondary captured images (n = 59). Overall, clinically annotated imaging data were extracted in 79% of patients (n = 3,055), and the primary trial end point analysis in each trial remained representative of each original trial end point. CONCLUSION: The sharing and analysis of source imaging data from large randomized trials is feasible and offer a rich and reusable, but largely untapped, resource for future research on novel trial-level response and progression imaging metrics.

What evidence do we need for biomarker qualification?

Biomarkers can facilitate all aspects of the drug development process. However, biomarker qualification-the use of a biomarker that is accepted by the U.S. Food and Drug Administration-needs a clear, predictable process. We describe a multistakeholder effort including government, industry, and academia that proposes a framework for defining the amount of evidence needed for biomarker qualification. This framework is intended for broad applications across multiple biomarker categories and uses.

Association of Minimal Residual Disease With Clinical Outcome in Pediatric and Adult Acute Lymphoblastic Leukemia: A Meta-analysis.

IMPORTANCE: Minimal residual disease (MRD) refers to the presence of disease in cases deemed to be in complete remission by conventional pathologic analysis. Assessing the association of MRD status following induction therapy in patients with acute lymphoblastic leukemia (ALL) with relapse and mortality may improve the efficiency of clinical trials and accelerate drug development. OBJECTIVE: To quantify the relationships between event-free survival (EFS) and overall survival (OS) with MRD status in pediatric and adult ALL using publications of clinical trials and other databases. DATA SOURCES: Clinical studies in ALL identified via searches of PubMed, MEDLINE, and clinicaltrials.gov. STUDY SELECTION: Our search and study screening process adhered to the PRISMA Guidelines. Studies that addressed EFS or OS by MRD status in patients with ALL were included; reviews, abstracts, and studies with fewer than 30 patients or insufficient MRD description were excluded. DATA EXTRACTION AND SYNTHESIS: Study sample size, patient age, follow-up time, timing of MRD assessment (postinduction or consolidation), MRD detection method, phenotype/genotype (B cell, T cell, Philadelphia chromosome), and EFS and OS. Searches of PubMed and MEDLINE identified 566 articles. A parallel search on clinicaltrials.gov found 67 closed trials and 62 open trials as of 2014. Merging results of 2 independent searches and applying exclusions gave 39 publications in 3 arms of patient populations (adult, pediatric, and mixed). We performed separate meta-analyses for each of these 3 subpopulations. RESULTS: The 39 publications comprised 13 637 patients: 16 adult studies (2076 patients), 20 pediatric (11 249 patients), and 3 mixed (312 patients). The EFS hazard ratio (HR) for achieving MRD negativity is 0.23 (95% Bayesian credible interval [BCI] 0.18-0.28) for pediatric patients and 0.28 (95% BCI, 0.24-0.33) for adults. The respective HRs in OS are 0.28 (95% BCI, 0.19-0.41) and 0.28 (95% BCI, 0.20-0.39). The effect was similar across all subgroups and covariates. CONCLUSIONS AND RELEVANCE: The value of having achieved MRD negativity is substantial in both pediatric and adult patients with ALL. These results are consistent across therapies, methods of and times of MRD assessment, cutoff levels, and disease subtypes. Minimal residual disease status warrants consideration as an early measure of disease response for evaluating new therapies, improving the efficiency of clinical trials, accelerating drug development, and for regulatory approval. A caveat is that an accelerated approval of a particular new drug using an intermediate end point, such as MRD, would require confirmation using traditional efficacy end points.

The Role of Minimal Residual Disease Testing in Myeloma Treatment Selection and Drug Development: Current Value and Future Applications.

Treatment of myeloma has benefited from the introduction of more effective and better tolerated agents, improvements in supportive care, better understanding of disease biology, revision of diagnostic criteria, and new sensitive and specific tools for disease prognostication and management. Assessment of minimal residual disease (MRD) in response to therapy is one of these tools, as longer progression-free survival (PFS) is seen consistently among patients who have achieved MRD negativity. Current therapies lead to unprecedented frequency and depth of response, and next-generation flow and sequencing methods to measure MRD in bone marrow are in use and being developed with sensitivities in the range of 10-5 to 10-6 cells. These technologies may be combined with functional imaging to detect MRD outside of bone marrow. Moreover, immune profiling methods are being developed to better understand the immune environment in myeloma and response to immunomodulatory agents while methods for molecular profiling of myeloma cells and circulating DNA in blood are also emerging. With the continued development and standardization of these methodologies, MRD has high potential for use in gaining new drug approvals in myeloma. The FDA has outlined two pathways by which MRD could be qualified as a surrogate endpoint for clinical studies directed at obtaining accelerated approval for new myeloma drugs. Most importantly, better understanding of MRD should also contribute to better treatment monitoring. Potentially, MRD status could be used as a prognostic factor for making treatment decisions and for informing timing of therapeutic interventions. Clin Cancer Res; 23(15); 3980-93. ©2017 AACR.

Biomarker development in the context of urologic cancers.

BACKGROUND: The Food and Drug Administration (FDA) has called for the use of analytically validated biomarkers that have strong evidence of being fit for purpose to identify patients likely to respond and to evaluate the patient response to a therapy, potential toxicity, and drug resistance. This article discusses development and application of these biomarkers in the context of urologic cancers-specifically in cancers of the prostate and urinary bladder. METHODS: The FDA has defined four specific categories for contexts of biomarker use: prognostic, predictive, response-indicator, and efficacy-response (surrogate endpoints). Prognostic and predictive biomarkers include pretreatment characteristics of the patient and the tumor. Response-indicator and efficacy response biomarkers occur after treatment and show the effects of treatment on biomarkers. Efficacy response biomarkers show changes associated with clinical benefit and can be surrogates for clinical endpoints leading to drug approvals. RESULTS: Well-structured development plans are required to satisfy rigorous criteria that must be met to qualify biomarkers for specific contexts of use in drug development and patient management. A description of the extensive effort applied to the validation and qualification of circulating tumor cells in castration resistant prostate cancer is described as an example of the potential utility of biomarkers in urological cancers. CONCLUSIONS: Many potential biomarkers have been identified in prostate and urinary bladder cancers, but few have sufficient demonstration of analytical and clinical validity to meet FDA standards for use in clinical settings. Circulating tumor cell (CTC) assays are particularly promising candidates for informative new biomarkers to measure disease before and after treatment. New technologies are providing opportunities for high definition, more informative analysis. Statistical and computational methodologies to describe assay results are also rapidly evolving. These advances will lead to better diagnosis, earlier indications of treatment response and failure, and better definition of patient cohorts that will respond to a specific treatment.

Lung Master Protocol (Lung-MAP)-A Biomarker-Driven Protocol for Accelerating Development of Therapies for Squamous Cell Lung Cancer: SWOG S1400.

The Lung Master Protocol (Lung-MAP, S1400) is a groundbreaking clinical trial designed to advance the efficient development of targeted therapies for squamous cell carcinoma (SCC) of the lung. There are no approved targeted therapies specific to advanced lung SCC, although The Cancer Genome Atlas project and similar studies have detected a significant number of somatic gene mutations/amplifications in lung SCC, some of which are targetable by investigational agents. However, the frequency of these changes is low (5%-20%), making recruitment and study conduct challenging in the traditional clinical trial setting. Here, we describe our approach to development of a biomarker-driven phase II/II multisubstudy "Master Protocol," using a common platform (next-generation DNA sequencing) to identify actionable molecular abnormalities, followed by randomization to the relevant targeted therapy versus standard of care.

The Quantitative Imaging Network: NCI's Historical Perspective and Planned Goals.

The purpose of this editorial is to provide a brief history of National Institutes of Health National Cancer Institute (NCI) workshops as related to quantitative imaging within the oncology setting. The editorial will then focus on the recently supported NCI initiatives, including the Quantitative Imaging Network (QIN) initiative and its organizational structure, including planned research goals and deliverables. The publications in this issue of Translational Oncology come from many of the current members of this QIN research network.

Mitigating the risk of radiation-induced cancers: limitations and paradigms in drug development.

The United States radiation medical countermeasures (MCM) programme for radiological and nuclear incidents has been focusing on developing mitigators for the acute radiation syndrome (ARS) and delayed effects of acute radiation exposure (DEARE), and biodosimetry technologies to provide radiation dose assessments for guiding treatment. Because a nuclear accident or terrorist incident could potentially expose a large number of people to low to moderate doses of ionising radiation, and thus increase their excess lifetime cancer risk, there is an interest in developing mitigators for this purpose. This article discusses the current status, issues, and challenges regarding development of mitigators against radiation-induced cancers. The challenges of developing mitigators for ARS include: the long latency between exposure and cancer manifestation, limitations of animal models, potential side effects of the mitigator itself, potential need for long-term use, the complexity of human trials to demonstrate effectiveness, and statistical power constraints for measuring health risks (and reduction of health risks after mitigation) following relatively low radiation doses (<0.75 Gy). Nevertheless, progress in the understanding of the molecular mechanisms resulting in radiation injury, along with parallel progress in dose assessment technologies, make this an opportune, if not critical, time to invest in research strategies that result in the development of agents to lower the risk of radiation-induced cancers for populations that survive a significant radiation exposure incident.

Evidence of clinical utility: an unmet need in molecular diagnostics for patients with cancer.

This article defines and describes best practices for the academic and business community to generate evidence of clinical utility for cancer molecular diagnostic assays. Beyond analytical and clinical validation, successful demonstration of clinical utility involves developing sufficient evidence to demonstrate that a diagnostic test results in an improvement in patient outcomes. This discussion is complementary to theoretical frameworks described in previously published guidance and literature reports by the U.S. Food and Drug Administration, Centers for Disease Control and Prevention, Institute of Medicine, and Center for Medical Technology Policy, among others. These reports are comprehensive and specifically clarify appropriate clinical use, adoption, and payer reimbursement for assay manufacturers, as well as Clinical Laboratory Improvement Amendments-certified laboratories, including those that develop assays (laboratory developed tests). Practical criteria and steps for establishing clinical utility are crucial to subsequent decisions for reimbursement without which high-performing molecular diagnostics will have limited availability to patients with cancer and fail to translate scientific advances into high-quality and cost-effective cancer care. See all articles in this CCR Focus section, "The Precision Medicine Conundrum: Approaches to Companion Diagnostic Co-development."