JCO Special Series Tackles Key Issues in Oncology Drug Development in an Era of Precision Medicine

Mar 08, 2023

By Geraldine Carroll, ASCO Publishing 
 
The Journal of Clinical Oncology published a special series, “Statistics in Oncology,” featuring perspectives from a wide range of renowned experts in drug development, including regulators, bioethicists, statisticians, clinician-scientists, and stakeholders in industry and beyond. The series addresses a range of issues across the drug development continuum and highlights recent drug approvals to illustrate how stakeholders can work together to increase the pace of drug development in oncology while maintaining ethical standards and scientific rigor in medical research.  
 
“Cancer treatments are rapidly changing, and, as drug development evolves, it is invaluable to have the reflections of renowned authors, many with decades of experience, to assess how the statistics community has addressed the landscape of drug development,” said guest editor Alexia Iasonos, PhD, of Memorial Sloan Kettering Cancer Center (MSK). 
 
The series of eight review articles tackles the challenges raised by new classes of therapies such as immunotherapy, targeted therapies, CAR T therapy, and treatment effects changing over time. Experts also address dose optimization in the phase I setting and the ethics of early-phase trials that file for U.S. Food and Drug Administration (FDA) accelerated approval or breakthrough therapy designation. 

FDA-Approved CAR T-Cell Products  

To date, the FDA has approved five autologous CAR T-cell products for seven indications. Unlike traditional oncology products, CAR T products are manufactured specifically for each patient, having implications in study design, statistical analyses, and interpretation of study results. Lin et al provide a statistical review of CAR T-cell products and share experiences and considerations for the design and statistical analyses of CAR T-cell clinical trials. Additionally, the authors describe how the newly adopted estimand framework for trials can help clarify issues in CAR T-cell trial design.  
 
Guest editor Sean Devlin, PhD, of MSK, said Lin et al’s article is an excellent resource for people working in CAR T therapies. “I work in CAR T and found the FDA’s perspective on all of the CAR T-cell approvals and the key design considerations incredibly insightful about what the current approval landscape looks like,” he said.  

Improving Dose Optimization Processes to Minimize Toxicity 

Dose optimization in cancer care is crucial to ensure that patients receive therapies which maximize efficacy while minimizing toxicity. Fourie Zirkelbach et al note a renewed focus in oncology drug development on a premarket dose optimization paradigm that selects the right dose(s) for patients before drug approval. The authors highlight major principles for dose optimization and share recent examples of FDA approvals to illustrate how investigation of dose- and exposure-response relationships and the use of randomized dose trials can support dose optimization to minimize toxicity and maximize benefit to patients. 

Balancing Risk and Efficiency in Drug Development for Rare Tumors 

How to balance risk and efficiency in drug development for rare and challenging tumors is a question addressed in the series by Mellinghoff and Cloughesy, with glioma cancers as an example. The authors review clinical trial designs during early drug development, such as window-of-opportunity and other perioperative designs. Window-of-opportunity trial designs leverage the period between the cancer diagnosis, typically by tumor biopsy, and tumor resection to carry out detailed pharmacodynamic evaluation in tumors that are not affected by prior treatment. The authors share lessons learned in glioma and highlight examples from other cancers, illustrating that key concepts apply to other rare cancers. The authors’ insights are especially significant as drug development has evolved toward targeting highly specific molecular targets.  

Why So Many Trial Designs? 

Clinical trial protocols are assessed for their scientific integrity, data, and safety monitoring, and reviewed for methodological, scientific, and ethical issues. Understanding the trial design is crucial in evaluating investigational treatments and novel protocols. Over the years, an increasing number of early-phase trial designs have emerged, and Clertant reviews the efforts by statisticians over the past three decades to improve the design and accuracy of early-phase oncology trials.5 His exhaustive qualitative assessment of several designs that are currently proposed and in use explores the designs’ technical differences, advantages, and properties.  
 
“This is a comprehensive summary of all of the different designs that are currently being used and sheds new light on the different classes of designs that are available,” Dr. Devlin said.  

Methodologies to Analyze Observational Data  

In the era of biomedical data, observational data are increasingly being used for comparative effectiveness research and to generate real-world evidence. Xu et al review the latest statistical methodologies of how to incorporate individual patient variables into clinical research within oncology.6 The authors review methods such as double robustness, which have been intensively studied in statistics although they are not yet widely used in clinical research. The authors hope to familiarize oncology statisticians and researchers with state-of-the-art statistical approaches and provide additional references for further reading.  
 
Dr. Devlin described the article as “a comprehensive summary of where the field is now with great references that someone who is just entering this area can read and get up to speed with the current state-of-the-art methods.”  
 
Together, the articles in the special series highlight the need for industry, academia, regulators, patient advocates, and other independent groups to work together, share lessons learned, and improve the safety and efficacy of new agents to ultimately improve outcomes for patients with cancer.  

References 

  1. Devlin S, Iasonos A. Statistics in Oncology. J Clin Oncol. 2022;40:3471-3.  
  2. Lin X, Lee S, Sharma P, et al. Summary of US Food and Drug Administration Chimeric Antigen Receptor (CAR) T-Cell Biologics License Application Approvals From a Statistical PerspectiveJ Clin Oncol. 2022;40:3501-9. 
  3. Fourie Zirkelbach J, Shah M, Vallejo J, et al. Improving Dose-Optimization Processes Used in Oncology Drug Development to Minimize Toxicity and Maximize Benefit to Patients. J Clin Oncol. 2022;40:3489-3500. 
  4. Mellinghoff IK, Cloughesy TF. Balancing Risk and Efficiency in Drug Development for Rare and Challenging Tumors: A New Paradigm for Glioma. J Clin Oncol. 2022;40:3510-9. 
  5. Clertant M. Early-Phase Oncology Trials: Why So Many Designs? J Clin Oncol. 2022;40:3529-36. 
  6. Xu R, Chen G, Connor M, et al. Novel Use of Patient-Specific Covariates From Oncology Studies in the Era of Biomedical Data Science: A Review of Latest Methodologies. J Clin Oncol. 2022;40:3546-53. 
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