One-year access to more than 500 world journals available in the system
-
http://medilib.ir
- Duration of Time : 365 Day
Price : 300$- Special Price : 100$
Statistics in Oncology.
Devlin, Sean PhD 1,; Iasonos, Alexia PhD 1,,
doi : 10.1200/JCO.22.01457
Volume 40(30) pgs. 3471-3553 October 20, 2022
Ethical Considerations for Phase I Trials in Oncology.
Bittlinger, Merlin PhD 1; Bicer, Selin BSc 1; Peppercorn, Jeffrey MD 2,; Kimmelman, Jonathan PhD 1,,
doi : 10.1200/JCO.21.02125
AB Phase I trials often represent the first occasion where new cancer strategies are tested in patients. Various developments in cancer biology, methodology, regulation, and medical ethics have altered the ethical landscape of such trials.
Improving Dose-Optimization Processes Used in Oncology Drug Development to Minimize Toxicity and Maximize Benefit to Patients.
Fourie Zirkelbach, Jeanne PhD 1; Shah, Mirat MD 2; Vallejo, Jonathon PhD 3,; Cheng, Joyce PhD 3; Ayyoub, Amal PhD 1; Liu, Jiang PhD 1; Hudson, Rachel PhD 1; Sridhara, Rajeshwari PhD 3; Ison, Gwynn MD 2; Amiri-Kordestani, Laleh MD 2; Tang, Shenghui PhD 3; Gwise, Thomas PhD 3; Rahman, Atiqur PhD 1; Pazdur, Richard MD 4; Theoret, Marc R. MD 4,
doi : 10.1200/JCO.22.00371
AB This review highlights strategies to integrate dose optimization into premarketing drug development and discusses the underlying statistical principles. Poor dose optimization can have negative consequences for patients, most commonly because of toxicity, including poor quality of life, reduced effectiveness because of inability of patients to stay on current therapy or receive subsequent therapy because of toxicities, and difficulty in developing combination regimens.
Summary of US Food and Drug Administration Chimeric Antigen Receptor (CAR) T-Cell Biologics License Application Approvals From a Statistical Perspective.
Lin, Xue PhD 1,; Lee, Shiowjen PhD 1; Sharma, Poornima MD 1; George, Bindu MD 1; Scott, John PhD 1
doi : 10.1200/JCO.21.02558
AB The approval of tisagenlecleucel and axicabtagene ciloleucel in 2017 marked a milestone in the development of oncology therapies. Since 2017, the breakthrough in treatment or even cure of previously intractable diseases represented by this new class of cancer treatments has continued with subsequent chimeric antigen receptor T (CAR T)-cell approvals. To date, the US Food and Drug Administration has approved five autologous CAR T-cell products for seven indications.
Balancing Risk and Efficiency in Drug Development for Rare and Challenging Tumors: A New Paradigm for Glioma.
Mellinghoff, Ingo K. MD 1,; Cloughesy, Timothy F. MD 2,,
doi : 10.1200/JCO.21.02166
AB The process of developing cancer therapies is well established and has enabled the incorporation of many new drugs and classes of agents into the standard of care for common cancers.
Basket Trials: Review of Current Practice and Innovations for Future Trials.
Hobbs, Brian P. PhD 1,,; Pestana, Roberto Carmagnani MD 2,; Zabor, Emily C. PhD 3; Kaizer, Alexander M. PhD 4; Hong, David S. MD 5,
doi : 10.1200/JCO.21.02285
AB Advances in biology and immunology have elucidated genetic and immunologic origins of cancer. Innovations in sequencing technologies revealed that distinct cancer histologies shared common genetic and immune phenotypic traits.
Early-Phase Oncology Trials: Why So Many Designs?.
Clertant, Matthieu PhD 1,
doi : 10.1200/JCO.21.02493
AB The past 30 years have seen a considerable effort on the part of statisticians to improve the design and accuracy of early-phase oncology trials. Some of this effort has been rewarded via successful implementation in actual trials, yet it would be fair to say that among clinicians, there remains some reluctance to fully embrace more efficient model-based approaches.
Testing for Differences in Survival When Treatment Effects Are Persistent, Decaying, or Delayed.
O'Quigley, John PhD 1,
doi : 10.1200/JCO.21.01811
AB A statistical test for the presence of treatment effects on survival will be based on a null hypothesis (absence of effects) and an alternative (presence of effects). The null is very simply expressed. The most common alternative, also simply expressed, is that of proportional hazards. For this situation, not only do we have a very powerful test in the log-rank test but also the outcome is readily interpreted.
Novel Use of Patient-Specific Covariates From Oncology Studies in the Era of Biomedical Data Science: A Review of Latest Methodologies.
Xu, Ronghui PhD 1,; Chen, Guanhua PhD 2; Connor, Michael MD 1; Murphy, James MD, MPH 1,
doi : 10.1200/JCO.21.01957
AB In this article, we review different applications of how to incorporate individual patient variables into clinical research within oncology. These methodologies range from the more traditional use of baseline covariates from randomized clinical trials, as well as observational studies, to using covariates to generalize the results of randomized clinical trials to other populations.
