Automated synthesis and visualization of a chemotherapy treatment regimen network.
Cytotoxic treatments for cancer remain highly toxic, expensive, and variably efficacious. Many chemotherapy regimens are never directly compared in randomized clinical trials (RCTs); as a result, the vast majority of guideline recommendations are ultimately derived from human expert opinion. We introduce an automated network meta-analytic approach to this clinical problem, with nodes representing regimens and edges direct comparison via RCT(s). A chemotherapy regimen network is visualized for the primary treatment of chronic myelogenous leukemia (CML). Node and edge color, size, and opacity are all utilized to provide additional information about the quality and strength of the depicted evidence. Historical versions of the network are also created. With this approach, we were able to compactly compare the results of 17 CML regimens involving RCTs of 9700 patients, representing the accumulation of 45 years of evidence. Our results closely parallel the recommendations issued by a professional guidelines organization, the National Comprehensive Cancer Network (NCCN). This approach offers a novel method for interpreting complex clinical data, with potential implications for future objective guideline development.
Department of Medicine, Division of Hematology & Oncology, Vanderbilt University, Nashville, TN, USA.
Jeremy
J
Warner
Peter
P
Yang
Gil
G
Alterovitz
D000465:Algorithms; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D006801:Humans; D007951:Leukemia, Myeloid / Q000188:drug therapy* / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D012984:Software; D014584:User-Computer Interface