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Recently, the National Cancer Institute (NCI) has implemented a new initiative, the Pediatric Preclinical Testing Program (PPTP), comprising a consortium of investigators who will integrate in vivo and in vitro testing with expression and genomic profiling. The objective of the PPTP is to identify agents with significant activity in panels of pediatric preclinical models as a potential mechanism for prioritizing agents for advancement to clinical trials for children with specific cancers. Its ultimate goal is to expedite the discovery of more effective therapies for children with cancer so that childhood cancer mortality and morbidity are reduced in the future.
The PPTP has the capacity to test approximately 12 agents or combinations of agents annually in its preclinical models of common childhood cancers. Agents are selected for PPTP testing based on their potential relevance in the childhood cancer setting and based on their stage of clinical development. Selected standard agents are also being tested by the PPTP, both to calibrate the PPTP’s tumor panels and to serve as a basis for future combination studies.
However, the analysis of tumor xenogrfat data presents several statistical challenges. First, a relative small number of mice are treated in each treatment group due to cost of the experiments. Second, for each tumor, the tumor volumes are measured over time, resulting a longitudinal endpoint which adds the complexity of the data analysis. Third, a mouse may die of toxicity or may be sacrificed due to tumor burden, resulting in incomplete longitudinal measurements. Furthermore, the tumor xenograft model often produces very erratic growth patterns and modeling tumor growth curve is often difficult or even impossible.
A biostatisticians group in this department has been worked for PPTP data analysis since 2005. Several statistical methodologies were developed to assess the antitumor activity of tumor of PPTP tumor xenograft model, for example, event-free-survival assessment, relative tumor volume ratio (T/C ratio) assessment and objective response assessment. A SAS macro has been developed by this group for the PPTP data analysis. A total of 7 papers have been published for the PPTP studies (Houghton et al, 2007).
This article appears in Pediatric Blood and Cancer 2007. Other co-first authors include Peter Houghton (St. Jude-Molecular Pharmacology), Christopher Morton (St. Jude-Molecular Pharmacology), Richard Gorlick (The Children’s Hospital at Montefiore), E. Anders Kolb (The Children’s Hospital at Montefiore), Richard Lock (Children’s Cancer Institute Australia for Medical Research), C. Patrick Reynolds (Children’s Hospital of Los Angeles), John Maris (Children’s Hospital of Philadelphia), Tiebin Liu (St. Jude-Biostatistics), Catherine Billups (St. Jude-Biostatistics), Javed Khan (Pediatric Oncology Branch, Oncogenomics Section, NCI), Stephen Kier (Duke University Medical Center), Henry Friedman (Duke University Medical Center), and Malcolm Smith (Cancer Therapy Evaluation program, NCI).