Automated Ascertainment of Typhlitis From the Electronic Health Record.

PURPOSE: Adverse events (AEs) on Children's Oncology Group (COG) trials are manually ascertained using Common Terminology Criteria for Adverse Events. Despite significant effort, we previously demonstrated that COG typhlitis reporting sensitivity was only 37% when compared with gold standard physician chart abstraction. This study tested an automated typhlitis identification algorithm using electronic health record data. METHODS: Electronic health record data from children with leukemia age 0-22 years treated at a single institution from 2006 to 2019 were included. Patients were divided into derivation and validation cohorts. Rigorous chart abstraction of validation cohort patients established a gold standard AE data set. We created an automated algorithm to identify typhlitis matching Common Terminology Criteria for Adverse Events v5 that included antibiotics, neutropenia, and non-negated mention of typhlitis in a note. We iteratively refined the algorithm using the derivation cohort and then applied the algorithm to the validation cohort; performance was compared with the gold standard. For patients on trial AAML1031, COG AE report performance was compared with the gold standard. RESULTS: The derivation cohort included 337 patients. The validation cohort included 270 patients (961 courses). Chart abstraction identified 16 courses with typhlitis. The algorithm identified 37 courses with typhlitis; 13 were true positives (sensitivity 81.3%, positive predictive value 35.1%). For patients on AAML1031, chart abstraction identified nine courses with typhlitis, and COG reporting correctly identified 4 (sensitivity 44.4%, positive predictive value 100.0%). CONCLUSION: The automated algorithm identified true cases of typhlitis with higher sensitivity than COG reporting. The algorithm identified false positives but reduced the number of courses needing manual review by 96% (961 to 37) by detecting potential typhlitis. This algorithm could provide a useful screening tool to reduce manual effort required for typhlitis AE reporting.

Downregulation of SREBP inhibits tumor growth and initiation by altering cellular metabolism in colon cancer.

Sterol regulatory element-binding proteins (SREBPs) belong to a family of transcription factors that regulate the expression of genes required for the synthesis of fatty acids and cholesterol. Three SREBP isoforms, SREBP1a, SREBP1c, and SREBP2, have been identified in mammalian cells. SREBP1a and SREBP1c are derived from a single gene through the use of alternative transcription start sites. Here we investigated the role of SREBP-mediated lipogenesis in regulating tumor growth and initiation in colon cancer. Knockdown of either SREBP1 or SREBP2 decreased levels of fatty acids as a result of decreased expression of SREBP target genes required for lipid biosynthesis in colon cancer cells. Bioenergetic analysis revealed that silencing SREBP1 or SREBP2 expression reduced the mitochondrial respiration, glycolysis, as well as fatty acid oxidation indicating an alteration in cellular metabolism. Consequently, the rate of cell proliferation and the ability of cancer cells to form tumor spheroids in suspension culture were significantly decreased. Similar results were obtained in colon cancer cells in which the proteolytic activation of SREBP was blocked. Importantly, knockdown of either SREBP1 or SREBP2 inhibited xenograft tumor growth in vivo and decreased the expression of genes associated with cancer stem cells. Taken together, our findings establish the molecular basis of SREBP-dependent metabolic regulation and provide a rationale for targeting lipid biosynthesis as a promising approach in colon cancer treatment.