2024
Optimization criteria for ordering myeloid neoplasm next‐generation sequencing
Gisriel S, Howe J, Tormey C, Torres R, Hager K, Rinder H, Siddon A. Optimization criteria for ordering myeloid neoplasm next‐generation sequencing. EJHaem 2024 DOI: 10.1002/jha2.1036.Peer-Reviewed Original ResearchNext-generation sequencingNext-generation sequencing testMyeloid neoplasmsDiagnosis of chronic myeloid leukemiaAltering treatment plansEnd-of-inductionFluorescence in situ hybridizationRecurrence post-transplantChronic myeloid leukemiaSuspicion of progressionPathogenic mutationsClinical suspicionMutation statusMN diagnosisMyeloid leukemiaPost-transplantRisk stratificationWorsening diseaseTreatment planningCancellation criteriaSuspicionDiagnosisSequenceCenters for MedicareB test
2020
Impact of intra-tumoral heterogeneity detected by next-generation sequencing on acute myeloid leukemia survival
Schulz WL, Rinder HM, Durant TJS, Tormey CA, Torres R, Smith BR, Hager KM, Howe JG, Siddon AJ. Impact of intra-tumoral heterogeneity detected by next-generation sequencing on acute myeloid leukemia survival. Leukemia & Lymphoma 2020, 61: 3269-3271. PMID: 32715805, DOI: 10.1080/10428194.2020.1797016.Peer-Reviewed Original Research
2015
Computational Approach to Annotating Variants of Unknown Significance in Clinical Next Generation Sequencing
Schulz WL, Tormey CA, Torres R. Computational Approach to Annotating Variants of Unknown Significance in Clinical Next Generation Sequencing. Lab Medicine 2015, 46: 285-289. PMID: 26489672, DOI: 10.1309/lmwzh57brwopr5rq.Peer-Reviewed Original ResearchConceptsNext-generation sequencingClinical significanceUnknown clinical significanceMalignant neoplasmsHematologic malignanciesClinical next-generation sequencingSoftware algorithmsGeneration sequencingUnknown significanceBenign variantsConflicting resultsClinical laboratoriesComputational toolsCommon technologyAlgorithm