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Database-Guided Analysis for Immunophenotypic Diagnosis and Follow-Up of Acute Myeloid Leukemia With Recurrent Genetic Abnormalities
- Source :
- Frontiers in Oncology, Vol 11 (2021), Frontiers in Oncology
- Publication Year :
- 2021
- Publisher :
- Frontiers Media S.A., 2021.
-
Abstract
- Acute myeloid leukemias (AMLs) are hematologic malignancies with varied molecular and immunophenotypic profiles, making them difficult to diagnose and classify. High-dimensional analysis algorithms might increase the utility of multicolor flow cytometry for AML diagnosis and follow-up. The objective of the present study was to assess whether a Compass database-guided analysis can be used to achieve rapid and accurate diagnoses. We conducted this study to determine whether this method could be employed to pilote the genetic and molecular tests and to objectively identify different-from-normal (DfN) patterns to improve measurable residual disease follow-up in AML. Three Compass databases were built using Infinicyt 2.0 software, including normal myeloid-committed hematopoietic precursors (n = 20) and AML blasts harboring the most frequent recurrent genetic abnormalities (n = 50). The diagnostic accuracy of the Compass database-guided analysis was evaluated in a prospective validation study (125 suspected AML patients). This method excluded AML associated with the following genetic abnormalities: t(8;21), t(15;17), inv(16), and KMT2A translocation, with 92% sensitivity [95% confidence interval (CI): 78.6%–98.3%] and a 98.5% negative predictive value (95% CI: 90.6%–99.8%). Our data showed that the Compass database-guided analysis could identify phenotypic differences between AML groups, representing a useful tool for the identification of DfN patterns.
- Subjects :
- Cancer Research
Validation study
acute myeloid leukemia with recurrent genetic abnormalities
Diagnostic accuracy
Disease
computer.software_genre
different-from-normal (DfN) approach
hemic and lymphatic diseases
Medicine
Medical diagnosis
multicolor flow cytometry
Compass database-guided analysis
RC254-282
Original Research
Database
biology
business.industry
Myeloid leukemia
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Predictive value
Confidence interval
KMT2A
Oncology
biology.protein
measurable (minimal) residual disease
business
computer
Subjects
Details
- Language :
- English
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Frontiers in Oncology
- Accession number :
- edsair.doi.dedup.....e2080fd036c1968fee05cd4f0793b73e
- Full Text :
- https://doi.org/10.3389/fonc.2021.746951/full