title: Minimal screening analysis based algorithm for diagnosis and clinical stratification of patients with acute myeloid leukaemia (AML):  single centre experience.
abstract: In this paper we present our results from a study designed in order to establish and standardize a diagnostic algorithm for acute myeloid leukaemia (AML) in the Republic of Macedonia. A total of 146 consecutive adult patients (>15 years) were enrolled in the study. First, we determined the correct lineage assignment of the blast cells and evaluated the incidence of the favourable PML/RARα, AML1/ETO, CBFβ/MYH11 genetic markers among the AML cases. Additionally, the obtained results were correlated with patients' age, comorbidities, and performance status, and each single AML patient was stratified to effective treatment strategy. Our results showed that morphology and cytochemistry established a lineage in 132 (89.1%) of the patients, but not in 16 cases that presented as acute leukaemia, of which 7 were assigned as myeloid, and in two a non-haematopoietic malignancy was indicated with immunophenotyping. Mulitparameter flow cytometry immunophenotyping also changed the assigned lineage based on morphology and cytochemistry in 5 (3.3%) of the patients from lymphoid to myeloid and improved diagnosis in 21 (14.1%) cases. By using a reverse transcriptase-polymerase chain reaction (RT-PCR) essay 28 (23.1%) patients were classified in the prognostically favourable AML genetic group; 8 patients expressed the fusion transcript PML/RARα AML1/ETO and 15 CBFβ/MYH11. Moreover, analyses of the age, performance status and comorbidities further strtified an additional 12.5% of the patients to a different risk-adapted therapy. The applied minimal screening-analysis-based diagnostic algorithm enabled improved and more precise diagnosis and clinical stratification in 37.2 % of AML patients from our study group.
authors.affiliation: University Haematology Clinic, Faculty of Medicine, Ss. Cyril and Methodius University, Skopje, R. Macedonia.
authors.forename: I
authors.initials: I
authors.lastname: Panovska-Stavridis
authors.forename: S
authors.initials: S
authors.lastname: Trajkova
authors.forename: M
authors.initials: M
authors.lastname: Ivanovski
authors.forename: L
authors.initials: L
authors.lastname: Hadzi-Pecova
authors.forename: D
authors.initials: D
authors.lastname: Dukovski
authors.forename: M
authors.initials: M
authors.lastname: Popova-Simjanovska
authors.forename: L
authors.initials: L
authors.lastname: Cevreska
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D005260:Female; D005434:Flow Cytometry; D006801:Humans; D016130:Immunophenotyping; D015470:Leukemia, Myeloid, Acute / Q000145:classification / Q000175:diagnosis* / Q000235:genetics; D008297:Male; D008875:Middle Aged; D020133:Reverse Transcriptase Polymerase Chain Reaction; D012307:Risk Factors