ProGraME: A novel flow cytometry algorithm for the diagnosis of low-risk myelodysplastic syndromes in patients with cytopenia.

OBJECTIVES: Flow cytometry (FC) is, together with morphology, genetics, and cytogenetics, used in the diagnostic assessment of cytopenia, as its value in evaluating bone marrow dysplasia been highlighted by several studies. However, despite the development of algorithms and guidelines, there is still a lack of standardization of the FC assessment of bone marrow dysplasia. METHODS: By combining FC, together with morphological analysis and cytogenetic/molecular assessment in a training cohort of 209 patients, we created a novel score, ProGraME, which includes four parameters, each from a different cell lineage (Progenitor cells, Granulocytes, Monocytes, Erythroid precursors), solely based on relevant population gating. Points for ProGraME were attained for: lymphoid precursors ≤5% of all CD34+ cells (1.5 point); a granulocyte-to-lymphocyte side-scatter ratio ≤6 (1 point); a monocyte CD33-CV% ≥ 63 (2 points), and an erythroid precursor CD36-CV% ≥ 65 (2 points). RESULTS: Using a cutoff of ≥2 as suggestive of dysplasia, ProGraME showed a sensitivity of 91% and a specificity of 81% in the training cohort and 95% and 75%, respectively, in an independent validation cohort of 159 patients. In addition, ProGraME had a very high negative predictive value of 97.1% and 97.8% in the training and validation cohorts, respectively, offering a useful tool for excluding bone marrow dysplasia. Finally, among the 23 CCUS patients that scored positive for dysplasia with ProGraME in the training cohort, 16 of them (69%) carried high-risk mutations, suggesting that FC might help identify early changes of dysplasia. CONCLUSIONS: ProGraME can potentially optimize the FC diagnosis of low-risk myelodysplasia without minimal requirements of flow analysis other than accurate population gating.

A predictive model for bone marrow disease in cytopenia based on noninvasive procedures.

Bone marrow specimens are the core of the diagnostic workup of patients with cytopenia. To explore whether next-generation sequencing (NGS) could be used to rule out malignancy without bone marrow specimens, we incorporated NGS in a model to predict presence of disease in the bone marrow of patients with unexplained cytopenia. We analyzed the occurrence of mutations in 508 patients with cytopenia, referred for primary workup of a suspected hematologic malignancy from 2015 to 2020. We divided patients into a discovery (n = 340) and validation (n = 168) cohort. Targeted sequencing, bone marrow biopsy, and complete blood count were performed in all patients. Mutations were identified in 267 (53%) and abnormal bone marrow morphology in 188 (37%) patients. Patients with isolated neutropenia had the lowest frequency of both mutations (21%) and abnormal bone marrow morphology (5%). The median number of mutations per patient was 2 in patients with abnormal bone marrow morphology compared with 0 in patients with a nondiagnostic bone marrow morphology (P < .001). In a multivariable logistic regression, mutations in TET2, SF3B1, U2AF1, TP53, and RUNX1 were significantly associated with abnormal bone marrow morphology. In the validation cohort, a model combining mutational status and clinical data identified 34 patients (20%) without abnormal bone marrow morphology with a sensitivity of 100% (95% confidence interval: 93%-100%). Overall, we show that NGS combined with clinical data can predict the presence of abnormal bone marrow morphology in patients with unexplained cytopenia and thus can be used to assess the need of a bone marrow biopsy.