Possibility of myelodysplastic syndromes screening using a complete blood automated cell count

Rocco, Vincenzo; Maconi, Mariacaterina; Gioia, Maria; Silvestri, Michele; Tanca, Donatella; Catalano, Teodora; Avino, Daniela; Palma, A. Di; Rovetti, Adele; Danise, Paolo

doi:10.1016/j.leukres.2011.06.015

Cited by 12 publications

(15 citation statements)

References 18 publications

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“…In most specialized hematological centers/hospitals, the prevalence of MDS is higher than in the normal population. The study by Rocco et al [1] is multicentric, including mostly specialized hematological centers/hospitals. Our study is multicentric as well, but only includes local hospitals where the prevalence of MDS is in agreement with the normal population.…”

Section: E38mentioning

confidence: 99%

“…Sir, In 2001, Rocco et al [1] proposed a set of algorithms that recognizes MDS-related numerical aberrancies and dysplastic aspects in a full blood count (FBC) cytogram derived by the ADVIA 2120i.…”

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confidence: 99%

“…Herein, we set up a study in line with the research performed by Rocco et al [1]. Venous blood samples from 63 000 hospitalized and outpatients were collected by routine phlebotomy in K 2 EDTA tubes.…”

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confidence: 99%

“…WBCs were measured using two channels: the peroxidase channel that measured the absorption of the stained myeloperoxidase and the basophil/lobularity channel that measured the nuclear density of the WBC. The described algorithms [1] were programmed in HemaLink middleware (ICT informatik GmbH, Argenb€ uhl) which was connected to four ADVIA 2120i hematology analyzers (Siemens). As described [1], five different pattern could be identified which resulted in a dysplasia-flag.…”

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confidence: 99%

“…The described algorithms [1] were programmed in HemaLink middleware (ICT informatik GmbH, Argenb€ uhl) which was connected to four ADVIA 2120i hematology analyzers (Siemens). As described [1], five different pattern could be identified which resulted in a dysplasia-flag. Using the corresponding clinical data, the specificity and sensitivity of this flag were calculated.…”

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confidence: 99%

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Evaluation of myelodysplasia syndrome screening during routine hematological analysis on the ADVIA 2120i

Koenders

Taal

Hingh

et al. 2014

Int J Lab Hematology

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Section: E38mentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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Evaluation of myelodysplasia syndrome screening during routine hematological analysis on the ADVIA 2120i

Koenders

Taal

Hingh

et al. 2014

Int J Lab Hematology

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Automated screening for myelodysplastic syndromes through analysis of complete blood count and cell population data parameters

et al. 2014

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The diagnosis of myelodysplastic syndromes (MDS) requires a high clinical index of suspicion to prompt bone marrow studies as well as subjective assessment of dysplastic morphology. We sought to determine if data collected by automated hematology analyzers during complete blood count (CBC) analysis might help to identify MDS in a routine clinical setting. We collected CBC parameters (including those for research use only and cell population data) and demographic information in a large (>5,000), unselected sequential cohort of outpatients. The cohort was divided into independent training and test groups to develop and validate a random forest classifier that identifies MDS. The classifier effectively identified MDS and had a receiver operating characteristic area under the curve (AUC) of 0.942. Platelet distribution width and the standard deviation of red blood cell distribution width were the most discriminating variables within the classifier. Additionally, a similar classifier was validated with an additional, independent set of >200 patients from a second institution with an AUC of 0.93. This retrospective study demonstrates the feasibility of identifying MDS in an unselected outpatient population using data routinely collected during CBC analysis with a classifier that has been validated using two independent data sets from different institutions.

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Mean platelet component and mean platelet volume as useful screening markers for myelodysplastic syndrome

Masutani

Ikemoto

Maki

et al. 2018

Health Science Reports

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BackgroundHematologic disorders, including myelodysplastic syndrome (MDS), are difficult to identify in routine hematologic examinations using automated hematology analyzers. However, the practical uses of mean platelet component and mean platelet volume (MPV) measured by these analyzers as screening markers for MDS, remain unclear.MethodsMean platelet component and MPV values were measured in the peripheral blood of patients with MDS, aplastic anemia, idiopathic thrombocytopenic purpura, myeloproliferative neoplasms, and in healthy controls using an automated hematologic analyzer. Cutoff values for discriminating between the MDS group and healthy controls were determined by recursive partitioning analysis.ResultsMean platelet component was significantly lower in MDS patients compared with controls, while MPV was significantly higher. Combined cutoff values for MDS diagnosis of <25.3 g/dL for mean platelet component and >10.0 fL for MPV showed a specificity and positive predictive value of 99.9% and 99.1%, respectively. These cutoff values also differentiated between MDS and diagnoses of aplastic anemia, idiopathic thrombocytopenic purpura, and myeloproliferative neoplasms.ConclusionMean platelet component and MPV may, thus, be useful and convenient screening markers for MDS.

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Possibility of myelodysplastic syndromes screening using a complete blood automated cell count

Cited by 12 publications

References 18 publications

Evaluation of myelodysplasia syndrome screening during routine hematological analysis on the ADVIA 2120i

Evaluation of myelodysplasia syndrome screening during routine hematological analysis on the ADVIA 2120i

Automated screening for myelodysplastic syndromes through analysis of complete blood count and cell population data parameters

Mean platelet component and mean platelet volume as useful screening markers for myelodysplastic syndrome

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