Automated screening for myelodysplastic syndromes through analysis of complete blood count and cell population data parameters. Issue 4 (13th March 2014)
- Record Type:
- Journal Article
- Title:
- Automated screening for myelodysplastic syndromes through analysis of complete blood count and cell population data parameters. Issue 4 (13th March 2014)
- Main Title:
- Automated screening for myelodysplastic syndromes through analysis of complete blood count and cell population data parameters
- Authors:
- Raess, Philipp W.
van de, Gert‐Jan M.
Njo, Tjin L.
Klop, Boudewijn
Sukhachev, Dmitry
Wertheim, Gerald
McAleer, Tom
Master, Stephen R.
Bagg, Adam - Abstract:
- <abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>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 (&gt;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 &gt;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. Am. J. Hematol. 89:369–374,<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>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 (&gt;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 &gt;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. Am. J. Hematol. 89:369–374, 2014. © 2013 Wiley Periodicals, Inc.</p> </abstract> … (more)
- Is Part Of:
- American journal of hematology. Volume 89:Issue 4(2014:Apr.)
- Journal:
- American journal of hematology
- Issue:
- Volume 89:Issue 4(2014:Apr.)
- Issue Display:
- Volume 89, Issue 4 (2014)
- Year:
- 2014
- Volume:
- 89
- Issue:
- 4
- Issue Sort Value:
- 2014-0089-0004-0000
- Page Start:
- 369
- Page End:
- 374
- Publication Date:
- 2014-03-13
- Subjects:
- Hematology -- Periodicals
616.15 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1096-8652 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/ajh.23643 ↗
- Languages:
- English
- ISSNs:
- 0361-8609
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0824.800000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 3618.xml