A predictive algorithm using clinical and laboratory parameters may assist in ruling out and in diagnosing MDS
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023736%3A_____%2F21%3A00013269" target="_blank" >RIV/00023736:_____/21:00013269 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1182/bloodadvances.2020004055" target="_blank" >https://doi.org/10.1182/bloodadvances.2020004055</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1182/bloodadvances.2020004055" target="_blank" >10.1182/bloodadvances.2020004055</a>
Alternative languages
Result language
angličtina
Original language name
A predictive algorithm using clinical and laboratory parameters may assist in ruling out and in diagnosing MDS
Original language description
We present a noninvasive web-based app to help exclude or diagnose myelodysplastic syndrome (MDS), a bone marrow (BM) disorder with cytopenias and leukemic risk, diagnosed by BM examination. A sample of 502 MDS patients from the European MDS (EUMDS) registry (n > 2600) was combined with 502 controls (all BM proven). Gradient-boosted models (GBMs) were used to predict/exclude MDS using demographic, clinical, and laboratory variables. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to evaluate the models, and performance was validated using 100 times fivefold cross-validation. Model stability was assessed by repeating its fit using different randomly chosen groups of 502 EUMDS cases. AUC was 0.96 (95% confidence interval, 0.95-0.97). MDS is predicted/excluded accurately in 86% of patients with unexplained anemia. A GBM score (range, 0-1) of less than 0.68 (GBM < 0.68) resulted in a negative predictive value of 0.94, that is, MDS was excluded. GBM ≥ 0.82 provided a positive predictive value of 0.88, that is, MDS. The diagnosis of the remaining patients (0.68 ≤ GBM < 0.82) is indeterminate. The discriminating variables: age, sex, hemoglobin, white blood cells, platelets, mean corpuscular volume, neutrophils, monocytes, glucose, and creatinine. A Web-based app was developed, physicians could use it to exclude or predict MDS noninvasively in most patients without a BM examination. Future work will add peripheral blood cytogenetics/genetics, EUMDS-based prospective validation, and prognostication.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30205 - Hematology
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Blood advances
ISSN
2473-9529
e-ISSN
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Volume of the periodical
5
Issue of the periodical within the volume
16
Country of publishing house
US - UNITED STATES
Number of pages
10
Pages from-to
3066-3075
UT code for WoS article
000688536600003
EID of the result in the Scopus database
2-s2.0-85113900403