TY - JOUR
T1 - Is bone marrow examination always necessary to establish the diagnosis of myelodysplastic syndromes? A proposed non-invasive diagnostic model
AU - Oster, Howard S.
AU - Carmi, Gal
AU - Kolomansky, Alex
AU - Joffe, Erel
AU - Kaye, Irit
AU - Kirgner, Ilya
AU - Greenbaum, Uri
AU - Comaneshter, Doron
AU - Mittelman, Moshe
N1 - Publisher Copyright:
© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2018/9/2
Y1 - 2018/9/2
N2 - A non-invasive myelodysplastic syndromes (MDS) diagnostic model would allow for care while avoiding invasive bone marrow examinations (BME). BME-established MDS patients were compared to non-MDS (BME-excluded) patients. Variables (gender, age, hemoglobin (Hb), mean red blood cell corpuscular volume (MCV), platelet (PLT), and white blood cell (WBC)) were combined with multivariate logistic regression; a probability score (Y) was calculated. MDS (n = 48) and non-MDS (n = 63) patients were used to establish the model. The ROC was drawn, giving an AUC of 0.748 (95% CI: 0.656–0.84). Two cutoff values were used for Y. Y ≥ 0.633: high likelihood (positive predictive value (PPV) = 85%); Y ≤ 0.288: low likelihood (negative predictive value (NPV) = 81%) of MDS. The first group is defined as probable MDS (pMDS); the second, probably not MDS (pnMDS). The model was validated with 40 additional patients (20 with and 20 without MDS). Using clinical and lab data, we could diagnose or exclude MDS in about half of the patients, avoiding BME. Future work will use larger cohorts of patients to improve and further validate the model.
AB - A non-invasive myelodysplastic syndromes (MDS) diagnostic model would allow for care while avoiding invasive bone marrow examinations (BME). BME-established MDS patients were compared to non-MDS (BME-excluded) patients. Variables (gender, age, hemoglobin (Hb), mean red blood cell corpuscular volume (MCV), platelet (PLT), and white blood cell (WBC)) were combined with multivariate logistic regression; a probability score (Y) was calculated. MDS (n = 48) and non-MDS (n = 63) patients were used to establish the model. The ROC was drawn, giving an AUC of 0.748 (95% CI: 0.656–0.84). Two cutoff values were used for Y. Y ≥ 0.633: high likelihood (positive predictive value (PPV) = 85%); Y ≤ 0.288: low likelihood (negative predictive value (NPV) = 81%) of MDS. The first group is defined as probable MDS (pMDS); the second, probably not MDS (pnMDS). The model was validated with 40 additional patients (20 with and 20 without MDS). Using clinical and lab data, we could diagnose or exclude MDS in about half of the patients, avoiding BME. Future work will use larger cohorts of patients to improve and further validate the model.
KW - Myelodysplastic syndromes
KW - diagnosis
KW - logistic regression
KW - model
KW - noninvasive
UR - http://www.scopus.com/inward/record.url?scp=85039845820&partnerID=8YFLogxK
U2 - 10.1080/10428194.2017.1416363
DO - 10.1080/10428194.2017.1416363
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
C2 - 29295649
AN - SCOPUS:85039845820
SN - 1042-8194
VL - 59
SP - 2227
EP - 2232
JO - Leukemia and Lymphoma
JF - Leukemia and Lymphoma
IS - 9
ER -