Large Unstained Cell, Blast Suspect and Delta Neutrophil Index ll Analyzed with Automated Hematology Analyzer as Parameters for the Prediction of Acute Leukemia Relapse
Laboratory Medicine Online
;
: 126-132, 2019.
Artículo
en Inglés
| WPRIM
| ID: wpr-760504
ABSTRACT
BACKGROUND:
Here we investigated the clinical utilities of blast suspect, large unstained cell (LUC), delta neutrophil index ll (DN ll), and delta neutrophil index l (DN l), analyzed in peripheral blood samples with automated hematology analyzers to predict the relapse of acute leukemia.METHODS:
We retrospectively reviewed the medical records of 112 patients, including 56 patients with acute leukemia relapse and 56 controls. Blast suspect, LUC, DN ll, and DN l were compared between the control and leukemia relapse groups.RESULTS:
Significant differences in blast suspect (P<0.001), LUC (P<0.001), DN ll (P<0.001), and DN l (P=0.002) were observed between the leukemia relapse and control groups. The areas under the curve (AUC) value was 0.927 for blast suspect (95% confidence interval [CI] 0.8750.978, P<0.001), 0.868 for LUC (95% CI 0.794–0.941, P<0.001), and 0.900 for DN ll (95% CI 0.841–0.960, P<0.001). Logistic regression analysis for the prediction of leukemia relapse revealed odds ratio values of 1.52 (95% CI 1.26–1.96, P=0.0002) for blast suspect, 1.66 (95% CI 1.27–2.42, P=0.0019) for LUC, 1.16 (95% CI 1.08–1.29, P=0.0014) for DN ll, and 1.05 (95% CI 1.01–1.13, P=0.0845) for DN l.CONCLUSIONS:
Multiple parameters provided by automated blood cell analyzers may serve as powerful ancillary tools for the prediction and diagnosis of leukemia relapse.
Texto completo:
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Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
Recurrencia
/
Células Sanguíneas
/
Leucemia
/
Modelos Logísticos
/
Oportunidad Relativa
/
Registros Médicos
/
Estudios Retrospectivos
/
Diagnóstico
/
Hematología
/
Neutrófilos
Tipo de estudio:
Estudio diagnóstico
/
Estudio de etiología
/
Estudio observacional
/
Estudio pronóstico
/
Factores de riesgo
Límite:
Humanos
Idioma:
Inglés
Revista:
Laboratory Medicine Online
Año:
2019
Tipo del documento:
Artículo
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