A simplified CD34+ based preharvest prediction tool for HPC(A) collection.
Transfusion
; 61(5): 1525-1532, 2021 05.
Article
em En
| MEDLINE
| ID: mdl-33694175
ABSTRACT
BACKGROUND:
Hematopoietic stem cell transplantation is an important treatment that is dependent on the collection of sufficient CD34+ hematopoietic progenitor cells. The peripheral blood CD34 count (PB CD34+ counts) measured by flow cytometry can be used in predicting CD34+ stem cell yields hours before the completion of collection. Previously described formulas to predict the yield have used many different variables. As such, there is currently no consensus on an industry-standard algorithm or formula. STUDY DESIGN ANDMETHODS:
Retrospective reviews of same-day PB CD34+ counts and the ensuing absolute CD34+ yields of mobilized donors (allogeneic and autologous) were used to develop and validate a formula using regression analysis to predict the CD34+ stem cell yield. A metric of prediction correlation, using root mean square error (RMSE), was used to assess the robustness of our prediction formula in addition to comparisons with two other published formulas, as well as subset analysis.RESULTS:
A formula in the form of y = mxb with r = 0.95 and 95% confidence intervals was generated and validated. The ratio of actual to predicted yield demonstrated a high correlation coefficient (r = 0.96) with linear regression and overall RMSE of 228.4, which was lower than the two prior studies (calculated RMSE = 330.8 and 405.2). Subset analyses indicated male patients, lymphoma patients, and patients >60 years of age demonstrated lower RMSEs.CONCLUSION:
We have demonstrated a simple yet robust formula that can be used prospectively to accurately predict the CD34+ stem cell yield in both autologous and allogeneic donors, which also accounts for recipient weight.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Células-Tronco Hematopoéticas
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Antígenos CD34
Tipo de estudo:
Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Adolescent
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Adult
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Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article