A machine-learning model that incorporates CD45 surface expression predicts hematopoietic progenitor cell recovery after freeze–thaw

Arwa Z. Al-Riyami, Elena Maryamchik, Richard S. Hanna, Amir Reza Pashmineh Azar, Xingwu Zheng, Shilpa Choudhari, Colleen Finn, Nicholas Giacobbe, Rene Machietto, Robert Rieser, Farzaneh Ghasemi Tahrir, Xiaoyong Zhang, Stephan Kadauke, Yongping Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

BACKGROUND AIMS: Sufficient doses of viable CD34+ (vCD34) hematopoietic progenitor cells (HPCs) are crucial for engraftment. Additional-day apheresis collections can compensate for potential loss during cryopreservation but incur high cost and additional risk. To aid predicting such losses for clinical decision support, we developed a machine-learning model using variables obtainable on the day of collection.

METHODS: In total, 370 consecutive autologous HPCs, apheresis-collected since 2014 at the Children's Hospital of Philadelphia, were retrospectively reviewed. Flow cytometry was used to assess vCD34% on fresh products and thawed quality control vials. The ratio of vCD34% thawed to fresh, which we call "post-thaw index," was used as an outcome measure, with a "poor" post-thaw index defined as <70%. HPC CD45 normalized mean fluorescence intensity (MFI) was calculated by dividing CD45 MFI of HPCs to the CD45 MFI of lymphocytes in the same sample. We trained XGBoost, k-nearest neighbor and random forest models for the prediction and calibrated the best model to minimize falsely-reassuring predictions.

RESULTS: In total, 63 of 370 (17%) products had a poor post-thaw index. The best model was XGBoost, with an area under the receiver operator curve of 0.83 evaluated on an independent test data set. The most important predictor for a poor post-thaw index was the HPC CD45 normalized MFI. Transplants after 2015, based on the lower of the two vCD34% values, showed faster engraftment than older transplants, which were based on fresh vCD34% only (average 10.6 vs 11.7 days, P = 0.0006).

CONCLUSIONS: Transplants taking into account post-thaw vCD34% improved engraftment time in our patients; however, it came at the cost of unnecessary multi-day collections. The results from applying our predictive algorithm retrospectively to our data suggest that more than one-third of additional-day collections could have been avoided. Our investigation also identified CD45 nMFI as a novel marker for assessing HPC health post-thaw.

Original languageEnglish
Pages (from-to)1048-1056
Number of pages9
JournalCytotherapy
Volume25
Issue number10
DOIs
Publication statusPublished - Oct 1 2023

Keywords

  • Antigens, CD34/metabolism
  • Child
  • Cryopreservation/methods
  • Freezing
  • Hematopoietic Stem Cell Transplantation/methods
  • Hematopoietic Stem Cells/metabolism
  • Humans
  • Leukocyte Common Antigens
  • Machine Learning
  • Retrospective Studies

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