TY - JOUR
T1 - A machine-learning model that incorporates CD45 surface expression predicts hematopoietic progenitor cell recovery after freeze–thaw
AU - Al-Riyami, Arwa Z.
AU - Maryamchik, Elena
AU - Hanna, Richard S.
AU - Pashmineh Azar, Amir Reza
AU - Zheng, Xingwu
AU - Choudhari, Shilpa
AU - Finn, Colleen
AU - Giacobbe, Nicholas
AU - Machietto, Rene
AU - Rieser, Robert
AU - Ghasemi Tahrir, Farzaneh
AU - Zhang, Xiaoyong
AU - Kadauke, Stephan
AU - Wang, Yongping
N1 - Publisher Copyright:
© 2023 International Society for Cell & Gene Therapy
PY - 2023/10/1
Y1 - 2023/10/1
N2 - 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.
AB - 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.
KW - Antigens, CD34/metabolism
KW - Child
KW - Cryopreservation/methods
KW - Freezing
KW - Hematopoietic Stem Cell Transplantation/methods
KW - Hematopoietic Stem Cells/metabolism
KW - Humans
KW - Leukocyte Common Antigens
KW - Machine Learning
KW - Retrospective Studies
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UR - https://www.mendeley.com/catalogue/a5006c6f-fd4e-3ee4-bbb2-7df66b0c3af7/
U2 - 10.1016/j.jcyt.2023.05.007
DO - 10.1016/j.jcyt.2023.05.007
M3 - Article
C2 - 37318396
AN - SCOPUS:85162159102
SN - 1465-3249
VL - 25
SP - 1048
EP - 1056
JO - Cytotherapy
JF - Cytotherapy
IS - 10
ER -