Autologous stem cell transplantation (ASCT) is a treatment modality for several diseases. Prediction of successful mobilization may be useful to optimize hematopoietic stem cell (HSC) collection. The objective was to identify characteristics that can influence the effectiveness of mobilization and create a model to predict the success of mobilization in candidates for ASCT.

This was a retrospective study, and data from patient candidates for ASCT between 09/2015 and 12/2021 were analyzed. Participants were assisted in five hospitals and laboratory procedures were performed at the Cell Processing Center (CPC) of Cetebio/Fundação Hemominas, Brazil. The medical records of the participants were reviewed to obtain the following information: gender, age, weight, diagnosis, mobilization, mobilization cycle, number of previous chemotherapy regimens and previous radiotherapy. The laboratory data analyzed were CD34+ cell enumeration and pre-collection peripheral blood (PB) blood count. Enumeration of CD34+ cell was performed using the ISHAGE protocol. The blood count was performed using an automated counter (SYSMEX XN-1000 AS-01). The studied outcome, good mobilization, was defined as a viable CD34+ cell count ≥ 20/uL in the PB. Model derivation was performed using logistic regression. The level of classification accuracy of model was tested in a subset of participants.

The study population included 807 patients, 413 (51%) of whom were male. The median age was 54 (1-74) years. Multiple myeloma was the most common diagnosis (58,2%), followed by lymphoma. Of the 807 participants, 74 failed in previous mobilization attempts, totaling 881 cycles of mobilizations and collection attempts. Of the 623 participants, 353 were good mobilizers. Increasing patient weight, lower mean corpuscular volume (MCV), higher nucleated red blood cells (nRBC), peripheral blood mononuclear cells (PBMC), and immature granulocyte count were significantly associated with good mobilization. In addition, participants diagnosed with multiple myeloma were two times more likely to be good mobilizers than patients with lymphoma (OR=1.92; 95%CI: 1.21 – 3.05; P=0.006). The model was applied to the validation set to identify patients who underwent apheresis (CD34+ cells count ≥ 10 μL), resulting in a sensibility of 69%, a specificity of 95%, positive predictive value of 98%, a negative predictive value of 50%.

The results of our study are extremely relevant to institutions that do not have a flow cytometer and rely on other institutions to define HSC collection by apheresis. Cetebio serves nine transplant centers. The centers that perform the collection of HSC are located between 40 to 568 km away from Cetebio (place of quantification of CD34+ cells). Predicting the outcome of mobilization may allow the adoption of complementary measures, such as the use of plerixafor. Furthermore, it would better optimize the collection of CPH by apheresis. Thus, it would be possible to avoid additional collection days, reducing costs and risks related to administration of additional doses of G-CSF, catheter maintenance and prolonged hospital stay.

Success in mobilization was greater in participants who underwent the first mobilization cycle and who had a diagnosis of multiple myeloma. Furthermore, higher weight and levels of nRBC, immature granulocytes, and PBMC, as well as lower levels of MCV, were associated with successful mobilization.