{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T18:42:23Z","timestamp":1770489743712,"version":"3.49.0"},"reference-count":23,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2018,12,7]],"date-time":"2018-12-07T00:00:00Z","timestamp":1544140800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100006432","name":"Terumo BCT","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006432","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Transfusion"],"published-print":{"date-parts":[[2019,2]]},"abstract":"<jats:sec><jats:title>BACKGROUND<\/jats:title><jats:p>Previous prediction algorithms to achieve target CD34+ goals have not been widely adopted, with many centers still using a set volume to process for hematopoietic progenitor cell collections. This may be because previous algorithms are challenging to implement. Additionally, no study has yet examined the utility of adjusting the collect flow rate (CFR) based on the donor's preprocedure total mononuclear cell (MNC) count, which correlates with CD34+ yield.<\/jats:p><\/jats:sec><jats:sec><jats:title>STUDY DESIGN AND METHODS<\/jats:title><jats:p>In this retrospective analysis of mobilized allogeneic donors collected using MNC (COBE Spectra, Terumo BCT) or continuous mononuclear cell collection (CMNC) (Spectra Optia, Terumo BCT) procedures, we validated a one\u2010step prediction algorithm to achieve the target CD34+ product dose (Appendix S1, available as supporting information in the online version of this paper). The COBE Spectra MNC Collect Flow Tool (Appendix S2, available as supporting information in the online version of this paper) was used to select the collect flow rate for both MNC and CMNC procedures. Procedural collection efficiency (CE) was compared to that of historical procedures utilizing fixed CFRs (1.0\u20131.5 mL\/min).<\/jats:p><\/jats:sec><jats:sec><jats:title>RESULTS<\/jats:title><jats:p>Ninety\u2010three percent of collections achieved the target CD34+ goal using our algorithm\u2010calculated process volumes. The remaining 7% of cases had CEs lower than the algorithm CE (0.40), and thus were below goal. Second, an MNC\u2010based CFR improved MNC and CD34+ CEs in patients with higher MNC counts compared to our historical controls.<\/jats:p><\/jats:sec><jats:sec><jats:title>CONCLUSION<\/jats:title><jats:p>We validated that this simple, single\u2010step prediction algorithm achieves the target CD34+ goal in most HPC collections. Secondly, we showed that an MNC\u2010based CFR for hematopoietic progenitor cell collections improves CE at higher MNCs; this may be preferable to a WBC\u2010based CFR because of variability of MNC counts at a given WBC count.<\/jats:p><\/jats:sec>","DOI":"10.1111\/trf.15034","type":"journal-article","created":{"date-parts":[[2018,12,7]],"date-time":"2018-12-07T16:25:28Z","timestamp":1544199928000},"page":"659-670","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["A dual strategy to optimize hematopoietic progenitor cell collections: validation of a simple prediction algorithm and use of collect flow rates guided by mononuclear cell count"],"prefix":"10.1111","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1042-1429","authenticated-orcid":false,"given":"Elizabeth A.","family":"Godbey","sequence":"first","affiliation":[{"name":"New York Blood Center Clinical Services  New York New York"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stephanie","family":"Dormesy","sequence":"additional","affiliation":[{"name":"New York Blood Center Clinical Services  New York New York"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lohith","family":"Gowda","sequence":"additional","affiliation":[{"name":"New York Blood Center Clinical Services  New York New York"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vijay","family":"Nandi","sequence":"additional","affiliation":[{"name":"New York Blood Center Lindsley F. Kimball Research Institute  New York New York"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarai","family":"Paradiso","sequence":"additional","affiliation":[{"name":"New York Blood Center Clinical Services  New York New York"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruce S.","family":"Sachais","sequence":"additional","affiliation":[{"name":"New York Blood Center Clinical Services  New York New York"},{"name":"New York Blood Center Lindsley F. Kimball Research Institute  New York New York"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7954-0055","authenticated-orcid":false,"given":"Patricia A.","family":"Shi","sequence":"additional","affiliation":[{"name":"New York Blood Center Clinical Services  New York New York"},{"name":"New York Blood Center Lindsley F. 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