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Predictors of Unsuccessful Mobilization with Granulocyte-Colony Stimulating Factor (G-CSF) Alone In Patients with Hematological Malignancies Undergoing Autologous Hematopoietic Stem Cell (AHSCT) Transplant

2010· article· en· W2553775977 on OpenAlexaffabout
Signy Chow, D. George Ormond, Alejandro Lazo‐Langner, Kang Howson‐Jan, Anargyros Xenocostas

Bibliographic record

VenueBlood · 2010
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsPlerixaforMedicineMobilizationGranulocyte colony-stimulating factorInternal medicineStem cellHaematopoiesisCD34RegimenHematopoietic stem cell transplantationChemotherapyOncologySurgeryTransplantationGastroenterologyCXCR4Biology

Abstract

fetched live from OpenAlex

Abstract Abstract 4445 Background Mobilization of hematopoetic stem cells (HSC) in patients undergoing AHSCT for hematological malignancies is usually done using hematopoietic growth factors such as G-CSF with or without concurrent use of chemotherapy or other agents such as plerixafor. While studies comparing G-CSF alone to combination regimens demonstrate an increase in the yield of stem cells in the latter case, mobilization with G-CSF alone is still effective and represents the standard of care at our institution. Therefore, we aimed to identify potential predictors of mobilization failure with G-CSF alone in patients undergoing AHSCT for hematological malignancies and for which alternative regimens might be considered. Patients and Methods We conducted a single centre retrospective case-control study of all consecutive patients who underwent at least one mobilization attempt with G-CSF for an AHSCT at the London Health Sciences Centre in London, Ontario, Canada between January 2000 and December 2008. The mobilization regimen consisted of G-CSF 10 μ g/kg/day for 4 days with collection on days 5 and 6. The primary outcome was successful mobilization defined as the collection of at least 2.0×109 CD34+cells/kg. The secondary outcome was the mean yield of stem cells mobilized. Groups (successful vs. unsuccessful mobilization) were compared using unpaired Student's t, Mann-Whitney U, χ2 or Fisher's exact tests, as appropriate. Logistic regression analysis was conducted using an unsuccessful mobilization as the dependent variable. CD34+cells/kg yields were compared using unpaired Student's t tests or one-way ANOVA. Results During the study period, mobilization was attempted in 293 patients (134 MM, 57 HD, 86 NHL, 17 Other). The mean age was 47.5±12.3 years. 251 patients (86.6%; 95%CI 82.3, 90.1) were successfully mobilized and 244 (83.6; 95%CI 78.9, 87.4) underwent AHSCT. The median yield was 3.55 ×106CD34+ cells/kg (Interquartile range 2.50–5.30). On univariate analysis, mobilization success was influenced by the number of previous chemotherapy regimens and underlying diagnosis (P<0.001 each), but not by age (P=0.114), sex (P=0.860) or prior radiotherapy (P=0.454). A diagnosis of NHL and number of previous chemotherapy regimens were predictors of unsuccessful mobilization on multivariate analysis (Table 1). CD34+cells/kg yield was influenced by diagnosis and previous chemotherapy (P <0.001 each). The percentage of patients with successful and unsuccessful mobilization using G-CSF alone according to diagnosis and number of attempts is shown in Table 2. Conclusions HSC mobilization with G-CSF alone yields adequate collections for most patients. Patients with NHL and patients treated with 2 or more previous chemotherapy regimens that fail an initial mobilization attempt have higher failure rates and can be considered for alternate mobilization regimes. Disclosures: Howson-Jan: Merck: Research Funding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.212
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2010
Admission routes2
Has abstractyes

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