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Transfusion Related Alloimmunization In Children: Epidemiology and Effects Of Chemotherapy (TRACE-EC Study)

2013· article· en· W2414432783 on OpenAlexaffabout
Ziad Solh, Uma H. Athale, Rebecca Barty, Erin Jamula, Yang Liu, Grace Wang, Korinne Hamilton, Nancy M. Heddle

Bibliographic record

VenueBlood · 2013
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsHamilton Health SciencesMcMaster Children's HospitalMcMaster University
Fundersnot available
KeywordsMedicineChemotherapyRetrospective cohort studyCancerInternal medicineHematologyCohortPediatricsMalignancy

Abstract

fetched live from OpenAlex

Abstract Introduction Pediatric hematology/oncology patients require numerous transfusions during myelosuppressive chemotherapy which may lead to red cell (RC) alloantibody formation. However, transfusion related alloimmunization in children has not been studied except in the neonatal and hemoglobinopathy populations. Variability of RC alloimmunization rates by cancer diagnosis has not been described and the immunosuppressive effect of chemotherapy on alloimmunization is unknown. One study has shown a reduction in IgM and IgG in pediatric leukemia patients receiving chemotherapy (Martín Ibáñez et al Allergol Immunopathol 2003); hence, one could hypothesize that chemotherapy could suppress the alloimmune response. This study aimed to: 1) report the rate of alloimmunization in children receiving RC transfusions, 2) compare these rates between oncology and non-oncology patients, and 3) compare these rates based on cancer diagnosis and stage. Methods TRACE-EC was a retrospective observational study using a large database containing patient blood utilization information from 3 academic hospitals. Patient inclusion criteria included: age ≥ 4 months and ≤ 17 years old at the time of receiving ³ 1 non-autologous RC transfusion between April 2002 and November 2011. Diagnoses were identified using ICD10 codes. Patients with immune disorders were excluded. Study patient cohort included patients with malignancies and recipients of hematopoietic stem cell transplant (HSCT) to treat a malignancy; control cohort included non-oncology patients who met the inclusion criteria. Patient and blood utilization data were extracted from the database, and chemotherapy data were obtained by retrospective review of patient medical records. Study patients were stratified for analysis based on cancer diagnosis and stage (surrogate for chemotherapy intensity). Cancer stage was categorized as low level (I, II, standard risk) and high level (III, IV, V, high risk). Control patients with hemoglobinopathy were analyzed separately due to their high alloimmunization rate (Aygun et al. Transfusion 2002). Results There were 1253 patients in the study: 944 in control group; 309 in study group. Females made up 49% of control group and 43% of study group. Mean age was 8.6 years (SD 6.4) in control group, and 7.2 years (SD 5.5) in study group. The frequency of alloimmunization and RC utilization by diagnosis in control and study groups is summarized in Table 1. Overall, a statistical difference in the frequency of alloimmunization was not demonstrated between control patients (4.3%) and study patients (5.5%), p=0.40. When hemoglobinopathy patients were removed from the control group, frequency of alloimmunization decreased to 3.8% (p=0.19). Alloimmunization occurred in 5.4% (10/186) and 5.7% (7/123) of patients with a high level and low level cancer stage respectively, p=0.91. HSCT recipients had a higher rate of alloimmunization than non-HSCT but this was not statistically significant (11.4% vs. 4.5% respectively, p=0.07). Alloimmunization occurred in 4.9% of patients with hematologic malignancies and 7.1% of patients with solid tumors (p=0.44). Conclusions This is the first study that has looked at the frequency of alloimmunization in transfused pediatric patients by diagnostic category and cancer stage. The study confirmed high alloimmunization rates in hemoglobinopathy patients. No difference in the frequency of alloimmunization was observed based on cancer diagnosis, stage, or HSCT status. Further studies are needed to assess the effect on alloimmunization of the high RC utilization rate shown in cancer patients and HSCT recipients. Disclosures: Heddle: Health Canada: Research Funding; Canadian Blood Services: Membership on an entity’s Board of Directors or advisory committees, Research Funding; CIHR: 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.035
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.233
Teacher spread0.228 · 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 teacher head, 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
Published2013
Admission routes2
Has abstractyes

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