P‐BB‐75 | The Science … or Not Behind Deferrals of Blood Donors with a History of Cancer
Bibliographic record
Abstract
In the United States, the Food and Drug Administration and the Association for the Advancement of Blood and Biotherapies allow blood centers to screen and defer donors with a history of cancer based upon the discretion of their medical directors (MDs). A working group of America's Blood Centers' (ABC) Scientific, Medical, and Technical Committee developed a survey composed of 31 questions to understand blood center policies for collecting blood from donors with a history of cancer. In June of 2022, the survey was distributed to representatives of 47 ABC blood centers in the United States and Canada by email. Literature of a history of cancer, blood donation safety and transfusion-transmitted cancer was reviewed. Responses were received from 37 (79%) centers. There were no permanent deferrals for benign lesions and for donors with a history of carcinoma or sarcoma who had completed treatment. Donors with a history of leukemia or lymphoma were only accepted if the diagnosis occurred prior to age 18. Donors with a myelodysplastic or myeloproliferative syndrome were deferred permanently at 32 (86.5%) of centers with only 1 (2.7%) accepting with no deferral. Handling of donors with high white blood cell (WBC) counts varied from 8 (21.6%) not notifying the donor to 11 (29.7%) notifying donors at WBC counts of 12,000–16,000/μL. Donors with cancer who were not in active treatment (i.e., prostate cancer) were subject to a variety of deferrals. Blood center response to post-donation reports of cancer ranged from no action because the donor remains eligible 5 (13.5%) to donor deferral 20 (54.0%) (Table). Regarding the prevalence of donors deferred for cancer 17 (45.9%), respondents stated it was 1%–5% of all donors and the remainder 20 (54.1%) did not know. Literature review yielded no evidence of transfusion-transmitted cancer. TABLE 1. Minimum and maximum cancer deferrals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".