Predictors of Blood Transfusion Requirements in Patients Undergoing Autologous Stem Cell Transplantation for Multiple Myeloma.
Bibliographic record
Abstract
Abstract INTRODUCTION: The majority of patients with multiple myeloma undergoing autologous stem cell transplant require transfusion support during the engraftment period. A retrospective study was conducted to identify factors predicting need for blood transfusion in this population: METHODS: Charts were reviewed for all patients undergoing their first autologous stem cell transplantation for multiple myeloma (MM) at the Princess Margaret Hospital (PMH) from July 1, 1999 to Oct 31, 2002. In order to ensure all transfusion needs were tracked, patients who did not receive all follow-up care at PMH were excluded from analysis. Use of blood products during the 90-day period following stem cell infusion (Day 0–90) was determined by review of the hospital blood bank laboratory information system. An RBC transfusion was defined as a single unit, and a platelet transfusion as either one apheresis unit or 3–5 pooled whole-blood derived units. The following factors were evaluated as predictors for receipt of an RBC and/or platelet transfusion: patient age and sex, myeloma subtype (IgG vs. other) and stage (Salmon-Durie I/II vs. III); presence of hematologic comorbidity (active blood loss and being on therapeutic anticoagulation) in the post-transplant period; previous treatment with alkylating agent(s) >1 month and > 4 months; pre-transplant pelvic or lumbar radiation therapy; hemoglobin at transplant admission (Day -2), white blood cell count, platelet count, and creatinine; number of CD34 cells infused. Results were analyzed by both univariate and multivariate logistic regression analysis. RESULTS: Over the 40-month period of review, 280 transplants for MM were performed with 128 cases identified with complete transfusion and follow-up data available. The overall transfusion rate in the post-transplant period was 54.0 % for RBCs, 67.6% for platelets. By univariate analysis, significant predictors for RBC transfusion were female sex (OR 2.03, p =0.046), previous treatment with alkylating agent(s) >1 month (OR 3.29, p =0.013) or > 4 months (OR 4.83, p =0.018) and decreased admission hemoglobin (OR 0.90, p<0.001). In the multivariate model, admission hemoglobin and > 4 months alkylator treatment remained as independent predictors. If hemoglobin was dichotomized as ≥110 vs. <110 g/L, this variable remained the only significant multivariate predictor of RBC transfusion (p < 0.001). In the univariate model, no predictors for platelet transfusion were identified. CONCLUSIONS: Hemoglobin at time of transplant and prior alkylator therapy were predictive of transfusion needs in myeloma patients post-transplant. Although prolonged alkylator exposure can slow engraftment by damaging stem cells for autologous collection, we were not able to consistently identify total stem cell collection volume as an independent predictor for transfusion. Further data collection is planned with aims to develop approaches to blood product conservation in this transplant population.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".