Patient Tailored Crossmatch, Do Islet Cell and Pancreas Transplants Call for a Different Fit?
Bibliographic record
Abstract
Introduction: We have previously demonstrated that pre-formed donor specific antibodies (DSA) to human leukocyte antigens (HLA) are associated with reduced islet function and survival but positive (pos) T and/or B cell flow crossmatch (FCXM) alone is not. (1) Thresholds for FCXM are established using HLA un-sensitized normal samples, which may not reflect serum background reactivity in all patient populations. Here we re-evaluated T and B cell FCXM pos thresholds using un-sensitized kidney and islet cell/pancreas transplant patient sera. Methods: The FCXM method includes incubating pronased treated donor lymphocytes with patient serum followed by detection of IgG antibody on the CD3 labelled donor T and CD19 labelled B cells. (2) Determination of routine positive (pos) threshold was determined by FCXM with 10 cells and 20 sera from un-sensitized normal donors. Patient FCXM data from July 2013 to December 2015 were examined. Calculated panel reactive antibody (cPRA) values were determined using the Canadian cPRA tool. A 0 cPRA was assigned to all patients with no HLA antibody determined by threshold of MFI 1000 and no evidence of reactivity pattern to HLA epitopes. The median channel value (MCV) shift above the negative control serum was determined for all FCXM and results were separated by donor peripheral blood (PBL) or spleen (SPL) source as per routine threshold determination. The mean and standard deviation (SD) were calculated for each patient and cell type. Results: A total of 1417 FCXM were performed; 367 patients had 0 cPRA. The total number of kidney and islet transplant patients was 166 and 63, respectively. The breakdown of PBL vs SPL cell source is shown Table 1. The FCXM pos cut-offs determined using the kidney sera are very similar to those established from normal controls. The pos thresholds calculated using islet/pancreas patient sera are higher. Conclusion: Islet and pancreas patient sera may have inherent, non-HLA specific reactivity to T and B cells, which affects the interpretation of FCXM. The current thresholds may result in false positive T and B FCXM in some islet and pancreas transplant patients. Our data suggest that the crossmatch must be interpreted in the context of HLA antibody specificity information. Higher pos thresholds for FCXM may be required in this patient population however an increased threshold requires validation in the setting of known DSA to ensure that false negative FCXM results do not result.Table 1: Flow cytometry crossmatch Tand B thresholds as established using serum from kidney vs. islet cell/pancreas transplant patients.References: 1. Campbell PM, Salam A, Ryan EA, Senior P, Paty BW, Bigam D, et al. Pretransplant HLA Antibodies Are Associated with Reduced Graft Survival After Clinical Islet Transplantation. American Journal of Transplantation. 2007 May;7(5):1242-8. 2. Liwski R, Pochinco D, Tinckam K, Gebel H, Campbell P, Nickerson P. 30-or: Canada-Wide Evaluation of Rapid Optimized Flow Crossmatch (rofcxm) Protocol. Human Immunology. 2012 October 2;73:26-.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".