B-380 Drift of Freelite on Optilite
Bibliographic record
Abstract
Abstract Background Serum free light chains (sFLC) which include kappa (KFLC), lambda (LFLC) and their ratio (K/L) are used for diagnosis and monitoring of plasma cell dyscrasias (PCDs). In 2002, the Binding Site Freelite assay established reference intervals (RIs) for KFLC, LFLC and K/L. Since that time, renal RIs have been proposed and drift for the Freelite assays has been reported. The objective of this study was to evaluate healthy and renal insufficiency population RIs and examine retrospective data to ascertain the reported assay drift. Methods 260 serum samples were measured using the Freelite assay on the Optilite. Creatinine was measured on the Abbott Alinity and eGFR was calculated. Binding Site’s RIs for KFLC, LFLC and K/L were compared to samples with ≥60 eGFR and ≤59 eGFR samples were compared to the hypergammaglobulinemia population from a previous report in 2002. IFE was used to exclude samples with detectable monoclonal proteins. Retrospective data from University Health Network (UHN) was examined. Results The comparison results for the samples are in the tables below: The data suggest that Freelite has drifted up approximately 300% for KFLC, 150% for LFLC and 200% for K/L. Using 220 000 data points from UHN and applying these recalibration factors, the normal KFLC vs LFLC bivariate distribution appears centered to the well-known ‘0.26–1.65’ K/L 100% diagnostic range. Conclusions Drift of Freelite is confirmed with this study and recalibration factors for Freelite are proposed which are lower KFLC values by 300% and lower LFLC values by 150% for K/L to be centered to 0.26–1.65. Institutions should review their data with Freelite on Optilite and any clinical data to confirm this finding. Drift of this magnitude has the potential to cause false positives for kappa and false negatives for lambda in the diagnosis and monitoring of PCDs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".