Serum Free Light Chain Assay and κ/λ Ratio: Performance in Patients With Monoclonal Gammopathy-High False Negative Rate for κ/λ Ratio
Bibliographic record
Abstract
BACKGROUND: Serum free light chain assay (SFLCA) and κ/λ ratio, and protein electrophoretic methods are used in the diagnosis and monitoring of monoclonal gammopathies. METHODS: Results for serum free light chains, serum and urine protein electrophoreses and immunofixation electrophoreses in 468 patients with a diagnosis of monoclonal gammopathy were compared. The results of the two methods were graded as concordant, non-concordant or discordant with the established diagnoses to assess the relative performance of the methods. Results of κ/λ ratio in samples with monoclonal protein detectable by electrophoretic methods were also analyzed. RESULTS: Protein electrophoreses results were concordant with the established diagnoses significantly more often than κ/λ ratio. The false negative rate for κ/λ ratio was higher than that for electrophoretic methods. κ/λ ratio was falsely negative in about 27% of the 1,860 samples with detectable monoclonal immunoglobulin. The false negative rate was higher in lesions with lambda chains (32%) than those with kappa chains (24%). The false negative rate for κ/λ ratio was over 55% in samples with monoclonal gammopathy of undetermined significance. Even at first encounter, the false negative rates for κ/λ ratios for monoclonal gammopathy of undetermined significance, smoldering myeloma and multiple myeloma were 66.98%, 23.08%, and 30.15%, respectively, with false negative rate for lambda chain lesions being higher. CONCLUSIONS: , is not diagnostic of monoclonal gammopathy. A normal κ/λ ratio does not exclude monoclonal gammopathy. False negative rates for lesions with lambda chain are higher than those for lesions with kappa chains. Electrophoretic studies of urine are underutilized. Clinical usefulness and medical necessity of SFLCA and κ/λ ratio is of questionable value in routine clinical testing.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".