Diagnostic Test Accuracy of Serum and Urine Immunofixation and Free Light Chains in the Diagnosis of Light Chain Amyloidosis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: Light-chain (AL) amyloidosis is caused by the secretion of immunoglobulin light chains by monoclonal plasma cells. The increase in the levels of these monoclonal proteins may proceed the development of any clinical symptoms, and their identification in the serum and urine remains an integral part of establishing a diagnosis of AL amyloidosis. This systematic review aims to evaluate the diagnostic test accuracy of serum immunofixation (SIFE), urine immunofixation (UIFE), and free light chain (FLC) ratio for the diagnosis of AL amyloidosis. Methods: As part of the ASH AL Amyloidosis Diagnostic Guideline, we performed systematic reviews for 7 prioritized PICO questions related to the screening, diagnosis and organ involvement evaluation of AL amyloidosis. Electronic searches were conducted on PubMed, Embase, and the Cochrane Central Register of Controlled Trials from inception till January 2024. Two reviewers independently and in duplicate performed title and abstract screening and full text article screening on LASER AI, with conflicts resolved by a third reviewer. Eligible studies were those that included patients who performed one of the three tests (SIFE, UIFE, and κ/λ FLC) and had their AL amyloidosis diagnosis confirmed via a biopsy. Diagnostic test accuracy measures of interest were sensitivity, specificity, positive and negative predictive value. Statistical analysis was performed on OpenMeta[Analyst]. Grading of Recommendations Assessment, Development and Evaluation (GRADE) was used to assess the certainty of evidence. Results: After deduplication, we retrieved 29,237 studies from electronic databases. 31 studies with 3973 patients reported on the use of serum immunofixation (SIFE) with a pooled sensitivity of 72.4% (95% CI 68.1%-76.4%). 27 studies with 2855 patients reported on the use of urine immunofixation UIFE for the diagnosis of AL amyloidosis with a pooled sensitivity of 78.6% (95% CI 74.6%-82%). 29 studies with 5305 patients reported on the use of κ/λ FLC ratio amyloidosis with a pooled sensitivity of 79.9% (95% CI 73.7%-84.9%). 24 studies reported on the use of both SIFE and UIFE with a sample size of 3751 patients and a pooled sensitivity of 90% (95% CI 85.3%-93.3%). 3 studies reported on the use SIFE and κ/λ FLC ratio with 321 patients and a pooled sensitivity of 97.7% (95% CI 95.6%-99.9%). Finally, we identified 10 studies that performed SIFE,UIFE, and κ/λ FLC ratio concurrently with 1926 patients and a pooled sensitivity of 99% (95% CI 97%-99.7%) of all three tests and considering a result abnormal if any of the components had a positive result. We also identified 5 studies with 957 patients reporting on the concurrent use of SIFE, UIFE, and κ/λ FLC ratio for the diagnosis AL amyloidosis and differentiation of AL from ATTR amyloidosis in a population of patients with suspected cardiac amyloid involvement, the pooled sensitivity was found to be 99%(95% CI 99%-100%) and with a pooled specificity of 77%(95% CI 75%-80%). Certainty of evidence moderate for all outcomes. Conclusion: The combined use of SIFE, UIFE, and κ/λ FLC ratio has a high sensitivity for the diagnosis of AL amyloidosis, and the tests remain a valuable initial screening of AL amyloidosis and differentiation from ATTR amyloidosis.
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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 | 0.020 | 0.071 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.035 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".