Mass spectrometry in IgG4-related disease diagnosis
Bibliographic record
Abstract
We compared liquid chromatography tandem mass spectrometry (LC-MS/MS) against Binding Site immunonephelometry (BSIN) with regards to these methods' abilities to diagnose IgG4-related disease (IgG4-RD). IgG subclasses were gathered from laboratory from December 2011 to December 2020. The IgG4-RD positive and negative patients were diagnosed according to the ACR/EULAR classification criteria by extensive chart review. Both methods' results were compared in terms of test characteristics. For BSIN, there were 43 IgG4-RD positive cases and 174 disease negative cases, while for LC-MS/MS, there were 102 IgG4-RD positive cases and 562 disease negative cases. The majority of IgG4-RD patients by BSIN and LC-MS/MS had an elevated IgG4 level, 81% and 86%, respectively. For BSIN, the ROC curve, cut-off value of 1.25 g/L, had a sensitivity of 81% and a specificity of 84%. For LC-MS/MS, the ROC curve, cut-off value of 1.25 g/L, had a sensitivity of 86% and a specificity of 84%. The responder index score to IgG4 level r-correlation value for BSIN and LC-MS/MS was 0.5 and 0.6, respectively. In our center, LC-MS/MS and BSIN are equivalent test methods in IgG4-RD diagnosis. IgG4 level does correlate with disease activity by the responder index. LC-MS/MS is a valid and equally reliable alternative to BSIN in the diagnosis of IgG4-related disease.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".