Line blot immunoassays in idiopathic inflammatory myopathies: retrospective review of diagnostic accuracy and factors predicting true positive results
Bibliographic record
Abstract
Abstract Background Line blot immunoassays (LIA) for myositis-specific (MSA) and myositis-associated (MAA) autoantibodies have become commercially available. In the largest study of this kind, we evaluated the clinical performance of a widely used LIA for MSAs and MAAs. Methods Adults tested for MSA/MAA by LIA at a tertiary myositis centre (January 2016–July 2018) were identified. According to expert-defined diagnoses, true and false positive rates were calculated for strongly and weakly positive autoantibody results within three cohorts: idiopathic inflammatory myopathy (IIM), connective tissue disease (CTD) without myositis, and non-CTD/IIM. Factors associated with true positivity were determined. Results We analysed 342 cases. 67 (19.6%) had IIM, in whom 71 autoantibodies were detected (50 strong positives [70.4%], 21 weak positives [29.6%]). Of the strong positives, 48/50 (96.0%; 19 MSAs, 29 MAAs) were deemed true positives. Of the weak positives, 15/21 (71.4%; 3 MSAs, 12 MAAs) were deemed true positives. In CTD without myositis cases (n = 120), 31/61 (51.0%; 5 MSAs, 26 MAAs) autoantibodies were strongly positive, with 24/31 (77.4%; 0 MSAs, 24 MAAs) true positives. 30/61 (49.2%; 13 MSAs, 17 MAAs) were weakly positive, with 16/30 (53.3%; 0 MSAs, 16 MAAs) true positives. In non-CTD/IIM cases (n = 155), all 24 MSAs and 22 MAAs were false positives; these results included 17 (37.0%; 7 MSAs, 10 MAAs) strong positives. Individual autoantibody specificities were > 98.2 and > 97.5% for weakly and strongly positive results, respectively. True positivity was associated with high pre-test for IIM (odds ratio 50.8, 95% CI 13.7–189.2, p < 0.001) and strong positive (versus weak positive) results (4.4, 2.3–8.3, p < 0.001). Conclusions We demonstrated the high specificity of a myositis LIA in a clinical setting. However, a significant burden of false positive results was evident in those with a low pre-test likelihood of IIM and for weakly positive autoantibodies.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".