Phenotype of diffuse cutaneous systemic sclerosis patients with positive anticentromere antibodies: A systematic literature review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: Anticentromere antibodies (ACA) are typically found in limited cutaneous systemic sclerosis (lcSSc), whereas patients with anti-topoisomerase I antibodies (ATA) usually exhibit diffuse cutaneous involvement (dcSSc). We aimed to investigate the clinical phenotype and outcome of ACA-dcSSc. METHODS: A systematic literature review was conducted (January 1970 to April 2023) across MEDLINE, Scopus and OVID, to define whether SSc patients (population) within the ACA-dcSSc subset (exposure) had higher/lower risk for major organ involvement (interstitial lung disease-ILD, pulmonary hypertension-PH, primary myocardial involvement-PMI, scleroderma renal crisis-SRC) and mortality (outcomes) compared to ACA-lcSSc and ATA-dcSSc. Inclusion criteria were: 1) adult SSc patients with identifiable demographic and clinical features by subtype; 2) observational studies. The quality of the studies was evaluated by the Newcastle-Ottawa Scale. Random-effects meta-analysis was performed to compare odds ratios (OR) for major organ involvement, and the 5- and 10-year mortality of ACA-dcSSc with the other subsets. RESULTS: Out of 1570 hits, six articles were included, identifying 177 ACA-dcSSc patients. In ACA-dcSSc, ILD was more frequent than in ACA-lcSSc (OR 2.60; 95 %CI 1.39-4.87) but less frequent compared to ATA-dcSSc (OR 0.17; 95 %CI 0.10-0.29). ACA-dcSSc patients had a higher prevalence of PH vs. both conventional subsets; PMI and SRC were more frequent in ACA-dcSSc compared to ACA-lcSSc, and similar to ATA-dcSSc. While 5-year survival rates were comparable among the subsets, ACA-dcSSc patients exhibited a lower 10-year mortality than ATA-dcSSc (OR 0.42; 95 %CI 0.2-0.85). CONCLUSION: Although uncommon, the ACA-dcSSc subset appears to have a distinct clinical phenotype, with a better prognosis than ATA-dcSSc.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.025 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".