Biomarkers of rheumatoid arthritis-associated interstitial lung disease: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Interstitial Lung Disease (ILD) represents the most common extra-articular manifestation of Rheumatoid Arthritis (RA) and is a major cause of mortality. This study aims to identify and evaluate biomarkers associated with Rheumatoid Arthritis-Associated Interstitial Lung Disease (RA-ILD). Methods: We searched PubMed, Cochrane Library, EMBASE, and Web of Science databases for studies related to biomarkers of RA-ILD up until October 7, 2023. The Newcastle-Ottawa Scale (NOS) and standards recommended by the Agency for Healthcare Research and Quality (AHRQ) were used for quality assessment, and meta-analysis was conducted using Stata18.0 software. Results: A total of 98 articles were assessed for quality, 48 of which were included in the meta-analysis. 83 studies were of high quality, and 15 were of moderate quality. The meta-analysis showed significant differences in biomarkers such as C-Reactive Protein (CRP), Erythrocyte Sedimentation Rate (ESR), Anti-Cyclic Citrullinated Peptide (anti-CCP) antibody, Rheumatoid Factor (RF), Krebs von den Lungen-6 (KL-6), Surfactant Protein D (SP-D), Carcinoembryonic Antigen (CEA), Carbohydrate Antigen 19-9 (CA19-9), Matrix Metalloproteinase-7 (MMP-7), C-X-C Motif Chemokine Ligand 10 (CXCL-10), and Neutrophil-to-Lymphocyte Ratio (NLR) between RA-ILD patients and RA patients. However, Platelet-to-Lymphocyte Ratio [Platelet-to-Lymphocyte Ratio (PLR)], Cancer Antigen 125 [Cancer Antigen 125 (CA-125)], and Cancer Antigen 153 [Cancer Antigen 153 (CA-153)] did not show significant differences between the two groups. KL-6, MMP-7, and Human Epididymis Protein 4 (HE4) are negatively correlated with lung function, and KL-6 is associated with the prognosis of RA-ILD. Conclusions: Biomarkers hold promising clinical value for prediction, diagnosis, severity assessment, and prognosis evaluation in RA-ILD. However, these findings need to be validated through multicenter, large-sample, prospective cohort studies. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023448372.
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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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.040 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".