With Minor Salivary Gland Biopsy in Sjögren Syndrome, Is a Negative Result Possible?
Bibliographic record
Abstract
In this issue of The Journal , Sharma, et al 1 report on the differences among 3 groups of patients with Sjögren syndrome (SS). The first had a focus score (FS) of < 1 in the minor salivary gland (MSG) biopsy, another had an FS ≥ 1, and the other had an FS of zero. Patients without focal lymphocytic infiltration (i.e., FS = 0) exhibited a low frequency of anti-La antibodies, corneal compromise, and hypergammaglobulinemia, and had no elevated expression of interferon-regulated genes, but did have systemic disease. However, all these patients showed positive anti-Ro antibodies. These results indicate that anti-Ro antibodies may be a key factor influencing the development of the disease, and that the MSG biopsy may be negative in patients with SS. SS is a chronic autoimmune disease characterized by a progressive lymphocytic and plasma cell infiltration that mainly affects the salivary and lachrymal glands and leads to xerostomia and keratoconjunctivitis sicca (sicca symptoms). The diagnosis of SS is based on the combination of symptoms (sicca symptoms) and the presence of autoimmune characteristics: activation of B cells (i.e., presence of auto-antibodies) and/or T cells (i.e., positive MSG biopsy)2. The classification of the disease is currently based on the American-European consensus group classification criteria [American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR)], which include serological tests, clinical findings, and histological examination3. The presence of autoantibodies or a positive MSG biopsy is mandatory3. MSG biopsy plays an essential role in the diagnosis, stratification, and prognosis of SS as well as in the differential diagnosis of the disease (i.e., sarcoidosis, amyloidosis, etc.)4,5. In our view, for diagnostic purposes the MSG biopsy is preferred to parotid and lacrimal gland biopsies because it is less invasive and safer while offering similar … Address correspondence to Dr. J.M. Anaya, CREA, School of Medicine and Health Sciences, Universidad del Rosario, Carrera 24 No. 63C-69, Bogotá, Colombia. E-mail: juan.anaya{at}urosario.edu.co
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".