Sarcoidosis and lymphoma: a comparative study
Bibliographic record
Abstract
AIM: To assess the clinical features and outcome of lymphoma when associated with sarcoidosis and to determine whether this association gives lymphoma a better prognosis. DESIGN: Multicentre retrospective cohort study. METHODS: Retrospective chart review. RESULTS: Twenty-one patients were included (9 males, 12 females). Median age at sarcoidosis diagnosis was 48 years (range: 24-68 years). In 14 cases, lymphoma occurred within a previously known sarcoidosis. Five patients received a concomitant diagnosis of sarcoidosis and lymphoma, whereas lymphoma preceded sarcoidosis in two patients. Three patients were diagnosed with Hodgkin's lymphoma and 18 patients with non-Hodgkin's lymphoma (diffuse large B-cell lymphoma (DLBCL) (n = 11), follicular lymphoma (n = 2), chronic lymphocytic leukemia/small lymphocytic lymphoma (n = 2), anaplastic large cell lymphoma ALK + (n = 1), angioimmunoblastic T-cell lymphoma (n = 1) and T-cell prolymphocytic leukemia (n = 1)). Thirteen patients were alive and in complete remission. Median age at the time of diagnosis of sarcoidosis was lower in patients with concomitant lymphoma compared with patients with sarcoidosis preceding lymphoma (34 years vs. 51 years, P = 0.01). Patients presenting with DLBCL associated with sarcoidosis were compared with DLBCL without sarcoidosis. No statistical difference was found in the risk of death or progression between the two groups (P = 0.685). CONCLUSIONS: We report here the largest series of lymphoma associated sarcoidosis patients. As opposed to previous studies, we observed a predominance of patients with DLBCL. Our study confirms the concept of the sarcoidosis-lymphoma syndrome. Large B-cell lymphoma does not have a better prognosis when associated with sarcoidosis.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".