Lymphoproliferative and Intestinal Malignancies in 214 Patients With Biopsy-defined Celiac Disease
Bibliographic record
Abstract
Prior studies have suggested that the incidence of some neoplastic disorders, particularly malignant lymphoma, is increased in celiac disease. In the present study, lymphoproliferative and intestinal cancers in 214 consecutive biopsy-defined celiac disease patients, including 148 females (69.2%) and 66 males (30.8%), seen by a single clinician over more than 20 years were tabulated. Of the 214 patients, 151 were diagnosed with celiac disease before age 60 and 63 at or after age 60. In total, 18 malignant lymphomas and 3 small intestinal adenocarcinomas were detected. While the overall incidence of malignant lymphoma was 8.4%, similar to other European centers, the incidence in elderly celiacs in this study was 22.2%. Celiac disease was detected before or even after the diagnoses of lymphoma or small intestinal adenocarcinoma were established. In some, epithelial lymphocytosis was evident in gastric, colonic, or biliary ductal epithelium. In addition, other immune-mediated disorders, dermatitis herpetiformis, and autoimmune thyroid disease were common, suggesting a distinct clinical and pathologic phenotype in celiac disease that may predispose to malignant complications. Finally, except for a single hypopharyngeal carcinoma in a celiac disease patient with a malignant lymphoma, other malignant disorders of esophagus, stomach, and colon were not detected.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".