Diagnosis of lymphoproliferative disorders: experience of a single institution in the long-term follow-up of discordant cases.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the usefulness of morphologic diagnosis, immunophenotyping and immunoglobulin (Ig) and T-cell receptor (TcR) gene rearrangement studies in the diagnosis of lymphoproliferative disorder. DESIGN: A retrospective cohort study with clinical follow-up of controversial cases. SETTING: Single institution, tertiary care centre. PATIENTS: All 273 patients whose lymphoid tissue samples were sent for molecular analysis by Southern blotting over a 4-year period. INTERVENTIONS: Patient reports were retrieved from the laboratory data system. Repeat assessment and clinical follow-up was done for discordant cases. OUTCOME MEASURES: Correlation between morphologic features and the results of immunophenotype and gene rearrangement studies of the samples. Value of the different tests in discordant cases. RESULTS: The 273 samples included 130 of non-Hodgkin's lymphoma (NHL), 23 of Hodgkin's disease, 80 of benign lymphoid hyperplasia, 16 of atypical lymphoid hyperplasia and other diagnoses. Of the 130 NHL cases diagnosed by morphologic study, 22 (17%) did not show gene rearrangement. Of the 80 morphologically benign samples, 4 (5%) showed gene rearrangement, and malignant disease developed later in those patients. Five (31%) of the 16 cases of atypical lymphoid hyperplasia showed gene rearrangement. Six of the remaining 11 cases had no detectable gene rearrangement, but hematologic malignant disease developed. No gene rearrangement was detected in Hodgkin's disease samples. One carcinoma showed gene rearrangement. Of the NHL group, 86% of the B cells and 50% of the T cells showed gene rearrangement. Seven samples showed both Ig and TcR gene rearrangement. CONCLUSIONS: Gene rearrangement analyses correlate highly with conventional morphologic diagnosis and phenotyping. The detection of gene rearrangement in lymphoid tissue has a high specificity (99%) and a reasonable sensitivity (83%) to the development of a lymphoproliferative disorder.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".