T-cell clonality is detected in a high frequency among patients with incidental lymphocytosis by PCR assays for <i>TCR</i> gene rearrangements
Bibliographic record
Abstract
AIMS: Clonal expansion of lymphocytes may account for asymptomatic lymphocytosis. Unlike monoclonal B lymphocytosis, the detection of T-cell clones is difficult using immunophenotype-based assays. This study aimed to evaluate PCR-based clonality assays for the identification of T-cell clones among patients with unexplained lymphocytosis. METHODS: We incorporated the BIOMED-2 multiplex PCR into the investigation of peripheral lymphocytosis. Clonality analysis was performed with three reactions for TCRβ and two reactions for TCRγ gene rearrangements. The analysis was performed with blood specimens from a total of 150 adult patients who presented with incidental lymphocytosis. RESULTS: PCR assays were validated using confirmed T-cell malignancies and the detection sensitivity was determined at a level of 2%. Using the TCRβ and TCRγ combination, 25 (16.6%) of 150 patients were found to have clonal TCR arrangement. Patients who harboured clonal T cells presented with a mild to moderate absolute lymphocytosis, with a median lymphocyte count of 4.5 × 10(9)/l (range 3.7-9.8 × 10(9)) and the absence of other haematological abnormalities. Immunophenotyping confirmed T-cell lymphocytosis with an increase in CD8 T cells in the majority of patients. CONCLUSIONS: This study demonstrated the use of PCR assays for the effective detection of clonal T lymphocytosis. Our data indicate a high prevalence of silent T-cell clones among patients with peripheral lymphocytosis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".