A Single‐Center Retrospective Study of the Investigation of Monoclonal B‐Cell Lymphocytosis (<scp>MBL</scp>) and Chronic Lymphocytic Leukemia (<scp>CLL</scp>) in Southwestern Ontario: Are We Over‐Investigating?
Bibliographic record
Abstract
INTRODUCTION: Monoclonal B-cell lymphocytosis (MBL) is a common cause of lymphocytosis in older individuals. Although cytogenetic/molecular testing is usually reserved for patients requiring treatment, recent studies suggest that early testing may have a prognostic benefit in MBL and early-stage chronic lymphocytic leukemia (CLL). We evaluated local practices of expanded diagnostics in the MBL/CLL population to assess (1) adherence to international workshop on CLL (iwCLL) guidelines with respect to additional cytogenetic testing and (2) anticipated costs of expanded diagnostic testing. METHODS: A retrospective chart review was conducted on all patients who underwent flow cytometry testing at our center for a suspected hematologic disorder between 2016 and 2021. Patients were subdivided into CLL, high-count MBL, and low-count MBL, and cytogenetic/molecular testing numbers were calculated as well as associated costs. RESULTS: Of 974 patients who underwent flow cytometry testing, 100 had CLL, 49 had high-count MBL, and 5 had low-count MBL. Cytogenetic testing was performed in 54/100 CLL, 2/49 high-count MBL, and 0/5 low-count MBL patients. Most testing occurred in symptomatic CLL patients (38/54) especially after the 2018 iwCLL guideline changes. The estimated cost of cytogenetic testing for the 56 patients tested was $27 600. Expanding testing to all patients would have incurred an additional $87 900 during the study period. CONCLUSION: This retrospective study shows high adherence to iwCLL guidelines for the investigation of early-stage CLL/MBL, especially after the 2018 guideline changes. Future studies are needed to weigh the benefits of improved prognostication against resources/costs required by expanded cytogenetics/molecular testing in these common hematologic conditions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".