Epidemiological study of chronic lymphocytic leukemia (CLL) in the province of Manitoba, Canada
Bibliographic record
Abstract
A previous population-based study of survival in Chronic Lymphocytic Leukemia (CLL) patients in the province of Manitoba demonstrated a lower five-year relative survival among CLL patients compared with the age- and gender-adjusted general population. This decreased relative survival was most pronounced among elderly male CLL patients. In this study, we have demonstrated that the reduced five-year relative survival observed in CLL patients compared to the general population of Manitoba may partially be attributed to increased risk of second cancers and non-referral to specialized CLL clinics. The increased risk of second cancers in CLL patients compared to Follicular Lymphoma (FL), a similar indolent B cell malignancy, was only observed after CLL diagnosis indicating that a CLL-specific factor may be responsible for the increased risk of second cancers in these patients. The risk of second cancers is independent of treatment and surveillance bias but is further increased with chemotherapy. A superior outcome in CLL patients who have been referred to the CancerCare Manitoba (CCMB) specialized CLL clinic was observed that was independent of age, gender, treatment and history of previous cancers. This superior outcome was most pronounced in the elderly CLL patients. We propose that CLL patients should be referred to CLL-specific hematologists and, where not possible, that guidelines created by such experts be followed. Appropriate screening for second cancers should be performed during routine follow up of CLL patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".