lncidence and lmplications of Skin Cancers in Chronic Lymphocytic Leukemia (cLL)
Bibliographic record
Abstract
A recent population-based study in Manitoba showed that skin cancers are very common in chronic lymphocytic leukemia (CLL), probably as a result of immunosuppression. We have now studied 592 newly diagnosed CLL patients attending the CancerCare Manitoba CLL Clinic from 2002 until 2012. The median age at diagnosis of CLL was 67 years (range, 36-99) with a M:F ratio of 1.6.1. The median follow-up was 4.63 years (range, 0.0't-11.00 years). There were 133 (22.39o/o) patients with skin cancers, half having skin cancers before the CLL diagnosis (pre- CLL) and half following the diagnosis (post-CLL). ln the pre-CLL group, the risk of skin cancer increased 5-6 years before the CLL diagnosis indicating that immunosuppression can precede the diagnosis of CLL. For all patients, the risk of skin cancer correlated with Rai stage and duration of disease. Of 368 total skin cancers, 208 (56.520lo) were basal cell carcinomas (BCC), 92 (25.00yo) squamous cell carcinomas (SCC), 47 (12.77o/o) Bowen's disease, 18 (4.89%) melanomas, and 3 (0.82o/o) Merkel cell carcinomas (MCC). Multiple skin cancers occurred in half the patients. 22.72o/o patients died, usually from second malignancies or CLL. There were three deaths from skin cancer, two melanomas and one BCC. ln summary, one-quarter of CLL patients developed skin cancer, and this was predictive for developing a solid tumor. CLL patients, particularly those with advanced Rai stage, require regular surveillance screening for other cancers, especially those of the skin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".