Risk of malignancy associated with chronic lymphocytic leukemia: A population based Canadian study
Bibliographic record
Abstract
20020 Background: Patients with Chronic Lymphocytic Leukemia (CLL) may have an increased risk of other malignancies. Available literature reports on malignancies that develop after the diagnosis of CLL, but does not discuss malignancies that precede the diagnosis of CLL. Methods: All patients diagnosed with CLL between 01/1998 and 12/2003 were extracted from the provincial cancer registry and a centralized flow cytometry database. All other malignancies were obtained from the cancer registry. Dates of diagnoses were compared. A malignancy within 30 days before or after the diagnosis of CLL was considered synchronous with that diagnosis. Results were compared with the age-adjusted incidence of cancer in the province, excluding CLL. Results: Of the 713 cases of CLL, 333 invasive cancers and 38 in situ neoplasia were identified before, synchronous to, or after the diagnosis of CLL. Synchronous malignancies occurred in 4% of cases. The Standardized Incidence Ratio (SIR) for other malignancy subsequent to CLL was 1.40 (95% confidence interval [CI] 1.09–1.80) derived from 65 tumors for males, and 1.29 (95% CI 0.90–1.80) from 35 tumors for females. Mean time to diagnosis of subsequent cancer was 2.0 years (standard deviation[SD] 1.5). The SIR for other malignancy in the 5 years preceding the diagnosis of CLL was 1.36 (95% CI 0.93–1.94) from 31 tumors for males and 0.77 (95% CI 0.54–1.08) from 35 tumors for females. Mean time from diagnosis of preceding malignancy to CLL was 9.4 years (SD 8.7). Conclusions: In this population based study, patients with CLL are at increased risk of other invasive and in situ cancers. This risk is apparent after but not before the diagnosis of CLL, particularly in males. The mechanism of this increased risk may be acquired with the presence of CLL through an underlying but undetermined mechanism, as opposed to an inherent or more longstanding predisposition to malignancy. No significant financial relationships to disclose.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".