Incidence and Implications of Skin Cancers in Cancercare Manitoba Chronic Lymphocytic Leukemia (CLL) Clinic Patients
Bibliographic record
Abstract
Abstract Background:We previously conducted a population-based study on chronic lymphocytic leukemia (CLL) in Manitoba, which showed that second cancers are twice as common and skin cancers eight times as common in this disease, as compared to an age- and sex-matched control population and patients with follicular lymphoma. It is postulated that this is related to immunosuppression, secondary to the disease and chemo-immunotherapy. Here we set out to investigate rates and types of skin cancers in CLL patients and how these influence the outcome of CLL patients. Methods: Newly diagnosed CLL patients attending the CancerCare Manitoba CLL Clinic from the January 1st, 2002 until December 31st, 2012 were selected for this study. Patients were followed until December 31, 2014. Cox Proportional Hazard models were constructed to predict hazard's ratios (HR) and 95% confidence intervals (95% CI) for survival as well as risk of non-cutaneous malignancies. Association between skin cancer and CLL prognostic markers were investigated by Fisher's Exact test, Student's t-test and logistic regression analysis. P-value <0.05 was considered statistically significant. Statistical analysis was performed using SAS Studio 3.5. Results: There were 582 CLL patients in this study. The median age was 67 years (range 36-99 years) with a M:F ratio of 1.6:1. This compares with a median age of 71.5 years and a M:F ratio of 1.3:1 in the Manitoba CLL population. The median follow-up for the study was 5.8 years (range 0.1-13.0 years). There were 131 (23%) CLL patients with at least one skin cancer; 73 (56%) had their first skin cancer before the diagnosis of CLL and 58 (44%) after. Rates of first skin cancer diagnoses were constant before CLL diagnosis (5.2 per 1000 CLL cases), but began to increase three years prior to the CLL diagnosis (10.2 per 1000 CLL cases) and continued to increase after the CLL diagnosis (22.7 per 1000 CLL cases). There were a total of 368 skin cancers; 208 (57%) were basal cell carcinomas (BCC), 92 (25%) were squamous cell carcinomas (SCC), 47 (13%) were Bowen's disease, 18 (5%) were melanomas, and three (1%) were Merkel cell carcinomas. Interestingly, multiple skin cancers with varying histologies occurred in almost half the patients. When the total number of skin cancers/year was assessed, the number started to increase seven years before the CLL diagnosis and continued to increase yearly after the CLL diagnosis. Within the follow-up period, 154 (27%) patients died, with the major causes of death being CLL and second malignancies. However, the presence of skin cancers did not appear to influence survival. There were a total of three deaths due to skin cancers; two patients died of melanoma and one from BCC. However, the presence of a skin cancer, in CLL cases without a history of a solid tumor, increased the risk of a non-cutaneous malignancy by seven-fold (HR 7.55, 05% CI 3.92 - 14.53, p<0.0001). The presence of a skin cancer prior to the diagnosis of CLL did not predict CLL aggressiveness at diagnosis, as evaluated by Rai stage, Zap-70 or CD38 status, immunoglobulin levels or IGHV mutational status. However, for those patients developing their first skin cancer after the CLL diagnosis, the risk of developing a skin cancer correlated with the unmutated IGHV status (HR 1.54, 95% CI 1.01 - 2.34, p=0.0462) and baseline CD38 positivity (HR 1.58, 95% CI 1.02 - 2.44, p=0.0405). Interestingly, the risk of developing skin cancer was not increased by chemotherapy. Discussion: In summary, with a median follow-up of 5.8 years, 23% of patients had a skin cancer, half before the diagnosis of CLL and half after the CLL diagnosis. The incidence of skin cancers increased prior to the diagnosis of CLL, indicating that immunosuppression possibly preceded the diagnosis of CLL by years. The increased risk of developing skin cancers in patients with unmutated IGHV and CD38 positivity indicates that CLL patients with a more aggressive disease are more likely to develop skin cancer, probably due to a more pronounced immune deficiency. The diagnosis of skin cancer in CLL patients was associated with a seven-fold increased risk of developing a solid tumour. These results underscore the need for close monitoring and active surveillance of CLL patients for skin and other cancers throughout their disease course, by clinicians experienced in skin and other malignancies. Disclosures No relevant conflicts of interest to declare.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".