Hidradenitis Suppurativa and the Association With Hematological Malignancies
Bibliographic record
Abstract
BACKGROUND: Hidradenitis suppurativa (HS) is a chronic inflammatory disease affecting skin sites with a high density of apocrine glands. HS commonly presents after puberty, with most patients diagnosed in the second decade of their life. Several studies have investigated smoking, obesity, hypertension, diabetes, and dyslipidemia as possible underlying risk factors for HS. However, we encountered 2 patients with a long-standing history of untreated leukemia who developed late-onset HS. OBJECTIVE: To investigate the presence of malignancy as an underlying risk factor for development of HS. METHOD: The PubMed and Scopus databases were searched for keywords such as hidradenitis suppurativa, malignancy, cancer, and epidemiology. OBSERVATION: Only 1 retrospective Swedish study with 2119 patients investigated the prevalence of cancer, including 6 hematopoietic malignancies, in HS patients. However, the study did not assess the timeline of developing HS in relation to the cancer diagnosis. We report 2 patients with a long-standing history of hematopoietic cancers who received no continuous treatments for their malignancies and developed late-onset HS: a 60-year-old male patient with hairy cell leukemia and a 68-year-old male patient with chronic lymphocytic leukemia who developed HS later in life. CONCLUSION: Multiple epidemiologic studies found the average age of HS diagnosis to be well prior to the fourth decade of life. The latency of the HS diagnosis as well as the presence of long-standing leukemia in both of our patients raises the necessity for assessing the possibility of malignancy, especially hematopoietic cancer, as a risk factor for HS. LIMITATION: This is a small retrospective analysis including only 2 patients. Larger studies would better assess the role of malignancy, leukemia in particular, as a possible risk factor for development of HS.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".