Paraneoplastic pyoderma gangrenosum in solid organ malignancy: a literature review
Bibliographic record
Abstract
Pyoderma gangrenosum (PG) is a rare destructive, ulcerative, and inflammatory cutaneous disease. PG can be associated with inflammatory bowel disease (IBD), arthritis, autoinflammatory syndromes, and hematological malignancies. Multiple reports in the literature have found an association between PG and solid organ tumors. This article provides a summary and review of PG in patients with solid organ malignancies. We performed a PubMed search using the terms pyoderma gangrenosum, paraneoplastic pyoderma gangrenosum, cancer, malignancy, tumor, and solid organ malignancy. Out of 529 papers screened, 19 relevant cases were included that reported patients above the age of 12 years old with antecedent, coincident, or subsequent occurrence of PG in association with a solid organ malignancy. The most common malignancies associated with PG were found in the breast (n = 6, 31.6%). In a majority of the cases, the site of PG was found to be the lower extremities (n = 12, 63.2%). Almost all cases were presented with ulcerative PG subtype (n = 18, 94.7%). Moreover, 78.9% of cases (n = 15) were reported to have PG prior to tumor diagnosis. PG lesions resolved in 100% of patients after either tumor or PG-specific treatment. We identified a strong temporal relationship between ulcerative PG and its associated solid organ malignancy. Other associations with breast cancer and lower extremity location exist but are not as strong.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".