Cutaneous Malignancies in Tattoos, a Case Series of Six Patients
Bibliographic record
Abstract
BACKGROUND: A variety of side effects following the tattooing of the skin were reported over the years. Analytical studies showed that some tattoo inks contain harmful compounds. METHODS: We presented six patient cases with cutaneous malignancies in tattooed skin and performed an extensive literature research. RESULTS: Two patients with black ink tattoos that were diagnosed with malignant melanoma raises the number of described cases to 36 patients. One of the patients developed an immunologic reaction limited to the tattoo area after treatment with a targeted immune therapy. In the other patient, the malignancy (malignant melanoma) was fatal. Basal cell carcinoma was seen in four patients with tattoos containing varying ink colors (black, green, red). This increased the number of described patient cases to 18. Although some ink components and their cleavage products have carcinogenic properties, epidemiological evidence for a causative correlation fails. Further epidemiologic studies on tattoos and malignancies, as well as on the appearance of naevi in tattoos, are necessary. Determining the type of mutation might be helpful to separate sun-induced tumors from skin cancers due to other pathogenic mechanisms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".