Case Report: Chemotherapy-Associated Systemic Sclerosis: Is DNA Damage to Blame?
Bibliographic record
Abstract
Systemic sclerosis, also known as scleroderma, is an autoimmune disease characterized by cutaneous and visceral fibrosis, immune dysregulation, and vasculopathy. Generally, the degree of skin fibrosis is associated with an increased likelihood of visceral organ involvement. Its pathogenesis is poorly understood; however, it is clear that changes in both the innate and adaptive immune responses are associated with fibroblast dysfunction and vascular damage. Further, DNA damage has been postulated as one of the triggering factors in systemic sclerosis, although the association of DNA damage with the progression of this disease is more poorly established. Recently, abnormal DNA damage response repair pathways have also been identified in patients with systemic sclerosis, suggesting that cells from patients with this disease may be more susceptible to DNA damaging agents. Chemotherapeutic drugs and other DNA damaging agents have been associated with the development of systemic sclerosis, as these agents may provide additional "hits" that promote abnormal DNA damage responses and subsequent inflammatory changes. Herein, we present the case of a 39-year-old female who developed scleroderma after the treatment of her breast cancer with chemotherapeutic agents. Her scleroderma was subsequently successfully treated with autologous hematopoietic stem cell transplantation. We also completed a literature review for previously published cases of chemotherapy associated with systemic sclerosis and highlighted a role of DNA damage in promoting the disease. Our case is the first case of chemotherapy associated with systemic sclerosis treated with hematopoietic stem cell transplantation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".