Limbal stem cell deficiency secondary to systemic paclitaxel (Taxol) for breast cancer: a case report
Bibliographic record
Abstract
BACKGROUND: Paclitaxel (PTX) is an antineoplastic drug widely used in treatments for ovarian, breast, and small-cell lung cancer. Although ocular effects associated with PTX have been previously described, very few studies have specifically reported systemic PTX as a contributing factor for limbal stem cell deficiency (LSCD), which is characterized by the loss of stem cell and barrier function of the limbus leading to progressive pain and reduction in visual acuity. Described here is a unique case where a patient was diagnosed with LSCD secondary to PTX use for the treatment of breast cancer, at doses of PTX far lower than what is reported in current literature. CASE PRESENTATION: A 73-year-old woman with a previous diagnosis of breast cancer with liver metastasis presented with a complaint of increasing pain in the left eye more than the right, along with decreasing visual acuity in both eyes following 3 months of PTX therapy for recurrent liver metastases. Upon examination, best-corrected visual acuity was 20/100 in the right eye and counting fingers on the left. Peripheral neovascularization, stromal scarring, and features of limbal stem cell deficiency (LSCD) were noted on the right cornea. A central neurotrophic ulcer with thinning to 50% and 360 degrees of conjunctivalization were noted on the left. After the discontinuation PTX with doxorubicin as the substitute, there was no further progression of her LSCD, and stabilization of her ocular surface was achieved. CONCLUSION: Although chemotherapy induced LSCD is a relatively rare adverse event, it is essential for clinicians starting new chemotherapy agents to consider the potential ocular toxicities that may result in their use. Ophthalmology review is recommended for patients after starting PTX therapy to assess for signs of LSCD, particularly in patients where drug toxicity can be aggravated due to impaired hepatic function.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| 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".