Prevalence of Excessive Tearing in Women With Early Breast Cancer Receiving Adjuvant Docetaxel-Based Chemotherapy
Bibliographic record
Abstract
PURPOSE: To define the incidence and impact of tearing in patients receiving adjuvant docetaxel-based chemotherapy and assess for lacrimal duct obstruction (LDO) as a causative factor. PATIENTS AND METHODS: Consecutive patients with early breast cancer recommended for docetaxel-based chemotherapy with no prior ocular symptoms were included. Before and after completion of chemotherapy, patients underwent lacrimal drainage evaluation by computed tomographic dacrocystography (CT-DCG) and ophthalmic assessment. Eye symptoms were assessed at baseline, during, and after completion of chemotherapy. RESULTS: Over a 22-month period, 100 patients were recruited. Asymptomatic LDO was present at baseline in 17% and 18% of patients, as assessed by ophthalmic review and CT-DCG, respectively. Overall, 86% of patients developed tearing, with no significant difference between those who did and did not have LDO (94% v 84%; P = .45). Blepharitis occurred in 37% and minor corneal epitheliopathy in 22% of patients, with neither condition predicting for the development of tearing. Impairment of visual activities was greatest after cycle one (70% of patients) but had decreased to < 5% by 4 months after treatment. CONCLUSION: Tearing occurs in the majority of patients receiving adjuvant docetaxel-based chemotherapy regimens and occurred similarly in patients with and without LDO. There was poor concordance between CT-DCG and ophthalmic examination in the detection of LDO. Tearing and other eye symptoms impaired visual activities, but in nearly all patients, both symptoms and functional impairment were mild and had resolved by 4 months after chemotherapy. Our study demonstrates docetaxel-related tearing is not caused by LDO, and as such, evaluation or stenting of the duct is not considered necessary.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".