Effect of Capecitabine on Mean Corpuscular Volume in Patients With Metastatic Breast Cancer
Bibliographic record
Abstract
Capecitabine is a novel oral chemotherapy agent designed to generate 5-fluorouracil (5-FU) preferentially in tumor tissue, and is the most effective therapy for anthracycline and taxane-resistant breast cancer. Macrocytosis has not been previously reported in association with capecitabine therapy. We performed a retrospective review of consecutive metastatic breast cancer (MBC) patients receiving standard 21-day cycles of oral capecitabine therapy at a single center during the year 2000. Patients were assessed prior to each cycle with clinical examinations and complete blood counts. Seventy-six women (median age 52 years, median follow-up 273 days) met inclusion criteria for the study. Prior to treatment, the average mean corpuscular volume (MCV) was 91.6 fl (normal range 80-100 fl). During chemotherapy, MCV increased in a dose-dependent and time-dependent manner. Fifty-seven percent of study patients developed macrocytosis (MCV > 100 fl) while on capecitabine therapy; 85% of women who received at least nine cycles of therapy exhibited macrocytosis. Development of macrocytosis was independent of anemia, thrombocytopenia, neutropenia, liver metastasis, and hepatic dysfunction; however, increases in MCV were more pronounced in 5-FU-naive patients. Alternative causes of macrocytosis were not identified in patients without coexisting anemia. We conclude that capecitabine therapy produces time-dependent and dose-dependent macrocytosis in MBC patients. However, macrocytosis was not associated with anemia or overt myelosuppression. When capecitabine-treated breast cancer patients develop macrocytosis in the absence of anemia, investigations of other causes of macrocytosis are not warranted.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".