Neutropenic complications with neo/adjuvant adriamycin and cyclophosphamide in early stage breast cancer patients: A prospective study at the McGill University health center.
Bibliographic record
Abstract
e12127 Background: We prospectively investigated the incidence of neutropenic complications (NC) with neo/adjuvant AC (doxorubicin and cyclophosphamide) chemotherapy (CTX) among early-stage breast cancer (ESBC) patients. NC was defined as febrile neutropenia (FN), dose delay/reduction or need of granulocyte colony-stimulating factors (G-CSF) to proceed with CTX. Methods: This was a single-center, observational, prospective cohort study conducted at the McGill University Health Center. All ESBC patients who received AC regimen as neo/adjuvant CTX between February 2016 and February 2017 were included. Hazard ratios (HRs) with 95% confidence intervals (CIs) of predictors of NC were estimated using Cox-proportional hazards models. Results: A total of 118 patients, corresponding to 409 cycles of AC were analyzed. Most patients underwent Q3week cycles (83.1%). Median age was 52 years old (IQR 43-61). Prophylactic G-CSF was given to 20 dose-dense patients and 10 Q3weeks patients. In patients not receiving prophylactic G-CSF, 57 (65.5%) manifested at least one episode of NC (corresponding to an incidence rate of 26.4%/cycle of CTX [95% CI: 20.0%-34.2%]), of which 9 developed FN requiring hospital admission. In the final prediction model, body mass index < 25 kg/m2(HR: 2.36, 95% CI: 1.16-4.78) and increasing glucose levels (HR: 1.56, 95% CI: 1.14-2.14) were significantly associated with NC. Baseline absolute neutrophil count (ANC) was protective. Conclusions: The incidence of NC in our prospective study is significantly higher than previously reported in retrospective studies (26.4% vs. 12%). Normal BMI and high glucose were associated with the highest risk of NC. More importantly, 65% of ESBC on AC will require G-CSF during their treatment due to a NC episode. [Table: see text]
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".