Clinicopathological Factors and Interleukin-6 Levels Associated With Low Relative Dose Intensity in Women With Breast Cancer Receiving First-Line Chemotherapy
Bibliographic record
Abstract
Background: Chemotherapy has a substantial role in decreasing the risk of recurrence and mortality in breast cancer (BC) in a dose-dependent manner where a low relative dose intensity (RDI) is associated with unfavorable outcomes. Several baseline clinicopathological factors, including pro-inflammatory biomarkers, were found to be significant determinants of low RDI. This study aimed to explore the occurrence of low RDI and its influencing factors in women with BC. Methods: ) and duration (weeks). RDI less than 85% was defined as "low". Multivariate analysis with logistic regression was conducted to determine the association between pre-chemotherapy parameters and RDI < 85%. Results: The mean CRP level was 10.82 ± 19.17 mg/L (0.00 - 151.73 mg/L) and the mean IL-6 level was 1.12 ± 3.41 pg/mL (0.00 - 27.67 pg/mL). The average RDI for all patients was 93±8.19%. An RDI < 85% occurred in 23 patients (13.4%). The presence of diabetes mellitus (odds ratio (OR): 4.78, 95% confidence interval (CI): 1.03 - 22.27, P = 0.046), triple-negative tumors (OR: 6.45, 95% CI: 1.39 - 29.83, P = 0.017), and IL-6 levels > 0.5 pg/mL (OR: 3.45, 95% CI: 1.01 - 11.79, P = 0.049) was associated with an increased low RDI risk. Conclusion: The proportion of BC patients receiving a low chemotherapy RDI in our study was comparable to published literature and drove close monitoring of patients at risk to provide adequate management.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".