Impact of granulocyte colony–stimulating factors in metastatic colorectal cancer patients
Bibliographic record
Abstract
BACKGROUND: Delays in chemotherapy because of neutropenia may be associated with poorer outcomes. The purpose of the present study was to examine the effect that granulocyte colony-stimulating factors (g-csfs) have on survival. METHODS: We conducted a chart review of all outpatients diagnosed with metastatic colorectal cancer and treated with folfiri chemotherapy (irinotecan, 5-fluorouracil, leucovorin) with or without bevacizumab at Mount Sinai Hospital between 2007 and 2012. Multivariable Cox proportional hazards models were used to compare survival in neutropenic patients treated with g-csf, in neutropenic patients not so treated, and in patients without neutropenia. RESULTS: The review identified 93 patients, 31 of whom did not experience a neutropenic event. Of the 62 who experienced neutropenia, 18 were managed with g-csf support, and 44, with reductions or delays in dose. Compared with patients experiencing a neutropenic episode not treated with g-csf, those treated with g-csf experienced a nonsignificant increase in time to event [progression or death: hazard ratio (hr): 1.37; 95% confidence limits (cl): 0.72, 2.61], but compared with patients not having a neutropenic episode, the same patients experienced a significant increase in time to event (hr: 2.07; 95% cl: 1.03, 4.15). CONCLUSIONS: In patients who experienced neutropenia, g-csf did not have a statistically significant impact on survival. Time to event was prolonged in g-csf-treated patients compared with patients who did not experience neutropenia.
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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 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".