Serious adverse events among a population-based cohort of patients receiving first-line chemotherapy for metastatic colorectal cancer (mCRC).
Bibliographic record
Abstract
e14003 Background: Little is known about the toxicity of first line chemotherapy for mCRC in the general population. We sought to determine the proportion of patients who experienced at least one of the following: a serious toxicity (defined as an emergency department visit or hospitalization) or death within 30 days of receiving chemotherapy. Methods: All patients, age 18 or older, diagnosed with CRC from January 1 2007 to December 31 2009 in Ontario, Canada were identified using the Ontario Cancer Registry. Patient records were linked deterministically to multiple provincial healthcare databases to identify receipt of first-line chemotherapy for metastatic disease and to evaluate Emergency Department (ED) visits, hospitalizations, and deaths. An event was determined to be potentially treatment related if it occurred within 30 days of any cycle of chemotherapy. Results: The cohort contained 2359 patients. Mean age was 62 (range 19-89) and 59% were men. See table below. Conclusions: A significant proportion of patients visit the ED at some point during first line chemotherapy and many are hospitalized. A quarter of all patients had a hospital admission whereby an infectious complication was at least a contributing diagnosis. A significant minority of patients died within 30 days of receiving chemotherapy, raising concerns of either poor patient selection or severe treatment toxicity. [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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".