Fertility Risk Discussions in Young Patients Diagnosed with Colorectal Cancer
Bibliographic record
Abstract
PURPOSE: In 2006, the American Society of Clinical Oncology established guidelines on fertility preservation in cancer patients, but recent data suggest that the guidelines are not widely followed. To identify the frequency of fertility discussions and the characteristics that influence the rate of discussion, we performed a retrospective chart review for patients less than 40 years of age with newly diagnosed colorectal cancer (CRC). METHODS: Charts of patients aged 18-40 years with newly diagnosed crc presenting to the Juravinski Cancer Centre from 2000 to 2009 were reviewed for documentation of discussions regarding fertility risks with treatment and reproductive options available. The influences of sex, age, year of diagnosis, stage of cancer, and type of treatment on the frequency of discussions were explored. RESULTS: The review located 59 patients (mean age: 35 years) who met the criteria for inclusion. A fertility discussion was documented in 20 of those patients [33.9%; 95% confidence interval (CI): 22.1% to 47.4%]. In the multivariate analysis, the odds of fertility being addressed was higher for patients receiving radiation [odds ratio (OR): 9.31; 95% ci: 2.49 to 34.77, p < 0.001) and lower by age (OR: 0.86; 95% ci: 0.74 to 0.99; p = 0.040). Of patients less than 35 years of age undergoing radiation treatment, 85% had a documented fertility discussion. We observed no significant difference in the frequency of discussions after 2006, when the American Society of Clinical Oncology guidelines were published (31.4% for 2000-2006 vs. 37.5% for 2007-2009, p = 0.63). CONCLUSIONS: Discussions about fertility risks associated with CRC treatment occur infrequently among young adults with newly diagnosed CRC. However, discussions occur more frequently in younger patients and in those undergoing radiation. Further investigations assessing barriers and physician attitudes to fertility risk discussion and reproductive options are planned.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".