Factors Associated with Adolescent and Young Adult Males with Cancer Attending Fertility Consultation: A Population-Based Cohort Study in Ontario, Canada
Bibliographic record
Abstract
Purpose: Cancer and its treatment can impair fertility in men. It is recommended that they be referred for fertility consultation before the start of treatment. This study examined factors associated with men attending a fertility consultation within 30 days of diagnosis. Methods: Males 15 to 39 years of age, diagnosed with cancer in Ontario, Canada, between 2006 and 2019, were identified from the Ontario Cancer Registry. Linked administrative data were used to obtain other clinical and sociodemographic variables. The main outcome was a fertility consultation within 30 days of diagnosis, defined using Ontario Health Insurance Plan billing codes (606 or 628). A backward selection multivariate logistic regression was performed. Results: Of 13,720 cases identified, 8.5% attended a fertility consultation within 30 days of diagnosis. A more recent year of diagnosis (odds ratio [OR] = 5.5; 95% confidence interval [CI] 4.6–6.6), living in an urban area (OR = 1.3; 95% CI 1.0–1.8), receiving radiation therapy (OR = 1.4; 95% CI 1.2–1.6), chemotherapy (OR = 1.9; 95% CI 1.6–2.2), and reproductive organ-related cancer surgery (OR = 1.5; 95% CI 1.2–1.7) were associated with a greater likelihood of attending a consultation. Older age (OR = 0.2; 95% CI 0.1–0.2), living in a northern region (OR = 0.3; 95% CI 0.2–0.5), having a cancer with low (OR = 0.3; 95% CI 0.2–0.4) or moderate risk to fertility (OR = 0.6; 95% CI 0.5–0.7), and residing in a neighborhood with lower income (OR = 0.4; 95% CI 0.3–0.5) or residential instability quintile (OR = 0.8; 95% CI 0.6–1.0) were associated with being less likely to attend a consultation. Conclusion: Although rates of fertility consultation have increased over time, these remain low in various clinical and demographic groups. Funding for fertility preservation appears to have had an important impact on fertility consultation in young men with cancer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".