The implementation of fertility guidelines and impact on the rate of pre-therapy fertility risk discussions in pediatric oncology: A retrospective cohort study.
Bibliographic record
Abstract
e22027 Background: Pediatric cancer patients undergoing treatment are often at risk for infertility or subfertility. Healthcare providers do not consistently deliver fertility information prior to therapy. Our objective was to assess if development and implementation of a fertility guideline improves the frequency of pre-treatment fertility discussions with pediatric cancer families. Methods: This retrospective cohort study analyzed all consecutively eligible patients over two time periods. The pre-guideline time period was 18 months prior to implementation and the post-guideline time period was 12 months after implementation. Guideline implementation included an education session with oncology staff. Eligible patients were < 19 years old at cancer diagnosis and received chemotherapy and/or radiation therapy. Patients treated with palliative intent were excluded. Pre-guideline rate of pre-treatment fertility discussions was estimated at 40%. An estimated 40 participants in the post-guideline cohort can detect a 30% increase in fertility discussions with β 0.8 and α 0.05. Exploratory analysis assessed factors associated with the frequency of fertility risk discussions. Results: Ninety-five patients were included. Fifty-seven percent were < 10, 26% were 10-15, and 17% were ≥ 16 years old. Pre- and post-guideline cohorts are compared in table. In the pre-guideline cohort, 41% of patients had a discussion about risks of fertility impairment documented, while post-guideline cohort had 49% documented ( p = 0.531). Exploratory assessment of combined cohorts found males (OR 0.2.7, 95% CI 0.1.2-6.3-0.87) and patients ≥ 10 years old (OR 5.0, CI 2.1-12.1) were more likely to receive fertility discussions prior to therapy. Radiation and cancer type did not influence whether fertility discussions occurred. Conclusions: Implementation of a fertility guideline did not increase discussions of fertility risk, and less than half of patients had a documented fertility risk discussion. Male patients and age ≥ 10 years old were more likely to have documented discussions about risks to future fertility. Effective strategies are needed to improve the rate of discussions regarding fertility risk to ensure families receive this information prior to therapy. [Table: see text]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".