Systematic Review of Available Guidelines on Fertility Preservation of Young Patients with Breast Cancer
Bibliographic record
Abstract
BACKGROUND: Since the survival rate of breast cancer patients has improved, harmful effects of new treatment modalities on fertility of the young breast cancer patients has become a focus of attention. This study aimed to systematically review and critically appraise all available guidelines for fertility preservation in young breast cancer patients. MATERIALS AND METHODS: Major citation databases were searched for treatment guidelines. Experts from relevant disciplines appraised the available guidelines. The AGREE II Instrument that includes 23 criteria in seven domains (scope and purpose of the guidelines, stakeholder involvement, rigor of development, clarity, applicability, editorial independence, and overall quality) was used to apprise and score the guidelines. RESULTS: The search strategy retrieved 2,606 citations; 72 were considered for full-text screening and seven guidelines were included in the study. There was variability in the scores assigned to different domains among the guidelines. ASCO (2013), with an overall score of 68.0%, had the highest score, and St Gallen, with an overall score of 24.7%, had the lowest scores among the guidelines. CONCLUSIONS: With the promising survival rate among breast cancer patients, more attention should be given to include specific fertility preservation recommendations for young breast cancer patients.
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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 | 0.009 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".