101 Decision aid, algorithms, and a handbook for decision-making support on fertility preservation for women with breast cancer undergoing treatment
Bibliographic record
Abstract
Introduction Breast cancer is the leading cancer type among women in Japan, with more than 10,000 women of reproductive age developing the disease annually. Therefore, this study aims to develop a decision aid (DA), handbook and algorithms to support decision-making for cancer patients regarding fertility preservation. Methods DAs and brochures that address these aims were collected from preceding studies on fertility preservation decision-making in breast cancer patients, the Ottawa Hospital Research Institute A to Z Inventory, patient booklets, and medical institutions websites. The researchers of this study attended an educational program for developing decision aids and created a DA draft based on the International Patient Decision Aid Standards instrument (IPDASi), decision support algorithms, and a DA handbook. A series of tests were administered to both three breast cancer patients, seven physicians, and two nurses. Results The results demonstrated that the following points should be considered in the proposed DA structure: first, the impact of breast cancer treatment on fertility and fertility preservation therapy should be explained, followed by questions about what decisions must be made by what stage in the treatment process; information applicable to many medical institutions should be provided in terms of when fertility preservation therapy and subsidies are available; the text should avoid Illustrations reminiscent of children; and patients should be able to organize their thoughts as they fill out the DA. Discussion The original draft DA, algorithms, and handbook were revised based on the study results to develop the final version. Conclusion It is anticipated that the DA, algorithms, and the handbook, modified in accordance with the study results, will be commonly understood by both health care providers and patients. Future research will now concentrate on evaluating the feasibility of the proposed solution.
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 | 0.014 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".