Breastfeeding experiences among young breast cancer survivors: A survey study
Bibliographic record
Abstract
BACKGROUND: Following breast cancer (BC), many young women are interested in future childbearing and some may wish to breastfeed. However, limited information is available regarding their lactation experiences. METHODS: Participants in the Young Women's Breast Cancer Study, a multicenter, prospective cohort study of women ≤40 years diagnosed with stage 0-III BC between 2006-2016 and who reported one or more live births following diagnosis, were surveyed about pregnancy and breastfeeding after BC treatment, including reasons for attempting and stopping breastfeeding, satisfaction, and supports. RESULTS: Of 143 eligible women sent a survey, 115 responded and 94 were included in the analytic cohort. Breastfeeding was attempted by 55% of women (52 of 94). Among those who had not attempted, 93% noted prior bilateral mastectomies (39 of 42). Among those who attempted breastfeeding, 69% had undergone lumpectomy and radiotherapy (36 of 52), 83% of whom reported no milk production from their treated breast (30 of 36). Most (65%, 34 of 52) were at least somewhat satisfied with their ability to breastfeed. Reasons for stopping breastfeeding included: having completed the planned duration (36%, 19 of 52); to start/resume endocrine therapy (21%, 11 of 52); and to resume breast imaging (8%, 4 of 52). Approximately half (27 of 55) of women who had not undergone bilateral mastectomies recalled receiving specific information about breastfeeding after BC, mostly from the oncology team (59%, 16 of 27), online resources (48%, 13 of 27), or a lactation consultant (44%, 12 of 27). CONCLUSION: Most young BC survivors who attempted to breastfeed were able to and were satisfied with the experience, despite challenges. Specific resources to support BC survivors who wish to breastfeed are needed.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".