Reproductive concerns and depression among younger survivors
Bibliographic record
Abstract
About a quarter of breast cancer cases in the United States are diagnosed in premenopausal women. The issues and decisions faced by younger women are different than those of older women, including concerns about early menopause, fertility, and long-term survivorship. Breast cancer treatment may increase the risk of early menopause and cause difficulties with fertility. This can be especially challenging for younger women who have not finished growing their families. There is limited research on how fertility problems impact the long-term well-being breast cancer survivors. The primary questions we will address among younger breast cancer survivors in this project include: (1) how do symptoms of depression change over time?, and (2) are problems with fertility associated with increased symptoms of depression over time? In addition, we will describe younger breast cancer survivors’ reproductive history, experiences with fertility-related side effects of treatment, and whether they made treatment decisions in order to maintain fertility. We will use data from approximately 200 younger breast cancer survivors who participated in the Women’s Healthy Eating and Living (WHEL) study. WHEL is a nutritional intervention designed to test whether a diet high in fruits and vegetables can lower breast cancer recurrence. The sample for this study includes survivors who were 40 at younger when they were diagnosed and who have agreed to be contacted again. Some data has already been collected, including demographics, cancer characteristics/treatment, and physical and mental well-being. We will conduct a follow-up survey to ask whether survivors wanted to have children or attempted pregnancy, whether they’ve had problems with infertility or fertility-related side effects of their treatment, whether they currently have any symptoms of depression, and about their current feelings toward pregnancy and their ability to have children. There are few studies that follow a group of younger breast cancer survivors over time. The WHEL study includes a significant number of younger women who have survived for 10 years or longer. The proposed project provides a great opportunity to combine existing long-term data with new questions to explore the association between the reproductive concerns and long-term well being.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".