Discharge to Primary Care for Survivorship Follow-Up: How Are Patients With Early-Stage Breast Cancer Faring?
Bibliographic record
Abstract
PURPOSE: Oncology centers in public health systems often transfer routine follow-up of patients with early-stage breast cancer (BC) to primary care physicians because of the increasing numbers of survivors and evidence supporting the safety of this practice. After transfer of care, it is unknown how BC survivors fare with treatment and surveillance goals, and whether they have unmet needs for access to specialist care. This study conducted in a sample of women in Alberta, Canada, examined adherence with follow-up guidelines, symptoms, and need for a telephone-based survivorship clinic. METHODS: Through the Alberta Cancer Registry, we randomly invited women with stage I-III invasive BC (N=960) to participate. Of those, 272 responded, and 240 consented to a structured telephone interview and chart review. RESULTS: Women adhered well to follow-up guidelines for mammogram, but less so for clinical examination and endocrine therapy (ET). However, most patients reported ongoing bothersome symptoms, which tended to be higher in those not on ET. More than one-third of patients reported ongoing needs (managing weight, side effects, exercise adherence, and psychosocial health). Younger, fatigued or depressed, nonurban women not on ET reported the most need for a telephone clinic. CONCLUSIONS: Adherence with follow-up goals (examination, mammography, ET) was better than expected. Despite this, interest in a telephone survivorship clinic was high. Perceived needs included symptom management plus support for lifestyle behavior change. Medical follow-up needs might be well-met by discharge to primary care. However, high levels of ongoing symptoms and psychosocial needs would suggest that telephone-based survivorship clinics, psychosocial and exercise interventions, or transition programs might benefit the survivorship experience of patients with BC.
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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 | 0.002 | 0.014 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".