Breast Cancer Survivor Symptoms: A Comparison of Physicians’ Consultation Records and Nurse-Led Survivorship Care Plans
Bibliographic record
Abstract
BACKGROUND: Survivorship care plans (SCPs) have been used to address ongoing health problems associated with the diagnosis and treatment of early-stage breast cancer. OBJECTIVES: The aim of this article was to determine whether nurse-led consultations using SCPs, as compared with a standard medical consultation, identify more side effects and supportive care needs and lead to appropriate referral patterns. METHODS: The study audited 160 retrospective medical clinic and nursing SCP records in a sample of patients receiving treatment for early-stage breast cancer at a tertiary-level breast service in Australia. FINDINGS: Breast care nurses (BCNs) undertaking SCPs at a nurse-led consultation were significantly more likely than physicians to record symptoms related to menopausal/hormonal therapy, psychosocial/mental health, lifestyle, bone health, and sexuality. BCNs were also significantly more likely to refer patients for concerns related to psychosocial/mental health, lifestyle, and sexuality.
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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 | 0.003 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".