Randomized Trial of Long-Term Follow-Up for Early-Stage Breast Cancer: A Comparison of Family Physician Versus Specialist Care
Bibliographic record
Abstract
PURPOSE: Most women with breast cancer are diagnosed at an early stage and more than 80% will be long-term survivors. Routine follow-up marks the transition from intensive treatment to survivorship. It is usual practice for routine follow-up to take place in specialist clinics. This study tested the hypothesis that follow-up by the patient's family physician is a safe and acceptable alternative to specialist follow-up. PATIENTS AND METHODS: A multicenter, randomized, controlled trial was conducted involving 968 patients with early-stage breast cancer who had completed adjuvant treatment, were disease free, and were between 9 and 15 months after diagnosis. Patients may have continued receiving adjuvant hormonal therapy. Patients were randomly allocated to follow-up in the cancer center according to usual practice (CC group) or follow-up from their own family physician (FP group). The primary outcome was the rate of recurrence-related serious clinical events (SCEs). The secondary outcome was health-related quality of life (HRQL). RESULTS: In the FP group, there were 54 recurrences (11.2%) and 29 deaths (6.0%). In the CC group, there were 64 recurrences (13.2%) and 30 deaths (6.2%). In the FP group, 17 patients (3.5%) compared with 18 patients (3.7%) in the CC group experienced an SCE (0.19% difference; 95% CI, -2.26% to 2.65%). No statistically significant differences (P < .05) were detected between groups on any of the HRQL questionnaires. CONCLUSION: Breast cancer patients can be offered follow-up by their family physician without concern that important recurrence-related SCEs will occur more frequently or that HRQL will be negatively affected.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".