Decision regret in breast cancer patients after adjuvant radiotherapy
Bibliographic record
Abstract
PURPOSE: Breast cancer patients often engage in shared decision-making to select an individualized treatment regimen from multiple options. However, dissatisfaction with treatment outcomes can lead to decision regret. We evaluated decision regret and physical and psychological well-being among breast cancer patients who underwent adjuvant radiotherapy and explored their associations with patient, tumor, treatment, and symptom characteristics. METHODS: This cross-sectional study involved retrospectively obtaining clinical data and data collected through interviews carried out as part of regular long-term medical aftercare. Decision regret regarding the radiotherapy was assessed using the Ottawa Decision Regret Scale, physical and psychological well-being were assessed using the PROMIS Global Health-10 questionnaire, and patients were asked about their treatment outcomes and symptoms. The questionnaire was administered 14 months to 4 years after completion of radiotherapy. RESULTS: Of the 172 included breast cancer patients, only 13.9% expressed high decision regret, with most patients expressing little or no decision regret. More decision regret was associated with volumetric modulated arc therapy, chest wall irradiation, use of docetaxel as a chemotherapy agent, lymphangiosis carcinomatosa, new heart disease after radiotherapy, and lower psychological well-being. CONCLUSION: Although most patients reported little or no decision regret, we identified several patient, treatment, and symptom characteristics associated with more decision regret. Our findings suggest that psychological well-being influences patients' satisfaction with therapy decisions, implying that practitioners should pay special attention to maintaining psychological well-being during shared decision-making and ensuring that psychological assessment and treatment is provided after cancer therapy to deal with long-term effects of radiotherapy.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".