Helping Patients Make Informed Choices: A Randomized Trial of a Decision Aid for Adjuvant Chemotherapy in Lymph Node-Negative Breast Cancer
Bibliographic record
Abstract
BACKGROUND: In recent years, patients have indicated a desire for more information about their disease and to be involved in making decisions about their care. We developed an aid called the "Decision Board" to help clinicians inform patients with lymph node-negative breast cancer of the risks and benefits of adjuvant chemotherapy. We determined whether adding the Decision Board to the medical consultation improved patient knowledge and satisfaction compared with the medical consultation alone. METHODS: Between October 1995 and March 2000, 176 women with lymph node-negative breast cancer who were candidates for adjuvant chemotherapy were randomly assigned to receive the Decision Board plus the medical consultation (83 patients) or the medical consultation alone (93 patients). One week after the consultation, patients completed a questionnaire assessing their knowledge about breast cancer and chemotherapy. Satisfaction with decision making was assessed 1 week and 3, 6, and 12 months after randomization, and differences between groups were analyzed by a repeated measures analysis of variance. All statistical tests were two-sided. RESULTS: Patients in the Decision Board arm were better informed about breast cancer and adjuvant chemotherapy than patients in the control arm (mean knowledge score = 80.2 [on a scale of 0-100], 95% confidence interval [CI] = 77.1 to 83.3, and 71.7, 95% CI = 69.0 to 74.4, respectively; P<.001). Over the entire study period, satisfaction with decision making was higher for patients in the Decision Board arm than for patients in the control arm (P =.032). There was no statistically significant difference between the two groups in the number of patients who chose adjuvant chemotherapy (77% and 70% for patients in the Decision Board arm and those in the control arm, respectively; P =.303). CONCLUSION: When making decisions regarding adjuvant chemotherapy, patients with early breast cancer who had been exposed to the Decision Board had better knowledge of the disease and treatment options and greater satisfaction with their decision making than those who received the standard consultation.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".