Doctor, what are my options? A prospective cohort study of an individualized care plan for patients with gastrointestinal cancer.
Bibliographic record
Abstract
12 Background: For new cancer patients, information about the complexity of the disease, treatment schedule and potential side effects is often delivered during an emotional, stressful visit which can lead to misunderstanding. Appropriate informational support can improve informed decision making, adherence to treatment, and reduce anxiety and cancer morbidity. This is a 3-part clinical study investigating the utility of a patient-centered individualized care plan for patients with gastrointestinal (GI) cancer starting a new treatment. Methods: Part 1: Items identified in a comprehensive literature search were formatted into a questionnaire. For each item, participants ranked its importance. Part 2: MDs and RNs involved in the care of patients with GI cancer provided comments about the content of the care plan. Part 3: A prospective cohort study was conducted. During the first 10-weeks, patients received the standard of care. During the subsequent 10-weeks, patients received the intervention, a written individualized care plan. Outcomes were assessed at baseline and 2-4 weeks: QOL (FACT-G), anxiety and depression (HADS), treatment compliance and patient satisfaction (FACT-TS-PS). Results: Part 1: 73 items were included in the questionnaire. 20 patients completed the interview. Part 2: A long and short version of the care plan were created. The majority of MDs and RNs preferred the long version. Based on the comments, the final version was created. Part 3: 54 and 41 patients have been enrolled in the control and intervention cohorts, respectively. Analysis of the baseline data revealed fewer self-reported anxious (p=0.008) and depressive symptoms (p=0.002) in the intervention group. The nursing satisfaction score was significantly higher in the intervention group (7.09 vs. 4.80, p=0.018). Overall QOL and satisfaction scores were higher in the intervention group, but not statistically significant (81.30 vs. 76.25, 79.70 vs. 76.27). Conclusions: The care plan resulted in fewer anxious and depressive symptoms. There was a trend towards improved QOL and satisfaction in the intervention group, although not significant. We are continuing to enroll patients and analyze follow-up data.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".