Impact of patient and physician factors on oncologists’ recommendations for adjuvant chemotherapy in stage III colon cancer
Bibliographic record
Abstract
6051 Background: Population-based studies indicate that elderly patients with colon cancer are less likely to receive adjuvant therapy (tx). Lack of tx may reflect patient preference, appropriate consideration of comorbid illness, or physician bias. Methods: To study physician preference for tx of elderly patients with colon cancer, a vignette-based survey was developed then mailed to a nationally representative sample of 1,000 oncologists. Patient age (61/72/83 yrs), comorbidity level (none/mild/severe CHF with symptoms on minimal exertion) and preference were varied across 8 vignettes. Physician preference for recommending tx was measured using a 7-pt Likert scale; mixed effects linear regression was used to evaluate the results. Results: 485 oncologists returned the survey (RR = 49%); 363 that had seen patients with colon cancer during the previous year were included in further analyses. Median age of the respondents was 52 (range 30–77), 73 (20%) were women. Median time since graduation from medical school was 25 yrs (range 5–53); 17% were employed in academic centers, 8% in HMOs and the remainder in the community. Patient age and comorbid illness interacted to significantly influence physician recommendations. Among patients with mild comorbidity, physician preference for tx of an 83 yr old patient was 1.1 lower than for a 72 yr old (3.8 vs 4.9 on a 7-pt Likert scale) and 1.7 lower than for a 61 yr old (each p<0.0001). This age effect was similar among patients with no comorbidity (p=0.30), with physicians’ preferences consistently higher by about 1.5 than for patients with mild comorbidity (p<0.0001). Among patients with severe comorbidity, preference for tx of an 83 yr old was only 0.9 lower than for a 61 yr old patient (p<0.0001), whereas the decrease was 2.6 for a 61 yr old with severe vs mild comorbidity. Patient preference against tx resulted in 0.3 (p<.0001) decrease in physicians’ recommendations for tx. Among physician factors, only type of employment was associated with tx recommendations with a 0.3 decrease in preference for tx (p=0.0014) among academic oncologists. Conclusions: Patient rather than physician factors have the greatest effect on oncologists’ preferences for adjuvant tx with age and severe comorbidity having the strongest effect. No significant financial relationships to disclose.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".