Predictors of referral for adjuvant therapy for colorectal cancer.
Bibliographic record
Abstract
OBJECTIVE: We carried out a retrospective cohort study at the Ottawa Hospital-Civic Campus to determine the proportions of patients referred for and provided adjuvant therapy for colorectal cancer (CRC) among those eligible according to published clinical practice guidelines. METHOD: Patients with stage III colon or stage II or stage III rectal cancer who had had potentially curative surgical resection for CRC and were seen at the Ottawa Hospital during 1999 and 2000 were eligible. We noted the number of medical or radiation oncology consultations, or both, and the subsequent receipt of adjuvant chemotherapy or radiotherapy, or both. RESULTS: Of 158 eligible patients, 135 (85%) had medical or radiation oncology consultations, or both. Of the total, 104 were less than 75 years of age and of these 99 (95%) were referred; of the 54 patients 75 years of age or older, 36 (67%) were referred. Of the 158 patients, 113 (72%) received adjuvant therapy, 90 (87%) eligible patients aged less than 75 years and 23 (43%) older patients. Increasing age and the presence of comorbidity were independent predictors of nonreferral and nontreatment. Gender and cancer site (colon or rectum) were not significant predictors of referral for, or receipt of, adjuvant therapy in general. CONCLUSIONS: The observed rates of referral for and receipt of adjuvant therapy for CRC are greater than generally published and appear reasonably concordant with current clinical practice guidelines, but optimal rates are undefined. Older patients and those with comorbidity were less likely to be referred and treated. However, our knowledge of the factors important to the process of clinical decision-making about adjuvant therapy for CRC is incomplete, and there may be patients, especially older ones, for whom adjuvant therapy would be appropriate but who are not being referred or treated.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".