Quality of adjuvant chemotherapy in stage III colon cancer.
Bibliographic record
Abstract
228 Background: The goal of the Systemic Treatment Program at Cancer Care Ontario is to ensure equitable access to high quality systemic therapy for all patients in Ontario. To provide information on performance and inform planning we evaluated the quality of care in stage III colon cancer pertaining to adjuvant chemotherapy using multiple indicators focusing on access, guideline concordance and toxicity. Methods: Patients with stage III colon cancer in 2010 were identified from the Ontario Cancer Registry then linked with several other health administrative databases to obtain information regarding wait times, consultation with medical oncology, receipt of guideline concordant adjuvant chemotherapy and treatment related toxicity. Results: In 2010, 1,133 patients were diagnosed with stage III colon cancer in Ontario of whom 49% were women and 60% were older than 65. 92% of patients were seen by a medical oncologist within four months of diagnosis. Among patients seen at one of the regional cancer centres, 56% consulted with an oncologist within the provincial target of 14 days from referral. Overall, 47% of patients received oxaliplatin-based adjuvant chemotherapy therapy; 70% of those younger than 65 versus 34% of those older than 65. Among patients older than 65 on whom information regarding oral chemotherapy use is available in Ontario, 58% received adjuvant chemotherapy (59% oxaliplatin-based, 41% capecitabine). With respect to timeliness of adjuvant chemotherapy, 85% of patients received chemotherapy within 120 days from diagnosis, 57% started treatment within 60 days of surgery and 61% started within 28 days of consultation with a medical oncologist. Among patients who received oxaliplatin based adjuvant chemotherapy, 42% had at least one ER visit and 18% at least one hospital admission during adjuvant treatment. There was evidence of geographic and age-based variation across multiple indicators. Conclusions: While good quality was observed for several of the indicators examined, opportunities for improvement were identified in access to treatment and toxicity management. Evaluating multiple indicators in the same population provides a broader perspective on quality facilitating a focused, efficient approach to improvement efforts.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".