Reasons for delay in time to initiation of adjuvant chemotherapy for colon cancer: A multi-institution study.
Bibliographic record
Abstract
e14504 Background: Although adjuvant chemotherapy (AC) has been shown to improve survival in patients with colon cancer (CC), meta-analyses have suggested decreased survival with increasing Time To AC (TTAC). We examined the predominant factors leading to delayed TTAC in routine clinical practice. Methods: Individual medical records were reviewed for 1,608 patients with CC who initiated AC 2005-2012 at eight cancer centers in the Province of Ontario. Patient, disease, and treatment characteristics, plus time intervals between each step in the cancer care pathway from surgery to AC, were captured. Patients were then categorized into three groups for comparison: (I) inter-current illness and/or post-operative complications, (II) oncologist/patient-initiated delay, (III) no medical reason for delay. Groups were compared using chi square tests and one-way ANOVA. A multivariate logistic regression analysis (MVA) was used to determine factors associated with TTAC >8 weeks (wks) for each cohort. Results: The proportion of patients in each group was: (I) 24.7%, (II) 19.5%, (III) 55.8%; mean TTAC was: (I) 10.1±2.7, (II) 10.5±3.6, (III) 8.5±2.1 wks (p<0.001); the proportion of cases with TTAC>8 wks was: (I) 76.4%; (II) 81.4%; (III) 57.9%. The most common post-operative complication in Group I was ileus (34.2%). The only significant predictor of TTAC >8 wks by MVA in group I was AC via central venous catheter (OR=2.4, 95%, CI:1.2-4.9). Median length of stay in hospital after surgery was 10, 6 and 6 days for Group I, II, and III, respectively (p<0.001). When MVA was performed on all patients, the presence of post-operative complications (OR=2.4, 95%CI:1.6-3.8) and oncologist/patient-initiated delay (OR=3.5, 95%CI:2.1-6.0) were the strongest predictors of delay. There was no effect on TTAC if surgery was performed in peripheral versus academic hospital (p=0.32). Conclusions: Although the majority of patients had no medical reason for delay, the average TTAC was > 8 wks. Our findings suggest that health-system factors such as waiting for consultations and chemotherapy booking cause the majority of delays in TTAC. These are modifiable and quality improvement initiatives should focus on how to reduce these delays.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".