Effect of geographic distance from a cancer centre on choice of systemic therapy in metastatic colorectal cancer
Bibliographic record
Abstract
e17559 Background: There is little data on whether geographic distance from patient residence to a treatment facility is a predictor of systemic therapy utilization or clinical trial (CT) enrollment. Therefore a retrospective chart review was undertaken to investigate this variable. Methods: Consecutive patients with metastatic colorectal cancer (mCRC) assessed by a medical oncologist at the Juravinski Cancer Centre (JCC), Ontario during 2006 were selected. Patients with pathology other than adenocarcinoma and those with complete surgical resection of metastases were excluded. Distance and time to JCC were calculated using online mapping software. The study received full ethics approval. Results: 276 patients were included with full data available on 169 patients. Median travel time and distance to JCC were 23.0 minutes (min) and 19.2 kilometers (km), respectively. The maximum travel time was 120 min and 87% of patients lived within 60 min of JCC. Distance and time were highly correlated (p<0.0001). Overall, 43% of patients had discussed a CT with their oncologist and 20% enrolled in a CT. Patients living >50 km from JCC were less likely to discuss a CT (38%) or participate in a CT (15%) than patients who lived 25–50 km (39% and 19%) or <25 km (47% and 23%) from JCC. These trends did not attain statistical significance (odds ratio [OR] = 0.88, 95% CI = 0.66–1.17, p = 0.39 for CT discussion, OR = 0.76, 95% CI = 0.54–1.08, p = 0.13 for CT enrollment). Distance was not a statistically significant (p = 0.42) predictor of number of treatment regimens, however, 44% of patients <25 km from JCC received 3 or more lines of treatment compared with 33% of patients ≥25 km away. No association with survival was observed. Conclusions: Patients with mCRC living ≥25 km from JCC received fewer systemic regimens and were less likely to discuss or enter a CT. These trends were not statistically significant. Data collection is ongoing to increase the power of this study. No significant financial relationships to disclose.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".