Remoteness from urban centre does not affect gastric cancer outcomes with established care pathway to specialist centre
Bibliographic record
Abstract
Background: Patients living in rural communities experience difficulty accessing specialized medical care. Rural patients with cancer present with more advanced disease, have reduced access to treatment and have poorer overall survival than urban patients. This study’s aim was to evaluate outcomes of patients with gastric cancer living in rural and remote areas versus urban and suburban communities in the context of an established care corridor to a tertiary care centre. Methods: All patients treated for gastric cancer at the McGill University Health Centre during 2010–2018 were included. Travel, lodging and cancer care coordination were provided for patients from remote and rural areas and coordinated centrally by dedicated nurse navigators servicing these regions. Statistics Canada’s remoteness index was used to categorize patients into a rural and remote group and an urban and suburban group. Results: A total of 274 patients were included. Compared with patients from urban and suburban areas, patients from rural and remote areas were younger and their clinical tumour stage was higher at presentation. The number of curative resections and palliative surgeries and rate of nonresection were comparable (p = 0.96). Overall, disease-free and progression-free survival were comparable between the groups, and having locally advanced cancer correlated with poorer survival (p < 0.001). Conclusion: Although patients with gastric cancer from rural and remote areas had more advanced disease at presentation, their treatment patterns and survival were comparable to those of patients from urbanized areas in the context of a publicly funded care corridor to a multidisciplinary specialist cancer centre. Equitable access to health care is necessary to diminish any preexisting disparities among patients with gastric cancer.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".