Geographical Variations in the Clinical Management of Colorectal Cancer in Australia: A Systematic Review
Bibliographic record
Abstract
Background: Colorectal cancer (CRC) presents considerable health, economic, and societal burden, and Australia has one of the highest incidence rates of this disease. Over a third of the Australian population live in nonmetropolitan areas and research has shown that they experience a range of health disadvantages that result in a higher disease burden and lower life expectancy. One of the main contributors of poorer CRC outcomes in rural Australia may be limited access to treatment facilities and optimal care; however, the extent to which geographical disparities exist in CRC management has not been systematically explored. Aim: To understand the nature of geographical variations in the clinical management and treatment of CRC (including surgery, chemotherapy, and radiotherapy) in Australia, incorporating clinical reports as well as peer-reviewed literature. Methods: A systematic review of published and gray literature was conducted. Five databases (CINAHL, PubMed, Embase, ProQuest, and Informit) were searched for articles published in English from 1990 to 2018. Studies were included if they assessed differences in clinical management according to geographical location; focused on CRC patients; and were conducted in Australia. Included studies were critically appraised using a modified Newcastle-Ottawa Scale. PRISMA systematic review reporting methods were applied. Results: Only 17 articles met inclusion criteria. All were of high (53%) or moderate (47%) quality. The evidence available may suggest that patients in nonmetropolitan areas are more likely to experience delays in surgery and are less likely to receive chemotherapy for stage III colon cancer and adjuvant radiotherapy for rectal cancer. Conclusion: The present review found limited information on clinical management across geographic regions in Australia and the synthesis highlights significant issues both for data collection and reporting at the population level. Where geographical disparities exist, these may be due to a combination of patient and system factors reflective of location. Population-level data regarding clinical management and treatment of CRC needs to be routinely collected to better understand geographical variations and inform future guidelines and policy.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| 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".