Impact of COVID-19 on hospital screening, diagnosis and treatment activities among prostate and colorectal cancer patients in Canada
Bibliographic record
Abstract
BACKGROUND: Suspension of cancer screening and treatment programs were instituted to preserve medical resources and protect vulnerable populations. This research aims to investigate the implications of COVID-19 on cancer management and clinical outcomes for patients with prostate and colorectal cancer in Canada. METHODS: We examined hospital cancer screening, diagnosis, treatment, length of stay, and mortality data among prostate and colorectal cancer patients between April 2017 and March 2021. Baseline trends were established with data between April 2017 and March 2020 for comparison with data collected between April 2020 and March 2021. Scenario analyses were performed to assess the incremental capacity requirements needed to restore hospital cancer care capacities to the pre-pandemic levels. RESULTS: For prostate cancer, A 12% decrease in diagnoses and 5.3% decrease in treatment activities were observed during COVID-19 between April 2020 and March 2021. Similarly, a 43% reduction in colonoscopies, 11% decrease in diagnoses and 10% decrease in treatment activities were observed for colorectal cancers. An estimated 1,438 prostate and 2,494 colorectal cancer cases were undiagnosed, resulting in a total of 620 and 1,487 unperformed treatment activities for prostate and colorectal cancers, respectively, across nine provinces in Canada. To clear the backlogs of unperformed treatment procedures will require an estimated 3%-6% monthly capacity increase over the next 6 months. INTERPRETATION: A concerted effort from all stakeholders is required to immediately ameliorate the backlogs of cancer detection and treatment activities. Mitigation measures should be implemented to minimize future interruptions to cancer care in Canada.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".