Impact of COVID-19-related health care disruptions on pathologic cancer staging during the first pandemic year: a retrospective cohort study from March 2018 to March 2021
Bibliographic record
Abstract
<h3>Background:</h3> The COVID-19 pandemic has created major disruptions in cancer care, with reductions in diagnostic tests and treatments. We evaluated the impact of these health care–related changes on cancer staging by comparing cancers staged before and during the pandemic. <h3>Methods:</h3> We performed a retrospective cohort study at London Health Sciences Centre and St. Joseph’s Health Care London, London, Ontario, Canada. We evaluated all pathologically staged breast, colorectal, prostate, endometrial and lung cancers (the 5 most common cancers by site, excluding nonmelanoma skin cancer) over a 3-year period (Mar. 15, 2018–Mar. 14, 2021). The pre-COVID-19 group included procedures performed between Mar. 15, 2018, and Mar. 14, 2020, and the COVID-19 group included procedures performed between Mar. 15, 2020, and Mar. 14, 2021. The primary outcome was cancer stage group, based on the pathologic tumour, lymph node, metastasis system. We performed univariate analyses to compare demographic characteristics, pathologic features and cancer stage between the 2 groups. We performed multivariable ordinal regression analyses using the proportional odds model to evaluate the association between stage and timing of staging (before v. during the pandemic). <h3>Results:</h3> There were 4055 cases across the 5 cancer sites. The average number of breast cancer staging procedures per 30 days increased during the pandemic compared to the yearly average in the pre-COVID-19 period (41.3 v. 39.6), whereas decreases were observed for endometrial cancer (15.9 v. 16.4), colorectal cancer (21.8 v. 24.3), prostate cancer (13.6 v. 18.5) and lung cancer (11.5 v. 15.9). For all cancer sites, there were no statistically significant differences in demographic characteristics, pathologic features or cancer stage between the 2 groups (<i>p</i> > 0.05). In multivariable regression analysis, for all cancer sites, cases staged during the pandemic were not associated with higher stage (breast: odds ratio [OR] 1.071, 95% confidence interval [CI] 0.826–1.388; colorectal: OR 1.201, 95% CI 0.869–1.661; endometrium: OR 0.792, 95% CI 0.495–1.252; prostate: OR 1.171, 95% CI 0.765–1.794; and lung: OR 0.826, 95% CI 0.535–1.262). <h3>Interpretation:</h3> Cancer cases staged during the first year of the COVID-19 pandemic were not associated with higher stage; this likely reflects the prioritization of cancer procedures during times of reduced capacity. The impact of the pandemic period on staging procedures varied between cancer sites, which may reflect differences in clinical presentation, detection and treatment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".