Changes in New Patient Consultations During the COVID-19 Pandemic at a Canadian Comprehensive Cancer Center
Bibliographic record
Abstract
BACKGROUND: The impact of COVID-19 pandemic-related disruptions on cancer services is emerging. We evaluated the impact of the first 2 years of the pandemic on new patient consultations for all cancers at a comprehensive cancer center within a publicly funded health care system and assessed whether there was evidence of stage shift. METHODS: We performed a retrospective study using the Princess Margaret Cancer Registry. New consultations with medical, radiation, or surgical oncology were categorized by year and quarter. Logistic regression was used to assess the effect of period before and during the COVID-19 pandemic on cancer stage at consultation, adjusting for age, sex, and diagnosis location (our hospital network vs elsewhere). RESULTS: In all, 53,759 new patient consultations occurred from January 1, 2018, to June 30, 2022. After the pandemic was declared, there was a decrease in all types of consultations by 43.3% in the second quarter of 2020, and referral volumes did not recover during the first year. There was no evidence of stage shift for all cancer types during the later quarters of the pandemic for the overall population. CONCLUSIONS: New patient consultations decreased across cancer stages, referral type, and most disease sites at our tertiary cancer center. We did not observe evidence of stage shift in this population. Further research is needed to determine whether this reflects the resilience of our health care system in maintaining cancer services or a delay in the presentation of advanced cancer cases. These data are important for shaping future cancer care delivery and recovery strategies.
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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 | 0.001 |
| 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".