Association Between Pre‐Diagnostic Delay and Survival Among Patients With Esophageal and Gastric Cancer Treated With Curative Intent During the <scp>COVID19</scp> Pandemic
Bibliographic record
Abstract
BACKGROUND: The majority of esophageal and gastric cancers are diagnosed at an advanced stage with poor overall survival (OS). Whether the pre-diagnostic interval from symptom onset has any impact on OS is unclear. We investigated this question in the peri-COVID19 pandemic era. METHODS: We retrospectively analyzed a cohort of 308 patients with esophageal, gastroesophageal junction, or gastric carcinoma treated with curative intent at the Princess Margaret Cancer Centre from January 2017 to December 2021. Clinical details pertaining to the initial presentation were determined through a retrospective chart review. Cox proportional hazards regression models were used to assess the association between pre-diagnostic intervals and OS, adjusting for baseline patient characteristics. RESULTS: The median interval from symptom onset to diagnosis was 98 days (IQR 47-169 days). Using a cox proportional hazard model, prolonged pre-diagnostic interval was not associated with worse OS (HR 1.00, p = 0.62). Comparing patients diagnosed before and during the COVID19 pandemic, there was a notable increase in diagnostic delay with median pre-diagnostic interval increasing from 92 to 126 days (p = 0.007). Median age at time of diagnosis was 69.6 during the pandemic vs. 64.7 before the pandemic. Linear regression showed squamous cell histology was significantly associated with increasing time to initial diagnosis (p = 0.04), but this did not hold true in a multivariable model. Looking at other delay metrics, there were no changes in time interval from diagnosis to treatment during versus before the pandemic (median = 1.7 weeks for both), and there was no change in time from diagnosis to resection in those patients who underwent surgery. CONCLUSION: The COVID19 pandemic caused significant diagnostic delay for patients presenting with curative gastroesophageal and gastric cancer. The lack of correlation of pre-diagnostic interval with OS may reflect underlying tumor biology as the driving force that determines prognosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".