Restricted access and advanced disease in post-pandemic testicular cancer
Bibliographic record
Abstract
INTRODUCTION: Urologists observed reduced cancer consultations and surgeries during the SARS-CoV-2 pandemic, raising concern about treatment delays. Testicular cancer serves as a particularly sensitive marker of this phenomenon, as the clinical stage of testicular cancer at presentation is predictive of cancer-specific survival. We aimed to investigate whether COVID-related restrictions to primary care access resulted in increased incidence of metastatic germ cell testis cancer. METHODS: A retrospective chart review was conducted on all cases of testicular cancer managed surgically at our center from March 1, 2018, to February 28, 2023. Patients were categorized into temporal cohorts, representing before, during, and following the implementation of COVID-19 public health restrictions in the province of Newfoundland and Labrador. RESULTS: Forty-one cases of testicular germ cell tumors were identified during the study period. The mean age at diagnosis was 40.8 years (standard deviation ±13.7). Demographics did not vary across the cohorts. Clinical stage 3 disease remained stable before and during the pandemic at 10.5% and 9.1% of cases, respectively. In the post-pandemic period, there was an increase to 27.3% (p=0.617). Surgical wait times remained stable across the pandemic (p=0.151). CONCLUSIONS: There was a 16.8% rise in clinical stage 3 disease from the pre-pandemic to post-pandemic period. Our study failed to identify a statistically significant increase in metastatic testis cancer incidence upon lifting of pandemic restrictions. Further study is necessary to confirm suspicions that pandemic restrictions contributed to increased incidence of metastatic testis cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".