Stage migration of testicular germ cell tumours in Alberta, Canada, during the COVID-19 pandemic: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: An absence of screening recommendations and the rapid progression of testicular germ cell tumours (TGCTs) offer a perspective on the potential impact of the COVID-19 pandemic on cancer presentations. We evaluated the presenting cancer stages of TGCTs in a real-world population before and during the pandemic to assess stage migration. METHODS: We performed a retrospective review of all new patients with TGCT diagnoses in Alberta, Canada, from Dec. 31, 2018, to Apr. 30, 2021, using the Alberta Cancer Registry. Because potential changes in staging should not occur instantaneously, we used a 6-month lag time from Apr. 1, 2020, for seminomas, and a 3-month lag time for nonseminomas, to compare initial cancer stages at presentation before and during the pandemic. We evaluated monthly rates of presentation by stage and histology. Exploratory outcomes included the largest tumour dimension, tumour markers and, for advanced disease, risk category and treatment setting. RESULTS: Of 335 patients with TGCTs, 231 were diagnosed before the pandemic and 104 during the pandemic (using a lag time). In total, 18 (7.8%) patients diagnosed before the pandemic presented with stage III disease, compared to 16 (15.4%) diagnosed during the pandemic (relative risk 1.97, 95% confidence interval [CI] 1.05-3.72). We observed no significant differences for secondary outcomes. Without a lag time, the rate ratio for a stage II presentation decreased significantly during the pandemic (0.40, 95% CI 0.21-0.72). INTERPRETATION: We observed signs of TGCT stage migration during the COVID-19 pandemic, driven by a decline in stage II disease and a potential rise in stage III disease. Management of TGCTs should remain a priority, even during a global pandemic.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".