Indolent lymphoma care delivery and outcomes during the COVID‐19 pandemic in Ontario, Canada
Bibliographic record
Abstract
The treatment pattern and outcomes in patients with indolent B-cell lymphoma treated during the coronavirus disease 2019 (COVID-19) pandemic period compared to the prepandemic period are unclear. This was a retrospective population-based study using administrative databases in Ontario, Canada (follow-up to 31 March 2022). The primary outcome was treatment pattern; secondary outcomes were death, toxicities, healthcare utilization (emergency department [ED] visit, hospitalization) and SARS-CoV-2 outcomes. Adjusted hazard ratios (aHR) from Cox proportional hazards models were used to estimate associations. We identified 4143 patients (1079 pandemic, 3064 prepandemic), with a median age of 69 years. In both time periods, bendamustine (B) + rituximab (BR) was the most frequently prescribed regimen. During the pandemic, fewer patients received R maintenance or completed the full 2-year course (aHR 0.81, 95% CI 0.71-0.92, p = 0.001). Patients treated during the pandemic had less healthcare utilization (ED visit aHR 0.77, 95% CI 0.68, 0.88, p < 0.0001; hospitalization aHR 0.81, 95% CI 0.70-0.94, p = 0.0067) and complications (infection aHR 0.69, 95% CI 0.57-0.82, p < 0.0001; febrile neutropenia aHR 0.66, 95% CI 0.47-0.94, p = 0.020), with no difference in death. Independent of vaccination, active rituximab use was associated with a higher risk of COVID-19 complications. Despite similar front-line regimen use, healthcare utilization and admissions for infection were less in the pandemic cohort.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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".