The impact of virtual oncology care on chemotherapy continuity and clinical outcomes in patients treated for colorectal cancer: A pre-post analysis of the COVID-19 pandemic.
Bibliographic record
Abstract
e13649 Background: The coronavirus (COVID-19) pandemic has resulted in an abrupt transition to virtual oncology care at most cancer centres worldwide. A pillar of the American Medical Association’s proposed framework for digitally enabled care is assessing clinical quality, safety, and outcomes. This study’s objective is to evaluate chemotherapy quality and clinical outcomes in patients receiving intravenous chemotherapy for colorectal cancer before and during the COVID-19 pandemic. Methods: This is an observational study assessing patients treated with intravenous chemotherapy for colorectal cancer consecutively at the Ottawa Hospital Cancer Centre from June 2019 to September 2021. Patients with non-metastatic rectal cancer were excluded. Patient were stratified by whether they were started on chemotherapy pre-pandemic (June 2019 – Jan 2020) versus intra-pandemic (Feb 2020 – Sept 2021). Baseline characteristics and treatment data were collected from the electronic medical records. Outcomes of interest included chemotherapy delays, dose reductions, emergency department (ED) visits and hospitalizations. We used generalized linear and binary logistic regression modelling to compare outcomes between pre- and intra-pandemic periods. Results: There were 220 patients included in this study with 108 (49%) diagnosed with metastatic disease. In total, there were 66 (30%) patients treated in the pre-pandemic and 154 (70%) in the intra-pandemic period. As expected, virtual care consultations increased during the pandemic from 1.5% to 43.5% (p < 0.001). Likewise, the proportion of follow-up visits also increased from 37% to 84% (p < 0.001). There was no difference in the incidence of treatment delays (odds ratio [OR] = 1.01, p = 0.78), dose reductions (OR = 0.99, p = 0.69), ED visits (OR = 1.23, p = 0.37), hospitalizations (OR = 0.73, p = 0.43) or the total length of time off treatment (OR = 0.85, p = 0.17) between the pre- and intra-pandemic periods by multivariable analysis. A subgroup analysis was performed based on stage, which showed no difference in outcomes independent of the presence of metastases. Conclusions: This study demonstrates no significant difference in chemotherapy interruptions, dose intensity, or clinical outcomes in patients treated for colorectal cancer during the COVID-19 pandemic. These findings serve as an important quality-care indictor and demonstrate that virtual oncology care appears safe in a cohort of high-risk colorectal cancer patients. Future work dedicated to other tumor sites would allow for broader application of these findings.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".