Impact of COVID-19 on care of older adults with cancer: a narrative synthesis of reviews, guidelines and recommendations
Bibliographic record
Abstract
PURPOSE OF REVIEW: The aim of this study was to summarize the literature on the impact of COVID-19 on older adults with cancer, including both the impacts of COVID-19 diagnosis on older adults with cancer and the implications of the pandemic on cancer care via a synthesis of reviews, guidelines and other relevant literature. RECENT FINDINGS: Our synthesis of systematic reviews demonstrates that older adults with cancer are prone to greater morbidity and mortality when experiencing concurrent COVID-19 infection. Current evidence related to the association between anticancer treatment and COVID-19 prognosis for older adults with cancer is conflicting. Guidelines and recommendations advocate for preventive measures against COVID-19; the uptake of telemedicine and virtual care; encourage vaccination for older adults with cancer; and the use of geriatric assessment. SUMMARY: The COVID-19 virus itself may be particularly deleterious for older adults with cancer. However, the health system and social impact of the pandemic, including global disruptions to the healthcare system and related impacts to the delivery of cancer care services, have equally important consequences.
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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 | 0.013 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".