Impact of COVID-19 pandemic on older cancer patients: Proposed solution by the International Geriatric Radiotherapy Group
Bibliographic record
Abstract
Older cancer patients are disproportionally affected by the Coronavirus 19 (COVID-19) pandemic. A higher rate of death among the elderly and the potential for long-term disability have led to fear of contracting the virus in these patients. This fear can, paradoxically, cause delay in diagnosis and treatment that may lead to a poor outcome that could have been prevented. Thus, physicians should devise a policy that both supports the needs of older patients during cancer treatment, and serves to help them overcome their fear so they seek out to cancer diagnosis and treatment early. A combination of telemedicine and a holistic approach, involving prayers for older cancer patients with a high level of spirituality, may improve vaccination rates as well as quality of life during treatment. Collaboration between health care workers, social workers, faith-based leaders, and cancer survivors may be crucial to achieve this goal. Social media may be an important component, providing a means of sending the positive message to older cancer patients that chronological age is not an impediment to treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".