The Impact of the COVID-19 Pandemic on Genitourinary Cancer Care: Re-envisioning the Future
Bibliographic record
Abstract
CONTEXT: The coronavirus disease 2019 (COVID-19) pandemic necessitated rapid changes in medical practice. Many of these changes may add value to care, creating opportunities going forward. OBJECTIVE: To provide an evidence-informed, expert-derived review of genitourinary cancer care moving forward following the initial COVID-19 pandemic. EVIDENCE ACQUISITION: A collaborative narrative review was conducted using literature published through May 2020 (PubMed), which comprised three main topics: reduced in-person interactions arguing for increasing virtual and image-based care, optimisation of the delivery of care, and the effect of COVID-19 in health care facilities on decision-making by patients and their families. EVIDENCE SYNTHESIS: Patterns of care will evolve following the COVID-19 pandemic. Telemedicine, virtual care, and telemonitoring will increase and could offer broader access to multidisciplinary expertise without increasing costs. Comprehensive and integrative telehealth solutions will be necessary, and should consider patients' mental health and access differences due to socioeconomic status. Investigations and treatments will need to maximise efficiency and minimise health care interactions. Solutions such as one stop clinics, day case surgery, hypofractionated radiotherapy, and oral or less frequent drug dosing will be preferred. The pandemic necessitated a triage of those patients whose treatment should be expedited, delayed, or avoided, and may persist with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in circulation. Patients whose demographic characteristics are at the highest risk of complications from COVID-19 may re-evaluate the benefit of intervention for less aggressive cancers. Clinical research will need to accommodate virtual care and trial participation. Research dissemination and medical education will increasingly utilise virtual platforms, limiting in-person professional engagement; ensure data dissemination; and aim to enhance patient engagement. CONCLUSIONS: The COVID-19 pandemic will have lasting effects on the delivery of health care. These changes offer opportunities to improve access, delivery, and the value of care for patients with genitourinary cancers but raise concerns that physicians and health administrators must consider in order to ensure equitable access to care. PATIENT SUMMARY: The coronavirus disease 2019 (COVID-19) pandemic has dramatically changed the care provided to many patients with genitourinary cancers. This has necessitated a transition to telemedicine, changes in threshold or delays in many treatments, and an opportunity to reimagine patient care to maintain safety and improve value moving forward.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".