Childhood cancer survivorship care during the COVID-19 pandemic: an international report of practice implications and provider concerns
Bibliographic record
Abstract
PURPOSE: Long-term follow-up (LTFU) care is essential to optimise health outcomes in childhood cancer survivors (CCS). We aimed to assess the impact of the COVID-19 pandemic on LTFU services and providers. METHODS: A COVID-19 working group within the International Late Effects of Childhood Cancer Guideline Harmonization Group (IGHG) distributed a questionnaire to LTFU service providers in 37 countries across Europe, Asia, North America, Central/South America, and Australia. The questionnaire assessed how care delivery methods changed during the pandemic and respondents' level of worry about the pandemic's impact on LTFU care delivery, their finances, their health, and that of their family and friends. RESULTS: Among 226 institutions, providers from 178 (79%) responded. Shortly after the initial outbreak, 42% of LTFU clinics closed. Restrictions during the pandemic resulted in fewer in-person consultations and an increased use of telemedicine, telephone, and email consultations. The use of a risk assessment to prioritise the method of LTFU consultation for individual CCS increased from 12 to 47%. While respondents anticipated in-person consultations to remain the primary method for LTFU service delivery, they expected significantly increased use of telemedicine and telephone consultations after the pandemic. On average, respondents reported highest levels of worry about psychosocial well-being of survivors. CONCLUSIONS: The pandemic necessitated changes in LTFU service delivery, including greater use of virtual LTFU care and risk-stratification to identify CCS that need in-person evaluations. IMPLICATIONS FOR CANCER SURVIVORS: Increased utilisation of virtual LTFU care and risk stratification is likely to persist post-pandemic.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 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".