The Global Impact of COVID-19 on Childhood Cancer Outcomes and Care Delivery - A Systematic Review
Bibliographic record
Abstract
Background: Childhood cancer represents a leading cause of death and disease burden in high income countries (HICs) and low-and-middle income countries (LMICs). It is postulated that the current COVID-19 pandemic has hampered global development of pediatric oncology care programs. This systematic review aimed to comprehensively review the global impact of COVID-19 on childhood cancer clinical outcomes and care delivery. Methods: A systematic search was conducted on PubMed, Embase, Medline, and the African Medical Index from inception to November 3, 2021 following PRISMA guidelines. A manual search was performed to identify additional relevant studies. Articles were selected based on predetermined eligibility criteria. Findings: The majority of studies reported patients with cancer and COVID-19 presenting as asymptomatic (HICs: 33.7%, LMICs: 22.0%) or with primary manifestations of fever (HICs: 36.1%, LMICs: 51.4%) and respiratory symptoms (HICs: 29.6%, LMICs: 11.7%). LMICs also reported a high frequency of patients presenting with cough (23.6%) and gastrointestinal symptoms (10.6%). The majority of patients were generally noted to have a good prognosis; however the crude mortality rate was higher in LMICs when compared to HICs (8.0% vs 1.8%). Moreover, the pandemic has resulted in delays and interruptions to cancer therapies and delays in childhood cancer diagnoses in both HICs and LMICs. However, these findings were disproportionately reported in LMICs, with significant staff shortages, supply chain disruptions, and limited access to cancer therapies for patients. Conclusions: The COVID-19 pandemic has resulted in delays and interruptions to childhood cancer therapies and delays in childhood cancer diagnoses, and disproportionately so within LMICs. This review provides lessons learned for future system-wide disruptions to care, as well as provides key points for moving forward better with care through the remainder of this pandemic. Systematic Review Registration: CRD42021266758, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=266758.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".