Preventive strategies of cancer therapeutics-related cardiotoxicity in childhood cancer survivors: a protocol of systematic review
Bibliographic record
Abstract
INTRODUCTION: Five-year survival in childhood cancer has been improved markedly in the past decades. Childhood cancer survivors are at high risk of cardiovascular diseases due to anticancer therapy-induced cardiotoxicity. The comprehensive evidence for the prevention of anticancer therapy-induced cardiovascular disease is, however, sparse. The systematic review described in the protocol aims to summarise the effect of current prevention for anticancer therapy-induced cardiotoxicity among childhood cancer survivors. METHODS AND ANALYSIS: This protocol is reported in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols checklist. We will search PubMed (via Medline), Embase and the Cochrane Library and include the studies investigating the effect of prevention against anticancer therapy-induced cardiotoxicity of childhood cancer. To assess the risk of bias, we will use the Cochrane Collaboration's risk of bias tool for randomised control trials and the Newcastle-Ottawa Scale for cohort studies and case-control studies. Furthermore, we will conduct meta-analyses if there is no substantial clinical heterogeneity between included studies. The Grading of Recommendations, Assessment, Development and Evaluation will be used to evaluate the quality of evidence. ETHICS AND DISSEMINATION: Ethical approval is not needed for systematic review of published data. The findings will be published in a peer-reviewed journal and disseminated at scientific conferences. PROSPERO REGISTRATION NUMBER: CRD42022333877.
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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 | 0.084 | 0.112 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.015 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.045 | 0.006 |
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".