Interventional Radiology-Guided Procedures in the Treatment of Pediatric Solid Tumors: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction The use of interventional radiology (IR) in the treatment of pediatric solid tumors has markedly increased over the last three decades. However, data on effectiveness of IR-techniques, such as embolization/ablation, are scarce. In this systematic review and meta-analysis, we examined the outcomes of IR-procedures in the treatment of solid tumors in children. Materials and Methods Using a defined search strategy, we searched for studies reporting the use of IR-techniques for pediatric solid tumors from 1980 to 2017. Reports with less than three patients, review, and opinion articles were excluded. The study was conducted under preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. We analyzed dichotomous and continuous variables by appropriate statistical methods. Results Of 567 articles screened, 21 papers met the inclusion criteria (12 retrospective, 7 prospective, and 2 randomized-control trials). Many of the analyzed papers described relatively small cohorts of patients. IR-guided procedures were mainly rescue procedures to treat primarily unresectable tumors, local recurrences, or metastases. Inclusion/exclusion criteria and success definition were not specified in most reports. Major side effects were documented in 17/286 (6%) infants, while minor side effects were self-limiting in most patients. Six studies had a comparison between tumor embolization (127 infants) to surgery or chemotherapy without IR-procedures (113 controls). The meta-analysis showed lower mortality (16 vs. 47%) and surgical time for resection (206 vs. 250 m), higher 2-year tumor-free survival (82 vs. 36%), and favorable histology in IR group (p < 0.001 for all). Conclusion IR-guided techniques are promising in the treatment of pediatric solid tumors. Further prospective (randomized) trials are needed to clarify efficacy.
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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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.031 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".