Cumulative temporal association between assisted reproductive technology and childhood cancer: a systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
Objective: Assisted reproductive technology (ART) has contributed to the birth of over 10 million children worldwide; however, its long-term health impacts, especially the potential risk of childhood cancer, continue to be a subject of debate. This study aims to examine the most current risk associations between ART and childhood cancer. Methods: We conducted a comprehensive search across PubMed, Embase, Web of Science, and Cochrane Library databases up to August 1, 2024. These studies aimed to explore the association between ART and childhood cancer risk, covering overall cancers, haematological malignancies, neural tumors, other solid tumors, and 11 specific cancers. Pooled analyses of risk estimates and 95% confidence intervals were conducted using random effects models, while cumulative meta-analyses were conducted to provide a time-based summary of the evidence. The study was prospectively registered on PROSPERO (CRD42024547262). Results: Sixteen large sample observational studies were included. Our findings showed a 21% increased risk of overall cancer in children conceived via ART (relative risk [RR] = 1.21, 95% CI, 1.11-1.33), with elevated risks also noted for haematological malignancies (RR = 1.16, 95% CI, 1.05-1.28), neural tumors (RR = 1.19, 95% CI, 1.07-1.32), and other solid tumors (RR = 1.48, 95% CI, 1.26-1.73). Six specific cancer types also demonstrated higher risks. The direction and magnitude of the effects remained relatively constant over time, while the degree of precision increased as data from newer studies were incorporated. Sensitivity analyses confirmed the robustness of these findings, and no publication bias was found. Conclusions: Our findings suggest a potential risk association between ART and childhood cancer, raising concerns regarding the future application of ART. These findings are critical in informing infertile couples considering ART about the potential risks involved. Clinical trial registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42024547262.
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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 | 0.017 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.038 |
| Bibliometrics | 0.006 | 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 | 0.002 |
| 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".