Obstetric and perinatal outcomes in female survivors of childhood or adolescent cancer: Protocol of a meta-analysis of population-based cohort studies
Bibliographic record
Abstract
INTRODUCTION: Approximately 80% of children, adolescents and young adults (CAYA) cancer patients are expected to fully recover and survive for five years or more. The reproductive health is a particular area of their concern. Evidence demonstrates that previous therapeutic treatments for cancer and comorbidities may have harmful effects on female fertility and delivery outcomes, which will significantly affect patient quality of life. However, these reports are heterogeneous. Therefore, the purpose of this study is to provide the up-to-date evidence on the risk of adverse obstetric and perinatal outcomes in female survivors of childhood or adolescent cancer. METHODS AND ANALYSIS: This meta-analysis will be carried out and reported with adherence to the Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidelines and the Cochrane Handbook. We will search online databases including PubMed, Cochrane Library, and Embase from inception to August, 2022 to identify all relevant cohort studies examining the relationship between cancer and subsequent obstetric and perinatal outcomes. Data extraction from eligible studies will be conducted and crosschecked separately by two investigators using pre-tested standardized data extraction forms. Discrepancies will be resolved via a third investigator. Methodological quality assessment for each study will be conducted using the Newcastle-Ottawa scale (NOS) tool. We will apply the DerSimonian-Laird random-effects model to calculate the pooled estimates. Further sources of heterogeneity will be explored by performing subgroup analysis based on multiple study characteristics. Potential publication bias will be assessed by inspection of a funnel plot, Begg's and Egger's regression tests of funnel plot asymmetry. ETHICS AND DISSEMINATION: Ethical approval will not be required as all data used for this pooled analysis will be obtained from published cohort studies. The results of this study will be disseminated in a peer-reviewed journal and conference presentation. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/K6QBG.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.087 | 0.110 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.019 | 0.048 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".