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The burden of BRCA1 and BRCA2 gene mutations among Vietnamese women and their associated factors: A protocol for a systematic review and meta-analysis

2022· review· en· W4288084712 on OpenAlexaboutno aff
Trần Thái Phúc, Duc Quang Tran, Chi Thi Quynh Vu, Quang Ngoc Phan, Anh Thi Thu Nguyen

Bibliographic record

VenueF1000Research · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsnot available
Fundersnot available
KeywordsVietnameseMeta-analysisMedicineInternal medicine

Abstract

fetched live from OpenAlex

Background: BReast CAncer gene (BRCA)1 and BRCA2 mutation carriers are frequently provided genetic counselling. A precise estimation of the prevalence of BRCA gene mutations is essential to provide an appropriate risk prediction. However, the data in Vietnam is ambiguous and include unreliable risk factors from individual studies. Hence, the objective of this protocol is to provide a method to synthesize evidence pertaining to the proportion of BRCA mutations among Vietnamese women and their risk factors for cancer. Methods: PRISMA-P was followed in developing and reporting this protocol. From the databases' inception until June 2023, a comprehensive search will be undertaken in electronic PubMed and Scopus databases. In two stages, title/abstract screening and full-text screening, two independent authors will assess all retrieved articles for inclusion. This review includes papers providing the relevant results reflecting the prevalence of BRCA gene mutations in Vietnamese women who are at least 18 years old with or without cancer. Predefined selection criteria will be used to establish each publication's eligibility. Using the Newcastle-Ottawa Scale and Cochrane Risk of Bias tools, the quality of included studies will be assessed, and overall evidence quality will be appraised using the GRADE approach. All pertinent data from the included articles will be entered into an Excel spreadsheet for meta-analysis, which will be imported into Rstudio. Meta-analyses using random effects will be used to obtain the pooled percentages. The chi-squared test and I 2 parameter will be used to evaluate heterogeneity. Publication bias will be investigated visually using funnel plots for asymmetry and Egger's statistical tests. Conclusions: Based on the prevalence of BRCA muations and its associated comprehensive and specific risk factors, we hope our findings will provide a reference for future strategies to build an effective treatment plan and manage the risk of cancer development. Registration: PROSPERO ( CRD42022340152 ; 30 June 2022).

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 imitation

Not 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.

metaresearch head score (Codex)0.086
metaresearch head score (Gemma)0.138
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.086
Threshold uncertainty score0.453

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0860.138
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0180.028
Bibliometrics0.0130.011
Science and technology studies0.0040.003
Scholarly communication0.0070.006
Open science0.0060.005
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0730.008

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.

Opus teacher head0.113
GPT teacher head0.422
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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