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Record W3157259320 · doi:10.21037/tcr-21-104

Diagnostic accuracy of circulating miR-126 for malignant pleural mesothelioma: a systematic review and meta-analysis

2021· review· en· W3157259320 on OpenAlexaff
Lei Zhang, Qianghua Zhou, Yanqiu Han, Peng Li, Pei-Heng Ouyang, Mei-ying Wang, Zhide Hu

Bibliographic record

VenueTranslational Cancer Research · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineMeta-analysisDiagnostic accuracyMesotheliomaOncologyInternal medicineSystematic reviewDiagnostic testPathologyMEDLINEPediatrics

Abstract

fetched live from OpenAlex

BACKGROUND: Circulating microRNAs are novel diagnostic markers for various types of cancer. Several studies have investigated the diagnostic accuracy of circulating miR-126 for malignant pleural mesothelioma (MPM), but the results varied. Therefore, we performed a systematic review and meta-analysis to investigate the diagnostic value of circulating miR-126 for MPM. METHODS: The PubMed database was searched to identify potentially eligible studies published before October 2020. The studies investigating the diagnostic value of circulating miR-126 for MPM were included in a systematic review and meta-analysis. A bivariate model was used to pool eligible studies' sensitivity and specificity. The revised tool for the quality assessment of diagnostic accuracy studies (QUADAS-2) was used to assess eligible studies' quality. RESULTS: Four studies with 156 MPM patients and 459 controls were included in this systematic review and meta-analysis. The pooled diagnostic sensitivity and specificity of circulating miR-126 for MPM were 0.71 and 0.69, respectively. A high risk of bias was observed in the domains of patient selection, index test, and flow and timing. CONCLUSIONS: Circulating miR-126 has limited value for diagnosing MPM. Considering that the available studies have a high risk of bias, further rigorous studies are needed to assess the diagnostic value of circulating miR-126 for MPM.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.244
GPT teacher head0.486
Teacher spread0.243 · 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 teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations9
Published2021
Admission routes1
Has abstractyes

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