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Record W2896397428 · doi:10.2147/cmar.s174143

Long noncoding RNA ROR as a novel biomarker for progress and prognosis outcome in human cancer: a meta-analysis in the Asian population

2018· article· en· W2896397428 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCancer Management and Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCochrane LibraryOncologyInternal medicineOdds ratioHazard ratioMeta-analysisPopulationConfidence interval

Abstract

fetched live from OpenAlex

Background: Long intergenic non-protein coding RNA, a regulator of reprogramming (ROR), has been found to play an oncogene role in various human malignant tumors. This meta-analysis aimed to synthesize available data to verify the association between clinical prognosis value and ROR expression level. Materials and methods: We performed a systematic search by using PubMed (Medline), Embase, Cochrane Library, ScienceDirect, Springer, and ISI Web of Knowledge from inception to November 15, 2017. Eleven studies with 903 patients were included in this meta-analysis according to the exclusion and inclusion criteria, and the quality of the publications was assessed by using the Newcastle-Ottawa Scale. Pooled odds ratios (OR) and hazard ratios (HR) with 95% CI were used to describe the effect. Results: The results showed that overexpression of ROR is positively associated with lymph node metastasis (OR=4.472, 95% CI: 3.212–6.225, Z=8.87, P =0.000), tumor invasion depth (OR=9.93, 95% CI: 5.33–18.47, Z=7.24, P <0.001), TNM stage (III/IV vs I/II, OR=2.96, 95% CI: 2.18–4.02, Z=6.95, P <0.001), distant metastasis (OR=3.142, 95% CI: 2.187–4.513, Z=6.20, P <0.001) respectively. Additionally, high expression of ROR was significantly correlated with unfavorable disease-free survival (DFS) (HR=2.74, 95% CI: 1.65–3.82, Z=4.93, P =0.000) and overall survival (OS) (HR=2.09, 95% CI: 1.64–2.54, Z=9.07, P <0.001). Subgroup analysis demonstrated that neither cancer type (digestive or respiratory system) nor sample size (more or less than 100) did not alter the prognostic value of ROR. Furthermore, we performed publication bias and sensitivity analysis in order to examine the stability of meta-analysis of ROR along with OS, which showed that the shape of the funnel plot was nearly symmetrical and the resulting pattern was not significantly influenced while disconnecting each suitable study. Conclusion: In accordance with these results, we suggested that the overexpression of long noncoding RNA ROR could act as a novel biomarker for predicting poor prognosis in different human cancers. Keywords: long noncoding RNA, regulator of reprogramming, ROR, prognosis, cancers, meta-analysis

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.162
GPT teacher head0.465
Teacher spread0.303 · 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