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Record W4308352232 · doi:10.3390/curroncol29110661

Correlation between Serum 25-Hydroxyvitamin D Levels and Gastric Cancer: A Systematic Review and Meta-Analysis

2022· review· en· W4308352232 on OpenAlexvenueno aff
Xing Liu, Yueyue Zhou, Xihuan Zou

Bibliographic record

VenueCurrent Oncology · 2022
Typereview
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMedicineMeta-analysisCancerVitamin D and neurologySystematic reviewInternal medicineBioinformaticsOncologyMEDLINEBiology

Abstract

fetched live from OpenAlex

The purpose of this meta-analysis was to evaluate the relationship between serum 25-hydroxyvitamin D[25(OH)D] levels and gastric cancer. PubMed, Embase, Cochrane Library, Web of Science, The China Academic Journals full-text database, Wanfang Database of Chinese Academic Journals, VIP Chinese Science and Technology Periodicals database, and Chinese Biomedical Literature database were systematically searched. Case-control studies on the correlation between serum 25-hydroxyvitamin D levels and gastric cancer were retrieved, and the data extracted were analyzed. The results of 9 case-control studies containing 671 patients showed that serum 25(OH)D levels in the gastric cancer group were lower than those in the control group (weighted mean difference (WMD) = −8.90, 95% confidence interval (CI): −11.5, −6.32, p < 0.01); the risk of vitamin D deficiency in the gastric cancer group was higher than that in the control group (Odds ratio = 3.09, 95% CI: 1.96, 4.87, p < 0.01). The serum 25(OH)D levels in patients with well and moderately differentiated gastric cancer were higher than those in patients with poorly differentiated gastric cancer (WMD = −3.58, 95% CI: −6.41, −0.74, p = 0.01). Thus, low levels of vitamin D may increase the risk of gastric cancer. Systematic review registration: PROSPERO CRD42022327942.

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)0.011
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.026
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0190.039
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.427
GPT teacher head0.515
Teacher spread0.088 · 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 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

Citations8
Published2022
Admission routes1
Has abstractyes

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