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Record W4308125372 · doi:10.3390/diagnostics12112655

Lymphocyte-to-Monocyte Ratio and Clinical Outcomes in Cholangiocarcinoma: A Systematic Review and Meta-Analysis

2022· review· en· W4308125372 on OpenAlexaboutno aff
Giuseppe Dotto-Vasquez, Andrea K. Villacorta-Ampuero, Juan R. Ulloque‐Badaracco, Enrique A. Hernández-Bustamante, Esteban A. Alarcón‐Braga, Percy Herrera‐Añazco, Vicente A. Benítes-Zapata, Adrían V. Hernández

Bibliographic record

VenueDiagnostics · 2022
Typereview
Languageen
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisHazard ratioPublication biasInternal medicineFunnel plotConfidence intervalOncologyGastroenterology

Abstract

fetched live from OpenAlex

Lymphocyte-to-Monocyte ratio (LMR) has shown an association with survival outcomes in several oncological diseases. This study aimed to evaluate the association between LMR and clinical outcomes for cholangiocarcinoma patients. A systematic review and meta-analysis were performed to assess the association between LMR values and overall survival (OS), disease-free survival (DFS), recurrence-free survival (RFS) and time to recurrence (TTR) in cholangiocarcinoma patients. We used Hazard ratio (HR) and their 95% confidence interval (CI) as a measure of effect for the random effect model meta-analysis. The Newcastle–Ottawa Scale was used for quality assessment. The Egger test and funnel plot were developed for approaching publication bias. A total of 19 studies were included in this study (n = 3860). The meta-analysis showed that cholangiocarcinoma patients with low values of LMR were associated with worse OS (HR: 0.82; 95% CI: 0.71–0.96; I2 = 86%) and worse TTR (HR: 0.71; 95% CI: 0.58–0.86; I2 = 0%). DFS and RFS also were evaluated; however, they did not show statistically significant associations. Low LMR values were associated with a worse OS and TTR.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.751
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0160.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.172
GPT teacher head0.422
Teacher spread0.250 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

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