MétaCan
Menu
Back to cohort
Record W4321597851 · doi:10.3390/diagnostics13050843

Systemic Immune-Inflammation Index and Mortality in Testicular Cancer: A Systematic Review and Meta-Analysis

2023· review· en· W4321597851 on OpenAlexaboutno aff
Farley E. Salazar-Valdivia, Valeria A. Valdez-Cornejo, Juan R. Ulloque‐Badaracco, Enrique A. Hernández-Bustamante, Esteban A. Alarcón‐Braga, Melany D. Mosquera-Rojas, Diana P. Garrido-Matta, Percy Herrera‐Añazco, Vicente A. Benítes-Zapata, Adrían V. Hernández

Bibliographic record

VenueDiagnostics · 2023
Typereview
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHazard ratioMeta-analysisInternal medicineOncologyCancerObservational studySystemic inflammationInflammationConfidence interval

Abstract

fetched live from OpenAlex

The systemic immune-inflammation index (SIII) is a marker studied in multiple types of urologic cancer. This systematic review evaluates the association between SIII values with overall survival (OS) and progression-free survival (PFS) in testicular cancer. We searched observational studies in five databases. The quantitative synthesis was performed using a random-effects model. The risk of bias was assessed using the Newcastle–Ottawa Scale (NOS). The only measure of the effect was the hazard ratio (HR). A sensitivity analysis was performed according to the risk of bias in the studies. There were 833 participants in a total of 6 cohorts. We found that high SIII values were associated with worse OS (HR = 3.28; 95% CI 1.3–8.9; p < 0.001; I2 = 78) and PFS (HR = 3.9; 95% CI 2.53–6.02; p < 0.001; I2 = 0). No indication of small study effects was found in the association between SIII values and OS (p = 0.5301). High SIII values were associated with worse OS and PFS. However, further primary studies are suggested to enhance the effect of this marker in different outcomes of testicular cancer patients.

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)0.006
metaresearch head score (Gemma)0.017
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.018
Bibliometrics0.0050.007
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.090
GPT teacher head0.386
Teacher spread0.295 · 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

Citations22
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueDiagnosticsSame topicInflammatory Biomarkers in Disease PrognosisFrench-language works237,207