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Record W3206009833 · doi:10.1155/2021/3456629

Systemic Inflammatory Markers for Predicting Overall Survival in Patients with Osteosarcoma: A Systematic Review and Meta‐Analysis

2021· review· en· W3206009833 on OpenAlex
Xiaotong Song, Hao Zhang, Fanxing Yin, Panpan Guo, Xiaocheng Yang, Jinzhu Liu, Yanshuo Han, Zhaozhou Ren

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

VenueMediators of Inflammation · 2021
Typereview
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsMedicineInternal medicineHazard ratioCochrane LibraryMeta-analysisOsteosarcomaOncologyLymphocytePopulationConfidence intervalGastroenterologyPathology

Abstract

fetched live from OpenAlex

Background . Inflammatory markers are associated with tumor genesis and progression, but their prognostic significance in osteosarcoma remains unclear. Therefore, we discussed the prognostic value of related inflammatory markers in osteosarcoma through a meta‐analysis and systematic review. These inflammatory markers include C‐reactive protein (CRP), neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio (PLR), and Glasgow prognostic score (GPS). Methods . The Chinese National Knowledge Infrastructure (CNKI), Wanfang, Chinese Scientific Journals (VIP), PubMed, Embase, and Cochrane libraries were searched. The design of meta‐analysis was made based on the PICOS (population, intervention/exposure, control, outcomes, and study design) principles, and STATA 15.1 was used to analyze the data. The Newcastle‐Ottawa scale (NOS) was used to assess the quality of included studies. Hazard ratios (HRs) for overall survival (OS) and disease‐specific survival (DPS) were extracted for the investigation of the prognostic value of inflammatory markers. Results . Twelve researches with 2162 osteosarcoma patients were included in total. The pooled results showed that elevated NLR, CRP, and GPS are all greatly related to shortening of OS among patients with osteosarcoma (HR = 1.68, P = 0.007, 95% CI: 1.15‐2.45; HR = 1.96, P = 0.002, 95% CI: 1.28‐3.00; HR = 2.54, P < 0.0001, 95% CI: 1.95‐3.31, respectively), and CRP level is significantly associated with shortening of DPS among patients with osteosarcoma (HR = 2.76, 95% CI:2.01‐3.80, P < 0.0001), additionally. However, the correlation between LMR or PLR and the prognosis of osteosarcoma is not statistically significant (HR = 0.60, 95% CI: 0.30‐1.18, P = 0.138; HR = 1.13, 95% CI: 0.85‐1.49, P = 0.405, respectively). The outcomes of subgroup analysis to NLR and CRP suggested that histology, ethnicity, metastasis, and sample size all have an impact on its prognosis of patients with osteosarcoma. Conclusion . Worsened prognosis may be related to high levels of NLR, CRP, and GPS before treatment rather than LMR or PLR, which can provide the basis for clinicians to judge the outcomes of prognosis. Trial Registration . PROSPERO ( CRD42021249954 ), https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=249954 .

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)0.003
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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.656
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0110.002
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 head0.018
GPT teacher head0.278
Teacher spread0.260 · 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