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Record W2325418286 · doi:10.2147/ott.s104004

Prognostic value of IGF-1R expression in bone and soft tissue sarcomas: comments on a meta-analysis by Liang et al

2016· article· en· W2325418286 on OpenAlex
Zhihong Li, Chao Tu, Jieyu He

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

VenueOncoTargets and Therapy · 2016
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsnot available
FundersNatural Science Foundation of Hunan ProvinceNational Natural Science Foundation of China
KeywordsMedicineBone SarcomaSoft tissueOsteosarcomaMeta-analysisSarcomaSubgroup analysisValue (mathematics)Soft tissue sarcomaOrthopedic surgeryOncologyInternal medicinePathologySurgeryComputer science

Abstract

fetched live from OpenAlex

Recently, we read with deep interest a meta-analysis by Liang et al entitled "Prognostic value of IGF-1R expression in bone and soft tissue sarcomas: a meta-analysis" 1 published in OncoTargets and Therapy. In this article, the investigators systematically reviewed the trials on the effects of IGF-1R expression in various bone and soft tissue sarcomas (BSTSs) and performed a meta-analysis. They reached an important conclusion that elevated IGF-1R expression was associated with poor overall survival in BSTS patients. Furthermore, subgroup analysis revealed that IGF-1R level was negatively correlated with prognosis in osteosarcoma but not significantly associated with Ewing's sarcoma. Nevertheless, before their results can be accepted, some worthwhile issues need to be addressed first. 1. To begin with, there are quite a few deficiencies in the literature research. First, only two electronic databases (PubMed and Web of Science) were systematically searched to identify eligible studies. In our opinion, more electronic databases, including Embase, Ovid, Scopus, the Cochrane Library, and Cochrane Central Register of Controlled Trials, and several Chinese databases (CNKI (Chinese National Knowledge Infrastructure), CBM (Chinese Biology Medicine) disc, VIP, Wanfang database, etc) should be thoroughly searched to achieve a comprehensive literature retrieval. Second, the search strategy report of database and manual search protocol were not clearly described, 1 which may be regarded as a flaw in the metaanalysis. Third, the publication language of selected literature was strangely limited to English, which could inevitably lead to potential language bias. 1 2. With respect to quality assessment section, the investigators clarified that "A study was considered high-quality if it achieved a score of 7 or more", while a low-quality study conducted by van Gaal et al 2 with a Newcastle-Ottawa quality assessment scale score of 6 was not excluded by the investigators 1 (Table We would like to know the possible reason for the inclusion of this study. In addition, the authors claimed that they performed this meta-analysis in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) standardized guidelines. 3 However, sensitivity analysis, a procedure which is strongly recommended in PRISMA guidelines, was not performed in this review. We take the attitude that any effort to increase the credibility of meta-analysis should be attached importance

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)0.000
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 score0.187
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.040
GPT teacher head0.330
Teacher spread0.291 · 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