Evidence map›Paper›PMID 28008988›Full record

Trial reportScientific reports2016

Prognostic value of inflammation-based scores in patients with osteosarcoma.

Bangjian Liu, Yujing Huang, Yuanjue Sun, Jianjun Zhang, Yang Yao, Zan Shen, Dongxi Xiang, Aina He

Open access · goldAbstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed, 7 pooled it
2.4field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

63 citing papers in PubMed, 7 syntheses or guidelines pooled it, 88 citations in OpenAlex.

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3 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 2 countries.

Bangjian LiuDepartment of Neurology, Affiliated Sixth People's Hospital, Shanghai Jiaotong University, No. 600, Yishan Road, 200233 Shanghai, People's Republic of China.
Yujing HuangDepartment of Oncology, Affiliated Sixth People's Hospital, Shanghai Jiaotong University, No. 600, Yishan Road, 200233 Shanghai, People's Republic of China.
Yuanjue SunDepartment of Oncology, Affiliated Sixth People's Hospital, Shanghai Jiaotong University, No. 600, Yishan Road, 200233 Shanghai, People's Republic of China.
Jianjun ZhangDepartment of Oncology, Affiliated Sixth People's Hospital, Shanghai Jiaotong University, No. 600, Yishan Road, 200233 Shanghai, People's Republic of China.
Yang YaoDepartment of Oncology, Affiliated Sixth People's Hospital, Shanghai Jiaotong University, No. 600, Yishan Road, 200233 Shanghai, People's Republic of China.
Zan ShenDepartment of Oncology, Affiliated Sixth People's Hospital, Shanghai Jiaotong University, No. 600, Yishan Road, 200233 Shanghai, People's Republic of China.
Dongxi XiangDepartment of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Aina HeDepartment of Oncology, Affiliated Sixth People's Hospital, Shanghai Jiaotong University, No. 600, Yishan Road, 200233 Shanghai, People's Republic of China.
Shanghai Sixth People's Hospital · CNBrigham and Women's Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systemic inflammation responses have been associated with cancer development and progression. C-reactive protein (CRP), Glasgow prognostic score (GPS), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and neutrophil-platelet score (NPS) have been shown to be independent risk factors in various types of malignant tumors. This retrospective analysis of 162 osteosarcoma cases was performed to estimate their predictive value of survival in osteosarcoma. All statistical analyses were performed by SPSS statistical software. Receiver operating characteristic (ROC) analysis was generated to set optimal thresholds; area under the curve (AUC) was used to show the discriminatory abilities of inflammation-based scores; Kaplan-Meier analysis was performed to plot the survival curve; cox regression models were employed to determine the independent prognostic factors. The optimal cut-off points of NLR, PLR, and LMR were 2.57, 123.5 and 4.73, respectively. GPS and NLR had a markedly larger AUC than CRP, PLR and LMR. High levels of CRP, GPS, NLR, PLR, and low level of LMR were significantly associated with adverse prognosis (P < 0.05). Multivariate Cox regression analyses revealed that GPS, NLR, and occurrence of metastasis were top risk factors associated with death of osteosarcoma patients.

Indexed as

AdultBone NeoplasmsChildChild, PreschoolDisease-Free SurvivalFemaleHumansInflammationMaleMiddle AgedOsteosarcomaRetrospective StudiesSurvival Rate

Identifiers

PMID28008988
PMCPMC5180218
OpenAlexW2564198898

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.