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An inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy

Overview of attention for article published in BMC Cancer, June 2018
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1 Redditor

Citations

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9 Dimensions

Readers on

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10 Mendeley
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Title
An inflammation-related nomogram for predicting the survival of patients with non-small cell lung cancer after pulmonary lobectomy
Published in
BMC Cancer, June 2018
DOI 10.1186/s12885-018-4513-4
Pubmed ID
Authors

Ying Wang, Xiao Qu, Ngar-Woon Kam, Kai Wang, Hongchang Shen, Qi Liu, Jiajun Du

Abstract

Emerging inflammatory response biomarkers are developed to predict the survival of patients with cancer, the aim of our study is to establish an inflammation-related nomogram based on the classical predictive biomarkers to predict the survivals of patients with non-small cell lung cancer (NSCLC). Nine hundred and fifty-two NSCLC patients with lung cancer surgery performed were enrolled into this study. The cutoffs of inflammatory response biomarkers were determined by Receiver operating curve (ROC). Univariate and multivariate analysis were conducted to select independent prognostic factors to develop the nomogram. The median follow-up time was 40.0 months (range, 1 to 92 months). The neutrophil to lymphocyte ratio (cut-off: 3.10, HR:1.648, P = 0.045) was selected to establish the nomogram which could predict the 5-year OS probability. The C-index of nomogram was 0.72 and the 5-year OS calibration curve displayed an optimal agreement between the actual observed outcomes and the predictive results. Neutrophil to lymphocyte ratio was shown to be a valuable biomarker for predicting survival of patients with NSCLC. The addition of neutrophil to lymphocyte ratio could improve the accuracy and predictability of the nomogram in order to provide reference for clinicians to assess patient outcomes.

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 20%
Student > Bachelor 2 20%
Researcher 1 10%
Student > Postgraduate 1 10%
Unknown 4 40%
Readers by discipline Count As %
Medicine and Dentistry 5 50%
Biochemistry, Genetics and Molecular Biology 1 10%
Unknown 4 40%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 July 2018.
All research outputs
#11,692,604
of 13,165,892 outputs
Outputs from BMC Cancer
#4,008
of 4,915 outputs
Outputs of similar age
#233,048
of 268,382 outputs
Outputs of similar age from BMC Cancer
#1
of 1 outputs
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