Reply to: Comments on “Nomograms based on inflammatory biomarkers for predicting tumor grade and micro-vascular invasion in stage I/II hepatocellular carcinoma”
Author(s) -
Peng Li,
Wei Huang,
Feng Wang,
Ye-Fang Ke,
Lin Gao,
Keqing Shi,
Mengtao Zhou,
Bicheng Chen
Publication year - 2019
Publication title -
bioscience reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 77
eISSN - 1573-4935
pISSN - 0144-8463
DOI - 10.1042/bsr20193401
Subject(s) - nomogram , multivariate statistics , hepatocellular carcinoma , multivariate analysis , stage (stratigraphy) , medicine , oncology , categorical variable , proportional hazards model , computer science , machine learning , biology , paleontology
We appreciate to receive commentary from Dr Guangtong Deng and Dr Liang Xiao to our article, "Nomograms based on inflammatory biomarkers for predicting tumor grade and micro-vascular invasion in stage I/II hepatocellular carcinoma". First, neutrophil-to-lymphocyte ratio (NLR) and derived NLR (dNLR) are two different parameters. Some studies show that NLR is inconsistent with dNRL in prognostic value through multivariate Cox regression, therefore, it is reasonable that both NLR and dNLR entered into multivariate analysis simultaneously. Second, it is common that articles of predictive nomograms turned continuous variables into categorical variables. The reason is that the categorization of patient clinical variables is beneficial to doctors to make decisions based on the risk level of individual patients in clinical. At last, multicenter validation is quite difficult and we have listed the shortcomings in the limitations of our article. Further validation will need the joint efforts by other institutions.
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