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Chinese Journal of Radiation Oncology ; (6): 417-420, 2019.
Artigo em Chinês | WPRIM | ID: wpr-755040

RESUMO

Objective To externally validate the accuracy of combined use of neutrophil-lymphocyte ratio (NLR),V20,and Dmean in predicting the incidence of grade Ⅲ or higher radiation-induced lung injury (RILI) in lung cancer patients.Methods A total of 166 lung cancer patients,who participated in the model establishment were selected into the internal validation group,and 85 lung cancer patients who received intensity-modulated radiotherapy in our department between June 2016 and June 2018 were assigned into the external validation group.The incidence rate of grade 3 or higher RILI was statistically compared between the internal and external validation groups.Multivariate logistic analysis was performed for NLR,V20 and Dmean The discrimination degree of the predictive model was evaluated by using ROC curve in combination with NLR,V20 and Dmean The calibration degree of the predictive model was assessed by Hosmer-Lemeshow test.Results The incidence rate of grade 3 or higher RILI in the internal and external validation groups was 23.8% and 22.9%.Multivariate logistic analysis demonstrated that NLR,V20 and Dmean significantly differed in the internal validation group (P=0.032,0.006 and 0.005).However,only V20 significantly differed in the external validation group (P=0.038).The discrimination and calibration degree of RILI was almost consistent between the internal and external validation groups (both P>0.05).The area under the curve (AUC) predicted by NLR,V20,Dmean and the combination of three indexes were 0.611,0.646,0.682 and 0.775 in the internal validation group,and 0.544,0.702,0.658 and 0.754 in the external validation group,respectively.The calibration degree in the internal validation group was P=2.797and 0.834,P=2.452 and 0.653 in the external validation group.Conclusion Combined application of NLR,V20 and Dmean can accurately predict the incidence of grade Ⅲ or higher RILI in lung can cancer patients,which has been validated by external dataset.

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