Nomogram for preoperative estimation of lung cancer risk - Evidencio
Nomogram for preoperative estimation of lung cancer risk
This model consists of seven liver function biomarkers ( alkaline-phosphatase [ALP], alanine-transaminase [ALT], total-bilirubin [TBIL], albumin [ALB], gamma- glutamyltransferase [GGT], aspartate-transaminase [AST] and total protein[TP])and seven traditional predictors (age, sex, history of hay fever and/or allergic rhinitis and/or eczma, history of emphyse and/or machronic and/or bronchitis, family history of lung cancer, FEV1 and smoking-packyears). Our study is the first to assess the predictive ability of liver function biomarkers in lung cancer risk model.
Research authors: Xiang Yu Sun
Version: 1.0
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  • Oncology
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You have possibility of lung cancer

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Using backward stepwise logistic regression selection, a lung cancer risk prediction model incorporating liver function biomarkers was developed.  Enter the calculator interface, inputing personal data of the predictors, the individualized lung cancer risk probabilities can be quickly calculated.
The full model generated a C-index of 0.813 (95%CI, 0.805 to 0.820). Significance was observed when excluding these biomarkers (C-index = 0.802, 95%CI, 0.794 to 0.810, P < 0.001). Similarly, we found significant improvement of both category NRI (0.040, 95% CI, 0.034 to 0.077, P < 0.001) and continuous NRI (0.030, 95% CI, 0.017 to 0.047, P < 0.001). Hosmer-lemeshow test showed the predicted and observed lung cancer risk probabilities agreed well, suggesting that the full model was well calibrated (P value = 0.1631). 

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