ABSTRACT
Objective:To investigate the predictive value of enhanced CT-based radiomics for brain metastasis (BM) and selective use of prophylactic cranial irradiation (PCI) in limited-stage small cell lung cancer (LS-SCLC).Methods:Clinical data of 97 patients diagnosed with LS-SCLC confirmed by pathological and imaging examination in Shanxi Provincial Cancer Hospital from January 2012 to December 2018 were retrospectively analyzed. The least absolute shrinkage and selection operator (LASSO) Cox and Spearman correlation tests were used to select the radiomics features significantly associated with the incidence of BM and calculate the radiomics score. The calibration curve, the area under the receiver operating characteristic (ROC) curve (AUC), 5-fold cross-validation, decision curve analysis (DCA), and integrated Brier score (IBS) were employed to evaluate the predictive power and clinical benefits of the radiomics score. Kaplan-Meier method and log-rank test were adopted to draw survival curves and assess differences between two groups.Results:A total of 1272 radiomics features were extracted from enhanced CT. After the LASSO Cox regression and Spearman correlation tests, 8 radiomics features associated with the incidence of BM were used to calculate the radiomics score. The AUCs of radiomics scores to predict 1-year and 2-year BM were 0.845 (95% CI=0.746-0.943) and 0.878 (95% CI=0.774-0.983), respectively. The 5-fold cross validation, calibration curve, DCA and IBS also demonstrated that the radiomics model yielded good predictive performance and net clinical benefit. Patients were divided into the high-risk and low-risk cohorts based on the radiomics score. For patients at high risk, the 1-year and 2-year cumulative incidence rates of BM were 0% and 18.2% in the PCI group, and 61.8% and 75.4% in the non-PCI group, respectively ( P<0.001). In the PCI group, the 1-year and 2-year overall survival rates were 92.9% and 78.6%, and 85.3% and 36.8% in the non-PCI group, respectively ( P=0.023). For patients at low risk, the 1-year and 2-year cumulative incidence rates of BM were 0% and 0% in the PCI group, and 10.0% and 20.2% in the non-PCI group, respectively ( P=0.062). In the PCI group, the 1-year and 2-year overall survival rates were 100% and 77.0%, and 96.7% and 79.3% in the non-PCI group, respectively ( P=0.670). Conclusion:The radiomics model based on enhanced CT images yields excellent performance for predicting BM and individualized PCI.
ABSTRACT
Objective:To explore the prognostic value of pretreatment albumin in extranodal nasal type NK/T cell lymphoma (ENKTL).Methods:The clinical data of 184 ENKTL patients in Shanxi Province Cancer Hospital from January 2002 to December 2018 were retrospectively analyzed. The Contal-O'Quigley change point method was used to determine the optimal cut-off value of albumin for predicting the prognosis of patients. The propensity score matching (PSM) was used to minimize selection biases. The Kaplan-Meier method was used for survival analysis, and Cox proportional hazards model was used to determine the factors affecting survival. The time-dependent receiver operating characteristic curve, Akaike information criterion and integrated Brier score were used to evaluate the efficacy of international prognostic index (IPI), Korean prognostic index (KPI) and prognostic index of NK cell lymphoma (PINK) models incorporating albumin for predicting the prognosis of patients.Results:The optimal cut-off value of pretreatment albumin for predicting the prognosis of ENKTL patients was 37.5 g/L. The 3-year and 5-year overall survival (OS) rates in >37.5 g/L group (126 cases) were 66.2% and 60.3%, and the progression-free survival (PFS) rates were 58.8% and 49.6%; the 3-year and 5-year OS rates in ≤37.5 g/L group (58 cases) were 35.0% and 32.4%, and the PFS rates were 32.5% and 30.0%. The OS and PFS in > 37.5 g/L group were better than those in ≤37.5 g/L group (both P<0.001). After PSM, the OS and PFS in >37.5 g/L group were still better than those in ≤37.5 g/L group (both P = 0.002). Multivariate analysis showed that albumin was an independent influencing factor for OS ( RR = 0.419, 95% CI 0.266-0.660, P < 0.001) and PFS ( RR = 0.493, 95% CI 0.322-0.755, P < 0.001). After PSM, albumin was still an independent influencing factor for OS ( RR = 0.305, 95% CI 0.156-0.598, P = 0.001) and PFS ( RR = 0.341, 95% CI 0.185-0.627, P = 0.001). The prognostic prediction performance of the IPI, KPI and PINK models incorporating albumin were all improved. Conclusions:Pretreatment albumin is an important prognostic indicator for ENKTL.