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A Systemic Inflammation Response Score for Prognostic Prediction of Breast Cancer Patients Undergoing Surgery.

ABSTRACT: Background: Systemic inflammatory response is related to the occurrence, progression, and prognosis of cancers. In this research, a novel systemic inflammation response score (SIRS) was calculated, and its prognostic value for postoperative stage I-III breast cancer (BC) patients was analyzed. Methods: 1583 BC patients were included in this research. Patients were randomly divided into a training cohort (n = 1187) and validation cohort (n = 396). SIRS was established in the training cohort based on independent prognostic hematological indicator, its relationship between prognosis and clinical features was analyzed. Then, a nomogram consisted of SIRS and clinical features was established, its performance was examined by calibration plots and receiver operating characteristic curve analysis. Results: The SIRS was an independent prognostic indicator for BC patients, and a high-SIRS was related to multifocality, advanced N stage, and worse prognosis. Incorporating SIRS into a nomogram could accurately predict the prognosis of BC patients, the results of receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) of nomogram was up to 0.806 in training cohort and 0.905 in the validation cohort. Conclusion: SIRS was associated with the prognosis of patients with breast cancer. Nomogram based on SIRS can accurately predict the prognosis of breast cancer patients.

SUBMITTER: Zhang K

PROVIDER: S-EPMC8156296 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Oxidative stress plays an important role in the development of colorectal cancer (CRC). This study is aimed at developing and validating a novel scoring system, based on oxidative stress indexes, for prognostic prediction in CRC patients. A retrospective analysis of 1422 CRC patients who underwent surgical resection between January 2013 and December 2017 was performed. These patients were randomly assigned to the training set (n = 1022) or the validation set (n = 400). Cox regression model was used to analyze the laboratory parameters. The CRC-Integrated Oxidative Stress Score (CIOSS) was developed from albumin (ALB), direct bilirubin (DBIL), and blood urea nitrogen (BUN), which were significantly associated with survival in CRC patients. Furthermore, a survival nomogram was generated by combining the CIOSS with other beneficial clinical characteristics. The CIOSS generated was as follows: 0.074 × albumin (g/L), -0.094 × bilirubin (μmol/L), and -0.099 × blood urea nitrogen (mmol/L), based on the multivariable Cox regression analysis. Using 50% (0.1025) and 85% (0.481) of CIOSS as cutoff values, three prognostically distinct groups were formed. Patients with high CIOSS experienced worse overall survival (OS) (hazard ratio [HR] = 4.33; 95% confidence interval [CI], 2.80-6.68; P < 0.001) and worse disease-free survival (DFS) (HR = 3.02; 95% CI, 1.96-4.64; P < 0.001) compared to those with low CIOSS. This predictive nomogram had good calibration and discrimination. ROC analyses showed that the CIOSS possessed excellent performance (AUC = 0.818) in predicting DFS. The AUC of the OS nomogram based on CIOSS, TNM stage, T stage, and chemotherapy was 0.812, while that of the DFS nomogram based on CIOSS, T stage, and TNM stage was 0.855. Decision curve analysis showed that these two prediction models were clinically useful. CIOSS is a CRC-specific prognostic index based on the combination of available oxidative stress indexes. High CIOSS is a powerful indicator of poor prognosis. The CIOSS also showed better predictive performance compared to TNM stage in CRC patients.

Project description:Inflammation has a critical role in the development and progression of cancers. We developed a novel systemic inflammation score (SIS) based on lymphocyte, monocyte, and CA19-9 and explored its prognostic value in intrahepatic cholangiocarcinoma (ICC). From January 2005 to December 2011, 322 consecutive ICC patients who underwent curative resection in our center were included in this study, and validated in a retrospective study of 126 patients enrolled from 2012 to 2014. Clinicopathological variables including preoperative serum CA19-9 and LMR were analyzed. The cutoff values of CA19-9 and LMR were determined based on receiver operating characteristics curve analysis in the primary cohort. Kaplan-Meier curves and multivariate Cox-regression analyses were calculated for time to recurrence (TTR) and overall survival (OS). In univariate analysis of all patients, all three inflammatory and tumor marker including NLR ? 2.49 (P<0.001), LMR ? 4.45 (P=0.002), and CA19-9?89 (P<0.001) were associated with poor prognoses. When omitting SIS in multivariate analysis, preoperative LMR (P =0.006) and serum CA19-9 (P<0.001) were independent predictors of OS. In addition, elevated CA19-9 (P=0.001), multiple tumors (P<0.001), and lymph node metastasis (P<0.001) were significant predictors of worse recurrence free survival. Moreover, high SIS was significantly associated with aggressive tumor behaviours including large tumor size (P<0.001), multiple tumors (P=0.033), lymphonodus node metastasis (P=0.001), and high TNM stage (P<0.0001). Finally, univariate and multivariate analyses revealed the SIS was an independent predictor for TTR (HR=2.077, 95% CI, 1.365-3.162, P=0.001) and OS (HR=3.133 95% CI, 2.058-4.769, P<0.001). These results were further confirmed in the validation cohort. In conclusions, our findings demonstrate that the SIS as a potentially powerful prognostic biomarker in ICC that predicts poor clinical outcomes and is a promising tool for ICC treatment strategy decisions.

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A Systemic Inflammation Response Score for Prognostic Prediction of Breast Cancer Patients Undergoing Surgery.

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