Background. The systemic immune-inflammation index (SII) is a useful prognostic indicator for some types of cancer, but it remains to be elucidated if it is similarly useful for colon cancer.Objectives. This study aims to investigate the prognostic value of preoperative SII in patients with colon cancer undergoing radical surgery. Materials and methods.The clinical materials of 188 patients with colon cancer who underwent radical surgery from September 1, 2013, to August 31, 2018, in Zhongda Hospital at Southeast University (Nanjing, China) were collected retrospectively. The SII was calculated as platelet count × neutrophil count / lymphocyte count. All patients enrolled in the study were then assigned into 2 different groups according to the median value of SII for comparison of clinical features between the 2 groups. The survival curve was drawn using the Kaplan-Meier method. Univariate and multivariate analysis were performed using the Cox regression model, analyzing the independent risk factors. The independent factors were analyzed with the R software to construct a nomogram of 1-, 2-and 3-year disease-free survival (DFS) after operation. Lastly, a web-based probability calculator was constructed to dynamically predict the possibility of DFS of patients.Results. The SII could significantly predict DFS of patients with colon cancer with the median value of 514. 13xs. For DFS, multivariate Cox analysis indicated that age, tumor location, pathological N stage, and preoperative SII level were independent risk factors for patients with colon cancer after radical resection (p < 0.05). A nomogram and a web-based probability calculator were constructed based on these factors. Conclusions.The preoperative SII level can predict DFS in patients who received radical surgery with colon cancer. The nomogram constructed based on independent risk factors is helpful in predicting DFS of colon cancer patients in clinical practice.
Purpose Actin-like 6A (ACTL6A), a regulatory subunit of the ATP-dependent chromatin-remodeling complex SWI/SNF, acts as an oncogenic factor. This study is aimed at evaluating the correlation between ACTL6A expression and clinicopathological parameters in pancreatic cancer (PC) patients. Methods The differences of Actl6a mRNA expression between PC tissues and normal pancreatic tissues were analyzed in public databases, and ACTL6A expression was then determined and confirmed in 60 paired tissue specimens using immunohistochemistry staining. The association analysis between ACTL6A expression and the clinicopathological characteristics was analyzed, as well as Kaplan–Meier survival analysis. Univariate and multivariate Cox analyses were performed to identify the prognostic factors in the overall survival (OS) of patients with PC. Results The mRNA expression of Actl6a showed significantly higher in PC compared to normal controls (p < 0.05) from public databases. The score of immunohistochemistry staining further confirmed that ACTL6A expression was significantly upregulated in PC tissues (p < 0.001) through immunohistochemistry staining. High ACTL6A expression was associated with lymphovascular space invasion of PC. Kaplan–Meier analysis revealed that the high expression of ACTL6A was markedly associated with poor OS. Moreover, univariate and multivariate analysis demonstrated that ACTL6A acted as an independent risk factor for PC prognosis. Conclusion ACTL6A is upregulated in PC and acts as a risk factor for poor prognosis in patients with PC, and therefore clinicians could around it design preventive measures and individualized treatment to improve mortality in patients with PC.
Background: Radiation pneumonitis (RP) is one of the most severe complications of radiotherapy or concurrent chemoradiotherapy for thoracic segment esophageal squamous cell carcinoma (TSESCC) with delayed diagnose by conventional computed tomography (CT). The study aimed to develop a nomogram to predict the risk of RP early.Methods: Data was collected from 174 patients with clinicopathologically confirmed TSESCC from October 2013 to June 2020. Procalcitonin (PCT), C-reactive protein (CRP), and interleukin-6 (IL-6) levels in serum were dynamically monitored during radiotherapy. Lasso analysis was used for feature screening before multivariate logistic regression analysis to reduce the multicollinearity of variables. A nomogram combined with biological factors and clinical signs for individualized risk assessment and precise prediction of RP was developed and assed the performance with respect to its calibration, discrimination.Results: Of the 174 patients, 30 patients developed RP (grade ≥2) while 144 patients did not. After variable screening by Lasso analysis and logistics multivariate regression analysis, the predictor variables that were finally retained in the nomogram prediction model included IL-6, CRP, and radiotherapy techniques. The model displayed good discrimination with an AUC of 0.898 (95% CI: 0.849-0.947), with the sensitivity and specificity of 0.967 and of 0.736, respectively. This model also shows good calibration and clinical practical value. In addition, the study provided a web-based version of the dynamic nomogram to facilitate clinical application. Conclusions:The study provides a nomogram model containing IL-6, CRP, and radiotherapy (RT) techniques, which could be conveniently used for individualized prediction of RP in patients with TSESCC during radiotherapy or concurrent chemoradiotherapy.
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