AIM:Clinicopathologic factors predicting overall survival (OS) would help identify a subset to benefit from adjuvant therapy. METHODS: One hundred and sixty-nine patients patients from 1984 to 2009 with curative resec...AIM:Clinicopathologic factors predicting overall survival (OS) would help identify a subset to benefit from adjuvant therapy. METHODS: One hundred and sixty-nine patients patients from 1984 to 2009 with curative resections for pancreatic adenocarcinoma were included. Tumors were staged by American Joint Committee on Cancer 7th edition criteria. Univariate and multivariable analyses were performed using Kaplan-Meier methodology or Cox proportional hazard models. Log-rank tests were performed. Statistical inferences were assessed by two-sided 5% significance level. RESULTS: Median age was 67.1 (57.2-73.0) years with equal gender distribution. Tumors were in the head (89.3%) or body/tail (10.7%). On univariate analysis, adjuvant therapy, lymph node (LN) ratio, histologic grade, negative margin status, absence of peripancreatic extension, and T stage were associated with improved OS. Adjuvant therapy, LN ratio, histologic grade, number of nodes examined, negative LN status, and absence of peripancreatic extension were associated with improved recurrence-free survival (RFS). On multivariable analysis, LN ratio and carbohydrate antigen (CA) 19-9 levels were associated with OS. LN ratio was associated with RFS. CONCLUSION: The LN ratio and CA 19-9 levels are independent prognostic factors following curative resections of pancreatic cancer.展开更多
In the conventional differential quadrature （DQ） method the functional values along a mesh line are used to approximate derivatives and its application is limited to regular regions. In this paper, a local different...In the conventional differential quadrature （DQ） method the functional values along a mesh line are used to approximate derivatives and its application is limited to regular regions. In this paper, a local differential quadrature （LDQ） method was developed by using irregular distributed nodes, where any spatial derivative at a nodal point is approximated by a linear weighted sum of the functional values of nodes in the local physical domain. The weighting coefficients in the new approach are determined by the quadrature rule with the aid of nodal interpolation. Since the proposed method directly approximates the derivative, it can be consistently well applied to linear and nonlinear problems and the mesh-free feature is still kept. Numerical examples are provided to validate the LDQ method.展开更多
文摘AIM:Clinicopathologic factors predicting overall survival (OS) would help identify a subset to benefit from adjuvant therapy. METHODS: One hundred and sixty-nine patients patients from 1984 to 2009 with curative resections for pancreatic adenocarcinoma were included. Tumors were staged by American Joint Committee on Cancer 7th edition criteria. Univariate and multivariable analyses were performed using Kaplan-Meier methodology or Cox proportional hazard models. Log-rank tests were performed. Statistical inferences were assessed by two-sided 5% significance level. RESULTS: Median age was 67.1 (57.2-73.0) years with equal gender distribution. Tumors were in the head (89.3%) or body/tail (10.7%). On univariate analysis, adjuvant therapy, lymph node (LN) ratio, histologic grade, negative margin status, absence of peripancreatic extension, and T stage were associated with improved OS. Adjuvant therapy, LN ratio, histologic grade, number of nodes examined, negative LN status, and absence of peripancreatic extension were associated with improved recurrence-free survival (RFS). On multivariable analysis, LN ratio and carbohydrate antigen (CA) 19-9 levels were associated with OS. LN ratio was associated with RFS. CONCLUSION: The LN ratio and CA 19-9 levels are independent prognostic factors following curative resections of pancreatic cancer.
文摘In the conventional differential quadrature （DQ） method the functional values along a mesh line are used to approximate derivatives and its application is limited to regular regions. In this paper, a local differential quadrature （LDQ） method was developed by using irregular distributed nodes, where any spatial derivative at a nodal point is approximated by a linear weighted sum of the functional values of nodes in the local physical domain. The weighting coefficients in the new approach are determined by the quadrature rule with the aid of nodal interpolation. Since the proposed method directly approximates the derivative, it can be consistently well applied to linear and nonlinear problems and the mesh-free feature is still kept. Numerical examples are provided to validate the LDQ method.
