| 11. |
- Omazic, B., et al.
(author)
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A Preliminary Report : Radical Surgery and Stem Cell Transplantation for the Treatment of Patients with Pancreatic Cancer
- 2017
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In: Journal of immunotherapy (1997). - : Lippincott Williams and Wilkins. - 1524-9557 .- 1537-4513. ; 40:4, s. 132-139
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Journal article (peer-reviewed)abstract
- We examined the immunologic effects of allogeneic hematopoietic stem cell transplantation (HSCT) in the treatment of pancreatic ductal adenocarcinoma, a deadly disease with a median survival of 24 months for resected tumors and a 5-year survival rate of 6%. After adjuvant chemotherapy, 2 patients with resected pancreatic ductal adenocarcinoma underwent HSCT with HLA-identical sibling donors. Comparable patients who underwent radical surgery, but did not have a donor, served as controls (n=6). Both patients developed humoral and cellular (ie, HLA-A∗01:01-restricted) immune responses directed against 2 novel tumor-associated antigens (TAAs), INO80E and UCLH3 after HSCT. Both TAAs were highly expressed in the original tumor tissue suggesting that HSCT promoted a clinically relevant, long-lasting cellular immune response. In contrast to untreated controls, who succumbed to progressive disease, both patients are tumor-free 9 years after diagnosis. Radical surgery combined with HSCT may cure pancreatic adenocarcinoma and change the cellular immune repertoire capable of responding to clinically and biologically relevant TAAs.
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| 12. |
- Alkhamisi, M. A., et al.
(author)
-
Estimation of SUR model with VAR(p) disturbances
- 2019
-
In: Communications in Statistics: Case Studies, Data Analysis and Applications. - : Taylor & Francis Group. - 2373-7484. ; 5:4, s. 432-453
-
Journal article (peer-reviewed)abstract
- The multiple time series and ridge regression techniques are proposed for modeling and analyzing a scaled real life (or a simulated) data as a SUR model with VAR(p) disturbances. The regression coefficients are estimated via the generalized least squares method if collinearity is weak and otherwise the regression coefficients are estimated by the generalized ridge regression method. Small sample likelihood ratio test statistic and model selection criteria are employed for selecting the smallest possible lag order for the VAR process. Moreover, Monte Carlo simulations (1000 replications) are conducted to examine the properties of some new and some of the existing ridge parameters in rectifying the collinearity problem in SUR models with VAR(2) disturbances via the trace(MSE) and condition number criteria. Two data sets are analyzed to illustrate the findings of the article.
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| 13. |
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| 14. |
- Gaiser, RA, et al.
(author)
-
Integrated targeted metabolomic and lipidomic analysis: A novel approach to classifying early cystic precursors to invasive pancreatic cancer
- 2019
-
In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10208-
-
Journal article (peer-reviewed)abstract
- Pancreatic cystic neoplasms (PCNs) are a highly prevalent disease of the pancreas. Among PCNs, Intraductal Papillary Mucinous Neoplasms (IPMNs) are common lesions that may progress from low-grade dysplasia (LGD) through high-grade dysplasia (HGD) to invasive cancer. Accurate discrimination of IPMN-associated neoplastic grade is an unmet clinical need. Targeted (semi)quantitative analysis of 100 metabolites and >1000 lipid species were performed on peri-operative pancreatic cyst fluid and pre-operative plasma from IPMN and serous cystic neoplasm (SCN) patients in a pancreas resection cohort (n = 35). Profiles were correlated against histological diagnosis and clinical parameters after correction for confounding factors. Integrated data modeling was used for group classification and selection of the best explanatory molecules. Over 1000 different compounds were identified in plasma and cyst fluid. IPMN profiles showed significant lipid pathway alterations compared to SCN. Integrated data modeling discriminated between IPMN and SCN with 100% accuracy and distinguished IPMN LGD or IPMN HGD and invasive cancer with up to 90.06% accuracy. Free fatty acids, ceramides, and triacylglycerol classes in plasma correlated with circulating levels of CA19-9, albumin and bilirubin. Integrated metabolomic and lipidomic analysis of plasma or cyst fluid can improve discrimination of IPMN from SCN and within PMNs predict the grade of dysplasia.
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| 15. |
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| 16. |
- Kibria, B. M. Golam, et al.
(author)
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A simulation study of some biasing parameters for the ridge type estimation of Poisson regression
- 2015
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In: Communications in statistics. Simulation and computation. - : Taylor & Francis. - 0361-0918 .- 1532-4141. ; 44:4, s. 943-957
-
Journal article (peer-reviewed)abstract
- This paper proposes several estimators for estimating the ridge parameter k based for Poisson ridge regression (RR) model. These estimators have been evaluated by means of Monte Carlo simulations. As performance criteria, we have calculated the mean squared error (MSE), the mean value and the standard deviation of k. The first criterion is commonly used, while the other two have never been used when analyzing Poisson RR. However, these performance criterion are very informative because, if several estimators have an equal estimated MSE then those with low average value and standard deviation of k should be preferred. Based on the simulated results we may recommend some biasing parameters which may be useful for the practitioners in the field of health, social and physical sciences.
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| 17. |
- Månsson, Kristofer, et al.
(author)
-
A New Liu Type of Estimators for the Restricted SUR Estimator
- 2019
-
In: Journal of Modern Applied Statistical Methods. - : JMASM Inc.. - 1538-9472. ; 18:1, s. 1-11
-
Journal article (peer-reviewed)abstract
- A new Liu type of estimator for the seemingly unrelated regression (SUR) models is proposed that may be used when estimating the parameters vector in the presence of multicollinearity if the it is suspected to belong to a linear subspace. The dispersion matrices and the mean squared error (MSE) are derived. The new estimator may have a lower MSE than the traditional estimators. It was shown using simulation techniques the new shrinkage estimator outperforms the commonly used estimators in the presence of multicollinearity.
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| 18. |
- Månsson, Kristofer, et al.
(author)
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A restricted Liu estimator for binary regression models and its application to an applied demand system
- 2016
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In: Journal of Applied Statistics. - : Taylor & Francis. - 0266-4763 .- 1360-0532. ; 43:6, s. 1119-1127
-
Journal article (peer-reviewed)abstract
- In this article, we propose a restricted Liu regression estimator (RLRE) for estimating the parameter vector, β, in the presence of multicollinearity, when the dependent variable is binary and it is suspected that β may belong to a linear subspace defined by Rβ = r. First, we investigate the mean squared error (MSE) properties of the new estimator and compare them with those of the restricted maximum likelihood estimator (RMLE). Then we suggest some estimators of the shrinkage parameter, and a simulation study is conducted to compare the performance of the different estimators. Finally, we show the benefit of using RLRE instead of RMLE when estimating how changes in price affect consumer demand for a specific product.
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| 19. |
- Månsson, Kristofer, 1983-, et al.
(author)
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On the Estimation of the CO2 Emission, Economic Growth and Energy Consumption Nexus Using Dynamic OLS in the Presence of Multicollinearity
- 2018
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In: Sustainability. - : MDPI. - 2071-1050. ; 10:5
-
Journal article (peer-reviewed)abstract
- This paper introduces shrinkage estimators (Ridge DOLS) for the dynamic ordinary least squares (DOLS) cointegration estimator, which extends the model for use in the presence of multicollinearity between the explanatory variables in the cointegration vector. Both analytically and by using simulation techniques, we conclude that our new Ridge DOLS approach exhibits lower mean square errors (MSE) than the traditional DOLS method. Therefore, based on the MSE performance criteria, our Monte Carlo simulations demonstrate that our new method outperforms the DOLS under empirically relevant magnitudes of multicollinearity. Moreover, we show the advantages of this new method by more accurately estimating the environmental Kuznets curve (EKC), where the income and squared income are related to carbon dioxide emissions. Furthermore, we also illustrate the practical use of the method when augmenting the EKC curve with energy consumption. In summary, regardless of whether we use analytical, simulation-based, or empirical approaches, we can consistently conclude that it is possible to estimate these types of relationships in a considerably more accurate manner using our newly suggested method.
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| 20. |
- Månsson, Kristofer, 1983-, et al.
(author)
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Performance of Some Ridge Regression Estimators for the Multinomial Logit Model
- 2018
-
In: Communications in Statistics - Theory and Methods. - : Taylor & Francis. - 0361-0926 .- 1532-415X. ; 47:12, s. 2795-2804
-
Journal article (peer-reviewed)abstract
- This article considers several estimators for estimating the ridge parameter k for multinomial logit model based on the work of Khalaf and Shukur (2005), Alkhamisi et al. (2006), and Muniz et al. (2012). The mean square error (MSE) is considered as the performance criterion. A simulation study has been conducted to compare the performance of the estimators. Based on the simulation study we found that increasing the correlation between the independent variables and the number of regressors has negative effect on the MSE. However, when the sample size increases the MSE decreases even when the correlation between the independent variables is large. Based on the minimum MSE criterion some useful estimators for estimating the ridge parameter k are recommended for the practitioners
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