Daniel R. Schmidt

Leukocyte Depletion in Allogeneic Blood Transfusion Does Not Change the Negative Influence on Survival Following Transthoracic Resection for Esophageal Cancer

BackgroundPerioperative transfusion of allogeneic blood has been hypothesized to have an immunomodulatory effect and influence survival in several cancer types. This study evaluates the association between receipt of leucocyte-depleted and non-depleted allogeneic blood and survival following esophagectomy for cancer.MethodsA retrospective analysis was performed including 291 patients with esophageal cancers who underwent transthoracic en bloc esophagectomy and extended mediastinal lymphadenectomy. Neoadjuvant chemoradiation was administered in 152 (52.2%) patients. Perioperative blood transfusions were quantified and the potential prognostic cutoff for transfused units was calculated according to LeBlanc.ResultsThe median number of perioperative blood transfusions was 2 (0–24), and 106 patients (36.4%) received no transfusions. Patients with one or less blood transfusion showed a significantly improved survival compared to patients receiving more than one unit (p < 0.009). In multivariate analysis, blood transfusion categories showed significance (p < 0.015) next to pT, pN, pM category, and residual tumor categories (R-categories). Separate analysis of 183 patients treated after the mandatory introduction of leukocyte-depleted blood transfusions detected a strong tendency, but no significant difference in survival for patients getting one or less or more than one transfusion (p = 0.056). Receipt of leukocyte-depleted versus non-depleted units, however, had no influence on survival (p = 0.766).ConclusionsThe need for perioperative allogeneic blood transfusions is significantly associated with poorer survival following resection for esophageal cancer by univariate and multivariate analysis. Our data suggest that the reduction of leukocytes in allogeneic transfusions is not sufficient to overcome the negative influence on survival.

Single-commodity robust network design problem: Complexity, instances and heuristic solutions

We study a single-commodity Robust Network Design problem (RND) in which an undirected graph with edge costs is given together with a discrete set of balance matrices, representing different supply/demand scenarios. In each scenario, a subset of the nodes is exchanging flow. The goal is to determine the minimum cost installation of capacities on the edges such that the flow exchange is feasible for every scenario. Previously conducted computational investigations on the problem motivated the study of the complexity of some special cases and we present complexity results on them, including hypercubes. In turn, these results lead to the definition of new instances (random graphs with {−1,0,1} balances) that are computationally hard for the natural flow formulation. These instances are then solved by means of a new heuristic algorithm for RND, which consists of three phases. In the first phase the graph representing the network is reduced by heuristically deleting a subset of the arcs, and a feasible solution is built. The second phase consists of a neighborhood search on the reduced graph based on a Mixed-Integer (Linear) Programming (MIP) flow model. Finally, the third phase applies a proximity search approach to further improve the solution, taking into account the original graph. The heuristic is tested on the new instances, and the comparison with the solutions obtained by Cplex on a natural flow formulation shows the effectiveness of the proposed method.

Single-commodity robust network design with finite and Hose demand sets

We study a single-commodity robust network design problem (sRND) defined on an undirected graph. Our goal is to determine minimum cost capacities such that any traffic demand from a given uncertainty set can be satisfied by a feasible single-commodity flow. We consider two ways of representing the uncertainty set, either as a finite list of scenarios or as a polytope. We propose a branch-and-cut algorithm to derive optimal solutions to sRND, built on a capacity-based integer linear programming formulation. It is strengthened with valid inequalities derived as

Solving k-means on High-Dimensional Big Data

\{0,\frac{1}{2}\}

Approximating earliest arrival flows in arbitrary networks

{0,12}-Chvátal–Gomory cuts. Since the formulation contains exponentially many constraints, we provide practical separation algorithms. Extensive computational experiments show that our approach is effective, in comparison to existing approaches from the literature as well as to solving a flow based formulation by a general purpose solver.

Increased Platelet Counts after Transthoracic En Bloc Resection for Esophageal Cancer is Associated with Significantly Improved Survival

We consider a robust network design problem: optimum integral capacities need to be installed in a network such that supplies and demands in each of the explicitly known traffic scenarios can be satisfied by a single-commodity flow. In Buchheim et al. (LNCS 6701, 7---17 (2011)), an integer-programming (IP) formulation of polynomial size was given that uses both flow and capacity variables. We introduce an IP formulation that only uses capacity variables and exponentially many, but polynomial time separable constraints. We discuss the advantages of the latter formulation for branch-and-cut implemenations and evaluate preliminary computational results for the root bounds. We define a class of instances that is difficult for IP-based approaches. Finally, we design and implement a heuristic solution approach based on the exploration of large neighborhoods of carefully selected size and evaluate it on the difficult instances. The results are encouraging, with a good understanding of the trade-off between solution quality and neighborhood size.

MIP Formulations for the Steiner Forest Problem.

In recent years, there have been major efforts to develop data stream algorithms that process inputs in one pass over the data with little memory requirement. For the k-means problem, this has led to the development of several