Block-Coordinate Frank-Wolfe Optimization for Structural SVMs

We propose a randomized block-coordinate variant of the classic Frank-Wolfe algorithm for convex optimization with block-separable constraints. Despite its lower iteration cost, we show that it achieves a similar convergence rate in duality gap as the full Frank-Wolfe algorithm. We also show that, when applied to the dual structural support vector machine (SVM) objective, this yields an online algorithm that has the same low iteration complexity as primal stochastic subgradient methods. However, unlike stochastic subgradient methods, the block-coordinate Frank-Wolfe algorithm allows us to compute the optimal step-size and yields a computable duality gap guarantee. Our experiments indicate that this simple algorithm outperforms competing structural SVM solvers.Comment: Appears in Proceedings of the 30th International Conference on Machine Learning (ICML 2013). 9 pages main text + 22 pages appendix. Changes from v3 to v4: 1) Re-organized appendix; improved & clarified duality gap proofs; re-drew all plots; 2) Changed convention for Cf definition; 3) Added weighted averaging experiments + convergence results; 4) Clarified main text and relationship with appendi

Inpatient hospital costs of febrile neutropenia as a consequence of chemotherapy for breast cancer and non-Hodgkin lymphoma in Switzerland

Febrile neutropenia (FN) can be a serious complication of chemotherapy (CHT), increasing mortality risk and healthcare costs. Incidence and inpatient hospital costs of FN in Switzerland are currently not reported. The study aimed to: 1. Estimate the number of CHT induced FN-related hospitalizations. 2. Assess inpatient hospital costs per FN event in Switzerland

Cost-effectiveness of dabigatran for stroke prevention in atrial fibrillation in Switzerland

Objectives: Atrial fibrillation is a major risk factor for ischemic stroke and anticoagulation therapy is indicated to reduce risk. Dabigatran is a new oral anticoagulant that does not require INR monitoring. This study evaluated the cost-effectiveness of dabigatran versus vitamin K antagonists for stroke prevention in atrial fibrillation in Switzerland. Methods: A Markov model simulating the course of treatment and occurrence of clinical events in two treatment arms over the lifetime of patients was adapted to the Swiss context. The adaptation included the cost of anticoagulation therapy and clinical events in Switzerland. The cost of inpatient care was estimated on data of all inpatient hospital stays in 2008. The calculation of outpatient care costs was based on peer reviewed studies, expert interviews and local tariffs. Results: Patients treated with dabigatran had a higher life expectancy and experienced more quality adjusted life years (QALY) while incurring higher costs than patients treated with vitamin K antagonists. The estimated incremental cost-effectiveness ratio (ICER) was CHF 25,108.‒ per QALY with 110 mg and CHF 9,702 per QALY with 150 mg of dabigatran. A sequential dosage scheme, in which 150 mg are administered up to the age of 80 years and 110 mg thereafter, resulted in an ICER of CHF 10,215 per QALY. A sensitivity analysis confirmed that these results are robust. Conclusions: Dabigatran can be considered cost-effective in comparison with vitamin K antagonists in the Swiss context. The higher drug cost of dabigatran is compensated by savings in INR monitoring, lower cost of clinical events and QALY-gains

Mass spectrometry of human leukocyte antigen class I peptidomes reveals strong effects of protein abundance and turnover on antigen presentation.

HLA class I molecules reflect the health state of cells to cytotoxic T cells by presenting a repertoire of endogenously derived peptides. However, the extent to which the proteome shapes the peptidome is still largely unknown. Here we present a high-throughput mass-spectrometry-based workflow that allows stringent and accurate identification of thousands of such peptides and direct determination of binding motifs. Applying the workflow to seven cancer cell lines and primary cells, yielded more than 22,000 unique HLA peptides across different allelic binding specificities. By computing a score representing the HLA-I sampling density, we show a strong link between protein abundance and HLA-presentation (p < 0.0001). When analyzing overpresented proteins - those with at least fivefold higher density score than expected for their abundance - we noticed that they are degraded almost 3 h faster than similar but nonpresented proteins (top 20% abundance class; median half-life 20.8h versus 23.6h, p < 0.0001). This validates protein degradation as an important factor for HLA presentation. Ribosomal, mitochondrial respiratory chain, and nucleosomal proteins are particularly well presented. Taking a set of proteins associated with cancer, we compared the predicted immunogenicity of previously validated T-cell epitopes with other peptides from these proteins in our data set. The validated epitopes indeed tend to have higher immunogenic scores than the other detected HLA peptides. Remarkably, we identified five mutated peptides from a human colon cancer cell line, which have very recently been predicted to be HLA-I binders. Altogether, we demonstrate the usefulness of combining MS-analysis with immunogenesis prediction for identifying, ranking, and selecting peptides for therapeutic use

Dictionary construction and identification of possible adverse drug events in Danish clinical narrative text

OBJECTIVE: Drugs have tremendous potential to cure and relieve disease, but the risk of unintended effects is always present. Healthcare providers increasingly record data in electronic patient records (EPRs), in which we aim to identify possible adverse events (AEs) and, specifically, possible adverse drug events (ADEs). MATERIALS AND METHODS: Based on the undesirable effects section from the summary of product characteristics (SPC) of 7446 drugs, we have built a Danish ADE dictionary. Starting from this dictionary we have developed a pipeline for identifying possible ADEs in unstructured clinical narrative text. We use a named entity recognition (NER) tagger to identify dictionary matches in the text and post-coordination rules to construct ADE compound terms. Finally, we apply post-processing rules and filters to handle, for example, negations and sentences about subjects other than the patient. Moreover, this method allows synonyms to be identified and anatomical location descriptions can be merged to allow appropriate grouping of effects in the same location. RESULTS: The method identified 1 970 731 (35 477 unique) possible ADEs in a large corpus of 6011 psychiatric hospital patient records. Validation was performed through manual inspection of possible ADEs, resulting in precision of 89% and recall of 75%. DISCUSSION: The presented dictionary-building method could be used to construct other ADE dictionaries. The complication of compound words in Germanic languages was addressed. Additionally, the synonym and anatomical location collapse improve the method. CONCLUSIONS: The developed dictionary and method can be used to identify possible ADEs in Danish clinical narratives