Center for Personalized Cancer Medicine

Innsbruck, Austria

Center for Personalized Cancer Medicine

Innsbruck, Austria
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Siebert U.,UMIT University for Health Sciences, Medical Informatics and Technology | Siebert U.,Center for Personalized Cancer Medicine | Siebert U.,Center for Health Decision Science | Siebert U.,Harvard University | And 3 more authors.
Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen | Year: 2013

Decision analysis (DA) and value-of-information (VOI) analysis provide a systematic, quantitative methodological framework that explicitly considers the uncertainty surrounding the currently available evidence to guide healthcare decisions. In medical decision making under uncertainty, there are two fundamental questions: 1) What decision should be made now given the best available evidence (and its uncertainty)?; 2) Subsequent to the current decision and given the magnitude of the remaining uncertainty, should we gather further evidence (i.e., perform additional studies), and if yes, which studies should be undertaken (e.g., efficacy, side effects, quality of life, costs), and what sample sizes are needed? Using the currently best available evidence, VoI analysis focuses on the likelihood of making a wrong decision if the new intervention is adopted. The value of performing further studies and gathering additional evidence is based on the extent to which the additional information will reduce this uncertainty. A quantitative framework allows for the valuation of the additional information that is generated by further research, and considers the decision maker's objectives and resource constraints. Claxton et al. summarise: "Value of information analysis can be used to inform a range of policy questions including whether a new technology should be approved based on existing evidence, whether it should be approved but additional research conducted or whether approval should be withheld until the additional evidence becomes available." [Claxton K. Value of information entry in Encyclopaedia of Health Economics, Elsevier, forthcoming 2014.] The purpose of this tutorial is to introduce the framework of systematic VoI analysis to guide further research. In our tutorial article, we explain the theoretical foundations and practical methods of decision analysis and value-of-information analysis. To illustrate, we use a simple case example of a foot ulcer (e.g., with diabetes) as well as key references from the literature, including examples for the use of the decision-analytic VoI framework by health technology assessment agencies to guide further research. These concepts may guide stakeholders involved or interested in how to determine whether or not and, if so, which additional evidence is needed to make decisions.

Dams J.,University of Marburg | Klotsche J.,Leibniz Institute | Bornschein B.,UMIT University for Health Sciences, Medical Informatics and Technology | Reese J.P.,University of Marburg | And 10 more authors.
Health and Quality of Life Outcomes | Year: 2013

Background: Clinical studies employ the Unified Parkinson's Disease Rating Scale (UPDRS) to measure the severity of Parkinson's disease. Evaluations often fail to consider the health-related quality of life (HrQoL) or apply disease-specific instruments. Health-economic studies normally use estimates of utilities to calculate quality-adjusted life years. We aimed to develop an estimation algorithm for EuroQol- 5 dimensions (EQ-5D)-based utilities from the clinical UPDRS or disease-specific HrQoL data in the absence of original utilities estimates.Methods: Linear and fractional polynomial regression analyses were performed with data from a study of Parkinson's disease patients (n=138) to predict the EQ-5D index values from UPDRS and Parkinson's disease questionnaire eight dimensions (PDQ-8) data. German and European weights were used to calculate the EQ-5D index. The models were compared by R2, the root mean square error (RMS), the Bayesian information criterion, and Pregibon's link test. Three independent data sets validated the models.Results: The regression analyses resulted in a single best prediction model (R2: 0.713 and 0.684, RMS: 0.139 and 13.78 for indices with German and European weights, respectively) consisting of UPDRS subscores II, III, IVa-c as predictors. When the PDQ-8 items were utilised as independent variables, the model resulted in an R2 of 0.60 and 0.67. The independent data confirmed the prediction models.Conclusion: The best results were obtained from a model consisting of UPDRS subscores II, III, IVa-c. Although a good model fit was observed, primary EQ-5D data are always preferable. Further validation of the prediction algorithm within large, independent studies is necessary prior to its generalised use. © 2013 Dams et al.; licensee BioMed Central Ltd.

Scheuringer M.,MSD Sharp and Dohme GmbH | Sahakyan N.,Ludwig Maximilians University of Munich | Sahakyan N.,Center for Personalized Cancer Medicine | Sahakyan N.,UMIT University for Health Sciences, Medical Informatics and Technology | And 3 more authors.
Cost Effectiveness and Resource Allocation | Year: 2012

Guidance from the Institute for Quality and Efficiency in Health Care (IQWiG) on cost estimation in cost-benefit assessments in Germany acknowledges the need for standardization of costing methodology. The objective of this review was to assess current methods for deriving clinical event costs in German economic evaluations. A systematic literature search of 24 databases (including MEDLINE, BIOSIS, the Cochrane Library and Embase) identified articles, published between January 2005 and October 2009, which reported cost-effectiveness or cost-utility analyses. Studies assessed German patients and evaluated at least one of 11 predefined clinical events relevant to patients with diabetes mellitus. A total of 21 articles, describing 199 clinical cost events, met the inclusion criteria. Year of costing and time horizon were available for 194 (97%) and 163 (82%) cost events, respectively. Cost components were rarely specified (32 [16%]). Costs were generally based on a single literature source (140 [70%]); where multiple sources were cited (32 [16%]), data synthesis methodology was not reported. Cost ranges for common events, assessed using a Markov model with a cycle length of 12 months, were: acute myocardial infarction (nine studies), first year, 4,618-17,556 €; follow-up years, 1,006-3,647 €; and stroke (10 studies), first year; 10,149-24,936 €; follow-up years, 676-7,337 €. These results demonstrate that costs for individual clinical events vary substantially in German health economic evaluations, and that there is a lack of transparency and consistency in the methods used to derive them. The validity and comparability of economic evaluations would be improved by guidance on standardizing costing methodology for individual clinical events. © 2012 Scheuringer et al.; licensee BioMed Central Ltd.

Geiger-Gritsch S.,UMIT University for Health Sciences, Medical Informatics and Technology | Geiger-Gritsch S.,Ludwig Boltzmann Institute of Health Technology Assessment | Stollenwerk B.,UMIT University for Health Sciences, Medical Informatics and Technology | Stollenwerk B.,Helmholtz Center for Environmental Research | And 8 more authors.
Oncologist | Year: 2010

Objective. We performed a meta-analysis on adverse events seen with bevacizumab to combine the existing evidence about its safety in patients with advanced cancer. Methods. A systematic literature search was conducted to identify published, randomized controlled trials of bevacizumab in cancer patients with data on adverse events available. The primary endpoint was "severe adverse event," a composite of grade 3 and 4 adverse events. Secondary endpoints for the exploratory analysis were individual adverse events. We used random-effects meta-analysis to combine data. Results. Thirteen eligible publications were identified and eight trials reported the primary endpoint. Compared with the control group, the bevacizumab group had a slightly higher risk for any severe adverse event (pooled relative risk, 1.10; 95% confidence interval [95% CI], 1.01-1.19). The pooled risk difference was 7%(95%CI, 1%-13%), withanumber neededtoharm of 14 treated patients. Exploratory analyses showed a statistically significant higher risk for eight of the 15 evaluated secondary endpoints: bevacizumab was associated with a fourfold higher risk for hypertension, epistaxis, and gastrointestinal hemorrhage/perforation; a threefold higher risk for any bleeding events; and a lower, but elevated risk for proteinuria, leukopenia, diarrhea, and asthenia. No statistically significant differences were found for any thrombotic event (arterial or venous), hemoptysis, cardiac event, thrombocytopenia, neutropenia, impaired wound healing, or death related to an adverse event. Conclusion. Treatment with bevacizumab was associated with a slightly higher risk for any severe (grade 3 or 4) adverse event in patients with cancer. The result may impact individual benefit-risk assessments and policy guidelines. ©AlphaMed Press.

Oberaigner W.,Tyrolean State Hospitals Ltd. | Oberaigner W.,University for Information Science and Technology | Oberaigner W.,Center for Personalized Cancer Medicine | Oberaigner W.,TILAK GmbH | And 4 more authors.
European Journal of Public Health | Year: 2011

Background: Gender aspects in medicine are receiving increasing attention, namely also in oncology. For this reason, we decided to investigate whether for solid cancer sites women have better survival outcome than do men in the population of Tyrol, Austria. Methods: We conducted an observational population-based study in Tyrol. All solid cancer sites excluding non-melanoma skin cancer and sex-specific sites were analysed in total and all specific sites with more than 500 patients in the analysis. By the end of 2006, follow-up was ended. We applied a relative excess risk model, thus correcting for differences in life expectancy between women and men. Results: For all cancer sites combined, after adjusting for case mix, women had a relative excess risk of 0.95 (95 CI 0.91-0.99). For the following sites our analysis resulted in a relative excess risk statistically different from 1, namely for women as compared to men: head and neck without larynx 0.72 (95 CI 0.56-0.93), stomach 0.86 (95 CI 0.75-0.97) and lung 0.82 (95 CI 0.75-0.90). Conclusion: In a healthcare system with free access to diagnostics and therapy, after adjusting for staging distribution female cancer patients have a lesser excess mortality risk than do men for lung, stomach and head and neck cancer and also for all cancer sites combined after adjusting for case mix. © 2010 The Author.

PubMed | TARGOS Molecular Pathology GmbH, Protagen, Cornell University, Innsbruck Medical University and Center for Personalized Cancer Medicine
Type: Journal Article | Journal: PloS one | Year: 2016

Chronic inflammation is frequently observed on histological analysis of malignant and non-malignant prostate specimens. It is a suspected supporting factor for prostate diseases and their progression and a main cause of false positive PSA tests in cancer screening. We hypothesized that inflammation induces autoantibodies, which may be useful biomarkers. We aimed to identify and validate prostate inflammation associated serum autoantibodies in prostate cancer patients and evaluate the expression of corresponding autoantigens.Radical prostatectomy specimens of prostate cancer patients (N = 70) were classified into high and low inflammation groups according to the amount of tissue infiltrating lymphocytes. The corresponding pre-surgery blood serum samples were scrutinized for autoantibodies using a low-density protein array. Selected autoantigens were identified in prostate tissue and their expression pattern analyzed by immunohistochemistry and qPCR. The identified autoantibody profile was cross-checked in an independent sample set (N = 63) using the Luminex-bead protein array technology.Protein array screening identified 165 autoantibodies differentially abundant in the serum of high compared to low inflammation patients. The expression pattern of three corresponding antigens were established in benign and cancer tissue by immunohistochemistry and qPCR: SPAST (Spastin), STX18 (Syntaxin 18) and SPOP (speckle-type POZ protein). Of these, SPAST was significantly increased in prostate tissue with high inflammation. All three autoantigens were differentially expressed in primary and/or castration resistant prostate tumors when analyzed in an inflammation-independent tissue microarray. Cross-validation of the inflammation autoantibody profile on an independent sample set using a Luminex-bead protein array, retrieved 51 of the significantly discriminating autoantibodies. Three autoantibodies were significantly upregulated in both screens, MUT, RAB11B and CSRP2 (p>0.05), two, SPOP and ZNF671, close to statistical significance (p = 0.051 and 0.076).We provide evidence of an inflammation-specific autoantibody profile and confirm the expression of corresponding autoantigens in prostate tissue. This supports evaluation of autoantibodies as non-invasive markers for prostate inflammation.

Fischer M.,Innsbruck Medical University | Snajder R.,Innsbruck Medical University | Snajder R.,Center for Personalized Cancer Medicine | Pabinger S.,Innsbruck Medical University | And 6 more authors.
PLoS ONE | Year: 2012

In recent studies, exome sequencing has proven to be a successful screening tool for the identification of candidate genes causing rare genetic diseases. Although underlying targeted sequencing methods are well established, necessary data handling and focused, structured analysis still remain demanding tasks. Here, we present a cloud-enabled autonomous analysis pipeline, which comprises the complete exome analysis workflow. The pipeline combines several in-house developed and published applications to perform the following steps: (a) initial quality control, (b) intelligent data filtering and pre-processing, (c) sequence alignment to a reference genome, (d) SNP and DIP detection, (e) functional annotation of variants using different approaches, and (f) detailed report generation during various stages of the workflow. The pipeline connects the selected analysis steps, exposes all available parameters for customized usage, performs required data handling, and distributes computationally expensive tasks either on a dedicated high-performance computing infrastructure or on the Amazon cloud environment (EC2). The presented application has already been used in several research projects including studies to elucidate the role of rare genetic diseases. The pipeline is continuously tested and is publicly available under the GPL as a VirtualBox or Cloud image at additional supplementary data is provided at © 2012 Fischer et al.

Stoitzner P.,Innsbruck Medical University | Schaffenrath S.,Innsbruck Medical University | Schaffenrath S.,Center for Personalized Cancer Medicine | Tripp C.H.,Innsbruck Medical University | And 9 more authors.
Experimental Dermatology | Year: 2014

Skin dendritic cells (DC) express C-type lectin receptors for the recognition of pathogens. Langerhans cells (LC) express the receptor Langerin/CD207, whereas DEC-205/CD205 is mainly expressed by dermal DC, but can also be detected at low levels on LC. In this study, we tested an ex vivo approach for targeting DC in situ with monoclonal antibodies (mAb) against Langerin and DEC-205. The targeting mAb was injected intradermally into human skin biopsies or added to the medium during skin explant culture. Corresponding to the expression patterns of these lectin receptors on skin DC, Langerin mAb was detected merely in LC in the epidermis and DEC-205 mainly in dermal DC in human skin explants, regardless of the application route. Migratory skin DC bound and carried targeting mAb from skin explants according to their lectin receptor expression profiles. In contrast to the very selective transport of Langerin mAb by LC, DEC-205 mAb was more widely distributed on all CD1a+ skin DC subsets but almost absent in CD14+ dermal DC. As effective vaccination requires the addition of adjuvant, we co-administered the toll-like receptor (TLR)-3 ligand poly I:C with the mAb. This adjuvant enhanced binding of DEC-205 mAb to all skin DC subsets, whereas Langerin targeting efficacy remained unchanged. Our findings demonstrate that LC can be preferentially targeted by Langerin mAb. In contrast, DEC-205 mAb can be bound by all CD1a+ skin DC subsets. The efficacy of DEC-205 mAb targeting strategy can be boosted by addition of poly I:C underlining the potential of this combination for immunotherapeutical interventions. © 2014 John Wiley & Sons A/S.

Dubrac S.,Innsbruck Medical University | Elentner A.,Innsbruck Medical University | Ebner S.,Innsbruck Medical University | Ebner S.,Center for Personalized Cancer Medicine | And 2 more authors.
Journal of Immunology | Year: 2010

The pregnane X receptor (PXR) is a ligand-activated transcription factor regulating genes central to drug and hormone metabolism in the liver. Previous reports indicated that PXR is expressed in PBMC, but the role of PXR in immune cells remains unknown. In this paper, we report increased PXR expression in mouse and human T lymphocytes upon immune activation. Furthermore, pharmacologic activation of PXR inhibits T lymphocyte proliferation and anergizes T lymphocytes by decreasing the expression of CD25 and IFN-γ and decreasing phosphorylated NF-κB and MEK1/2. Although these effects are preceded by an increase of suppressor of cytokine signaling 1, a master switch for IFN-γ expression, in a PXR-dependent manner, T-bet expression remains unchanged. Conversely, PXR-deficient mice exhibit an exaggerated T lymphocyte proliferation and increased CD25 expression. Furthermore, PXR-deficient lymphocytes produce more IFN-γ and less of the anti-inflammatory cytokine IL-10. In summary, these results reveal a novel immune-regulatory role of PXR in T lymphocytes and identify suppressor of cytokine signaling 1 as an early signal in PXR-mediated T lymphocyte suppression. Copyright © 2010 by The American Association of Immunologists, Inc.

PubMed | Center for Personalized Cancer Medicine
Type: Journal Article | Journal: Applied health economics and health policy | Year: 2014

Several tyrosine kinase inhibitors (TKIs) are approved for the treatment of chronic myeloid leukemia (CML). Decision-analytic modeling can help to extrapolate data from short-term clinical trials and also consider quality of life when evaluating different treatment strategies.Our goal was to describe and analyze the structural and methodological approaches of published decision-analytic models for various treatment strategies in CML and to derive recommendations for the development of future CML models.We performed a systematic literature search in electronic databases (MEDLINE/PreMEDLINE, EconLit, EMBASE, NHS EED, and Tufts CEA Registry) to identify published studies evaluating CML treatment strategies using mathematical models. The search was updated in August 2013.The models were required to compare different treatment strategies in relation to relevant clinical and patient-relevant health outcomes [e.g., life-years gained, quality-adjusted life-years] over a defined time horizon and population.We used standardized forms for data extraction, description of study design, methodological framework, and data sources for each model.We identified 18 different decision-analytic modeling studies. Of these, 17 included economic evaluations. Modeling approaches included decision trees, Markov cohort models, state-transition models with individual (Monte Carlo) simulations, and mathematical equations. Analytic time horizons ranged from 2 years to a lifetime. Treatment strategies compared included bone marrow or stem cell transplantation, conventional chemotherapy, interferon-, and TKIs. Only one model evaluated a second-generation TKI. Most models did not report a model validation. All models conducted deterministic sensitivity analyses and four reported a probabilistic sensitivity analysis.Articles that were not published in English or German were not included in this review. Our literature search was restricted to published full-text articles in certain databases. Therefore, publications that met our inclusion criteria but were published in different databases, different languages, or as abstracts only may have been missed.While several well-designed models of CML treatment strategies exist, there remains a need for the assessment of the long-term efficacy and cost effectiveness of novel treatment options such as second-generation TKIs. Additionally, these models should be validated using independent data.

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