Roland Andersson

Lund University, Lund, Skåne, Sweden

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Publications (3)17.37 Total impact

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    ABSTRACT: Pancreatic cancer (PC) has a poor prognosis, with a 5-year survival of 3-4%. This is mainly due to late diagnosis because of diffuse symptoms, where 80-85% of the patients are inoperable. Consequently, early diagnosis would be of significant benefit, resulting in a potential 5-year survival of 30-40%. However, new technologies must be carefully evaluated concerning effectiveness and healthcare costs. We have developed a framework for modelling cost and health effects from early detection of PC, which for the first time allowed us to analyse its cost-effectiveness. A probabilistic cohort model for estimating costs and quality adjusted life-years (QALY) arising from screening for PC, compared to a "wait-and-see"-approach, was designed. The test accuracy, Swedish survival and costs by tumour stage, expected life gain from early detection and pre-test probabilities in risk-groups, were retrieved from previous investigations. In a cohort of newly diagnosed diabetic patient (incidence 0.71%) the incremental cost per QALY gained (ICER) was €13,500, which is considered cost-effective in Europe. Results were mainly sensitive to the incidence with the ICER ranging from €315 to €204,000 (familial PC 35% and general population 0.046%, respectively). This is the first study focusing on clinical implementation of advanced testing and what is required for novel technologies in cancer care to be cost-effective. The model clearly demonstrated the potential of multiplexed proteomic-testing of PC and also identified the requirements for test accuracy. Consequently, it can serve as a model for assessing the possibilities to introduce advanced test platforms also for other cancer indications. © 2013 Wiley Periodicals, Inc.
    No preview · Article · Nov 2013 · International Journal of Cancer
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    ABSTRACT: Pancreatitis is an inflammatory state of the pancreas, for which high-performing serological biomarkers are lacking. The aim of the present study was to evaluate the use of affinity proteomics for identifying potential markers of disease and stratifying pancreatitis subtypes. High-content, recombinant antibody microarrays were applied for serum protein expression profiling of 113 serum samples from patients with chronic, acute, and autoimmune pancreatitis, as well as healthy controls. The sample groups were compared using supervised classification based on support vector machine analysis. This discovery study showed that pancreatitis subtypes could be discriminated with high accuracy. Using unfiltered data, the individual subtypes, as well as the combined pancreatitis cohort, were distinguished from healthy controls with high AUC values (0.96–1.00). Moreover, characteristic protein patterns and AUC values in the range of 0.69–0.95 were observed for the individual pancreatitis entities when compared to each other, and to all other samples combined. This study demonstrated the potential of the antibody microarray approach for stratification of pancreatitis. Distinct candidate multiplex serum biomarker signatures for chronic, acute, and autoimmune pancreatitis were defined, which could enhance our fundamental knowledge of the underlying molecular mechanisms, and potentially lead to improved diagnosis.
    No preview · Article · Oct 2012 · PROTEOMICS - CLINICAL APPLICATIONS
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    ABSTRACT: Pancreatic cancer is an aggressive disease with poor prognosis, due, in part, to the lack of disease-specific biomarkers that could afford early and accurate diagnosis. With a recombinant antibody microarray platform, targeting mainly immunoregulatory proteins, we screened sera from 148 patients with pancreatic cancer, chronic pancreatitis, autoimmune pancreatitis (AIP), and healthy controls (N). Serum biomarker signatures were derived from training cohorts and the predictive power was evaluated using independent test cohorts. The results identified serum portraits distinguishing pancreatic cancer from N [receiver operating characteristics area under the curve (AUC) of 0.95], chronic pancreatitis (0.86), and AIP (0.99). Importantly, a 25-serum biomarker signature discriminating pancreatic cancer from the combined group of N, chronic pancreatitis, and AIP was determined. This signature exhibited a high diagnostic potential (AUC of 0.88). In summary, we present the first prevalidated, multiplexed serum biomarker signature for diagnosis of pancreatic cancer that may improve diagnosis and prevention in premalignant diseases and in screening of high-risk individuals.
    No preview · Article · May 2012 · Cancer Research