Modelling the benefits of early diagnosis of pancreatic cancer using a biomarker signature.

Ola Ghatnekar, Roland Andersson, Marianne Greiff Svensson, Ulf Persson, Ulrika Ringdahl, Paula Zeilon, Carl Borrebaeck

Research output: Contribution to journalArticlepeer-review

33 Citations (SciVal)

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.
Original languageEnglish
Pages (from-to)2392-2397
JournalInternational Journal of Cancer
Volume133
Issue number10
DOIs
Publication statusPublished - 2013

Subject classification (UKÄ)

  • Cancer and Oncology

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