Peer-Reviewed Publication
Cancers (Basel)2026;18(13)June 25, 2026Journal Article

Economic Evidence on Biliary Tract Cancer: A Systematic Review.

João Rocha-Gomes1,2, Ana Sofia Teixeira3, Marina Ruiz-Romeo4,5,6, José Manuel Oliveira7,8, Patrícia Ramos7,9
1RISE-Health, Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal.
2Ada Health GmbH, 10179 Berlin, Germany.
3Department of Informatics Engineering, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal.
4Department of Clinical Psychology and Psychobiology, Universitat de Barcelona, 08035 Barcelona, Spain.
5ICOnnecta't Digital Health Program, Catalan Institute of Oncology, Hospitalet de Llobregat, 08908 Barcelona, Spain.
6Psychooncology and Digital Health Group, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908 Barcelona, Spain.
7Institute for Systems and Computer Engineering, Technology and Science, 4200-465 Porto, Portugal.
8Faculty of Economics, University of Porto, 4200-464 Porto, Portugal.
9CEOS.PP, ISCAP, Polytechnic of Porto, 4465-004 São Mamede de Infesta, Portugal.

Abstract

Background: Biliary tract cancers (BTCs), encompassing cholangiocarcinoma and gallbladder carcinoma, are aggressive malignancies with poor prognosis and increasing incidence in selected regions worldwide. Advances in imaging, biomarker profiling, immunotherapy, and targeted therapies have improved treatment options but have also increased the economic pressure on health systems. Understanding the…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.