BACKGROUND: The spectrum of cancer treatment is very wide and increases every year. There is not enough certainty in oncology about decision-making process and factors that may be associated with observed variation in cancer treatment and patient outcomes. Nonetheless, there exist a logical, structured, and transparent approach that can increase transparency of the decision-making process and is referred to as multicriteria decision analysis (MCDA). OBJECTIVES:  to identify application experience of MCDA in the context of oncology by reviewing published literature. METHODS:  The search was conducted in PubMed and the Cochrane Library in January 2016. Studies of any design that used MCDA within the context of oncology published in English were considered. Databases were searched using the free text terms: ‘multi-criteria decision analysis’, ‘multicriteria decision analysis’, ‘multiple criteria decision aiding’, ‘multi-criteria decision making’, ‘multicriteria analysis’. The above free text terms were combined with ‘oncology’ and ‘cancer’ using Boolean operators when necessary. RESULTS:  Fourteen publications were included. Eight studies focused on decision-making in regard to cancer diagnosis. Four of them have demonstrated the applicability of the Analytic Hierarchy Process (AHP) method in the field of patient decision-making. In three studies MCDA was implemented in the clinical decision support systems. Other three studies applied MCDA in quantitative benefit–risk assessment of the quadrivalent HPV vaccine; to develop a decision support tool in order to assist pharmacists choosing the anticancer drugs that can be produced in advance; and to develop a rating tool for policy makers to prioritize breast cancer interventions in low- and middle- income countries. CONCLUSIONS:  Possibility of carrying out of such an analysis as the AHP by one person, represents significant opportunities for its development in patient decision-making process in regard to cancer diagnosis. MCDA is not routinely used in oncology and most studies focus on the clinicians and patients side instead policymakers.