Multi-criteria Decision Analysis to Support Clinical Decision Making in Oncology: A Literature Review

Clinical decision-making for patients with cancer is often complex as many treatment combinations and sequences (e.g., surgery, chemotherapy, radiotherapy) can be considered, taking into account many clinical inputs. Multicriteria Group Decision-processes are usually considered to facilitate and improve this complex decision process for each cancer patient. Even though the literature includes several reviews on MCDA methods, reviews limited to the applications of MCDA specifically in clinical decision–making for oncology are not popular. In this work, we conduct a literature review with the objective to describe characteristic aspects and approaches, as well as the specifics of the various MCDA methods used in clinical decisions and structure. To this end, we focused on papers related to the use of MCDA methods while selecting the best treatment or diagnosis plan in oncology. Our initial literature search yielded 430 abstracts, 15 of which met the inclusion requirements and were taken into consideration for additional investigation. The majority of clinical decision-making (treatment, diagnostic) issues are solved using Value-Based Strategies. In fact AHP and ANP are the most used MCDA techniques, followed by Fuzzy PROMETHEE, EVIDEM, and TOPSIS. It’s interesting to note that practically reviewed paper adopted direct weighting, although the most popular methods for scoring and weighting are scales and AHP. Our findings can serve as a reference to develop strategies and frameworks that use MCDA to deal with clinical decision-making issues such as selecting the most efficient therapy strategy or method of diagnosis for a particular cancer patient