OBJECTIVES: This systematic review was carried out to identify Multiple Criteria Decision Analysis (MCDA) modeling approaches and methods for health care decision in oncology considering regulatory, reimbursement and coverage decisions.

METHODS: We searched MEDLINE via PubMed, EMBASE, LILACS, Web of Science Web of Science and CRD's NHS EED (from inception to Nov 2018) for studies that used MCDA to support health care decisions in cancer care. We placed no language restriction on our search. Two reviewers independently assessed eligibility and extracted data from the included studies.

RESULTS: We included 11 studies involving MCDA in cancer care. The studies compared a variety of health technologies to different cancer types. Six studies were related to health technology assessment, 4 to priority setting frameworks and 1 to benefit-risk assessment. The most used MCDA modeling approach was value measurement models, applied in 10 studies. The scoring and weighting techniques used in these studies were direct rating in 5 studies, pairwise and swing weighting in 3 studies, discrete choice experiments in 1 study, and scoring function in 1 study. One study used the goals, aspiration or reference-levels model and the pairwise-ranking technique was used to scoring and weighting. Most of the studies used Linear aggregation or linear additive model as aggregation function (6 and 2 studies, respectively).

CONCLUSIONS: MCDA can be useful for health care decision making, however, this is a relatively new tool and further understanding about modeling approaches and methods used is needed. This review may help on designing future MCDA studies highlighting important issues in oncology.