Hindawi Publishing Corporation Computational and Mathematical Methods in Medicine Volume 2012, Article ID 103919, 6 pages doi:10.1155/2012/103919 Research Article Multicriteria Optimization Model for the Study of the Efficacy of Skin Antiaging Therapy Maria Cris ¸an, 1 Guido Cappare, 2 Luciana Neamt ¸iu, 3 Ioana Chiorean, 4 Liana Lups ¸a, 4 Diana Cris ¸an, 5 and Radu Badea 6 1 Department of Histology, Iuliu Hat ¸ieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania 2 Department of Aestetics, AMIA, Milano, Italy 3 Ion Chiricut ¸˘ a Cancer Institute, Cluj-Napoca, Romania 4 Faculty of Mathematics and Computer Science, Babes ¸-Bolyai University, Cluj-Napoca, Romania 5 Iuliu Hat ¸ieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania 6 Department of Ultrasonography, Iuliu Hat ¸ieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania Correspondence should be addressed to Maria Cris ¸an, mcrisan7@yahoo.com Received 29 September 2011; Accepted 12 December 2011 Academic Editor: Carlo Cattani Copyright © 2012 Maria Cris ¸an et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The evolution of the cutaneous structure after topical treatment with P63 antiaging complex, assessed with high frequency ultrasound, is studied by means of multicriteria optimization model. Due to the fact that the impact of the treatment may influence the quality of life, a medical index which measures, from this point of view, the efficacy of the treatment is given, also taking into account medical and economical aspects. 1. Introduction The basic idea of Pharmaco-Economics studies is to gain a physical and psychical comfort state for as long as possible, with the smallest amount of money. Therefore, according to these studies (see [1]) which consider a treatment in terms of results related to costs, one of the following five types of analysis is used: and cost-effects (CEA), cost-minimization (CMA), cost-utility (CUA), cost-efficiency (CEAC), and cost-benefit (CBA). Then, the data obtained after each of this analysis are used to compare two or more treatments. Cost-utility analysis was developed to help decision makers compare the value of alternative interventions that have very different health benefits, and it facilitates these com- parisons without recourse to placing monetary values on different health states. The primary outcome of a cost-utility analysis is the cost per quality-adjusted life years (QALYs) or incremental cost-effectiveness ratio (ICER), which is calculated as the difference in the expected cost of two interventions, divided by the difference in the expected QALYs produced by the two interventions. QALYs measure health as a combination of the duration of life and the health- related quality of life. Also, there is another index, denoted by NB or INB, which means incremental net benefit, defined by INB = λΔ e − Δ c , (1) where λ is the willingness to pay. These indexes are largely used in the literature (see, e.g., [2–5]). Unfortunately, they may not always reflect with suffi- cient accuracy all aspects of medical outcomes of treatment, perception and impact of treatment on the patient’s psyche, economic effects, and so forth. Using the multicriteria optimization technique, in [6] a new index, called medicoeconomic index of a treatment (denoted by MEI), is introduced. Its construction may use all the desired aspects. It permits a simultaneous comparison of two or more medical treatments. And, in addition, due to the fact that it emphasizes the importance of every aspect in a general context, it gains an increased flexibility (see [7–10]). There are papers in the literature which use multifactorial decisions to compare the medical treatments (see the book [11] and the studies [12, 13]).