Using informative prior based on expert opinion in Bayesian estimation of the transition probability matrix in Markov modelling-an example from the cost-effectiveness analysis of the treatment of patients with predominantly negative symptoms of schizophrenia with cariprazine.

BACKGROUND: When patient health state transition evidence is missing from clinical literature, analysts are inclined to make simple assumptions to complete the transition matrices within a health economic model. Our aim was to provide a solution for estimating transition matrices by the Bayesian statistical method within a health economic model when empirical evidence is lacking. METHODS: We used a previously published cost-effectiveness analysis of the use of cariprazine compared to that of risperidone in patients with predominantly negative symptoms of schizophrenia. We generated the treatment-specific state transition probability matrices in three different ways: (1) based only on the observed clinical trial data; (2) based on Bayesian estimation where prior transition probabilities came from experts' opinions; and (3) based on Bayesian estimation with vague prior transition probabilities (i.e., assigning equal prior probabilities to the missing transitions from one state to the others). For the second approach, we elicited Dirichlet prior distributions by three clinical experts. We compared the transition probability matrices and the incremental quality-adjusted life years (QALYs) across the three approaches. RESULTS: The estimates of the prior transition probabilities from the experts were feasible to obtain and showed considerable consistency with the clinical trial data. As expected, the estimated health benefit of the treatments was different when only the clinical trial data were considered (QALY difference 0.0260), its combination with the experts' beliefs were used in the economic model (QALY difference 0.0253), and when vague prior distributions were used (QALY difference 0.0243). CONCLUSIONS: Imputing zeros to missing transition probabilities in Markov models might be untenable from the clinical perspective and may result in inappropriate estimates. Bayesian statistics provides an appropriate framework for imputing missing values without making overly simple assumptions. Informative priors based on expert opinions might be more appropriate than vague priors.

[Model concept of the health economic evaluation of low-dose CT lung cancer screening in Hungary]. / Az alacsony dózisú CT-vel végzett tüdorákszurés magyarországi egészség-gazdaságtani elemzésének koncepcionális terve.

INTRODUCTION: Lung cancer is a rapidly progressing, often life-threatening disease that constitutes a huge societal burden. Because of the scarce resources of the Hungarian health care system, the cost-effectiveness of introducing low-dose computed tomography screening is a relevant health policy matter. AIM: The aim of this study is to design a model concept for assessing the cost-effectiveness of low-dose computed tomography lung cancer screening in Hungary, and to define the required steps for performing the analysis. METHOD: A targeted literature review was conducted to identify and synthesize the evidence on efficacy and effectiveness of screening, and results were evaluated based on adaptability to Hungarian settings. We also summarized the available Hungarian scientific evidence and reconstructed the potential patient pathways. RESULTS: In accordance with these findings, we recommend to perform the full health-economic evaluation of low-dose computed tomography lung cancer screening using a complex model structure that consists of several sub-models and is capable to follow the population at risk on life-time horizon. CONCLUSIONS: The proposed cost-effectiveness model will be suitable to provide data for further analyses that support decision-making on introducing low-dose computed tomography lung cancer screening as public health program. Orv Hetil. 2017; 158(25): 963-975.

[Dental fear and anxiety scores of a Hungarian population living in the Hungarian-Slovakian border region. A pilot study]. / Adatok a magyar-szlovák határ mentén élo magyar populáció fogászati félelem- és szorongás-értékeirol. Tájékozódó vizsgálat.

The aim of the authors was to investigate whether living as a minority has an influence on the dental fear and anxiety values. In this study 201 volunteers (n = 201, inside border Hungarians 144, outside border Hungarians 57, male 90, female 111; age 8 to 83 years, mean 44 +/- 16 yrs.) were investigated. Our methods included collection of demographic data (gender, age, marital status, profession), and administration of the Hungarian versions of dental fear and anxiety related scales namely: DAS, DAQ, DASQ, DFS, DBS, STAI-S, STAI-T and Expectation Scale. Mean values of the scales were: DAS: 10,34 +/- 3,54; DAQ: 2,3 +/- 1,15; DASQ: 12,58 +/- 4,55; DFS: 40,37 +/- 15,67; DBS: 32,89 +/- 12,94; Expectation Scale: 2,87 +/- 3,56, STAI-S: 39,51 +/- 10,68; STAI-T 41,65 +/- 9,08. The mean scores of all the scales were higher in the case of Hungarians living inside the borders of Hungary. The differences were significant in the case of DAS, DAQ, DASQ and DFS scales (p < 0,05). Data of our study indicate that living as a minority not necessarily leads to the increase of dental fear and anxiety.

Comparison of weighting methods used in multicriteria decision analysis frameworks in healthcare with focus on low- and middle-income countries.

AIM: Criteria weighting is a key element of multicriteria decision analysis that is becoming extensively used in healthcare decision-making. In our narrative review we describe the advantages and disadvantages of various weighting methods. METHODS: An assessment of the eight identified primary criteria weighting methods was compiled on domains including their resource requirements, and potential for bias. RESULTS: In general, we found more complex methods to have less potential for bias; however, resource intensity and general participant burden is greater for these methods. CONCLUSION: The selection of the most appropriate method depends on the decision-making context. The simple multiattribute rating technique (SMART) method combined with swing-weighting technique and the analytic hierarchy process methods may be the most feasible approaches for low- and middle-income countries.

A systematic review of health economic models and utility estimation methods in schizophrenia.

INTRODUCTION: There is a growing need for economic evaluations describing the disease course, as well as the costs and clinical outcomes related to the treatment of schizophrenia. AREAS COVERED: A systematic review on studies describing health economic models in schizophrenia and a targeted literature review on utility mapping algorithms in schizophrenia were carried out. Models found in the review were collated and assessed in detail according to their type and various other attributes. Fifty-nine studies were included in the review. Modeling techniques varied from simple decision trees to complex simulation models. The models used various clinical endpoints as value drivers, 47% of the models used quality-adjusted life years, and eight percent used disability-adjusted life years to measure benefits, while others applied various clinical outcomes. Most models considered patients switching between therapies, and therapeutic adherence, compliance or persistence. The targeted literature review identified four main approaches to map PANSS scores to utility values. EXPERT COMMENTARY: Health economic models developed for schizophrenia showed great variability, with simulation models becoming more frequently used in the last decade. Using PANSS scores as the basis of utility estimations is justifiable.

Quality-adjusted life year difference in patients with predominant negative symptoms of schizophrenia treated with cariprazine and risperidone.

AIM: Our study aimed at estimating differences in quality-adjusted life year (QALY) gain for patients with predominant negative symptoms of schizophrenia treated with cariprazine compared with risperidone. MATERIALS & METHODS: A Markov model was built, based on the Mohr-Lenert approach and data derived from clinical trials, to estimate potential QALY gains of patients. RESULTS: Patients had higher probability of reaching better health states treated with cariprazine compared with risperidone. In the model, this resulted in an estimated QALY gain of 0.029 per patient, after 1 year of treatment. CONCLUSION: Cariprazine, which showed clinically meaningful improvement in the symptoms, and personal and social performance, can also provide significant QALY gain in the treatment of patients with predominant negative symptoms of schizophrenia compared with risperidone.