Additional offer of sigmoidoscopy in colorectal cancer screening in Germany: rationale and protocol of the decision-analytic modelling approach in the SIGMO study

IntroductionIn Germany, statutory insured persons are entitled to a stool test (faecal immunochemical test (FIT)) or colonoscopy for colorectal cancer (CRC) screening, depending on age and sex, yet participation rates are rather low. Sigmoidoscopy is a currently not available screening measure that has a strong evidence base for incidence and mortality reduction. Due to its distinct characteristics, it might be preferred by some, who now reject colonoscopy. The objective of this study is to estimate the economic consequences of the additional offer of sigmoidoscopy for CRC screening in Germany compared with the present screening practice while considering the preferences of the general population.Methods and analysisA decision-analytic modelling approach will be developed that compares the present CRC screening programme in Germany (FIT, colonoscopy) with a programme extended by sigmoidoscopy from a societal perspective. A decision tree and Markov model will be combined to assess both short-term and long-term effects, such as CRC and adenoma detection rates, the number of CRC cases, CRC mortality as well as complications. The incremental cost per quality-adjusted life year gained for each alternative will be calculated. The model will incorporate the general population’s preferences based on a discrete choice experiment. Further, input parameters will be taken from the literature, the German cancer registry and health insurance claims data.Ethics and disseminationEthical approval for the study was obtained from the Ethics Committee of Hannover Medical School (ID: 8671_BO_K_2019). The findings of the study will be published in peer-reviewed journals and presented at national and/or international conferences.Trial registration numberDRKS00019010.

Quality of health economic evaluations submitted to the Italian Medicines Agency: current state and future actions

ObjectivesThe purpose of this study was to evaluate the current state of health economic evaluations (HEEs) submitted by pharmaceutical companies to the Italian Medicines Agency (AIFA) as part of their pricing and reimbursement (P&R) dossiers, and to explore potential future actions in order to enhance their quality.MethodsAll company dossiers submitted from October 2016 to December 2018 were reviewed to select those containing pharmacoeconomic studies. The general characteristics of HEEs were described and their quality assessed based on a checklist adapted from Philips et al. (Review of guidelines for good practice in decision-analytic modelling in health technology assessment. Health Technol Assess. 2004;8: 1–158).ResultsOf the 299 dossiers submitted to AIFA, 105 included one or more pharmacoeconomic studies, of which fifty-three were cost-effectiveness analyses. Overall, the compliance of the HEEs with the quality checklist was highly variable: some studies reached high methodological standards whereas others had serious flaws (mean 59.22 percent, range 19.35–90.32 percent). The main weaknesses were the unjustified exclusion of relevant alternatives, poor description and justification of model data and assumptions, and insufficient exploration of uncertainty and study validity. Non-homogeneity across studies was found in study perspectives, discount rates, methods for costing, estimating quality-adjusted life-years and conducting sensitivity analyses.ConclusionsBased on the results of this study, the recommended actions for increasing the quality of HEEs within reimbursement submissions in Italy are twofold: first, to set methodological standards for conducting and reporting HEEs; second, to strengthen the internal assessment process, also through the acquisition of companies' models and re-evaluation of results. These actions will hopefully provide greater contribution to the evidence-based P&R decision making.

Evaluating Quality Adjusted Life Years in the Absence of Standard Utility Values- A Dynamic Joint Modelling Approach

Estimation of Quality Adjusted Life Years (QALYs) is pivotal towards cost-effectiveness analysis (CEA) of medical interventions. Most of the CEA studies employ multi-state decision analytic modelling approach, where fixed utility values are assigned to each disease state and total QALYs are calculated on the basis of total lengths of stay in each state.In this paper, we have formulated a new approach to CEA by defining utility as a function of a longitudinal covariate which is significantly associated with disease progression. Association parameter between the longitudinal covariate and survival times is estimated through joint modelling of the longitudinal linear mixed effects model and the Weibull accelerated failure time survival model. Metropolis-Hastings algorithm and Monte Carlo integration are used to predict expected survival times of each censored case using the joint model. Fitted longitudinal model is further used to project values of the longitudinal covariate at all time points for each patient. Utility values calculated using these projected covariate values are used to evaluate QALYs for each patient.Retrospective survival data of HIV/ AIDS patients undergoing treatment at the Antiretroviral Therapy centre of Ram Manohar Lohia hospital in New Delhi is used to demonstrate the implementation of the proposed methodology. A simulation exercise is also carried out to gauge the predictive capability of the joint model in projecting the values of the longitudinal covariate.The proposed dynamic approach to calculate QALY provides a promising alternative to the popular multi-state decision analytic modelling approach, especially when the standard utility values for different stages of the concerned disease are not available.