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Analyse comparative coût et efficacité des traitements du cancer du rein métastatique : analyse à partir des données de vie réelleet des données d’essais

Abstract : Targeted therapies have improved the survival of patients suffering from cancer. However, due to the introduction of new targeted therapies, treatment costs have rapidly increased. In this context, Economic Evaluation (EE) proposes a set of tools in healthcare decision making. EE is usually based on decision modeling that requires a set of clinical, economical and quality of life data. These data are often collected in randomized controlled clinical trials also called Direct Comparisons (DC), in the literature and on the basis of experts’ opinions. Yet, it is not always possible to conduct a clinical trial that directly compares treatment A to treatment B. Therefore, the use in EE of statistical techniques that uses results from separate clinical trials to compare the efficacy between treatment A and B is increasing. One of these techniques is called Indirect Comparisons (IC). Differences in patients’ characteristics between the population in the trial and the one treated in practice, makes it difficult to extrapolate the results of clinical trials to the population treated in real life. Moreover, analytic decision models are often sensitive to clinical, quality of life and costing parameters. Hence, real life cost-effectiveness may differ from the cost-effectiveness based on clinical trials data. In addition, the use of indirect comparisons in decision analytic modeling may yield different results from the use of data collected in head to head trials. The objective of this thesis was to evaluate the impact of using different data sources (DC, IC and real life data) on the results of a decision analytic model. To attain our objectives, the effectiveness of pazopanib versus sunitinib in first line treatment of patients with metastatic Renal Cell Carcinoma (mRCC) was used as a case study. To evaluate the impact of different data sources on the cost-effectiveness results, we used a partioned survival model and compared the results of three different scenarios: direct comparison, indirect comparison and real life. In order to derive the parameters used in the model, we conducted three retrospective database analyses. For DC and IC scenarios, cost data were collected using multiple data sources (PMSI, Oncology Analyzer and the literature) and clinical data were collected respectively in a clinical trial and from an indirect comparison comparing pazopanib to sunitinib. Costs and survival data used in the real life scenario were collected in the DCIR. Similar utility values were used for the three scenarios. In the DC scenario, pazopanib was found to be more effective and less costly than sunitinib. However, for both IC and real life scenarios, pazopanib was found to be more effective and costlier than sunitinib. Even though both scenarios found pazopanib more effective and costlier than sunitinib, there is an important variability on the Incremental Cost-Effectiveness Ratio (ICER) that may lead to different decisions according to the willingness to pay. Sensitivity analyses showed that the results were sensitive to utility and cost data. This thesis highlighted the disparity of the cost-effectiveness results based on clinical trial data (CD and IC) and those estimated using real life data. We observed that a small variation in survival data estimates has a significant impact on the cost-effectiveness results. In order to reduce uncertainty around real life cost-effectiveness, a preliminary work on harmonizing the methods used to estimate cost data from the DCIR must be performed. Furthermore, no matter the scenario studied, we observed a great uncertainty regarding the cost-effectiveness of pazopanib versus sunitinib in first line treatment of mRCC patients. Hence the importance of modeling the value of information to identify the studies that should be implemented in order to reduce the uncertainty around the cost-effectiveness results.
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Submitted on : Thursday, March 29, 2018 - 2:05:08 PM
Last modification on : Friday, October 23, 2020 - 4:56:08 PM


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  • HAL Id : tel-01753032, version 1



Rana Maroun. Analyse comparative coût et efficacité des traitements du cancer du rein métastatique : analyse à partir des données de vie réelleet des données d’essais. Santé publique et épidémiologie. Université Paris Saclay (COmUE), 2018. Français. ⟨NNT : 2018SACLS012⟩. ⟨tel-01753032⟩



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