the mapping problem as a missing data problem and clarify such conditions. Methods: We define a valid mapping algorithm as a mapping algorithm that can produce unbiased estimates of expected health utility in the experimental and control treatments in cost-utility analysis. This definition reflects the purpose of mapping (i.e., not for individual health utility prediction but for CUA). As mapping can be viewed as imputation of missing health utility data, we derive a sufficient set of statistical conditions for a valid mapping algorithm based on the theory of missing data analysis. We conducted a simulation study to investigate properties of a mapping algorithm under situations where the derived conditions are satisfied and violated. Results: The derived sufficient conditions indicate importance of the "complete overlap" of the source measure to the target health utility measure and a covariates that is omitted from a mapping algorithm but has an effect on the target health utility measure not captures by the source measure. The conditions cannot be verified from observed data in CUA, but can be supported using external data. A simulation study showed that when at least one of the derived conditions was violated, a mapping algorithm provided biased health utility estimates in CUA, and that prediction accuracy did not necessarily reflect performances of a mapping algorithm in CUA. Conclusions: The derived conditions for a valid mapping algorithm provide a guidance for better practices in developing and selecting a mapping algorithm for CUA.
Purpose: The clinical study report (CSR) documents of a full clinical development pathway (CDP) have been publicly available on the European Medicines Agency (EMA; Amsterdam, Netherlands) clinical data website (ECDW) since October 2016. Our analysis aimed to determine the extent to which the available clinical development program could be assessed. Methods: The documents available on the ECDW up to April 1, 2018 and the corresponding European Public Assessment Report (EPAR) were reviewed. Information extracted from the available CSRs focused on dates, phase of development, module leaf structure, and number of protocol amendments. Data analyses included generalized activity normalization time table (GANTT) charts and network analyses. Results: Of the 86 available CDPs, 55 were initial marketing authorizations covering a diverse range of clinical developments from generics to advanced therapy in the electronic common technical documents (eCTDs). Non-redacted dates were available in 444 CSRs from 15 CDPs to perform retrospective project clinical development management analyses. In these 15 marketing authorizations, the median timespan to submission was 9.3 years (range: 6.2-22.2). The timespan within these 15 clinical developments ranged from 5.9 to 21.4 years (median 8.3). The median time to first-subject-in in the first controlled clinical study pertinent to the claimed indication (CCSPCI) was 4.4 years (range: 0-12.1); the duration of the CCSPCI ranged from 2.4 to 16.9 years (median: 4.4; interquartile range: 4.2-7.0). Four CDPs had concurrent subject enrolment, while seven CDPs had seamless study designs. Subject participation ranged from 52% to 97% of a clinical development timeline. Conclusion: The publication of CSR documents by the EMA has enabled insights into timelines and project management aspects of the clinical development of medications.
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