Mycophenolate mofetil (MMF), a mycophenolic acid prodrug, is a highly effective adjunct immunosuppressive agent in transplant therapy. Although MMF is generally well tolerated, optimal therapy may be limited by adverse effects, in particular gastrointestinal (GI) toxicity, which has been reported to occur in up to 45% of MMF-treated patients. MMF dose changes resulting from these adverse events may lead to sub-therapeutic dosing and impaired clinical outcomes. This retrospective study analyzed clinical records from 772 renal transplant patients from 10 US transplant centers who were initiated on MMF. The analysis revealed that 49.7% (n = 382) of patients experienced at least one GI complication within the first 6 months post-transplant, with 66.8% (n = 255) of these having multiple GI complications. Of the patients with GI complications, 39.0% experienced MMF dose adjustments or discontinuation of MMF therapy. Patients with GI complications who experienced MMF dose adjustments/discontinuation had a significantly increased incidence of acute rejections compared with patients without GI complications (30.2% vs. 19.4%; p = 0.005). Mean treatment costs were higher in patients with GI complications than in those with no GI complications, particularly in those who experienced MMF dose adjustments/discontinuation (p = 0.0001). The mean incremental cost for patients experiencing GI complications was US$3700 per patient during the 6 months post-transplant (p < 0.001), which was mainly attributable to hospitalization costs. In summary, GI complications and MMF dose adjustments/discontinuations are associated with a significant negative impact on transplant outcomes and markedly increase short-term treatment costs.

The GSRS and the GIQLI are appropriate for use in a post-renal transplant population. Scores on both instruments demonstrated significant differences between renal transplant patients with GI complications and without GI complications.

These results show that posttransplant clinical outcomes result in a significant increase in treatment costs. Because the economic impact of primary causes of chronic rejection (acute rejection and CMV) and delayed graft function is substantial, careful selection of the most appropriate immunosuppressive regimen is essential.

It is common practice for developers of new health care technologies to engage in early dialogue with the major regulatory agencies; such discussions frequently center around the proposed clinical trial designs to support the registration of new interventions and suggestions on their improvement. Pricing and reimbursement agencies are increasingly using the results from health technology assessments to inform their decision making for new technologies. Such assessments are invariably underpinned by the phase 3 clinical trial evidence which may not provide answers to the key questions. Technology developers are beginning to realize that direct, early dialogue on the evidence requirements of the major pricing and reimbursement agencies, before phase 3 clinical trial designs for their key development compounds have been finalized, may be beneficial. This article reports on the pioneering efforts of one technology developer in seeking early dialogue with seven pricing and reimbursement agencies in five countries globally in 2007-2008 on their likely evidence requirements for a new oral treatment for patients with chronic plaque psoriasis. The pilot project demonstrated that a feasible process of early dialogue could be established, through a face-to-face meeting with prior circulation of a briefing book. Although there was some variation in the advice the similarities far outweighed the differences. More experience of early dialogue needs to be accumulated, involving a wider range of pricing and reimbursement agencies and compounds. The conclusion of this study, however, was that early dialogue can be a worthwhile process for all parties and can lead to a common understanding about evidence development for market access.

BackgroundPharmaceutical companies design clinical development programs to generate the data that they believe will support reimbursement for the experimental compound.ObjectiveThe objective of the study was to present a process for using multicriteria decision analysis (MCDA) by a pharmaceutical company to estimate the probability of a positive recommendation for reimbursement for a new drug given drug and environmental attributes.MethodsThe MCDA process included 1) selection of decisions makers who were representative of those making reimbursement decisions in a specific country; 2) two pre-workshop questionnaires to identify the most important attributes and their relative importance for a positive recommendation for a new drug; 3) a 1-day workshop during which participants undertook three tasks: i) they agreed on a final list of decision attributes and their importance weights, ii) they developed level descriptions for these attributes and mapped each attribute level to a value function, and iii) they developed profiles for hypothetical products ‘just likely to be reimbursed’; and 4) use of the data from the workshop to develop a prediction algorithm based on a logistic regression analysis. The MCDA process is illustrated using case studies for three countries, the United Kingdom, Germany, and Spain. The extent to which the prediction algorithms for each country captured the decision processes for the workshop participants in our case studies was tested using a post-meeting questionnaire that asked the participants to make recommendations for a set of hypothetical products.ResultsThe data collected in the case study workshops resulted in a prediction algorithm: 1) for the United Kingdom, the probability of a positive recommendation for different ranges of cost-effectiveness ratios; 2) for Spain, the probability of a positive recommendation at the national and regional levels; and 3) for Germany, the probability of a determination of clinical benefit. The results from the post-meeting questionnaire revealed a high predictive value for the algorithm developed using MCDA.ConclusionsPrediction algorithms developed using MCDA could be used by pharmaceutical companies when designing their clinical development programs to estimate the likelihood of a favourable reimbursement recommendation for different product profiles and for different positions in the treatment pathway.