Choosing Immune Suppression in Renal Transplantation by Efficacy and Morbidity

描述（由申请人提供）：肾移植（KTx）专业人员为患者提供多种免疫抑制（IS）药物和方案。由于早期急性排斥反应（AR）率现在很低，短期移植存活率很高，个体化的长期移植存活率取决于患者潜在的合并症或IS药物的并发症。然而，关于如何平衡IS疗效（预防AR）与并发症（包括移植后感染、癌症和新发糖尿病（NODAT））之间的权衡的研究或数据很少。随机试验或fda批准的风险评估和缓解策略有助于非常具体的情况；但是根据之前对大型国家数据库的分析，也有

DESCRIPTION (provided by applicant): Kidney transplant (KTx) professionals have many choices of immunosuppressive (IS) medications and regimens for their patients. With early acute rejection (AR) rates now low and short term graft survival high, individualized long-term graft survival depends on patients' underlying co-morbidities or complications of IS medications. Yet few studies or data exist on how to balance the trade-offs between IS efficacy (in preventing AR) versus complications, including infections, cancers and new onset diabetes after transplant (NODAT). Randomized trials or FDA-sanctioned Risk Evaluation and Mitigation Strategies help with very specific situations; but along with prior analyses of large national databases, also have many limitations. In this study, we propose to use a novel, three-database linkage of the a) U.S.A. national Organ Procurement and Transplant Network (OPTN) registry: recording initial data on all KTx and subsequent survival outcomes, b) a Medicare billing claims database: covers the first 3 years post-KTx, and c) a national Pharmacy Clearinghouse Database (PCD) that covers 60% of all medication fills in the U.S.A. Using this integration, we can minimize limitations of prior approaches to develop accurate, longitudinal, national level data on the transplant procedures, IS use, survival and non-fatal morbidity. Our investigative team of KTx specialists, economists and statisticians, all with transplant database and outcomes research expertise, can then assess in a more rigorous way than previously possible, the efficacy and morbidity tradeoffs of the IS regimens and doses. In the proposed CISTEM study (Choosing Immune Suppression in Renal Transplantation by Efficacy and Morbidity), we will complete the following three aims: 1) To construct a novel linkage of data from the OPTN registry, an updated Medicare claims dataset and the PCD to quantify the associations of KTx IS with outcome metrics of efficacy and morbidity, adjusted for demographic, medical and immunologic parameters; through propensity-score and covariate-adjusted survival models that will quantify the association between IS regimen or dose and specific measures of efficacy (AR) or morbidity (major infections, cancers, NODAT) that contribute to the hard outcomes of graft survival and patient survival, with sub-analyses for key racial and high-risk subgroups; 2) To use the transition probabilities of events, generated in aim 1, to develop Markov models and calculate the overall cost-effectiveness, including trade-off costs, for each of the major IS regimens in use, by overall group and in the key sub-groups mentioned above; and 3) To use the decision analytics from Aims 1 and 2 to generate individualized and real-time reports of the predicted efficacy/complications outcomes and costs of different KTx IS regimens through a free and updateable patient-focused web- or mobile phone-based risk engine and communication tool. The long-term significance is that physicians and patients will be able to make IS choices in a more cost-effective and better informed manner than any other strategy currently available.