Demonstrating Benefit-Risk Profiles of Novel Therapeutic Strategies in Kidney Transplantation: Opportunities and Challenges of Real-World Evidence

Abstract

While great progress has been made in transplantation medicine, long-term graft failure and serious side effects still pose a challenge in kidney transplantation. Effective and safe long-term treatments are needed. Therefore, evidence of the lasting benefit-risk of novel therapies is required. Demonstrating superiority of novel therapies is unlikely via conventional randomized controlled trials, as long-term follow-up in large sample sizes pose statistical and operational challenges. Furthermore, endpoints generally accepted in short-term clinical trials need to be translated to real-world (RW) care settings, enabling robust assessments of novel treatments. Hence, there is an evidence gap that calls for innovative clinical trial designs, with RW evidence (RWE) providing an opportunity to facilitate longitudinal transplant research with timely translation to clinical practice. Nonetheless, the current RWE landscape shows considerable heterogeneity, with few registries capturing detailed data to support the establishment of new endpoints. The main recommendations by leading scientists in the field are increased collaboration between registries for data harmonization and leveraging the development of technology innovations for data sharing under high privacy standards. This will aid the development of clinically meaningful endpoints and data models, enabling future long-term research and ultimately establish optimal long-term outcomes for transplant patients.

Determinants of immunosuppressive therapy in renal transplant recipients: an Italian observational study (the CESIT project)

“…The great heterogeneity in the choice of drug treatment observed, suggests the need to improve evidence, by RCT or RWE, in the risk-bene t pro le of immunosuppressive strategies in speci c subgroup population, including patients with comorbidities, such as hypertension hyperparathyroidism, cardiovascular diseases, history of chronic infections, in order to better tailoring immunosuppressive strategy on patient's characteristics [14].…”

Immune tolerance via FCR001 cell therapy compared with maintenance immunosuppression for kidney transplantation: Real‐world evidence analysis of safety and efficacy

“…Benefits of RWE include longer follow-up, a diverse population, and reduced cost. 12,23 The NMEDW is particularly valuable for these studies, as it includes data from diverse sources including clinical records, laboratory data, biopsy reports, and linked transplant registry data. These detailed data provide insight into the functional outcome of SOC-R patients not available in studies based exclusively on administrative claims.…”

“…The incidence of adverse events (AEs) including infection, malignancy, hospitalization, hematologic abnormalities, thromboembolism, new‐onset diabetes mellitus or dyslipidemia, and select cardiovascular events were determined using electronic medical records and international classification of diseases (ICD)−9/10, Healthcare Common Procedure Coding System (HCPCS), Diagnostic‐Related Group (DRG), Systemized Nomenclature of Medicine (SNOMED), and Logical Observation Identifiers Names and Codes (LOINC) codes summarized in Supplemental Digital Content: Appendix. Direct chart review was not used consistent with RWE methodologies to define computable phenotypes 12,22,23 . Graft‐vs‐host disease was also evaluated in the FCR‐R group using case review forms as there were no cases of graft‐vs‐host disease in SOC kidney transplant recipients.…”

“…Direct chart review was not used consistent with RWE methodologies to define computable phenotypes. 12,22,23 Graft-vs-host disease was also evaluated in the FCR-R group using case review forms as there were no cases of graft-vs-host disease in SOC kidney transplant recipients. To increase the precision of these computable phenotypes, an adverse event was considered significant if the defined code associated with an inpatient hospitalization that lasted ≥2 days or was…”

“…[8][9][10] Real-world data, such as those originating from electronic health records and health care claims, are increasingly used to generate real-world evidence (RWE) that can contribute to treatment development programs investigating potential benefits and risks of medical products. 11,12 Through the use of modern statistical techniques, RWE can be used to create quasi-experimental analyses in which treated patients are matched with similar patients treated with existing clinical regimens to assess differences in patient outcome, resource utilization, and treatment-related complications. RWE can inform regulatory decision-making, including the approval of new treatments or expansion of indications for available treatments, as directed by recent guidance from the Food and Drug Administration.…”