We summarise a study, published in Pharmacoepidemiology and Drug Safety, that harnessed real–world data to define a reproducible procedure. This procedure is able to identify a CAR-T target population for diffuse large B-cell lymphoma (DLBCL).
RWD and DLBCL
RWD reflects the experience of individuals through their routine interactions with healthcare systems or through data collected in surveys, registries and sensors or devices. For several decades, RWD has been utilised in clinical and epidemiological research, particularly to assess product safety. In some circumstances, observational evidence can also be used to assess the effectiveness and benefit-risk profile of medicinal products.
Nonetheless, the rapid expansion of RWD suggests that its use may extend beyond the post-authorisation phase. In fact, it may act as a tool to support health technology assessments (HTA) decision processes in the identification of target therapies. For example, RWD may be useful for defining characteristics of the target population for new medicines and measuring the validity of any surrogate endpoint used to measure effectiveness.
In this study, the authors believed that record linkages might be helpful in defining the number and type of patients who will benefit from new advanced therapies for B-cell malignancies. DLBCL is the most common subtype of non-Hodgkin lymphoma. It accounts for about 25-30% of newly diagnosed cases of B-cell lymphoma worldwide. DLBCL is an aggressive tumour pathology often refractory to currently available treatments and with a high incidence of relapse. The standard first line therapies for DLBCL is chemo-immunotherapy and autologous stem cell transplantation (ASCT). Although beneficial in many patients, these regimens can often lead to patient relapse. In these cases, CAR-T therapy has shown promise.
HTA’s activity to estimate the impact of new CAR T therapy is not an easy task. Additionally, given the high costs of DLBCL treatments, defining the correct target population is critical.
Identifying a target population
Here, researchers used RWD to define a reproducible procedure that identified a DLCBCL CAR-T target population useful for HTA purpose. Specifically, they conducted an observational, record-linkage, multi-database, retrospective study using healthcare databases from the Lazio Region. DLBCL patients were followed using pathological anatomy (PA) reports, up to 3 years.
The cohort consisted of 7,384 NHL patients – 68% presented a PA report and 29% of these had DLBCL codes. In their cohort, patients surviving to first line therapy experienced a second relapse in 39% or 41% of cases in the ASCT and conventional second line therapy cohorts, respectively. Also, patients in the two subgroups were very different in terms of age and comorbidity.
To estimate the number of potential candidates for CAR-T, the team applied the incidence rate of second relapse and relative bootstrap confidence intervals to the overall DLBCL population. From this, they showed that 45 patients per year are eligible for CAR-T in the Lazio region.
This study highlights the use of RWD to identify a target population with new advanced therapies. The authors noted that this approach is rigorous, transparent and verifiable over time. Their findings demonstrate the importance of RWD for the decision-making process at the time of defining the economic burden of new advanced therapies in the context of HTA.
Image credit: Photo by National Cancer Institute on Unsplash