Utilizzo dei Real World Data per definire la popolazione target di nuove indicazioni terapeutiche: l’esempio delle terapie CAR-T.

Abstract

CAR-T therapies are a form of innovative and personalised immunotherapy in the field of onco-haematology. Diffuse large B-cell lymphoma (DLBCL) is a very aggressive form of non-Hodgkin's lymphoma (NHL) for which CAR-T therapies are approved as 3rd-line and more recently (from 11/11/2023), as 2nd-line for patients who relapse within 12 months after 1st-line chemo-immunotherapy. This study was conducted to estimate the eligible DLBCL population for CAR-T therapies in 2024 in Lazio region. Starting with a cohort of DLBCL patients from a previous work, a series of proportions were first obtained applying the eligibility criteria for CAR-T, and then applied to the annual incident cases of NHL in Lazio region. From 1,353 NHL cases, 392 (29%) were considered DLBCL of which 82% (322) received first line chemo-immunotherapy. They were then divided into two groups: with relapse ≤12 months (Group 1) and with relapse >12 months (Group 2). Fifty percent of Group 1 (46 cases) and part of those not eligible to ASCT (35%=16 cases) constitute the eligible population for CAR-T therapy as 2nd-line. From the 29 cases of Group 2, were calculated the proportions of CAR-T eligible patients among those not eligible for ASCT (35%=5 cases) and those who did not respond to salvage chemotherapy (65%=4 cases) and with post-transplant relapse (39%=3 cases). A total of 74 DLBCL patients were found to be eligible for CAR-T therapies. This study demonstrates that the use of Real World Data is a valuable tool in defining the target population for new therapeutic indications.