Occult hepatitis B virus infection status is not associated with impaired efficacy of anti‐CD19 CAR‐T‐cell therapy for lymphoma and shows a distinct immune toxicity profile: Results from the CART‐SIE study

Hepatitis B virus (HBV) remains one of the most common chronic viral infections worldwide, with an estimated 257 million people affected. HBV-positive (HBV+), defined by the presence of anti-HBc antibodies without detectable HBV-DNA (occult hepatitis B virus infection, OBI), is particularly relevant in immunocompromised patients. In the setting of hematologic malignancies, HBV reactivation can occur during or after chemotherapy, immunotherapy, or stem cell transplantation, leading to potentially life-threatening complications.1, 2 Therefore, prophylactic antiviral therapy is generally recommended in these clinical scenarios, with recent updates regarding the choice of agent and duration of treatment.3 T-cell engagers such as bispecific antibodies and chimeric antigen receptor T (CAR-T) cells are becoming pivotal in the treatment of several hematological disorders; in particular, CAR-T-cell therapy has emerged as a breakthrough treatment for relapsed or refractory lymphomas, including large B-cell lymphomas (LBCLs), mantle cell lymphoma (MCL), follicular lymphoma, and other neoplasms.4 However, limited data exist regarding the safety and efficacy of such therapies in the context of HBV carriers.5-8 In a recent report on 99 multiple myeloma (MM) patients treated with BCMA-targeted CAR-T-cell therapy, 7 of those with chronic infection and 43 with resolved HBV infection, 4 patients (1 with chronic and 3 with resolved infection) experienced HBV reactivation, resulting in 2 cases of severe hepatitis and 1 HBV-related death, despite use of specific antiviral therapy.9 To the best of our knowledge, only two OBI patients treated with CD19-targeted CAR-T cells have been reported so far.10 The CART-SIE study, an ongoing multicenter prospective observational study collecting data on all consecutive lymphoma patients treated with commercial CAR-T cells in Italy, offers a unique opportunity to explore this question in a large, real-world population.11 Thus, we retrospectively analyzed 1124 consecutive patients treated with anti-CD19 commercially available CAR-T-cell therapy for lymphoma within the CART-SIE study. Patients with active HBV infection were excluded according to Italian regulatory requirements. Patients with evidence of prior HBV exposure (anti-HBc positive, HBV-DNA negative; HBV+) were compared with HBV serologically negative patients (HBV−). All HBV+ patients received antiviral prophylaxis before and after CAR-T-cell therapy, mostly with lamivudine (>90%). Median follow-up, calculated by reverse Kaplan–Meier method,12 was 16.5 months (95% CI, 13.2–17.8). Primary endpoints were progression-free survival (PFS) and overall survival (OS). Secondary endpoints included overall response rate (ORR), complete response (CR) rate, relapse incidence, and CAR-T-cell–related toxicities, including cytokine release syndrome (CRS), immune effector cell–associated neurotoxicity syndrome (ICANS), immune effector cell–associated hematotoxicity (ICAHT), infections, and secondary malignancies. Survival outcomes were estimated using the Kaplan–Meier method and Cox proportional hazards regression models. Associations between OBI status and patient- and disease-related characteristics, as well as categorical outcomes—including response rates, relapse incidence, and treatment-related toxicities—were assessed using the t test for continuous variables and the chi-square test for categorical variables, as appropriate. Multivariable logistic regression models were used to identify factors associated with treatment-related toxicities and HBV positivity. For CAR-T-cell kinetic analyses, between-group comparisons were performed using two-sided Mann–Whitney U tests, and results were reported as medians with interquartile ranges (Q1–Q3). A two-sided P-value < 0.05 was considered statistically significant. Baseline characteristics were largely balanced between HBV+ (n = 114) and HBV− patients (n = 1010), except that HBV+ patients were older (median 62.2 vs. 57.2 years; P < 0.001) and had a higher prevalence of diffuse large B-cell lymphoma (DLBCL; 77.2% vs. 61.9%; P = 0.001). Table 1 details the patients' characteristics by HBV serostatus. Response rates at Day 30 were comparable between the two groups (ORR 79.3% vs. 80.3%, with CR rates of 56.1% in HBV− vs. 57.0% in HBV+ patients, P = 0.913). Similar results were observed at Day 90 (ORR 72.2% vs. 72.2%, with CR rates of 63.3% vs. 60.2%; P = 0.791). Relapse rates were slightly higher in the HBV+ cohort (50.9% vs. 42.0%, P = 0.073); however, when analyzed in a time-dependent manner, long-term outcomes were comparable between groups. The 12- and 36-month OS rates were 70.8% (95% CI, 67.4–73.9) and 53.8% (95% CI, 48.8–58.6) in HBV− patients, compared with 64.0% (95% CI, 52.9–73.2) and 52.6% (95% CI, 40.7–63.2) in HBV+ patients (P = 0.239). The corresponding 12- and 36-month PFS rates were 50.6% (95% CI, 47.1–53.9) and 42.0% (95% CI, 37.7–46.2) in HBV− patients versus 43.2% (95% CI, 33.0–52.9) and 35.8% (95% CI, 25.8–45.9) in HBV+ patients, respectively (P = 0.163) (Figure 1A,B). After adjustment for factors known to be associated with outcomes (age, sex, lymphoma histotype [DLBCL vs. other types], number of prior therapies, previous autologous stem cell transplant, and use of bridging therapy), multivariable analyses confirmed that HBV positivity did not significantly affect either OS (HR 1.12, 95% CI, 0.80–1.57, P = 0.497) or PFS (HR 1.15, 95% CI, 0.88–1.51, P = 0.304). Regarding toxicities, no cases of HBV reactivation were detected. Notably, CRS occurred less frequently in HBV+ patients (81.6% vs. 88.4%, P = 0.049), a finding that remained significant after adjustment for age, diagnosis, and CAR-T-cell product (odds ratio 0.55; 95% CI, 0.32–0.95, P = 0.033). In contrast, the incidence of ICANS was similar between HBV– and HBV+ patients (26.8% vs. 28.1%, P = 0.824), although HBV+ patients more frequently experienced milder forms (Grade I: 56.2% vs. 39.2%, P = 0.043). Rates of ICAHT (24.6% vs. 18.4%, P = 0.165), secondary malignancies (3.9% vs. 6.1%, P = 0.219), and infections (11.5% vs. 9.6%, P = 0.642) were comparable between the HBV– and HBV+ groups, respectively. Given the established association between early CAR-T-cell expansion and the risk/severity of CRS and ICANS,13 we evaluated expansion kinetics to assess whether HBV serostatus and/or antiviral prophylaxis could modulate in vivo CAR-T-cell activity. No statistically significant differences were observed between HBV+ and HBV− patients with respect to time to maximal expansion (TMAX; HBV+ n = 38: 10.00 days [7.00–10.00] vs. HBV− n = 306: 10.00 [7.00–14.00]; P = 0.233), Day 10 expansion (C10; HBV+ n = 24: 13.37 [6.07–71.02] vs. HBV− n = 172: 24.45 [9.20–61.91]; P = 0.483), overall expansion during the first 30 days post-infusion (area under curve [AUC]0–30; HBV+ n = 39: 324.70 [164.90–1137.79] vs. HBV− n = 316: 436.80 [191.76–1169.87]; P = 0.749), or peak of expansion (CMAX; HBV+ n = 39: 39.67 [13.93–127.88] vs. HBV− n = 317: 44.74 [16.18–109.24]; P = 0.947). Overall, HBV serostatus was not associated with measurable differences in the magnitude or timing of early CAR-T-cell expansion within the first 30 days post-infusion (Figure S1). In this large real-world analysis from the CART-SIE study, we show that occult HBV infection does not negatively impact efficacy or safety outcomes of anti-CD19 CAR-T-cell therapy in lymphoma patients when appropriate antiviral prophylaxis is adopted. To our knowledge, this represents the largest dataset addressing this clinically relevant issue in the CAR-T-cell setting. Despite HBV+ patients being older and more frequently affected by DLBCL, both unfavorable prognostic features,14, 15 early response rates and long-term outcomes were comparable between HBV+ and HBV− cohorts. Neither OS nor PFS differed significantly in the long term, and multivariable analyses confirmed that HBV serostatus was not independently associated with inferior outcomes. Although relapse incidence was numerically higher among HBV+ patients, this did not translate into worse survival, suggesting no clinically meaningful impact on long-term disease control. From a safety standpoint, no cases of HBV reactivation were observed, underscoring the effectiveness of systematic antiviral prophylaxis in this setting.16 This finding is particularly reassuring in light of previous reports describing severe HBV reactivation following T-cell–engaging therapies, in which prophylactic antiviral treatment was less consistently adopted.17 Notably, despite recent recommendations favoring entecavir or tenofovir for HBV prophylaxis, no reactivation events were observed in our cohort, in which lamivudine was widely used.18 In the context of undetectable HBV-DNA at baseline, the use of a low–genetic barrier but well-tolerated agent such as lamivudine appears effective in preventing HBV reactivation. Nevertheless, given the limited prospective evidence, further studies are warranted to better define the optimal prophylactic strategy in this setting.3 Overall, CAR-T-cell–related toxicities were comparable between groups. Interestingly, HBV+ patients experienced a lower incidence of CRS, a signal that remained significant after adjustment for relevant confounders. Additionally, milder forms of ICANS were documented in the HBV+ population. Notably, this toxicity profile was not associated with differences in early CAR-T-cell expansion kinetics, which were comparable between HBV+ and HBV− patients. While the biological basis of these observations remains speculative, they may reflect immunomodulatory effects related to viral exposure or antiviral therapy19, 20; however, the lack of correlative immunological data precludes definitive conclusions. Accordingly, these findings should be interpreted with caution and considered hypothesis-generating. Limitations include the retrospective nature of the analysis and the absence of extended longitudinal HBV-DNA and lymphoid population monitoring. Nevertheless, the large sample size, multicenter prospective data collection, and real-world setting strengthen the robustness and generalizability of our findings. In conclusion, OBI status (anti-HBc positive, HBV-DNA negative) does not appear to adversely affect clinical outcomes or toxicity profiles in lymphoma patients undergoing CAR-T-cell therapy. With appropriate antiviral prophylaxis, HBV positivity should not be considered a contraindication to CAR-T-cell treatment. We are deeply grateful to the patients who participated in this study and their caregivers, as well as to the healthcare professionals, hospital staff, and clinical study coordinators for their invaluable support and dedication. Nicola Polverelli: Conceptualization; methodology; data curation; validation; supervision; writing—original draft; writing—review and editing. Annalisa Chiappella: Conceptualization; writing—original draft; writing—review and editing. Cristiana Carniti: Conceptualization; writing—original draft; writing—review and editing; formal analysis. Pierluigi Zinzani: Data curation. Maurizio Musso: Data curation. Maria Chiara Tisi: Data curation. Fabio Ciceri: Data curation. Ilaria Cutini: Data curation. Armando Santoro: Data curation. Patrizia Chiusolo: Data curation. Anna Maria Barbui: Data curation. Mirko Farina: Data curation. Livia Donzelli: Data curation. Lucia Brunello: Data curation. Massimo Martino: Data curation. Mauro Krampera: Data curation. Alessia Castellino: Data curation. Giovanni Grillo: Data curation. Barbara Botto: Data curation. Jacopo Olivieri: Data curation. Michele Clerico: Data curation. Pellegrino Musto: Data curation. Attilio Olivieri: Data curation. Antonio Bianchessi: Data curation. Irene Defrancesco: Data curation. Giulia Losi: Data curation. Caterina Zerbi: Data curation. Gianluca Martini: Data curation. Elisa Roncoroni: Data curation. Manuel Gotti: Data curation. Maria Grazia Benevento: Data curation. Alessia Taurino: Data curation. Anna Fedina: Data curation; project administration. Paolo Corradini: Conceptualization; writing—review and editing. Luca Arcaini: Methodology; conceptualization; writing—review and editing. N.P. received honoraria from Novartis and Kite Pharma and acted as a consultant for Kite Pharma. ACh advisory boards—AbbVie, Gilead-Sciences/Kite Pharma Inc., Incyte Corporation, and Sobi; lecture fees/educational events—Eli Lilly and Gilead-Sciences/Kite Pharma Inc. Other authors declare no conflict of interest. This study was approved by the ethics committee of the Fondazione IRCCS Istituto Nazionale dei Tumori (INT 180/19) and by the institutional review boards at each site (clinicaltrials gov. Identifier: NCT06339255). This research received no funding. The data that support the findings of this study are available on request from the corresponding author. 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