Characterization of second primary malignancies post CAR T-cell therapy: real-world insights from the two global pharmacovigilance databases of FAERS and VigiBase

Abstract

Background: The FDA's alerts regarding the T-cell lymphoma risk post CAR-T therapy has garnered global attention, yet a comprehensive profile of second primary malignancies (SPMs) following CAR-T treatment is lacking.

Methods: We extracted adverse event reports of hematological malignancies (HMs) patients with clearly definable SPMs from the FAERS and VigiBase databases (2017-2023). Disproportionality analysis using reporting odds ratio (ROR) and adjusted ROR was performed to assess associations between SPMs and CAR-T therapy. Time-to-onset analysis explored factors affecting SPM manifestation.

Findings: SPMs post CAR T-cell therapy include HMs and solid tumors. T-cell lymphoma and myelodysplastic syndromes were consistently identified as positive signals across the overall and subgroup analyses. Hematological SPMs showed earlier onset with increasing annual incidence post CAR-T therapy, whereas solid tumors exhibit delayed manifestation. SPMs in CAR-T recipients had significantly earlier onset than non-recipients. Furthermore, age-specific characteristics reveal earlier SPM manifestations in pediatric, adolescent, and young adult populations compared to older populations post CAR-T therapy.

Interpretation: The current SPM profile highlights the necessity of long-term safety monitoring for all CAR-T recipients given the observed yearly increase of SPMs. Customizing long-term SPM screening across different age groups may enhance early detection and intervention strategies, ultimately improving patient outcomes in the follow-up of CAR-T recipients.

Funding: This work was supported by grants from the Natural Science Foundation of Guangdong Province (2018A030313846 and 2021A1515012593), the Science and Technology Planning Project of Guangdong Province (2019A030317020), the National Natural Science Foundation of China (81802257, 81871859, 81772457, 82172750, 82172811, and 82260546), the Guangdong Basic and Applied Basic Research Foundation (Guangdong-Guangzhou Joint Funds) (2022A1515111212), and the Science and Technology Program of Guangzhou (2023A04J1257).

Keywords: CAR-T; FAERS; Myelodysplastic syndromes; Second primary malignancy; T-cell lymphoma; VigiBase.

Fig. 1

Data processing flowchart delineating the selection process of SPMs post CAR-T therapy. Cases lacking accurate inference as SPMs are excluded; refer to Supplementary Table S2 for examples. FAERS indicates the FDA adverse event reporting system, SPM indicates secondary primary malignancies.

Fig. 2

The overview of SPMs post CAR-T therapy. (A and B) The cumulative histogram illustrates the annual incidence of SPMs post CAR-T therapy in patients with hematological tumors, juxtaposed with corresponding drug-related cases in FAERS and VigiBase. The annual incidence rate from 2017 to 2023 was calculated by dividing the number of reported SPM cases associated with CAR-T therapy each year by the total number of adverse event cases related to CAR-T treatment within the same year. (C and D) Statistical analysis of SPM post CAR-T therapy occurrences in FAERS and VigiBase databases spanning 2017–2023. The histogram showcases the incidence of all malignancies, solid tumors, and hematological malignancies, respectively. The line chart delineates the proportion of SPM cases post CAR-T therapy among all CAR-T-related AEs. (E and F) Examination of the association between the primary malignancies (FPMs) and the corresponding SPMs in CAR-T recipients.

Fig. 3

Identification of high-risk SPMs post CAR-T therapy utilizing FAERS and VigiBase databases. (A) The heatmap displays the ROR of SPMs with cases exceeding three in FAERS and VigiBase, respectively. All CAR-T products and the subgroups targeting CD19-and BCMA-antigens are represented. The size of the point corresponds to the number of cases, while reddish hues indicate higher ROR values. Gray denotes insignificance of the SPM signal. (B) Forest plot presenting ROR values of high-risk SPMs with significant signals across all targets in FAERS or VigiBase. The error bars show the 95% CI of the ROR. Red signifies a significant positive signal, whereas gray denotes insignificance. (C) The forest plot illustrates ROR values of SPMs post CAR-T therapy with cases exceeding three in FAERS and VigiBase, using all chemotherapy drugs and specific subgroups as control groups for comparison. The error bars show the 95% CI of the ROR. Red signifies a significant positive signal, blue signifies a significant negative signal, whereas gray denotes insignificance. ROR indicates reporting odds ratio.

Fig. 4

Time to onset analysis of SPMs. (A) The cumulative distribution curve depicts the onset times of SPMs in patients with hematological malignancies receiving CAR-T vs Non-CAR-T therapy. (B) The cumulative distribution curve depicts the onset time of SPMs post CAR-T therapy across different sexes in FAERS. (C and D) The cumulative distribution curve depicts the onset time of SPMs post CAR-T therapy across different age group in FAERS. In D, the age group of 0–39 years is subdivided into two categories: “0–17 years old” and “18–39 years old”. (E) The cumulative distribution curve depicts the onset time of SPMs post CAR-T therapy across different cancer types in FAERS. Utilizing a 500-day cutoff, the landmark method portrays the onset time of various cancer types before and after this threshold. Data with TTO time less than 14 days were excluded. Statistical analyses employed the Mann–Whitney U test and pairwise comparisons were conducted using the Kruskal–Wallis test, with corrections applied using the Benjamini & Hochberg method. TTO indicates time to onset.