Real-world analyses of bispecific antibodies and CAR-T cell therapy in relapsed or refractory multiple myeloma: a global TriNetX discovery and contemporary validation cohort.

Theo Leitner¹, Lorenz Oelschläger^1,2,3, Francisco Henriquez Mosquera⁴, Christoph Schaefers⁵, Lisa Leypoldt^5,6, Katja Weisel⁵, Nikolas von Bubnoff¹, Markus Rückert⁴, Christoph Kimmich^2,3, Helal Ahmed^1,2,3,7, Jan Vorwerk^1,8, Cyrus Khandanpour^1,2,3

¹Department of Hematology and Oncology, University Cancer Center Schleswig-Holstein (UCCSH), University Hospital Schleswig-Holstein (UKSH) and University of Luebeck, Luebeck, Germany.

²Department of Oncology and Hematology, Klinikum Oldenburg, Oldenburg, Germany.

³University Medicine Oldenburg, Carl von Ossietzky University, Oldenburg, Germany.

⁴TriNetX Oncology GmbH, Freiburg, Germany.

⁵Department of Hematology, Oncology, and Bone Marrow Transplantation with Section of Pneumology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.

⁶Mildred Scheel Early Career Center, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.

⁷Faculty of Medicine and Health Sciences, Amran University, Amran, Yemen.

⁸Detlef Zillikens Clinician Scientist Academy, University of Luebeck, Luebeck, Germany.

PubMed DOI

Abstract

Bispecific antibodies (BsAbs) and BCMA-directed CAR-T cell therapies have transformed late-line relapsed/refractory multiple myeloma (RRMM), yet real-world comparisons are confounded by treatment selection, line of therapy, and supportive care. We combined a global propensity-matched TriNetX discovery analysis with a contemporary, treatment-line-aware validation cohort. In TriNetX, 223,703 myeloma…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free Account Sign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.