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We herein report the case of a 73‐year‐old male patient who was diagnosed with leukemic non‐nodal MCL. This patient had received six cycles of bendamustine, which resulted in a transient remission, and a second‐line therapy with ibrutinib, which unfortunately failed to induce remission. We started a treatment with single‐agent obinutuzumab at a dose of 20 mg on day 1, 50 mg on day 2‐4, 330 mg on day 5, and 1000 mg on day 6. The laboratory analysis showed a rapid decrease of leukocyte count. Four weeks later, we repeated the treatment with obinutuzumab at a dose of 1000 mg q4w and started a therapy with venetoclax at a dose of 400 mg qd, which could be increased to 800 mg qd from the third cycle. This combination therapy was well tolerated. The patient achieved a complete remission (CR) after three cycles of obinutuzumab and venetoclax. To date, the patient has a progression‐free survival of 17 months under ongoing obinutuzumab maintenance q4w. This is the first report about obinutuzumab and venetoclax induced CR in rituximab‐intolerant patient with an ibrutinib‐resistant MCL. This case suggests that obinutuzumab‐ and venetoclax‐based combination therapy might be salvage therapy in patients with ibrutinib‐resistant MCL.
Background: Natural language processing (NLP) is a powerful tool supporting the generation of Real-World Evidence (RWE). There is no NLP system that enables the extensive querying of parameters specific to multiple myeloma (MM) out of unstructured medical reports. We therefore created a MM-specific ontology to accelerate the information extraction (IE) out of unstructured text. Methods: Our MM ontology consists of extensive MM-specific and hierarchically structured attributes and values. We implemented “A Rule-based Information Extraction System” (ARIES) that uses this ontology. We evaluated ARIES on 200 randomly selected medical reports of patients diagnosed with MM. Results: Our system achieved a high F1-Score of 0.92 on the evaluation dataset with a precision of 0.87 and recall of 0.98. Conclusions: Our rule-based IE system enables the comprehensive querying of medical reports. The IE accelerates the extraction of data and enables clinicians to faster generate RWE on hematological issues. RWE helps clinicians to make decisions in an evidence-based manner. Our tool easily accelerates the integration of research evidence into everyday clinical practice.