| Title: |
Real-World Evidence on the Clinical Characteristics and Management of Patients with Chronic Lymphocytic Leukemia in Spain Using Natural Language Processing: The SRealCLL Study. |
| Authors: |
Loscertales, Javier, Abrisqueta-Costa, Pau, Gutierrez, Antonio, Hernández-Rivas, José Ángel, Andreu-Lapiedra, Rafael, Mora, Alba, Leiva-Farré, Carolina, López-Roda, María Dolores, Callejo-Mellén, Ángel, Álvarez-García, Esther, García-Marco, José Antonio |
| Source: |
Cancers; Aug2023, Vol. 15 Issue 16, p4047, 13p |
| Subject Terms: |
CHRONIC lymphocytic leukemia treatment, NATURAL language processing, MACHINE learning, ARTIFICIAL intelligence, SYMPTOMS, DESCRIPTIVE statistics, RESEARCH funding, ELECTRONIC health records, COMORBIDITY |
| Geographic Terms: |
SPAIN |
| Abstract: |
Simple Summary: To our knowledge, this is the first study to use free text from electronic healthcare records as a data source extracted with natural language processing to characterize the clinical characteristics and management of patients with chronic lymphocytic leukemia. A total of 534 included patients were stratified regarding the type of therapeutic management during the study period. Our results highlight the increased use of drugs directed to specific target therapies and the lower frequency of treatment with chemoimmunotherapy both in the first line and in relapsed/refractory settings in our sample of seven academic hospitals from 2016 to 2018. This real-world evidence study provides information on the diversity of clinical features and treatment patterns of chronic lymphocytic leukemia, evidencing the need to optimize patients' clinical management through personalizing their therapeutic approach. The SRealCLL study aimed to obtain real-world evidence on the clinical characteristics and treatment patterns of patients with chronic lymphocytic leukemia (CLL) using natural language processing (NLP). Electronic health records (EHRs) from seven Spanish hospitals (January 2016–December 2018) were analyzed using EHRead® technology, based on NLP and machine learning. A total of 534 CLL patients were assessed. No treatment was detected in 270 (50.6%) patients (watch-and-wait, W&W). First-line (1L) treatment was identified in 230 (43.1%) patients and relapsed/refractory (2L) treatment was identified in 58 (10.9%). The median age ranged from 71 to 75 years, with a uniform male predominance (54.8–63.8%). The main comorbidities included hypertension (W&W: 35.6%; 1L: 38.3%; 2L: 39.7%), diabetes mellitus (W&W: 24.4%; 1L: 24.3%; 2L: 31%), cardiac arrhythmia (W&W: 16.7%; 1L: 17.8%; 2L: 17.2%), heart failure (W&W 16.3%, 1L 17.4%, 2L 17.2%), and dyslipidemia (W&W: 13.7%; 1L: 18.7%; 2L: 19.0%). The most common antineoplastic treatment was ibrutinib in 1L (64.8%) and 2L (62.1%), followed by bendamustine + rituximab (12.6%), obinutuzumab + chlorambucil (5.2%), rituximab + chlorambucil (4.8%), and idelalisib + rituximab (3.9%) in 1L and venetoclax (15.5%), idelalisib + rituximab (6.9%), bendamustine + rituximab (3.5%), and venetoclax + rituximab (3.5%) in 2L. This study expands the information available on patients with CLL in Spain, describing the diversity in patient characteristics and therapeutic approaches in clinical practice. [ABSTRACT FROM AUTHOR] |
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| Database: |
Complementary Index |
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