Real-World Evidence on the Clinical Characteristics and Management of Patients with Chronic Lymphocytic Leukemia in Spain Using Natural Language Processing: The SRealCLL Study.

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.

Cytotoxic Natural Killer Subpopulations as a Prognostic Factor of Malignant Pleural Effusion.

BACKGROUND: Malignant pleural effusion (MPE) is a sign of advanced disease of poor prognosis. As natural killer (NK) cells are involved in the first line of tumour defence, we aimed to validate a new diagnostic and prognostic indicator for MPE based on NK subpopulations of pleural fluid (PF) and peripheral blood (PB). METHODS: NK subpopulations were determined in PF and PB in 71 patients with malignant, paramalignant or benign pleural effusion. The receiver operating characteristic (ROC) curves, Kaplan-Meier, multivariable Cox model and decision trees created with the CHAID (Chi-square automatic interaction detector) methodology were employed. RESULTS: We demonstrated that the PF/PB ratios of the CD56 bright CD16- and CD56 dim CD16- NK subpopulations were higher (p = 0.013 and p = 0.003, respectively) in MPEs and paramalignant pleural effusions (PPEs) than in benign ones, with an AUC of 0.757 and 0.741, respectively. The PF/PB ratio of CD16+ NK and CD57+ NK obtained a higher hazard ratio (HR) in the crude Cox's regression analysis. In the adjusted Cox's regression analysis, the PF/PB ratio of CD16+ NK gave the highest HR (HR 6.1 [1.76-21.1]) (p = 0.004). In the decision tree created for the MPE prognosis, we observed that the main predictor variable among the studied clinical, radiological, and analytical variables was lung mass, and that 92.9% of the patients who survived had a PF/PB ratio of the CD56 dim CD16+ NK subpopulation ≤ 0.43. CONCLUSIONS: Our data suggest that both the PF/PB ratios of cytotoxic subpopulations CD57+ NK and CD16+ NK are useful as a prognostic factor of MPE. Other subpopulations (CD56 bright CD16- and CD56 dim CD16- NK) could help to diagnose MPE.

Predicting Malignant and Paramalignant Pleural Effusions by Combining Clinical, Radiological and Pleural Fluid Analytical Parameters.

BACKGROUND: The usefulness of clinical, radiological and pleural fluid analytical parameters for diagnosing malignant and paramalignant pleural effusion is not clearly stated. Hence this study aimed to identify possible predictor variables of diagnosing malignancy in pleural effusion of unknown aetiology. METHODS: Clinical, radiological and pleural fluid analytical parameters were obtained from consecutive patients who had suffered pleural effusion of unknown aetiology. They were classified into three groups according to their final diagnosis: malignant, paramalignant and benign pleural effusion. The CHAID (Chi-square automatic interaction detector) methodology was used to estimate the implication of the clinical, radiological and analytical variables in daily practice through decision trees. RESULTS: Of 71 patients, malignant (n = 31), paramalignant (n = 15) and benign (n = 25), smoking habit, dyspnoea, weight loss, radiological characteristics (mass, node, adenopathies and pleural thickening) and pleural fluid analytical parameters (pH and glucose) distinguished malignant and paramalignant pleural effusions (all with a p < 0.05). Decision tree 1 classified 77.8% of malignant and paramalignant pleural effusions in step 2. Decision tree 2 classified 83.3% of malignant pleural effusions in step 2, 73.3% of paramalignant pleural effusions and 91.7% of benign ones. CONCLUSIONS: The data herein suggest that the identified predictor values applied to tree diagrams, which required no extraordinary measures, have a higher rate of correct identification of malignant, paramalignant and benign effusions when compared to techniques available today and proved most useful for usual clinical practice. Future studies are still needed to further improve the classification of patients.