Objective: To verify whether absolute monocyte count (AMC) and lymphocyte- monocyte ratio (LMR) at diagnosis are valid prognostic parameters in classical Hodgkin lymphoma (cHL).
Patients And Methods: Data were collected from 1450 patients with cHL treated in Israel and Italy from January 1, 1988, through December 31, 2007.
Results: The median age of the patients was 33 years (range, 17-72 years), and 70% (1017) of the patients had nodular sclerosis (NS); the median follow-up duration was 87 months. The best cutoff value for AMC was 750 cells/mm(3), and the best ratio for LMR was 2.1. The adverse prognostic impact of an AMC of more than 750 cells/mm(3) was confirmed for the entire cohort, and its clinical significance was particularly evident in patients with NS histology. The progression-free survival (PFS) at 10 years for an AMC of more than 750 cells/mm(3) was 65% (56%-72%), and the PFS at 10 years for an AMC of 750 cells/mm(3) or less was 81% (76%-84%; P<.001). The overall survival (OS) at 10 years for an AMC of more than 750 cells/mm(3) was 78% (70%-85%), and the OS at 10 years for an AMC of 750 cells/mm(3) or less was 88% (84%-90%; P=.01). In multivariate analysis, both AMC and LMR maintained prognostic significance for PFS (hazard ratio [HR], 1.54, P=.006, and HR, 1.50, P=.006) after adjusting for the international prognostic score, whereas the impact on OS was confirmed (HR, 1.56; P=.04) only in patients with NS and an AMC of more than 750 cells/mm(3).
Conclusion: This study confirms that AMC has prognostic value in cHL that is particularly significant in patients with NS subtype histology. This finding links the known impact of macrophages and monocytes in Hodgkin lymphoma with routine clinical practice.
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http://dx.doi.org/10.1016/j.mayocp.2015.03.025 | DOI Listing |
Clin Gastroenterol Hepatol
August 2024
Department of Gastroenterology, Liver Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea. Electronic address:
Background & Aims: Hepatocellular carcinoma (HCC) risk persists in patients with chronic hepatitis B (CHB) despite antiviral therapy. The relationship between pre-treatment baseline hepatitis B virus (HBV) viral load and HCC risk during antiviral treatment remains uncertain.
Methods: This multinational cohort study aimed to investigate the association between baseline HBV viral load and on-treatment HCC risk in 20,826 noncirrhotic, hepatitis B e antigen (HBeAg)-positive and HBeAg-negative patients with baseline HBV DNA levels ≥2000 IU/mL (3.
J Imaging Inform Med
August 2024
Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
BMJ Open
August 2024
Department of Neurology, Amsterdam UMC Location AMC, Amsterdam, The Netherlands
Objectives: Diagnostic prediction models exist to assess the probability of bacterial meningitis (BM) in paediatric patients with suspected meningitis. To evaluate the diagnostic accuracy of these models in a broad population of children suspected of a central nervous system (CNS) infection, we performed external validation.
Methods: We performed a systematic literature review in Medline to identify articles on the development, refinement or validation of a prediction model for BM, and validated these models in a prospective cohort of children aged 0-18 years old suspected of a CNS infection.
J Korean Med Sci
April 2024
Department of Pediatrics, Asan Medical Center Children's Hospital, University of Ulsan College of Medicine, Seoul, Korea.
Eur Radiol
October 2024
Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea.
Objectives: To evaluate the use of a commercial artificial intelligence (AI)-based mammography analysis software for improving the interpretations of breast ultrasound (US)-detected lesions.
Methods: A retrospective analysis was performed on 1109 breasts that underwent both mammography and US-guided breast biopsy. The AI software processed mammograms and provided an AI score ranging from 0 to 100 for each breast, indicating the likelihood of malignancy.
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