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SplenoMegaly study (SMS): exploring the etiologies for "unexplained" splenomegalies in the real world
Guillaume Denis1, Louis Terriou2, Thomas Sené3
1Department of Internal Medicine and Hematology, Rochefort Hospital, Rochefort, France. guillaume.denis@ght-atlantique17.fr.
Background:
The predominant etiologies of splenomegaly (SM) are readily discernible through routine clinical assessments, yet in numerous instances, the etiological basis remains elusive. Subsequent diagnostic steps are not consensual and are challenging for physicians due to miscellaneous causes and non-specific symptoms. This study aimed to estimate the prevalence of Gaucher disease (GD) and other etiologies in patients presenting with unexplained splenomegaly (SM) after exclusion of first intention-diagnoses (e.g., portal hypertension, hematological malignancy, hemolytic anemia, and infection) based on basic physical examination, patient interview, and routine biological exams (e.g., full blood count, liver enzymes, and reticulocyte count). Additionally, the study aimed to describe the diagnostic tests performed and the most frequent associations observed. This French prospective, observational, multicenter, longitudinal SMS study enrolled 505 patients from September 2015 to April 2020, aged ≥ 15 years, referred to hematology or internal medicine departments, with a diagnostically confirmed SM (spleen length ≥ 13 cm). SM was defined as unexplained when routine clinical and biological tests were negative. Patients were followed up until an etiology was identified or up to 18 months after inclusion.
Results:
An etiology of SM was found in 223 (44.5%) of 501 patients with follow up. Patients with explained SM were older, had a larger spleen, and had altered biological parameters compared with patients with unexplained SM. There was a higher prevalence of non-malignant diseases than hematological malignancies (27.1% vs. 17.0%). Overall, lysosomal storage diseases (LSDs) were diagnosed in 10 patients (2.0%), including 4 patients with GD (0.8%).
Conclusions:
A list of potential predictive factors for the main diagnostic categories was identified that could optimize the diagnostic strategy for unexplained SM. This study provides new insights into exploring SM in the real world and proposes clinical and biological factors associated with specific etiologies.
Clinical Trial Registration:
NCT04430881.
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