CT-defined Body Composition As a Prognostic Factor in Multiple Myeloma

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Abstract

Objectives Body composition assessment is comprised by skeletal muscle mass (SMM) and subcutaneous and visceral adipose tissue (SAT and VAT) and can be quantified by imaging. It can be predictive of several clinically outcomes in patients with hematological diseases. Our aim was to establish the effect of body composition parameters on overall survival (OS) and progression-free survival (PFS) in patients with multiple myeloma (MM). Materials and methods All patients with MM were retrospectively analyzed between 2009 and 2019. One hundred twenty-three patients were included into the analysis. Whole-body computed tomography (CT) was used to calculate SMM, VAT, and SAT. Results Overall, 22 patients (17.9%) of the patient sample died. Forty patients were sarcopenic (32.5%), 79 patients were visceral obese (64.2%), and 18 patients (14.6%) were sarcopenic obese. Parameter of body composition did not influence OS: sarcopenia, hazard ratio (HR) = 1.3 (95% CI 0.50-3.34), p = .59; visceral obesity, HR = 1.6 (95% CI 0.70-3.76), p = .26; sarcopenic obesity, HR = 2.3 (95% CI 0.90-5.63), p = 0.08. Patients with infectious complications showed higher VAT values. Conclusions CT-defined body composition parameters have no influence on survival in patients with MM undergoing autologous stem-cell therapy. These results corroborate previous smaller studies that body composition might have a limited role in this tumor entity. VAT may predict the occurrence of infectious complications.

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CT,body composition,multiple myeloma

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
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