Clinical Report: Body Composition Analysis in Newly Diagnosed Multiple Myeloma Patients
Overview
This study evaluated the prognostic impact of muscle and fat composition assessed by 18F-FDG PET/CT in 341 newly diagnosed multiple myeloma patients. Key findings include the prevalence of sarcopenia and the association of body composition parameters with progression-free and overall survival.
Background
Multiple myeloma (MM) outcomes vary widely due to disease and host factors. While cytogenetic prognostic markers are established, the role of patient-specific characteristics like body composition remains unclear. Sarcopenia, defined by low skeletal muscle mass, has been linked to adverse outcomes in various cancers but is understudied in MM. This study leverages PET/CT imaging at diagnosis to quantify muscle and fat compartments and assess their prognostic significance in MM.
Data Highlights
Characteristic
Value
Number of patients
341
Median age
65 years
Male sex
66%
R-ISS stage I
23%
R-ISS stage II
65%
R-ISS stage III
13%
Median BMI
28.1 kg/m2
Overweight (BMI 25-<30)
37%
Obese (BMI ≥30)
36%
Induction with novel agents
98%
Underwent transplantation
54%
Median follow-up
5.7 years (95% CI: 5.4–6.3)
Median progression-free survival (PFS)
37.9 months (95% CI: 31.0–55.0)
Median overall survival (OS)
7.7 years (95% CI: 6.0–not fully reported)
Key Findings
Body composition was assessed using a single-slice CT image at L3 level from PET/CT scans.
Sarcopenia was defined using sex-specific skeletal muscle index (SMI) cutoffs from literature and population medians.
37% of patients were overweight and 36% were obese by BMI classification.
Muscle and adipose tissue areas and indices were calculated and stratified by sex-specific medians and tertiles.
Median progression-free survival was 37.9 months and median overall survival was 7.7 years in this cohort.
Clinical Implications
Assessment of body composition via PET/CT at diagnosis provides valuable prognostic information in multiple myeloma. Identification of sarcopenia and adipose tissue distribution may help stratify patients' risk and guide therapeutic decisions. Incorporating muscle and fat analysis could complement existing prognostic models to optimize patient management.
Conclusion
This study demonstrates the feasibility and potential prognostic relevance of body composition analysis in newly diagnosed multiple myeloma patients using PET/CT imaging. Further research is warranted to validate these findings and integrate them into clinical practice.
References
Multiple Myeloma Prognostic Factors and Body Composition Studies (2010-2022)
by Nadine H. Abdallah, Hiroki Nagayama, Naoki Takahashi, Wilson Gonsalves, Amie Fonder, Angela Dispenzieri, David Dingli, Francis K. Buadi, Martha Q. Lacy, Miriam Hobbs, Morie A. Gertz, Moritz Binder, Prashant Kapoor, Rahma Warsame, Suzanne R. Hayman, Taxiarchis Kourelis, Yi L. Hwa, Yi Lin, Robert A. Kyle, S. Vincent Rajkumar, Stephen M. Broski, Shaji K. Kumar
