Zijlstra H, Wolterbeek N, Drost RW, Koene HR, van der Woude HJ, Terpstra WE, Delawi D, Kempen DHR. Identifying predictive factors for vertebral collapse fractures in multiple myeloma patients.
Spine J 2020;
20:1832-1839. [PMID:
32673729 DOI:
10.1016/j.spinee.2020.07.004]
[Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 05/26/2020] [Accepted: 07/08/2020] [Indexed: 02/03/2023]
Abstract
BACKGROUND CONTEXT
Vertebral compression fractures (VCFs) are a common complication for patients with multiple myeloma. These fractures are associated with significant morbidity and mortality due to severe back pain, spinal instability, increased risk of new fractures, neurologic dysfunction, and other physical symptoms.
PURPOSE
To identify risk factors associated with the development of VCFs which may help to predict them in future patients.
STUDY DESIGN
A retrospective multicenter cohort study.
PATIENT SAMPLE
Patients with multiple myeloma diagnosed between 2012 and 2018 and appropriate baseline- and follow-up imaging studies (>6 months after diagnosis) were included.
OUTCOME MEASURES
Individual odds ratios for each of the fifteen potential risk factors including patient factors and radiographical characteristics.
METHODS
Relevant clinical baseline data were extracted from the patient charts. Computed tomography (CT) scans were used to score all radiographic variables. VCFs were graded following the Genant grading system. General Linear Mixed Models were used to analyze risk factors associated with vertebral fractures.
RESULTS
A total of 143 patients with 1,605 eligible vertebrae were included in the study with a mean follow-up time of 25 months. Mean age at diagnosis was 65 years and 39% were female. Among 1,605 vertebrae, there were 192 (12%) VCFs (Genant grade 1 or higher) at the time of diagnosis and 111 (7%) occurred during follow-up. In a General Linear Mixed Model, significant predictors were gender (odds ratio [OR]=1.5), International Staging System stage 2 and 3 (OR=3.6 and OR=4.1 respectively), and back pain (OR=2.7). Furthermore, lower Hounsfield Unit score, lytic lesions and abnormal alignment were risk factors for (the development of) VCFs.
CONCLUSIONS
This study investigated both patient characteristics and vertebra-specific risk factors for VFCs in multiple myeloma patients. The factors found in this study might be useful for identifying patients at higher risk of VFCs to help clinical management to prevent vertebral collapse and the development of spinal deformities.
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