Prevalence, Outcomes and Impact of Disease-Related Complications in the Survival of Multiple Myeloma Patients.
Wachiralak TothongAdisak TantiworawitLalita NorasetthadaChatree Chai-AdisaksophaTeerachat PunnachetNonthakorn HantrakunPokpong PiriyakhuntornThanawat RattanathammetheeSasinee HantrakoolEkarat RattaritamrongPublished in: Hematology reports (2024)
There are limited data regarding the impact of disease-related complications on the survival of multiple myeloma (MM) patients. The primary objective of this study was to determine the prevalence of disease-related complications, including hypercalcemia, renal insufficiency, anemia, and bone lytic lesions in MM patients. The secondary objectives were to determine clinical characteristics, treatment outcomes, and the association of disease-related complications and mortality. A retrospective chart review of MM patients from November 2014 to December 2019 was conducted. A total of 200 MM patients were enrolled. The median age at diagnosis was 63 years. The bone lytic lesion was the most common disease-related complication found in 85% during first-line therapy, followed by anemia (71.5%), renal insufficiency (28.5%), and hypercalcemia (20%). While anemia was the most common complication during the second (51.2%) and third-line therapy (72%). The development of skeletal-related events (SREs) after treatment is a disease-related complication that is associated with decreased overall survival (HR 4.030, 95% CI 1.97-8.24, p < 0.001). The most common disease-related complication of MM at initial diagnosis is bone lytic lesions, whereas anemia is more common with subsequent relapses. The presence of SRE after treatment is associated with the increased mortality of MM patients.
Keyphrases
- end stage renal disease
- chronic kidney disease
- ejection fraction
- newly diagnosed
- prognostic factors
- peritoneal dialysis
- adipose tissue
- type diabetes
- multiple myeloma
- machine learning
- weight loss
- coronary artery disease
- bone marrow
- cell therapy
- body composition
- electronic health record
- artificial intelligence
- patient reported
- skeletal muscle