Journal Article Review Epublish
PubMed: 40647707 DOI: 10.3390/diagnostics15131708
Challenges, Difficulties, and Delayed Diagnosis of Multiple Myeloma.
Diagnostics (Basel) 15(13)
Authors: Tugba Zorlu, Merve Apaydin Kayer, Nazik Okumus, Turgay Ulaş, Mehmet Sinan Dal, Fevzi Altuntas
Affiliations
- Department of Hematology & Apheresis Unit, Ankara Oncology Training and Research Hospital, University of Health Sciences, Ankara 06200, Türkiye.
Abstract
Background: Multiple myeloma (MM) is a heterogeneous plasma cell malignancy with non-specific symptoms and disease heterogeneity at clinical and biological levels. This non-specific set of symptoms, including bone pain, anemia, renal failure, hypercalcemia, and neuropathy, can mislead diagnosis as chronic or benign conditions, resulting in a delay in diagnosis. Timely identification is paramount to prevent organ damage and reduce morbidity. Methods: In this review, we present an overview of recent literature concerning the factors leading to the delayed diagnosis of MM and the impact of delayed diagnosis. This includes factors relevant to physicians and systems, diagnostic processes, primary healthcare services, and laboratory and imaging data access and interpretation. Other emerging technologies to diagnose NCIs include AI-based decision support systems and biomarker-focused strategies. Findings: Delayed diagnosis can lead to presentation at advanced disease stages associated with life-threatening complications and shorter progression-free survival. Patients are often seen by many physicians before they are referred to hematology. Understanding of clinical red flags for MM in primary care is inadequate. Our findings indicate that limited access to diagnostic tests, inconsistent follow-up of MGUS/SMM patients, and a lack of interdepartmental coordination delay the diagnostic process. Conclusions: Multimodal tools for early diagnosis of MM. Educational campaigns to raise awareness of the disease, algorithms dedicated to routine care and novel technologies, including AI and big data analytics, and new biomarkers may serve this purpose, as well as genomic approaches to the premalignant MGUS stage.
MeSH
Biomarkers, Delayed Diagnosis, Signs And Symptoms, Multiple Myeloma, Physicians, Diagnosis, Artificial Intelligence, Monoclonal Gammopathy Of Undetermined Significance