How Does Age at Diagnosis Influence Multiple Myeloma Survival? Empirical Evidence

Background/Objectives: Disparities in multiple myeloma (MM) survival occur based on factors like genetics, age, race, income level, and access to healthcare. The impact of age at diagnosis on MM survival is not fully understood and continues to draw research attention. This study explores the link between age at diagnosis and survival outcomes using data from the University of Arkansas Medical Sciences Myeloma Center Database (MMDB). Methods: Kaplan-Meier curves and Cox models were used to analyze the data. The log-transformed age variable strongly predicted survival. Results: The analysis found survival curves showing that patients in lower age brackets tend to have better survival profiles. Thus, for example, those in the oldest category (>70) showed the steepest decline, while the youngest age category (under 40) had better survival. Spline functions identified a non-linear relationship between age and survival. The likelihood ratio test, Wald test, and log-rank score test confirmed that the overall model was statistically significant, indicating that the spline-based approach effectively captured the relationship between age and survival. Further analysis using a stratified Cox model by age group showed significant risk differences. Patients aged 50-59, 60-69, and over 70 all had higher risks of death compared to younger patients, with those over 70 having a 3.3 times greater risk. Conclusions: In conclusion, the study confirmed that age at diagnosis has a significant association with survival outcomes for MM patients.