Hematological impact and risk stratification in beta-thalassemia intermedia: A multivariate and cluster analysis approach to tailored management

BACKGROUND: Intermediate beta-thalassemia has different clinical observations due to its phenotypic differences, which may complicate how it has been managed. Understanding the biochemical characteristics can assist in pharmacotherapeutic melee strategy. OBJECTIVE: This study aims to establish a correlation between demographic variables and biochemical indicators in intermediate thalassemia patients. PATIENTS AND METHODS: This study used 200 beta-thalassemia intermedia patients’ information by conducting a survey. In addition, blood levels of calcium, iron, magnesium, phosphorus, copper, and zinc were measured. Age and gender, and their interactions with these biochemical markers were investigated using multivariate regression analysis. Moreover, for grouping patients according to their biochemical parameters, K-means clustering was conducted. RESULTS: The obtained data showed that gender provided the strongest effect on zinc levels based on a P = 0.0014, thus establishing that males displayed lower mean zinc levels than females. The zinc gender coefficient value (−17.691) proved that males experienced a substantial reduction in zinc levels compared to females. The zinc model fit demonstrated an R-squared value of 0.366, while its adjusted R-squared amounted to 0.220 with an F-statistic probability of 0.048. These results indicated suitable model compatibility compared to other markers. The patient samples were distributed into three distinct clusters, which helped evaluate their biochemical compositions for determining risk elements and required treatment methods. The intense chelation requirement exists for Cluster 1 because it has the highest iron content levels, even though Cluster 2 focuses on zinc supplementation due to its lowest zinc concentration. CONCLUSION: This study examined the biochemical characteristics of patients with intermediate thalassemia, revealing significant disease heterogeneity and gender-specific differences, particularly lower zinc levels in males. Multivariate regression and cluster analyses identified distinct biochemical patterns and patient subgroups, supporting the need for personalized, gender-sensitive treatment approaches. These insights suggest that individualized therapies tailored to each patient’s metabolic profile can improve treatment outcomes and quality of life.