Designing a Human T-Lymphotropic Virus Type 1 (HTLV-I) Diagnostic Model using the Complete Blood Count

Area of Science:

• Medical Science
• Epidemiology
• Virology

Background:

• Human T-Lymphotropic Virus Type 1 (HTLV-I) infection is endemic in certain Iranian regions.
• Most HTLV-I infections are asymptomatic, but some can lead to serious neurological disorders and malignancies.
• Timely detection and intervention are crucial for managing HTLV-I and improving patient prognosis.

Purpose of the Study:

• To design and implement a screening model for early detection of HTLV-I infection.
• To identify individuals infected with HTLV-I, particularly in endemic areas.
• To facilitate timely referral for further testing and management, thereby improving health outcomes.

Main Methods:

• The study analyzed complete blood count (CBC-diff) data from 599 healthy individuals and patients with leukemia or HTLV-I.
• A classification and regression tree (CHAID) model was developed.
• The final model utilized white blood cell count (WBC), platelet count, and eosinophil percentage as key parameters.

Main Results:

• The developed screening model achieved an accuracy of 91%.
• The model effectively identifies potential HTLV-I carriers among asymptomatic individuals and those with non-specific symptoms in endemic regions.
• Application of the model enables targeted referral for confirmatory diagnostic tests.

Conclusions:

• Early identification of HTLV-I infected individuals is possible through the validated screening model.
• Improved prognosis and enhanced public health status, especially in endemic areas, can be achieved by timely detection.
• The model offers a valuable tool for managing HTLV-I prevalence and its associated complications.