Utility of hematological parameters to predict tuberculosis disease among PLHIV: A retrospective cohort study

Objectives Tuberculosis (TB) remains a significant health challenge for people living with human immunodeficiency virus (PLHIV), highlighting the need for improved diagnostic and monitoring strategies. Hematological parameters, such as the monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), and anemia status, have emerged as potential biomarkers for TB disease in this vulnerable population. This present study aimed to assess the utility of hematological parameters in predicting TB disease among PLHIV attending an antiretroviral therapy (ART) center. Materials and Methods This retrospective cohort study was conducted in an ART center in a tertiary care hospital in Gujarat. Data from 813 PLHIV were analyzed, including hematological profiles, TB status, and demographic/clinical characteristics. TB was defined as either bacteriologically confirmed (through smear microscopy, GeneXpert Mycobacterium tuberculosis /rifampicin, or culture) or clinically diagnosed pulmonary TB based on suggestive symptoms and radiological findings. Statistical analysis Logistic regression models were developed to evaluate the association between hematological parameters and TB disease, adjusted for age, gender, baseline CD4 count, World Health Organization clinical stage, cotrimoxazole preventive therapy, isoniazid preventive therapy, and ART regimen. Results The proportion of TB-positive cases was substantially higher in the greater MLR group (49.4% vs. 10.3%). The logistic regression analysis revealed a strong association between a higher MLR and increased odds of having TB disease (adjusted odds ratio = 8.13, 95% confidence interval: 5.54–11.93, P < 0.001). Individuals with mild, moderate, or severe anemia had significantly higher odds of TB disease compared to those without anemia. The model incorporating MLR and anemia status demonstrated superior performance (area under the receiver operating characteristic curve [AUC] = 0.816, accuracy = 0.801) compared to the model with NLR and anemia status (AUC = 0.734, accuracy = 0.710), potentially reflecting the crucial role of monocytes in TB pathogenesis and granuloma formation in the context of human immunodeficiency virus coinfection. Conclusions This study highlights the potential utility of routinely available hematological parameters, particularly MLR and anemia status, as adjunctive tools for predicting TB disease in PLHIV. The integration of these cost-effective markers into existing diagnostic algorithms could enhance early detection, risk stratification, and targeted interventions.