Platelet-to-Neutrophil ratio as a predictor of risk of complications in sickle cell disease: a valuable insight for resource-limited settings

Sickle cell disease (SCD) presents significant clinical challenges, particularly in resource-limited settings where early identification of high-risk patients remains difficult, necessitating the use of simple, cost-effective biomarkers to improve risk stratification and guide timely interventions. This study investigates the potential of platelet-to-neutrophil ratio (PNR) to serve as a predictor for risk of specific SCD complications in a population of Nigerian patients. This hospital-based cross-sectional analytical study was conducted over 7 months and included a total of 73 adult patients with haemoglobin SS genotype in a steady state. Data on socio-demographics, medical history, clinical characteristics, and laboratory parameters, including platelet-to-neutrophil ratio (PNR) were obtained. Data analysis was performed using the Statistical Package for the Social Sciences (SPSS) version 25. Comparative statistical analyses, binary logistic regression, and receiver operating characteristic (ROC) curve evaluations were performed to determine the predictive value of PNR for risk of SCD complications. Patients with avascular necrosis (AVN) had significantly lower median PNR values compared to those without the condition (151.0 IQR: 311.2 vs. 77.5 IQR: 61.0, p = 0.004). Multivariate logistic regression analysis identified PNR as an independent predictor of AVN (p = 0.034, OR = 1.003, 95% CI: 1.000-1.006), with an ROC-derived optimal cutoff of 96.6 yielding a sensitivity of 69.6% and specificity of 76.5% (AUC = 0.733, p = 0.004). This study reveals that RNR demonstrates reasonable potential as a predictor of AVN in Nigerian SCD patients and could serve as an easily accessible biomarker for SCD risk stratification, particularly in resource-limited settings. Further studies are needed for validation of its clinical utility and possible integration into SCD management protocols.

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Publication Details

Journal
Annals of Hematology
Published
2025-05-01
DOI
https://doi.org/10.1007/s00277-025-06419-6
Primary Topic
Hemoglobinopathies and Related Disorders
Type
article
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article

Platelet-to-Neutrophil ratio as a predictor of risk of complications in sickle cell disease: a valuable insight for resource-limited settings

Chilota Chibuife Efobi, Bruno Basil, Onyinye Ezinne Eze, Nnanna Ukpai
Annals of Hematology
Hemoglobinopathies and Related Disorders
article

Platelet-to-Neutrophil ratio as a predictor of risk of complications in sickle cell disease: a valuable insight for resource-limited settings

Chilota Chibuife Efobi, Bruno Basil, Onyinye Ezinne Eze, Nnanna Ukpai
article en

Abstract

Sickle cell disease (SCD) presents significant clinical challenges, particularly in resource-limited settings where early identification of high-risk patients remains difficult, necessitating the use of simple, cost-effective biomarkers to improve risk stratification and guide timely interventions. This study investigates the potential of platelet-to-neutrophil ratio (PNR) to serve as a predictor for risk of specific SCD complications in a population of Nigerian patients. This hospital-based cross-sectional analytical study was conducted over 7 months and included a total of 73 adult patients with haemoglobin SS genotype in a steady state. Data on socio-demographics, medical history, clinical characteristics, and laboratory parameters, including platelet-to-neutrophil ratio (PNR) were obtained. Data analysis was performed using the Statistical Package for the Social Sciences (SPSS) version 25. Comparative statistical analyses, binary logistic regression, and receiver operating characteristic (ROC) curve evaluations were performed to determine the predictive value of PNR for risk of SCD complications. Patients with avascular necrosis (AVN) had significantly lower median PNR values compared to those without the condition (151.0 IQR: 311.2 vs. 77.5 IQR: 61.0, p = 0.004). Multivariate logistic regression analysis identified PNR as an independent predictor of AVN (p = 0.034, OR = 1.003, 95% CI: 1.000-1.006), with an ROC-derived optimal cutoff of 96.6 yielding a sensitivity of 69.6% and specificity of 76.5% (AUC = 0.733, p = 0.004). This study reveals that RNR demonstrates reasonable potential as a predictor of AVN in Nigerian SCD patients and could serve as an easily accessible biomarker for SCD risk stratification, particularly in resource-limited settings. Further studies are needed for validation of its clinical utility and possible integration into SCD management protocols.

Annals of HematologyVol. 104(5)
Enugu State University of Science and Technology (NG), Nnamdi Azikiwe University (NG), Pro Health International (NG), Nnamdi Azikiwe University Teaching Hospital (NG)
Openalex Percentile: Top 83%
Hemoglobinopathies and Related Disorders
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