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Competing risks analysis for neutrophil to lymphocyte ratio as a predictor of diabetic retinopathy incidence in the Scottish population. | LitMetric

AI Article Synopsis

  • Diabetic retinopathy (DR) is a severe eye complication linked to diabetes, driven by systemic inflammation and oxidative stress; the neutrophil-lymphocyte ratio (NLR) serves as a potential indicator of immune activity and may predict DR incidence.
  • A study analyzed data from over 23,000 individuals with type 2 diabetes to assess the impact of NLR on developing DR, using advanced statistical models to account for factors like mortality.
  • The findings revealed that a higher NLR (optimal cut-off at 3.04) correlated with increased risk of DR, with 35.8% of subjects developing the condition over 10 years, indicating NLR's significance as a prognostic biomarker in diabetes-related eye health

Article Abstract

Background: Diabetic retinopathy (DR) is a major sight-threatening microvascular complication in individuals with diabetes. Systemic inflammation combined with oxidative stress is thought to capture most of the complexities involved in the pathology of diabetic retinopathy. A high level of neutrophil-lymphocyte ratio (NLR) is an indicator of abnormal immune system activity. Current estimates of the association of NLR with diabetes and its complications are almost entirely derived from cross-sectional studies, suggesting that the nature of the reported association may be more diagnostic than prognostic. Therefore, in the present study, we examined the utility of NLR as a biomarker to predict the incidence of DR in the Scottish population.

Methods: The incidence of DR was defined as the time to the first diagnosis of R1 or above grade in the Scottish retinopathy grading scheme from type 2 diabetes diagnosis. The effect of NLR and its interactions were explored using a competing risks survival model adjusting for other risk factors and accounting for deaths. The Fine and Gray subdistribution hazard model (FGR) was used to predict the effect of NLR on the incidence of DR.

Results: We analysed data from 23,531 individuals with complete covariate information. At 10 years, 8416 (35.8%) had developed DR and 2989 (12.7%) were lost to competing events (death) without developing DR and 12,126 individuals did not have DR. The median (interquartile range) level of NLR was 2.04 (1.5 to 2.7). The optimal NLR cut-off value to predict retinopathy incidence was 3.04. After accounting for competing risks at 10 years, the cumulative incidence of DR and deaths without DR were 50.7% and 21.9%, respectively. NLR was associated with incident DR in both Cause-specific hazard (CSH = 1.63; 95% CI: 1.28-2.07) and FGR models the subdistribution hazard (sHR = 2.24; 95% CI: 1.70-2.94). Both age and HbA were found to modulate the association between NLR and the risk of DR.

Conclusions: The current study suggests that NLR has a promising potential to predict DR incidence in the Scottish population, especially in individuals less than 65 years and in those with well-controlled glycaemic status.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10413718PMC
http://dx.doi.org/10.1186/s12916-023-02976-7DOI Listing

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