Evaluation of the role of inflammation in fibromyalgia through haematological indices: A retrospective study

Background & objectives Fibromyalgia is a chronic pain disorder possibly linked to low-grade inflammation. Haematological indices derived from routine blood tests have emerged as potential markers for evaluating inflammatory status in such conditions. This study aimed to investigate the relationship between fibromyalgia syndrome (FMS) and inflammation, using haematological indices derived from routine complete blood count data. Furthermore, whether these markers can be used to diagnose FMS, was also studied. Methods This was a retrospective hospital-based study on data retrieved from medical records. A total of 294 individuals with FMS and 277 control individuals were included in this study. The routine hemogram data of the FMS and control groups were analysed through a retrospective chart review from hospital records. Mean platelet volume (MPV) and platelet distribution width (PDW) were recorded, and inflammatory markers such as platelet/lymphocyte ratio (PLR), neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), systemic immune-inflammation index (SII), and systemic immune response index (SIRI) were calculated. These markers were statistically compared between the FMS and control groups. Results NLR, PLR, MLR, SII, and SIRI were found to be statistically higher in the FMS group compared to the control group (P<0.01). There was no statistically significant difference between the groups in terms of MPV and PDW values (P>0.05). When evaluating the areas under the curve in the Receiver Operating Characteristic (ROC) analysis, the results for PRL, MLR, NLR, SII, and SIRI calculations were found to be statistically significant (P<0.05). Interpretation & conclusions Fibromyalgia is associated with inflammation. NLR, MLR, PLR, SII, and SIRI are simple and inexpensive biomarkers that indicate this relationship. These markers, which have moderate sensitivity and specificity, are insufficient for independent diagnosis and can be used in addition to existing diagnostic criteria or in monitoring treatment.