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

Materials & Methods

Our study obtained data from 294 individuals aged 18-65 yr who applied to the Physical Medicine and Rehabilitation Clinic of Ankara Training and Research Hospital between March 2022 and March 2024 through a retrospective chart review of hospital records. The control group comprised 277 individuals without a history of inflammatory disease or FMS who applied to the physical therapy outpatient clinic with various local and mechanical complaints.

Inclusion criteria were defined as being in the 18-65 yr age range and having been diagnosed with FMS according to the 2016 American College of Rheumatology (ACR) criteria. Exclusion criteria included a history of diabetes mellitus, inflammatory rheumatic diseases, malignancy, cardiovascular diseases, liver disease, chronic kidney disease, steroid use, non-steroidal anti-inflammatory drug (NSAID) use, chronic alcohol use, and trauma history. The control group consisted of individuals without a history of inflammatory disease or FMS and no history of medication use.

Results

This study included a total of 294 cases (patients diagnosed with FMS) and 277 controls (individuals without a history of FMS or inflammatory disease who presented with local mechanical complaints). The average age of the FMS group was found to be 48.07±9 yr, while the control group was 45.55±11.2 yr (P<0.05). In the FMS group, there were 280 (95.2%) women and 14 (4.8%) men (P<0.01), whereas in the control group, there were 247 (89.2%) women and 30 (10.8%) men (P<0.01).

When comparing the data of the FMS and control groups, it was found that neutrophil and monocyte counts were significantly higher in the FMS group (P<0.05), while erythrocyte count was lower (P<0.05). Platelet count (P<0.01) and CRP (P<0.01) were significantly higher in the FMS group, whereas haemoglobin and haematocrit levels were lower (P<0.05). NLR, PLR, MLR, SII, and SIRI were significantly 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 lymphocyte count, MPV, PDW, leukocyte count, B12, or NHL scores (Mann-Whitney U test; P<0.05; P<0.01; Table I).

In fibromyalgia, according to the results of the ROC analysis for haematological markers calculated from peripheral blood results, the sensitivity was 56.5 per cent, and specificity was 56.3 per cent at a cutoff value of 118.84 for PLR (P<0.05). MLR’s sensitivity was 54.1 per cent, and specificity was 54.2 per cent at a cutoff value of 0.22 (P<0.001). For the NLR parameter, the sensitivity was 54.1 per cent, and the specificity was 54.2 per cent at a cutoff value of 1.69 (P<0.05). For NHL, the sensitivity was 50.0 per cent, and the specificity was 50.5 per cent at a cutoff value of 0.69 (P>0.05). For SII, the sensitivity was 54.8 per cent, and the specificity was 54.5 per cent at a cutoff value of 0.60 (P>0.001). For SIRI, the sensitivity was 53.7 per cent, and the specificity was 53.8 per cent at a cutoff value of 0.91 (P>0.001). The diagnostic value of other parameters, except NHL, for inflammation in fibromyalgia was statistically significant (Table II).

When evaluating the areas under the curve in the ROC analysis, the results obtained for PLR, MLR, NLR, SII, and SIRI calculations were found to be statistically significant (0.002, 0.0001, 0.005, 0.0001, and 0.0001, respectively). However, the AUC values of all tests were below 0.6, indicating that these have limited predictive power in the diagnosis of fibromyalgia. These findings highlight the limited effectiveness of risk factors used in the diagnosis of fibromyalgia and emphasize the need for further research (Figure).

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Figure.

Evaluation of haematological markers in predicting inflammation in study participants with fibromyalgia through ROC analysis.

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The P values for PLR, MLR, NLR, SII, and SIRI are statistically significant, suggesting that these tests may be associated with fibromyalgia. However, the P value for NHL is 0.333, indicating that this test does not show a significant association.

Discussion

In this study, NLR, PLR, MLR, SII, and SIRI were significantly higher in the FMS group. These results suggest a relationship between FMS and inflammation. The sensitivity and specificity of these biomarkers are limited, and in this context, they may be used as complementary diagnostic parameters or clinical markers for evaluating therapeutic response monitoring.

The aetiology of fibromyalgia is still not fully understood. Various pathogenetic hypotheses exist, focusing on multifactorial pathogenesis based on genetic predisposition¹⁷. Central sensitisation is a well-known phenomenon in the pathogenesis of FMS. It is defined as a dysfunction of neuro-circuits involving the perception, transmission, and processing of afferent nociceptive stimuli, following the widespread occurrence of pain at the locomotor system level. There is a problem with pain processing in the brain¹⁸. In fibromyalgia, disruptions in monoaminergic signalling contribute to elevated levels of excitatory neurotransmitters such as glutamate and substance P along the descending antinociceptive pathways of the spinal cord, while serotonin and norepinephrine levels are reduced. Moreover, alterations in dopamine regulation and the endogenous opioid system further characterize the central mechanisms underlying the condition¹⁹. Increased peripheral stimuli lead to increased tonic input in the spinal cord, causing central sensitisation. Neuroendocrine, psychosocial, and environmental factors, as well as oxidative stress, are other contributors to the development of FMS²⁰.

Recently the pathogenesis of fibromyalgia has also been associated with inflammatory and immune mechanisms. Studies investigating the role of pro-inflammatory cytokines in patients with FMS focus mainly on IL-6 and IL-8, reporting them as the most consistent inflammatory mediators in the pathogenesis of FMS²¹. However, the use of these cytokines in clinical diagnoses is challenging. Therefore, simpler inflammatory haematological biomarkers derived from routine haemogram data, such as NLR, PLR, MLR, SII, and SIRI, are increasingly being considered. These markers are based on changes in neutrophil, platelet, and monocyte counts and a decrease in lymphocyte count during inflammation. Particularly, NLR is reported to have diagnostic and prognostic value in various inflammatory diseases and is associated with systemic inflammation^22,23.

MPV, NLR, and PLR have been identified as prognostic markers for assessing disease activity in rheumatologic conditions like SLE and RA. SII and SIRI have recently been added to these^24,25. While there are studies supporting the importance of these markers in the diagnosis and monitoring of FMS, some have been inconclusive. In a study by Ilgun et al²⁶ involving 70 FMS patients and 50 healthy controls, PLR was found to be significantly higher in the patient group, while no difference was found between the two groups in terms of NLR. Xiao et al²⁷, in a study on 48 FMS patients and 36 controls, found elevated CRP and NLR levels in FMS. However, these studies have relatively small control groups. Other studies have also found that PLR and NLR are significantly higher in FMS patients compared to healthy individuals^28,29.

The present study includes many participants in both case and control groups (294 FMS and 277 controls) and aims to provide more reliable results. Due to conflicting results related to NLR, PLR, and MLR in FMS, we also evaluated two newer inflammatory markers: SII and SIRI. Unlike NLR and PLR, SII includes the ratio of three blood cell types and more accurately reflects systemic immune and inflammatory balance³⁰. SII has been reported as a valuable biomarker in inflammatory rheumatic diseases like RA and infectious diseases like tonsillitis^11,31. SIRI has surpassed NLR, PLR, and MLR in prognostic prediction³². In our study, both SII and SIRI were found to be significantly higher in the FMS group compared to the control group, supporting the FMS-inflammation relationship. However, according to our results, the sensitivity and specificity of these tests are moderate. Therefore, we believe that these are not sufficient to be used alone in the diagnosis of FMS.

MPV and PDW are platelet markers widely used in clinical practice and reflect platelet activation and inflammation^33,34. In a study by Jayakrishnan et al³⁵ involving 266 FMS patients, MPV was reported to be associated with pain severity in FMS and could serve as a cost-effective biomarker for symptom severity. During inflammation, increased IL-6 results in increased platelet activation. Increased platelet production in the bone marrow and their release into circulation result in increased MPV. Larger platelets (increased MPV) are enzymatically more active than smaller platelets, creating a tendency towards increased thrombosis and inflammation alongside more thromboxane A2 and inflammatory cytokines. As platelet production and release into the bloodstream increase in the bone marrow, PDW also increases as different-sized platelets in circulation increase. PDW has been defined as a more specific marker of platelet activation³². Despite these theoretical insights supporting the relationship between inflammation and MPV and PDW, study results regarding the inflammation-MPV and PDW relationship are inconsistent. Some studies have found PDW to be significant in inflammatory diseases³⁶, while others have reported it as a negative acute phase reactant, either low or high³⁷.

Similarly, studies on FMS have reported both low⁷ and high PDW levels³⁸. This can be explained by potential heterogeneity in haematological procedures applied for MPV and PDW analysis, which may affect laboratory results and the consistency of data. MPV and PDW levels can change over time, leading to different results depending on the time between blood collection and analysis. Additionally, the type of anticoagulant used in blood tubes can affect platelet indices^39,40. It has been reported that MPV values are not affected when measured within an hour after blood collection, and since blood samples in our centre are processed within this timeframe, we ensure the reliability of our measurements.

Although the platelet count in the FMS group of our study was higher compared to the control group, there was no significant difference in MPV and PDW, unlike the results of Jayakrishnan et al³⁵. Considering the conflicting results in the literature, it can be deduced that MPV and PDW are not reliable markers for assessing inflammation in FMS.

The results obtained from the present study showed that inflammatory markers such as NLR, PLR, MLR, SII, and SIRI are increased in FMS patients. This supports the FMS-inflammation relationship. However, we suggest that these indices, with moderate sensitivity and specificity, can be used as complementary diagnostic markers or biomarkers for treatment monitoring alongside other diagnostic criteria in FMS. In the future, new randomised controlled trials investigating the effects of applied treatments on haematological indices in FMS patients are believed to be enlightening on this issue.

Overall, the findings from this study suggest a relationship between inflammation and FMS. NLR, PLR, MLR, SII, and SIRI are simple and inexpensive biomarkers supporting this relationship. Although not sufficient alone for diagnosis, these can be used as complementary diagnostic biomarkers in FMS.