Although fibromyalgia (FM) is better understood and recognized today than it was 25 years ago when FM classification criteria (ie, history of widespread pain, and pain on palpation of ≥11 of 18 specific sites) were first published, researchers still have an incomplete understanding of FM's mechanisms and predictors.1 Because of this, prevention of FM is impossible. The few prospective, population-based studies on the incidence and predictors of FM to date have touched on the relationship between higher age and multiple pain sites at baseline and risk factors for widespread pain; high body mass index (BMI) and the risk for FM; sleep disturbance and increased sensitivity to noxious stimuli and with chronic pain; and poor sleep and FM or widespread pain.
Using the Finnish Twin Cohort, as well as data from assessments conducted 9 to 15 years prior, Ritva A. Markkula, PhD, Anaesthesiology, Intensive Care and Pain Medicine, University of Helsinki and Helsinki University Hospital, Finland, and colleagues conducted a study to evaluate several potential predictors of FM, as well as possible genetic confounds. They found that regional pain, frequent headaches, persistent back or neck pain, sleep issues, and being overweight are predictors for having symptoms that are consistent with FM.
Using results from a previous study of 3 questionnaires that were submitted to a cohort of twin pairs born before 1958 during a 15-year time period, Dr Markkula and colleagues limited the study participants to those born between 1930 and 1957, and separated them into 3 latent classes (LCs) based on their answers to FM symptom questions (ie, LC1, having no or few symptoms; LC2, having some symptoms; and LC3, having many symptoms). Patients with possible symptoms of FM, and who frequently used analgesics at baseline, were excluded; a total of 8343 patients were included in the final sample.
In their assessments, the study authors used questions pertaining to FM symptoms and FM-associated symptoms in accordance with the American College of Rheumatology 1990 classification criteria. The investigators also used answers from 49 clinically diagnosed patients with FM as a validation data set.
To analyze the potential predictors for FM symptoms among individual participants, Dr Markkula and colleagues used a multinomial logistic regression analysis, with the 3 latent symptom classes as the categories of the dependent variable. LC1 served as the reference category. Back, neck, and shoulder pain; headaches; migraines; sleeping problems; physical passivity or activity; BMI; and smoking were analyzed as potential predictors.
Associations between persistence or recurrence of regional pain and future symptom class were measured through reanalysis of a subsample of patients who had replied to the 2 earlier questionnaires. The possible effect of genetic or familial environmental factors on the relationship between predictors and FM symptoms was also analyzed, using a conditional logistic regression analysis, through identification of twins with conflicting LC statuses.
In the final multivariate regression model, regional pain, sleeping problems, and being overweight were all determined to be predictors for being classified as LC3. Frequent headache was the strongest nongenetic predictor, followed by persistent back pain and persistent neck pain. The study authors found headaches, back and neck pain, sleeping problems, and high BMI to be potential predictors of FM symptoms. They also reported that high BMI and sleeping problems were influenced by familial factors, and that there was a relationship between the persistence and intensity of regional pain and increased FM symptom risk.
"Heritability plays an important role in FM symptoms, but also in many of the predictors," Dr Markkula and colleagues concluded. "Therefore that headache and regional pain are predictors independent of family background is an important finding. Further studies must evaluate possibilities of preventing FM by treatment and management of such predictors."
- Markkula RA, Kalso EA, Kaprio JA. Predictors of fibromyalgia: a population-based twin cohort study. BMC Musculoskelet Disord. 2016;17:29.