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INTRODUCTION Despite successful therapy, acromegalic patients have reduced health-related quality of life (HRQoL) compared to healthy controls. Finding predictors of poor HRQoL can be crucial to improving these patients' global health state.  Aim: The primary objective of the study was to find out predictors of HRQoL. Secondary objectives were: (I) to determine correlations with AcroQoL subscales, and (II) to identify predictors for subscales. MATERIALS AND METHODS In this cross-sectional study conducted in 2019 at the Messina Policlinic Hospital, 45 acromegalic patients were assessed at the Physical and Rehabilitative Medicine Ambulatory. During routine outpatient clinic attendances, the following questionnaires were administered: Acromegaly Quality of Life Questionnaire (AcroQoL), Patient-Assessed Acromegaly Symptom Questionnaire (PASQ), and Western Ontario and McMaster Universities Arthritis Index (WOMAC). We furthermore included the following variables obtained by medical record review: age, BMI, disease duration, previous surgery (Yes/No), previous radiotherapy (Yes/No), use of GH lowering medications (Yes/No), hypertension (Yes/No), diabetes mellitus (Yes/No), and biochemical control of the disease (Yes/No): immunoradiometric assays were employed to serum GH and IGF-1 measurements to identify biochemical control of the disease. Correlation between outcome measures and AcroQoL has been performed. Pearson's r was calculated for continuous data following normal distribution (AcroQoL, PASQ, AcroQoL-B, AcroQoL-R, WOMAC-P), while Spearman's rank order correlation was calculated for non-normally distributed data (WOMAC, WOMAC-F, WOMAC-S, AcroQoL-P) and point-biserial correlation for binary variables (biochemically controlled disease, use of GH lowering medications, radiotherapy, surgery).  The same correlation analysis was performed for the AcroQoL subscales. Multiple linear regression with backwards, stepwise analysis was used to assess the influence on AcroQoL of correlated variables. RESULTS AcroQoL was strongly negatively correlated with PASQ (r=-0.700, p<0.001) and negatively correlated with WOMAC [rs (43)=-0.530, p<0.001] and among WOMAC subscales with WOMAC-Physical fitness [rs (43)=-0.518, p<0.001] WOMAC-Pain [r (43)=-0.428, p=0.003], WOMAC-Stiffness [rs (43)=-0.393, p=0.007], and radiotherapy [r (43) =-0.314, p=0.035]. After univariate stepwise regression, PASQ was the strongest independent predictor of AcroQoL, with R2 of 0.392 [F (1,43)=27.695, p<0.001]. CONCLUSIONS This study shows that the severity of painful symptoms is the most important predictor of HRQoL in patients with acromegaly; at the same time, acromegalic arthropathy leads to pain and to a variable amount of functional impairment, exerting great impact on the patient's perception of his health status. Measure of the progression of arthropathy and symptomatic management could lead to a great HRQoL benefit.