ABSTRACT: BACKGROUND: F-FDG PET/CT (PET) is useful in assessing inflammatory activity in sarcoidosis. However, no appropriate indications are available. The aim of this study was to develop a prediction rule that can be used to identify symptomatic sarcoidosis patients who have a high probability of PET-positivity. METHODS: We retrospectively analyzed a cohort of sarcoidosis patients with non organ specific persistent disabling symptoms (n[THIN SPACE]=[THIN SPACE]95). Results of soluble interleukin-2 receptor (sIL-2R) assessment and high-resolution computed tomography (HRCT) were included in the predefined model. HRCT scans were classified using a semi-quantitative scoring system and PET findings as positive or negative, respectively. A prediction model was derived based on logistic regression analysis. We quantified the model[RIGHT SINGLE QUOTATION MARK]s performance using measures of discrimination and calibration. Finally, we constructed a prediction rule that should be easily applicable in clinical practice. RESULTS: The prediction rule showed good calibration and good overall performance (goodness-of-fit test, p[THIN SPACE]=[THIN SPACE]0.78, Brier score 20.1 %) and discriminated between patients with positive and negative PET findings (area under the receiver-operating characteristic curve, 0.83). If a positive predictive value for the presence of inflammatory activity of [GREATER-THAN OR EQUAL TO]90 % is considered acceptable for clinical decision-making without referral to PET, PET would be indicated in only 29.5 % of the patients. Using a positive predictive value of 98 %, about half of the patients (46.3 %) would require referral to PET. CONCLUSIONS: The derived and internally validated clinical prediction rule, based on sIL-2R levels and HRCT scoring results, appeared to be useful to identify sarcoidosis patients with a high probability of inflammatory activity. Using this rule may enable a more effective use of PET scan for assessment of inflammatory activity in sarcoidosis.