title: A predictive tool for an effective use of (18)F-FDG PET in assessing activity of sarcoidosis.
abstract: BACKGROUND
  (18)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 = 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'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 = 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 ≥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.
authors.affiliation: Department of Respiratory Medicine, Atrium Medical Centre, Heerlen, The Netherlands.
authors.forename: Rémy L M
authors.initials: RL
authors.lastname: Mostard
authors.forename: Sander M J
authors.initials: SM
authors.lastname: Van Kuijk
authors.forename: Johny A
authors.initials: JA
authors.lastname: Verschakelen
authors.forename: Marinus J P G
authors.initials: MJ
authors.lastname: van Kroonenburgh
authors.forename: Patty J
authors.initials: PJ
authors.lastname: Nelemans
authors.forename: Petal A H M
authors.initials: PA
authors.lastname: Wijnen
authors.forename: Marjolein
authors.initials: M
authors.lastname: Drent
mesh_terms: D000328:Adult; D000368:Aged; D015331:Cohort Studies; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D049268:Positron-Emission Tomography / Q000379:methods*; D011237:Predictive Value of Tests; D015375:Receptors, Interleukin-2 / Q000097:blood; D012189:Retrospective Studies; D017565:Sarcoidosis, Pulmonary / Q000097:blood / Q000000981:diagnostic imaging*; D012720:Severity of Illness Index; D014057:Tomography, X-Ray Computed
chemical_list: D015375:Receptors, Interleukin-2; D019788:Fluorodeoxyglucose F18