title: The probability of malignancy in solitary pulmonary nodules. Application to small radiologically indeterminate nodules.
abstract: BACKGROUND
  A clinical prediction model to identify malignant nodules based on clinical data and radiological characteristics of lung nodules was derived using logistic regression from a random sample of patients (n = 419) and tested on data from a separate group of patients (n = 210).
  
  
  OBJECTIVE
  To use multivariate logistic regression to estimate the probability of malignancy in radiologically indeterminate solitary pulmonary nodules (SPNs) in a clinically relevant subset of patients with SPNs that measured between 4 and 30 mm in diameter.
  
  
  METHODS
  A retrospective cohort study at a multispecialty group practice included 629 patients (320 men, 309 women) with newly discovered (between January 1, 1984, and May 1, 1986) 4- to 30-mm radiologically indeterminate SPNs on chest radiography. Patients with a diagnosis of cancer within 5 years prior to the discovery of the nodule were excluded. Clinical data included age, sex, cigarette-smoking status, and history of extrathoracic malignant neoplasm, asbestos exposure, and chronic interstitial or obstructive lung disease; chest radiological data included the diameter, location, edge characteristics (eg, lobulation, spiculation, and shagginess), and other characteristics (eg, cavitation) of the SPNs. Predictors were identified in a random sample of two thirds of the patients and tested in the remaining one third.
  
  
  RESULTS
  Sixty-five percent of the nodules were benign, 23% were malignant, and 12% were indeterminate. Three clinical characteristics (age, cigarette-smoking status, and history of cancer [diagnosis, > or = 5 years ago]) and 3 radiological characteristics (diameter, spiculation, and upper lobe location of the SPNs) were independent predictors of malignancy. The area (+/-SE) under the evaluated receiver operating characteristic curve was 0.8328 +/- 0.0226.
  
  
  CONCLUSIONS
  Three clinical and 3 radiographic characteristics predicted the malignancy in radiologically indeterminate SPNs.
authors.affiliation: Department of Diagnostic Radiology, Mayo Clinic, Rochester, Minn, USA.
authors.forename: S J
authors.initials: SJ
authors.lastname: Swensen
authors.forename: M D
authors.initials: MD
authors.lastname: Silverstein
authors.forename: D M
authors.initials: DM
authors.lastname: Ilstrup
authors.forename: C D
authors.initials: CD
authors.lastname: Schleck
authors.forename: E S
authors.initials: ES
authors.lastname: Edell
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D016015:Logistic Models; D008171:Lung Diseases / Q000175:diagnosis; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000473:pathology; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011336:Probability; D012372:ROC Curve; D011859:Radiography; D012189:Retrospective Studies; D012307:Risk Factors