title: Physician Assessment of Pretest Probability of Malignancy and Adherence With Guidelines for Pulmonary Nodule Evaluation.
abstract: The annual incidence of pulmonary nodules is estimated at 1.57 million. Guidelines recommend using an initial assessment of nodule probability of malignancy (pCA). A previous study found that despite this recommendation, physicians did not follow guidelines.
  
  
  
  Physician assessments (N = 337) and two previously validated risk model assessments of pretest probability of cancer were evaluated for performance in 337 patients with pulmonary nodules based on final diagnosis and compared. Physician-assessed pCA was categorized into low, intermediate, and high risk, and the next test ordered was evaluated.
  
  
  
  The prevalence of malignancy was 47% (n = 158) at 1 year. Physician-assessed pCA performed better than nodule prediction calculators (area under the curve, 0.85 vs 0.75; P < .001 and .78; P = .0001). Physicians did not follow indicated guidelines when selecting the next test in 61% of cases (n = 205). Despite recommendations for serial CT imaging in those with low pCA, 52% (n = 13) were managed more aggressively with PET imaging or biopsy; 12% (n = 3) underwent biopsy procedures for benign disease. Alternatively, in the high-risk category, the majority (n = 103 [75%]) were managed more conservatively. Stratified by diagnosis, 92% (n = 22) with benign disease underwent more conservative management with CT imaging (20%), PET scanning (15%), or biopsy (8%), although three had surgery (8%).
  
  
  
  Physician assessment as a means for predicting malignancy in pulmonary nodules is more accurate than previously validated nodule prediction calculators. Despite the accuracy of clinical intuition, physicians did not follow guideline-based recommendations when selecting the next diagnostic test. To provide optimal patient care, focus in the areas of guideline refinement, implementation, and dissemination is needed.
authors.affiliation: Thoracic Oncology Research Group, Division of Pulmonary and Critical Care, Medical University of South Carolina, Charleston, SC; Health Equity and Rural Outreach Innovation Center, Ralph H. Johnson Veterans Affairs Hospital, Charleston, SC. Electronic address: tripici@musc.edu.
authors.forename: Nichole T
authors.initials: NT
authors.lastname: Tanner
authors.affiliation: Integrated Diagnostics, Inc., Seattle, WA.
authors.forename: Alexander
authors.initials: A
authors.lastname: Porter
authors.affiliation: Kaiser Permanente Southern California, Pasadena, CA.
authors.forename: Michael K
authors.initials: MK
authors.lastname: Gould
authors.affiliation: Integrated Diagnostics, Inc., Seattle, WA.
authors.forename: Xiao-Jun
authors.initials: XJ
authors.lastname: Li
authors.affiliation: Pulmonary, Allergy, and Critical Care Division, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
authors.forename: Anil
authors.initials: A
authors.lastname: Vachani
authors.affiliation: Thoracic Oncology Research Group, Division of Pulmonary and Critical Care, Medical University of South Carolina, Charleston, SC.
authors.forename: Gerard A
authors.initials: GA
authors.lastname: Silvestri
mesh_terms: D000328:Adult; D000368:Aged; D002983:Clinical Competence / Q000592:standards*; D055088:Early Detection of Cancer; D005260:Female; D019983:Guideline Adherence; D006801:Humans; D033162:Incidental Findings; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging; D008297:Male; D008875:Middle Aged; D055613:Multiple Pulmonary Nodules / Q000150:complications* / Q000000981:diagnostic imaging; D000072078:Positron Emission Tomography Computed Tomography; D017410:Practice Guidelines as Topic; D011446:Prospective Studies; D000072106:Pulmonologists / Q000592:standards*; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D003074:Solitary Pulmonary Nodule / Q000150:complications* / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed
keywords: guideline adherence; nodule management; nodule risk prediction; pulmonary nodules