Development of a clinical prediction model for assessment of malignancy risk in Bosniak III renal lesions.

Academic Article

Abstract

  • OBJECTIVE: To identify independent predictors of malignancy in Bosniak III (BIII) renal lesions and to build a prediction model based on readily identifiable clinical variables. METHODS: In this institutional review board-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant retrospective study, radiology, and hospital information systems containing data from January 1, 1994, to August 31, 2009, were queried for adult patients (age >18 years) with surgically excised BIII lesions. Clinical variables and results of histopathology were noted. Univariate and multiple-variable logistic regression analyses were performed to identify potential predictors and to build a prediction model. Cross-validation was used to assess generalizability of the model's performance, as characterized by concordance (c) index. RESULTS: Of the 107 lesions in 101 patients, 59 were malignant and 48 benign. On univariate analyses, the strongest potential predictors of malignancy were African American race (P = .043), history of renal cell carcinoma (RCC; P = .026), coexisting BIII lesions (P = .032), coexisting Bosniak IV (BIV) lesions (P = .104), body mass index (BMI; P = .078), and lesion size (P <.001). A model with lesion size (odds ratio [OR] = 0.69; 95% confidence interval [CI] 0.58-0.82), history of RCC (9.02; CI 0.99-82.15), and BMI (OR 1.1; 95% CI 0.99-1.19) offered the best performance with a c-index after cross-validation of 0.719. Using an estimated probability of malignancy of >80%, the positive predictive value of the model is 92% (CI 78%-100%). CONCLUSION: Clinical risk factors offer modest but definite predictive ability for malignancy in BIII lesions. In particular, a prediction model encompassing lesion size, BMI, and history of RCC seems promising. Further refinements with possible inclusion of imaging biomarkers and validation on an independent dataset are desirable.
  • Published In

  • Urology  Journal
  • Keywords

  • Adult, Aged, Aged, 80 and over, Carcinoma, Renal Cell, Decision Support Techniques, Female, Humans, Kidney Diseases, Cystic, Kidney Neoplasms, Logistic Models, Male, Medical History Taking, Middle Aged, Multivariate Analysis, Predictive Value of Tests, Preoperative Period, Retrospective Studies, Risk Assessment
  • Digital Object Identifier (doi)

    Author List

  • Goenka AH; Remer EM; Smith AD; Obuchowski NA; Klink J; Campbell SC
  • Start Page

  • 630
  • End Page

  • 635
  • Volume

  • 82
  • Issue

  • 3