title: Distinguishing malignant and benign renal masses with composite models and nomograms: A systematic review and meta-analysis of clinically localized renal masses suspicious for malignancy.
abstract: Solid renal masses and cystic lesions with solid components are suspicious for renal cell carcinoma. Without an effective screening test, composite models and nomograms rely on patient and tumor characteristics to stratify the risk of benign disease versus malignant disease. To guide decisions about the use of renal mass sampling or excision, a systematic review and meta-analysis of the ability of composite models to predict the likelihood of malignancy on the basis of preoperative clinical variables was performed. MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials were searched from January 1, 1997, through May 1, 2015, according to the Preferred Reporting Items for Systematic Review and Meta-Analyses statement. Composite models necessarily included imaging results and at least 1 element from the following to be compared with surgical pathology: demographic characteristics, clinical characteristics, and blood or urine tests. Two independent reviewers screened citations and extracted data. Quality Assessment Tool for Diagnostic Accuracy Studies 2 was used to assess the risk of bias. The strength of evidence was graded with the scheme recommended by Methods Guide for Effectiveness and Comparative Effectiveness Reviews. Twenty studies (12,149 patients) were included in this review. The only significant predictors of malignancy in the composite models were tumor size (effect size, 1.33-fold increased risk per centimeter; 95% confidence interval [CI], 1.22-1.43) and male sex (effect size, 2.71; 95% CI, 2.39-3.02). The results were inconclusive or not significant for tumor characteristics, age, body mass index, and incidental presentation. In conclusion, composite models currently have a limited ability to distinguish malignant renal masses from benign renal masses, with increased tumor size and male sex associated with malignancy. Cancer 2016;122:3267-3276. © 2016 American Cancer Society.
authors: James Buchanan Brady Urological Institute, Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors: Phillip M
authors: PM
authors: Pierorazio
authors: James Buchanan Brady Urological Institute, Johns Hopkins Medical Institutions, Baltimore, Maryland. hitenpatel@jhmi.edu.
authors: Hiten D
authors: http://orcid.org/0000-0003-4028-010X
authors: HD
authors: Patel
authors: James Buchanan Brady Urological Institute, Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors: Michael H
authors: MH
authors: Johnson
authors: Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, Maryland.|Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors: Stephen M
authors: SM
authors: Sozio
authors: Johns Hopkins Evidence-Based Practice Center, Johns Hopkins School of Public Health, Baltimore, Maryland.
authors: Ritu
authors: R
authors: Sharma
authors: Johns Hopkins Evidence-Based Practice Center, Johns Hopkins School of Public Health, Baltimore, Maryland.
authors: Emmanuel
authors: E
authors: Iyoha
authors: Johns Hopkins Evidence-Based Practice Center, Johns Hopkins School of Public Health, Baltimore, Maryland.
authors: Eric B
authors: EB
authors: Bass
authors: James Buchanan Brady Urological Institute, Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors: Mohamad E
authors: ME
authors: Allaf
mesh_terms: D002292:Carcinoma, Renal Cell / Q000473:pathology*; D005260:Female; D006801:Humans; D007680:Kidney Neoplasms / Q000473:pathology*; D008297:Male; D015233:Models, Statistical; D049451:Nomograms; D011230:Precancerous Conditions / Q000473:pathology*
keywords: composite models; malignancy; nomogram; predictors; renal cell carcinoma; renal mass