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

Ajit Goenka, Erick M. Remer, Andrew D. Smith, Nancy A. Obuchowski, Joseph Klink, Steven C. Campbell

Research output: Contribution to journalArticle

17 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)630-635
Number of pages6
JournalUrology
Volume82
Issue number3
DOIs
StatePublished - Sep 1 2013
Externally publishedYes

Fingerprint

Kidney
Radiology Information Systems
Hospital Information Systems
Health Insurance Portability and Accountability Act
Neoplasms
Research Ethics Committees
Renal Cell Carcinoma
African Americans
Body Mass Index
Retrospective Studies
Biomarkers
Logistic Models
Regression Analysis
Datasets

ASJC Scopus subject areas

  • Urology

Cite this

Development of a clinical prediction model for assessment of malignancy risk in bosniak III renal lesions. / Goenka, Ajit; Remer, Erick M.; Smith, Andrew D.; Obuchowski, Nancy A.; Klink, Joseph; Campbell, Steven C.

In: Urology, Vol. 82, No. 3, 01.09.2013, p. 630-635.

Research output: Contribution to journalArticle

Goenka, Ajit ; Remer, Erick M. ; Smith, Andrew D. ; Obuchowski, Nancy A. ; Klink, Joseph ; Campbell, Steven C. / Development of a clinical prediction model for assessment of malignancy risk in bosniak III renal lesions. In: Urology. 2013 ; Vol. 82, No. 3. pp. 630-635.
@article{bf92b1bcb0b94e1ea86a0e1fb0667657,
title = "Development of a clinical prediction model for assessment of malignancy risk in bosniak III renal lesions",
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.",
author = "Ajit Goenka and Remer, {Erick M.} and Smith, {Andrew D.} and Obuchowski, {Nancy A.} and Joseph Klink and Campbell, {Steven C.}",
year = "2013",
month = "9",
day = "1",
doi = "10.1016/j.urology.2013.05.016",
language = "English (US)",
volume = "82",
pages = "630--635",
journal = "Urology",
issn = "0090-4295",
publisher = "Elsevier Inc.",
number = "3",

}

TY - JOUR

T1 - Development of a clinical prediction model for assessment of malignancy risk in bosniak III renal lesions

AU - Goenka, Ajit

AU - Remer, Erick M.

AU - Smith, Andrew D.

AU - Obuchowski, Nancy A.

AU - Klink, Joseph

AU - Campbell, Steven C.

PY - 2013/9/1

Y1 - 2013/9/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84883218234&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84883218234&partnerID=8YFLogxK

U2 - 10.1016/j.urology.2013.05.016

DO - 10.1016/j.urology.2013.05.016

M3 - Article

C2 - 23876583

AN - SCOPUS:84883218234

VL - 82

SP - 630

EP - 635

JO - Urology

JF - Urology

SN - 0090-4295

IS - 3

ER -