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

机译:临床评估模型的开发,以评估Bosniak III肾病变的恶性风险

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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.
机译:目的确定Bosniak III(BIII)肾脏病变恶性程度的独立预测因素,并基于易于识别的临床变量建立预测模型。方法在经过机构审查委员会批准的,符合健康保险携带和责任法案(HIPAA)的回顾性研究,放射学和医院信息系统中,对1994年1月1日至2009年8月31日之间的成人患者(年龄)进行了查询。 > 18岁)并手术切除BIII病变。记录临床变量和组织病理学结果。进行单变量和多变量逻辑回归分析以识别潜在的预测因素并建立预测模型。以一致性(c)指数为特征,使用交叉验证来评估模型性能的一般性。结果101例患者的107个病变中,恶性59例,良性48例。在单因素分析中,最有可能预测恶性肿瘤的因素是非裔美国人种族(P = .043),肾细胞癌病史(RCC; P = .026),BIII病变并存(P = .032),波斯尼亚IV(BIV)共存)病变(P = .104),体重指数(BMI; P = .078)和病变大小(P <.001)。具有病变大小的模型(赔率[OR] = 0.69; 95%置信区间[CI] 0.58-0.82),RCC历史(9.02; CI 0.99-82.15)和BMI(OR 1.1; 95%CI 0.99-1.19) )在交叉验证为0.719后提供了c-index的最佳性能。使用估计的大于80%的恶性概率,该模型的阳性预测值为92%(CI 78%-100%)。结论临床危险因素可为BIII病变提供适度但确定的恶性预测能力。特别是,一个包含病灶大小,BMI和RCC历史的预测模型似乎很有希望。需要进一步完善,包括可能包含成像生物标志物,并在独立的数据集上进行验证。

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