Objective: This study aimed to develop a diagnostic model to estimate the distribution of small renal mass (SRM; ≤4 cm) histologic subtypes for patients with different demographic backgrounds and clear cell likelihood score (ccLS) designations.
Materials and methods: A bi-institution retrospective cohort study was conducted where 347 patients (366 SRMs) underwent magnetic resonance imaging and received a ccLS before pathologic confirmation between June 2016 and November 2021. Age, sex, race, ethnicity, socioeconomic status, body mass index (BMI), and the ccLS were tabulated. The socioeconomic status for each patient was determined using the Area Deprivation Index associated with their residential address. The magnetic resonance imaging-derived ccLS assists in the characterization of SRMs by providing a likelihood of clear cell renal cell carcinoma (ccRCC). Pathological subtypes were grouped into four categories (ccRCC, papillary renal cell carcinoma, other renal cell carcinomas, or benign). Generalized estimating equations were used to estimate probabilities of the pathological subtypes across different patient subgroups.
Results: Race and ethnicity, BMI, and ccLS were significant predictors of histology (all P < 0.001). Obese (BMI, ≥30 kg/m2) Hispanic patients with ccLS of ≥4 had the highest estimated rate of ccRCC (97.1%), and normal-weight (BMI, <25 kg/m2) non-Hispanic Black patients with ccLS ≤2 had the lowest (0.2%). The highest estimated rates of papillary renal cell carcinoma were found in overweight (BMI, 25-30 kg/m2) non-Hispanic Black patients with ccLS ≤2 (92.3%), and the lowest, in obese Hispanic patients with ccLS ≥4 (<0.1%).
Conclusions: Patient race, ethnicity, BMI, and ccLS offer synergistic information to estimate the probabilities of SRM histologic subtypes.
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