Zhan Y, Zhang R, Li C, et al. - Researchers sought to develop an effective microRNA (miRNA)-clinical model to predict the prognosis of kidney renal clear cell carcinoma (KIRC). Using the Cancer Genome Atlas database, 94 differentially expressed miRNAs were identified between para-tumor and tumor tissues. Prognostic indicators included seven miRNAs (hsa-miR-21-5p, hsa-miR-3613-5p, hsa-miR-144-5p, hsa-miR-376a-5p, hsa-miR-5588-3p, hsa-miR-1269a, and hsa-miR-137-3p). Based on their cox coefficient, a risk score formula was developed. On the basis of median score, patients with risk scores were classified into high- and low-risk groups. In Kaplan–Meier curves analysis, a better survival probability was observed in the low-risk group vs the high-risk group. For the miRNA model, an area under the ROC curve (AUC) of 0.744 was generated. Besides, a nomogram was constructed incorporating age, metastasis, and miRNA prognostic model based on the results of multivariate Cox regression analysis. The decision curve analysis demonstrated the clinical net advantage of the prognostic model. Overall, this study offers the miRNA-clinical model which is not only an effective but also accurate tool for prognosis prediction in KIRC.