Abstract
Rationale and Objectives: Prediction of growth, in particular knowing the possibility of aggressive cancer in small renal masses on active surveillance, remains poorly understood. The study was designed to determine whether serial nephrometry score measurements could predict possibility of aggressive malignancy (grade of cancer) in patients with small renal masses opting for active surveillance initially. Materials and Methods: One hundred sixteen patients between January 2000 and December 2016 undergoing partial nephrectomy were recruited. Out of these, 97 were analyzed using different nephrometry scoring systems. Measurement of nephrometry scores (Radius of tumors, Exo/Endophytic; Nearness of tumors to the collecting system or sinus; Anterior/posterior; Location in relation to polar lines, Preoperative Aspects and Dimensions Used for Anatomical, Centrality Index) was performed by two researchers. Among the patients opting for partial nephrectomy, 40 were on active surveillance for at least 12 months (mean 32; 12-60 months) before partial nephrectomy. Computed tomography scan images of these patients were retrieved and analyzed including comparison to histopathology. Results: Nephrometry scores measured on serial computed tomography scan images showed a significant correlation between change in score and grade of cancer on multivariate analysis (P value .001). Addition of multivariate analysis to nomogram based on change in size alone did not improve predictive value of area under the curve significantly. Conclusions: Change in nephrometry scoring measurements correlates with grade of cancer in small renal masses but falls short of significantly predicting presence of malignancy or grade of cancer on nomogram in patients opting for active surveillance for small renal masses. At present, this approach may be inadequate for decision-making.
| Original language | English |
|---|---|
| Pages (from-to) | 1381-1387 |
| Number of pages | 7 |
| Journal | Academic Radiology |
| Volume | 25 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 2018 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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