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.
Introduction
The size of small renal masses (SRMs) correlates with the rate of malignancy on histology following excision . Whether changes in nephrometry scoring, a system that measures a range of parameters including the position of tumors in relation to hilar structures, can predict the rate of malignancy or aggressiveness of cancer is not known. The information related to growth patterns in relation to hilar structures may inform physicians to adopt the best possible management plans, including the prediction of postoperative complications .
There are three main nephrometry scoring systems described for kidney tumors according to pre-intervention computed tomography images and these are RENAL (Radius of tumors, Exo/Endophytic; Nearness of tumors to the collecting system or sinus; Anterior/posterior; Location in relation to polar lines) nephrometry score , PADUA (Preoperative Aspects and Dimensions Used for Anatomical) nephrometry score , and Centrality Index (C-index) . Detailed description of these methods is described in their original reports ; however, these measurement methods are designed to separate complex renal masses from noncomplex ones by measuring their anatomic location within renal parenchyma and their relationship to hilar vessels and renal pelvis. Published literature mainly focuses on using these scoring systems to assess the possibility of complications or technical difficulties that surgeons may encounter in the surgical resection of SRMs. Reports in literature suggest a good interobserver agreement in experienced hands and a predictability value of these scoring systems for postoperative complications following surgical excision and cryotherapy . Little is known about the predictive ability of these measurements to distinguish between benign and malignant histology and the grade of cancers. Few studies exploring the relations between nephrometry scores and histology concentrate on the single measurement of nephrometry scores , and a detailed correlation between changes in nephrometry scores and histology has not been reported.
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Patients and Methods
Study Cohort
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TABLE 1
Basic Demographics of the Cohort
Characteristics_N_ (SD/%) Numbers 97 Age (y) 59.7(±12.4) Sex Male 61 Female 36 Operative characteristics Kidney Right 43 Left 54 Tumor characteristics Tumor location Anterior 9 Posterior 88 Tumor diameter, mean (range) 3.8 (range 2–4) Tumor pathology Malignant 86 Clear cell carcinoma 67 Papillary cell carcinoma 14 Chromophobe 4 Tubulocystic 1 Benign 11 Grade of cancer Low (Furhman 1 and 2) 46 High (Furhman 3 and 4) 51 RENAL nephrometry (mean) 6.8 (±4.2) PADUA score (mean) 8.3 (±4.8) C-index (mean) 2.1(±1.9)
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Image Retrieval and Measurements
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Pathologic and Follow-up Data
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Statistical Analysis
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Results
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TABLE 2
Shows Association Between Type of Pathology, Complications, and Nephrometry Scores
Type of Cancer Patients in Total Patients with Complication R.E.N.A.L Score PADUA Score C-Index Score Statistical Significance ( P Value) Clear cell renal carcinoma 67 22 6.82 8.32 2.18 0.12 Papillary renal cell carcinoma 14 1 6.59 7.89 2.29 0.23 Chromophobe 4 0 6.64 7.9 2.32 0.10 Tubulocystic 1 0 8.12 9 1.84Benign 11 1 6.89 8.36 2.17 0.36
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TABLE 3
Scoring System Measurements and Histology of Excised SRMs
Type of Nephrometry Scoring Histological Type Following Nephron-sparing Surgery in SMRs Clear Cell Carcinoma, Mean (SD) Papillary Cell Carcinoma, Mean (SD) Chromophobe, Mean (SD) Benign, Mean (SD) Statistical Significance ( P Value) RENAL (Mean and SD) 6.82 (2.15) 6.56 (2.02) 6.64 (2.58) 6.89 (1.68) 0.21 PADUA (Mean and SD) 8.32 (2.11) 7.89 (1.67) 7.9 (3.20) 8.36 (1.87) 0.26 C-Index (Mean and SD) 2.18 (0.99) 2.29 (0.66) 2.33 (1.38) 2.17 (0.57) 0.46
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TABLE 4
Logistic Regression Analysis of Presurgical Factors Predicting Grade of Cancer in Excised Tumor (pT1a)
Presurgical Factors Small Renal Masses Removed by Partial Nephrectomy Univariate Analysis Multivariate Analysis Odds Ratio (95% CI)P Value Odds Ratio (95% CI)P Value Age (y) 1.004 (1.000–1.34) .021 1.04 (1.20–2.45) .102 Sex (male) 3.004 (2.01–3.34) .08 2.90 (1.5–4.98) .45 Increase in tumor size 4.02 (2.03–6.00) .001 3.02 (2.75–4.00) .001 Change in nephrometry score 5.00 (3.002–8.04) .0001 4.40 (2.09–5.45) .001 Obesity (BMI >29) 1.34 (0.09–2.03) .09 1.45 (1.12–3.45) .14 Multiple co-morbid conditions (>2) 2.001 (1.05–3.03) .12 2.98 (1.78–3.89) .23
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Discussion
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Conclusions
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