Combined Charlson comorbidity/C-Reactive Protein Index Is a Novel Predictor in Renal Cell Carcinoma: Analysis of the International Marker Consortium for Renal Cancer (INMARC) Registry.

OBJECTIVE: To evaluate predictive ability of a novel combined index, Charlson comorbidity index and C-reactive protein (CCI-CRP), for outcomes in renal cell carcinoma (RCC), and compare predictive outcomes with of CCI-CRP to its separate components and to the UCLA integrated staging system (UISS). PATIENTS AND METHODS: We retrospectively analyzed INMARC registry of RCC patients. Receiver Operator Characteristics (ROC) analysis was fitted to identify threshold defining low-CRP (LCRP) and high-CRP (HCRP). Patients were stratified according to CCI [low-CCI ≤ 3 (LCCI); intermediate-CCI 4-6 (ICCI); high-CCI > 6 (HCCI)] and CRP level. Kaplan-Meier analysis (KMA) was conducted for overall (OS) and cancer-specific survival (CSS). Based on survival analysis distribution we proposed a new stratification: CCI-CRP. Model performance was assessed with ROC/area under the curve (AUC) analysis and compared to CCI and CRP alone, and UISS. RESULTS: We analyzed 2,890 patients (median follow-up 30 months). ROC identified maximum product sensitivity and specificity for CRP at 3.5 mg/L. KMA revealed 5-year OS of 95.6% for LCRP/LCCI, 83% LCRP/ICCI, 73.3% LCRP/HCCI, 62.6% HCRP/LCCI, 51.6% HCRP/ICCI and 40.5% HCRP/HCCI (P < .001). From this distribution, new CCI-CRP is proposed: low CCI-CRP (LCRP/LCCI and LCRP/ICCI), intermediate CCI-CRP (LCRP/HCCI and HCRP/LCCI), and high CCI-CRP (HCRP/ICCI and HCRP/HCCI). AUC for CCI-CRP showed improved performance for predicting OS/CSS vs. CCI alone (0.73 vs. 0.63/0.77 vs. 0.60), CRP alone (0.73 vs. 0.71/0.77 vs. 0.74) and UISS (0.73 vs 0.67/0.77 vs 0.73). CONCLUSIONS: CCI-CRP, exhibits increased prognostic performance for survival outcomes in RCC compared to CCI and CRP alone, and UISS. Further investigation is requisite.

Association of Elevated C-Reactive Protein with Worsened Outcomes in Different Histologies of Renal Cortical Tumors: Analysis of the INMARC Registry.

BACKGROUND: To evaluate relationship between histological subtypes of renal cell carcinoma (RCC) and preoperative c-reactive protein (CRP). PATIENTS AND METHODS: We queried the International Marker Consortium for Renal Cancer database for patients affected by RCC. Patients were classified according to their histology: benign tumors, clear cell (cc) RCC, chromophobe (ch) RCC, papillary (p) RCC, and variant histology (vh) RCC; and according to CRP (mg/L): low CRP ≤5 and high CRP >5. Primary outcome was all-cause mortality (ACM). Secondary outcomes were cancer-specific mortality (CSM), recurrence and association between CRP and histology. Multivariable analysis (MVA) via Cox regression and multivariable logistic regression were fitted to elucidate predictors of outcomes. RESULTS: Total 3902 patients (high CRP n = 1266) were analyzed; median follow up 51 (IQR 20-91) months. On MVA elevated CRP was an independent risk factor associated with increased risk of ACM in benign tumors (HR 5.98, P < .001), ccRCC (HR 2.69, P < .001), chRCC (HR 3.99, P < .001), pRCC (HR 1.76, P = .009) and vhRCC (HR 2.97, P =.007). MVA for CSM showed CRP as risk factor in ccRCC (HR 2.77, P < .001), chRCC (HR 6.16, P = .003) and pRCC (HR 2.29, P = .011), while in vhRCC was not (P = .27). MVA for recurrence reported CRP as risk factor for ccRCC (HR 1.30, P = .013), while in chRCC (P = .33), pRCC (P = .34) and vhRCC (P = .52) was not. On multivariable logistic regression CRP was a predictor of pRCC (OR 1.003, P = .002), while decreasing CRP was associated with benign tumors (OR 0.994, P = .048). CONCLUSION: Elevated CRP was a robust predictor of worsened ACM in all renal cortical neoplasms. While most frequently observed in pRCC patients, elevated CRP was independently associated with worsened CSM in non-vhRCC. Conversely, elevated CRP was least likely to be noted in benign tumors, and elevation in this subgroup of patients should prompt further consideration for surveillance given increased risk of ACM. Further investigation is requisite.

Unraveling the BMI paradox in different renal cortical tumors: insights from the INMARC registry.

OBJECTIVE: To investigate impact of body mass index (BMI) on survival across different histologies and stages of renal cell carcinoma (RCC). METHODS: We conducted a retrospective multicenter analysis of clear cell (ccRCC) and non-ccRCC. Obesity was defined according to the WHO criteria (non-Asian BMI >30 Kg/m2, Asian BMI >27.5 Kg/m2). Multivariable analysis (MVA) via Cox regression model was conducted for all-cause (ACM), cancer-specific mortality (CSM) and recurrence. RESULTS: A total of 3,880 patients with a median follow-up of 31 (IQR 9-64) months were analyzed. Overall, 1,373 (35.3%) were obese; 2,895 (74.6%) were ccRCC and 985 (25.3%) were non-ccRCC (chRCC 246 [24.9%], pRCC 469 [47.6%] and vhRCC 270 [27.4%]). MVA in ccRCC revealed obesity associated with decreased risk of ACM, CSM and recurrence (hazard ratio [HR] 0.80, P = 0.044; HR 0.71, P = 0.039; HR 0.73, P = 0.012, respectively), while in non-ccRCC was not associated with decreased risk of ACM, CSM, and recurrence (P = 0.84, P = 0.53, P = 0.84, respectively). Subset analysis in stage IV ccRCC demonstrated obesity as associated with a decreased risk of ACM, CSM, and recurrence (HR 0.68, P = 0.04; HR 0.59, P = 0.01; HR 0.59, P = 0.01, respectively), while in stage I-III ccRCC was not (P = 0.21; P = 0.30; P = 0.19, respectively). CONCLUSION: Our findings refute a broad "obesity paradox" for RCC. Obesity was not associated with improved survival in non-ccRCC and in nonmetastatic ccRCC, while metastatic ccRCC patients with obesity had improved survival outcomes.

Development of a novel score (RENSAFE) to determine probability of acute kidney injury and renal functional decline post surgery: A multicenter analysis.

OBJECTIVE: To create and validate 2 models called RENSAFE (RENalSAFEty) to predict postoperative acute kidney injury (AKI) and development of chronic kidney disease (CKD) stage 3b in patients undergoing partial (PN) or radical nephrectomy (RN) for kidney cancer. METHODS: Primary objective was to develop a predictive model for AKI (reduction >25% of preoperative eGFR) and de novo CKD≥3b (<45 ml/min/1.73m2), through stepwise logistic regression. Secondary outcomes include elucidation of the relationship between AKI and de novo CKD≥3a (<60 ml/min/1.73m2). Accuracy was tested with receiver operator characteristic area under the curve (AUC). RESULTS: AKI occurred in 452/1,517 patients (29.8%) and CKD≥3b in 116/903 patients (12.8%). Logistic regression demonstrated male sex (OR = 1.3, P = 0.02), ASA score (OR = 1.3, P < 0.01), hypertension (OR = 1.6, P < 0.001), R.E.N.A.L. score (OR = 1.2, P < 0.001), preoperative eGFR<60 (OR = 1.8, P = 0.009), and RN (OR = 10.4, P < 0.0001) as predictors for AKI. Age (OR 1.0, P < 0.001), diabetes mellitus (OR 2.5, P < 0.001), preoperative eGFR <60 (OR 3.6, P < 0.001) and RN (OR 2.2, P < 0.01) were predictors for CKD≥3b. AUC for RENSAFE AKI was 0.80 and 0.76 for CKD≥3b. AKI was predictive for CKD≥3a (OR = 2.2, P < 0.001), but not CKD≥3b (P = 0.1). Using 21% threshold probability for AKI achieved sensitivity: 80.3%, specificity: 61.7% and negative predictive value (NPV): 88.1%. Using 8% cutoff for CKD≥3b achieved sensitivity: 75%, specificity: 65.7%, and NPV: 96%. CONCLUSION: RENSAFE models utilizing perioperative variables that can predict AKI and CKD may help guide shared decision making. Impact of postsurgical AKI was limited to less severe CKD (eGFR<60 ml/min 71.73m2). Confirmatory studies are requisite.