April 2020

Perioperative Detection of Circulating Tumor Cells in Radical or Partial Nephrectomy for Renal Cell Carcinoma

Haga, N., Onagi, A., Koguchi, T. et al.
Ann Surg Oncol 27, 1272–1281 (2020)
DOI: 10.1245/s10434-019-08127-8



The current study was conducted to clarify the frequency of systemic circulating tumor cells (CTCs) appearing after surgery for renal cell carcinoma and to evaluate the differences in postoperative CTCs between different surgical procedures.


This prospective, cohort study included 60 consecutive patients who underwent laparoscopic radical nephrectomy (RN) (n = 22), laparoscopic partial nephrectomy (PN) (n = 19), open RN (n = 8), or open PN (n = 11). In this study CTCs were measured by the FISHMAN-R system, and CTCs drawn from a peripheral artery were collected just before and immediately after surgery. The number of pre- and postoperative CTCs and the perioperative changes in CTCs were measured for each surgical method.


Six patients were excluded from the current analyses. Preoperative CTCs did not differ significantly by surgical approach (laparoscopic RN: 3.4 ± 4.2; laparoscopic PN: 3.4 ± 4.1; open RN: 7.7 ± 6.8; open PN: 6.0 ± 7.6; P = 0.19). Open RN resulted in a significantly greater number of postoperative CTCs (laparoscopic RN: 4.8 ± 3.7; laparoscopic PN: 7.9 ± 9.1; open RN: 22.5 ± 26.3; open PN: 6.4 ± 6.3; P < 0.001) and perioperative changes in CTCs (laparoscopic RN: 1.3 ± 5.3; laparoscopic PN: 4.5 ± 9.6; open RN: 14.7 ± 25.0; open PN: 0.4 ± 6.3; P < 0.001). No significant differences in these were observed among the three groups except in the open RN group. In the multivariate analysis, the surgical approach was significantly correlated with the number of postoperative CTCs (P = 0.016) and the perioperative change in CTCs (P = 0.01).


This proof-of-concept study indicated that after surgery, more cancer cells can be expelled into the bloodstream, especially after open RN. Sufficient and careful follow-up assessment for the emergence of distant metastases is needed for patients undergoing open RN.

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Non-contrast imaging characteristics of papillary renal cell carcinoma: implications for diagnosisand subtyping

Badri AV, Waingankar N, Edwards K, et al.
Can J Urol. 2019 Oct;26(5):9916-9921.



Current radiographic guidelines suggest unenhanced renal lesions < 20 Hounsfield Units (HU) are overwhelmingly benign, requiring no further evaluation. We evaluate our experience with papillary renal cell carcinoma (pRCC) presenting with low pre-contrast attenuation and the relationship of attenuation with histologic pRCC subtype.

Materials and Methods

We reviewed our institutional kidney cancer database for patients with pT1 or pT2 pRCC between 2003-2017. Tumors were categorized by papillary subtype by expert uropathologists. Preoperative CT images were analyzed at six regional tumor locations. Low, presumably benign, unenhanced median attenuation was defined as ≤ 20 HU. We calculated the frequency of pRCC with low attenuation and assessed the relationship between attenuation and pRCC subtype using logistic regression.


Sixty-one patients with evaluable imaging were included. Median tumor size was 6 cm (1.7 cm-15.3 cm) with 39% (n = 24) type-1 and 61% (n = 37) type-2. Half of all pRCC tumors (n = 30) exhibited very low pre-contrast attenuation (< 20 HU), risking misdiagnosis as benign using current guidelines. Of these, 80% (n = 24) were type-2 with significant biological potential. Overall, type-2 tumors demonstrated a lower pre-contrast attenuation than type-1 (median HU: 19.8 (1.5-42.3) versus 29.6 HU (10-45.8), p < 0.01; max HU: 25.3 versus 36.5 HU, p < 0.01). After adjustment, lower pre-contrast HU was an independent predictor of pRCC subtype associated with a 5.5-fold increase of being type-2 (OR = 5.47, p < 0.01).


pRCCs may exhibit very low attenuation on pre-contrast CT. This appears more common among the more aggressive type-2 subtype. These data suggest that low attenuation (< 20 HU) alone on non-contrast CT imaging is insufficient as a single parameter to rule out malignancy.

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First-line Immuno-Oncology Combination Therapies in Metastatic Renal-cell Carcinoma: Resultsfrom the International Metastatic Renal-cell Carcinoma Database Consortium

Dudani S, Graham J, Wells JC, et al.
Eur Urol. 2019 Dec;76(6):861-867.
DOI: 10.1016/j.eururo.2019.07.048. Epub 2019 Aug 22.



In metastatic renal-cell carcinoma (mRCC), recent data have shown efficacy of first-line ipilimumab and nivolumab (ipi-nivo) as well as immuno-oncology (IO)/vascular endothelial growth factor (VEGF) inhibitor combinations. Comparative data between these strategies are limited.


To compare the efficacy of ipi-nivo versus IO-VEGF (IOVE) combinations in mRCC, and describe practice patterns and effectiveness of second-line therapies.

Design, setting, and participants

Using the International Metastatic Renal-cell Carcinoma Database Consortium (IMDC) dataset, patients treated with any first-line IOVE combination were compared with those treated with ipi-nivo.


All patients received first-line IO combination therapies.

Outcome measurements and statistical analysis

First- and second-line response rates, time to treatment failure (TTF), time to next treatment (TNT), and overall survival (OS) were analysed. Hazard ratios were adjusted for IMDC risk factors.

Results and limitations

In total, 113 patients received IOVE combinations and 75 received ipi-nivo. For IOVE combinations versus ipi-nivo, first-line response rates were 33% versus 40% (between-group difference 7%, 95% confidence interval [CI] -8% to 22%, p =  0.4), TTF was 14.3 versus 10.2 mo (p =  0.2), TNT was 19.7 versus 17.9 mo (p =  0.4), and median OS was immature but not statistically different (p = 0.17). Adjusted hazard ratios for TTF, TNT, and OS were 0.71 (95% CI 0.46-1.12, p =  0.14), 0.65 (95% CI 0.38-1.11, p =  0.11), and 1.74 (95% CI 0.82-3.68, p =  0.14), respectively. Sixty-four (34%) patients received second-line treatment. In patients receiving subsequent VEGF-based therapy, second-line response rates were lower in the IOVE cohort than in the ipi-nivo cohort (15% vs 45%; between-group difference 30%, 95% CI 3-57%, p =  0.04; n = 40), though second-line TTF was not significantly different (3.7 vs 5.4 mo; p =  0.4; n = 55). Limitations include the study’s retrospective design and sample size.


There were no significant differences in first-line outcomes between IOVE combinations and ipi-nivo. Most patients received VEGF-based therapy in the second line. In this group, second-line response rate was greater in patients who received ipi-nivo initially.

Patient summar

There were no significant differences in key first-line outcomes for patients with metastatic renal-cell carcinomareceiving immuno-oncology/vascular endothelial growth factor inhibitor combinations versus ipilimumab and nivolumab.

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Predicting Renal Cancer Recurrence: Defining Limitations of Existing Prognostic Models With Prospective Trial-Based Validation

Correa AF, Jegede O, Haas NB, et al.
J Clin Oncol. 2019 Aug 10;37(23):2062-2071.
DOI: 10.1200/JCO.19.00107.



To validate currently used recurrence prediction models for renal cell carcinoma (RCC) by using prospective data from the ASSURE (ECOG-ACRIN E2805; Adjuvant Sorafenib or Sunitinib for Unfavorable Renal Carcinoma) adjuvant trial.

Patients and methods

Eight RCC recurrence models (University of California at Los Angeles Integrated Staging System [UISS]; Stage, Size, Grade, and Necrosis [SSIGN]; Leibovich; Kattan; Memorial Sloan Kettering Cancer Center [MSKCC]; Yaycioglu; Karakiewicz; and Cindolo) were selected on the basis of their use in clinical practice and clinical trial designs. These models along with the TNM staging system were validated using 1,647 patients with resected localized high-grade or locally advanced disease (≥ pT1b grade 3 and 4/pTanyN1Mo) from the ASSURE cohort. The predictive performance of the model was quantified by assessing its discriminatory and calibration abilities.


Prospective validation of predictive and prognostic models for localized RCC showed a substantial decrease in each of the predictive abilities of the model compared with their original and externally validated discriminatory estimates. Among the models, the SSIGN score performed best (0.688; 95% CI, 0.686 to 0.689), and the UISS model performed worst (0.556; 95% CI, 0.555 to 0.557). Compared with the 2002 TNM staging system (C-index, 0.60), most models only marginally outperformed standard staging. Importantly, all models, including TNM, demonstrated statistically significant variability in their predictive ability over time and were most useful within the first 2 years after diagnosis.


In RCC, as in many other solid malignancies, clinicians rely on retrospective prediction tools to guide patient care and clinical trial selection and largely overestimate their predictive abilities. We used prospective collected adjuvant trial data to validate existing RCC prediction models and demonstrate a sharp decrease in the predictive ability of all models compared with their previous retrospective validations. Accordingly, we recommend prospective validation of any predictive model before implementing it into clinical practice and clinical trial design.

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