Pathologically examining a minimum of three lymph nodes could better determine node negativity in patients with non-metastatic chromophobe renal cell carcinoma
To evaluate the prognostic value of lymph node (LN) involvement for patients with chromophobe renal cell carcinoma (chRCC) and ascertain the minimum number of LNs that need to be pathologically examined to reliably diagnose a patient with node negative chRCC. From 2004 to 2014, non-metastatic chRCC...
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Published in: | Japanese journal of clinical oncology Vol. 48; no. 10; pp. 942 - 949 |
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Abstract | To evaluate the prognostic value of lymph node (LN) involvement for patients with chromophobe renal cell carcinoma (chRCC) and ascertain the minimum number of LNs that need to be pathologically examined to reliably diagnose a patient with node negative chRCC.
From 2004 to 2014, non-metastatic chRCC patients receiving radical nephrectomy together with lymphadenectomy were identified from the Surveillance, Epidemiology and End Results (SEER) database. The primary outcome was overall survival (OS).
Two hundred and forty-six patients received lymph node dissection during the surgery. Of the patients, 24 (10%) had pathologically confirmed positive LN. Multivariate Cox regression model showed that positive LN was an independent unfavorable predictor for OS (HR = 2.83, 95%CI = 1.14-6.98, P = 0.024). More importantly, LN(-) patients with at least three LNs dissected had significantly better OS compared with when 1-2 LNs were examined (P = 0.048). Multivariate analysis confirmed that in LN(-) patients, the examination of three or more LNs could independently predict better OS compared with patients with only 1-2 LNs dissected (HR≥3LNs = 0.362, 95% CI = 0.135-0.972, P = 0.044). Additionally, the likelihood of finding at least one positive LN was significantly higher on dissection of ≥3 LNs compared with examination of 1-2 LNs (15% vs 5%, P = 0.018). Decision curve analysis found a better clinical validity of the '3 LNs examined'-based classification compared with the traditional LN(-)/LN(+) classification.
The proportion of positive LNs in chRCC was far from neglectable and LN metastasis could independently predict unfavorable OS. We recommended a minimum of three LNs should be pathologically examined in order to reliably determine node negative. |
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AbstractList | To evaluate the prognostic value of lymph node (LN) involvement for patients with chromophobe renal cell carcinoma (chRCC) and ascertain the minimum number of LNs that need to be pathologically examined to reliably diagnose a patient with node negative chRCC.
From 2004 to 2014, non-metastatic chRCC patients receiving radical nephrectomy together with lymphadenectomy were identified from the Surveillance, Epidemiology and End Results (SEER) database. The primary outcome was overall survival (OS).
Two hundred and forty-six patients received lymph node dissection during the surgery. Of the patients, 24 (10%) had pathologically confirmed positive LN. Multivariate Cox regression model showed that positive LN was an independent unfavorable predictor for OS (HR = 2.83, 95%CI = 1.14-6.98, P = 0.024). More importantly, LN(-) patients with at least three LNs dissected had significantly better OS compared with when 1-2 LNs were examined (P = 0.048). Multivariate analysis confirmed that in LN(-) patients, the examination of three or more LNs could independently predict better OS compared with patients with only 1-2 LNs dissected (HR≥3LNs = 0.362, 95% CI = 0.135-0.972, P = 0.044). Additionally, the likelihood of finding at least one positive LN was significantly higher on dissection of ≥3 LNs compared with examination of 1-2 LNs (15% vs 5%, P = 0.018). Decision curve analysis found a better clinical validity of the '3 LNs examined'-based classification compared with the traditional LN(-)/LN(+) classification.
The proportion of positive LNs in chRCC was far from neglectable and LN metastasis could independently predict unfavorable OS. We recommended a minimum of three LNs should be pathologically examined in order to reliably determine node negative. OBJECTIVETo evaluate the prognostic value of lymph node (LN) involvement for patients with chromophobe renal cell carcinoma (chRCC) and ascertain the minimum number of LNs that need to be pathologically examined to reliably diagnose a patient with node negative chRCC. METHODSFrom 2004 to 2014, non-metastatic chRCC patients receiving radical nephrectomy together with lymphadenectomy were identified from the Surveillance, Epidemiology and End Results (SEER) database. The primary outcome was overall survival (OS). RESULTSTwo hundred and forty-six patients received lymph node dissection during the surgery. Of the patients, 24 (10%) had pathologically confirmed positive LN. Multivariate Cox regression model showed that positive LN was an independent unfavorable predictor for OS (HR = 2.83, 95%CI = 1.14-6.98, P = 0.024). More importantly, LN(-) patients with at least three LNs dissected had significantly better OS compared with when 1-2 LNs were examined (P = 0.048). Multivariate analysis confirmed that in LN(-) patients, the examination of three or more LNs could independently predict better OS compared with patients with only 1-2 LNs dissected (HR≥3LNs = 0.362, 95% CI = 0.135-0.972, P = 0.044). Additionally, the likelihood of finding at least one positive LN was significantly higher on dissection of ≥3 LNs compared with examination of 1-2 LNs (15% vs 5%, P = 0.018). Decision curve analysis found a better clinical validity of the '3 LNs examined'-based classification compared with the traditional LN(-)/LN(+) classification. CONCLUSIONThe proportion of positive LNs in chRCC was far from neglectable and LN metastasis could independently predict unfavorable OS. We recommended a minimum of three LNs should be pathologically examined in order to reliably determine node negative. |
Author | Shen, Yifan Chen, Shanwen Zhang, Minguang Ding, Qiang Wang, Xianjin Dong, Fan Peng, Xiaoqiong Xu, Liqi Zhong, Shan Zhang, Xiaohua Xu, Tianyuan Gao, Fengbin |
Author_xml | – sequence: 1 givenname: Fan surname: Dong fullname: Dong, Fan organization: Department of Urology, Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai – sequence: 2 givenname: Liqi surname: Xu fullname: Xu, Liqi organization: Department of Urology, No.113 Hospital of PLA, Ningbo, Zhejiang – sequence: 3 givenname: Xiaoqiong surname: Peng fullname: Peng, Xiaoqiong organization: Department of Urology, Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai – sequence: 4 givenname: Tianyuan surname: Xu fullname: Xu, Tianyuan organization: Department of Urology, Shanghai Tenth People's Hospital, Tongji University, Shanghai – sequence: 5 givenname: Yifan surname: Shen fullname: Shen, Yifan organization: Department of Urology, Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai – sequence: 6 givenname: Fengbin surname: Gao fullname: Gao, Fengbin organization: Department of Urology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China – sequence: 7 givenname: Xianjin surname: Wang fullname: Wang, Xianjin organization: Department of Urology, Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai – sequence: 8 givenname: Xiaohua surname: Zhang fullname: Zhang, Xiaohua organization: Department of Urology, Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai – sequence: 9 givenname: Shanwen surname: Chen fullname: Chen, Shanwen organization: Department of Urology, Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai – sequence: 10 givenname: Minguang surname: Zhang fullname: Zhang, Minguang organization: Department of Urology, Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai – sequence: 11 givenname: Shan surname: Zhong fullname: Zhong, Shan organization: Department of Urology, Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai – sequence: 12 givenname: Qiang surname: Ding fullname: Ding, Qiang organization: Department of Urology, Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai |
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