Section 37
Chapter 36,951

When to perform lymph node dissection in patients with renal cell carcinoma: a novel approach to the preoperative assessment of risk of lymph node invasion at surgery and of lymph node progression during follow-up

Capitanio, U.; Abdollah, F.; Matloob, R.; Suardi, N.; Castiglione, F.; Di Trapani, E.; Capogrosso, P.; Gallina, A.; Dell'Oglio, P.; Briganti, A.; Salonia, A.; Montorsi, F.; Bertini, R.

Bju International 112(2): E59-E66


ISSN/ISBN: 1464-4096
PMID: 23795799
DOI: 10.1111/bju.12125
Accession: 036950292

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To identify preoperatively patients who might benefit from lymph node dissection (LND). We assessed lymph node invasion (LNI) at final pathology and lymph node (LN) progression during the follow-up for 1983 patients with RCC, treated with either partial or radical nephrectomy. LN progression was defined as the onset of a new clinically detected lymphadenopathy (>10 mm) in the retroperitoneal lymphatic area. Logistic regression analyses were used to assess the effect of each potential clinical predictor (age, body mass index, tumour side, symptoms, performance status, clinical tumour size, clinical tumour-node-metastasis stage, and albumin, calcium, creatinine, haemoglobin and platelet levels) on the outcome of interest. The most parsimonious multivariable predictive model was developed, and discrimination, calibration and net benefit were calculated. The prevalence of LNI was 6.1% (120/1983 patients) and during the follow-up period, 82 patients (4.1%) experienced LN progression. On multivariable analyses, the most informative independent predictors were tumour stage (cT3-4 vs cT1-2, odds ratio [OR] 1.52, P = 0.05), clinical nodal status [cN1 vs cN0, OR 7.09, P < 0.001], metastases at diagnosis (OR 3.04, P < 0.001) and clinical tumour size (OR 1.14, P < 0.001). The accuracy of the multivariable model was found to be 86.9%, with excellent calibration and net benefit at decision-curve analyses. By relying on a unique approach, combining the risk of harbouring LNI and/or LN progression during the follow-up period, we have provided the first clinical presurgery model predicting the need for LND.

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