Computed-tomography based scoring system predicts outcome for clinical lymph node-positive patients undergoing radical cystectomy.

Contrast-enhanced CT scan is the standard staging modality for patients with bladder cancer undergoing radical cystectomy (RC). Involvement of lymph nodes (LN) determines prognosis of patients with bladder cancer. The detection of LN metastasis by CT scan is still insufficient. Therefore, we investigated various CT scan characteristics to predict lymph node ratio (LNR) and its impact on survival. Also, pre-operative CT scan characteristics might hold potential to risk stratify cN+ patients.

We analyzed preoperative CT scans of patients undergoing RC in a tertiary high volume center. Retrospectively, local tumor stage and LN characteristics such as size, morphology (MLN) and number of loco-regional LN (NLN) were investigated and correlation to LNR and survival was analyzed. CT scan characteristics were used to develop a risk stratification using Kaplan-Maier and multivariate analysis.

764 cN0 and 166 cN+ patients with complete follow-up and imaging data were included in the study. Accuracy to detect LN metastasis and locally advanced tumor stage in CT scan was 72% and 62%. LN larger than 15mm in diameter were significantly associated with higher LNR (p=0.002). Increased NLN correlated with decreased CSS and OS (p=0.001: p=0.002). Furthermore, CT scan based scoring system precisely differentiates low-risk and high-risk profiles to predict oncological outcome (p < 0.001).

In our study, solely LN size >15mm significantly correlated with higher LNR. Identification of increased loco-regional LN was associated with worse survival. For the first time, precise risk stratification based on computed-tomography findings was developed to predict oncological outcome for clinical lymph node-positive patients undergoing RC.

International braz j urol : official journal of the Brazilian Society of Urology. 2021 Sep 10 [Epub ahead of print]

Lennert Eismann, Severin Rodler, Alexander Tamalunas, Gerald Schulz, Friedrich Jokisch, Yannic Volz, Paulo Pfitzinger, Boris Schlenker, Christian Stief, Olga Solyanik, Alexander Buchner, Tobias Grimm

Department of Urology, Ludwig-Maximilians-University, Munich, Germany., Department of Radiology, Ludwig-Maximilians-University, Munich, Germany.

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