Literature DB >> 22805163

Accurate preoperative prediction of non-organ-confined bladder urothelial carcinoma at cystectomy.

David A Green1, Michael Rink, Jens Hansen, Eugene K Cha, Brian Robinson, Zhe Tian, Felix K Chun, Scott Tagawa, Pierre I Karakiewicz, Margit Fisch, Douglas S Scherr, Shahrokh F Shariat.   

Abstract

UNLABELLED: WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: Upstaging to non-organ-confined (NOC) disease is frequent at the time of radical cystectomy for urothelial carcinoma of the bladder (UCB). Pre-surgical models that can accurately predict which patients are likely to have more extensive disease are sparse. The present study developed an accurate nomogram for the prediction of NOC-UCB based on a cohort of patients with clinically organ-confined disease. Adoption of such a tool into daily clinical decision-making may lead to more appropriate integration of perioperative chemotherapy, thereby potentially improving survival in patients with UCB.
OBJECTIVE: To create an accurate pre-cystectomy decision-making tool that allows for the accurate identification of patients with clinically organ-confined urothelial carcinoma of the bladder (UCB) who have non-organ-confined UCB (NOC-UCB) at cystectomy, as identification of patients with UCB most likely to benefit from neoadjuvant chemotherapy (NACTx) is hampered by inaccurate clinical staging. PATIENTS AND METHODS: A prospectively maintained single-institution database containing 201 patients who underwent cystectomy and pelvic lymph node (LN) dissection without NACTx for UCB was analysed. Predictive variables for NOC-UCB included, among others, age, gender, transurethral resection of bladder tumour (TURBT) findings (stage, grade, histology, size, presence of carcinoma in situ, lymphovascular invasion [LVI], multifocality), history of intravesical therapy, time from TURBT to cystectomy, and cross-sectional imaging findings.
RESULTS: Clinical stage distribution was 19 patients with Ta, 15 with Tis, 67 with T1, and 100 with T2. At the time of cystectomy, NOC-UCB and LN-positive disease were found in 71 (35%) and 38 (19%) of patients, respectively; 81 (40%) of patients had NOC-UCB (≥pT3/Nany or pTany/N+). Tumour stage (P [trend] <0.001), presence of LVI (odds ratio [OR] 5.2; P = 0.02), and radiographic evidence of NOC-UCB or hydronephrosis (OR 3.2; P = 0.01) were independently associated with ≥pT3 Nany UCB. Tumour stage (P [trend] < 0.001) and presence of LVI (OR 6.64; P = 0.01) were independently associated with (≥pT3/Nany or pTany/N+) UCB. A nomogram to predict (≥pT3/Nany or pTany/N+) based on all three variables was highly accurate (area under the curve 0.828) and well calibrated, deviating <8% from ideal prediction. Decision curve analysis showed net benefit across all threshold probabilities.
CONCLUSIONS: NOC-UCB can be predicted with high accuracy by integrating standard clinicopathological factors with imaging information. This model may help to identify patients with NOC-UCB who may benefit from NACTx.
© 2012 BJU International.

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Mesh:

Year:  2012        PMID: 22805163     DOI: 10.1111/j.1464-410X.2012.11370.x

Source DB:  PubMed          Journal:  BJU Int        ISSN: 1464-4096            Impact factor:   5.588


  12 in total

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2.  Accuracy and prognostic value of variant histology and lymphovascular invasion at transurethral resection of bladder.

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5.  Scoring system for prediction of lymph node metastasis in radical cystectomy cohort.

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7.  Upregulation of Arp2 expression is associated with the prognosis and prediction of lymph node metastasis in bladder urothelial carcinoma.

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Authors:  Zijian Tian; Lingfeng Meng; Xin Wang; Tongxiang Diao; Maolin Hu; Miao Wang; Yaqun Zhang; Ming Liu
Journal:  Front Oncol       Date:  2021-06-16       Impact factor: 6.244

10.  Concordance in Biomarker Status Between Bladder Tumors at Time of Transurethral Resection and Subsequent Radical Cystectomy: Results of a 5-year Prospective Study.

Authors:  Niccolò M Passoni; Shahrokh F Shariat; Aditya Bagrodia; Franto Francis; Varun Rachakonda; Evanguelos Xylinas; Payal Kapur; Arthur I Sagalowsky; Yair Lotan
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