Ferro Matteo, Tataru Octavian S, Fallara Giuseppe, Fiori Cristian, Manfredi Matteo, Claps Francesco, Hurle Rodolfo, Buffi Nicolò M, Lughezzani Giovanni, Lazzeri Massimo, Aveta Achille, Pandolfo Savio D, Barone Biagio, Crocetto Felice, Ditonno Pasquale, Lucarelli Giuseppe, Lasorsa Francesco, Carrieri Giuseppe, Busetto Gian M, Falagario Ugo G, Del Giudice Francesco, Maggi Martina, Cantiello Francesco, Borghesi Marco, Terrone Carlo, Bove Pierluigi, Antonelli Alessandro, Veccia Alessandro, Mari Andrea, Luzzago Stefano, Gherasim Raul, Todea-Moga Ciprian, Minervini Andrea, Musi Gennaro, Mistretta Francesco A, Bianchi Roberto, Tozzi Marco, Soria Francesco, Gontero Paolo, Marchioni Michele, Janello Letizia M, Terracciano Daniela, Russo Giorgio I, Schips Luigi, Perdonà Sisto, Autorino Riccardo, Catellani Michele, Sighinolfi Chiara, Montanari Emanuele, DI Stasi Savino M, Porpiglia Francesco, Rocco Bernardo, de Cobelli Ottavio, Contieri Roberto
Unit of Urology, Department of Health Science, University of Milan, ASST Santi Paolo e Carlo, Milan, Italy -
I.O.S.U.D., George Emil Palade University of Medicine, Pharmacy, Sciences, and Technology from Targu Mures, Targu Mures, Romania.
Minerva Urol Nephrol. 2024 Dec 3. doi: 10.23736/S2724-6051.24.05876-2.
Approximately 70% of bladder cancer is diagnosed as non-muscle invasive (NMIBC) and inflammation is known to impact the oncological outcomes. Adjuvant intravesical BCG in intermediate/high risk can lower recurrence and progression. The efficacy of intravesical BCG can be impacted by smoking effects on systemic inflammation.
Our retrospective, multicenter study with data from 1.313 NMIBC patients aimed to assess the impact of smoking and the systemic inflammatory status on BCG response in T1G3 bladder cancer, using a machine-learning CART based algorithm.
In a median of 50-month follow-up (IQR 41-75), 344 patients experienced progression to muscle invasive or metastatic disease and 65 died due to bladder cancer. A CART algorithm has been employed to stratify patients in three prognostic clusters using smoking status, LMR (lymphocytes to monocytes ratio), NLR (neutrophil-to-lymphocyte ratio) and PLR (platelet-to-lymphocyte ratio) as variables. Cox regression models revealed a 1.5-fold (HR 1.66, 95%, CI 1.20-2.29, P=0.002) and three-fold (HR 2.99, 95% CI 2.08-4.30, P<0.001) risk of progression, in intermediate and high risk NMIBC respectively, compared to the low-risk group. The model's concordance index was 0.66.
Our study provides an insight into the influence of smoking on inflammatory markers and BCG response in NMIBC patients. Our machine-learning approach provides clinicians a valuable tool for risk stratification, treatment, and decision-making. Future research in larger prospective cohorts is required for validating these findings.
大约70%的膀胱癌被诊断为非肌层浸润性（NMIBC），已知炎症会影响肿瘤学结局。中/高危患者辅助膀胱内灌注卡介苗（BCG）可降低复发和进展风险。吸烟对全身炎症的影响可能会影响膀胱内灌注BCG的疗效。
我们的回顾性多中心研究纳入了1313例NMIBC患者的数据，旨在使用基于机器学习CART算法评估吸烟和全身炎症状态对T1G3膀胱癌患者BCG反应的影响。
在中位50个月的随访期（四分位间距41 - 75个月）内，344例患者进展为肌层浸润性或转移性疾病，65例死于膀胱癌。采用CART算法，将吸烟状态、淋巴细胞与单核细胞比值（LMR）、中性粒细胞与淋巴细胞比值（NLR）和血小板与淋巴细胞比值（PLR）作为变量，将患者分为三个预后组。Cox回归模型显示，与低风险组相比，中危和高危NMIBC患者进展风险分别增加1.5倍（风险比[HR] 1.66，95%置信区间[CI] 1.20 - 2.29，P = 0.002）和3倍（HR 2.99，95% CI 2.08 - 4.30，P < 0.001）。该模型的一致性指数为0.66。
我们的研究深入了解了吸烟对NMIBC患者炎症标志物和BCG反应的影响。我们的机器学习方法为临床医生提供了一个用于风险分层、治疗和决策的有价值工具。需要在更大的前瞻性队列中进行进一步研究以验证这些发现。
