The introduction of Bacillus Calmette-Guérin (BCG) therapy has been a pivotal advancement for intermediate- and high-risk NMIBC patients, reducing recurrence and progression risks.2 However, the efficacy of BCG therapy can be influenced by systemic inflammation and external factors such as smoking, necessitating an in-depth understanding of these interactions to refine patient risk stratification and treatment strategies.
Our multicenter retrospective study evaluated 1,313 T1G3 NMIBC patients treated with BCG instillations following transurethral resection of bladder tumors (TURBT).3 Using a machine-learning approach based on Classification and Regression Trees (CART), we aimed to assess the impact of smoking and systemic inflammatory markers, including lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), on disease progression.
Patients were classified into three prognostic clusters using the CART algorithm: low-risk non-smokers with PLR ≤ 156, intermediate-risk non-smokers with PLR > 156 or smokers with PLR ≤ 187 and LMR > 1.86, and high-risk smokers with PLR > 187 or LMR ≤ 1.86.
Kaplan-Meier survival analysis showed a significant difference in five-year progression-free survival (PFS): 86% in the low-risk group, 73% in the intermediate-risk group, and 56% in the high-risk group. Smoking emerged as a critical variable associated with increased systemic inflammation and poorer BCG response. Cox regression analyses confirmed a 1.5-fold (HR 1.66) and three-fold (HR 2.99) higher risk of progression in intermediate- and high-risk clusters, respectively, compared to the low-risk group.
Elevated inflammatory ratios (NLR, LMR, PLR) were strongly correlated with disease progression, underscoring their potential as biomarkers for risk stratification. Smoking intensified these effects, highlighting its role in exacerbating systemic inflammation and impairing the immune response to BCG.
Our findings emphasize the necessity of incorporating smoking status and inflammatory markers into existing risk stratification models for NMIBC. The use of CART algorithms enables a nuanced understanding of patient-specific risk, fostering informed decision-making and personalized treatment strategies. Furthermore, these results advocate for smoking cessation programs as an integral component of comprehensive BCa management. While our study provides valuable insights, its retrospective nature and the exclusion of certain variables such as genetic factors and environmental exposures limit its generalizability. Prospective, multicenter studies with larger cohorts are warranted to validate these findings and explore the potential benefits of integrating smoking cessation into NMIBC therapeutic protocols.
Leveraging machine-learning tools like CART enhances our ability to predict NMIBC outcomes and optimize therapeutic approaches, particularly by accounting for modifiable risk factors such as smoking. This study contributes to a growing body of evidence supporting the interplay between systemic inflammation, smoking, and cancer progression, reinforcing the importance of targeted interventions in high-risk populations.
Written by: Giuseppe Fallara, MD & Prof. Matteo Ferro, MD, PhD, Unit of Urology, Department of Health Science, University of Milan, ASST Santi Paolo e Carlo, Milan, Italy
References:
- Babjuk M, Burger M, Capoun O, Cohen D, Compérat EM, Dominguez Escrig JL, et al. European Association of Urology Guidelines on Non-muscle-invasive Bladder Cancer (Ta, T1, and Carcinoma in Situ). Eur Urol 2022;81:75–94.
- Kamat AM, Hahn NM, Efstathiou JA, Lerner SP, Malmström PU, Choi W, et al. Bladder cancer. Lancet 2016;388:2796–810.
- Ferro M, Tataru OS, Fallara G, et al. Assessing the influence of smoking on inflammatory markers in bacillus Calmette Guérin response among bladder cancer patients: a novel machine-learning approach. Minerva Urol Nephrol. Published online December 3, 2024. doi:10.23736/S2724-6051.24.05876-2