In this context, a long-term follow-up study showed that patients with low grade T1/Ta NMIBC managed with active surveillance (AS) had a treatment-free probability at 12, 18, 24, and 36 months of 59.7%, 54.5%, 46.3%, and 40.4%, respectively. Patients with history of multiple transurethral resections of bladder tumors (TURBT) and multifocality at the time of diagnosis had a significantly higher risk of experiencing AS failure. In those patients that required conversion to treatment, the final pathology showed benign conditions in 19.2% of the cases. Conversely, TaLG was identified in 70.7% of resections, while 9.2% of patients had high-grade Ta/T1 recurrence, and only 0.7% had muscle-invasive disease.8 This evidence led the European Urological Association guidelines to consider AS as an alternative to TURBT or office-based fulguration. Still, it also acknowledged the lack of well-designed studies to provide a stronger recommendation.2
Collectively, this highlights the critical need for a risk-based approach when we follow and treat these patients, which are exposed to financial burden and inherent risks of in-office cystoscopies and TURBTs. In our study, we developed a model using data from 202 TaLG NMIBC patients from a population based dataset with long-term follow up.
We performed a classification tree analysis that identified risk groups associated with recurrence. Kaplan Meier analysis was performed using the risk groups defined by the regression tree and to predict the independent association of the risk factors selected by the regression tree analysis, we fit a Cox proportional hazard model using the variables and cutoffs defining the risk groups. Then, we created a nomogram to manually obtain the predicted values from the Cox proportional hazard model. We evaluated the performance of our model using a Decision curve analysis (DCA) to estimate our model’s net benefit and a net reduction in interventions per 100 patients and compare it against the AUA/EUA models across the evaluated time points.
The classification tree found that tumor number (single or multiple), tumor size (< 4 cm vs ≥ 4 cm), and age (< 48, 48 –71, ≥ 72) were the most relevant variables associated with recurrence (Figure 1). The patients with the lowest RFS were those with multifocal or single ≥ 4 cm tumors. In this context, patients with multifocal tumors (27%) had a 93% probability of recurrence while those with single ≥ 4 cm tumors (8%) had a 92% probability of recurrence in a median follow-up of 139 months. Conversely, a small group of patients younger than 48 years old and with a single < 4 cm tumor (3%) were recurrence free at 170 months. Kaplan Meier analysis showed significant differences in RFS between all the risk groups created by the classification tree regression except when comparing the multifocal and single ≥ 4 cm tumor groups. Moreover, the probability of RFS of the patients with single < 4 cm tumors was > 90% at four months regardless of the age group (Figure 2).
Figure 1
Figure 2
The categorical variables selected by the classification tree were used to fit a Cox proportional hazard model to evaluate the association of such variables with RFS at 6, 12, 18 and 24 months. We found that age at diagnosis (< 48, 48–71, ≥ 72), tumor size (<4 vs ≥4cm) and number of tumors (single vs multiple) were significantly associated with RFS (Figure 3). DCA analysis revealed that our model outperformed the AUA/EAU stratification and the treat all/none approaches by displaying a higher net benefit and net reduction in interventions per 100 patients across all the timepoints evaluated.
Figure 3
Our analysis identified TaLG patients that are at a higher risk of recurrence and found risk factors associated with RFS. We developed a nomogram to estimate risk of recurrence which if externally validated will decrease the frequency of in-office cystoscopy which will impact surveillance recommendations in these patients.
Written by: Jorge Daza, MD, Society of Urologic Oncology Fellow, Department of Urology, Roswell Park Cancer Center, Buffalo, NY & John P. Sfakianos, MD, Associate Professor, Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY
References
- Aldousari S, Kassouf W. Update on the management of non-muscle invasive bladder cancer. Can Urol Assoc J. 2010;4(1):56-64.
- EAU Guidelines. Edn.presented at the EAU Annual Congress Milan 2023.
- Heney NM, Ahmed S, Flanagan MJ, Frable W, Corder MP, Hafermann MD, et al. Superficial bladder cancer: progression and recurrence. The Journal of urology. 1983;130(6):1083-6.
- Herr HW. Tumor progression and survival of patients with high grade, noninvasive papillary (TaG3) bladder tumors: 15-year outcome. The Journal of urology. 2000;163(1):60-1; discussion 1-2.
- Montironi R, Lopez-Beltran A. The 2004 WHO classification of bladder tumors: a summary and commentary. Int J Surg Pathol. 2005;13(2):143-53.
- Nerli RB, Ghagane SC, Shankar K, Sanikop AC, Hiremath MB, Dixit NS, et al. Low-Grade, Multiple, Ta Non-muscle-Invasive Bladder Tumors: Tumor Recurrence and Worsening Progression. Indian J Surg Oncol. 2018;9(2):157-61.
- Prout GR, Jr., Barton BA, Griffin PP, Friedell GH. Treated history of noninvasive grade 1 transitional cell carcinoma. The National Bladder Cancer Group. The Journal of urology. 1992;148(5):1413-9.
- Contieri R, Paciotti M, Lughezzani G, Buffi NM, Frego N, Diana P, et al. Long-term Follow-up and Factors Associated with Active Surveillance Failure for Patients with Non-muscle-invasive Bladder Cancer: The Bladder Cancer Italian Active Surveillance (BIAS) Experience. Eur Urol Oncol. 2022;5(2):251-5.