Journal of Peking University (Health Sciences) ›› 2022, Vol. 54 ›› Issue (4): 669-673. doi: 10.19723/j.issn.1671-167X.2022.04.014

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Optimal surveillance intensity of cystoscopy in intermediate-risk non-muscle invasive bladder cancer

Fei WANG,Cai-peng QIN,Yi-qing DU,Shi-jun LIU,Qing LI,Tao XU*()   

  1. Department of Urology, Peking University People's Hospital, Beijing 100044, China
  • Received:2022-03-28 Online:2022-08-18 Published:2022-08-11
  • Contact: Tao XU E-mail:xutao@pkuph.edu.com
  • Supported by:
    National Natural Science Foundation of China(81802533);National Key Research and Development Program of China(2018YFA0902802);Beijing Natural Science Foundation of China(7202219);Beijing Municipal Science & Technology Commission(Z191100006619010)

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Abstract:

Objective: To determine the optimal cystoscopic frequency for intermediate-risk non-muscle invasive bladder cancer. Methods: Patients with intermediate-risk non-muscle invasive bladder cancer, who underwent transurethral resection of bladder tumor in Peking University People's Hospital from January 2001 to October 2019, were retrospectively analyzed. Their clinical, pathological and follow-up data were collected. In postoperative 2-year period, the patients were underwent cystoscopy every 3 to 6 months. Depending on recurrence and progression of the patients, we hypothesized three strategies of surveillance intensity in the first 2 years after surgery: model 1: 3-month intervals, model 2: 6-month intervals, and model 3: 12-month intervals. The differences in the numbers and time of delayed detection of recurrence and progression were compared among the three models. Results: A total of 185 patients were enrolled, including 144 males (77.8%) and 41 females (22.2%). The median age was 68 (59-76) years. There were 118 cases (63.8%) with single tumor and 67 cases (36.2%) with multiple tumor. Of the patients 179 (96.8%) had stage Ta and 6 (3.2%) had stage T1. There were 108 cases (58.4%) with high-grade disease and 77 cases (41.6%) with low-grade disease. During the follow-up period of the first 2 years, 52 patients (28.1%) had recurrence, 133 cases (71.9%) had no recurrence, 11 cases (5.9%) had progression and 174 cases (94.1%) had no progression. Compared with model 1, 29 (55.8%) delayed detection of recurrence in model 2 vs. 41 (78.8%) delayed detection of recurrence in model 3, and the difference was statistically significant (P=0.012). The median delayed time of detecting recurrence was 1.00 months in model 1, 1.99 months in model 2 and 4.19 months in model 3, respectively. There were statistically significant differences between mode 1 and model 3 (P=0.001), and between model 2 and model 3 (P=0.013). Compared with model 1, 5 (45.4%) delayed detection of progression in model 2 vs. 8 (72.7%) delayed detection of progression in model 3, and the difference was not statistically significant. The median delayed time of detecting progression was 1.00 month in model 1, 2.00 months in model 2 and 3.00 months in model 3, respectively. There was no statistically significant difference among them. Conclusion: Although providing slightly slower detection of tumor recurrence and progression, compared with 3-month intervals of cystoscopy, 6-month intervals do not result in serious adverse outcomes and reduce cost and pain of the patients, which is feasible in intermediate-risk non-muscle invasive bladder cancer.

Key words: Bladder cancer, Cystoscopy, Follow-up, Surveillance intensity

CLC Number: 

  • R737.1

Table 1

Clinical, tumor and treatment characteristics of patients"

Variables n %
All patients 185 100.0
Gender
  Female 41 22.2
  Male 144 77.8
Age/years
  ≤65 82 44.3
  >65 103 55.7
Smoking history
  No 132 71.4
  Yes 53 28.6
Tumor number
  1 118 63.8
  2 31 16.8
  3 12 6.5
  4 3 1.6
  5 2 1.0
  >5 19 11.3
Tumor size
  ≤3 cm 166 89.7
  >3 cm 13 7.0
Unknown 6 3.3
T stage
  T1 6 3.2
  Ta 179 96.8
Grade
  LG 77 41.6
  HG 108 58.4
Immediate single instillation
  No 54 29.2
  Yes 131 70.8
Adjuvant intravesical therapy
  Epirubicin 30 16.2
  Pirarubicin 118 63.8
  Other 13 7.0
  Unknown 24 13.0

Figure 1

Time of recurrence for 52 patients"

Figure 2

Delayed time of detecting recurrence for 3 models"

Figure 3

Time of progression for 11 patients"

Figure 4

Delayed time of detecting progression for 3 models"

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