pT1 Subclassification Predicts Progression-Free Survival in En Bloc Resection of Bladder Tumor Specimens.
Arch Pathol Lab Med
; 2023 Sep 05.
Article
en En
| MEDLINE
| ID: mdl-37671794
CONTEXT.: The pathologic diagnosis of pT1 substage in conventional transurethral resection of bladder tumor specimens is inaccurate and has low interobserver reproducibility owing to fragmentation and cauterization of the specimens. En bloc resection of bladder tumor is a novel surgical procedure that improves diagnostic feasibility and accuracy in the pathologic diagnosis of bladder cancer, including depth and extent of invasion. OBJECTIVE.: To examine the prognostic value of multiple pT1 subclassification methods, using only en bloc resection specimens. DESIGN.: We examined 106 patients with T1 bladder cancer who underwent en bloc resection. The pT1 substages were assigned by 3 different subclassification methods by using the muscularis mucosae or stalk of the papillary lesion as diagnostic landmarks or millimetric depth of invasion. Intergroup differences in progression-free survival and recurrence-free survival rates were analyzed. The prognostic values of clinicopathologic factors for progression/recurrence were analyzed by using multivariate analysis. RESULTS.: The pT1 substage was evaluable in all cases. Tumors with invasion into/beyond the muscularis mucosae and those beyond the stalk of the papillary lesion were associated with worse progression-free survival (P = .002 and P = .01, respectively). Notably, no patient with invasion confined to the stalk had disease progression during the 23-month median follow-up period. Only the pT1 subclassification method using the muscularis mucosae was an independent prognosticator of progression in multivariate analysis (P = .03). CONCLUSIONS.: Precise pathologic subclassification of invasion using en bloc resection specimens may enable accurate prognosis and assessment in patients with bladder cancer with suspicious shallow invasion.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Arch Pathol Lab Med
Año:
2023
Tipo del documento:
Article
País de afiliación:
Japón