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Research Article | Volume 12 Issue 1 (Jan, 2026) | Pages 594 - 600
Diagnostic Accuracy of Urinary Cytology Compared with Histopathology in Transitional Cell Carcinoma of the Urinary Bladder: A Prospective Observational Study
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1
Final year Post graduate, Department of Urology, Gandhi Medical College and Gandhi Hospital, Hyderabad, Telangana, India
2
Assistant Professor, Department of Urology, Gandhi Medical College and Gandhi Hospital, Hyderabad, Telangana, India
3
Head of the department, Department of Urology, Gandhi Medical College and Gandhi Hospital, Hyderabad, Telangana, India
4
Post graduate, Department of Urology, Gandhi Medical College and Gandhi Hospital, Hyderabad, Telangana, India
5
Post graduate , Department of Urology, Gandhi Medical College and Gandhi Hospital, Hyderabad, Telangana.
Under a Creative Commons license
Open Access
Received
Jan. 8, 2026
Revised
Jan. 14, 2026
Accepted
Jan. 22, 2026
Published
Jan. 27, 2026
Abstract
Background: Urinary cytology is a widely used, non-invasive investigation for the detection and surveillance of urothelial carcinoma of the bladder. However, its diagnostic accuracy, particularly in low-grade tumours, remains controversial. Objectives: To evaluate the diagnostic performance of urinary cytology and to correlate cytological findings with histopathological examination in patients with transitional cell carcinoma (TCC) of the urinary bladder. Materials and Methods: This prospective observational study was conducted at a tertiary care centre from July 2023 to June 2025. Voided urine samples from 59 patients with suspected bladder tumours were analysed using the Paris System for Reporting Urinary Cytology. All patients subsequently underwent transurethral resection of bladder tumour (TURBT), and histopathological examination (HPE) served as the reference standard. Sensitivity, specificity, predictive values, diagnostic accuracy, and kappa agreement were calculated. Results: Of the 59 patients, histopathology confirmed urothelial carcinoma in 56 cases (94.9%). Urinary cytology was positive in 15 cases (25.4%). The sensitivity, specificity, positive predictive value, negative predictive value, and overall diagnostic accuracy of urine cytology were 25.0%, 66.7%, 93.3%, 4.6%, and 27.1%, respectively. Agreement between cytology and histopathology was poor (κ = −0.011, p = 0.747). Cytology demonstrated better performance in high-grade tumours compared to low-grade lesions. Conclusion: Urinary cytology demonstrates high specificity and positive predictive value for the detection of urothelial carcinoma of the bladder; however, its low sensitivity and poor negative predictive value limit its utility as a standalone diagnostic modality. Cytology is most effective as an adjunct to cystoscopy and histopathology, particularly for confirmation and surveillance of high-grade disease. Negative cytological findings should not preclude further evaluation when clinical suspicion persists.
Keywords
INTRODUCTION
Bladder cancer is one of the most common malignancies of the urinary tract and represents a significant global health burden. It is the fourth most common cancer in men, accounting for approximately 6% of all malignancies, and the tenth most common cancer in women, contributing nearly 2% of cases. Bladder cancer accounts for about 3% of cancer-related deaths in men. Urothelial carcinoma, also referred to as transitional cell carcinoma (TCC), constitutes the majority of bladder cancers. Due to its recurrent nature and risk of progression, bladder cancer necessitates accurate diagnostic methods and long-term surveillance(1). Cystoscopy with histopathological examination remains the gold standard for the diagnosis of urothelial carcinoma. However, nearly 70–75% of bladder cancers are non–muscle invasive at presentation and are managed with bladder preservation strategies. These patients require lifelong surveillance with repeated cystoscopies and biopsies, which are invasive, costly, and associated with patient discomfort. Furthermore, tumour progression from low-grade to high-grade disease may occur between follow-up visits, underscoring the need for reliable, non-invasive adjunctive diagnostic tools(2). Urinary cytology is a well-established, non-invasive investigation widely used for screening and follow-up of patients with bladder tumours. It plays an important role in the multidisciplinary diagnostic approach to bladder cancer and serves as a valuable adjunct to cystoscopy and biopsy. Cytological examination of voided urine offers the advantage of sampling the entire urothelial lining, allowing detection of occult lesions that may not be visible on cystoscopy(3). In addition, urine cytology is inexpensive, easily repeatable, and feasible in resource-limited settings, making it particularly relevant in developing countries(3). Urinary cytology has traditionally been regarded as the gold standard among non-invasive tests for bladder cancer detection(2). It demonstrates high specificity and good sensitivity for high-grade urothelial carcinoma, with reported sensitivity ranging from 60% to 90%. In contrast, although specificity for low-grade tumours may be as high as 98%, sensitivity remains low and highly variable, ranging from 0% to 50%. This limitation significantly restricts its role as a standalone diagnostic modality, particularly for low-grade lesions. The prognostic value of conventional urine cytology in monitoring patients with superficial bladder carcinoma is well recognised. While cystoscopy and biopsy remain gold standard for detecting visible disease(1), cytology allows continuous assessment of the entire urothelium and facilitates early detection of high-grade recurrences and carcinoma in situ. However, interpretation of cytological findings especially atypical urothelial cells continues to pose diagnostic challenges, as reactive and degenerative changes may mimic malignancy(4). Despite advances in molecular diagnostics and urinary biomarkers, cytomorphological evaluation remains an integral component of bladder cancer assessment. Given the variability in reported diagnostic performance and the evolving role of standardised reporting systems, it is essential to reassess the accuracy of urine cytology in contemporary clinical practice. The present study was therefore undertaken to correlate urinary cytology findings with final histopathological examination in patients undergoing transurethral resection of bladder tumour (TURBT), with the aim of evaluating its diagnostic utility and potential role in optimising follow-up strategies, particularly for early detection of high-grade disease.
MATERIAL AND METHODS
Study Design and Population This prospective observational study was conducted in the Department of Urology in coordination with the Department of Pathology at a tertiary care teaching hospital between July 2023 and June 2025. A total of 59 patients aged over 18 years with radiologically or cystoscopically suspected bladder tumours were included. Inclusion and Exclusion Criteria Patients with bladder neoplasms detected on ultrasonography, cystoscopy, or computed tomography who were willing to participate in the study were included. Patients with haematuria due to causes other than bladder cancer, those with coagulopathies, prior intravesical therapy, or those unwilling to participate were excluded. Cytological Evaluation Freshly voided midstream urine samples were collected preoperatively, avoiding early morning specimens. Three consecutive samples were examined for each patient. Smears were prepared, stained using Papanicolaou and haematoxylin and eosin stains, and reported according to the Paris System for Reporting Urinary Cytology. Histopathological Examination All patients underwent TURBT, and resected specimens were subjected to routine histopathological examination using haematoxylin and eosin staining. Tumours were classified according to WHO/ISUP grading criteria. Statistical Analysis Cytological findings were compared with histopathological results. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were calculated. Agreement between cytology and histopathology was assessed using Cohen’s kappa statistic. A p-value <0.05 was considered statistically significant. Statistical analysis was performed using standard statistical software.
RESULTS
A total of 59 patients were included in the study. Of these, 44 patients (74.6%) were male and 15 patients (25.4%) were female, yielding a male-to-female ratio of approximately 3:1. The mean age of the study population was 57.75 ± 13.1 years (range: 32–81 years). The highest incidence was observed in the 60–69 year age group (32.2%), followed by the 40–49 year group (23.7%). Figure 1: Age distribution of the study population. Urinary Cytology Findings Preoperative urinary cytology was performed on voided urine samples and reported according to the Paris System for Reporting Urinary Cytology. Cytology was positive in 15 patients (25.4%) and negative in 44 patients (74.6%). Based on cytological grading, 6 patients (10.2%) were reported as having high-grade urothelial carcinoma, 9 patients (15.3%) as low-grade urothelial carcinoma, and 44 patients (74.6%) were negative for malignancy. Histopathological Findings Histopathological examination of TURBT specimens confirmed urothelial carcinoma in 56 patients (94.9%). Among these, 30 patients (50.8%) had high-grade urothelial carcinoma, while 26 patients (44.1%) had low-grade urothelial carcinoma. Three patients (5.1%) were negative for malignancy on histopathology. Correlation Between Cytology and Histopathology Correlation between urinary cytology and histopathology findings demonstrated limited concordance. Among the 30 patients with high-grade urothelial carcinoma on histopathology, cytology was positive in 10 cases (33.3%) and negative in 20 cases (66.7%). Of the 26 patients with low-grade urothelial carcinoma, cytology was positive in only 4 cases (15.4%) and negative in 22 cases (84.6%). Table 1: CYTOLOGY Total Positive Negative HPE High grade 10 (33.3%) 20(66.7) 30 Low grade 4(15.4%) 22(84.6%) 26 Negative 1 2 3 Total 15 44 59 χ² = 2.393, p = 0.122 (not significant) The above table shows the correlation of cases between HPE and cytology and this difference in distribution was not found to be statistically significant (P value >0.05). Among the three histopathologically negative cases, cytology was positive in one case and negative in two cases. Grade-wise Agreement Analysis Grade-wise comparison revealed poor agreement between cytology and histopathology. Of the 14 cytology-positive cases included for grade correlation, 6 were reported as high-grade and 8 as low-grade on cytology. Among cytology high-grade cases, 4 correlated with high-grade histopathology, while 2 were low grade on histopathology. Among cytology low-grade cases, 6 were histologically high grade and 2 were low grade. Overall agreement between cytological and histopathological grading was poor, with a Cohen’s kappa value of −0.011 (p = 0.747), indicating no significant agreement beyond chance. Diagnostic Performance of Urinary Cytology Using histopathology as the reference standard, the diagnostic performance of urinary cytology was assessed. Of the total cases analysed, there were 14 true positives, 1 false positive, 42 false negatives, and 2 true negatives. Table 2: Statistic Value 95% CI Sensitivity 25.00% 14.39% to 38.37% Specificity 66.67% 9.43% to 99.16% Positive Predictive Value 93.33% 72.62% to 98.66% Negative Predictive Value 4.55% 2.07% to 9.71% Accuracy 27.12% 16.36% to 40.27% Postoperative Cytology Findings Postoperative urinary cytology was correlated with final histopathological findings. Cytology was positive in 3 cases, all of which were histopathologically positive. Among the 56 cases with negative postoperative cytology, 53 had positive histopathology and 3 were negative. Agreement between postoperative cytology and histopathology remained poor (κ = 0.006, p = 0.681). Diagnostic Performance of Urine Cytology post TURBT: Statistic Value 95% CI Sensitivity 5.36% 1.12% to 14.87% Specificity 100.00% 29.24% to 100.00% Positive Predictive Value 100.00% 29.24% to 100.00% Negative Predictive Value 5.36% 5.05% to 5.68% Accuracy 10.17% 3.82% to 20.83%
DISCUSSION
Urinary cytology remains a widely used, non-invasive diagnostic modality for the detection and surveillance of urothelial carcinoma of the bladder. However, its diagnostic performance particularly for low-grade tumours continues to be a subject of debate. The present study evaluated the diagnostic accuracy of urinary cytology using the Paris System(5) and correlated cytological findings with histopathological examination following transurethral resection of bladder tumour (TURBT). In this study, urinary cytology demonstrated a low overall sensitivity of 25%, while maintaining a relatively high specificity of 66.7% and a high positive predictive value of 93.3%. These findings reaffirm the well-recognized limitation of urine cytology as a screening tool, particularly for low-grade urothelial carcinoma. Similar observations have been reported in earlier studies, which consistently demonstrate superior cytological detection rates for high-grade tumours compared to low-grade lesions. The low sensitivity observed in our study can be attributed to minimal cytological atypia and poor exfoliation of malignant cells in low-grade tumours, as well as masking of tumour cells by inflammation or hemorrhage. Among patients with histologically confirmed high-grade urothelial carcinoma, cytology was positive in only one-third of cases, while the detection rate for low-grade tumours was even lower. These findings are comparable to those reported by El-Bolkainy et al. and Koss et al.,(6,7) who demonstrated higher sensitivity for high-grade tumours but limited utility in detecting low-grade disease. Despite this limitation, the high positive predictive value observed in our study underscores the reliability of a positive cytological result in confirming malignancy, particularly in high-grade disease. The Paris System for Reporting Urinary Cytology(5) was employed in this study to improve diagnostic consistency and reduce equivocal reporting. Although this system emphasizes detection of high-grade urothelial carcinoma, our results indicate that its application did not significantly improve overall sensitivity or agreement with histopathology. The poor concordance between cytology and histopathology, reflected by a negative kappa value, highlights the inherent limitations of cytological grading and reinforces the need for complementary diagnostic approaches. Postoperative urinary cytology in our study demonstrated very low sensitivity but retained perfect specificity. This finding suggests that while a positive postoperative cytology result is highly predictive of residual or recurrent disease, a negative result does not reliably exclude ongoing malignancy. Similar observations have been reported in previous studies, indicating limited utility of postoperative cytology as a standalone surveillance tool. Recent advances in diagnostic technology have focused on improving the limitations of conventional urine cytology(8,9,10). Adjunctive investigations such as fluorescence in situ hybridization (FISH), nuclear matrix protein 22 (NMP22), telomerase activity assays, and bladder tumour antigen tests have shown improved sensitivity compared to cytology alone, though their routine use is limited by cost, availability, and variable specificity(10,11,12). More recently, artificial intelligence (AI)–based approaches have emerged as promising adjuncts in bladder cancer diagnostics(13,14). AI-driven image analysis and deep learning algorithms have demonstrated potential in improving the detection and classification of urothelial carcinoma by reducing observer variability and identifying subtle cytomorphological features. Preliminary studies suggest that AI-assisted cytology and digital pathology tools may enhance sensitivity for both high-grade and low-grade tumours. However, these technologies remain investigational, and large-scale validation studies are required before routine clinical implementation(15,16,17). The findings of the present study emphasize that urine cytology, despite its advantages of being non-invasive and cost-effective, cannot replace cystoscopy and histopathology. Instead, it should be used as an adjunctive tool, particularly for confirming high-grade disease and monitoring high-risk patients. Integration of adjunctive molecular markers and emerging AI-based diagnostic tools may help overcome current limitations and improve early detection in the future.
CONCLUSION
This study assessed the diagnostic performance of urinary cytology in detecting transitional cell carcinoma of the urinary bladder using histopathology as the reference standard. Urinary cytology demonstrated high specificity and positive predictive value, confirming its reliability in identifying high-grade urothelial carcinoma when results are positive. However, its low sensitivity and poor negative predictive value limit its usefulness, particularly for low-grade tumours. Urinary cytology should not be used as a standalone diagnostic or screening tool, as negative cytological findings do not exclude malignancy. It is best utilised as an adjunct to cystoscopy and histopathology, particularly for surveillance of high-grade disease. Integration of adjunctive biomarkers and emerging artificial intelligence–based diagnostic tools may improve diagnostic accuracy and warrants further multicentric evaluation. Ethical Approval The study was approved by the Institutional Ethics Committee, and informed consent was obtained from all participants. Conflicts of Interest None declared. Funding No external funding was received for this study.
REFERENCES
1. Comploj E, Trenti E, Palermo S, Pycha A, Mian C. Urinary cytology in bladder cancer: why is it still relevant? Urol J. 2015;82:203–205. 2. Kars M, Çetin M, Toper MH, Filinte D, Çam K. Contemporary role of urine cytology in bladder cancer. Bull Urooncology. 2024;23:73–77. 3. Vijayakumar P, Gnanasekaran T. A prospective study on comparison of urinary cytology and histopathological examination in bladder transitional cell carcinoma. Int Arch Integr Med. 2016;3(2):88–94. 4. Sharma I, Joseph M, Pant M, Jha AK, Kandukuri MK. Detection of malignant lesions of the urinary bladder using urine cytology and correlating with histopathology findings: a prospective study. Int Arch Integr Med. 2016;3(2):79–87. 5. Soloway MS, Botteman MF, Carroll PR. Non–muscle-invasive bladder cancer. In: Wein AJ, Kavoussi LR, Partin AW, Peters CA, editors. Campbell-Walsh Urology. 12th ed. Philadelphia: Elsevier; 2021. p. 2302–2330. 6. El-Bolkainy MN, Mokhtar NM, Ghoneim MA, Hussein MH. The impact of schistosomiasis on the pathology of bladder carcinoma. Cancer. 1981;48(12):2643–2648. doi:10.1002/1097-0142(19811215)48:12<2643::AID-CNCR2820481216>3.0.CO;2-C. 7. Koss LG, Deitch D, Ramanathan R, Sherman AB. Diagnostic value of cytology of voided urine. Acta Cytol. 1985;29:810–816. 8. Badalament RA, Hermansen DK, Kimmel M, et al. The sensitivity of bladder wash flow cytometry, bladder wash cytology, and voided cytology in the detection of bladder carcinoma. Cancer. 1987;60:1423–1427. 9. Desgrippes A, Izadifar V, Assailly J, Fontaine E, Beurton D. Diagnosis and prediction of recurrence and progression in superficial bladder cancer with DNA image cytometry and urinary cytology. BJU Int. 2000;85:434–436. 10. Cummings KB, Baron JG, Ward WS. Diagnosis and staging of bladder cancer. Urol Clin North Am. 1992;19:455–465. 11. Ramkumar S, Bhuiyan J, Besse JA, Roberts SG, Wollan PC, Blute ML, O’Kane DJ. Comparison of screening methods in the detection of bladder cancer. J Urol. 1999;161:388–394. 12. Brown FM. Urine cytology: is it still the gold standard for screening? Urol Clin North Am. 2000;27:25–37. 13. Brodie A, Alghazo O, Lin G, et al. Integration of artificial intelligence into urologic oncology: promise and pitfalls. Curr Opin Urol. 2021;31(3):245–251. 14. Prata TS, Silva L, Lopes FM. Artificial intelligence and machine learning in urological cancers: current state and future directions. Front Oncol. 2023;13:1174295. doi:10.3389/fonc.2023.1174295. 15. Khoraminia M, Yazdi MH, Daryaei M. Deep learning in bladder cancer: state-of-the-art and future directions. Diagnostics (Basel). 2023;13(7):1302. doi:10.3390/diagnostics13071302. 16. Goceri E. Deep learning for histopathology image analysis in urologic oncology. J Digit Imaging. 2024;37(1):12–24. doi:10.1007/s10278-023-00824-4. 17. Barrios R, Santiago J, Alfaro J, et al. U-Net and AI-based segmentation for bladder cancer histopathology: current performance and future promise. Comput Methods Programs Biomed. 2022;215:106633. doi:10.1016/j.cmpb.2022.106633.
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