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Keywords:

  • bladder cancer;
  • urine markers;
  • combination;
  • cytology;
  • fluorescence in situ hybridization;
  • nuclear matrix protein 22;
  • immunocytology

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES

BACKGROUND

The sensitivity of cytology for the detection of urothelial carcinoma (UC) is limited. Newer methods such as fluorescence in situ hybridization (FISH), immunocytology (uCyt+), and protein markers have been developed to improve urine-based detection of UC. As only little is known regarding the combined application of these markers, we investigated whether combinations of 4 of the most broadly available tests (cytology, FISH, uCyt+, and nuclear matrix protein 22 [NMP22-ELISA]) may improve their diagnostic performance.

METHODS

The study was comprised of 808 patients who were suspected of having UC. All patients underwent urethrocystoscopy and upper urinary tract imaging and, in the case of positive findings, transurethral resection/biopsy. FISH, uCyt+, cytology, and NMP22-ELISA were performed in all patients.

RESULTS

UC was diagnosed in 115 patients (14.2%). Cytology and FISH were found to be the single tests with the best overall performance (area under the curve [AUC], 0.78/0.79). Combinations of 2, 3, and 4 markers were found to increase the AUC to various extents compared with the use of single markers. Combining cytology and FISH improved the sensitivity and performance (AUC, 0.83) compared with the single tests and identified 12 tumors that were not detected by cytology alone. The percentage of WHO grade 3/carcinoma in situ tumors not detected by cytology was reduced by 62.5% when FISH was performed in cytology-negative patients. The addition of uCyt+ as a third test further improved performance (AUC, 0.86), whereas the addition of NMP22-ELISA was not found to have any additional influence on the performance of the test combination.

CONCLUSIONS

The results of the current study support the combined use of urine markers and may form the basis of further studies investigating whether risk stratification based on urine marker combinations may individualize diagnostic algorithms and the surveillance of patients suspected of having UC. Cancer (Cancer Cytopathol) 2013;121:252–60. © 2012 American Cancer Society


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES

Urothelial carcinoma (UC) accounts for > 70,000 new cancer cases per year and approximately 14,000 deaths annually[1] in the United States. Approximately 70% of patients initially present with Ta/T1 tumors. Depending on risk stratification, up to 15% of these tumors progress to a muscle-invasive stage, which is associated with a limited 5-year survival rate. Early diagnosis is essential to prevent progression to a muscle-invasive stage, which is associated with a remarkable increase in mortality.[2] Cystoscopy with subsequent transurethral resection remains the gold standard for the diagnosis of bladder cancer.[3] In addition, current guidelines recommend performing urine cytology (CYT) as an adjunct tool in patients with suspected UC.[3] Although it demonstrates a relatively high specificity, the diagnostic value of CYT is impaired by its low sensitivity.[5] Therefore, several additional urine tests have been developed within the last 20 years to improve the detection rate of UC. These include fluorescence in situ hybridization (FISH)[6] for the detection of chromosomal aberrations (loss of the 9p21 locus, site of the p16 tumor suppressor gene, has been identified as a common chromosomal aberration in patients with UC[6]) and immunocytology, which in addition to normal urine CYT uses a cocktail of antibodies against UC-associated surface antigens such as carcinoembryonic antigen and mucin-like glycoprotein (the uCyt+ test).[8] Furthermore, protein-based tests such as the quantitative nuclear matrix protein 22—enzyme-linked immunoadsorbent assay (NMP22-ELISA) have become widely available and are frequently used by specialized centers and practitioners. In the majority of previous studies, these tests all demonstrated improved sensitivity but decreased specificity compared with CYT.[9] One limitation of some of these markers is a relatively high false-positive test rate because of endogenous or exogenous factors including mechanical manipulations, urinary tract infection (UTI),[11] hematuria,[13] and impaired renal excretory function.[15]

Although several studies have been performed that directly compare the diagnostic performance of various urine tests, to our knowledge little is known regarding whether a combined application of these markers may improve their diagnostic performance in patients suspected of having UC.

Therefore, the objective of the current study was to investigate the diagnostic performance of combined applications of the 4 most broadly available urine markers (CYT, FISH, uCyt+ and NMP22-ELISA) in a large cohort of 808 patients suspected to have UC.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES

Patients and Samples

A total of 808 patients without a history of UC who reported symptoms that were suspicious for UC (such as hematuria or irritative voiding symptoms) were enrolled (645 men and 163 women; median age, 67 years [range, 21 years-92 years]). The study was approved by the local ethics committee (No. 400/2009A). Urine samples were obtained before cystoscopy and analyzed by dipstick analysis and urine microscopy using a Neubauer hemocytometer. The average volume of urine submitted for evaluation was approximately 160 mL to 180 mL. CYT, FISH (UroVysion, Abbott Laboratories, Abbott Park, Ill), uCyt+, and NMP22-ELISA were performed in all patients. All patients underwent cystoscopy and upper urinary tract imaging, and patients with suspicious findings also underwent transurethral biopsy/resection of suspicious lesions.

Urine Tests

For CYT, slides were cytospinned, stained using the Papanicolaou method,[16] and microscopically assessed by an experienced urologic cytologist according to the recommendations of the Papanicolaou Society of Cytopathology.[17] Accepted characteristic features of UCs were taken into consideration: papillary clusters comprised of cells with eccentric nuclei, single cells with eccentric nuclei, an increased nuclear-to-cytoplasmic ratio, cells with irregular nuclear borders, and cells with coarse chromatin. Categories for cytology were “benign”; “atypia, favor reactive”; “atypia, unclear if reactive or neoplastic”; “suspicious”; “positive for UC”; and “suspicious for high-grade UC.” The categories of “benign” and “atypia, favor reactive” were considered as negative CYT whereas all other categories were considered to be positive. The FISH test was performed on cytospin slides as previously described.[18] At least 4 nuclei of 25 morphologically suspicious cells had to demonstrate ≥ 3 signals of at least 2 chromosomes (3, 7, or 17) or at least 12 nuclei had to demonstrate no signal of 9p21 for a test to be considered positive.[19] The uCyt+ test was performed according to the manufacturer's recommendations, as recently described.[8] The criterion for a positive result was at least 1 clear positive cell.[20] The NMP22-ELISA test was performed according to the manufacturer's protocol. We used > 10 IU/mL as a threshold for a positive test, which is consistent with other studies and the recommendations of the manufacturer.[21]

Urinary Tract Infection

Because a UTI might impair the diagnostic accuracy, its presence was determined using dipstick analysis and urine microscopy and defined as the number of leukocytes per at least 100/μL and, simultaneously, the number of erythrocytes > 1 or the number of leukocytes per at least 100/μL and the simultaneous presence of urine nitrite.

Statistical Analysis

Sensitivities, specificities, negative predictive values (NPVs), positive predictive values (PPVs), and accuracies were determined by contingency analyses for single tests. Nominal logistic regression analyses followed by receiver operating curve (ROC) analysis were performed to determine the area under the curve (AUC) for single tests, 2-test combinations, 3-test combinations, and the combination of all 4 tests.[22] Furthermore, the probability obtained by nominal logistic regression analysis demonstrating the highest Youden index (sensitivity + specificity-1) was determined as the optimal cutoff value by ROC analysis. Sensitivities, specificities, NPVs, and PPVs were then determined for optimal cutoff values of test combinations. For every test combination, the nominal logistic model was used to calculate whether the probability for having a tumor was associated with a higher or lower sensitivity compared with the optimal cutoff value determined by ROC analysis.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES

A total of 115 patients (14.2%) were diagnosed with UC on final histopathology whereas 693 patients (85.8%) did not have UC. UC of the bladder was present in 109 patients, whereas 6 patients had UC of the upper urinary tract. A total of 118 patients (14.6%) had a UTI according to the definition. Six hundred eighteen patients (76.5%) underwent a mechanical manipulation of the lower urinary tract before urine sampling (catheterization, digital rectal examination, or cystoscopy). Patient characteristics are summarized in Table 1.

Table 1. Patient Characteristics
CharacteristicNo.
  1. Abbreviations: CIS, carcinoma in situ; UC, urothelial carcinoma.

Total808
Men645 (79.8%)
Women163 (20.2 %)
Median age (range), y67 (20–92)
Patients without tumor693 (85.7%)
UC of the bladder109 (13.5%)
pTa68 (62.4%)
pT120 (18.3%)
≥pT218 (16.5%)
Pure pTis3 (2.8%)
Concomitant CIS20 (18.3%)
Grade 
147 (43.1%)
235 (32.1%)
324 (22.0%)
Upper urinary tract UC6 (0.7%)
pTa4 (66.7%)
pT11 (16.7%)
≥pT21 (16.7%)
Grade 
14 (66.7%)
21 (16.7%)
31 (16.7%)

Single Tests

Sensitivities, specificities, PPVs, NPVs, and AUCs for each single test are summarized in Table 2. The specificity of NMP22-ELISA could be improved to 75.3% by excluding patients who underwent mechanical manipulation or those with a UTI (combined with a decrease in sensitivity to 27.3%).

Table 2. Sensitivities, Specificities, PPVs, NPVs, and AUCs for Optimal Cutoff Values in ROC Analysis of Single Urine Tests
Single MarkersSensitivitySpecificityPPVNPVAUC
  1. Excluding patients with a urinary tract infection and those who underwent mechanical manipulation of the lower urinary tract.

  2. Abbreviations: AUC, area under the curve; CIS, carcinoma in situ; CYT, cytology; ELISA, enzyme-linked immunoadsorbent assay; FISH, fluorescence in situ hybridization; NMP22, nuclear matrix protein 22; NPV, negative predictive value; PPV, positive predictive value; ROC, receiver operating curve; uCyt+, immunocytology.

CYT67.887.547.394.30.78
Grade 1/Grade 257.7    
Grade 3/CIS88.9    
FISH71.386.346.394.80.79
Grade 1/Grade 261.5    
Grade 3/CIS94.4    
uCyt+73.976.634.494.70.75
Grade 1/Grade 269.2    
Grade 3/CIS83.3    
NMP22-ELISA84.441.319.294.10.63
Grade 1/Grade 283.3    
Grade 3/CIS86.1    
NMP22-ELISAa27.375.37.593.40.63
Grade 1/Grade 225.0    
Grade 3/CIS33.3    

Combinations of 2 Tests

ROC analyses for all possible 2-test combinations are shown in Figure 1 (rows 2–3). Table 3 shows sensitivities, specificities, PPVs, NPVs, and AUCs for the optimal cutoff point determined by ROC analysis. Combinations with probabilities for UC (according to the nominal logistic regression model) above or below the cutoff point proposed by ROC analysis are listed in Table 3.

image

Figure 1. Receiver operating curve analyses for single urine tests (row 1), combinations of 2 tests (rows 2–3) and 3 tests (row 4), and the combination of all 4 urine markers (row 5) are shown. Sensitivities, specificities, positive predictive values (PPVs), and negative predictive values (NPVs) are indicated for the optimal cutoff value (highest Youden index). CYT indicates cytology; AUC, area under the curve; FISH, fluorescence in situ hybridization; uCyt+, immunocytology; NMP22, nuclear matrix protein 22–enzyme-linked immunoadsorbent assay.

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Table 3. Sensitivities, Specificities, PPVs, NPVs, and AUCs for Optimal Cutoff Values in ROC Analysis of the Combination of 2 Tests
2-Test CombinationsSensitivitySpecificityPPVNPVAUCProfiles Categorized as Positive When Using the Optimal CutoffProfiles Categorized as Negative When Using the Optimal Cutoff
  1. Abbreviations: +, positive; −, negative; AUC, area under the curve; C, cytology, CYT, cytology; ELISA, enzyme-linked immunoadsorbent assay; F, fluorescence in situ hybridization; FISH, fluorescence in situ hybridization; N, nuclear matrix protein 22-enzyme-linked immunoadsorbent assay; NMP22, nuclear matrix protein 22; NPV, negative predictive value; PPV, positive predictive value; ROC, receiver operating curve; U, immunocytology; uCyt+, immunocytology.

CYT and FISH78.381.140.795.70.83C+F−; C−F+; C+F+C−F−
CYT and uCyt+67.887.547.194.30.83C+U−; C+U+C−U+; C−U−
CYT and NMP22-ELISA67.887.547.194.30.79C+N−; C+N+C−N+; C−N−
FISH and uCyt+71.386.346.394.80.85F+U−; F+U+F−U−; F−U+
FISH and NMP22-ELISA71.386.346.394.80.81F+N−; F+N+F−N−; F−N+
uCyt+ and NMP22-ELISA90.435.91995.80.86U+N−; U+N+U−N+; U−N−

All 2-test combinations demonstrated higher AUCs compared with the single tests. However, taking the cutoff value proposed by ROC analysis into consideration, the only 2-test combination with both an improved AUC and improved sensitivity compared with both single tests was the combination of CYT and FISH. According to the proposed cutoff point in ROC analysis, the positivity of either CYT or FISH led to a positive test combination and thereby improved sensitivity with a slight decrease in specificity compared with the single tests. By contrast, the combination of uCyt+ and FISH demonstrated an improved AUC compared with the single tests. However, using the cutoff value proposed by ROC analysis, the sensitivity and specificity were found to be identical to those when FISH was used as a single test. The probability of having UC according to the applied model for the test profile of uCyt+ positive/FISH negative was lower than the proposed cutoff value. Therefore, the results of the uCyt+ test did not affect the overall dichotomized result of the combination. The same effect can be observed for the combination of CYT and NMP22-ELISA, CYT and uCyt+, FISH and NMP22, and uCyt+ and NMP22.

Because the combination of CYT and FISH appears to be promising, we investigated how many patients also can be identified as harboring a UC when FISH is performed in patients with negative CYT findings. Of 643 patients with negative CYT, 56 had a positive FISH result. Of these, 12 were found to have UC (5 of whom had WHO grade 3 disease or carcinoma in situ [CIS]). The additional performance of FISH reduced the rate of missed grade 3/CIS tumors by 62.5%. Twenty-four patients with UC were found to be negative for both CYT and FISH (3 grade 3/CIS UCs) and also would have been missed using the combination of FISH and CYT.

Combinations of 3 and 4 Tests

ROC analyses for the models containing combinations of 3 and 4 urine markers are shown in Figure 1 (rows 4 and 5). Tables 4 and 5 show the sensitivities, specificities, PPVs, NPVs, and AUCs for the optimal cutoff point determined by ROC analysis. Combinations with probabilities for UC (according to the nominal logistic regression model) above or below the cutoff value proposed by ROC analysis are listed in Tables 4 and 5.

Table 4. Sensitivities, Specificities, PPVs, NPVs, and AUCs for Optimal Cutoff Values in ROC Analysis of the Combination of 3 Tests
3-Test CombinationsSensitivitySpecificityPPVNPVAUCProfiles Categorized as Positive When Using the Optimal CutoffProfiles Categorized as Negative When Using the Optimal Cutoff
  1. Abbreviations: +, positive; −, negative; AUC, area under the curve; C, cytology, CYT, cytology; ELISA, enzyme-linked immunoadsorbent assay; F, fluorescence in situ hybridization; FISH, fluorescence in situ hybridization; N, nuclear matrix protein 22-enzyme-linked immunoadsorbent assay; NMP22, nuclear matrix protein 22; NPV, negative predictive value; PPV, positive predictive value; ROC, receiver operating curve; U, immunocytology; uCyt+, immunocytology.

CYT, FISH, and uCyt+76.584.444.995.60.86F+C−U−; F+C+U−; F+C−U+; F−C+U+; F+C+U+F−C+U−; F−C−U+; F−C−U−
CYT, FISH, and NMP22-ELISA75.784.744.695.40.83F+C−N+; F+C−N−; F+C+N+; F+C+N−; F−C+N+F−C−N−; F−C+N−; F−C−N+
CYT, uCyt+, and NMP22-ELISA80.97534.959.90.84C+U−N−; C−U+N+; C+U+N−; C+U−N+; C+U+N+C−U−N−; C−U+N−; C−U−N+
FISH, uCyt+, and NMP22-ELISA83.574.134.996.40.85F+U−N−; F−U+N+; F+U+N+; F+U−N+; F+U+N−F−U+N−; F−U−N+; F−U−N−
Table 5. Sensitivities, Specificities, PPVs, NPVs, and AUCs for Optimal Cutoff Values in ROC Analysis of the Combination of All 4 Tests
4-Test CombinationSensitivitySpecificityPPVNPVAUCProfiles Categorized as Positive When Using the Optimal CutoffProfiles Categorized as Negative When Using the Optimal Cutoff
  1. Abbreviations: +, positive; −, negative; AUC, area under the curve; C, cytology, CYT, cytology; ELISA, enzyme-linked immunoadsorbent assay; F, fluorescence in situ hybridization; FISH, fluorescence in situ hybridization; N, nuclear matrix protein 22-ELISA; NMP22, nuclear matrix protein 22; NPV, negative predictive value; PPV, positive predictive value; ROC, receiver operating curve; U, immunocytology; uCyt+, immunocytology.

CYT, FISH, uCyt+, and NMP22-ELISA74.886.247.295.40.86C−F+U−N−; C+F−U+N−; C+F−U+N+; C+F+U+N+; C+F+U+N−; C+F+U−N+; C−F+U+N−; C−F+U−N+; C−F+U+N+; C+F+U−N−C+F−U−N−; C+F−U−N+; C−F−U+N−; C−F−U−N−; C−F−U−N+; C−F−U+N+

The addition of NMP22-ELISA to the combinations of CYT and FISH, CYT and uCyt+ or FISH and uCyt+ was not found to further improve the AUCs of the 2-test combinations. The 3-test model of CYT, FISH, and uCyt+ demonstrated a higher AUC (0.86) compared with CYT and FISH used as a 2-test combination (AUC, 0.83). However, when using the cutoff value proposed by ROC analysis to dichotomize test patterns, the sensitivity decreased with a clearly improved specificity. An isolated positive CYT (with negative FISH and negative uCyt+ findings) was considered to be a negative 3-test combination when applying the cutoff value proposed by ROC analysis.

The combination of CYT, FISH, uCyt+, and NMP22-ELISA did not lead to an improved AUC compared with the combination of CYT, FISH, and uCyt+.

Improvement of the Model by Including Age and Grade of Hematuria

To investigate whether the additional use of urine markers can improve the ROC statistic based on demographic and clinical parameters correlating with the incidence of UC, we constructed a base model including patient age and grade of hematuria as quantified by dipstick analysis into 0 (no erythrocytes), I (1 ≤ erythrocytes/μL < 100), II (100 ≤ erythrocytes/μL < 250), and III (≥ 250 erythrocytes/μL) and determined its AUC using ROC analysis. The base model was combined with the 2 single tests that demonstrated the highest AUCs on ROC analysis (Fig. 2, rows 2–3). Moreover, the base model was combined with the two 2-test combinations with the highest AUCs and the 3-test combination with the highest AUC. Resulting ROC analyses and respective AUCs are shown in Figure 2.

image

Figure 2. Receiver operating curve (ROC) analyses for the base model (including patient age and grade of hematuria) and algorithms containing the base model and the 2 single tests with the best performance on ROC analysis (cytology [CYT] and fluorescence in situ hybridization [FISH], upper row) and an algorithm containing the base model and the 3 test combinations with the best performance (lower row) are shown. uCyt+ indicates immunocytology; AUC, area under the curve.

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DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES

Cystoscopy is still the gold standard for the primary diagnosis and follow-up of patients with UC. However, the performance of cystoscopy every 3 to 6 months in the follow-up setting is associated with discomfort and stress for patients.[23] Therefore, there has been an intense search for reliable noninvasive markers of UC within the last decade. The tests, which to our knowledge have shown the most promising results to date, include FISH for the detection of chromosomal abnormalities within malignant cells in the urine, uCyt+ for the detection of cancer-associated antigens, and a protein-based assay for the detection of NMP22. Several studies have been performed to compare these tests with conventional CYT and the majority revealed an increased sensitivity associated with a decreased specificity, with the result that these tests are not yet able to replace cystoscopy.[7, 8, 10] Because some markers are characterized by high specificity whereas others have the advantage of having higher sensitivity, the objective of the current study was to investigate whether the combined use of the 4 most broadly used urine markers (CYT, FISH, uCyt+, and NMP22-ELISA) could improve diagnostic performance in a large cohort of patients receiving diagnostic workup for symptoms believed to be suspicious for UC.

The overall performances of the applied tests were found to be similar to those of prior studies.[24] The 2 tests that were found to perform best were CYT and FISH, which demonstrated AUCs of 0.78 and 0.79, respectively. Although CYT demonstrated a slightly higher specificity (87.5% vs 86.3 %), FISH had a better sensitivity (71.3% vs 67.8%). However, compared with previous studies, CYT achieved a considerably higher sensitivity. This most likely is the consequence of having a well-experienced cytologist involved, which has been demonstrated to be of major importance for the accuracy of CYT.[26] NMP22-ELISA was the test with the highest overall sensitivity (84.4%) but lowest specificity (41.3%). When excluding patients with factors that influenced the performance of NMP22-ELISA, specificity was found to be clearly increased (75.3%) whereas sensitivity was far lower, which is in accordance with the findings of prior studies.[27] Similar to other studies, uCyt+ outperformed CYT with regard to test sensitivity.[24] However, the specificity of uCyt+ was found to be lower.

Whenever investigators perform combinations of biomarker tests for cancer, they are faced with the question of what are the criteria for a positive test combination. By considering a test combination to be positive if 1 of 2 tests is positive, a better sensitivity is expected with a parallel decrease in specificity. A combination requiring multiple positive tests to be considered positive is expected to be associated with an increase in specificity and a decrease in sensitivity.[29] One reasonable method with which to compare various test combinations, which has also been performed by others,[24] is ROC analysis of models containing various marker combinations.[22] In this case, the AUC reflects the overall performance of the model. Moreover, the cutoff value with the optimal correlation of sensitivity and specificity can be determined.

The results of the current study indicate that particular test combinations demonstrate a clearly improved performance compared with single tests. Combining CYT and FISH clearly improved the detection of UC compared with the use of single tests. Using the optimal cutoff value of ROC analysis for this 2-test algorithm, only patients who are negative for both FISH and CYT are considered to have a negative test combination. Because one would hardly omit either a positive FISH result or a positive CYT result, this combination appears to be realistic for clinical practice. One reasonable approach would be a stepwise performance (CYT in the first setting and FISH in CYT-negative patients). The FISH method is associated with considerable costs and CYT has such a high specificity, that CYT-positive patients should undergo an invasive workup in any case.[5] In the current study cohort, the performance of FISH in CYT-negative patients identified 12 additional tumors and reduced the percentage of missed grade 3/CIS tumors by 62%. However, 44 patients who were CYT negative were found to have false-positive FISH results. A 2-test combination of FISH and uCyt+ was found to have the highest AUC of all the 2-test combinations (AUC, 0.85). However, the implications of this model cannot be transferred directly into clinical practice. By dichotomizing test patterns into positive and negative according to the optimal cutoff value (based on ROC analysis), the result of the combination is still determined by FISH and an additional uCyt+ test does not alter the decision based on the applied model. This phenomenon also can be observed with other combinations. Therefore, the increased explanatory power of these combinations cannot be fully exploited by dichotomizing test combinations into positive and negative. Rather, these combinations may increase the accuracy of models predicting the probability of a patient having UC. One practical approach for calculating the risks of UC are nomograms that include demographic and clinical parameters. Nomograms including the results of urine markers have been recently implemented.[24] The results of the current study indicate that urine marker combinations might increase the predictive ability of these nomograms, because the AUC of the base model containing factors frequently used for nomograms (age and hematuria status) was clearly improved by the addition of urine marker panels.

One issue that has been discussed frequently is whether urinary tumor markers might individualize the intervals between cystoscopies in the surveillance of patients with a history of bladder cancer.[32] To our knowledge, because no single marker to date has demonstrated sufficient performance to replace cystoscopy in this setting, there is a need to examine whether combinations of urine markers may be suitable.[10] Although the current study was performed in patients without a history of UC, the improved performance noted through the combination of urine markers may also be observed in patients under surveillance[34] and models including multiple urine tests might be used for future studies addressing this issue.

The main limitation of performing multiple urine markers is the relatively high costs.[35] However, regular cystoscopy is also associated with considerable costs. Therefore, it appears to be reasonable to address the cost-effectiveness of different approaches for UC surveillance in future studies.[36] Moreover, cost-benefit analyses are required to analyze whether the performance of additional urine markers is cost-effective.

The current study has various limitations. First, a high percentage of urine samples were obtained by instrumented urinary sampling. Second, we did not assess the smoking status of the patients involved, which could have an effect on the base model applied in the current study.[24]

Conclusions

In conclusion, to the best of our knowledge, the current study is the first to investigate whether the combined use of cytology, FISH, uCyt+ and NMP22-ELISA can improve diagnostic performance compared with single tests in patients who are suspected of having primary UC. The results demonstrate that the expedient combination of urine markers enhances their diagnostic accuracy. FISH appears to be a reasonable amendment to routine CYT and identifies a considerable percentage of tumors that are not detected by CYT alone with an acceptable rate of false-positive results. These results may form the basis of further studies investigating whether risk stratification based on the combined application of urine markers may individualize diagnostic algorithms and the surveillance of patients with symptoms that are suspicious for UC.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  • 1
    Kohler BA, Ward E, McCarthy BJ, et al. Annual report to the nation on the status of cancer, 1975-2007, featuring tumors of the brain and other nervous system. J Natl Cancer Inst. 2011;103:714-736.
  • 2
    Millan-Rodriguez F, Chechile-Toniolo G, Salvador-Bayarri J, Palou J, Algaba F, Vicente-Rodriguez J. Primary superficial bladder cancer risk groups according to progression, mortality and recurrence. J Urol. 2000;164( 3 pt 1):680-684.
  • 3
    Babjuk M, Oosterlinck W, Sylvester R, et al; European Association of Urology (EAU). EAU guidelines on non–muscle-invasive urothelial carcinoma of the bladder, the 2011 update. Eur Urol. 2011;59:997-1008.
  • 4
    Brausi M, Witjes JA, Lamm D, et al. A review of current guidelines and best practice recommendations for the management of nonmuscle invasive bladder cancer by the International Bladder Cancer Group. J Urol. 2011;186:2158-2167.
  • 5
    Budman LI, Kassouf W, Steinberg JR. Biomarkers for detection and surveillance of bladder cancer. Can Urol Assoc J. 2008;2:212-221.
  • 6
    Bubendorf L. Multiprobe fluorescence in situ hybridization (UroVysion) for the detection of urothelial carcinoma-FISHing for the right catch. Acta Cytol. 2011;55:113-119.
  • 7
    Daniely M, Rona R, Kaplan T, et al. Combined analysis of morphology and fluorescence in situ hybridization significantly increases accuracy of bladder cancer detection in voided urine samples. Urology. 2005;66:1354-1359.
  • 8
    Mian C, Pycha A, Wiener H, Haitel A, Lodde M, Marberger M. Immunocyt: a new tool for detecting transitional cell cancer of the urinary tract. J Urol. 1999;161:1486-1489.
  • 9
    Mowatt G, Zhu S, Kilonzo M, et al. Systematic review of the clinical effectiveness and cost-effectiveness of photodynamic diagnosis and urine biomarkers (FISH, ImmunoCyt, NMP22) and cytology for the detection and follow-up of bladder cancer. Health Technol Assess. 2010;14:1-331, iii-iv.
  • 10
    Tilki D, Burger M, Dalbagni G, et al. Urine markers for detection and surveillance of non-muscle-invasive bladder cancer. Eur Urol. 2011;60:484-492.
  • 11
    Sharma S, Zippe CD, Pandrangi L, Nelson D, Agarwal A. Exclusion criteria enhance the specificity and positive predictive value of NMP22 and BTA stat. J Urol. 1999;162:53-57.
  • 12
    Todenhofer T, Hennenlotter J, Kuhs U, et al. Influence of urinary tract instrumentation and inflammation on the performance of urine markers for the detection of bladder cancer. Urology. 2012;79:620-624.
  • 13
    Hennenlotter J, Huber S, Todenhofer T, et al. Point-of-care tests for bladder cancer: the influencing role of hematuria. Adv Urol. 2011;2011:937561.
  • 14
    Todenhofer T, Hennenlotter J, Tews V, et al. Impact of different grades of microscopic hematuria on the performance of urine-based markers for the detection of urothelial carcinoma [published online ahead of print November 28, 2011]. Urol Oncol.
  • 15
    Todenhofer T, Hennenlotter J, Witstruk M, et al. Influence of renal excretory function on the performance of urine based markers to detect bladder cancer. J Urol. 2012;187:68-73.
  • 16
    Papanicolaou GN, Marshall VF. Urine sediment smears as a diagnostic procedure in cancers of the urinary tract. Science. 1945;101:519-520.
  • 17
    Layfield LJ, Elsheikh TM, Fili A, Nayar R, Shidham V; Papanicolaou Society of Cytopathology. Review of the state of the art and recommendations of the Papanicolaou Society of Cytopathology for urinary cytology procedures and reporting: the Papanicolaou Society of Cytopathology Practice Guidelines Task Force. Diagn Cytopathol. 2004;30:24-30.
  • 18
    Riesz P, Lotz G, Paska C, et al. Detection of bladder cancer from the urine using fluorescence in situ hybridization technique. Pathol Oncol Res. 2007;13:187-194.
  • 19
    Kipp BR, Tyner HL, Campion MB, et al. Chromosomal alterations detected by fluorescence in situ hybridization in urothelial carcinoma and rarer histologic variants of bladder cancer. Am J Clin Pathol. 2008;130:552-559.
  • 20
    Greene KL, Berry A, Konety BR. Diagnostic utility of the ImmunoCyt/uCyt+ test in bladder cancer. Rev Urol. 2006;8:190-197.
  • 21
    Shariat SF, Marberger MJ, Lotan Y, et al. Variability in the performance of nuclear matrix protein 22 for the detection of bladder cancer. J Urol. 2006;176:919-926; discussion 926.
  • 22
    Pepe MS. The Statistical Evaluation of Medical Tests for Classification and Prediction. New York: Oxford University Press; 2003.
  • 23
    van der Aa MN, Steyerberg EW, Sen EF, et al. Patients' perceived burden of cystoscopic and urinary surveillance of bladder cancer: a randomized comparison. BJU Int. 2008;101:1106-1110.
  • 24
    Cha EK, Tirsar LA, Schwentner C, et al. Immunocytology is a strong predictor of bladder cancer presence in patients with painless hematuria: a multicentre study. Eur Urol. 2012;61:185-192.
  • 25
    Bubendorf L, Grilli B, Sauter G, Mihatsch MJ, Gasser TC, Dalquen P. Multiprobe FISH for enhanced detection of bladder cancer in voided urine specimens and bladder washings. Am J Clin Pathol. 2001;116:79-86.
  • 26
    Raitanen MP, Aine R, Rintala E, et al; FinnBladder Group. Differences between local and review urinary cytology in diagnosis of bladder cancer. An interobserver multicenter analysis. Eur Urol. 2002;41:284-289.
  • 27
    Huber S, Schwentner C, Taeger D, et al; the UroScreen Study Group. Nuclear matrix protein-22: a prospective evaluation in a population at risk for bladder cancer. Results from the UroScreen study. BJU Int. 2012;110:699-708.
  • 28
    Schmitz-Drager B, Tirsar LA, Schmitz-Drager C, Dörsam J, Bismarck E, Ebert T. Immunocytology in the assessment of patients with painless gross haematuria. BJU Int. 2008;101:455-458.
  • 29
    Bravaccini S, Casadio V, Gunelli R, et al. Combining cytology, TRAP assay, and FISH analysis for the detection of bladder cancer in symptomatic patients. Ann Oncol. 2011;22:2294-2298.
  • 30
    Wild PJ, Fuchs T, Stoehr R, et al. Detection of urothelial bladder cancer cells in voided urine can be improved by a combination of cytology and standardized microsatellite analysis. Cancer Epidemiol Biomarkers Prev. 2009;18:1798-1806.
  • 31
    Lotan Y, Capitanio U, Shariat SF, Hutterer GC, Karakiewicz PI. Impact of clinical factors, including a point-of-care nuclear matrix protein-22 assay and cytology, on bladder cancer detection. BJU Int. 2009;103:1368-1374.
  • 32
    Sanchez-Carbayo M, Urrutia M, Gonzalez de Buitrago JM, Navajo JA. Utility of serial urinary tumor markers to individualize intervals between cystoscopies in the monitoring of patients with bladder carcinoma. Cancer. 2001;92:2820-2828.
  • 33
    Lotan Y, Shariat SF, Schmitz-Drager BJ, et al. Considerations on implementing diagnostic markers into clinical decision making in bladder cancer. Urol Oncol. 2010;28:441-448.
  • 34
    Horstmann M, Patschan O, Hennenlotter J, Senger E, Feil G, Stenzl A. Combinations of urine-based tumour markers in bladder cancer surveillance. Scand J Urol Nephrol. 2009;43:461-466.
  • 35
    Fradet Y. Screening for bladder cancer: the best opportunity to reduce mortality. Can Urol Assoc J. 2009;3 ( 6 suppl 4):S180-S183.
  • 36
    Youssef RF, Schlomer BJ, Ho R, Sagalowsky AI, Ashfaq R, Lotan Y. Role of fluorescence in situ hybridization in bladder cancer surveillance of patients with negative cytology. Urol Oncol. 2012;30:273-277.