The role of haematuria in bladder cancer screening among men with former occupational exposure to aromatic amines



This article is corrected by:

  1. Errata: Corrigenda Volume 108, Issue 7, 1232, Article first published online: 13 September 2011

Beate Pesch, Institut für Prävention und Arbeitsmedizin der Deutschen Gesetzlichen Unfallversicherung (IPA), Bürkle-de-la-Camp-Platz 1, 44789 Bochum, Germany. e-mail:


Study Type – Diagnostic (validating cohort)

Level of Evidence 1b

What's known on the subject? and What does the study add?

Microscopic haematuria (µH) is frequently detected in elderly adults. The American Urological Association recommends the follow-up of subjects with µH on bladder cancer. Whereas gross haematuria is considered an important sign of the presence of bladder cancer, the disease-predictive value of µH is less clear.

No association of µH with the development of bladder tumours in a prospective screening cohort of chemical workers was observed. The positive predictive value of µH for bladder cancer was as low as 1.2%. Haematuria interfered with NMP22 but not with cytology and UroVysionTM test results.


• To assess the positive predictive value (PPV) of microhaematuria (µH) and gross haematuria (GH) in bladder cancer screening and the influence of haematuria on tumour tests in a prospective study.


• From September 2003 to January 2010, 1323 men took part in an annual voluntary bladder cancer screening programme for chemical workers with former exposure to aromatic amines.

• In 5315 urine samples haematuria was determined with a dipstick, followed by a microscopic blood cell count in the sediment. Haematuria was categorized into traces, µH and GH.

• Urinary leukocytes and other factors were investigated as potential predictors of haematuria using a generalized estimating equation model for repeated urinalysis. The risk of haematuria for positive tumour tests was analysed correspondingly.

• The bladder cancer risk was estimated for the highest degree of haematuria occurring during the study with Poisson regression.


• As of July 2010, 15 bladder tumours were detected in 14 participants.

• GH was found in four out of nine high-grade tumours and associated with a rate ratio of 3.82, 95% confidence interval (CI) 0.50–29.15 for the development of bladder lesions.

• The PPV of GH was 11.4%, but only 1.2% for µH. µH occurred in 18.8% of urine samples and was not associated with bladder cancer [rate ratio (RR) 0.72, 95% CI 0.11–4.78].

• Abundant urinary leukocytes were associated with µH [odds ratio (OR) 8.34, 95% CI 2.26–30.69] and even stronger with GH (OR 22.25, 95% CI 6.42–77.06).

• Haematuria and leukocytes influenced NMP22 positivity (µH: OR 1.63, 95% CI 1.06–2.51, abundant leukocytes: OR 8.90, 95% CI 1.58–50.16), but not test results for urine cytology and UroVysionTM.


• While the PPV of µH for bladder cancer was low, there was a strong influence of haematuria and leukocytes on the protein-based tumour test NMP22®.

• Erythrocytes and leukocytes should be determined at least semi-quantitatively for the interpretation of positive NMP22 test results.

• In addition, a panel of tumour tests that includes methods not affected by the presence of erythrocytes or leukocytes such as cytology and UroVysionTM would improve bladder cancer screening.


positive predictive value




gross haematuria


rate ratio


odds ratio


generalized estimating equation


inter-quartile range.


Asymptomatic microscopic haematuria (microhaematuria, µH) is frequently detected in elderly adults [1]. The American Urological Association recommended the follow-up of subjects with µH, in particular on the development of bladder cancer [2,3]. Whereas gross haematuria (GH) is considered an important sign of the presence of bladder cancer, the disease-predictive value of µH is less clear. Only a few prospective studies assessed µH, and so far the positive predictive value (PPV) for subsequent bladder cancer is likely to be low as a result of other various sources of bleeding [4].

Screening for haematuria is feasible in at-risk populations together with tumour marker tests [5]. Haematuria can also be used to define at-risk groups for bladder-cancer screening [6]. Dipstick testing for filtered haemoglobin or myoglobin in fresh urine and microscopic analysis of red blood cells in the urine sediment are commonly applied detection methods [7]. Whereas several methodological issues such as sample degradation have been evaluated, predictors of µH and the interference of µH with tumour tests are less well explored.

In order to assess the role of µH in bladder cancer screening and its association with tumour tests we analysed a subset of urine samples from the prospective study UroScreen. UroScreen is part of a surveillance programme of the German Social Accident Insurance (Deutsche Gesetzliche Unfallversicherung, DGUV) among subjects with a previous occupational exposure to aromatic amines.



Eligible participants of the prospective surveillance cohort UroScreen are subjects who were formerly exposed to aromatic amines in two chemical plants. From 2003 to 2010, 1772 subjects were annually invited by DGUV to take part in a voluntary screening programme for bladder cancer offered by the occupational medical service in charge for each company. Figure 1 presents the work flow of UroScreen. The quantitative determination of the urinary nuclear matrix protein 22 (NMP22) and the UroVysionTM test were offered in addition to urine cytology. Further, the investigation of the performance of survivin as a non-approved marker was part of the project but was not included in this analysis. A questionnaire was applied to document smoking habits and other relevant diseases. Approval was given by the ethics committee of the Eberhard-Karls-University of Tübingen (No. 1/2003V). All participants gave written informed consent.

Figure 1.

Work flow of the UroScreen study.

Participants with a urinary tract infection or insufficient cell yield in the urine sample were asked to repeat the investigation. Because of the low compliance for a second investigation we did not include repeated measurements in this analysis. Participants with at least one positive test result for cytology, UroVysion or NMP22 received a written recommendation for urethrocystoscopy on a voluntary basis. A positive result for survivin was not considered in diagnostic follow-up.

Haematuria was assessed with different methods in the two sub-cohorts. In the present study, data are presented from 1323 males from BASF where detailed urine-status information was available according to a common protocol until January 2010. The database comprised 5583 urine samples. As of January 2010, 15 tumours in 14 participants were detected. Reference pathology was performed for histological classification of the bladder lesions according to the WHO classification of 2004 [8].


Voided urine samples were collected at the medical service centre of the plant. Urine status, including erythrocytes, haemoglobin (Hb) and leukocytes, was determined in fresh urine with Combur 10 test® strips (Roche Diagnostics, Mannheim, Germany). Creatinine was determined using the enzymatic test CREA plus® (Roche Diagnostics). After centrifugation at 500g, the cell sediment was analysed microscopically. Erythrocytes and leukocytes were documented semi-quantitatively in at least 15 high-power fields. The cells were stabilized for cytology and the UroVysionTM test. The supernatant was stabilized using the Matritech NMP22® Urine Collection Kit (Matritech, Freiburg, Germany). NMP22® samples were stored at −20 °C until shipping at 4–8 °C to the laboratory in Tübingen.

Haematuria was assessed as none, if neither erythrocytes nor Hb could be detected with any method (microscope or dipstick). Traces were assigned if up to five erythrocytes were found with any of the two methods. µH was defined for blood detection within the range between traces (<5 erythrocytes) and GH (>250 erythrocytes) with the dipstick or abundant erythrocytes in the sediment analysis. A similar semi-quantitative rating was performed for leukocytes with the categories none, traces, non-abundant and abundant.


NMP22 was quantitatively determined in the supernatant with the NMP22® ELISA (Matritech Inc, Newton, MA), which employed two monoclonal antibodies (MAb302-18 and MAb302-22). The analysis was performed according to the manufacturer’s protocol. The concentration of NMP22 was calculated proportionally to the colour extinction from a standard curve, and 10 units/mL was used as cut-off for positive results.

Chromosomal instability in urothelial cells was assessed using the UroVysionTM Bladder Cancer Kit (Abbott Laboratories, Abbott Park, IL, USA). This fluorescence in situ hybridization assay was applied according to the manufacturer’s protocol. DNA was denatured for 3 min at 76 °C followed by a hybridization step with a mixture of fluorochrome-marked DNA probes (CEP 3, CEP 7, CEP 17 and LSI 9p21) at 39 °C for 20 h using a HYBriteTM or ThermoBriteTM (Abbott Molecular, Des Plaines, IL, USA). For each sample, at least 25 morphologically suspicious cells were evaluated. The test was considered positive if at least four nuclei had three signals of two or three chromosomes (3, 7 and 17) or at least 12 nuclei showed one signal for the 9p21 locus.

Urinary cytology was performed by successive staining of cytospinned slides using Papanicolaou’s solutions 1a Harris’ haematoxylin solution, 2a Orange G solution (OG 6) and 3b polychromatic solution EA 50 (Merck, Darmstadt, Germany) [9]. Samples were evaluated at 400 × magnification. Results were classified as positive, suspicious or negative [10].


The distribution of data is presented by median and inter-quartile range (IQR). Odds ratios (ORs) and 95% CIs were estimated for the predictors of haematuria and of positive tumour tests with generalized estimating equation (GEE) models. The bladder cancer risk of haematuria was estimated for the highest category observed until diagnosis. The bladder cancer risk of haematuria was estimated as the rate ratio (RR) using Poisson regression, adjusted for potential confounders. All calculations were performed with SAS/STAT and SAS/IML software, version 9.2 (SAS Institute Inc., Cary, NC, USA).


Between September 2003 and January 2010, 1323 men took part at least once in the extended surveillance programme UroScreen. So far, 15 bladder tumours have been detected in 14 participants. Table 1 depicts demographic and other characteristics of the screening participants at baseline, of cases with bladder tumours, and of subjects with at least one occurrence of erythrocytes or leukocytes during this period. The median age of cases with bladder cancer was 64 years. The median age of the cohort was 60 years in 2010, for participants with µH 63 years and 62 years for GH. The median age was 72 years for abundant urinary leukocytes. The proportion of never smokers was 33.9% in the cohort, 28.6% in cases, 35.1% in participants with µH and 30.6% in men with any GH.

Table 1.  Characteristics of male participants of UroScreen with former occupational exposure to aromatic amines
  • *

    µH, microhaematuria, or inflammation non-abundant if 5 ≤ 250 cells (erythrocytes respectively leukocytes) could be detected with a dipstick or microscopically in the sediment; GH, gross hematuria, or abundant leukocytes if ≥250 cells could be detected.

N132314 (1.06%)408 (30.84%)85 (6.42%)224 (16.93%) 11 (0.83%)
Age in 2010 (years)      
 Median (range)60 (28–91)66 (44–81)63 (32–91)62 (38–81)67 (42–90)72 (52–81 )
 Age at diagnosis 64 (38–76)    
Smoking status at baseline      
 Never447 (33.89%)(28.57%)143 (35.05%)26 (30.59%)64 (28.70%)5 (45.45%)
 Former491 (37.23%)7 (50.00%)148 (36.27%)29 (34.12%)72 (32.29%)2 (18.18%)
 Current381 (28.89%)3 (21.43%) 117 (28.68%)30 (35.29%)87 (39.01%)4 (36.36%)
Former bladder cancer21 (1.59%)3 (21.43%)9 (2.21%)3 (3.53%)6 (26.79%)0 (0%)

Table 2 shows the prevalence of haematuria in cases by histology, together with other information on the last urine sample before diagnosis. GH was detected in four out of nine cases with high-grade bladder cancer while eighth out of all 14 tumours were free of blood or contained only traces. µH was present in three of the tumours. However, the interval between screening and diagnosis varied considerably and exceeded 12 months in four cases. Leukocytes could be found at least in traces in most samples except two with low creatinine concentrations.

Table 2.  Histopathological findings, haematuria and inflammation in the last screening round before diagnosis of 15 bladder lesions in 14 cases in the prospective study UroScreen
CaseHistopathological findingMonths before diagnosisCreatinine (g/L)Erythrocytes*Leukocytes*
  • *

    µH, microhaematuria, or inflammation non-abundant if 5 ≤ 250 cells (erythrocytes respectively leukocytes) could be detected with a dipstick or microscopically in the sediment; GH, gross hematuria, or abundant leukocytes if ≥250 cells could be detected.

 1High grade240.87GHTraces
 3Low grade100.23µHTraces
 4Low grade21.59TracesTraces
 5Low grade20.44NoneNone
 6Low grade30.74µHTraces
 7High grade71.28GHTraces
 8High grade261.01NoneTraces
 9High grade10.24NoneNone
10High grade142.92NoneTraces
11High grade01.53GHNon-abundant
12High grade20.32GHNon-abundant
13High grade182.93TracesTraces
14High grade20.72NoneTraces

Potential predictors of haematuria are presented in Table 3. Leukocytes were strongly associated with both µH (abundant: OR 8.34, 95% CI 2.26–30.69) and GH (abundant: OR 22.25, 95% CI 6.42–77.06). µH was less frequently observed in urines with creatinine <0.5 g/L (OR 0.43, 95% CI 0.34–0.54). Current smokers had marginally more haematuria (µH: OR 1.24, 95% CI 0.97–1.58; GH: OR 1.72, 95% CI 0.95–3.12).

Table 3.  Potential predictors of microhaematuria in 5067 urine samples from 1312 male participants (samples with gross haematuria not included) and gross haematuria in 5181 urine samples from 1323 male participants of the UroScreen cohort
Variable at samplingCategoryMicrohaematuriaGross haematuria
N (samples)OR95% CIN (samples)OR95% CI
LeukocytesNone16091 16281 
Abundant88.342.26–30.69 1122.256.42–77.06
Creatinine<0.5 g/L8340.430.34–0.548430.610.32–1.15
0.5–2.5 g/L39471 40421 
>2.5 g/L2861.060.85–1.322961.470.77–2.78
Age<60 years28981 29671 
≥60 years21691.180.96–1.4522140.810.49–1.33
Smoking statusNever17891 18191 
Former urogenital tumour except bladderNone49481 5051 
Yes 1191.330.83–2.121252.650.91–7.76
Former bladder cancerNone49981 51061 
Incident bladder cancerNone50351 5141 

The risk of haematuria for bladder cancer is depicted in Table 4. Ever µH was associated with a RR of 0.72 (95% CI 0.11–4.78) and ever GH with a RR of 3.82 (95% CI 0.50–29.15). The cancer-predictive value of µH was low (1.24%) and slightly higher for GH (11.43%) (Table 5).

Table 4.  Risk of haematuria and other factors on newly detected bladder lesions in male participants of the UroScreen cohort
Potential risk factorPerson-YearsCasesRate Ratio95% CI
Haematuria until diagnosis    
 Ever gross haematuria310.1143.820.50–29.15
Leukocytes until diagnosis    
 Never or traces3809.16 111.0 
 Non-abundant or ever abundant939.3330.620.13–2.86
Age at entry    
 <60 years2930.6471.0 
 ≥60 years1817.8571.660.47–5.85
Smoking status    
 Never 1411.1541.0 
Former bladder cancer    
 None4676.77 111.0 
Table 5.  Evaluation of the cancer-predictive value of haematuria for bladder lesions in the UroScreen cohort
 ResultAll lesions N= 15Papilloma N= 2Low grade N= 4High grade N= 9
MicrohaematuriaTrue positive3120
False negative8125
True negative1039   
False positive239   
Positive predictive value1.24%0.42%0.83%0%
Negative predictive value99.24%99.90%99.81%99.52%
Gross haematuriaTrue positive4004
False negative 11245
True negative1278   
False positive31   
Positive predictive value 11.43%0%0% 11.43%
Negative predictive value99.15%99.84%99.69%99.61%

Table 6 shows the association of haematuria with tumour tests. Both µH and GH influence NMP22 positivity (OR 1.63, 95% CI 1.06–2.51 and OR 3.94, 95% CI 1.93–8.03, respectively). Urinary leukocytes had a strong effect on the NMP22 test results (abundant: OR 8.90, 95% CI 1.58–50.16). Erythrocytes and leukocytes did not show an influence on the cytology and UroVysionTM test. Incident bladder cancer was associated with test positivity (NMP22: OR 4.25, 95% CI 1.69–10.68, UroVysion: OR 11.14, 95% CI 3.18–39.04, cytology: OR 32.23, 95% CI 10.02–103.65). Smoking and former bladder cancer were associated with positivity of cytology and the UroVysionTM test, but not with NMP22 where current smokers were less frequently associated with positive results (OR 0.51, 95% CI 0.28–0.90). The UroVysionTM test was more frequently positive in urines with creatinine <0.5 g/L (OR 2.73, 95% CI 1.63–4.57).

Table 6.  Potential influences of haematuria and other factors on positivity of tumour tests in urine samples from male participants of the UroScreen cohort
Variable at samplingNMP22 N= 5167Cytology N= 4911UroVysion N= 4822
Categoryn (npos)OR (95% CI)n (npos)OR (95% CI)n (npos)OR (95% CI)
  • *

    Risk of haematuria for positivity of cytology: none or traces as a reference group vs the combined group of microhaematuria and gross haematuria; †Risk of leukocytes for positivity of cytology and UroVysionTM test: none or traces as the reference group vs the combined group of non-abundant and abundant leukocytes.

Haematuria*None2529 (48)13818 (14)12359 (36)1
Traces1555 (43)1.15 (0.74–1.78)  1459 (20)1.09 (0.62–1.92)
Microhaematuria969 (40)1.63 (1.06–2.51)1004 (7)1.20 (0.47–3.04)894 (12)0.96 (0.50–1.84)
Gross haematuria 114 (14)3.94 (1.93–8.03)  110 (2)0.81 (0.23–2.87)
Leukocytes†None1623 (29)14522 (20)14522 (65)1
Traces3212 (78)1.06 (0.69–1.65)    
Non-abundant321 (35)4.32 (2.36–7.90)300 (1)1.19 (0.24–5.82)300 (5)1.17 (0.45–3.03)
Abundant 11 (3)8.90 (1.58–50.16)    
Creatinine<0.5 g/L840 (12)0.55 (0.29–1.06)  760 (25)2.73 (1.63–4.57)
0.5–2.5 g/L4032 (117)1  3790 (44)1
>2.5 g/L295 (16)1.86 (1.06–3.27)  271 (1)0.28 (0.03–2.40)
Prevalent bladderNone5094 (141)14752 (17)14752 (64)1
CancerYes73 (4)1.09 (0.39–3.01)70 (4)9.35 (2.02–43.42)70 (6)4.33 (1.35–13.90)
Incident bladderNone5130 (140)14785 (16)14785 (64)1
CancerYes37 (5)4.25 (1.69–10.68)37 (5)32.23 (10.02–103.7)37 (6) 11.14 (3.18–39.04)
SmokingNever1814 (53)11679 (2)11679 (15)1
StatusFormer2124 (71)1.13 (0.75–1.69)1990 (14)6.90 (1.60–29.85)1990 (35)2.00 (1.05–3.81)
Current1229 (21)0.51 (0.28–0.90) 1153 (5)4.64 (0.84–25.83)1153 (20)2.14 (1.06–4.33)
Age<60 years2959 (60)12741 (10)12741 (39)1
≥60 years2208 (85)1.46 (0.98–2.17)2081 (11)1.38 (0.56–3.44)2081 (31)1.05 (0.61–1.80)


The role of haematuria in bladder cancer screening was evaluated in a prospective cohort of 1323 chemical workers between 2003 and 2010. Results from dipstick and subsequent sediment analysis were combined to classify urine samples as free of blood or with traces of µH or GH. A similar assessment was performed for leukocytes which were a strong predictor of haematuria. Our results do not indicate an association of µH with bladder tumours. The PPV of µH for bladder cancer was as low as 1.2%. Haematuria and leukocytes interfered with NMP22 but not with cytology and UroVysionTM test results.

Bladder cancer screening in the general population is not yet an accepted standard as a result of the low incidence of the disease, raising concerns about cost effectiveness [11]. However, the availability of tumour tests and treatments improving survival fulfill general requirements for cancer screening. Haematuria and exposure to aromatic amines have been considered for establishing at-risk populations. So far, few screening cohort studies have been conducted (e.g. [4,5,12,13]). Because chemical workers with exposure to aromatic amines were at excess risk for bladder cancer [14,15] DGUV offers an annual surveillance programme with investigation of the urine status and cytology. UroScreen became part of this programme and included the determination of NMP22 and UroVysionTM.

A major advantage of UroScreen is the prospective design with repeated investigations because performance measures such as PPV have only be estimated in a longitudinal design [16,17]. Several biases of screening studies have been described [17]. Selection bias is of minor concern because the participation rate was about 90%. All participants of UroScreen were recruited from an on-going surveillance programme. Therefore, prevalent cases were less likely. However, the compliance to participate regularly in the annual screening rounds was low.

A challenge in screening for bladder cancer is the low incidence and therefore the need for defining at-risk populations [18]. Although we enrolled workers with former exposure to aromatic amines, we observed only 15 bladder tumours in 14 participants. The average age of the cohort was several years younger than the age at diagnosis (as presented in the German cancer database at Robert Koch Institute ( Because the surveillance programme was established for all workers with occupational exposure, exclusion criteria such as young age, former or newly detected bladder cancer or never smoking were not applied. While historical exposure resulted in very high risks for bladder cancer in chemical workers [15], technological progress and the ban of certain aromatic amines in the dyestuff production may have reduced the risks as observed in this and another study in Germany [19]. Other screening cohorts also face a small number of cases, for example in British men [12]. In a US cohort many participants had already undergone a recent urinalysis where prevalent cases are less likely to be detected [13]. This holds also for UroScreen.

Initial efforts at bladder cancer screening have focused on the detection of haematuria [1]. Especially high-grade tumors can become muscle invading, which may lead to haematuria. GH is therefore considered an important sign of bladder cancer. A classification into µH and GH is important because four out of nine UroScreen cases with high-grade bladder cancer showed abundant erythrocytes until diagnosis. While visible blood is a relatively rare symptom, asymptomatic occult urinary bleeding is a common finding. µH is an intermittent symptom in urine samples, where the probability of detection increases with the number of samples per subject. Various factors influence the detection of blood in urine and thus the measures of prevalence or risk. Urinary leukocytes turned out as major predictor of both µH and, even stronger, GH. While dipsticks can also detect Hb, the analysis of the sediment allows only counting intact cells. A detailed technical assessment of the diagnostic tests has been given by Rodgers et al. [7]. Dipsticks are point-of-care tests where readouts are possible that provide an automated calling of semi-quantitative results on the content of erythrocytes and leukocytes. Microscopic evaluation needs expertise and can be prone to observer bias. Automated investigations are possible but not commonly applied in practice. Further, microscopy was evaluated as generating more false-negative results, and dipstick testing might generate more false-positive results. Here we combined results from both methods. Only 40% of our samples were free of erythrocytes or Hb, and 2% demonstrated GH. Misclassification of haematuria is possible by low cell content in urines with <0.50 g/L creatinine. This cut-off was chosen according to the 10th percentile of creatinine in elderly German men [20]. Low creatinine might serve as a potential proxy for retention time and fluid consumption.

Current guidelines for US urologists recommend cystoscopic evaluation of elderly adults with µH. Former and incident bladder cancer were predictors of GH but not of µH. Further, µH was not associated with a bladder cancer risk. This was also reflected in the low PPV of 1.2% for µH that increased up to 11.4% for GH, in particular for high-grade tumours. A low PPV has also been reported for NMP22® BladderChek [13]. These low PPVs should be critically taken into account in clinical routine although PPVs can be improved in subjects at excess risk for bladder cancer [21]. However, dipsticks are important tools to determine urinary blood, leukocytes and creatinine for tumour tests because these parameters influenced the results.

The interference of erythrocytes and leukocytes with NMP22 positivity confirmed observations from an experimental approach by adding blood to urine samples and from subjects with a urinary tract infection [22]. Leukocytes were the strongest predictor of NMP22 positivity. These results need consensus on diagnostic algorithms before cystoscopy should be recommended. We recommended a second examination after treatment of an infection but the compliance was low. Further, an experience of the invasiveness of cystoscopy reduced the compliance for subsequent cystoscopies. However, neither erythrocytes nor leukocytes showed an influence on the detection of aberrant urothelial cells with cytology or the UroVysionTM test. An evaluation of the NMP22 or UroVysion results will be subject to another analysis.

In conclusion, the UroScreen study revealed for µH a low PPV and lack of an obvious association with bladder cancer. However, there was a strong influence of haematuria and leukocytes on the protein-based tumour test NMP22®. Erythrocytes and leukocytes should be determined at least semi-quantitatively for the interpretation of positive NMP22 test results. In addition, a panel of tumour tests that includes methods not affected by the presence of erythrocytes or leukocytes such as cytology and UroVysionTM would improve bladder cancer screening.


The study received grants from German Social Accident Insurance (DGUV), Sankt Augustin, Germany. Abbott GmbH & Co. KG, Wiesbaden, Germany, supplied the UroVysionTM kits at no cost.


None declared.


*UroScreen Group:

BASF SE, Occupational Medicine and Health Protection, Ludwigshafen: Bernd Scheuermann, Friedhelm Eberle, Thomas Mayer, Michael Nasterlack

Berufsgenossenschaft RCI, Fachreferat Arbeitsmedizin, Bereich Prävention, Heidelberg: Harald Wellhäußer, Matthias Kluckert; Organisationsdienst für nachgehende Untersuchungen (ODIN), Heidelberg: Reinhard Detzner

Institute for Prevention and Occupational Medicine of German Social Accident Insurance, Institute of Ruhr University Bochum (IPA), Bochum: Beate Pesch, Dirk Taeger, Nadine Bonberg, Heike Bontrup, Georg Johnen, Judith Delbanco, Evelyn Heinze, Thomas Brüning

Currenta GmbH & Co.OHG, Security – Health Protection, Leverkusen: Martin Pelster, Gabriele Leng

Department of Urology, Eberhard-Karls-University, Tübingen: Gerhard Feil, Karl-Dietrich Sievert, Séverine Huber, Margarete Geiger, Erika Senger, Valentina Gerber, Andrea Hohneder, Gundi Beger, Ursula Kuehs, Jörg Hennenlotter, Arnulf Stenzl