Investig Clin Urol. 2019 Jul;60(4):235-243. English.
Published online May 20, 2019.
© The Korean Urological Association, 2019
Original Article

Establishment of the Seoul National University Prospectively Enrolled Registry for Genitourinary Cancer (SUPER-GUC): A prospective, multidisciplinary, bio-bank linked cohort and research platform

Chang Wook Jeong,1 Jungyo Suh,1 Hyeong Dong Yuk,1,2 Bum Sik Tae,1,3 Miso Kim,4 Bhumsuk Keam,4 Jin Ho Kim,5 Sang Youn Kim,6 Jeong Yeon Cho,6 Seung Hyup Kim,6 Kyung Chul Moon,7 Gi Jeong Cheon,8 Ja Hyeon Ku,1 Hyeon Hoe Kim,1 and Cheol Kwak1
    • 1Department of Urology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
    • 2Department of Urology, Inje University Sanggye Paik Hospital, Seoul, Korea.
    • 3Department of Urology, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Korea.
    • 4Department of Internal Medicine, Seoul National University Hospital, Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea.
    • 5Department of Radiation Oncology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
    • 6Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
    • 7Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
    • 8Department of Nuclear Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Received February 07, 2019; Accepted March 19, 2019.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose

To establish a prospective, comprehensive, multidisciplinary, bio-bank linked genitourinary cancer cohort based on standard real practice.

Materials and Methods

We established the Seoul National University Prospectively Enrolled Registry for Genitourinary Cancer (SUPER-GUC), a prospective cohort clinical database and bio-specimen repository system for prostate cancer (SUPER-PC), renal cell carcinoma (SUPER-RCC), and urothelial cancer (SUPER-UC) at a high-volume, tertiary institution. Each cohort consists of several sub-cohorts based on treatment or disease status. Detailed longitudinal clinical information, and general and disease specific patient-reported outcomes are captured. We use the same evaluation format and questionnaires for all participating departments. Patients' blood, urine, tumor, and normal tissues are collected. The number of registered patients and their basic characteristics are summarized. For the surgical sub-cohort, study participation, bio-specimen, and tissue banking rates are analyzed.

Results

Since March 2016, 11 sub-cohorts for all disease statuses have been opened, ranging from low-risk localized to metastatic disease. SUPER-PC, SUPER-RCC, and SUPER-UC enrolled 929, 796, and 1,221 patients, respectively. Study participation, bio-sampling, and fresh frozen tumor banking rates of surgical sub-cohorts were 89.0% to 93.1%, 91.2% to 99.1%, and 56.9% to 79.1%, respectively.

Conclusions

SUPER-GUC is a study platform for comparative outcome, quality-of-life, and translational (genetics, biomarkers) research for genitourinary cancer.

Keywords
Biological specimen banks; Cohort studies; Prospective studies; Urogenital neoplasms

INTRODUCTION

Genitourinary cancers are commonly diagnosed malignancies worldwide and significantly impact human health. Prostate cancer (PC) is the most commonly diagnosed malignancy in men in the United States and second most frequent cancer in men worldwide in 2018 [1, 2]. Bladder and kidney cancers are globally the sixth and ninth most common cancers, respectively, in men [1]. European countries have the highest incidence of these all three genitourinary cancers [1, 3]. Furthermore, the incidence and mortality of these three genitourinary cancers have increased 2.5- and 1.6-fold between 1990 and 2013, respectively [4]. This substantial increasing trend of global genitourinary cancer burden has not subsided.

While randomized controlled trials (RCTs) provide the highest level of evidence, they are not always feasible and sometimes impossible [5]. Narrow eligibility criteria and highly controlled settings of RCTs can rather limit their applicability [5]. Alternatively, high-quality cohort studies sometimes generate valuable information that is generally applicable, even in situations in which RCT is impractical [6].

Accordingly, we aimed to develop a prospective, comprehensive, multidisciplinary, bio-bank-linked cohort based on standard real practice for PC, renal cell carcinoma (RCC), and urothelial cancer (UC). After preparing for three years, we established the Seoul National University Prospectively Enrolled Registry for Genitourinary Cancer (SUPER-GUC) in March 2016. The major goals of the SUPER-GUC are as follows: 1) to conduct comparative outcome studies between various treatment options, 2) to identify prognostic factors for disease progression and mortality, 3) to facilitate various type of translational research including genetic or molecular profiling and biomarker studies, 4) to understand patients' quality of life (QoL) and promote QoL research including a patient-oriented outcome study and comparative-effectiveness research [7], 5) to investigate changes in body composition and its impacts on outcomes, and 6) to understand the influence of aging and fragility on treatment and cancer in elderly patients.

The present paper describes the design and methodology of SUPER-GUC. Furthermore, we summarize current patient enrollment status and basic demographics.

MATERIALS AND METHODS

1. Ethics statement

All study protocols for SUPER-PC, SUPER-RCC, and SUPER-UC were approved by the Institutional Review Board (IRB) of Seoul National University Hospital (Seoul, Korea). The approval numbers are H-1506-121-682, H-1506-120-682, and H-1506-122-682, respectively. Informed consent was obtained by all subjects when they were enrolled.

2. Organization

As faculty providing direct treatment, four uro-oncologists, two medical oncologists, and one radiation oncologist, who mainly manage treat genitourinary cancer patients, participate with this cohort. They exclusively manage almost all genitourinary cancer patients in our tertiary high-volume institution. As supporting faculty, three uroradiologists, one nuclear medicine physician, and one uropathologist exclusively interpret medical images and pathological results. Participating faculty are all well-experienced, dedicated specialists in their field. We have one permanent information technology (IT) engineer consultant and three IT advisors.

3. Sub-cohorts and eligibility criteria

SUPER-GUC consists of three cohorts based on cancer type, SUPER-PC, SUPER-RCC, and SUPER-UC. Each cohort is composed of several sub-cohorts based on treatment or disease status. Names of the sub-cohorts and their eligibility criteria are described in Table 1.

Table 1
Sub-cohorts of the SUPER-GUC and their eligibility criteria

4. Patient process, data collection, and bio-specimen repository

In principle, the cohort is based on real clinical practice, and the study does not interfere with actual practice. All patients are enrolled following provision of written informed consent for the cohort study based on cancer type as well as for the additional bio-specimen registry.

All data were collected using the Research Electronic Data Capture (REDCap) system in an independent server with a triple back-up system. REDCap is a secure, web-based application designed to support data capture for research studies [8]. Electronic case-report forms (eCRF) consist of several forms (designated as ‘instruments’ in REDCap), and selected forms can be repeatedly entered to capture longitudinal data. Furthermore, some common forms are shared by all sub-cohorts in SUPER-GUC. We categorized data entering forms as once entering, repeatedly entering, and revisingly entering forms. After entering all data in once entering type form, it is finalized and locked. We can handle repeating data using repeatedly entering forms, such as questionnaires or transurethral resection of bladder tumor information. In revisingly entering forms, we can revise data until it is finalized. For instance, the last follow-up date is revised following every hospital visit in this of form.

We constructed eCRF forms to be as detailed as possible. For example, SUPER-PC-Radical Prostatectomy (RP) has 20 forms with 784 fields. Table 2 shows construction of the eCRF for SUPER-PC-RP. Fig. 1 depicts the exemplary data collection process for SUPER-PC-RP with eCRFs. Each sub-cohort has its own predefined data collection process.

Fig. 1
Data collection process for the Seoul National University Prospectively Enrolled Registry for Prostate Cancer-Radical Prostatectomy (SUPER-PC–RP) with electronic case report forms. Preop., preoperative; character., characteristics; postop., postoperative; PO, postoperative; Qs, questionnaires; CARE, Convalescence And Recovery Evaluation; A/E, adverse events; PSA, prostate-specific antigen.

Table 2
Architecture of electronic case-report forms for Seoul National University Prospectively Enrolled Registry for Prostate Cancer-Radical Prostatectomy (SUPER-PC-RP)

We selected questionnaires according to two principles. First, the Korean version should be validated and easily incorporated in daily practice. Some questionnaires were already validated, and some were validated by our team for SUPER-GUC. For measuring health-related utility and general QoL, we universally use EQ-5D-5L across all sub-cohorts. In addition, we use the International Prostate Symptom Score (IPSS), International Index of Erectile Function-5 (IIEF-5), and Expanded Prostate Cancer Index Composite for Clinical Practice (EPIC-CP) for PC patients. The 15-item Functional Assessment of Cancer Therapy-Kidney Symptom Index (FKSI-15) and the Functional Assessment of Cancer Therapy-Vanderbilt Cystectomy Index (FACT-VCI) were selected as disease-specific questionnaires for RCC and cystectomy patients, respectively. We also use the Convalescence And Recovery Evaluation (CARE) questionnaire to evaluate short-term (≤3 months) QoL after major surgery [9]. The G8 geriatric screening tool is used for patients who are 65 years or older [10, 11].

Surgical complications are evaluated and collected using the revised Clavien–Dindo system and European Association of Urology (EAU) guidelines [12, 13]. All treatment-related adverse events are evaluated with the same forms of the Common Terminology Criteria for Adverse Events (CTCAE) ver. 4.0.3. Regardless of treating departments, we standardized all evaluation formats, including questionnaires and adverse events assessment.

To measure body composition based on bioelectrical impedance analysis (BIA), we use the InBody 570 (InBody Co., Ltd., Seoul, Korea). This is a well-established method to determine body composition such as lean muscle mass and body fat mass [14, 15, 16].

We collect patients' pre-treatment whole blood, serum, buffy coat, plasma, and urine samples at the time of entering new sub-cohorts. Collected samples are divided in microvials and stored in a −80℃ deep freezer or −195℃ liquid nitrogen container according to the sample type at the Seoul National University Hospital Human Biobank. Tumor and normal tissues are collected in the operating room or frozen biopsy room up to six vials each and immediately stored in a −195℃ liquid nitrogen tank at the Seoul National University Hospital Cancer Tissue Bank. These two banking systems are qualified, centralized bio-banking systems at our institution that have been in operation for almost a decade. Formalin-fixed, paraffin-embedded tissue blocks are available in virtually 100% patients managed by the Department of Pathology.

5. Outcome measurements

A major point of interest regarding the cohort is oncologic outcomes. Baseline cancer status and general condition are evaluated at the time of enrollment for each sub-cohort. Treatment response, time of recurrence, and survival are evaluated. Furthermore, baseline cancer status and oncologic outcome are repeatedly evaluated for every single major treatment in advanced or metastatic disease. Date and cause of death are confirmed by regular linkage with death registry at the Statistics Korea.

Functional outcomes measured in PC patients include urinary and sexual function. For the nephrectomy sub-cohort, renal function was also determined using estimated glomerular filtration rate or renal scan and progression to end-stage renal disease.

6. Statistical analysis

We summarize current enrollment status, basic demographics, and sampling information. Data are expressed as the mean±standard deviation. A p-values <0.05 were considered statistically significant. All statistical analyses were performed using R for Windows, version 3.5.1 (http://www.r-project.org).

RESULTS

The first patient was enrolled March 7, 2016 in SUPER-PC. At the end of December, 2018, a total of 929, 796, and 1,221 patients were enrolled in SUPER-PC, SUPER-RCC, and SUPER-UC, respectively. Results of patient enrollment are summarized in Table 3. Table 4 shows rates of study participation, bio-sampling, and fresh frozen tumor banking and baseline characteristics of surgical sub-cohorts.

Table 3
Patient enrollment status of Seoul National University Prospectively Enrolled Registry for Genitourinary Cancer (SUPER-GUC) at the end of December, 2018

Table 4
Participation, banking rates, and baseline characteristics of surgical sub-cohorts in SUPER-GUC

For SUPER-PC-RP, we also developed an online interactive data visualization and analysis platform using Tableau Server ver. 10.3.1 (Tableau Software, Inc., Seattle, WA, USA) (Fig. 2) [17, 18]. Results are interactively presented in real time as we change the dimensional variables.

Fig. 2
Image captures of online interactive data visualization and analysis platform for Seoul National University Prospectively Enrolled Registry for Prostate Cancer-Radical Prostatectomy (SUPER-PC-RP). Dashboards are interactively changed when dimensional variables are changed in left panel. (A) Enrollment status, (B) operative methods and results, (C) pathologic outcomes, (D) example of interactive analysis. Pathologic Gleason Score by operative type and D'Amico classification.

DISCUSSION

There are several types of prospective cohort or registries [19]. Population-based cohorts systematically collect data on all or randomly selected patients with a certain disease in a given geographic area within a given time [20]. They usually link with national claims data and statistics [21]. Thus, representativeness and generalizability are the advantage, while incomplete or inaccurate data coding and lack of detailed information are potential serious pitfalls [21]. Community and/or multicenter cohorts may be the most common form of cohorts [19]. A greater number of involved institutions increases the generalizability. However, relatively high cost, standardization between institutions, and maintaining high quality are ongoing challenges. Single institutional cohort may be limited by its lack of representativeness; however, it has the advantage of being able to collect additional detailed information [19]. Furthermore, it is relatively easy to maintain high quality.

Traditionally, numerous studies were conducted as retrospective single center case series, rather than an actual cohort [6, 19, 22]. Occasionally, the reports insisted they used a prospectively collected database, but they were usually limited by many biases and missing data. Thus, we initiated SUPER-GUC as a prospective, single institutional cohort with flexible structure; this can be extended as multicenter cohort in the future. Additionally, although we started it as a single institutional cohort, we endeavored to overcome limitation of single-center cohort and maximize its quality and potential for utilization.

First, we organized it as multidisciplinary cohort, which collects data from all related departments using standardized methods. We also unified data collection forms and timing, especially QoL questionnaires and adverse events assessment. Patients can select different treatment provided by different specialties, even for the same disease status. For example, localized PC patients may undergo either RP provided by a urologist or radiation therapy provided by a radiation oncologist [23]. Furthermore, patients may have sequential treatments through different departments dependent upon disease progression. For instance, after radical cystectomy performed by a urologist, adjuvant or palliative chemotherapy can be provided by a medical oncologist. Based on this multidisciplinary endeavor, we can compare any treatment outcome as well as that of any follow-up evaluation throughout long-term treatment without cessation.

Next, we constructed a comprehensive cohort consisting of sub-cohorts for all possible disease conditions and treatments. Patients may be entered to a specific sub-cohort from other sub-cohorts dependent upon disease progression; alternatively, newly referred patients may be enrolled directly to the sub-cohort. This sub-cohort structure allows us to effectively recruit patients, especially those with a more advanced condition, and collect specific detailed data focusing on the status of each patient. The Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) is one of the most successful prospective PC cohorts [19, 24]. This cohort recruited over 15,000 patients at all stages from 43 urology practices for three decades [19, 24, 25]. However, only newly diagnosed PC patients are eligible in a single-phase design [24, 25]. Therefore, localized cancer and initial treatment are highly focused, whereas data after progression or later phase treatment (e.g., androgen receptor-targeted treatment for castration-resistant PC) are limited. We expect we can overcome this using our comprehensive, multi-sub-cohort design.

Third, the bio-specimen repository is another important feature of SUPER-GUC. Traditionally, all formalin-fixed, paraffin-embedded tissue blocks of surgical specimens are stored in our institution. However, we extend this by collecting pre-treatment blood and urine in most cases and freshly frozen tumor and normal tissues in all possible cases. These bio-specimens are stored and managed by qualified, centralized bio-banking systems that are certified by the government. Thus, SUPER-GUC can support a variety of translational research, such as biomarker or genetic profiling studies. For instance, we are currently conducting a study to evaluate the association between congenital immune deficiency with cancer characteristics and outcomes in 540 bladder cancer patients. Several urine biomarker studies for bladder cancer were conducted or are currently in progress. We also performed comprehensive genetic characterization of transcription factor E3 (TFE3)-overexpressed RCC using the SUPER-RCC cohort. Recently, we conducted a predictive serum biomarker study that differentiates benign tumors from RCC using SUPER-RCC-Nephrectomy (Nx). We are cautiously confident that SUPER-GUC will be an important translational research platform.

Fourth, even though it is institutional cohort, mortality information is regularly collected from the government death registry at the Statistics Korea. Accordingly, we can assure survival data, the most important outcome of SUPER-GUC.

Finally, we collect a variety of data for comprehensive future studies. Using validated instruments, patient-reported health-related QoL are evaluated. Since usual health-related QoL questionnaires cannot sensitively capture differences in QoL between surgery types, we also collect CARE questionnaire before and within 3 months after operation [9]. To evaluate the effect of vulnerability, we also use the G8 geriatric screening tool for elderly patients for all treatments [10, 11]. Moreover, to more precisely measure muscle and fat mass and determine their association with outcome, we regularly measure body composition using BIA [14, 15, 16].

SUPER-GUC also has several limitations. Since it is a single-center cohort, it is difficult to enroll a large patient number and difficult to represent whole population. However, its flexible design and open structure can expend SUPER-GUC for multi-center collaboration. Actually, SUPER-PC-Active Surveillance (AS) is being adapted for a nationwide, multicenter cohort of the Korean Urological Oncology Society by reducing variables and restructuring the eCRF. Because non-surgical sub-cohorts were opened later, numbers of patients in these sub-cohorts are relatively small. An outpatient-based patient recruiting system has been recently established. Therefore, we expect a rapid increase in the size of non-surgical sub-cohorts. Furthermore, although inherent bias from an observational study is inevitable, it may be minimized using a recent statistical adjusting methodology [6, 26, 27].

There are many prospective cohorts in the uro-oncology field; however, they are for specific cancer types and are generally limited to specific disease conditions or treatments [19, 24, 28, 29, 30]. To our knowledge, SUPER-GUC is the first comprehensive, prospective, bio-bank-linked cohort covering all major genitourinary cancers for all disease statuses and treatments.

CONCLUSIONS

In summary, we successfully established a comprehensive, prospective, multidisciplinary, bio-bank-linked genitourinary cancer cohort, SUPER-GUC. It will support a variety of research regarding comparative outcomes, QoL studies, and translational research such as genetic or biomarker studies for prostate, kidney, and UCs.

Notes

CONFLICTS OF INTEREST:The authors have nothing to disclose.

ACKNOWLEDGMENTS

This study was supported by grants from the National R&D Program for Cancer Control (HA17C0039) and the Korea Health Technology R&D Project (HI14C2404) through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea. None of the sponsors had any access to the data or any influence on or access to the analysis plan, the results, or the manuscript.

The bio-specimens for this study were managed by the Seoul National University Hospital Cancer Tissue Bank and the Seoul National University Hospital Human Biobank, a member of the Korea Biobank Network, which is supported by the Ministry of Health and Welfare. All samples derived from these banking systems were obtained with informed consent under institutional review board-approved protocols.

References

    1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68:394–424.
    1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin 2018;68:7–30.
    1. Znaor A, Lortet-Tieulent J, Laversanne M, Jemal A, Bray F. International variations and trends in renal cell carcinoma incidence and mortality. Eur Urol 2015;67:519–530.
    1. Dy GW, Gore JL, Forouzanfar MH, Naghavi M, Fitzmaurice C. Global burden of urologic cancers, 1990-2013. Eur Urol 2017;71:437–446.
    1. Lavallée LT, Fergusson D, Breau RH. The role of randomized controlled trials in evidence-based urology. World J Urol 2011;29:257–263.
    1. Yang W, Zilov A, Soewondo P, Bech OM, Sekkal F, Home PD. Observational studies: going beyond the boundaries of randomized controlled trials. Diabetes Res Clin Pract 2010;88 Suppl 1:S3–S9.
    1. Ahn S, Lee M, Jeong CW. Comparative quality-adjusted survival analysis between radiation therapy alone and radiation with androgen deprivation therapy in patients with locally advanced prostate cancer: a secondary analysis of Radiation Therapy Oncology Group 85-31 with novel decision analysis methods. Prostate Int 2018;6:140–144.
    1. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42:377–381.
    1. Hollenbeck BK, Dunn RL, Wolf JS Jr, Sanda MG, Wood DP, Gilbert SM, et al. Development and validation of the convalescence and recovery evaluation (CARE) for measuring quality of life after surgery. Qual Life Res 2008;17:915–926.
    1. Bellera CA, Rainfray M, Mathoulin-Pélissier S, Mertens C, Delva F, Fonck M, et al. Screening older cancer patients: first evaluation of the G-8 geriatric screening tool. Ann Oncol 2012;23:2166–2172.
    1. Decoster L, Van Puyvelde K, Mohile S, Wedding U, Basso U, Colloca G, et al. Screening tools for multidimensional health problems warranting a geriatric assessment in older cancer patients: an update on SIOG recommendations†. Ann Oncol 2015;26:288–300.
    1. Dindo D, Demartines N, Clavien PA. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg 2004;240:205–213.
    1. Mitropoulos D, Artibani W, Graefen M, Remzi M, Rouprêt M, Truss M. European Association of Urology Guidelines Panel. Reporting and grading of complications after urologic surgical procedures: an ad hoc EAU guidelines panel assessment and recommendations. Eur Urol 2012;61:341–349.
    1. Gibson AL, Holmes JC, Desautels RL, Edmonds LB, Nuudi L. Ability of new octapolar bioimpedance spectroscopy analyzers to predict 4-component-model percentage body fat in Hispanic, Black, and White adults. Am J Clin Nutr 2008;87:332–338.
    1. Maeda K, Koga T, Nasu T, Takaki M, Akagi J. Predictive accuracy of calf circumference measurements to detect decreased skeletal muscle mass and European Society for Clinical Nutrition and Metabolism-defined malnutrition in hospitalized older patients. Ann Nutr Metab 2017;71:10–15.
    1. Koo BK, Kim D, Joo SK, Kim JH, Chang MS, Kim BG, et al. Sarcopenia is an independent risk factor for non-alcoholic steatohepatitis and significant fibrosis. J Hepatol 2017;66:123–131.
    1. Ko I, Chang H. Interactive data visualization based on conventional statistical findings for antihypertensive prescriptions using National Health Insurance claims data. Int J Med Inform 2018;116:1–8.
    1. Ko I, Chang H. Interactive visualization of healthcare data using tableau. Healthc Inform Res 2017;23:349–354.
    1. Gandaglia G, Bray F, Cooperberg MR, Karnes RJ, Leveridge MJ, Moretti K, et al. Prostate cancer registries: current status and future directions. Eur Urol 2016;69:998–1012.
    1. Parkin DM. The evolution of the population-based cancer registry. Nat Rev Cancer 2006;6:603–612.
    1. Kang M, Ku JH, Kwak C, Kim HH, Jeong CW. Effects of aspirin, nonsteroidal anti-inflammatory drugs, statin, and COX2 inhibitor on the developments of urological malignancies: a population-based study with 10-year follow-up data in Korea. Cancer Res Treat 2018;50:984–991.
    1. Kim BS, Tae BS, Ku JH, Kwak C, Kim HH, Jeong CW. Rate and association of lower urinary tract infection with recurrence after transurethral resection of bladder tumor. Investig Clin Urol 2018;59:10–17.
    1. Mottet N, Bellmunt J, Bolla M, Briers E, Cumberbatch MG, De Santis M, et al. EAU-ESTRO-SIOG guidelines on prostate cancer. Part 1: screening, diagnosis, and local treatment with curative intent. Eur Urol 2017;71:618–629.
    1. Cooperberg MR, Park S, Carroll PR. Prostate cancer 2004: insights from national disease registries. Oncology (Williston Park) 2004;18:1239–1247.
      discussion 1248-50, 1256-8.
    1. Lubeck DP, Litwin MS, Henning JM, Stier DM, Mazonson P, Fisk R, et al. The CaPSURE database: a methodology for clinical practice and research in prostate cancer. CaPSURE Research Panel. Cancer of the Prostate Strategic Urologic Research Endeavor. Urology 1996;48:773–777.
    1. Nohr EA, Liew Z. How to investigate and adjust for selection bias in cohort studies. Acta Obstet Gynecol Scand 2018;97:407–416.
    1. Törner A, Dickman P, Duberg AS, Kristinsson S, Landgren O, Björkholm M, et al. A method to visualize and adjust for selection bias in prevalent cohort studies. Am J Epidemiol 2011;174:969–976.
    1. Barocas DA, Alvarez J, Resnick MJ, Koyama T, Hoffman KE, Tyson MD, et al. Association between radiation therapy, surgery, or observation for localized prostate cancer and patient-reported outcomes after 3 years. JAMA 2017;317:1126–1140.
    1. Thorsteinsdottir T, Stranne J, Carlsson S, Anderberg B, Björholt I, Damber JE, et al. LAPPRO: a prospective multicentre comparative study of robot-assisted laparoscopic and retropubic radical prostatectomy for prostate cancer. Scand J Urol Nephrol 2011;45:102–112.
    1. Wijburg CJ, Michels CTJ, Oddens JR, Grutters JPC, Witjes JA, Rovers MM. Robot assisted radical cystectomy versus open radical cystectomy in bladder cancer (RACE): study protocol of a non-randomized comparative effectiveness study. BMC Cancer 2018;18:861

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