Developing a Diagnostic Multivariable Prediction Model for Urinary Tract Cancer in Patients Referred with Haematuria: Results from the IDENTIFY Collaborative Study

Khadhouri, Sinan, Gallagher, Kevin M., MacKenzie, Kenneth R., Shah, Taimur T., Gao, Chuanyu, Moore, Sacha, Zimmermann, Eleanor F., Edison, Eric, Jefferies, Matthew, Nambiar, Arjun, Anbarasan, Thineskrishna, Mannas, Miles P., Lee, Taeweon, Marra, Giancarlo, Gómez Rivas, Juan, Marcq, Gautier, Assmus, Mark A., Uçar, Taha, Claps, Francesco, Boltri, Matteo, La Montagna, Giuseppe, Burnhope, Tara, Nkwam, Nkwam, Austin, Tomas, Boxall, Nicholas E., Downey, Alison P., Sukhu, Troy A., Antón-Juanilla, Marta, Rai, Sonpreet, Chin, Yew-Fung, Moore, Madeline, Drake, Tamsin, Green, James S.A., Goulao, Beatriz, MacLennan, Graeme, Nielsen, Matthew, McGrath, John S., Kasivisvanathan, Veeru, Chaudry, Aasem, Sharma, Abhishek, Bennett, Adam, Ahmad, Adnan, Abroaf, Ahmed, Suliman, Ahmed Musa, Lloyd, Aimee, McKay, Alastair, Wong, Albert, Silva, Alberto, Schneider, Alexandre, MacKay, Alison, Knight, Allen, Grigorakis, Alkiviadis, Bdesha, Amar, Nagle, Amy, Cebola, Ana, Dhanasekaran, Ananda Kumar, Kond?a, Andra?, Barcelos, André, Galosi, Andrea Benedetto, Ebur, Andrea, Minervini, Andrea, Russell, Andrew, Webb, Andrew, de Jalón, Ángel García, Desai, Ankit, Czech, Anna Katarzyna, Mainwaring, Anna, Adimonye, Anthony, Das, Arighno, Figueiredo, Arnaldo, Villers, Arnauld, Leminski, Artur, Chippagiri, Arvinda, Lal, Asim Ahmed, Y?ld?r?m, As?f, Voulgaris, Athanasios Marios, Uzan, Audrey, Oo, Aye Moh Moh, Younis, Ayman, Zelhof, Bachar, Mukhtar, Bashir, Ayres, Ben, Challacombe, Ben, Sherwood, Benedict, Ristau, Benjamin, Lai, Billy, Nellensteijn, Brechtje, Schreiter, Brielle, Trombetta, Carlo, Dowling, Catherine, Hobbs, Catherine, Benitez, Cayo Augusto Estigarribia, Lebacle, Cédric, Ho, Cherrie Wing Yin, Ng, Chi-Fai, Mount, Chloe, Lam, Chon Meng, Blick, Chris, Brown, Christian, Gallegos, Christopher, Higgs, Claire, Browne, Clíodhna, McCann, Conor, Plaza Alonso, Cristina, Beder, Daniel, Cohen, Daniel, Gordon, Daniel, Wilby, Daniel, Gordon, Danny, Hrouda, David, Lau, David Hua Wu, Karsza, Dávid, Mak, David, Martin-Way, David, Suthaharan, Denula, Patel, Dhruv, Carrion, Diego M, Nyanhongo, Donald, Bass, Edward, Mains, Edward, Chau, Edwin, Canelon Castillo, Elba, Day, Elizabeth, Desouky, Elsayed, Gaines, Emily, Papworth, Emma, Yuruk, Emrah, Kilic, Enes, Dinneen, Eoin, Palagonia, Erika, Xylinas, Evanguelos, Khawaja, Faizan, Cimarra, Fernando, Bardet, Florian, Kum, Francesca, Peters, Francesca, Kovács, Gábor, Tanasescu, Geroge, Hellawell, Giles, Tasso, Giovanni, Lam, Gitte, La Montagna, Giuseppe, Pizzuto, Giuseppe, Lenart, Gordan, MacLennan, Graeme, Özgür, Günal, Bi, Hai, Lyons, Hannah, Warren, Hannah, Ahmed, Hashim, Simpson, Helen, Burden, Helena, Gresty, Helena, Rios Pita, Hernado, Clarke, Holly, Serag, Hosam, Kynaston, Howard, Crawford-Smith, Hugh, Mostafid, Hugh, Otaola-Arca, Hugo, Koo, Hui Fen, Ibrahim, Ibrahim, Ouzaid, Idir, Puche-Sanz, Ignacio, Toma?kovi?, Igor, Tinay, Ilker, Sahibzada, Iqbal, Thangasamy, Isaac, Cadena, Iván Revelo, Irani, Jacques, Udzik, Jakub, Brittain, James, Catto, James, Green, James, Tweedle, James, Hernando, Jamie Borrego, Leask, Jamie, Kalsi, Jas, Frankel, Jason, Toniolo, Jason, Raman, Jay D., Courcier, Jean, Kumaradeevan, Jeevan, Clark, Jennifer, Jones, Jennifer, Teoh, Jeremy Yuen-Chun, Iacovou, John, Kelly, John, Selph, John P., Aning, Jonathan, Deeks, Jon, Cobley, Jonathan, Olivier, Jonathan, Maw, Jonny, Herranz-Yagüe, José Antonio, Nolazco, Jose Ignacio, Cózar-Olmo, Jose Manuel, Bagley, Joseph, Jelski, Joseph, Norris, Joseph, Testa, Joseph, Meeks, Joshua, Hernandez, Juan, Vásquez, Juan Luis, Randhawa, Karen, Dhera, Karishma, Gronostaj, Katarzyna, Houlton, Kathleen, Lehman, Kathleen, Gillams, Kathryn, Adasonla, Kelvin, Brown, Kevin, Murtagh, Kevin, Mistry, Kiki, Davenport, Kim, Kitamura, Kosuke, Derbyshire, Laura, Clarke, Laurence, Morton, Lawrie, Martinez, Levin, Goldsmith, Louise, Paramore, Louise, Cormier, Luc, Dell'Atti, Lucio, Simmons, Lucy, Martinez-Piñeiro, Luis, Rico, Luis, Chan, Luke, Forster, Luke, Ma, Lulin, Moore, Madeline, Gallego, Maria Camacho, Freire, Maria José, Emberton, Mark, Feneley, Mark, Antón-Juanilla, Marta, Rivero, Marta Viridiana Muñoz, Pir?a, Matea, Tallè, Matteo, Crockett, Matthew, Liew, Matthew, Trail, Matthew, Peters, Max, Cooper, Meghan, Kulkarni, Meghana, Ager, Michael, He, Ming, Li, Mo, Omran Breish, Mohamed, Tarin, Mohamed, Aldiwani, Mohammed, Matanhelia, Mudit, Pasha, Muhammad, Akal?n, Mustafa Kaan, Abdullah, Nasreen, Hale, Nathan, Gadiyar, Neha, Kocher, Neil, Bullock, Nicholas, Campain, Nicholas, Pavan, Nicola, Al-Ibraheem, Nihad, Bhatt, Nikita, Bedi, Nishant, Shrotri, Nitin, Lobo, Niyati, Balderas, Olga, Kouli, Omar, Capoun, Otakar, Oteo Manjavacas, Pablo, Gontero, Paolo, Mariappan, Paramananthan, Marchiñena, Patricio Garcia, Erotocritou, Paul, Sweeney, Paul, Planelles, Paula, Acher, Peter, Black, Peter C., Osei-Bonsu, Peter K, Østergren, Peter, Smith, Peter, Willemse, Peter-Paul Michiel, Chlosta, Piotr L., Ul Ain, Qurrat, Barratt, Rachel, Esler, Rachel, Khalid, Raihan, Hsu, Ray, Stamirowski, Remigiusz, Mangat, Reshma, Cruz, Ricardo, Ellis, Ricky, Adams, Robert, Hessell, Robert, Oomen, Robert J.A., McConkey, Robert, Ritchie, Robert, Jarimba, Roberto, Chahal, Rohit, Andres, Rosado Mario, Hawkins, Rosalyn, David, Rotimi, Manecksha, Rustom P., Agrawal, Sachin, Hamid, Syed Sami, Deem, Samuel, Goonewardene, Sanchia, Swami, Satchi Kuchibhotla, Hori, Satoshi, Khan, Shahid, Mohammud Inder, Shakeel, Sangaralingam, Shanthi, Marathe, Shekhar, Raveenthiran, Sheliyan, Horie, Shigeo, Sengupta, Shomik, Parson, Sian, Parker, Sidney, Hawlina, Simon, Williams, Simon, Mazzoli, Simone, Grzegorz Kata, Slawomir, Pinheiro Lopes, Sofia, Ramos, Sónia, Rai, Sonpreet, Rintoul-Hoad, Sophie, O'Meara, Sorcha, Morris, Steve, Turner, Stacey, Venturini, Stefano, Almpanis, Stephanos, Joniau, Steven, Jain, Sunjay, Mallett, Susan, Nikles, Sven, Shahzad, Yan, Sylvia, Lee, Taeweon, Uçar, Taha, Drake, Tamsin, Toma, Tarq, Cabañuz Plo, Teresa, Bonnin, Thierry, Muilwijk, Tim, Wollin, Tim, Chu, Timothy Shun Man, Appanna, Timson, Brophy, Tom, Ellul, Tom, Austin, Tomas, Smrkolj, Toma?, Rowe, Tracey, Sukhu, Troy, Patel, Trushar, Garg, Tullika, Ça?kurlu, Turhan, Bele, Uros, Haroon, Usman, Crespo-Atín, Víctor, Parejo Cortes, Victor, Capapé Poves, Victoria, Gnanapragasam, Vincent, Gauhar, Vineet, During, Vinnie, Kumar, Vivek, Fiala, Vojtech, Mahmalji, Wasim, Lam, Wayne, Fung Chin, Yew, Filtekin, Yigit, Chyn Phan, Yih, Ibrahim, Youssed, Glaser, Zachary A, Abiddin, Zainal Adwin, Qin, Zijian, Zotter, Zsuzsanna and Zainuddin, Zulkifli 2022. Developing a Diagnostic Multivariable Prediction Model for Urinary Tract Cancer in Patients Referred with Haematuria: Results from the IDENTIFY Collaborative Study. European Urology Focus 8 (6) , pp. 1673-1682. 10.1016/j.euf.2022.06.001

PDF - Published Version Available under License Creative Commons Attribution. Download (326kB)

Abstract

Background Patient factors associated with urinary tract cancer can be used to risk stratify patients referred with haematuria, prioritising those with a higher risk of cancer for prompt investigation. Objective To develop a prediction model for urinary tract cancer in patients referred with haematuria. Design, setting, and participants A prospective observational study was conducted in 10 282 patients from 110 hospitals across 26 countries, aged ≥16 yr and referred to secondary care with haematuria. Patients with a known or previous urological malignancy were excluded. Outcome measurements and statistical analysis The primary outcomes were the presence or absence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC], and renal cancer). Mixed-effect multivariable logistic regression was performed with site and country as random effects and clinically important patient-level candidate predictors, chosen a priori, as fixed effects. Predictors were selected primarily using clinical reasoning, in addition to backward stepwise selection. Calibration and discrimination were calculated, and bootstrap validation was performed to calculate optimism. Results and limitations The unadjusted prevalence was 17.2% (n = 1763) for bladder cancer, 1.20% (n = 123) for UTUC, and 1.00% (n = 103) for renal cancer. The final model included predictors of increased risk (visible haematuria, age, smoking history, male sex, and family history) and reduced risk (previous haematuria investigations, urinary tract infection, dysuria/suprapubic pain, anticoagulation, catheter use, and previous pelvic radiotherapy). The area under the receiver operating characteristic curve of the final model was 0.86 (95% confidence interval 0.85–0.87). The model is limited to patients without previous urological malignancy. Conclusions This cancer prediction model is the first to consider established and novel urinary tract cancer diagnostic markers. It can be used in secondary care for risk stratifying patients and aid the clinician’s decision-making process in prioritising patients for investigation. Patient summary We have developed a tool that uses a person’s characteristics to determine the risk of cancer if that person develops blood in the urine (haematuria). This can be used to help prioritise patients for further investigation.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Medicine
Publisher:	Elsevier
ISSN:	2405-4569
Date of First Compliant Deposit:	5 April 2023
Date of Acceptance:	4 June 2022
Last Modified:	07 May 2023 18:22
URI:	https://orca.cardiff.ac.uk/id/eprint/158389

Citation Data

Cited 13 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item