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101. Epigenome-based cancer risk prediction: Rationale, opportunities and challenges

Author

Widschwendter, M, Jones, A, Evans, I, Reisel, D, Dillner, J, Sundström, K, Steyerberg, E, Vergouwe, Y, Wegwarth, O, Rebitschek, F, Siebert, U, Sroczynski, G, De Beaufort, I, Bolt, I, Cibula, D, Zikan, M, Bjørge, L, Colombo, N, Harbeck, N, Dudbridge, F, Tasse, A, Knoppers, B, Joly, Y, Teschendorff, A, Pashayan, N, Widschwendter, Martin, Jones, Allison, Evans, Iona, Reisel, Daniel, Dillner, Joakim, Sundström, Karin, Steyerberg, Ewout W., Vergouwe, Yvonne, Wegwarth, Odette, Rebitschek, Felix G., Siebert, Uwe, Sroczynski, Gaby, De Beaufort, Inez D., Bolt, Ineke, Cibula, David, Zikan, Michal, Bjørge, Line, Colombo, Nicoletta, Harbeck, Nadia, Dudbridge, Frank, Tasse, Anne-Marie, Knoppers, Bartha M., Joly, Yann, Teschendorff, Andrew E., Pashayan, Nora, Widschwendter, M, Jones, A, Evans, I, Reisel, D, Dillner, J, Sundström, K, Steyerberg, E, Vergouwe, Y, Wegwarth, O, Rebitschek, F, Siebert, U, Sroczynski, G, De Beaufort, I, Bolt, I, Cibula, D, Zikan, M, Bjørge, L, Colombo, N, Harbeck, N, Dudbridge, F, Tasse, A, Knoppers, B, Joly, Y, Teschendorff, A, Pashayan, N, Widschwendter, Martin, Jones, Allison, Evans, Iona, Reisel, Daniel, Dillner, Joakim, Sundström, Karin, Steyerberg, Ewout W., Vergouwe, Yvonne, Wegwarth, Odette, Rebitschek, Felix G., Siebert, Uwe, Sroczynski, Gaby, De Beaufort, Inez D., Bolt, Ineke, Cibula, David, Zikan, Michal, Bjørge, Line, Colombo, Nicoletta, Harbeck, Nadia, Dudbridge, Frank, Tasse, Anne-Marie, Knoppers, Bartha M., Joly, Yann, Teschendorff, Andrew E., and Pashayan, Nora

Abstract

The incidence of cancer is continuing to rise and risk-tailored early diagnostic and/or primary prevention strategies are urgently required. The ideal risk-predictive test should: integrate the effects of both genetic and nongenetic factors and aim to capture these effects using an approach that is both biologically stable and technically reproducible; derive a score from easily accessible biological samples that acts as a surrogate for the organ in question; and enable the effectiveness of risk-reducing measures to be monitored. Substantial evidence has accumulated suggesting that the epigenome and, in particular, DNA methylation-based tests meet all of these requirements. However, the development and implementation of DNA methylation-based risk-prediction tests poses considerable challenges. In particular, the cell type specificity of DNA methylation and the extensive cellular heterogeneity of the easily accessible surrogate cells that might contain information relevant to less accessible tissues necessitates the use of novel methods in order to account for these confounding issues. Furthermore, the engagement of the scientific community with health-care professionals, policymakers and the public is required in order to identify and address the organizational, ethical, legal, social and economic challenges associated with the routine use of epigenetic testing.

Published
2018

106. Preconception risk of gestational diabetes: Development of a prediction model in nulliparous Australian women

Author

Schoenaker, Danielle A. J. M, Vergouwe, Yvonne, Soedamah-Muthu, Sabita S, Callaway, Leonie, Mishra, Gita D, Schoenaker, Danielle A. J. M, Vergouwe, Yvonne, Soedamah-Muthu, Sabita S, Callaway, Leonie, and Mishra, Gita D

Abstract

Aim: To develop a prediction model for preconception identification of women at risk of gestational diabetes mellitus (GDM). Methods: Data from a prospective cohort, the Australian Longitudinal Study on Women's Health, were used. Nulliparous women aged 18-23 who reported a pregnancy up to age 37-42 were included. Preconception predictors of GDM during a first pregnancy were selected using logistic regression. Regression coefficients were multiplied by a shrinkage factor estimated with bootstrapping to improve prediction in external populations. Results: Among 6504 women, 314 (4.8%) developed GDM during their first pregnancy. The final prediction model included age at menarche, proposed age at future first pregnancy, ethnicity, body mass index, diet, physical activity, polycystic ovary syndrome, and family histories of type 1 or 2 diabetes and GDM. The model showed good discriminative ability with a C-statistic of 0.79 (95% CI 0.76, 0.83) after internal validation. More than half of the women (58%) were classified to be at risk of GDM (>2% predicted risk), with corresponding sensitivity and specificity values of 91% and 43%. Conclusions: Nulliparous women at risk of GDM in a future first pregnancy can be accurately identified based on preconception lifestyle and health-related characteristics. Further studies are needed to test our model in other populations.

Published
2018

107. Methods for Evaluating Medical Tests and Biomarkers

Author

Gopalakrishna, Gowri, Langendam, Miranda, Scholten, Rob, Bossuyt, Patrick, Leeflang, Mariska, Noel-Storr, Anna, Thomas, James, Marshall, Iain, Wallace, Byron, Whiting, Penny, Davenport, Clare, GopalaKrishna, Gowri, de Salis, Isabel, Mallett, Sue, Wolff, Robert, Riley, Richard, Westwood, Marie, Kleinen, Jos, Collins, Gary, Reitsma, Hans, Moons, Karel, Zapf, Antonia, Hoyer, Annika, Kramer, Katharina, Kuss, Oliver, Ensor, J., Deeks, J. J., Martin, E. C., Riley, R. D., Rücker, Gerta, Steinhauser, Susanne, Schumacher, Martin, Ensor, Joie, Snell, Kym, Willis, Brian, Debray, Thomas, Deeks, Jon, di Ruffano, Lavinia Ferrante, Taylor-Phillips, Sian, Hyde, Chris, Taylor, Stuart A., Batnagar, Gauraang, Di Ruffano, Lavinia Ferrante, Seedat, Farah, Clarke, Aileen, Byron, Sarah, Nixon, Frances, Albrow, Rebecca, Walker, Thomas, Deakin, Carla, Zhelev, Zhivko, Hunt, Harriet, Yang, Yaling, Abel, Lucy, Buchanan, James, Fanshawe, Thomas, Shinkins, Bethany, Wynants, Laure, Verbakel, Jan, Van Huffel, Sabine, Timmerman, Dirk, Van Calster, Ben, Zwinderman, Aeliko, Oke, Jason, O’Sullivan, Jack, Perera, Rafael, Nicholson, Brian, Bromley, Hannah L., Roberts, Tracy E., Francis, Adele, Petrie, Denniis, Mann, G. Bruce, Malottki, Kinga, Smith, Holly, Billingham, Lucinda, Sitch, Alice, Gerke, Oke, Holm-Vilstrup, Mie, Segtnan, Eivind Antonsen, Halekoh, Ulrich, Høilund-Carlsen, Poul Flemming, Francq, Bernard G., Dinnes, Jac, Parkes, Julie, Gregory, Walter, Hewison, Jenny, Altman, Doug, Rosenberg, William, Selby, Peter, Asselineau, Julien, Perez, Paul, Paye, Aïssatou, Bessede, Emilie, Proust-Lima, Cécile, Naaktgeboren, Christiana, de Groot, Joris, Rutjes, Anne, Reitsma, Johannes, Ogundimu, Emmanuel, Cook, Jonathan, Le Manach, Yannick, Vergouwe, Yvonne, Pajouheshnia, Romin, Groenwold, Rolf, Moons, Karen, Peelen, Linda, Nieboer, Daan, De Cock, Bavo, Pencina, Micael J., Steyerberg, Ewout W., Cooper, Jennifer, Parsons, Nick, Stinton, Chris, Smith, Steve, Dickens, Andy, Jordan, Rachel, Enocson, Alexandra, Fitzmaurice, David, Adab, Peymane, Boachie, Charles, Vidmar, Gaj, Freeman, Karoline, Connock, Martin, Court, Rachel, Moons, Carl, Harris, Jessica, Mumford, Andrew, Plummer, Zoe, Lee, Kurtis, Reeves, Barnaby, Rogers, Chris, Verheyden, Veerle, Angelini, Gianni D., Murphy, Gavin J., Huddy, Jeremy, Ni, Melody, Good, Katherine, Cooke, Graham, Hanna, George, Ma, Jie, Moons, K. G. M. (Carl), de Groot, Joris A. H., Altman, Doug G., Reitsma, Johannes B., Collins, Gary S., Moons, Karel G. M., Altman, Douglas G., Kamarudin, Adina Najwa, Kolamunnage-Dona, Ruwanthi, Cox, Trevor, Borsci, Simone, Pérez, Teresa, Pardo, M.Carmen, Candela-Toha, Angel, Muriel, Alfonso, Zamora, Javier, Sanghera, Sabina, Mohiuddin, Syed, Martin, Richard, Donovan, Jenny, Coast, Joanna, Seo, Mikyung Kelly, Cairns, John, Mitchell, Elizabeth, Smith, Alison, Wright, Judy, Hall, Peter, Messenger, Michael, Calder, Nicola, Wickramasekera, Nyantara, Vinall-Collier, Karen, Lewington, Andrew, Damen, Johanna, Cairns, David, Hutchinson, Michelle, Sturgeon, Cathie, Mitchel, Liz, Kift, Rebecca, Christakoudi, Sofia, Rungall, Manohursingh, Mobillo, Paula, Montero, Rosa, Tsui, Tjir-Li, Kon, Sui Phin, Tucker, Beatriz, Sacks, Steven, Farmer, Chris, Strom, Terry, Chowdhury, Paramit, Rebollo-Mesa, Irene, Hernandez-Fuentes, Maria, Damen, Johanna A. A. G., Debray, Thomas P. A., Heus, Pauline, Hooft, Lotty, Scholten, Rob J. P. M., Schuit, Ewoud, Tzoulaki, Ioanna, Lassale, Camille M., Siontis, George C. M., Chiocchia, Virginia, Roberts, Corran, Schlüssel, Michael Maia, Gerry, Stephen, Black, James A., van der Schouw, Yvonne T., Peelen, Linda M., Spence, Graeme, McCartney, David, van den Bruel, Ann, Lasserson, Daniel, Hayward, Gail, Vach, Werner, de Jong, Antoinette, Burggraaff, Coreline, Hoekstra, Otto, Zijlstra, Josée, de Vet, Henrica, Graziadio, Sara, Allen, Joy, Johnston, Louise, O’Leary, Rachel, Power, Michael, Johnson, Louise, Waters, Ray, Simpson, John, Fanshawe, Thomas R., Phillips, Peter, Plumb, Andrew, Helbren, Emma, Halligan, Steve, Gale, Alastair, Sekula, Peggy, Sauerbrei, Willi, Forman, Julia R., Dutton, Susan J., Takwoingi, Yemisi, Hensor, Elizabeth M., Nichols, Thomas E., Kempf, Emmanuelle, Porcher, Raphael, de Beyer, Jennifer, Altman, Douglas, Hopewell, Sally, Dennis, John, Shields, Beverley, Jones, Angus, Henley, William, Pearson, Ewan, Hattersley, Andrew, Scheibler, Fueloep, Rummer, Anne, Sturtz, Sibylle, Großelfinger, Robert, Banister, Katie, Ramsay, Craig, Azuara-Blanco, Augusto, Burr, Jennifer, Kumarasamy, Manjula, Bourne, Rupert, Uchegbu, Ijeoma, Murphy, Jennifer, Carter, Alex, Murphy, Jen, Marti, Joachim, Eatock, Julie, Robotham, Julie, Dudareva, Maria, Gilchrist, Mark, Holmes, Alison, Monaghan, Phillip, Lord, Sarah, StJohn, Andrew, Sandberg, Sverre, Cobbaert, Christa, Lennartz, Lieselotte, Verhagen-Kamerbeek, Wilma, Ebert, Christoph, Horvath, Andrea, Jenniskens, Kevin, Peters, Jaime, Grigore, Bogdan, Ukoumunne, Obi, Levis, Brooke, Benedetti, Andrea, Levis, Alexander W., Ioannidis, John P. A., Shrier, Ian, Cuijpers, Pim, Gilbody, Simon, Kloda, Lorie A., McMillan, Dean, Patten, Scott B, Steele, Russell J., Ziegelstein, Roy C, Bombardier, Charles H., Osório, Flavia de Lima, Fann, Jesse R., Gjerdingen, Dwenda, Lamers, Femke, Lotrakul, Manote, Loureiro, Sonia R, Löwe, Bernd, Shaaban, Juwita, Stafford, Lesley, van Weert, Henk C. P. M., Whooley, Mary A., Williams, Linda S., Wittkampf, Karin A., Yeung, Albert S., Thombs, Brett D., Cooper, Chris, Nieto, Tom, Smith, Claire, Tucker, Olga, Dretzke, Janine, Beggs, Andrew, Rai, Nirmala, Bayliss, Sue, Stevens, Simon, Mallet, Sue, Sundar, Sudha, Hall, Emma, Porta, Nuria, Estelles, David Lorente, and de Bono, Johann

Subjects
Faecal Immunochemical Test, Chronic Obstructive Pulmonary Disorder, Circulate Tumour Cell Count, Apply Health Research, Meeting Abstracts, Faecal Immunochemical Test Result
Abstract

unKnown

Published
2017

108. A new concordance measure for risk prediction models in external validation settings

Author

van Klaveren, David, Gonen, M, Steyerberg, Ewout, Vergouwe, Yvonne, and Public Health

Subjects
Logistic Models, Models, Statistical, Humans, Article, Diagnosis-Related Groups
Abstract

Concordance measures are frequently used for assessing the discriminative ability of risk prediction models. The interpretation of estimated concordance at external validation is difficult if the case-mix differs from the model development setting. We aimed to develop a concordance measure that provides insight into the influence of case-mix heterogeneity and is robust to censoring of time-to-event data. We first derived a model-based concordance (mbc) measure that allows for quantification of the influence of case-mix heterogeneity on discriminative ability of proportional hazards and logistic regression models. This mbc can also be calculated including a regression slope that calibrates the predictions at external validation (c-mbc), hence assessing the influence of overall regression coefficient validity on discriminative ability. We derived variance formulas for both mbc and c-mbc. We compared the mbc and the c-mbc with commonly used concordance measures in a simulation study and in two external validation settings. The mbc was asymptotically equivalent to a previously proposed resampling-based case-mix corrected c-index. The c-mbc remained stable at the true value with increasing proportions of censoring, while Harrell's c-index and to a lesser extent Uno's concordance measure increased unfavorably. Variance estimates of mbc and c-mbc were well in agreement with the simulated empirical variances. We conclude that the mbc is an attractive closed-form measure that allows for a straightforward quantification of the expected change in a model's discriminative ability due to case-mix heterogeneity. The c-mbc also reflects regression coefficient validity and is a censoring-robust alternative for the c-index when the proportional hazards assumption holds. Copyright © 2016 John WileySons, Ltd.

Published
2016

111. Prediction of cashew nut allergy in sensitized children

Author

van der Valk, Johanna P.M., primary, Vergouwe, Yvonne, additional, Gerth van Wijk, Roy, additional, Steyerberg, Ewout W., additional, Reitsma, Marit, additional, Wichers, Harry J., additional, Savelkoul, Huub F.J., additional, Vlieg-Boerstra, Berber, additional, de Groot, Hans, additional, Dubois, Anthony E.J., additional, and de Jong, Nicolette W., additional

Published
2017
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113. Abstracts from the Food Allergy and Anaphylaxis Meeting 2016

Author

Pouessel, Guillaume, Claverie, Claire, Labreuche, Julien, Renaudin, Jean‐Marie, Dorkenoo, Aimée, Eb, Mireille, Moneret‐Vautrin, Anne, Deschildre, Antoine, Leteurtre, Stephane, Grabenhenrich, Linus, Worm, Margitta, Dölle, Sabine, Scherer, Kathrin, Hutteger, Isidor, Christensen, Morten, Bindslev‐Jensen, Carsten, Mortz, Charlotte, Eller, Esben, Kjaer, Henrik Fomsgaard, Carneiro‐Leão, Leonor, Badas, Jenny, Coimbra, Alice, Levy, Dikla Pivko, Ben‐Shoshan, Moshe, Rimon, Ayelet, Benor, Shira, Arends, Nicolette JT, Edelbroek, Nikki, de Groot, Hans, Emons, Joyce AM, Brand, H Kim A, Verhoeven, Dirk, van Veen, Leonieke N, de Jong, Nicolette W, Noh, Geunwoong, Jang, Eun Ha, Pascal, Mariona, Dominguez, Olga, Piquer, Mònica, Alvaro, Montserrat, Jimenez‐Feijoo, Rosa, Lozano, Jaime, Machinena, Adriana, del Mar Folqué, Maria, Giner, Maria Teresa, Plaza, Ana María, Turner, Paul, Patel, Nandinee, Vazquez‐Ortiz, Marta, Lindsley, Sarah, Walker, Lucy, Rosenberg, Simon, Mari, Adriano, Alessandri, Claudia, Giangrieco, Ivana, Tuppo, Lisa, Rafaiani, Chiara, Mitterer, Georg, Ciancamerla, Michela, Ferrara, Rosetta, Bernardi, Maria Livia, Zennaro, Danila, Tamburrini, Maurizio, Ciardiello, Maria Antonetta, Harwanegg, Christian, Fernandez, Antonio, Selb, Regina, Egenmann, Philippe, Epstein, Michelle, Hoffmann‐Sommergruber, Karin, Koning, Frits, Lovik, Martinus, Mills, EN Clare, Moreno, Javier, van Loveren, Henk, Wal, Jean‐Michel, Diesner, Susanne, Bergmayr, Cornelia, Pfitzner, Barbara, Assmann, Vera Elisabeth, Starkl, Philipp, Endesfelder, David, Eiwegger, Thomas, Szepfalusi, Zsolt, Fehrenbach, Heinz, Jensen‐Jarolim, Erika, Hartmann, Anton, Pali‐Schöll, Isabella, Untersmayr, Eva, Wille, Soren, Meyer, Peter, Klingebiel, Caroline, Lidholm, Jonas, Ehrenberg, Angelica, Östling, Jonas, Cleach, Isabelle, Mège, Jean‐Louis, Vitte, Joana, Aina, Roberta, Dubiela, Pawel, Pfeifer, Sabine, Bublin, Merima, Radauer, Christian, Humeniuk, Piotr, Kabasser, Stefan, Asero, Riccardo, Bogas, Gador, Gomez, Francisca, Campo, Paloma, Salas, Maria, Doña, Inmaculada, Barrionuevo, Esther, Guerrero, Maria Auxiliadora, Mayorga, Cristobalina, Prieto, Ana, Barber, Domingo, Torres, Maria Jose, Jamin, Annette, Wangorsch, Andrea, Ballmer, Barbara, Vieths, Stefan, Scheurer, Stephan, Apostolovic, Danijela, Mihailovic, Jelena, Krstic, Maja, Starkhammar, Maria, Velickovic, Tanja Cirkovic, Hamsten, Carl, van Hage, Marianne, van Erp, Francine C, Knol, Edward F, Kansen, Hannah M, Pontoppidan, Bo, Meijer, Yolanda, van der Ent, Cornelis K, Knulst, André C, Sayers, Rebekah, Brown, Helen, Custovic, Adnan, Simpson, Angela, Mills, Claire, Schulz, Juliane, Registration of Anaphylaxis, Network for Online, Akkerdaas, Jaap, Totis, Muriel, Capt, Annabelle, Herouet‐Guicheney, Corinne, van Ree, Ronald, Banerjee, Tushar, Banerjee, Antima, Claude, Mathilde, Bouchaud, Grégory, Lupi, Roberta, Castan, Laure, Tranquet, Olivier, Denery‐Papini, Sandra, Bodinier, Marie, Brossard, Chantal, De Poi, Rosella, Gritti, Elisa, De Dominicis, Emiliano, Popping, Bert, de Laureto, Patrizia Polverino, Palosuo, Kati, Kukkonen, Anna Kaarina, Pelkonen, Anna, Mäkelä, Mika, Lee, Nanju Alice, Rost, Johanna, Muralidharan, Sridevi, Campbell, Dianne, Mehr, Sam, Nock, Catherine, Baumert, Joseph, Taylor, Steve, Mastrorilli, Carla, Tripodi, Salvatore, Caffarelli, Carlo, Perna, Serena, Di Rienzo Businco, Andrea, Sfika, Ifigenia, Dondi, Arianna, Bianchi, Annamaria, Dascola, Carlotta Povesi, Ricci, Giampaolo, Cipriani, Francesca, Maiello, Nunzia, del Giudice, Michele Miraglia, Frediani, Tullio, Frediani, Simone, Macrì, Francesco, Pistoletti, Chiara, Dello Iacono, Iride, Patria, Maria Francesca, Varin, Elena, Peroni, Diego, Comberiati, Pasquale, Chini, Loredana, Moschese, Viviana, Lucarelli, Sandra, Bernardini, Roberto, Pingitore, Giuseppe, Pelosi, Umberto, Olcese, Roberta, Moretti, Matteo, Cirisano, Anastasia, Faggian, Diego, Travaglini, Alessandro, Plebani, Mario, Verga, Maria Carmen, Calvani, Mauro, Giordani, Paolo, Matricardi, Paolo Maria, Ontiveros, Noe, Cabrera‐Chavez, Francisco, Galand, Julie, Beaudouin, Etienne, Society, The Anaphylaxis Working Group of the French Allergology SocietyThe Anaphylaxis Working Group of the French Allergology, Pineau, Florence, Sakai, Shinobu, Matsunaga, Kayoko, Teshima, Reiko, Larré, Colette, Denery, Sandra, Tschirner, Sebastian, Trendelenburg, Valérie, Schulz, Gabriele, Niggemann, Bodo, Beyer, Kirsten, Bouferkas, Youcef, Belabbas, Younes, Saidi, Djamel, Kheroua, Omar, Mecherfi, Kamel Eddine El, Guendouz, Malika, Haddi, Abir, Kaddouri, Hanane, Amaral, Luis, Pereira, Ana, Rodrigues, Susana, Datema, Mareen, Jongejan, Laurian, Clausen, Michael, Knulst, Andre, Papadopoulos, Nikolaos, Kowalski, Marek, de Blay, Frédéric, Zwinderman, Aeilko, Hoffman‐Sommergruber, Karin, Ballmer‐Weber, Barbara, Fernandez‐Rivas, Montserrat, Deng, Shan, Yin, Jia, Eisenmann, Charlotte, Nassiri, Maria, Reinert, Rabea, van der Valk, Johanna PM, van Wijk, Roy Gerth, Vergouwe, Yvonne, Steyerberg, Ewout W, Reitsma, Marit, Wichers, Harry J, Savelkoul, Huub FJ, Vlieg‐Boerstra, Berber, Dubois, Anthony EJ, Carolino, Fabrícia, Rodolfo, Ana, Cernadas, Josefina, Roa‐Medellín, Dasha, Rodriguez‐Fernandez, Ana, Navarro, Joaquín, Albendiz, Vicente, Baeza, María Luisa, Intente‐Herrero, Sonsoles, Mikkelsen, Andrea, Mehlig, Kirsten, Lissner, Lauren, Verrill, Linda, Luccioli, Stefano, van Bilsen, Jolanda, Kuper, Frieke, Wolterbeek, André, Rankouhi, Tanja Rouhani, Verschuren, Lars, Cnossen, Hilde, Jeurink, Prescilla, Garssen, Johan, Knippels, Léon, Garthoff, Jossie, Houben, Geert, Leeman, Winfried, Pettersson, M Eleonore, Schins, Afke MM, Koppelman, Gerard H, Kollen, Boudewjin J, Zubchenko, Svitlana, Kuntz, Sarah, Mérida, Pablo, Álvaro, Montserrat, Piquer, Monica, Riggioni, Carmen, Castellanos, Juan Heber, Jimenez, Rosa, Cap, Melanie, Drumez, Elodie, Lejeune, Stéphanie, Thumerelle, Caroline, Mordacq, Clémence, Nève, Véronique, Ricò, Sonia, Varini, Margherita, Nocerino, Rita, Cosenza, Linda, Amoroso, Antonio, Di Costanzo, Margherita, Di Scala, Carmen, Bedogni, Giorgio, Canani, Roberto Berni, Turner, Paul J, Poza‐Guedes, Paloma, González‐Pérez, Ruperto, Sánchez‐Machín, Inmaculada, Matheu‐Delgado, Victor, Wambre, Erik, Ballegaard, Anne‐Sofie, Madsen, Charlotte, Gregersen, Juliane, Bøgh, Katrine Lindholm, Aubert, Philippe, Neunlist, Michel, Magnan, Antoine, Lozano‐Ojalvo, Daniel, Pablos‐Tanarro, Alba, Pérez‐Rodríguez, Leticia, Molina, Elena, López‐Fandiño, Rosina, Rekima, Akila, Macchiaverni, Patricia, Turfkruyer, Mathilde, Holvoet, Sebastien, Dupuis, Lénaïck, Baiz, Nour, Annesi‐Maesano, Isabella, Mercenier, Annick, Nutten, Sophie, Verhasselt, Valérie, Mrakovcic‐Sutic, Ines, Banac, Srdan, Sutic, Ivana, Baricev‐Novakovic, Zdenka, Sutic, Ingrid, Pavisic, Valentino, Muñoz‐Cano, Rosa, Jiménez‐Rodríguez, Teodoríkez, Corbacho, Daniel, Roca‐Ferrer, Jordi, Bartra, Joan, Bulog, Aleksandar, Micovic, Vladimir, Markiewicz, Lidia, Szymkiewicz, Agata, Szyc, Anna, Wróblewska, Barbara, Harvey, Bryan M, Harthoorn, Lucien F, Burks, A Wesley, Rentzos, Georgios, Björk, Anna‐Lena Bramstång, Bengtsson, Ulf, Barber, Colin, Kalicinsky, Chrystyna, Breynaert, Christine, Coorevits, Lieve, Jansen, Cornelia, Van Hoeyveld, Erna, Verbeke, Kristin, Kochuyt, Anne‐Marie, Schrijvers, Rik, Deleanu, Diana, Muntean, Adriana, Konstantakopoulou, Maria, Pasioti, Maria, Papadopoulou, Anastasia, Iliopoulou, Anna, Mikos, Nikolaos, Kompoti, Evangelia, de Castro, Eunice Dias, Bartalomé, Borja, Ue, Kok Loong, Griffiths, Elizabeth, Till, Stephen, Grimshaw, Kate, Roberts, Graham, Selby, Anna, Butiene, Indre, Larco, Jose Ignacio, Dubakiene, Ruta, Fiandor, Ana, Fiocchi, Alessandro, Papadopoulos, Nikos, Sigurdardottir, Sigurveig, Sprikkelman, Aline, Schoemaker, Anne‐Fleur, Xepapadaki, Paraskevi, Keil, Thomas, Cojocariu, Zizi, Barbado, Beatriz Secades, Iancu, Vasti, Arroabarren, Esozia, Esarte, Marta Goñi, Arteaga, Miren, Andrade, Mayra Coutinho, Borges, Denise, Kalil, Jorge, Bianchi, Pedro Giavina, Agondi, Rosana Camara, Gupta, Rinkesh Kumar, Sharma, Akanksha, Gupta, Kriti, Das, Mukul, Dwivedi, Premendra, Karseladze, Rusudan, Jorjoliani, Liana, Saginadze, Lali, Tskhakaia, Mariam, Basello, Katia, Piuri, Gabriele, Speciani, Attilio Francesco, Speciani, Michela Carola, Camerotto, Carla, Zinno, Francesco, Pakholchuk, Olga, Nedelska, Svitlana, Pattini, Stefano, Costantino, Maria Teresa, Peveri, Silvia, Villalta, Danilo, Savi, Eleonora, Costanzi, Andrea, Revyakina, Vera A, Kiseleva, Marina A, Kuvshinova, Elena D, Larkova, Inna A, Shekhetov, Anton A, Silva, Diana, Moreira, André, Plácido, José, van der Kleij, Hanneke, van Twuijver, Esther, Sutorius, Robbert, de Kam, Pieter‐Jan, van Odijk, Jenny, Lindqvist, Helen, Lustig, Elin, Jácome, Amyra Ali Azamar, Aguilar, Karla Leversia Borjas, Domínguez, Miguel García, Hernández, David Alejandro Mendoza, Caruso, Cristiano, Casale, Cono, Rapaccini, Gian Lodovico, Romano, Antonino, De Vitis, Italo, Cocco, Renata R, Aranda, Carolina, Mallozi, Marcia C, Motta, Jackeline F, Moraes, Lilian, Pastorino, Antonio, Rosario, Nelson, Goudouris, Ekaterini, Porto, Arnaldo, Wandalsen, Neusa F, Sarinho, Emanuel, Sano, Flavio, Solé, Dirceu, Pitsios, Constantinos, Petrodimopoulou, Maria, Papadopoulou, Ekaterini, Passioti, Maria, Kontogianni, Meropi, Adamia, Nino, Khaleva, Ekaterina, del Prado, Ana Prieto, Du Toit, George, Krzych, Edyta, Samolinska‐Zawisza, Urszula, Furmanczyk, Konrad, Tomaszewska, Aneta, Raciborski, Filip, Lipiec, Agnieszka, Samel‐Kowalik, Piotr, Walkiewicz, Artur, Borowicz, Jacek, Samolinski, Boleslaw, Nano, Aimee Lou, Recto, Marysia, Somoza, Maria Luisa, López, Natalia Blanca, Alzate, Diana Pérez, Ruano, Francisco Javier, Garcimartín, Maria Isabel, Haroun, Elisa, de la Torre, Maria Vázquez, Rojas, Antonia, Onieva, Montserrat López, Canto, Gabriela, Rodrigues, Alexandra, Forno, Andreia, Cabral, António Jorge, Gonçalves, Rute, Vorozhko, Ilya, Sentsova, Tatyana, Chernyak, Olga, Denisova, Svetlana, Ilènko, Lidia, Muhortnich, Valery, Zimmermann, Caroline, Rohrbach, Alexander, Bakhsh, Faisal R, Boudewijn, Kollen, Oomkes‐Pilon, Anne‐Marie, Van Ginkle, Dorien, Šilar, Mira, Jeverica, Anja, Vesel, Tina, Avčin, Tadej, Korošec, Peter, van der Valk, Johanna, Berends, Irene, Arends, Nicolette, van Maaren, Maurits, Wichers, Harry, Emons, Joyce, Dubois, Anthony, de Jong, Nicolette, Matsyura, Oksana, Besh, Lesya, Huang, Chung‐Hsiung, Jan, Tong‐Rong, Stiefel, Gary, Tratt, Jean, Kirk, Kerrie, Carolino, Fabricia, Arasi, Stefania, Caminiti, Lucia, Crisafulli, Giuseppe, Fiamingo, Chiara, Fresta, Jlenia, Pajno, Giovanni, Remington, Ben, Kruizinga, Astrid, Blom, W Marty, Westerhout, Joost, Bijlsma, Sabina, Baumert, Joe, Blankestijn, Mark, Otten, Henny, Klemans, Rob, Michelsen‐Huisman, Anouska D, van Os‐Medendorp, Harmieke, Kruizinga, Astrid G, Versluis, Astrid, van Duijn, Gert, de Zeeuw‐Brouwer, H Mary‐Lene, Castenmiller, Jacqueline JM, Noteborn, Hub PJM, Houben, Geert F, Bravin, Kristian, Luyt, David, Javed, Bushra, Couch, Phil, Munro, Christopher, Padfield, Phil, Sperrin, Matt, Byrne, Aideen, Oosthuizen, Lizalet, Kelleher, Carina, Ward, Fiona, Brosnan, Niamh, King, Graham, Corbet, Eva, Guzmán, Josué Alejandro Huertas, García, Montserrat Bosque, Asensio, Oscar, Navarrete, Laura Valdesoiro, Larramona, Helena, Miró, Xavier Domingo, Pyrz, Katarzyna, Austin, Moira, Boloh, Yanne, Couch, Philip, Galloway, Deirdre, Hernandez, Pilar, Hourihane, Jonathan O’B, Kenna, Fiona, Majkowska‐Wojciechowska, Barbara, Regent, Lynne, Themisb, Marina, Schnadt, Sabine, Semic‐Jusufagic, Aida, Galvin, Audrey Dunn, Kauppila, Tiina, Kuitunen, Mikael, Kitsioulis, Nikolaos A, Douladiris, Nikolaos, Kostoudi, Sofia, Manolaraki, Ioanna, Mitsias, Dimitris, Manousakis, Emmanouil, Papadopoulos, Nikolaos G, Knibb, Rebecca, Hammond, Jennifer, Cooke, Richard, Yrjänä, Jaakko, Hanni, Anna‐Maija, Vähäsarja, Päivi, Mustonen, Oona, Dunder, Teija, Kulmala, Petri, Lasa, Eva, D’Amelio, Carmen, Martínez, Sara, Joral, Alejandro, Gastaminza, Gabriel, Goikoetxea, Maria Jose, Candy, David CA, Van Ampting, Marleen TJ, Nijhuis, Manon M Oude, Butt, Assad M, Peroni, Diego G, Fox, Adam T, Knol, Jan, Michaelis, Louise J, Padua, Ines, Padrao, Patricia, Moreira, Pedro, Barros, Renata, Sharif, Hanan, Ahmed, Manzoor, Gomaa, Nehad, Mens, Joris, Smit, Koen, Timmermans, Frans, Poredoš, Tomaž, Jeverica, Anja Koren, Sedmak, Marjeta, Benedik, Evgen, Accetto, Meta, Zupančič, Mirjana, Yonamine, Glauce, Soldateli, Gustavo, Aquilante, Bruna, Pastorino, Antonio Carlos, de Moraes Beck, Cleonir Lui, Gushken, Andrea Keiko, de Barros Dorna, Mayra, dos Santos, Cristiane Nunes, Castro, Ana Paula Moschione, Al‐Qahtani, Abdulhadi, Arnaout, Rand, Khaliq, Agha Rehan, Amin, Rashid, Sheikh, Farrukh, Alvarez, Jorge, Anda, Marta, Palacios, Miriam, De Prada, Montserrat, Ponce, Carmen, Balbino, Bianca, Sibilano, Riccardo, Marichal, Thomas, Gaudenzio, Nicolas, Karasuyama, Hajime, Bruhns, Pierre, Tsai, Mindy, Reber, Laurent L, Galli, Stephen J, Ferreira, Ana Reis, Cernadas, Josefina R, del Campo García, Aida, Fernández, Sara Pereiro, Carrera, Nerea Sarmiento, Sánchez‐Cruz, Fernando Bandrés, Lorenzo, José Ramón Fernández, Claus, Stephanie, Pföhler, Claudia, Ruëff, Franziska, Treudler, Regina, Jaume, Mercedes Escarrer, Madroñero, Agustin, Perez, Maria Teresa Guerra, Julia, Juan Carlos, Plovdiv, Charlotte Hands, Gethings, Lee, Langridge, Jim, Adel‐Patient, Karine, Bernard, Hervé, Barcievic‐Jones, Ivona, Sokolova, Raditsa, Yankova, Rumyana, Ivanovska, Mariya, Murdjeva, Marianna, Popova, Tatyana, Dermendzhiev, Svetlan, Karjalainen, Martin, Lehnigk, Ulrike, Brown, Duncan, Locklear, Julie C, Locklear, Julie, Maris, Ioana, Hourihane, Jonathan, Ornelas, Cristina, Caiado, Joana, Ferreira, Manuel Branco, Pereira‐Barbosa, Manuel, Puente, Yolanda, Daza, Juan Carlos, Monteseirin, Francisco Javier, Ukleja‐Sokolowska, Natalia, Gawronska‐Ukleja, Ewa, Zbikowska‐Gotz, Magdalena, Bartuzi, Zbigniew, Sokolowski, Lukasz, Adams, Aine, Mahon, Bernard, English, Karen, Gourdon‐Dubois, Nelly, Sellam, Laetitia, Pereira, Bruno, Michaud, Elodie, Messaoudi, Khaled, Evrard, Bertrand, Fauquert, Jean‐Luc, Palomares, Francisca, Gomez, Gador, Rodriguez, Maria Jose, Galindo, Luisa, Molina, Ana, Paparo, Lorella, Mennini, Maurizio, Aitoro, Rosita, Wawrzeńczyk, Adam, Przybyszewski, Michał, Wawrzeńczyk, Anna, Sarıcoban, Hulya Ercan, Ugras, Meltem, Yalvac, Zerrin, Blok, Bertine MJ Flokstra‐de, van der Velde, JL, Vereda, Andrea, Ippolito, Clara, Traversa, Amaranta, Adriano, Daniela, Bianchi, Daniela Manila, Gallina, Silvia, Decastelli, Lucia, Makatsori, Melina, Miles, Anne, Devetak, Sonja Posega, Devetak, Iztok, Tabet, Soraya Ainad, Trandbohus, Jeanette Fisker, Winther, Pernille, Malling, Hans‐Jørgen, Hansen, Kirsten Skamstrup, Garvey, Lene Heise, Wang, Chia‐Chi, Cheng, Yin‐Hua, Tung, Chun‐Wei, Dietrich, Mariola, Marenholz, Ingo, Kalb, Birgit, Grosche, Sarah, Blümchen, Katharina, Schlags, Rupert, Price, Mareike, Rietz, Sylke, Esparza‐Gordillo, Jorge, Lau, Susanne, 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Society, The Anaphylaxis Working Group of the French Allergology SocietyThe Anaphylaxis Working Group of the French Allergology, Pineau, Florence, Sakai, Shinobu, Matsunaga, Kayoko, Teshima, Reiko, Larré, Colette, Denery, Sandra, Tschirner, Sebastian, Trendelenburg, Valérie, Schulz, Gabriele, Niggemann, Bodo, Beyer, Kirsten, Bouferkas, Youcef, Belabbas, Younes, Saidi, Djamel, Kheroua, Omar, Mecherfi, Kamel Eddine El, Guendouz, Malika, Haddi, Abir, Kaddouri, Hanane, Amaral, Luis, Pereira, Ana, Rodrigues, Susana, Datema, Mareen, Jongejan, Laurian, Clausen, Michael, Knulst, Andre, Papadopoulos, Nikolaos, Kowalski, Marek, de Blay, Frédéric, Zwinderman, Aeilko, Hoffman‐Sommergruber, Karin, Ballmer‐Weber, Barbara, Fernandez‐Rivas, Montserrat, Deng, Shan, Yin, Jia, Eisenmann, Charlotte, Nassiri, Maria, Reinert, Rabea, van der Valk, Johanna PM, van Wijk, Roy Gerth, Vergouwe, Yvonne, Steyerberg, Ewout W, Reitsma, Marit, Wichers, Harry J, Savelkoul, Huub FJ, Vlieg‐Boerstra, Berber, Dubois, 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Ekaterini, Porto, Arnaldo, Wandalsen, Neusa F, Sarinho, Emanuel, Sano, Flavio, Solé, Dirceu, Pitsios, Constantinos, Petrodimopoulou, Maria, Papadopoulou, Ekaterini, Passioti, Maria, Kontogianni, Meropi, Adamia, Nino, Khaleva, Ekaterina, del Prado, Ana Prieto, Du Toit, George, Krzych, Edyta, Samolinska‐Zawisza, Urszula, Furmanczyk, Konrad, Tomaszewska, Aneta, Raciborski, Filip, Lipiec, Agnieszka, Samel‐Kowalik, Piotr, Walkiewicz, Artur, Borowicz, Jacek, Samolinski, Boleslaw, Nano, Aimee Lou, Recto, Marysia, Somoza, Maria Luisa, López, Natalia Blanca, Alzate, Diana Pérez, Ruano, Francisco Javier, Garcimartín, Maria Isabel, Haroun, Elisa, de la Torre, Maria Vázquez, Rojas, Antonia, Onieva, Montserrat López, Canto, Gabriela, Rodrigues, Alexandra, Forno, Andreia, Cabral, António Jorge, Gonçalves, Rute, Vorozhko, Ilya, Sentsova, Tatyana, Chernyak, Olga, Denisova, Svetlana, Ilènko, Lidia, Muhortnich, Valery, Zimmermann, Caroline, Rohrbach, Alexander, Bakhsh, Faisal R, Boudewijn, Kollen, Oomkes‐Pilon, Anne‐Marie, Van Ginkle, Dorien, Šilar, Mira, Jeverica, Anja, Vesel, Tina, Avčin, Tadej, Korošec, Peter, van der Valk, Johanna, Berends, Irene, Arends, Nicolette, van Maaren, Maurits, Wichers, Harry, Emons, Joyce, Dubois, Anthony, de Jong, Nicolette, Matsyura, Oksana, Besh, Lesya, Huang, Chung‐Hsiung, Jan, Tong‐Rong, Stiefel, Gary, Tratt, Jean, Kirk, Kerrie, Carolino, Fabricia, Arasi, Stefania, Caminiti, Lucia, Crisafulli, Giuseppe, Fiamingo, Chiara, Fresta, Jlenia, Pajno, Giovanni, Remington, Ben, Kruizinga, Astrid, Blom, W Marty, Westerhout, Joost, Bijlsma, Sabina, Baumert, Joe, Blankestijn, Mark, Otten, Henny, Klemans, Rob, Michelsen‐Huisman, Anouska D, van Os‐Medendorp, Harmieke, Kruizinga, Astrid G, Versluis, Astrid, van Duijn, Gert, de Zeeuw‐Brouwer, H Mary‐Lene, Castenmiller, Jacqueline JM, Noteborn, Hub PJM, Houben, Geert F, Bravin, Kristian, Luyt, David, Javed, Bushra, Couch, Phil, Munro, Christopher, Padfield, Phil, Sperrin, Matt, Byrne, Aideen, Oosthuizen, Lizalet, Kelleher, Carina, Ward, Fiona, Brosnan, Niamh, King, Graham, Corbet, Eva, Guzmán, Josué Alejandro Huertas, García, Montserrat Bosque, Asensio, Oscar, Navarrete, Laura Valdesoiro, Larramona, Helena, Miró, Xavier Domingo, Pyrz, Katarzyna, Austin, Moira, Boloh, Yanne, Couch, Philip, Galloway, Deirdre, Hernandez, Pilar, Hourihane, Jonathan O’B, Kenna, Fiona, Majkowska‐Wojciechowska, Barbara, Regent, Lynne, Themisb, Marina, Schnadt, Sabine, Semic‐Jusufagic, Aida, Galvin, Audrey Dunn, Kauppila, Tiina, Kuitunen, Mikael, Kitsioulis, Nikolaos A, Douladiris, Nikolaos, Kostoudi, Sofia, Manolaraki, Ioanna, Mitsias, Dimitris, Manousakis, Emmanouil, Papadopoulos, Nikolaos G, Knibb, Rebecca, Hammond, Jennifer, Cooke, Richard, Yrjänä, Jaakko, Hanni, Anna‐Maija, Vähäsarja, Päivi, Mustonen, Oona, Dunder, Teija, Kulmala, Petri, Lasa, Eva, D’Amelio, Carmen, Martínez, Sara, Joral, Alejandro, Gastaminza, Gabriel, Goikoetxea, Maria Jose, Candy, David CA, Van Ampting, Marleen TJ, Nijhuis, Manon M Oude, Butt, Assad M, Peroni, Diego G, Fox, Adam T, Knol, Jan, Michaelis, Louise J, Padua, Ines, Padrao, Patricia, Moreira, Pedro, Barros, Renata, Sharif, Hanan, Ahmed, Manzoor, Gomaa, Nehad, Mens, Joris, Smit, Koen, Timmermans, Frans, Poredoš, Tomaž, Jeverica, Anja Koren, Sedmak, Marjeta, Benedik, Evgen, Accetto, Meta, Zupančič, Mirjana, Yonamine, Glauce, Soldateli, Gustavo, Aquilante, Bruna, Pastorino, Antonio Carlos, de Moraes Beck, Cleonir Lui, Gushken, Andrea Keiko, de Barros Dorna, Mayra, dos Santos, Cristiane Nunes, Castro, Ana Paula Moschione, Al‐Qahtani, Abdulhadi, Arnaout, Rand, Khaliq, Agha Rehan, Amin, Rashid, Sheikh, Farrukh, Alvarez, Jorge, Anda, Marta, Palacios, Miriam, De Prada, Montserrat, Ponce, Carmen, Balbino, Bianca, Sibilano, Riccardo, Marichal, Thomas, Gaudenzio, Nicolas, Karasuyama, Hajime, Bruhns, Pierre, Tsai, Mindy, Reber, Laurent L, Galli, Stephen J, Ferreira, Ana Reis, Cernadas, Josefina R, del Campo García, Aida, Fernández, Sara Pereiro, Carrera, Nerea Sarmiento, Sánchez‐Cruz, Fernando Bandrés, Lorenzo, José Ramón Fernández, Claus, Stephanie, Pföhler, Claudia, Ruëff, Franziska, Treudler, Regina, Jaume, Mercedes Escarrer, Madroñero, Agustin, Perez, Maria Teresa Guerra, Julia, Juan Carlos, Plovdiv, Charlotte Hands, Gethings, Lee, Langridge, Jim, Adel‐Patient, Karine, Bernard, Hervé, Barcievic‐Jones, Ivona, Sokolova, Raditsa, Yankova, Rumyana, Ivanovska, Mariya, Murdjeva, Marianna, Popova, Tatyana, Dermendzhiev, Svetlan, Karjalainen, Martin, Lehnigk, Ulrike, Brown, Duncan, Locklear, Julie C, Locklear, Julie, Maris, Ioana, Hourihane, Jonathan, Ornelas, Cristina, Caiado, Joana, Ferreira, Manuel Branco, Pereira‐Barbosa, Manuel, Puente, Yolanda, Daza, Juan Carlos, Monteseirin, Francisco Javier, Ukleja‐Sokolowska, Natalia, Gawronska‐Ukleja, Ewa, Zbikowska‐Gotz, Magdalena, Bartuzi, Zbigniew, Sokolowski, Lukasz, Adams, Aine, Mahon, Bernard, English, Karen, Gourdon‐Dubois, Nelly, Sellam, Laetitia, Pereira, Bruno, Michaud, Elodie, Messaoudi, Khaled, Evrard, Bertrand, Fauquert, Jean‐Luc, Palomares, Francisca, Gomez, Gador, Rodriguez, Maria Jose, Galindo, Luisa, Molina, Ana, Paparo, Lorella, Mennini, Maurizio, Aitoro, Rosita, Wawrzeńczyk, Adam, Przybyszewski, Michał, Wawrzeńczyk, Anna, Sarıcoban, Hulya Ercan, Ugras, Meltem, Yalvac, Zerrin, Blok, Bertine MJ Flokstra‐de, van der Velde, JL, Vereda, Andrea, Ippolito, Clara, Traversa, Amaranta, Adriano, Daniela, Bianchi, Daniela Manila, Gallina, Silvia, Decastelli, Lucia, Makatsori, Melina, Miles, Anne, Devetak, Sonja Posega, Devetak, Iztok, Tabet, Soraya Ainad, Trandbohus, Jeanette Fisker, Winther, Pernille, Malling, Hans‐Jørgen, Hansen, Kirsten Skamstrup, Garvey, Lene Heise, Wang, Chia‐Chi, Cheng, Yin‐Hua, Tung, Chun‐Wei, Dietrich, Mariola, Marenholz, Ingo, Kalb, Birgit, Grosche, Sarah, Blümchen, Katharina, Schlags, Rupert, Price, Mareike, Rietz, Sylke, Esparza‐Gordillo, Jorge, Lau, Susanne, Lee, Young‐Ae, Almontasheri, Ali, Al Bahkali, Mohammad, Elshorbagi, Sahar, Alfhaid, Abdullah, Altamimi, Mashary, Madbouly, Eman, Al‐Dhekri, Hassan, Arnaout, Rand K, Basagaña, Maria, Miquel, Sira, Bartolomé, Borja, Brix, Bettina, Rohwer, Stefanie, Brandhoff, Sandra, Berger, Alena, Suer, Waltraud, Weimann, Alf, Bueno, Cristina, Martín‐Pedraza, Laura, Abián, Sara, San Segundo‐Acosta, Pablo, López‐Rodríguez, Juan Carlos, Barderas, Rodrigo, Batanero, Eva, Cuesta‐Herranz, Javier, Villalba, María Teresa, Correia, Magna, Benito‐Garcia, Filipe, Arêde, Cristina, Piedade, Susana, Morais‐Almeida, Mário, Hindley, James, Yarham, Ross, Kuklinska‐Pijanka, Anna, Gillick, David, Patient, Karine, Chapman, Martin D, Bøgh, Katrine L, Miranda, Ana, Matos, Eugénia, Sokolova, Anna, Rao, Huan, Baricevic‐Jones, Ivona, Smith, Frances, Xue, Wentong, Magnusdottir, Helga, Vidarsdottir, Anna G, Lund, Sigrun, Jensen, Anders Blom, Ludviksson, Bjorn R, Simon, Reyna, Elfont, Robert, Bennett, Sean, Voyksner, Robert, de Lurdes Torre, Maria, Yürek, Songül, Faber, Margaretha A, Bastiaensen, Annick, Mangodt, Evelyne, van Gasse, Athina, Decuyper, Ine, Sabato, Vito, Hagendorens, Margo M, Bridts, Chris H, De Clerck, Luc S, Ebo, Didier, Schwarz, Susanne, Ziegert, Mandy, Albroscheit, Saskia, Schwager, Christian, Kull, Skadi, Behrends, Jochen, Röckendorf, Niels, Schocker, Frauke, Frey, Andreas, Homann, Arne, Becker, Wolf‐Meinhard, Jappe, Uta, Zaabat, Nesrine, Osscini, Sylvia, Agabriel, Chantal, Sterling, Benoît, Carsin, Ania, Liabeuf, Valérie, Maćków, Monica, Zbróg, Alina, Bronkowska, Monica, Courtois, Justine, Gadisseur, Romy, Bertholet, Catherine, Lukas, Pierre, Cavalier, Etienne, Delahaut, Philippe, Quinting, Birgit, Gertmo, Margareta Brandt, Hasseus, Ewa Ternesten, Barzylovych, Vladyslava, Oliveira, Júlio, Ensina, Luis F, Aranda, Carolina S, Dopazo, Leire, Lopez, Rebeca, Perez, Raquel, Santos‐Diez, Laura, Bilbao, Agurtzane, Garcia, Juan Miguel, Núñez, Ignacio García, Mármol, María Ángeles Algaba, Villarejo, María José Barasona, Martos, José Antonio Bácter, Vergara, Marina Suárez, García, José María Ignacio, Michalska, Agata, Sergiejko, Grzegorz, Zacniewski, Robert, Ghiordanescu, Ileana‐Maria, Deaconu, Cristina, Popescu, Mihaela, Bumbacea, Roxana Silvia, Ibranji, Alkerta, Nikolla, Elida, Loloci, Gjustina, Juel‐Berg, Nanna, Larsen, Lau Fabricius, Poulsen, Lars Kjaergaard, Marcelino, João, Prata, Ricardo, Costa, Ana Célia, Duarte, Fátima, Neto, Marta, Santos, Jennifer, Pestana, Luís Câmara, Sampaio, Daniel, Minale, Paola, Dignetti, Paola, Bignardi, Donatella, Nedelea, Irena, Popescu, Florin‐Dan, Vieru, Mariana, Secureanu, Florin‐Adrian, Ganea, Carmen Saviana, Vieira, Miguel, Silva, José Pedro Moreira, Watts, Timothy, Watts, Sophia, Lomikovska, Marta, Peredelskaya, Marina, Nenasheva, Natalia, Filipovic, Ivana, Zivkovic, Zorica, Filipovic, Djordje, Higgs, Jennette, Warner, Amena, and Jones, Carla

Published
2017

114. A closed testing procedure to select an appropriate method for updating prediction models

Author

Epi Methoden Team 1, Circulatory Health, HEE, Epi Methoden, Cancer, Child Health, JC onderzoeksprogramma Methodologie, Vergouwe, Yvonne, Nieboer, Daan, Oostenbrink, Rianne, Debray, Thomas P A, Murray, Gordon D, Kattan, Michael W, Koffijberg, Hendrik, Moons, Karel G M, Steyerberg, Ewout W, Epi Methoden Team 1, Circulatory Health, HEE, Epi Methoden, Cancer, Child Health, JC onderzoeksprogramma Methodologie, Vergouwe, Yvonne, Nieboer, Daan, Oostenbrink, Rianne, Debray, Thomas P A, Murray, Gordon D, Kattan, Michael W, Koffijberg, Hendrik, Moons, Karel G M, and Steyerberg, Ewout W

Published
2017

115. Validation of prediction models:examining temporal and geographic stability of baseline risk and estimated covariate effects

Author

Austin, Peter C, van Klaveren, David, Vergouwe, Yvonne, Nieboer, Daan, Lee, Douglas S, Steyerberg, Ewout W, Austin, Peter C, van Klaveren, David, Vergouwe, Yvonne, Nieboer, Daan, Lee, Douglas S, and Steyerberg, Ewout W

Abstract

BACKGROUND: Stability in baseline risk and estimated predictor effects both geographically and temporally is a desirable property of clinical prediction models. However, this issue has received little attention in the methodological literature. Our objective was to examine methods for assessing temporal and geographic heterogeneity in baseline risk and predictor effects in prediction models.METHODS: We studied 14,857 patients hospitalized with heart failure at 90 hospitals in Ontario, Canada, in two time periods. We focussed on geographic and temporal variation in baseline risk (intercept) and predictor effects (regression coefficients) of the EFFECT-HF mortality model for predicting 1-year mortality in patients hospitalized for heart failure. We used random effects logistic regression models for the 14,857 patients.RESULTS: The baseline risk of mortality displayed moderate geographic variation, with the hospital-specific probability of 1-year mortality for a reference patient lying between 0.168 and 0.290 for 95% of hospitals. Furthermore, the odds of death were 11% lower in the second period than in the first period. However, we found minimal geographic or temporal variation in predictor effects. Among 11 tests of differences in time for predictor variables, only one had a modestly significant P value (0.03).CONCLUSIONS: This study illustrates how temporal and geographic heterogeneity of prediction models can be assessed in settings with a large sample of patients from a large number of centers at different time periods.

Published
2017

116. Combined anatomical and clinical factors for the long-term risk stratification of patients undergoing percutaneous coronary intervention: the Logistic Clinical SYNTAX score

Author

Farooq, Vasim, Vergouwe, Yvonne, Räber, Lorenz, Vranckx, Pascal, Garcia-Garcia, Hector, Diletti, Roberto, Kappetein, Arie Pieter, Morel, Marie Angèle, de Vries, Ton, Swart, Michael, Valgimigli, Marco, Dawkins, Keith D., Windecker, Stephan, Steyerberg, Ewout W., Serruys, Patrick W., Farooq, Vasim, Vergouwe, Yvonne, Räber, Lorenz, Vranckx, Pascal, Garcia-Garcia, Hector, Diletti, Roberto, Kappetein, Arie Pieter, Morel, Marie Angèle, de Vries, Ton, Swart, Michael, Valgimigli, Marco, Dawkins, Keith D., Windecker, Stephan, Steyerberg, Ewout W., and Serruys, Patrick W.

Abstract

Background The SYNTAX score (SXscore), an anatomical-based scoring tool reflecting the complexity of coronary anatomy, has established itself as an important long-term prognostic factor in patients undergoing percutaneous coronary intervention (PCI). The incorporation of clinical factors may further augment the utility of the SXscore to longer-term risk stratify the individual patient for clinical outcomes. Methods and results Patient-level merged data from >6000 patients in seven contemporary coronary stent trials was used to develop a logistic regression model—the Logistic Clinical SXscore—to predict 1-year risk for all-cause death and major adverse cardiac events (MACE). A core model (composed of the SXscore, age, creatinine clearance, and left ventricular ejection fraction) and an extended model [incorporating the core model and six additional (best performing) clinical variables] were developed and validated in a cross-validation procedure. The core model demonstrated a substantial improvement in predictive ability for 1-year all-cause death compared with the SXscore in isolation [area under the receiver operator curve (AUC): core model: 0.753, SXscore: 0.660]. A minor incremental benefit of the extended model was shown (AUC: 0.791). Consequently the core model alone was retained in the final the Logistic Clinical SXscore model. Validation plots confirmed the model predictions to be well calibrated. For 1-year MACE, the addition of clinical variables did not improve the predictive ability of the SXscore, secondary to the SXscore being the predominant determinant of all-cause revascularization. Conclusion The Logistic Clinical SXscore substantially enhances the prediction of 1-year mortality after PCI compared with the SXscore, and allows for an accurate personalized assessment of patient risk

Published
2017

120. Prognostic Factors in Chest Pain Patients: A Quantitative Analysis of the HEART Score

Author

Cardiovasculaire Epi Team 9, Cardiologie Arts-onderzoekers, Cardiologie, Regenerative Medicine and Stem Cells, Circulatory Health, Backus, Barbra E, Six, A Jacob, Doevendans, Pieter A, Kelder, Johannes C, Steyerberg, Ewout W, Vergouwe, Yvonne, Cardiovasculaire Epi Team 9, Cardiologie Arts-onderzoekers, Cardiologie, Regenerative Medicine and Stem Cells, Circulatory Health, Backus, Barbra E, Six, A Jacob, Doevendans, Pieter A, Kelder, Johannes C, Steyerberg, Ewout W, and Vergouwe, Yvonne

Published
2016

121. Barriers and facilitators perceived by physicians when using prediction models in practice

Author

Circulatory Health, Medische staf Anesthesiologie, AIOS Anesthesiologie, Brain, Other research (not in main researchprogram), Management Vitale Functies, Infection & Immunity, JC onderzoeksprogramma Methodologie, Cancer, Epi Methoden, Epi Methoden Team 1, Kappen, Teus H., Van Loon, Kim, Kappen, Martinus A M, Van Wolfswinkel, Leo, Vergouwe, Yvonne, Van Klei, Wilton A., Moons, Karel G M, Kalkman, Cor J., Circulatory Health, Medische staf Anesthesiologie, AIOS Anesthesiologie, Brain, Other research (not in main researchprogram), Management Vitale Functies, Infection & Immunity, JC onderzoeksprogramma Methodologie, Cancer, Epi Methoden, Epi Methoden Team 1, Kappen, Teus H., Van Loon, Kim, Kappen, Martinus A M, Van Wolfswinkel, Leo, Vergouwe, Yvonne, Van Klei, Wilton A., Moons, Karel G M, and Kalkman, Cor J.

Published
2016

124. Barriers and facilitators perceived by physicians when using prediction models in practice

Author

Kappen, TH, van Loon, K, Kappen, MAM, van Wolfswinkel, L, Vergouwe, Yvonne, Van Klei, WA, Moons, KGM, Kalkman, CJ, Kappen, TH, van Loon, K, Kappen, MAM, van Wolfswinkel, L, Vergouwe, Yvonne, Van Klei, WA, Moons, KGM, and Kalkman, CJ

Abstract

Objectives: Prediction models may facilitate risk-based management of health care conditions. In a large cluster-randomized trial, presenting calculated risks of postoperative nausea and vomiting (PONV) to physicians (assistive approach) increased risk-based management of PONV. This increase did not improve patient outcome that is, PONY incidence. This prompted us to explore how prediction tools guide the decision-making process of physicians. Study Design and Setting: Using mixed methods, we interviewed eight physicians to understand how predicted risks were perceived by the physicians and how they influenced decision making. Subsequently, all 57 physicians of the trial were surveyed for how the presented risks influenced their perceptions. Results: Although the prediction tool made physicians more aware of PONY prevention, the physicians reported three barriers to use predicted risks in their decision making. PONY was not considered an outcome of utmost importance; decision making on PONY prophylaxis was mostly intuitive rather than risk based; prediction models do not weigh benefits and risks of prophylactic drugs. Conclusion: Combining probabilistic output of the model with their clinical experience may be difficult for physicians, especially When their decision-making process is mostly intuitive. Adding recommendations to predicted risks (directive approach) was considered an important step to facilitate the uptake of a prediction tool. (C) 2016 Elsevier Inc. All rights reserved.

Published
2016

125. No Negative Impact of Palliative Sedation on Relatives' Experience of the Dying Phase and Their Wellbeing after the Patient's Death: An Observational Study

Author

Bruinsma, SM, van der Heide, Agnes, van der Lee, ML, Vergouwe, Yvonne, Rietjens, Judith, Bruinsma, SM, van der Heide, Agnes, van der Lee, ML, Vergouwe, Yvonne, and Rietjens, Judith

Abstract

Background Palliative sedation is the widely-used intervention of administering sedating agents to induce a state of unconsciousness to take away a dying patient's perception of otherwise irrelievable symptoms. However, it remains questionable whether this ethically complex intervention is beneficial for patients and whether the associated lack of communication in the last phase of life has a negative impact on relatives' wellbeing. Methods An observational questionnaire study was conducted among relatives of a consecutive sample of patients who died a non-sudden death in the Erasmus MC Cancer Institute or in the hospice 'Laurens Cadenza' (both in Rotterdam) between 2010 and 2013. Results Relatives filled in questionnaires regarding 151 patients who had been sedated and 90 patients who had not been sedated. The median time since all patients had passed away was 21 (IQR 14-32) months. No significant differences were found in relatives 'assessments of the quality of end-of-life care, patients 'quality of life in the last week before death and their quality of dying, between patients who did and did not receive sedation, or in relatives' satisfaction with their own life, their general health and their mental wellbeing after the patient's death. Conclusions The use of sedation in these patients appears to have no negative effect on bereaved relatives' evaluation of the patient's dying phase, or on their own wellbeing after the patient's death.

Published
2016

133. Improved Prediction by Dynamic Modeling

Author

Siregar, Sabrina, primary, Nieboer, Daan, additional, Vergouwe, Yvonne, additional, Versteegh, Michel I.M., additional, Noyez, Luc, additional, Vonk, Alexander B.A., additional, Steyerberg, Ewout W., additional, and Takkenberg, Johanna J.M., additional

Published
2016
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134. Assessing calibration of multinomial risk prediction models

Author

Van Hoorde, K, Vergouwe, Yvonne, Timmerman, D, Van Huffel, S, Steyerberg, Ewout, Calster, BJ, and Public Health

Subjects
SDG 3 - Good Health and Well-being
Abstract

Calibration, that is, whether observed outcomes agree with predicted risks, is important when evaluating risk prediction models. For dichotomous outcomes, several tools exist to assess different aspects of model calibration, such as calibration-in-the-large, logistic recalibration, and (non-)parametric calibration plots. We aim to extend these tools to prediction models for polytomous outcomes.We focus on models developed using multinomial logistic regression (MLR): outcome Y with k categories is predicted using k-1 equations comparing each category i (i=2,...,k) with reference category 1 using a set of predictors, resulting in k-1 linear predictors. We propose a multinomial logistic recalibration framework that involves an MLR fit where Y is predicted using the k-1 linear predictors from the prediction model. A non-parametric alternative may use vector splines for the effects of the linear predictors. The parametric and non-parametric frameworks can be used to generate multinomial calibration plots. Further, the parametric framework can be used for the estimation and statistical testing of calibration intercepts and slopes.Two illustrative case studies are presented, one on the diagnosis of malignancy of ovarian tumors and one on residual mass diagnosis in testicular cancer patients treated with cisplatin-based chemotherapy. The risk prediction models were developed on data from 2037 and 544 patients and externally validated on 1107 and 550 patients, respectively.We conclude that calibration tools can be extended to polytomous outcomes. The polytomous calibration plots are particularly informative through the visual summary of the calibration performance. Copyright (c) 2014 John Wiley & Sons, Ltd.

Published
2014

135. Identifying Axial Spondyloarthritis in Dutch Primary Care Patients, Ages 20-45 Years, With Chronic Low Back Pain

Author

van Hoeven, Lonneke, Luime, J.J., Han, H, Vergouwe, Yvonne, Weel, A, Rheumatology, and Public Health

Abstract

ObjectiveTo identify axial spondyloarthritis (SpA) in Dutch primary care patients with chronic low back pain (CLBP), and to design a simple referral model for general practitioners (GPs) that would identify patients at risk for axial SpA. MethodsPatients (ages 20-45 years) with CLBP were identified from GP records. Assessments included inflammatory back pain questionnaires, medical interviews, physical examinations, HLA-B27, C-reactive protein level, conventional radiography, and magnetic resonance imaging. The outcome measure was axial SpA defined by the Assessment of SpondyloArthritis international Society (ASAS) criteria. Multivariable regression analysis with bootstrapping was used to develop the referral model. ResultsA total of 364 patients (mean SD age 36.3 +/- 6.8 years) was recruited with a median symptom duration of 9.0 years. Eighty-six patients (24%) fulfilled the ASAS criteria for axial SpA. Of all potential determinants, the ASAS inflammatory back pain questionnaire, good response to nonsteroidal antiinflammatory drugs, family history of SpA, and symptom duration were identified as most relevant for diagnosing axial SpA by multivariable regression analysis related to axial SpA. The shrunken regression coefficients were, respectively, 1.04, 0.83, 0.73, and 0.23. The combination of these 4 items proved a useful area under the receiver operating characteristic curve of 0.75 (SE 0.03). In a simplified score model, at the suggested cutoff value of 1.5, the sensitivity was 83% and specificity was 59%. ConclusionThis study shows that 1 of 4 primary care patients with CLBP was classified as having axial SpA. A preselection in primary care based on a combination of clinical items may be useful to facilitate the identification of patients at risk of axial SpA.

Published
2014

136. Meta-analysis and aggregation of multiple published prediction models

Author

Debray, TPA, Koffijberg, H, Nieboer, Daan, Vergouwe, Yvonne, Steyerberg, Ewout, Moons, KGM (Karel), Public Health, and Epidemiology

Abstract

Published clinical prediction models are often ignored during the development of novel prediction models despite similarities in populations and intended usage. The plethora of prediction models that arise from this practice may still perform poorly when applied in other populations. Incorporating prior evidence might improve the accuracy of prediction models and make them potentially better generalizable. Unfortunately, aggregation of prediction models is not straightforward, and methods to combine differently specified models are currently lacking. We propose two approaches for aggregating previously published prediction models when a validation dataset is available: model averaging and stacked regressions. These approaches yield user-friendly stand-alone models that are adjusted for the new validation data. Both approaches rely on weighting to account for model performance and between-study heterogeneity but adopt a different rationale (averaging versus combination) to combine the models. We illustrate their implementation in a clinical example and compare them with established methods for prediction modeling in a series of simulation studies. Results from the clinical datasets and simulation studies demonstrate that aggregation yields prediction models with better discrimination and calibration in a vast majority of scenarios, and results in equivalent performance (compared to developing a novel model from scratch) when validation datasets are relatively large. In conclusion, model aggregation is a promising strategy when several prediction models are available from the literature and a validation dataset is at hand. The aggregation methods do not require existing models to have similar predictors and can be applied when relatively few data are at hand. Copyright (c) 2014 John Wiley & Sons, Ltd.

Published
2014

138. Validation of a score chart to predict the risk of chronic mesenteric ischemia and development of an updated score chart

Author

Dijk, Louisa JD, Noord, Desirée, Geelkerken, Robert H, Harki, Jihan, Berendsen, Sophie A, Vries, Annemarie C, Moelker, Adriaan, Vergouwe, Yvonne, Verhagen, Hence JM, Kolkman, Jeroen J, and Bruno, Marco J

Abstract

The objective of this article is to externally validate and update a recently published score chart for chronic mesenteric ischemia (CMI). A multicenter prospective cohort analysis was conducted of 666 CMI-suspected patients referred to two Dutch specialized CMI centers. Multidisciplinary consultation resulted in expert-based consensus diagnosis after which CMI consensus patients were treated. A definitive diagnosis of CMI was established if successful treatment resulted in durable symptom relief. The absolute CMI risk was calculated and discriminative ability of the original chart was assessed by the c-statistic in the validation cohort. Thereafter the original score chart was updated based on the performance in the combined original and validation cohort with inclusion of celiac artery (CA) stenosis cause. In 8% of low-risk patients, 39% of intermediate-risk patients and 94% of high-risk patients of the validation cohort, CMI was diagnosed. Discriminative ability of the original model was acceptable (c-statistic 0.79). The total score of the updated chart ranged from 0 to 28 points (low risk 19% absolute CMI risk, intermediate risk 45%, and high risk 92%). The discriminative ability of the updated chart was slightly better (c-statistic 0.80). The CMI prediction model performs and discriminates well in the validation cohort. The updated score chart has excellent discriminative ability and is useful in clinical decision making.

Published
2019
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139. Validation of a score chart to predict the risk of chronic mesenteric ischemia and development of an updated score chart

Author

van Dijk, Louisa JD, van Noord, Desirée, Geelkerken, Robert H, Harki, Jihan, Berendsen, Sophie A, de Vries, Annemarie C, Moelker, Adriaan, Vergouwe, Yvonne, Verhagen, Hence JM, Kolkman, Jeroen J, and Bruno, Marco J

Abstract

Background and objective The objective of this article is to externally validate and update a recently published score chart for chronic mesenteric ischemia (CMI).Methods A multicenter prospective cohort analysis was conducted of 666 CMI-suspected patients referred to two Dutch specialized CMI centers. Multidisciplinary consultation resulted in expert-based consensus diagnosis after which CMI consensus patients were treated. A definitive diagnosis of CMI was established if successful treatment resulted in durable symptom relief. The absolute CMI risk was calculated and discriminative ability of the original chart was assessed by the c-statistic in the validation cohort. Thereafter the original score chart was updated based on the performance in the combined original and validation cohort with inclusion of celiac artery (CA) stenosis cause.Results In 8% of low-risk patients, 39% of intermediate-risk patients and 94% of high-risk patients of the validation cohort, CMI was diagnosed. Discriminative ability of the original model was acceptable (c-statistic 0.79). The total score of the updated chart ranged from 0 to 28 points (low risk 19% absolute CMI risk, intermediate risk 45%, and high risk 92%). The discriminative ability of the updated chart was slightly better (c-statistic 0.80).Conclusion The CMI prediction model performs and discriminates well in the validation cohort. The updated score chart has excellent discriminative ability and is useful in clinical decision making.

Published
2019
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140. Prediction of recurrence of hypertensive disorders of pregnancy between 34 and 37 weeks of gestation : A retrospective cohort study

Author

Oostwaard, Miriam, Langenveld, J, Bijloo, R, Wong, KM, Scholten, I, Loix, S, Hukkelhoven, CWPM, Vergouwe, Yvonne, Papatsonis, Dimitri, Mol, BWJ (Ben), Ganzevoort, W, Graduate School, Center for Reproductive Medicine, Obstetrics and Gynaecology, Amsterdam Public Health, Obstetrics & Gynecology, and Public Health

Subjects
HELLP-syndrome, small for gestational age, hypertension, pre-eclampsia, recurrence, Cardiovascular diseases [NCEBP 14], pregnancy
Abstract

Please cite this paper as: van Oostwaard M, Langenveld J, Bijloo R, Wong K, Scholten I, Loix S, Hukkelhoven C, Vergouwe Y, Papatsonis D, Mol B, Ganzevoort W. Prediction of recurrence of hypertensive disorders of pregnancy between 34 and 37 weeks of gestation: a retrospective cohort study. BJOG 2012;119:840847. Objective To assess the recurrence risk of late-preterm hypertensive disease of pregnancy, and to determine whether potential risk factors are predictive. Design Retrospective cohort study. Setting Three secondary and three tertiary care hospitals in the Netherlands. Population We identified women with a hypertensive disorder in the index pregnancy and delivery at 3437 weeks of gestation, between January 2000 and December 2002. Methods Data were extracted from medical files and women were approached for additional information on subsequent pregnancies. An adverse outcome was defined as the recurrence of a hypertensive disorder in the next subsequent pregnancy. Main outcome measures Absolute risk of recurrence and a prediction model containing demographic and clinical factors predictive for adverse outcome. Results We identified 425 women who matched the criteria, of whom 351 could be contacted. Of these women, 189 (54%) had had a subsequent pregnancy. Hypertensive disorders recurred in 96 (51%, 95% CI 4358%) women, of whom 17 (9%, 95% CI 514%) delivered again before 37 weeks of gestation. Chronic hypertension and maternal age were the strongest predictors for recurrence. Women undergoing recurrence had a nine-fold chance of developing chronic hypertension (37% versus 6%, OR 8.7, 95% CI 3.323). Conclusions Women with hypertensive disorders and late-preterm delivery have a 50% chance of recurrence, but only a 9% chance of recurrence resulting in delivery before 37 weeks of gestation. Women with chronic hypertension are prone to develop recurrence, and women with a recurrence more often developed chronic hypertension.

Published
2012

141. Discrimination ability of prediction models for ordinal outcomes: Relationships between existing measures and a new measure

Author

Calster, BJ, Van Belle, V, Vergouwe, Yvonne, Steyerberg, Ewout, and Public Health

Abstract

In this paper, we focus on measures to evaluate discrimination of prediction models for ordinal outcomes. We review existing extensions of the dichotomous c-indexwhich is equivalent to the area under the receiver operating characteristic (ROC) curvesuggest a new measure, and study their relationships. The volume under the ROC surface (VUS) scores sets of cases including one case from each outcome category. VUS considers sets as either correctly or incorrectly ordered by the model. All other existing measures assess pairs of cases. We propose an ordinal c-index (ORC) that is set-based but, contrary to VUS, scores sets more gradually by indicating the closeness of the model-based ordering to the perfect ordering. As a result, the ORC does not decrease rapidly as the number of outcome categories increases. It turns out that the ORC can be rewritten as the average of pairwise c-indexes. Hence, the ORC has both a set- and pair-based interpretation. There are several relationships between the existing measures, leading to only two types of existing measures: a prevalence-weighted average of pairwise c-indexes and the VUS. Our suggested measure ORC positions itself in between as it is set-based but turns out to equal an unweighted average of pairwise c-indexes. The measures are demonstrated through a case study on the prediction of six-month outcome after traumatic brain injury. In conclusion, the set-based nature and graded scoring system make the ORC an attractive measure with a simple interpretation, together with its prevalence-independence that is a natural property of a discrimination measure.

Published
2012

142. Voorspellen van sterfte bij zeer premature kinderen

Author

Schuit, Ewoud, Hukkelhoven, C.W.P.M., Manktelow, Bradley N., Papatsonis, Dimitri N.M., De Kleine, Martin J.K., Draper, Elizabeth S., Steyerberg, Ewout W., and Vergouwe, Yvonne

Subjects
Life Science
Abstract

Validatie in de Nederlandse situatie van 2 Britse prognostische modellen die het risico op sterfte voorspellen bijkinderen die zeer prematuur worden geboren. De kinderen zijn in leven bij het begin van de baring (model 1) of zijnopgenomen op de neonatale intensivecare-unit (NICU; model 2).

Published
2012

143. Herhaling hypertensieve aandoening tijdens zwangerschap*

Author

Van Oostwaard, Miriam F., Langenveld, Josje, Bijloo, Rianne, Wong, Kai Mee, Scholten, Irma, Loix, Stephanie, Hukkelhoven, C.W.P.M., Vergouwe, Yvonne, Papatsonis, Dimitri N.M., Mol, Ben Willem J., Ganzevoort, Wessel, Graduate School, Center for Reproductive Medicine, Obstetrics and Gynaecology, Amsterdam Public Health, Obstetrics & Gynecology, and Public Health

Subjects
Life Science
Abstract

To assess the recurrence risk of late preterm hypertensive disease of pregnancy and to determine whether potential risk factors are predictive. Retrospective cohort study. Our study cohort included 425 women with a pregnancy-related hypertensive disorder who had delivered between 34 and 37 weeks of gestation at three different academic and three tertiary care hospitals in the Netherlands during the 2000-2002 period. Data were collected from medical files and by telephone interviews with the women. An adverse outcome was defined as the recurrence of a hypertensive disorder during the subsequent pregnancy. We also designed a prediction model containing demographic and clinical factors predictive for an adverse outcome. Of the 425 women who met the inclusion criteria, 351 could be contacted, of whom 189 (54%) had had a subsequent pregnancy. Pregnancy-related hypertensive disorders had recurred in 96 (51%; 95% CI: 43-58) women. Seventeen women (9%; 95% CI: 5-14) had delivered again before the 37th week. Pre-existing hypertension and maternal age were the strongest predictors for recurrence. Women who had experienced a recurrence had a 9-fold chance of developing chronic hypertension (37 vs. 6%; OR 8.7; 95% CI: 3.3-23). Women with hypertensive disorders and late preterm deliveries have a 50% chance of recurrence of the disorder and a 9% chance of recurrent premature delivery. Women with pre-existing hypertension or who are older are prone to recurrence. Women with a recurrent hypertensive disorder during a subsequent pregnancy often later develop chronic hypertension

Published
2012

146. A new framework to enhance the interpretation of external validation studies of clinical prediction models

Author

Epi Methoden Team 1, Circulatory Health, Julius Centrum, JC onderzoeksprogramma Methodologie, Cancer, Debray, Thomas P A, Vergouwe, Yvonne, Koffijberg, Hendrik, Nieboer, Daan, Steyerberg, Ewout W., Moons, K. (Carl) G.M., Epi Methoden Team 1, Circulatory Health, Julius Centrum, JC onderzoeksprogramma Methodologie, Cancer, Debray, Thomas P A, Vergouwe, Yvonne, Koffijberg, Hendrik, Nieboer, Daan, Steyerberg, Ewout W., and Moons, K. (Carl) G.M.

Published
2015

147. Palliative care consultation services in hospitals in the Netherlands: the design of the COMPASS study

Author

Stoppelenburg, Arianne, Polinder, Suzanne, Vergouwe, Yvonne, van der Heide, Agnes, Stoppelenburg, Arianne, Polinder, Suzanne, Vergouwe, Yvonne, and van der Heide, Agnes

Abstract

Background: Patients with an advanced incurable disease are often hospitalised for some time during the last phase of life. Care in hospitals is generally focussed at curing disease and prolonging life and may therefore not in all cases adequately address the needs of such patients. We present the COMPASS study, a study on the effects and costs of consultation teams for palliative care in hospitals. This observational study aims to investigate the use, effects and costs of PCT consultation services for hospitalized patients with incurable cancer in the Netherlands. Methods/design: The study consists of 3 parts: 1. A questionnaire, interviews and a focus group discussion to investigate the characteristics of PCT consultation in 12 hospitals. PCTs will register their activities to calculate the costs of PCT consultation. 2. Cancer patients for whom the attending physician would not be surprised that they would die within 12 month will be included in a medical file search in three hospitals. Medical records will be investigated to compare care, treatment and hospital costs between patients with and patients without PCT consultation. 3. In the other nine hospitals, we will perform a longitudinal study, and compare quality of life between 100 patients for whom a PCT was consulted with 200 patients without PCT consultation. Propensity score matching will be used to adjust for differences between both patient groups. Patients will be followed for three months after inclusion. Quality of life will be assessed with the Palliative Outcome Scale, the EuroQol-5d and the EORTC-QLQ-C15 PAL. Satisfaction with care in the hospital is measured with the IN-PATSAT32. The cost impact of PCT consultation will also be explored. Discussion: This is the first multicenter study on PCT consultation in the Netherlands. The study will give valuable insight in the process, effects and costs of PCT consultation in hospitals. It is anticipated that PCT consultation has a positive effect on patien

Published
2015

148. Impact of a Clinical Decision Model for Febrile Children at Risk for Serious Bacterial Infections at the Emergency Department: A Randomized Controlled Trial

Author

Kerkhof, Evelien, Nijman, Ruud, Vergouwe, Yvonne, Polinder, Suzanne, Steyerberg, Ewout, Lei, Johan, Moll, Henriette, Oostenbrink, Rianne, Kerkhof, Evelien, Nijman, Ruud, Vergouwe, Yvonne, Polinder, Suzanne, Steyerberg, Ewout, Lei, Johan, Moll, Henriette, and Oostenbrink, Rianne

Abstract

Objectives To assess the impact of a clinical decision model for febrile children at risk for serious bacterial infections (SBI) attending the emergency department (ED). Methods Randomized controlled trial with 439 febrile children, aged 1 month-16 years, attending the pediatric ED of a Dutch university hospital during 2010-2012. Febrile children were randomly assigned to the intervention (clinical decision model; n=219) or the control group (usual care; n=220). The clinical decision model included clinical symptoms, vital signs, and C-reactive protein and provided high/low-risks for "pneumonia" and "other SBI". Nurses were guided by the intervention to initiate additional tests for high-risk children. The clinical decision model was evaluated by 1) area-under-the-receiver-operating-characteristic-curve (AUC) to indicate discriminative ability and 2) feasibility, to measure nurses' compliance to model recommendations. Primary patient outcome was defined as correct SBI diagnoses. Secondary process outcomes were defined as length of stay; diagnostic tests; antibiotic treatment; hospital admission; revisits and medical costs. Results The decision model had good discriminative ability for both pneumonia (n=33; AUC 0.83 (95% CI 0.75-0.90)) and other SBI (n=22; AUC 0.81 (95% CI 0.72-0.90)). Compliance to model recommendations was high (86%). No differences in correct SBI determination were observed. Application of the clinical decision model resulted in less full-blood-counts (14% vs. 22%, p-value<0.05) and more urine-dipstick testing (71% vs. 61%, p-value<0.05). Conclusions In contrast to our expectations no substantial impact on patient outcome was perceived. The clinical decision model preserved, however, good discriminatory ability to detect SBI, achieved good compliance among nurses and resulted in a more standardized diagnostic approach towards febrile children, with less full blood-counts and more rightfully urine-dipstick testing.

Published
2015

149. Failure of introduction of food allergens after negative oral food challenge tests in children

Author

Valk, Hanna, Gerth van Wijk, Roy, Vergouwe, Yvonne, de Jong, Nicolette, Valk, Hanna, Gerth van Wijk, Roy, Vergouwe, Yvonne, and de Jong, Nicolette

Abstract

One of the purposes to perform an oral food challenge (FC) test is to avoid unnecessary elimination of food allergens. In case of a negative FC test result, the food can be introduced. It is, however, unknown if patients act according to the outcome of the test. This study evaluates the rate of introduction of peanut, hazelnut, cow's milk or hen's egg allergens after a negative FC test. We investigated the introduction rate of children (0-18 years) with a negative FC test visiting the Department of Allergology, Erasmus Medical Centre Rotterdam from 2008 till 2013 and the factors that influence the rate of introduction. Patients were asked to complete a comprehensive questionnaire about their FC test. In total, 157 (38 % girls, mean age during challenge 6.9 years) participated in the study. Of these FC tests, 104 (56 %) were followed by a successful introduction, 30 (16 %) by a partly introduction (traces or processed foods) and 52 (28 %) by a failed introduction. Peanut and hazelnut showed a statistically significant lower successful introduction rate. Age, gender, symptoms during FC test, dietary advice and time period to introduction significantly influenced the rate of introduction. One fourth of the children with failure of introducing foods experienced symptoms during the introduction. Conclusion: More than one quarter of all children with a negative FC test result did not introduce the food. The FC test in its current form does not achieve its objective for this group of children.

Published
2015

150. A new framework to enhance the interpretation of external validation studies of clinical prediction models

Author

Debray, TPA, Vergouwe, Yvonne, Koffijberg, H, Nieboer, Daan, Steyerberg, Ewout, Moons, KGM, Debray, TPA, Vergouwe, Yvonne, Koffijberg, H, Nieboer, Daan, Steyerberg, Ewout, and Moons, KGM

Abstract

Objectives: It is widely acknowledged that the performance of diagnostic and prognostic prediction models should be assessed in external validation studies with independent data from "different but related" samples as compared with that of the development sample. We developed a framework of methodological steps and statistical methods for analyzing and enhancing the interpretation of results from external validation studies of prediction models. Study Design and Setting: We propose to quantify the degree of relatedness between development and validation samples on a scale ranging from reproducibility to transportability by evaluating their corresponding case-mix differences. We subsequently assess the models' performance in the validation sample and interpret the performance in view of the case-mix differences. Finally, we may adjust the model to the validation setting. Results: We illustrate this three-step framework with a prediction model for diagnosing deep venous thrombosis using three validation samples with varying case mix. While one external validation sample merely assessed the model's reproducibility, two other samples rather assessed model transportability. The performance in all validation samples was adequate, and the model did not require extensive updating to correct for miscalibration or poor fit to the validation settings. Conclusion: The proposed framework enhances the interpretation of findings at external validation of prediction models. (C) 2015 The Authors. Published by Elsevier Inc.

Published
2015

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