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1. Assessing Selection Bias in Regression Coefficients Estimated from Non-Probability Samples, with Applications to Genetics and Demographic Surveys

Author

West, Brady T., Little, Roderick J. A., Andridge, Rebecca R., Boonstra, Philip S., Ware, Erin B., Pandit, Anita, and Alvarado-Leiton, Fernanda

Subjects
Statistics - Methodology, Statistics - Applications
Abstract

Selection bias is a serious potential problem for inference about relationships of scientific interest based on samples without well-defined probability sampling mechanisms. Motivated by the potential for selection bias in (a) estimated relationships of polygenic scores (PGSs) with phenotypes in genetic studies of volunteers, and (b) estimated differences in subgroup means in surveys of smartphone users, we derive novel measures of selection bias for estimates of the coefficients in linear and probit regression models fitted to non-probability samples, when aggregate-level auxiliary data are available for the selected sample and the target population. The measures arise from normal pattern-mixture models that allow analysts to examine the sensitivity of their inferences to assumptions about non-ignorable selection in these samples. We examine the effectiveness of the proposed measures in a simulation study, and then use them to quantify the selection bias in (a) estimated PGS-phenotype relationships in a large study of volunteers recruited via Facebook, and (b) estimated subgroup differences in mean past-year employment duration in a non-probability sample of low-educated smartphone users. We evaluate the performance of the measures in these applications using benchmark estimates from large probability samples., Comment: 29 pages, 4 figures, 2 tables, supplementary material

Published
2020

2. Extracorporeal Life Support Organization Registry International Report 2022: 100,000 Survivors

Author

Tonna, Joseph E., Boonstra, Philip S., MacLaren, Graeme, Paden, Matthew, Brodie, Daniel, Anders, Marc, Hoskote, Aparna, Ramanathan, Kollengode, Hyslop, Rob, Fanning, Jeffrey J., Rycus, Peter, Stead, Christine, Barrett, Nicholas A., Mueller, Thomas, Gómez, Rene D., Malhotra Kapoor, Poonam, Fraser, John F., Bartlett, Robert H., Alexander, Peta M.A., Barbaro, Ryan P., Abbasi, Adeel, Said Abdalmohsen, Ahmad, Abdelbary, Akram M., Abecasis, Francisco, Abel, Peter, Abu-Omar, Yasir, Adams, Douglas R, Manuel Africano, Juan, Aganga, Devon, Agati, Salvatore, Agerstrand, Cara, Aguillon, Mario V., Akers, Crystal S., Akhtarekhavari, Julia, Alazzam, Mohammad Izzat Salah, Albert, Martin, Alberti, Angela, Al-Fares, Abdulrahman A., Alfoudri, Huda, Allaert, Silvie, Allbert, Keesha N., Allen, Christopher T., Lescano Alva, Miguel Ángel, Alwardt, Cory M., Amigoni, Angela, Anandamurthy, Balaram, Anastasiadis, Kyriakos, Anders, Nicholas R., Anderson, Scott A., Anderson, Patricia L., Andrijević, Ana, Annoni, Alice, Anselmi, Michael, Anstey, James R., Antonini, Marta V., Antonitsis, Polychronis, Stein Araujo, Tays, Arcalas, Rhodney, Areinamo, Igor, Martin Arias, Anibal, Armijo-Garcia, Veronica, Aronsky, Vladimir, Arora, Lovkesh, Arora, Madhur, Leigh Aspenleiter, Marit, Atik, Fernando A., AugustGeorg Auzinger, Erin Colleen, Azzam, Ismail, Bacchetta, Matthew, Bak, Erica I., Balcells, Joan, Sánchez Ballesteros, Jesús, Banjac, Igor S., Barbaria, Jacqueline M., Barrigoto, Cleide L., Bass, Stephanie D., Batranović, Uroš, Bauer, Matthew H., Fernando Bautista, Diego, Beck, Robert M., Giraldo Bejarano, Estefania, Belohlavek, Jan, Bembea, Melania M., Benes, Jan, Benharash, Peyman, Benish, Lynne A., Bennett, Suzanne, Bento, Luís F.N., Bermudez, Christian A., Bertini, Pietro, Best, Derek, Bharat, Ankit, Bhutta, Omar J., Bizzell, Samantha J., Blakeman, Stephanie A., Blanco-Schweizer, Pablo, Blanton, Jessica K., Blood, Peggy S., Bohlmann, Allison S., Kyle Bohman, John, Bombino, Michela, Kathleen Bonadonna, Desiree, Bond, Ashley, Borgmann, Kristina M., Bourgoin, Pierre, Boville, Brian M., Boza, Raquel, Brady, Heather L., Brady, Alison, Braunlich, Jessica M., Bridges, Brian C., Brinkley, Karen K., Brookshire, Robert S., Brozzi Nicole Brueggemann, Nicolas A., Buckley, Dwight P., Jr., Buckley, Klayton, Budhani, Irfan B., Bukamal, Nazar, Burgos, Lucrecia M, Burša, Filip, Busby, Landon K., Buscher, Hergen, Butler, Menoly, Butt, Warwick W., Byrnes, Jonathan W., Calaritis, Christos, Caldwell, Lisa R., Calligaro, Gregory L., Campbell, Patrick T., Camporota, Luigi, Fernando Caneo, Luiz, Jovo Carapic, Vladimir, Carrasco-Carrasco, Cristina, Ivan Carrizo, Nestor, Carrow, Heidi, Carton, Edmund G., Casabella, Christian, Gomez Casal, Vanesa, Casey, Francis L., III, Castillo, Andres, Castleberry, Anthony W., Alexandros Cavayas, Yiorgos, Cerqua, Karey, Ming Chan, Kai Man ChanWai, Brian Chapman, Jason, Brahma Chari, Hari, Cheifetz, Omair ChaudharyIra M., Chen, Robin H.S, Chen, Weiting, Cheung, Eva W., Cheung, Anson, Chico, Juan I., Chiletti, Roberto, Jin Cho, Hwa, Cholette, Jill M., Christensen, Steffen, Chui, Betty S., Circelli, Alessandro, Clement, Katherine C., Cleuziou, Julie, Clouse, Brian, Cole, Gwendolen, Coles, Garrett M., Collins, Monika F., Collins, Monika F., Connelly, James, Conrad, Steven A., Cook, Marlene, Copeland, Hannah, Copus, Scott C., Cox, Charles S., Jr, Craig, Lynne K., Crain, Natasha, Cremonese, Ricardo V., Criswell, Emily A., Cross, Lisa M., Crowley, Moira A., Crowley, Jerome C., Cruz, Leonora, Cypel, Marcelo, Czarnik, Tomasz, Czuczwa, Miroslaw E., Sica da Rocha, Taís, Daddow, Samuel, Dali, Dante C., Dalton, Heidi J., Daly, Kathleen J.R., Damuth, Emily, Daniel, Dennis A., Daniel IV, John M., Daniel, Josiane M., Danis, Max D., Danko, Melissa E., Rodrigues Dantas, Joao Alberto, Daoust, Isabelle, Dauwe, Dieter F., Davidson, Mark, Davis, Joel C., Davis, Mitchell, D’Cunha, Jonathan, de Arruda Bravim, Bruno, de BoodeKim T. De La Cruz, Willem P., Gray DeAngelis, Kathryn, Debeuckelaere, Gerdy, Deitemyer, Matthew A., DellaVolpe, Jeffrey, Deneau, Jamie L., DeNino, Walter F., Denmark, Christopher G., Denney, Derek, DeValeria, Patrick A., Dewulf, Petra, Di Nardo, Matteo, DiBardino, Daniel J., DiMartino, Joseph, Dimopoulos, Stavros, Domico, Michele B., Dominy, Meaghan E., Donker, Dirk W., Dresbach, Till, Droogh, Joep M., Dunlap, Tiffany W., Dupon, Allsion, Durham, Lucian A., III, Durward, Andrew, Dvorak, Anna, Dyett, John F., Dziedzina, Carol L., Eaken, Carmen L., Eaton, Jonathan S., Eberle, Christopher J., Edwards, Linda, Efseviou, Christakis, Eigner, Juliann M., Ahmed Elhamrawi, Hazem, Elhazmi, Alyaa M., Elizondo, Tammy, Ellersick, Beverly L., Emling, Jonathan A., Ernst, Andreas, Pablo Escalante, Juan, Espinoza, Otoniel, Evey, Lee W., Fan, Eddy, Fang, Gary, Faulkner, Gail M., Fauman, Karen R, Ferguson, Niall, Ferreira, Benigno, Fiane, Arnt E., Andrade Fierro, Dario, Martha Filippi, María, Findeisen, Michael C., Finlay, Katie, Finlayson, Gordon, Fischer, Gwenyth A., Fischer, Courtney D., Fischer, William J., III, Fisher, Caleb M., Fitriasari, Reni, Fitzgerald, Jillian, Fix, Melissa K., Fleming, Sarah B., Flynn, Brigid C., Forst, Beth A., Fortuna, Philip P., Foti, Giuseppe, Fox, Matthew P., Franco, Thais O., David Freeland, C., Fried, Justin A., Friedman, Matthew L., Furlanetto, Beatriz, Fux, Thomas, Gaião, Sérgio, Gale, Michael J., Garcia, Joann Kathleen G., Garcia-Montilla, Romel, Gardner, Eric R., Garg, Meena, Garrison, Lawrence L., Gavrilovic, Srdjan M., Gawda, Ryszard, Geer, Laura W., Gelandt, Elton A., Gelvin, Michael G., Genovese, Bradley M., George, Jeffrey A., George, Timothy J, George, Sangley, Ghimire, Anup, Giani, Marco, Gill, Baljit S., Glikes, Erin, Golecki, Michael, Gongora, Enrique, Govener, Sara, Graf, Amanda, Grasselli, Giacomo, Gray, Brian W., Greenlee, Joseph A., III, Gregoric, Igor D., Gregory, Melinda, Grins, Edgars, Volker Groesdonk, Heinrich, Group, Kimberly F., Guarracino, Fabio, Joy Guidi-Solloway, Alexandra, Gunn, Tyler M., Guru, Pramod K, Haddle, John C., Haft, Jonathan W., Haisz, Emma, Hall, Julie L., Hall, Cameron, Hamaguchi, Jun, Hammond, Terese C., Han, Peggy K., Hardison, Daphne C., Harischandra, Dickwelle T., Hart, Shaun M., Harting, Matthew T., Hartley, Louise, Harvey, Chris J., Hasan, Zubair, Fawzy Hassan, Ibrahim, Hastings, Jennifer R., Hatcher, Renee’, Hatton, Kevin W., Haught, Christopher K., Awori Hayanga, Jeremiah, Peter Haydon, Timothy, Healy, Aaron H., Heard, Micheal L., Heather, Beth M., Hendrix, Rik H.J., Hennig, Felix, Hermens, Greet HermansJeannine A.J., Hernandez, Deborah A., Hernandez-Montfort, Jaime, Herrera, Guillermo, Hickman, Keri, Hittel, Ashley, Hobbs, Crystal, Hoffman, Jordan R.H., Hollinger, Laura E., Homishak, Michael, Horigoshi, Nelson K., Hoshino, Kota, Huang, Shu-Chien, Huenges, Katharina, Hussey, Alexander D., Hyslop, Robert W., Ihle, Rayan E., Ingemansson, Ola, Ivulich, Daniel, Jackson, Amanda L., Garcia Jacques, Rogelio, Jain, Harsh, Jakobs, Sharon M., Jan, Robert, Janowiak, Lisa M., Jara, Claire B., Jarden, Angela M., Jarzembowski, Jamie L., Jaudon, Andrew, Kishore Jayanthi, Venkata Krishna, Jennings, Joseph A., Jeong, Inseok, Meza Jiménez, Rafael, Jimenez-Rodriguez, Gian M., Joachim, Sabrina, Joelsons, Daniel, Johnson, Caroline A., Johnson, Andrea L., Jones, Jeffry H., Joseph, Mark, Joseph, Sunimol, Joshi, Raja, Joyce, Christopher J., Seung Jung, Jae, Carone Junior, José, Kallas, Harry J., KamerkarPilje Kang, Asavari, Kar, Biswajit, Karapanagiotidis, Georgios T., Kattan, Javier, Kaufman, David A., Kawauchi, Akira, Keene, Sarah D., Keller, Norma M., Keller, Roberta, Kelley, Emily W., Kelley, Kellie, Kelly-Geyer, Janet F., Kenderessy, Peter, Kenny, Laura E., Keshavjee, Shaf, Kessel, D., Kessler, Heather, Keuler, Suzanne, Khicha, Sanjay, Wan Kim, Do, Kim, Richard Y., Maxwell Kime, Aaron, Kincade, Robert C., Kipfmueller, Florian, Kirk, Douglas A., Klein, Liviu, Knapp, Randall S., Knapp, Randall S., Kneyber, Martin C.J., Knowles, Andrea L., Koch, Jillian M., Koepke, Stephanie, Kogelmann, Klaus M., Elzo Kraemer, Carlos, Krauklis, Amanda, Krumroy, Samantha L., Kumar, Madhan, Kumar, Arun, Kumpf, Matthias E, Kyle, Kimberly, Laffin, Anna, Kees Lagrand, Wim, Lahiji, Parshawn A., Keung Lai, Peter Chi, Ka Lai, Cally Ho, Danielle Laird, Amanda, Landsberg, Michelle LaMarreDavid M., Lanmueller, Pia, Oude Lansink-Hartgring, Annemieke, Beth Larson, Sharon, Laufenberg, De’Ann M., Lavana, Jayshree, Layne, Tracie L., John Lazar, Michael, Ledoux, Matthew R., Lee, Raymond C., Leek, Thomas M., Lequier, Laurance, Lesbekov, Timur, Leslie, Robert, Anne Leung, Kit Hung, Lillie, Jon, Phang Lim, Yeong, Lim, Sang-Hyun, Lin, Ling, Lindsey, Thomas, Ho Ling, Steven Kin, Lingle, Kaitlyn J., Lipes, Jed, Liu, Songqiao, Llevadias, Judit, Lomas, Erin A., Longenecker, Robert D., Lorusso, Roberto, Ann Low, Tracy, Steven Lubinsky, Anthony, Lucas, Matthias LubnowMark T., Lucchini, Alberto, Luze, Lisa E., Lynch, William R., Manoj, M.C., Maas, Jacinta J., MacNamara, Vanessa, Madden, Jesse L., Maimone, Justin, Malhotra, Rajiv, Malone, Matthew P., Mangukia, Chirantan, Manzur-Sandoval, Daniel, Maráczi, Veronika, Marinaro, Jonathan L., Marinucci, Christina R., Marshall, Tammy, Martin, Mark, Marwali, Eva M., Maslach-Hubbard, Anna, Matijašević, Jovan, Mattke, Adrian, Mattucci, Joseph, Maul, Timothy M., Maybauer, Marc O., Mayette, Michael, Mayville, Joni R., McAllister, Catherine, McBride, Martha W., Scott McCaul, David, McClelland, Samantha L.S., Gregory McCloskey, Colin, McGregor, Randy, McKamie, Wesley A., McKee, Andrew D., McMahon, Chelsea M., McMullin, Kaye, McNicol, Jane, McNulty, John P., McRae, Thomas, Meade, Maureen E., Meersseman, Philippe, Mekeirele, Michael, Ito Mendes, Elisa, Menon, Anuradha P., Meyer, Jason P., Meyers, Jourdan E., Meyns, Bart, Mignone, John L., Miller, Brittany D., Miller, Malcolm G.A., Miller, Deborah, Mintak, Renee, Minter, Sarah M., Reis Miranda, Dinis, Mirza, Farrukh, Mishkin, Joseph D., Modelewski, Paul, Mohan, Rajeev C., Hui Mok, Yee, Money, Dustin, Monteagudo, Julie, Moores, Russell R., Jr., Moran, Patrick, Morelock, Shawn, Moreno, Marsha R., Blanco Morillo, Juan, Morrison, Tracy, Morton, John M., Morton, Brenda, Moscatelli, Andrea, Mosier, Jarrod M., Muellenbach, Ralf M., Mueller, Andreas, Mueller, Dale, Musca, Steven C., Nagpal, Dave, Najaf, Tasnim, Narasimhan, Mangala, Nater, Melissa, Natividad, Zynthia, Nedeljkov, Djordje, Nelson, Bryan D., Newman, Sally F., Newton, Debra E., Neyman, Jonathan L., George Ng, Wing Yiu, Nicholson, Meghan C., Nicolaas, Christine, Nix, Charlie, Nkwantabisa, Raymond, Nolan, Shirley, Norese, Mariano, Norton, Bridget M., Norton, Bridget M., O’Brien, Serena G., O’Callaghan, Maura, Oishi, Peter, O’Leary, Tony D., Olia, Salim E., O’Meara, Carlisle, Oppel, Emily E., Arias Ortiz, Julian, Oza, Pranay L., Ozment, Caroline P., Pacific, Marjorie, Pálizas, Fernando, Palmer, David, Paoletti, Luca, Pardo, Diego H., Paredes, Pablo, Patel, Thomas PasgaardMrunal G., Patel, Sandeep M., Patel, Vijay S., Patel, Brijesh V., PatelDrisya Paul, Sameer, Pawale, Amit A., Pearson, Nicole M., Renee Pearson, Crystal, Peek, Giles J., Pellecchia, Crescens M., Pellegrino, Vincent, Peperstraete, Harlinde, Perkins, Rebecca L., Perkins, Brandon, Peterec, Steven, Peterman, Claire, Phillips, Cooper W., Piekutowski, Richard R., Pilan, María L., Luisa Pilan, Maria, Mark Pincus, Jason, Pino, Melissa, Plambeck, Robert W., Plisco, Michael S., Plumley, Donald A., Plunkett, Mark D., Poffo, Robinson, Poh, Pei-Fen, Polito, Angelo, Pollema, Travis L, Pozzi, Matteo, Pozzi, Matteo, Pranikoff, Thomas, Prekker, Matthew E., Prossen, Erik F., Puligandla, Pramod S., Puslecki, Mateusz, Raheel Qureshi, Muhammad, Emilia Rabanal, Lily, Abdulhamid Rabie, Ahmed, Rackley, Craig R., Radovancevic, Rajko, Raes, Matthias, Allen Raff, Lauren Desiree, Rahban, Youssef, Raimer, Patricia L., Rajbanshi, Bijoy G., Ramanan, Raj, Rambaud, Jerome, Ramírez-Arce, Jorge A., Simões Ramos, Ana Carolina, Rao, Suresh G., Rector, Raymond, Redfors, Bengt, Regmi, Ashim, Alejandro Rey, Jose, Miguel Ribeiro, Joao, Richards, Chelsea E, Joan Richardson, C., Riddle, Christy C., Riera, Jordi, Ripardo, Marina, Rivas, Fernando M., Roan, Ronald M., Robertson, Elizabeth, Robinson, Megan, Röder, Daniel, Rodrigus, Inez E.R., Paul Roeleveld, Peter, Romano, Jennifer C., Rona, Roberto, Ann Rosenberg, Carol, Rosenow, Felix, Rowe, Robert J., Rower, Katy E., Rudolph, Kristina L., Fernando Rueda, Luis, Ruf, Bettina, Russell, Hyde M., Russell, Nichole, Ryan, Kathleen, Saberi, Asif A., Said, Ahmed S., Sailor, Caitlin, Sakal, Angela, Lujan Salas, Gisela, Salazar, Leonardo, Saleem, Kashif, Samoukovic, Gordan, Sanchez, Pablo G., Marie Santiago, Lian, Sargin, Murat, Miguel Sassine, Assad, Satou, Nancy L., Saunders, Paul C., Schachinger, Scott, Schaible, Thomas, Schellongowski, Peter, Schlager, Gerald W., Schmid, Christof, Schmitt, Joachim, Schnell, LeeAndra, Schnur, Janos, Schroeder, Lukas, Schubach, Scott, Schuetz, Michael T., Schwartz, Gary S., Schwarz, Patricia, Scriven, Nicole M., Seabrook, Ruth B., Seefeldt, Cassandra, Seelhammer, Troy G., Segura-Matute, Susana, Sen, Ayan, Adrian Seoane, Leonardo, Shaffer, Jamie, Shafi, Bilal M., Shambley, Shannon, Shankar, Shyam, Shapland, Amanda, Sharng, Yih, Shavelle, David, Sheldrake, Jayne, Mohan Shetty, Rajesh, Shiber, Joseph R., Shimzu, Naoki, Lou Short, Billie, Sichting, Kay A., Sidehamer, Keith E., Siebenaler, Teka, Silvestry, Scott C., Sinclair, Jennifer T, Sinclair, Andrew, Singh, Aalok R., Singh, Gurmeet, Skinner, Sean C., Smart, Alexandra, Smith, Reanna M., Smith, Adam, Smith, Karen, Sommer-Candelario, Sherri, Song, Seunghwan, Sorensen, Gro, Sousa, Eduardo, Sower, Christopher T., Spadea, Nicholas V, Spangle, April, Speicher, David G., Spieth, Peter M., Srivastava, Ankur, Srivastava, Neeraj, Stahl, Mark, Stallkamp, Eric D., Jr, Stanley, Vanessa J., Starr, Joanne P., Staudinger, Thomas, Stevens, Berkeley E., Stevens, Kimberly, Stocker, Christian, Strickland, Richard, Suarez, Erik E., Kumar Subramanian, Rakesh, Sudakevych, Serhii, Summerall, Charlene, Sundararajan, Santosh, Susupaus, Attapoom, Suzuki, Hiroyuki, Sweberg, Todd, Sydzyik, Troy, Anh Ta, Tuan, Tagliari, Luciana, Tanaka, Hiroyuki, Tanski, Christopher T., Tasset, Mark, Taylor, Donna M., Teman, Nicholas R., Ramesh Thangaraj, Paul, Thiagarajan, Ravi R., Thiruchelvam, Timothy, Thomas, James A., Thomas, Owain D., Thompson, Shaun L., Thomson, David A., Thukaram, Roopa, Todd, Mark L., Toeg, Hadi, Torres, Silvio F., Trautner, Simon, Trombino, Terry, Tuazon, Divina M., Tuel, Julie, Tukacs, Monika, Turner, April N., Tyree, Melissa M., Uchiyama, Prashant Vaijyanath, Makoto, van den Brule, Judith M.D., van Dyck, Marlice A., van Gijlswijk, Mascha, Van Meurs, Krisa P., VanDyck, Tyler J., Vardi, Amir, Vega, Alejandra, Ventetuolo, Corey E., Vera, Magdalena, Vercaemst, Leen, Vets, Philippe, Viamonte, Heather, Vidlund, Mårten, Vitali, Sally H., Vlaa, Alexander P.J., Vuylsteke, Alain, Loon Wan, Kah, Watkins, Reuben, Watson, Pia, Weast, Travis A., Weaver, Karen E., Welkovics, Norbert, Wellner, Heidi L., Wells, Jason C., Welter, Karen, Westpheling, Amber G., Whalen, Lesta D.S., Whebell, Stephen, Wiersema, Ubbo, Wiisanen, Matthew E., Eugene Wilcox, Bradley, Wille, Keith, Jan Will, Ellyne, Wilson, Brock J., Win, April M., Winearls, James R., Wise, Linda J., Witter, Tobias, Ruby Wong, Hoi Mei, Worku, Berhane, Wright, Tina M, Wu, James K., Yalon, Larissa A., Yantosh, Garrett, Yaranov, Dmitry M., Yee, Pat, Yi, Cassia, Yost, Christian C., Young, John, Younger, Katrina, Zaborowski, Steven, Zachmann, Brenda, Zainab, Asma, Zanai, Rosanna, Zhao, Ju, Zhou, Chengbin, and Zinger, Marcia

Published
2024
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5. Definitions of adverse events associated with extracorporeal membrane oxygenation in children: results of an international Delphi process from the ECMO-CENTRAL ARC

Author

Alexander, Peta M A, Di Nardo, Matteo, Combes, Alain, Vogel, Adam M, Antonini, Marta Velia, Barrett, Nicholas, Benedetti, Giulia M, Bettencourt, Amanda, Brodie, Daniel, Gómez-Gutiérrez, René, Gorga, Stephen M, Hodgson, Carol, Kapoor, Poonam Malhotra, Le, Jennifer, MacLaren, Graeme, O’Neil, Erika R, Ostermann, Marlies, Paden, Matthew L, Patel, Neil, Rojas-Peña, Alvaro, Said, Ahmed S, Sperotto, Francesca, Willems, Ariane, Vercaemst, Leen, Yoganathan, Ajit P, Lorts, Angela, del Nido, Pedro J, Barbaro, Ryan P, Abecasis, Francisco, Al Foudri, Huda, Anders, Marc M., Angus, Derek C., Annich, Gail M., Arachchillage, Deepa J., Akcan-Arikan, Ayse, Armstrong, Aimee K., Balcells, Joan, Barrett, Meredith, Bartlett, Robert H., Belda-Hofheinz, Sylvia, Bembea, Melania M., Best, Derek J., Bonadonna, Desiree, Boonstra, Philip S., Brogan, Thomas V, Brown, Katherine L, Butragueño-Laiseca, Laura, Butt, Warwick W., Camporota, Luigi, Cardenas, Barbara, Cascarano, Maria T., Caspi, Joseph, Chen, Eric, Chiletti, Roberto, Colombo, Giovanna G., Conte, Marisa L., Crowe, Liz, Cvetkovic, Mirjana, Dalton, Heidi J., Daverio, Marco, Davidson, Mark G., Davis, Carl, DiGeronimo, Robert J., Egbunine, Ariel, Ellis, W. Cory, Fan, Eddy, Foster, Claire C, Fraser, John F., Friedman, Matthew L., Furlong-Dillard, Jamie, Fynn-Thompson, Francis, Garcia, Alejandro V., Geppert, Jeffery, Gillette, Nicole, Grazioli, Lorenzo, Greene, Christina L, Guerguerian, Anne-Marie, Guilliams, Kristin P., Haji Fortis, Jumana Y., Hao, Jianming, Heinsar, Silver, Hejduk, Mark W., Himebauch, Adam S., Horvat, Christopher M., Hoskote, Aparna, Hou, Xiaotong, Hyslop, Robert W., Ibrahim, Nicole, Ito, Takuya, Karagiannidis, Christian, Karam, Oliver, Kaushik, Shubhi, Kilbaugh, Todd J., Kim-Campbell, Nahmah, Kirsch, Roxanne E, Kormos, Robert L., Kornberger, Angela, Krucoff, Mitchell W., Lakshminrusimha, Satyan, LaRovere, Kerri L, Leger, Pierre-Louis, Levy, Philip T., Lorusso, Roberto, Lyster, Haifa, Malone, Matthew P., McMullan, D. Michael, Mečířová, Soña, Mehran, Roxana, Merz, Scott I., Mochizuki, Shuichi, Moler, Frank W., Molla, Kalkidan, Monagle, Paul, Morgan, Gareth J., Morgan, Catherine, Morice, Marie-Claude, Muszynski, Jennifer A., Najaf, Tasnim A., Nellis, Marianne E., Newburger, Jane W., O'Rourke, P. Pearl, Ostadal, Petr, Ozment, Caroline P., Pagani, Francis D., Peek, Giles J., Polito, Angelo, Priest, John R., Raman, Lakshmi, Rintoul, Natalie E., Roy, Nathalie, Rubin, Juli, Rumford, Martha, Rycus, Peter, Ryerson, Lindsay M., Sakamoto, Wakako, Segura-Matute, Susana, Shekar, Kiran, Spinella, Philip C., Spitzer, Ernest, Starr, Joanne P., Stead, Christine, Steffen, Katherine, Steiner, Marie E., Tan, Lucy, Tasker, Robert C., Taylor, J. Michael, Thiagarajan, Ravi R., Tonna, Joseph E., Ubertini, Gina M., van Leeuwen, Grace, Vang, Eric, Ventetuolo, Corey E., Venugopal, Prem S., Weinberg, Allison, Westrope, Claire, Wu, Changfu, Wylie, Gillian, Zeymer, Uwe, Zivick, Elizabeth E., and Zochios, Vasileios

Abstract

Extracorporeal membrane oxygenation (ECMO) is a high-risk and low-volume life support with increasing clinical study. However, heterogenous outcome definitions impede data assimilation into evidence to guide practice. The Academic Research Consortium (ARC), an international collaborative forum committed to facilitating the creation of stakeholder-driven consensus nomenclature and outcomes for clinical trials of medical devices, supported the ECMO Core Elements Needed for Trials Regulation And quality of Life (ECMO-CENTRAL) ARC. The ECMO-CENTRAL ARC was assembled to develop definitions of paediatric ECMO adverse events for use in clinical trials and regulatory device evaluation. An initial candidate list of ECMO adverse events derived from the mechanical circulatory support ARC was supplemented with a review of ECMO-relevant adverse event definitions collated from literature published between Jan 1, 1988, and Feb 20, 2023. Distinct teams of international topic experts drafted separate adverse event definitions that were harmonised to existing literature when appropriate. Draft definitions were revised for paediatric ECMO relevance with input from patients, families, and an international expert panel of trialists, clinicians, statisticians, biomedical engineers, device developers, and regulatory agencies. ECMO-CENTRAL ARC was revised and disseminated across research societies and professional organisations. Up to three rounds of internet-based anonymous surveys were planned as a modified Delphi process. The expert panel defined 13 adverse event definitions: neurological, bleeding, device malfunction, acute kidney injury, haemolysis, infection, vascular access-associated injury, non-CNS thrombosis, hepatic dysfunction, right heart failure, left ventricular overload, lactic acidaemia, and hypoxaemia. Definitional structure varied. Among 165 expert panel members, 114 were eligible to vote and 111 voted. Consensus was achieved for all proposed definitions. Agreement ranged from 82% to 95%. ECMO-CENTRAL ARC paired rigorous development with methodical stakeholder involvement and dissemination to define paediatric ECMO adverse events. These definitions will facilitate new research and the assimilation of data across clinical trials and ECMO device evaluation in children.

Published
2024
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7. Shrinkage priors for isotonic probability vectors and binary data modeling, with applications to dose–response modeling.

Author

Boonstra, Philip S., Owen, Daniel R., and Kang, Jian

Subjects
*VECTOR data, *ISOTONIC regression, *RANDOM variables, *DATA modeling, *PROBABILITY theory
Abstract

Motivated by the need to model dose–response or dose‐toxicity curves in clinical trials, we develop a new horseshoe‐based prior for Bayesian isotonic regression modeling a binary outcome against an ordered categorical predictor, where the probability of the outcome is assumed to be monotonically non‐decreasing with the predictor. The set of differences between outcome probabilities in consecutive categories of the predictor is equipped with a multivariate prior having support over simplex. The Dirichlet distribution, which can be derived from a normalized sum of independent gamma‐distributed random variables, is a natural choice of prior, but using mathematical and simulation‐based arguments, we show that the resulting posterior is prone to underflow and other numerical instabilities, even under simple data configurations. We propose an alternative prior based on horseshoe‐type shrinkage that is numerically more stable. We show that this horseshoe‐based prior is not subject to the numerical instability seen in the Dirichlet/gamma‐based prior and that the horseshoe‐based posterior can estimate the underlying true curve more efficiently than the Dirichlet‐based one. We demonstrate the use of this prior in a model predicting the occurrence of radiation‐induced lung toxicity in lung cancer patients as a function of dose delivered to normal lung tissue. Our methodology is implemented in the R package isotonicBayes and therefore suitable for use in the design of dose‐finding studies or other dose–response modeling contexts. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Optimizing the doses of cancer drugs after usual dose finding.

Author

Strohbehn, Garth W, Stadler, Walter M, Boonstra, Philip S, and Ratain, Mark J

Subjects
DRUG toxicity, PATIENT safety, DIFFUSION of innovations, ANTINEOPLASTIC agents, CLINICAL trials, DRUG dosage, DRUG approval, MOTIVATION (Psychology), DRUG efficacy, TUMORS, DRUG development, MEDICAL care costs
Abstract

Since the middle of the 20th century, oncology's dose-finding paradigm has been oriented toward identifying a drug's maximum tolerated dose, which is then carried forward into phase 2 and 3 trials and clinical practice. For most modern precision medicines, however, maximum tolerated dose is far greater than the minimum dose needed to achieve maximal benefit, leading to unnecessary side effects. Regulatory change may decrease maximum tolerated dose's predominance by enforcing dose optimization of new drugs. Dozens of already approved cancer drugs require re-evaluation, however, introducing a new methodologic and ethical challenge in cancer clinical trials. In this article, we assess the history and current landscape of cancer drug dose finding. We provide a set of strategic priorities for postapproval dose optimization trials of the future. We discuss ethical considerations for postapproval dose optimization trial design and review three major design strategies for these unique trials that would both adhere to ethical standards and benefit patients and funders. We close with a discussion of financial and reporting considerations in the realm of dose optimization. Taken together, we provide a comprehensive, bird's eye view of the postapproval dose optimization trial landscape and offer our thoughts on the next steps required of methodologies and regulatory and funding regimes. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Bayesian shrinkage methods for partially observed data with many predictors

Author

Boonstra, Philip S., Mukherjee, Bhramar, and Taylor, Jeremy M. G.

Subjects
Statistics - Applications
Abstract

Motivated by the increasing use of and rapid changes in array technologies, we consider the prediction problem of fitting a linear regression relating a continuous outcome $Y$ to a large number of covariates $\mathbf {X}$, for example, measurements from current, state-of-the-art technology. For most of the samples, only the outcome $Y$ and surrogate covariates, $\mathbf {W}$, are available. These surrogates may be data from prior studies using older technologies. Owing to the dimension of the problem and the large fraction of missing information, a critical issue is appropriate shrinkage of model parameters for an optimal bias-variance trade-off. We discuss a variety of fully Bayesian and Empirical Bayes algorithms which account for uncertainty in the missing data and adaptively shrink parameter estimates for superior prediction. These methods are evaluated via a comprehensive simulation study. In addition, we apply our methods to a lung cancer data set, predicting survival time ($Y$) using qRT-PCR ($\mathbf {X}$) and microarray ($\mathbf {W}$) measurements., Comment: Published in at http://dx.doi.org/10.1214/13-AOAS668 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)

Published
2014
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16. Radiation-induced lung toxicity in non-small-cell lung cancer: Understanding the interactions of clinical factors and cytokines with the dose-toxicity relationship

Author

Hawkins, Peter G., Boonstra, Philip S., Hobson, Stephen T., Hearn, Jason W.D., Hayman, James A., Ten Haken, Randall K., Matuszak, Martha M., Stanton, Paul, Kalemkerian, Gregory P., Ramnath, Nithya, Lawrence, Theodore S., Schipper, Matthew J., (Spring) Kong, Feng-Ming, and Jolly, Shruti

Published
2017
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18. Modeling basal body temperature data using horseshoe process regression.

Author

Chase, Elizabeth C., Taylor, Jeremy M. G., and Boonstra, Philip S.

Subjects
BODY temperature, HORSESHOES, MENSTRUAL cycle, EMBRYO implantation, STOCHASTIC processes
Abstract

Biomedical data often exhibit jumps or abrupt changes. For example, women's basal body temperature may jump at ovulation, menstruation, implantation, and miscarriage. These sudden changes make these data challenging to model: many methods will oversmooth the sharp changes or overfit in response to measurement error. We develop horseshoe process regression (HPR) to address this problem. We define a horseshoe process as a stochastic process in which each increment is horseshoe‐distributed. We use the horseshoe process as a nonparametric Bayesian prior for modeling a potentially nonlinear association between an outcome and its continuous predictor, which we implement via Stan and in the R package HPR. We provide guidance and extensions to advance HPR's use in applied practice: we introduce a Bayesian imputation scheme to allow for interpolation at unobserved values of the predictor within the HPR; include additional covariates via a partial linear model framework; and allow for monotonicity constraints. We find that HPR performs well when fitting functions that have sharp changes. We apply HPR to model women's basal body temperatures over the course of the menstrual cycle. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Development and validation of the pediatric risk estimate score for children using extracorporeal respiratory support (Ped-RESCUERS)

Author

Barbaro, Ryan P., Boonstra, Philip S., Paden, Matthew L., Roberts, Lloyd A., Annich, Gail M., Bartlett, Robert H., and Moler, Frank W.

Subjects
Pediatrics -- Usage, Mortality -- Usage, Children -- Usage -- Health aspects, Whooping-cough -- Usage, Health care industry, University of Michigan
Abstract

Purpose To develop and validate the Pediatric Risk Estimation Score for Children Using Extracorporeal Respiratory Support (Ped-RESCUERS). Ped-RESCUERS is designed to estimate the in-hospital mortality risk for children prior to receiving respiratory extracorporeal membrane oxygenation (ECMO) support. Methods This study used data from an international registry of patients aged 29 days to less than 18 years who received ECMO support from 2009 to 2014. We divided the registry into development and validation datasets by calendar date. Candidate variables were selected for model inclusion if the variable independently changed the mortality risk by at least 2 % in a Bayesian logistic regression model with in-hospital mortality as the outcome. We characterized the model's ability to discriminate mortality with the area under curve (AUC) of the receiver operating characteristic. Results From 2009 to 2014, 2458 non-neonatal children received ECMO for respiratory support, with a mortality rate of 39.8 %. The development dataset contained 1611 children receiving ECMO support from 2009 to 2012. The model included the following variables: pre-ECMO pH, pre-ECMO arterial partial pressure of carbon dioxide, hours of intubation prior to ECMO support, hours of admission at ECMO center prior to ECMO support, ventilator type, mean airway pressure, pre-ECMO use of milrinone, and a diagnosis of pertussis, asthma, bronchiolitis, or malignancy. The validation dataset included 438 children receiving ECMO support from 2013 to 2014. The Ped-RESCUERS model from the development dataset had an AUC of 0.690, and the validation dataset had an AUC of 0.634. Conclusions Ped-RESCUERS provides a novel measure of pre-ECMO mortality risk. Future studies should seek external validation and improved discrimination of this mortality prediction tool., Author(s): Ryan P. Barbaro [sup.1] [sup.2], Philip S. Boonstra [sup.3], Matthew L. Paden [sup.4], Lloyd A. Roberts [sup.5], Gail M. Annich [sup.6], Robert H. Bartlett [sup.7], Frank W. Moler [sup.2], [...]

Published
2016
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43. sj-pdf-2-ctj-10.1177_1740774520981939 – Supplemental material for A modular framework for early-phase seamless oncology trials

Author

Boonstra, Philip S, Braun, Thomas M, and Chase, Elizabeth C

Subjects
FOS: Clinical medicine, 160807 Sociological Methodology and Research Methods, 111599 Pharmacology and Pharmaceutical Sciences not elsewhere classified, FOS: Sociology
Abstract

Supplemental material, sj-pdf-2-ctj-10.1177_1740774520981939 for A modular framework for early-phase seamless oncology trials by Philip S Boonstra, Thomas M Braun and Elizabeth C Chase in Clinical Trials

Published
2021
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44. sj-pdf-1-ctj-10.1177_1740774520981939 – Supplemental material for A modular framework for early-phase seamless oncology trials

Author

Boonstra, Philip S, Braun, Thomas M, and Chase, Elizabeth C

Subjects
FOS: Clinical medicine, 160807 Sociological Methodology and Research Methods, 111599 Pharmacology and Pharmaceutical Sciences not elsewhere classified, FOS: Sociology
Abstract

Supplemental material, sj-pdf-1-ctj-10.1177_1740774520981939 for A modular framework for early-phase seamless oncology trials by Philip S Boonstra, Thomas M Braun and Elizabeth C Chase in Clinical Trials

Published
2021
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45. Investigating the SPECT Dose-Function Metrics Associated With Radiation-Induced Lung Toxicity Risk in Patients With Non-small Cell Lung Cancer Undergoing Radiation Therapy

Author

Owen, Daniel R., primary, Sun, Yilun, additional, Boonstra, Philip S., additional, McFarlane, Matthew, additional, Viglianti, Benjamin L., additional, Balter, James M., additional, El Naqa, Issam, additional, Schipper, Matthew J., additional, Schonewolf, Caitlin A., additional, Ten Haken, Randall K., additional, Kong, Feng-Ming S., additional, Jolly, Shruti, additional, and Matuszak, Martha M., additional

Published
2021
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46. Serial Molecular Profiling of Low-grade Prostate Cancer to Assess Tumor Upgrading: A Longitudinal Cohort Study

Author

Salami, Simpa S., primary, Tosoian, Jeffrey J., additional, Nallandhighal, Srinivas, additional, Jones, Tonye A., additional, Brockman, Scott, additional, Elkhoury, Fuad F., additional, Bazzi, Selena, additional, Plouffe, Komal R., additional, Siddiqui, Javed, additional, Liu, Chia-Jen, additional, Kunju, Lakshmi P., additional, Morgan, Todd M., additional, Natarajan, Shyam, additional, Boonstra, Philip S., additional, Sumida, Lauren, additional, Tomlins, Scott A., additional, Udager, Aaron M., additional, Sisk, Anthony E., additional, Marks, Leonard S., additional, and Palapattu, Ganesh S., additional

Published
2021
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47. Sentinel Lymph Node Biopsy in Head & Neck Melanoma: Long-Term Outcomes, Prognostic Value, & Accuracy

Author

Hanks, John E., Kovatch, Kevin J., Ali, S. Ahmed, Roberts, Emily, Durham, Alison B., Smith, Joshua D., Bradford, Carol R., Malloy, Kelly M., Boonstra, Philip S., Lao, Christopher D., and Mclean, Scott A.

Subjects
Adult, Aged, 80 and over, Male, Skin Neoplasms, Time Factors, Adolescent, Sentinel Lymph Node Biopsy, Reproducibility of Results, Middle Aged, Prognosis, Article, Cohort Studies, Survival Rate, Young Adult, Treatment Outcome, Head and Neck Neoplasms, Child, Preschool, Humans, Female, Child, Melanoma, Aged, Retrospective Studies
Abstract

OBJECTIVE: To evaluate the long-term outcomes of SLNB for HNCM STUDY DESIGN: Retrospective cohort study SETTING: Tertiary academic medical center SUBJECTS AND METHODS: Longitudinal review of 356 patient cohort with HNCM undergoing SLNB from 1997 to 2007. RESULTS: Descriptive characteristics include mean age 53.5±19 years, 26.8% female, median follow-up 4.9 years, and mean Breslow depth 2.52±1.87mm. 75 (21.1%) patients had a positive SLNB. Among patients undergoing CLND following positive SLNB, 20 (27.4%) had at least one additional positive NSLN(s). 18 patients with local control and negative SLNB developed regional disease, indicating a false omission rate 6.4%, including 10 recurrences in previously unsampled basins. 10-year overall survival (OS) and melanoma specific survival (MSS) were significantly greater in the negative SLN cohort (OS: 61%; Cl: 0.549–0.677; MSS: 81.9%, 95% Cl: 0.769–0.873) than the positive SLN (OS: 31%, Cl 0.162–0.677; MSS: 60.3%, Cl: 0.464–0.785) and positive SLN/positive NSLN (OS: 8.4%, Cl: 0.015–0.474; MSS: 9.6%, Cl: 0.017–0. 536) cohorts. OS was significantly associated with SLN positivity (hazard ratio (HR) 2.39, p

Published
2020

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