Citations 2
Advancing Prostate Cancer Survivorship Through Transatlantic Consortium Science: The iCCaRE Initiative
Odedina, Folakemi T. , Dronca, Roxana , Ashing, Kimlin , Kaninjing, Ernest , Rotimi, Solomon O. , Ngufor, Che , Merriweather, Arnold , Gordon, Vinessa , Asto-Flores, Emelina , Adeniji, Kayode, Agboola, Emmanuel, Aliche, Uju, Aliyu, Usman M., Ashing, Kimlin Tam, Asiedu, Gladys, Badejo, Paul, Johnson, Kim Barbel, Beckford, Patrick , Blocker, Renaldo, Bolajoko, Opeyemi, Bonner, Timethia J, Breland, Ivey, Caballero, Amanda , Carter, Rickey, Cattnell, Alex, COBRAN, Ewan, Colon-Otero, Gerardo, Copland, John A., Phd, Getachew Dagne, Campos, Opeyemi C. De, Doty, Melissa, Dronca, Roxana, Erefah, Ebenezer, Falzon, Kaila, Francis, Damian, Fudge, Michelle, Fullwood, Dottington , Gainer, Jeffery, Glaser-Boivin, Dee, Hill, Antony, Hinsom, Rakenya, Iweala, Emeka J., Kaninjing, Ernie, Kase, Adam, Knutsen, Keith, Lee, Daniel, Leyva, Sandra Casanova, Lindeman, Carolyn R., Mahin, Collisa, Maniaci, Michael, Hew, Trevanne Matthews, Hew, Trevanne R. Matthews, Melton, Jada K., Merriweather, Arnold, Mitchell, Luisa, Moore, Cassandra, Ngufor, Che, Nolan, Lucia, Odedina, Abimbola, Odedina, Folakemi, Oladoyinbo, Catherine, Olasehinde, Esther, Onyia, Abimbola F., Popoola, Ademoola, Rotimi, Solomon O., Scales, Tracie, Sledge, Hanna, Thompson-Reeves, Jade, Toye, Oluwaseyi, Duarte, Claudia Valles, Voorhis, Kaitlin Van, Waldon, Charles F., Walsh-Childers, Kim , Williams, Christopher, Willis, Floyd , Wimberly, Quincy , Yahaya, Ayinde, Yates, PhD Clayton, Yost, Kathleen, Young, Mary Ellen , Zou, Tingyu, Ashing, Kimlin Tam , Rotimi, Solomon , Odedina, Folakemi , Kaninjing, Ernest T , Ngufor, Che G , Aliche, Uju, Badejo, Paul, Blocker, Renaldo, Bolajoko, Opeyemi , Cattnell, Alex, Cobran, Ewan K. , Colon-Otero, Gerardo, Copland, John A., Francis, Damian, Fudge, Michelle , Gainer, Jeffery, Gokara, Mahesh , Hinsom, Rakenya, Iweala, Emeka J., Knutsen, Keith, Lee, Daniel, Lindeman, Carolyn R., McCall, John , Melton, Jada K., Mitchell, Luisa, Olasehinde, Esther, Popoola, Ademoola, Reynolds, Jordan , Scales, Tracie, Sledge, Hanna, Thompson-Reeves, Jade, Toye, Oluwaseyi, Duarte, Claudia Valles, Voorhis, Kaitlin Van, Waldon, Charles F., Williams, Christopher, Yost, Kathleen, Zou, Tingyu
Cancer Research Communications | July 24, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available
Abstract Black/African American populations, globally, bear the greatest prostate cancer (CaP) burden compared to other racial/ethnic groups. Addressing CaP disparities in Black men is complex, requiring a patient-centered, community-centric and comprehensive approach. This study integrates iCCaRE Consortium findings and broader literature to address unmet needs in survivorship care. The iCCaRE Consortium implemented five complementary pilot studies using mixed-methods designs, including feasibility trials, qualitative research, and observational analyses across the United States and sub-Saharan Africa. Descriptive statistics, subgroup analyses, and qualitative thematic analyses were performed across these studies. Collectively, projects addressed multilevel determinants including social, behavioral, and biological drivers of disparities. Project 1 implemented a Virtual Reality Assistant (ViRA) across clinical and community settings, with ongoing evaluation in pragmatic trials. Project 2 showed strong patient preference for home-based cancer care. Project 3 enrolled demonstrated trends toward improved health-related quality of life. Project 4 identified key themes influencing survivorship experiences. Project 5 identified biological mechanisms linking stress, immune modulation, and symptom burden. The iCCaRE pilot projects demonstrate the feasibility and early impact of a consortium-based, transdisciplinary approach to addressing CaP disparities in Black men. These findings highlight the importance of integrating patient-centered interventions, community engagement, and biological insights to inform scalable strategies aimed at improving survivorship outcomes and advancing health equity. The iCCaRE Consortium demonstrates that a transatlantic, patient-centered, and multidisciplinary approach integrating social, clinical, and biological factors can generate scalable strategies to improve survivorship outcomes and advance equity in CaP care for Black men.
Clinical Phenotyping with an Outcomes-driven Mixture of Experts for Patient Matching and Risk Estimation
Hurley, Nathan C. , Dhruva, Sanket S. , Desai, Nihar R. , Ross, Joseph S. , Ngufor, Che , Masoudi, Frederick A. , Krumholz, Harlan M. , Mortazavi, Bobak J. , Ross, Joseph S , Ngufor, Che G , Masoudi, Frederick , Krumholz, Harlan M. , Mortazavi, Bobak J
ACM Transactions on Computing for Healthcare | August 18, 2023 | Volume: 4 | Issue: 4 | Pages: 1-18
Observational medical data present unique opportunities for analysis of medical outcomes and treatment decision making. However, because these datasets do not contain the strict pairing of randomized control trials, matching techniques are to draw comparisons among patients. A key limitation to such techniques is verification that the variables used to model treatment decision making are also relevant in identifying the risk of major adverse events. This article explores a deep mixture of experts approach to jointly learn how to match patients and model the risk of major adverse events in patients. Although trained with information regarding treatment and outcomes, after training, the proposed model is decomposable into a network that clusters patients into phenotypes from information available before treatment. This model is validated on a dataset of patients with acute myocardial infarction complicated by cardiogenic shock. The mixture of experts approach can predict the outcome of mortality with an area under the receiver operating characteristic curve of 0.85 ± 0.01 while jointly discovering five potential phenotypes of interest. The technique and interpretation allow for identifying clinically relevant phenotypes that may be used both for outcomes modeling as well as potentially evaluating individualized treatment effects.