Blar i forfatter "Hüsing, Anika"

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    • Adherence to the World Cancer Research Fund/American Institute for Cancer Research cancer prevention recommendations and risk of in situ breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort 

      Karavasiloglou, Nena; Hüsing, Anika; Masala, Giovanna; van Gils, Carla H.; Fortner, Renée Turzanski; Chang-Claude, Jenny; Huybrechts, Inge; Weiderpass, Elisabete; Gunter, Marc; Arveux, Patrick; Fournier, Agnès; Kvaskoff, Marina; Tjønneland, Anne; Kyrø, Cecilie; Dahm, Christina C.; Vistisen, Helene Tilma; Bakker, Marije F.; Sánchez, María-José; Chirlaque López, María Dolores; Santiuste, Carmen; Ardanaz, Eva; Menéndez, Virginia; Agudo, Antonio; Trichopoulou, Antonia; Karakatsani, Anna; La Vecchia, Carlo; Peppa, Eleni; Palli, Domenico; Agnoli, Claudia; Panico, Salvatore; Tumino, Rosario; Sacerdote, Carlotta; Butt, Salma Tunå; Borgquist, Signe; Skeie, Guri; Schulze, Matthias; Key, Timothy; Khaw, Kay-Tee; Tsilidis, Konstantinos K.; Ellingjord-Dale, Merete; Riboli, Elio; Kaaks, Rudolf; Dossus, Laure; Rohrmann, Sabine; Kühn, Tilman (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-12-02)
      <i>Background</i> - Even though in situ breast cancer (BCIS) accounts for a large proportion of the breast cancers diagnosed, few studies have investigated potential risk factors for BCIS. Their results suggest that some established risk factors for invasive breast cancer have a similar impact on BCIS risk, but large population-based studies on lifestyle factors and BCIS risk are lacking. Thus, ...

    • Comparison of prognostic models to predict the occurrence of colorectal cancer in asymptomatic individuals: A systematic literature review and external validation in the EPIC and UK Biobank prospective cohort studies 

      Smith, Todd; Muller, David C.; Moons, Karel G.M.; Cross, Amanda J.; Johansson, Mattias; Ferrari, Pietro; Fagherazzi, Guy; Peeters, Petra H. M.; Severi, Gianluca; Hüsing, Anika; Kaaks, Rudolf; Tjønneland, Anne; Olsen, Anja; Overvad, Kim; Bonet, Catalina; Rodríguez-Barranco, Miguel; Huerta, Jose Maria; Gurrea, Aurelio Barricarte; Bradbury, Kathryn Erica; Trichopoulou, Antonia; Bamia, Christina; Orfanos, Philippos; Palli, Domenico; Pala, Valeria; Vineis, Paolo; Bueno-De-Mesquita, Bas; Ohlsson, Bodil; Harlid, Sophia; Van Guelpen, Bethany; Skeie, Guri; Weiderpass, Elisabete; Jenab, Mazda; Murphy, Neil; Riboli, Eilo; Gunter, Marc J.; Aleksandrova, Krasimira Jekova; Tzoulaki, Ioanna (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-04-03)
      <i>Objective</i> - To systematically identify and validate published colorectal cancer risk prediction models that do not require invasive testing in two large population-based prospective cohorts.<p><p> <i>Design</i> - Models were identified through an update of a published systematic review and validated in the European Prospective Investigation into Cancer and Nutrition (EPIC) and the UK ...

    • Correlates of circulating ovarian cancer early detection markers and their contribution to discrimination of early detection models: results from the EPIC cohort 

      Fortner, Renée T.; Vitonis, Allison F.; Schock, Helena; Hüsing, Anika; Johnson, Theron; Fichorova, Raina Nakove; Fashemi, Titilayo; Yamamoto, Hidemi S.; Tjønneland, Anne; Hansen, Louise; Overvad, Kim; Boutron-Ruault, Marie-Christine; Kvaskoff, Marina; Severi, Gianluca; Boeing, Heiner; Trichopoulou, Antonia; Benetou, Vassiliki; La Vecchia, Carlo; Palli, Domenico; Sieri, Sabina; Tumino, Rosario; Matullo, Giuseppe; Mattiello, Amalia; Onland-Moret, N. Charlotte; Peeters, Petra H.; Weiderpass, Elisabete; Gram, Inger Torhild; Jareid, Mie; Quirós, José Ramón; Duell, Eric J.; Sánchez, Mariá-José; Chirlaque, María-Dolores; Ardanaz, Eva; Larrañaga, Nerea; Nodin, Björn; Brändstedt, Jenny; Idahl, Annika; Khaw, Kay-Tee; Allen, Naomi; Gunter, Marc; Johansson, Mattias; Dossus, Laure; Merritt, Melissa A.; Riboli, Elio; Cramer, Daniel W.; Kaaks, Rudolf; Terry, Kathryn L. (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-03-20)
      Background: Ovarian cancer early detection markers CA125, CA15.3, HE4, and CA72.4 vary between healthy women, limiting their utility for screening. <br>Methods: We evaluated cross-sectional relationships between lifestyle and reproductive factors and these markers among controls ( n = 1910) from a nested case-control study in the European Prospective Investigation into Cancer and Nutrition ...

    • Development and validation of a lifestyle-based model for colorectal cancer risk prediction: the LiFeCRC score 

      Aleksandrova, Krasimira; Reichmann, Robin; Kaaks, Rudolf; Jenab, Mazda; Bueno-de-Mesquita, Hendrik Bastiaan; Dahm, Christina C.; Eriksen, Anne Kirstine; Tjønneland, Anne; Artaud, Fanny; Boutron-Ruault, Marie-Christine; Hüsing, Anika; Trichopoulou, Antonia; Karakatsani, Anna; Peppa, Eleni; Panico, Salvatore; Grioni, Sara; Sacerdote, Carlotta; Tumino, Rosario; Elias, Sjoerd G.; May, Anne M.; Sandanger, Torkjel M; Skeie, Guri; Sánchez, Maria-Jose; Huerta, José María; Sala, Núria; Gurrea, Aurelio Barricarte; Amiano, Pilar; Drake, Isabel; van Guelpen, Bethany; Key, Tim; Weiderpass, Elisabete; Aglago, Elom K.; Cross, Amanda J.; Tsilidis, Konstantinos K.; Riboli, Elio; Gunter, Marc J. (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-01-04)
      <b>Background</b> Nutrition and lifestyle have been long established as risk factors for colorectal cancer (CRC). Modifiable lifestyle behaviours bear potential to minimize long-term CRC risk; however, translation of lifestyle information into individualized CRC risk assessment has not been implemented. Lifestyle-based risk models may aid the identification of high-risk individuals, guide referral ...

    • An epidemiologic risk prediction model for ovarian cancer in Europe: The EPIC study 

      Li, Kuanrong; Hüsing, Anika; Fortner, Renée Turzanski; Tjønneland, Anne; Hansen, Louise Seier; Dossus, Laure; Chang-Claude, Jenny; Bergmann, Manuela M.; Steffen, Annika; Bamia, Christina; Trichopoulos, Dimitrios; Trichopoulou, Antonia; Palli, Domenico; Mattiello, Amalia; Agnoli, Claudia; Tumino, Rosaria; Onland-Moret, N. Charlotte; Peeters, Petra H.; Bueno-de-Mesquita, H. Bas; Gram, Inger Torhild; Weiderpass, Elisabete; Sánchez-Cantalejo, Emilio; Chirlaque, María-Dolores; Duell, Eric J.; Ardanaz, Eva; Idahl, Annika; Lundin, Eva; Khaw, Kay-Tee; Travis, Ruth C.; Merritt, Melissa A.; Gunter, Marc J.; Riboli, Elio; Ferrari, Pietro; Terry, Kathryn L.; Cramer, Daniel William; Kaaks, Rudolf (Journal article; Tidsskriftartikkel; Peer reviewed, 2015-03-05)
      Background: Ovarian cancer has a high case-fatality ratio, largely due to late diagnosis. Epidemiologic risk prediction models could help identify women at increased risk who may benefit from targeted prevention measures, such as screening or chemopreventive agents.<p> <p>Methods: We built an ovarian cancer risk prediction model with epidemiologic risk factors from 202 206 women in the European ...

    • Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts 

      Li, Kuanrong; Anderson, Garnet; Viallon, Vivian; Arveux, Patrick; Kvaskoff, Marina; Fournier, Agnès; Krogh, Vittorio; Tumino, Rosario; Sánchez, María-José; Ardanaz, Eva; Chirlaque, Maria-Dolores; Agudo, Antonio; Muller, David C.; Smith, Todd; Tzoulaki, Ioanna; Key, Timothy J.; Bueno-de-Mesquita, Hendrik Bastiaan; Trichopoulou, Antonia; Bamia, Christina; Orfanos, Philippos; Kaaks, Rudolf; Hüsing, Anika; Fortner, Renée T.; Zeleniuch-Jacquotte, Anne; Sund, Malin; Dahm, Christina C; Overvad, Kim; Aune, Dagfinn; Weiderpass, Elisabete; Romieu, Isabelle; Riboli, Elio; Gunter, Marc J.; Dossus, Laure; Prentice, Ross; Ferrari, Pietro (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-12-03)
      <p><i>Background</i>: Few published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction.</p> <p><i>Methods</i>: We built two models, for ER+ (Model<sub>ER+</sub>) and ER- tumors ...