Browsing by Author "Mancebo Moreno, Gemma"

Sort by: Order: Results:

  • Devis, Laura; Martínez-García, Elena; Moiola, Cristian P.; Quiles, Maria Teresa; Arbós, Maria Antonia; Stirbat, Tomita Vasilica; Brochard-Wyart, Françoise; García, Ángel; Alonso-Alconada, Lorena; Abal, Miguel; Díaz-Feijoo, Berta; Thomas, William; Dufour, Sylvie; Mancebo Moreno, Gemma; Alameda Quitllet, Francisco; Reventós, Jaume; Gil-Moreno, Antonio; Colas, Eva (Impact Journal, 2018)
    Endometrial cancer (EC) is the sixth deadliest cancer in women. The depth of myometrial invasion is one of the most important prognostic factors, being directly associated with tumor recurrence and mortality. In this study, ...
  • Mancebo Moreno, Gemma; Solé-Sedeño, Josep Maria; Membrive, Ismael; Taus García, Álvaro; Castells Zaragoza, Marta; Serrano, Laia; Carreras Collado, Ramón; Miralpeix, E. (BMJ Publishing Group, 2021)
    The SARS-CoV-2 (COVID-19) pandemic has significantly impacted the management of patients with gynecologic cancers. Many centers have reduced access to routine visits to avoid crowded waiting areas and specially to reduce ...
  • Miralpeix, Ester; Solé-Sedeño, Josep Maria; Rodriguez-Cosmen, Cristina; Taus García, Álvaro; Muns, Maria Dolors; Fabregó, Berta; Mancebo Moreno, Gemma (BioMed Central, 2022)
    Background: Cytoreductive surgery followed by systemic chemotherapy is the standard of treatment in advanced ovarian cancer where feasible. Neoadjuvant chemotherapy (NACT) followed by surgery is applicable where upfront ...
  • van der Putten, Louis J.M.; Mancebo Moreno, Gemma; Alameda Quitllet, Francisco; Pijnenborg, Johanna M.A. (Nature Publishing Group, 2016)
    BACKGROUND: Identification of aggressive endometrioid endometrial carcinomas (EECs) and non-endometrioid carcinomas (NEECs) is essential to improve outcome. L1 cell adhesion molecule (L1CAM) expression is a strong prognostic ...
  • Reijnen, Casper; Mancebo Moreno, Gemma; Pijnenborg, Johanna M.A. (Public Library of Science (PLoS), 2020)
    Background: Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical ...
  • Mancebo Moreno, Gemma; Solé-Sedeño, Josep Maria; Pino, O.; Miralpeix, E.; Mojal, Sergio; Garrigos, L.; Lloveras Rubio, Belen; Navarro Medrano, Pilar; Gibert, Joan; Lorenzo Perez, Marta; Aran, Iris; Carreras Collado, Ramón; Alameda Quitllet, Francisco (Nature Publishing Group, 2017)
    To assess the impact of CD133 expression on the prognosis of endometrioid endometrial carcinoma (EEC). We retrospectively assessed CD133 expression in tissue microarray of 116 surgically treated FIGO I-III EEC. Tumors with ...
  • Vrede, Stephanie W.; Hulsman, Anneloes M.C.; Reijnen, Casper; van de Vijver, Koen K.B.T.; Colas, Eva; Mancebo Moreno, Gemma; Moiola, Cristian Pablo; Gil-Moreno, Antonio; Huvila, Jutta; Koskas, Martin; Weinberger, Vit; Minář, Luboš; Jandáková, Eva; Santacana, Maria; Matias-Guiu, Xavier; Amant, Frédéric; Snijders, Marc P.L.M.; Küsters-Vandevelde, Heidi V.N.; ENITEC-Consortium; Bulten, Johan Hans; Pijnenborg, Johanna M.A. (Elsevier, 2022)
    Objective: To evaluate whether the amount of preoperative endometrial tissue surface is related to the degree of concordance with final low- and high-grade endometrial cancer (EC). In addition, to determine whether discordance ...
  • van Weelden, Willem Jan; Mancebo Moreno, Gemma; Amant, Frédéric; ENITEC-Consortium (Elsevier, 2021)
    There is no consensus on the cutoff for positivity of estrogen receptor (ER) and progesterone receptor (PR) in endometrial cancer (EC). Therefore, we determined the cutoff value for ER and PR expression with the strongest ...