← Back to cohort
Cholangiocarcinoma 2026: status quo, unmet needs and priorities
Jesús M. Bañales, Pedro M. Rodrigues, Silvia Affò, Jesper B. Andersen, Patricia Aspichueta, Luke Boulter, John Bridgewater, Diego F. Calvisi, Andrés Cárdenas, Vincenzo Cardinale, Guido Carpino, Cédric Coulouarn, Cristina Dopazo, Julien Edeline, Luca Fabris, Trine Folseraas, Alejandro Forner, Benjamin Goeppert, Mathias Heikenwälder, Timothy J. Kendall, Shahid A. Khan, Heinz‐Josef Klümpen, Bas Groot Koerkamp, Angela Lamarca, Stacie Lindsey, Ana Lleò, Tom Luedde, Rocı́o I.R. Macı́as, Helen Morement, Jean‐Charles Nault, Paula Olaizola, María J. Perugorria, Chiara Raggi, Lorenza Rimassa, Anna Saborowski, Juan W. Valle, Mathew Vithayathil, Arndt Vogel, Chiara Braconi, Abel Sanchez, Aldo J. Montaño‐Loza, Alessandra Elvevi, Alessandro Parisi, Alexander Link, Ana Landa-Magdalena, Anthony Turpin, Anu Ustav, Apinya Jusakul, Arun Valsan, Benjamin J. Dwyer, Bogdan Silviu Ungureanu, Bruno Sangro, Christoph Schramm, Cindy Neuzillet, Constantino Fondevila, David J. Pinato, David Malka, Elisa Lozano, Emmanuel Boleslawski, Enrique Carrera Estupiñán, Ernesto Sparrelid, Eugenio Gaudio, Fatima Higuera‐de la Tijera, Flavio G. Rocha, Florence Troisfontaine, Frank Lammert, Gianpaolo Vidili, Gonzalo Sapisochin, Gregory B. Lesinski, Gregory J. Gores, Hannes Jansson, Hassan Malik, Jan Philipp Jonas, Javier Díaz Ferrer, Javier Vaquero, Jens U. Marquardt, Joana Espírito Santo, Jorge Adeva, Joris I. Erdmann, José J.G. Marı́n, Juan Carlos Roa, Juli Busquets, Juozas Kupčinskas, Krzysztof Zieniewicz, Lara R. Heij, Laura W. Goff, Laura Izquierdo‐Sánchez, Leonardo Gomes da Fonseca, Luca Maroni, Luís Bujanda, Mairéad G. McNamara, Marco Carbone, Marco Marzioni, Marco Rengo, Mariano Ponz‐Sarvisé, Mario Strazzabosco, Markus Peck‐Radosavljevic, Massimiliano Cadamuro, Massimiliano Salati, Massimo Colombo, Matei Mandea, Matías A. Ávila, Matthias Evert, Mina Komuta, Mitesh J. Borad, Mohamed Bouattour, Mohamed El‐Kassas, Mónica Isabel Meneses Medina, Monica Niger, Monique M.A. Verstegen, Nabeel Bardeesy, Nilofer S. Azad, Olivier Detry, Olivier Scatton, Martín Padilla, Pilar Acedo, Pim B. Olthof, Piotr Milkiewicz, Rachel V. Guest, Rachna T. Shroff, Robert Montal, Robin Kate Kelley, Ruidong Xue, Sergio A. Gradilone, Shishir K. Maithel, Silvestre Vicent, Siwanon Jirawatnotai, Stefano Caruso, Stéphanie Roessler, Stephen L. Chan, Stephen P. Pereira, Teresa Macarulla, Thomas Gruenberger, Tian V. Tian, Tim F. Greten, Tudor Mocan, Tushar Patel, Umair Mahmood, Umberto Cillo, V. Megdanova, Víctor López‐López
Bibliographic record
VenueNature Reviews Gastroenterology & Hepatology · 2025
Typereview
Languageen
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer CentreUniversity of AlbertaToronto General Hospital
FundersNational Cancer InstituteBerrikuntza + Ikerketa + Osasuna Eusko FundazioaAgencia Estatal de InvestigaciónInstituto de Salud Carlos IIISociedad Española de Oncología MédicaIkerbasque, Basque Foundation for ScienceInstitut National Du CancerDeutsche KrebshilfeMinisterio de Economía y CompetitividadMinistero della SaluteFundación Científica Asociación Española Contra el CáncerPSC Partners Seeking a CureDeutsche ForschungsgemeinschaftAssociazione Italiana per la Ricerca sul CancroMinisterio de Ciencia, Innovación y UniversidadesEuropean Regional Development FundEuropean Commission
KeywordsDelphi methodMEDLINEConsensus conferenceRisk assessmentCancerIncidence (geometry)DelphiGlobal health
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.025
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.025
GPT teacher head0.352
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations35
Published2025
Admission routes1
Has abstractno