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Record W4415901190 · doi:10.1016/j.jhepr.2025.101635

Clinical practice and implications of biomarker testing in biliary tract cancer: An observational study

2025· article· en· W4415901190 on OpenAlexaff
Sabrina Welland, A Zöller, Ilektra A. Mavroeidi, Aurelie Tomczak, Christian Müller, Danmei Zhang, Felix Keil, Maria Pangerl, Taotao Zhou, Hossein Taghizadeh, Sebastian Lange, Maximilian N. Kinzler, Kateryna Shmanko, Maryam Barsch, Carolin Zimpel, Angela Djanani, Henning Schulze‐Bergkamen, Julius Keyl, Florian Lüke, Thomas Wirth, Michael T. Dill, Thomas Longerich, Sophia Petschnak, Jens U. Marquardt, Michael Quante, Arndt Weinmann, Dirk Walter, Nicole Pfarr, Gerald W. Prager, Bernhard Doleschal, Maria A. González-Carmona, Rainer Günther, Alexander Scheiter, Stefan Böck, Stephan Bartels, Thomas Gruenberger, Marino Venerito, Christoph Springfeld, Stefan Kasper, Anna Saborowski, Arndt Vogel

Bibliographic record

VenueJHEP Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsPrincess Margaret Cancer CentreToronto General Hospital
FundersCilagHorizon 2020 Framework ProgrammeIpsenServierDeutsche KrebshilfeEisaiLEO PharmaEuropean Cooperation in Science and TechnologyIncyteDeutsche BahnLes Laboratories Pierre FabreEli Lilly and CompanyAstraZenecaCelgeneDaiichi Sankyo EuropeSanofiDeutsche ForschungsgemeinschaftWilhelm Sander-StiftungAmgen
KeywordsObservational studyClinical PracticeClinical trialProfiling (computer programming)Biliary tractPrecision medicineRandomized controlled trialBiomarker

Abstract

fetched live from OpenAlex

Background & Aims Biliary tract cancers (BTC) comprise a group of aggressive malignancies with limited therapeutic options. Owing to the high frequency of actionable genomic alterations (GA) and the availability of targeted therapies, molecular testing has gained increasing importance; however, its implementation in clinical practice varies across centers. The aim of our analysis was to provide a comprehensive real-world assessment of molecular testing, annotate the molecular landscape in BTC patients, and understand the prognostic and predictive implications of selected GA. Methods We retrospectively analyzed genomic and clinical information of 1521 patients treated at 18 centers in Germany and Austria. A side-by-side comparison of clinical grade reports generated on two different sequencing platforms was performed for 90 patients. Results 24 different NGS panels were used across 18 centers. A comparative analysis highlighted the significant variability in reports used to inform therapeutic decisions in clinical practice. Although there were substantial differences in the number of GA covered, the broader panels identified a similar number of actionable GA, indicating that key therapeutic targets are sufficiently represented. Integration with clinical data suggested that certain GA, such as HER2 amplifications (3%) , BRAF V600E mutations (2%), and FGFR2 alterations (14%), may have prognostic significance beyond their predictive value. Patients with actionable alterations (610, 40%) that were treated accordingly (n=204, 13%) had prolonged overall survival (31.8 mo vs 22.8 mo, p<0.01). Conclusion Standardized biomarker testing is crucial for effective integration of targeted therapies in the management of BTC. Our findings reinforce the value of targeted treatments and underscore the predictive and prognostic significance of selected GA. Impact and Implications Genomic profiling is recommended in patients with biliary tract cancers (BTC) but lacks harmonization across platforms and centers. By retrospectively analyzing genomic and clinical information from 1521 BTC patients diagnosed and treated at 18 centers in Germany and Austria, we provide real-world insights into the implementation of molecular profiling in BTC, highlighting variability in NGS-based testing and its impact on the detection of genomic alterations. Standardized molecular testing strategies will be key to enable the integration of more consistent and comparable genomic datasets across studies. Further, by elucidating the prognostic relevance of individual genomic alterations, our insights carry significant implications for interpreting single-arm clinical trials within genomically stratified patient cohorts and underscore the importance of randomized studies to delineate the benefit of targeted therapies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.248
GPT teacher head0.481
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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