ReviewESMO open2026
New prognostic and predictive scoring systems for colorectal cancer liver metastases.
Review in ESMO open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer liver metastases (CRLM) remain a major therapeutic challenge, shaped by marked biological heterogeneity and unpredictable clinical outcomes. While classical Clinical Risk Scores (CRS) continue to inform surgical decision making, their static nature limits their relevance in an era defined by molecular profiling, dynamic biomarkers, and personalized therapy. Advances in genomics and liquid biopsy technologies have expanded the understanding of CRLM beyond traditional clinicopathological parameters, enabling real-time disease monitoring and more refined risk stratification. In parallel, dynamic scoring systems that incorporate evolving clinical and molecular data are redefining how risk is assessed and managed throughout the course of treatment. This review revisits classical CRS, explores emerging molecular and dynamic tools, and discusses their potential integration into clinical practice to improve patient selection, guide treatment timing, and refine the overall management of CRLM.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.