ArticleAnnals of surgical oncology2022
Circulating Lipid- and Inflammation-Based Risk (CLIR) Score: A Promising New Model for Predicting Outcomes in Complete Colorectal Liver Metastases Resection.
Article in Annals of surgical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Blood lipid metabolic biomarkers are emerging as significant prognostic indicators for survival in cancer patients.BMC cancer · 2024Pooled it
- Review
- Inflammation-tumor burden interaction score stratifies survival after irinotecan-eluting bead chemoembolization for colorectal liver metastases.Frontiers in medicine · 2026Article
- A machine learning-based prediction model for colorectal liver metastasis.Clinical and experimental medicine · 2025Article
- Integrative Predictive Nomograms for Treatment Decision-Making in Resectable Synchronous Colorectal Liver Metastases.Journal of Cancer · 2025Article
- Review
- Matrine impedes colorectal cancer proliferation and migration by downregulating endoplasmic reticulum lipid raft associated protein 1 expression.Bioengineered · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundColorectal cancer liver metastasis (CRLM) is a determining factor affecting the survival of colorectal cancer (CRC) patients. This study aims at developing a novel prognostic stratification tool for CRLM resection.
methodsIn this retrospective study, 666 CRC patients who underwent complete CRLM resection from two Chinese medical institutions between 2001 and 2016 were classified into the training (341 patients) and validation (325 patients) cohorts. The primary endpoint was overall survival (OS). Associations between clinicopathological variables, circulating lipid and inflammation biomarkers, and OS were explored. The five most significant prognostic factors were incorporated into the Circulating Lipid- and Inflammation-based Risk (CLIR) score. The predictive ability of the CLIR score and Fong's Clinical Risk Score (CRS) was compared by time-dependent receiver operating characteristic (ROC) analysis.
resultsFive independent predictors associated with worse OS were identified in the training cohort: number of CRLMs >4, maximum diameter of CRLM >4.4 cm, primary lymph node-positive, serum lactate dehydrogenase (LDH) level >250.5 U/L, and serum low-density lipoprotein-cholesterol (LDL-C)/high-density lipoprotein-cholesterol (HDL-C) ratio >2.9. These predictors were included in the CLIR score and each factor was assigned one point. Median OS for the low (score 0-1)-, intermediate (score 2-3)-, and high (score 4-5)-risk groups was 134.0 months, 39.9 months, and 18.7 months in the pooled cohort. The CLIR score outperformed the Fong score with superior discriminatory capacities for OS and RFS, both in the training and validation cohorts.
conclusionsThe CLIR score demonstrated a promising ability to predict the long-term survival of CRC patients after complete hepatic resection.
Identifiers
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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.