Distant Metastasis Pattern and Prognostic Prediction Model of Colorectal Cancer Patients Based on Big Data Mining.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35530362", "kind": "science-record", "revision": 4, "content_hash": "sha256:bca18092c6f75aae4b6f44931a1a34afd37f2bbae571ca5746d4f284dc66451b", "created_at": "2026-11-01T18:14:25Z", "updated_at": "2026-11-01T22:06:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Distant Metastasis Pattern and Prognostic Prediction Model of Colorectal Cancer Patients Based on Big Data Mining.", "doi": "10.3389/fonc.2022.878805", "pmid": "35530362", "authors": ["Chuan Liu", "Ting Wang", "Jiahui Yang", "Jixiang Zhang", "Shuchun Wei", "Yingyun Guo", "Rong Yu", "Zongbiao Tan", "Shuo Wang", "Weiguo Dong"], "journal": "Frontiers in oncology", "year": 2022, "abstract": "Aims: This study aimed to investigate the distant metastasis pattern from newly diagnosed colorectal cancer (CRC) and also construct and validate a prognostic nomogram to predict both overall survival (OS) and cancer-specific survival (CSS) of CRC patients with distant metastases.\nMethods: Primary CRC patients who were initially diagnosed from 2010 to 2016 in the SEER database were included in the analysis. The independent risk factors affecting the OS, CSS, all-cause mortality, and CRC-specific mortality of the patients were screened by the Cox regression and Fine-Gray competitive risk model. The nomogram models were constructed to predict the OS and CSS of the patients. The reliability and accuracy of the prediction model were evaluated by consistency index (C-index) and calibration curve. The gene chip GSE41258 was downloaded from the GEO database, and differentially expressed genes (DEGs) were screened by the GEO2R online tool (p < 0.05, |logFC|>1.5). The Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway and Gene Ontology (GO) annotation and String website were used for enrichment analysis and protein-protein interaction (PPI) analysis of DEGs, respectively, and Cytoscape software was used to construct PPI network and screen function modules and hub genes.\nResults: A total of 57,835 CRC patients, including 47,823 without distant metastases and 10,012 (17.31%) with metastases, were identified. Older age, unmarried status, poorly differentiated or undifferentiated grade, right colon site, larger tumor size, N2 stage, more metastatic sites, and elevated carcinoembryonic antigen (CEA) might lead to poorer prognosis (all p < 0.01). The independent risk factors of OS and CSS were included to construct a prognosis prediction model for predicting OS and CSS in CRC patients with distant metastasis. C-index and calibration curve of the training group and validation group showed that the models had acceptable predictive performance and high calibration degree. Furthermore, by comparing CRC tissues with and without liver metastasis, 158 DEGs and top 10 hub genes were screened. Hub genes were mainly concentrated in liver function and coagulation function.\nConclusion: The big data in the public database were counted and transformed into a prognostic evaluation tool that could be applied to the clinic, which has certain clinical significance for the formulation of the treatment plan and prognostic evaluation of CRC patients with distant metastasis.", "claims": [{"id": "claim-method", "statement": "The multivariable Cox regression was obtained to identify covariates associated with increased all-cause mortality (ACM) using the significant factors (p < 0.05) in the univariate Cox regression model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35530362", "locator": "sections[4] \"2.2 Statistical Analysis\" paragraph 2", "quote": "The multivariable Cox regression was obtained to identify covariates associated with increased all-cause mortality (ACM) using the significant factors (p < 0.05) in the univariate Cox regression model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. These data were derived from the following resources available in the public domain: Surveillance, Epidemiology, and End Results (SEER) (http://seer.cancer.gov/) and Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35530362", "locator": "sections[20] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. These data were derived from the following resources available in the public domain: Surveillance, Epidemiology, and End Results (SEER) (http://seer.cancer.gov/) and Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Among 57,835 CRC patients, 10,012 (17.31%) had distant metastasis, and prognostic nomograms for OS and CSS were constructed and validated, while 158 DEGs and 10 hub genes were identified.", "kind": "quantitative", "target": {"value": 17.31, "unit": "per cent", "tolerance": null, "source": "A total of 57,835 CRC patients, including 47,823 without distant metastases and 10,012 (17.31%) with metastases, were identified."}, "evidence": [{"asset": "source:pmid:35530362", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 57,835 CRC patients, including 47,823 without distant metastases and 10,012 (17.31%) with metastases, were identified."}, {"asset": "source:pmid:35530362", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The independent risk factors of OS and CSS were included to construct a prognosis prediction model for predicting OS and CSS in CRC patients with distant metastasis."}, {"asset": "source:pmid:35530362", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Furthermore, by comparing CRC tissues with and without liver metastasis, 158 DEGs and top 10 hub genes were screened."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Among 57,835 CRC patients, 10,012 (17.31%) had distant metastasis, and prognostic nomograms for OS and CSS were constructed and validated, while 158 DEGs and 10 hub genes were identified.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35530362"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE41258"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE41258"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35530362", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2022.878805", "sha256": "sha256:3a21f0c8099f81893075477305ed24fca55c171df1a63b3d5d2bda5f9db72922", "bytes": 40730, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2022.878805", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9074728", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE41258", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE41258", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE41258", "version": null, "note": "Publicly available datasets were analyzed in this study. These data were derived from the following resources available in the public domain: Surveillance, Epidemiology, and End Results (SEER) (http://seer.cancer.gov/) and Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. 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