Real-world survival of colon cancer after radical surgery: A single-institutional retrospective analysis

Pang, Xiangyi; Xu, Benjie; Lian, Jie; Ren, Wei; Wang, Xin; Shao, Jiayue; Tang, Shuli; Lu, Haibo

doi:10.3389/fonc.2022.914076

Cited by 13 publications

(5 citation statements)

References 32 publications

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“…Pang et al [ 29 ] showed that column-line diagrams performed better in risk stratification of prognosis for patients undergoing radical colon cancer surgery. Therefore, in the present study, we further constructed a column-line diagram prediction model of the occurrence of liver metastasis after radical resection of colon cancer by SII, CAR, and RDW.…”

Section: Discussionmentioning

confidence: 99%

Prognostic value of a nomogram model for postoperative liver metastasis of colon cancer

Cheng,

Xu,

Liu

et al. 2024

World J Gastrointest Surg

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BACKGROUND Colon cancer is one of the most common malignant tumors of the digestive system. Liver metastasis after colon cancer surgery is the primary cause of death in patients with colon cancer. AIM To construct a novel nomogram model including various factors to predict liver metastasis after colon cancer surgery. METHODS We retrospectively analyzed 242 patients with colon cancer who were admitted and underwent radical resection for colon cancer in Zhejiang Provincial People’s Hospital from December 2019 to December 2022. Patients were divided into liver metastasis and non-liver metastasis groups. Sex, age, and other general and clinicopathological data (preoperative blood routine and biochemical test indexes) were compared. The risk factors for liver metastasis were analyzed using single-factor and multifactorial logistic regression. A predictive model was then constructed and evaluated for efficacy. RESULTS Systemic inflammatory index (SII), C-reactive protein/albumin ratio (CAR), red blood cell distribution width (RDW), alanine aminotransferase, preoperative carcinoembryonic antigen level, and lymphatic metastasis were different between groups (P < 0.05). SII, CAR, and RDW were risk factors for liver metastasis after colon cancer surgery (P < 0.05). The area under the curve was 0.93 for the column-line diagram prediction model constructed based on these risk factors to distinguish whether liver metastasis occurred postoperatively. The actual curve of the column-line diagram predicting the risk of postoperative liver metastasis was close to the ideal curve, with good agreement. The prediction model curves in the decision curve analysis showed higher net benefits for a larger threshold range than those in extreme cases, indicating that the model is safer. CONCLUSION Liver metastases after colorectal cancer surgery could be well predicted by a nomogram based on the SII, CAR, and RDW.

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Section: Discussionmentioning

confidence: 99%

Prognostic value of a nomogram model for postoperative liver metastasis of colon cancer

Cheng,

Xu,

Liu

et al. 2024

World J Gastrointest Surg

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“…Systemic therapy is the primary treatment for advanced colon cancers. Unfortunately, the five-year overall survival (OS) is currently estimated at only 30% (2). Immunotherapy significantly prolonged the survival of patients with deficiency of mismatch repair (dMMR) or microsatellite instabilityhigh (MSI -H) (3)(4)(5).…”

Section: Introductionmentioning

confidence: 99%

Identification of colon cancer subtypes based on multi-omics data—construction of methylation markers for immunotherapy

Xu,

Lian,

Pang

et al. 2024

Front. Oncol.

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BackgroundBeing the most widely used biomarker for immunotherapy, the microsatellite status has limitations in identifying all patients who benefit in clinical practice. It is essential to identify additional biomarkers to guide immunotherapy. Aberrant DNA methylation is consistently associated with changes in the anti-tumor immune response, which can promote tumor progression. This study aims to explore immunotherapy biomarkers for colon cancers from the perspective of DNA methylation.MethodsThe related data (RNA sequencing data and DNA methylation data) were obtained from The Cancer Genome Atlas (TCGA) and UCSC XENA database. Methylation-driven genes (MDGs) were identified through the Pearson correlation analysis. Unsupervised consensus clustering was conducted using these MDGs to identify distinct clusters of colon cancers. Subsequently, we evaluated the immune status and predicted the efficacy of immunotherapy by tumor immune dysfunction and exclusion (Tide) score. Finally, The Quantitative Differentially Methylated Regions (QDMR) software was used to identify the specific DNA methylation markers within particular clusters.ResultsA total of 282 MDGs were identified by integrating the DNA methylation and RNA-seq data. Consensus clustering using the K-means algorithm revealed that the optimal number of clusters was 4. It was revealed that the composition of the tumor immune microenvironment (TIME) in Cluster 1 was significantly different from others, and it exhibited a higher level of tumor mutation burdens (TMB) and stronger anti-tumor immune activity. Furthermore, we identified three specific hypermethylation genes that defined Cluster 1 (PCDH20, APCDD1, COCH). Receiver operating characteristic (ROC) curves demonstrated that these specific markers could effectively distinguish Cluster 1 from other clusters, with an AUC of 0.947 (95% CI 0.903-0.990). Finally, we selected clinical samples for immunohistochemical validation.ConclusionIn conclusion, through the analysis of DNA methylation, consensus clustering of colon cancer could effectively identify the cluster that benefit from immunotherapy along with specific methylation biomarkers.

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“…Many social factors will affect the survival of colorectal cancer patients, and the disease itself, such as stage, differentiation, pathological type, tumor site, inflammatory factor, age and gender, will also affect survival (7). The 5-year survival rate of patients with stage I colon cancer was as high as 96.6%, while the 5-year survival rate of patients with stage IV colon cancer was only 34.3% (8). Research has reported that younger patients have a worse prognosis than older patients (9).…”

Section: Introductionmentioning

confidence: 99%

Survival rate of colorectal cancer in China: A systematic review and meta-analysis

et al. 2023

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BackgroundThis study aims to comprehensively summarize the colorectal survival rate in China. Method: In PubMed and Web of Science, keywords such as “colorectal cancer”, “survival” and “China” were used to search literatures in the past 10 years. Random effect models were selected to summarize 1-year, 3-year, and 5-year survival rates, and meta-regression and subgroup analyses were performed on the included studies.ResultsA total of 16 retrospective and prospective studies providing survival rates for colorectal cancer in China were included. The 1-year, 3-year, and 5-year survival rates of colorectal cancer in China were 0.79, 0.72 and 0.62, respectively. In the included studies, the 5-year survival rates of stage I (5474 cases), stage II (9215 cases), stage III (8048 cases), and stage IV (4199 cases) colorectal cancer patients were 0.85, 0.81, 0.57 and 0.30, respectively. Among them, the 5-year survival rates of colorectal cancer were 0.82, 0.76, 0.71, 0.67, 0.66, 0.65 and 0.63 in Tianjin, Beijing, Guangdong, Shandong, Liaoning, Zhejiang and Shanghai, respectively.ConclusionThe 5-year survival rate in China is close to that of most European countries, but still lower than Japan and South Korea, and the gap is gradually narrowing. Region, stage, differentiation, pathological type, and surgical approach can affect 5-year survival in colorectal cancer.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/ identifier, CRD42022357789.

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Real-world survival of colon cancer after radical surgery: A single-institutional retrospective analysis

Cited by 13 publications

References 32 publications

Prognostic value of a nomogram model for postoperative liver metastasis of colon cancer

Prognostic value of a nomogram model for postoperative liver metastasis of colon cancer

Identification of colon cancer subtypes based on multi-omics data—construction of methylation markers for immunotherapy

Survival rate of colorectal cancer in China: A systematic review and meta-analysis

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