Research progresses of nomogram in predicting lymph node metastasis of colorectal cancer

DENG Longlian; SUN Haibin; Enri-Letu; WANG Tengqi

doi:10.7619/jcmp.20223328

Journal of Clinical Medicine in Practice > 2023 > 27(5): 143-148. > DOI: 10.7619/jcmp.20223328

DENG Longlian, SUN Haibin, Enri-Letu, WANG Tengqi. Research progresses of nomogram in predicting lymph node metastasis of colorectal cancer[J]. Journal of Clinical Medicine in Practice, 2023, 27(5): 143-148. DOI: 10.7619/jcmp.20223328

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Research progresses of nomogram in predicting lymph node metastasis of colorectal cancer

DENG Longlian^{1, 2},
SUN Haibin²,
Enri-Letu²,
WANG Tengqi^{1, 2, ,}

1.
Graduate School of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010110
2.
Department of Gastrointestinal Surgery, Bayannur Hospital of Inner Mongolia Autonomous Region, Bayannur, Inner Mongolia, 015000

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Received Date: November 07, 2022
Revised Date: November 08, 2022
Available Online: April 06, 2023

Graphical Abstract

Abstract

Abstract

Lymph node metastasis (LNM) affects the choice of treatment and prognosis of patients with colorectal cancer (CRC), and how to predict lymph node status more accurately is a major challenge in the field of CRC. As a visual prediction model, nomogram has been widely studied in the field of lymph node metastasis of colorectal cancer (CRC-LNM) prediction in recent years. Nomogram based on clinical features, radiology, genomic or transcriptomic features is significantly better than traditional TNM staging in identifying LNM preoperatively, which provides a basis for healthcare professionals to more accurately identify LNM high-risk groups and develop personalized treatment strategies. Non-invasive blood tests can obtain non-invasive, convenient, and inexpensive preoperative acquisition of circulating tumor biomarkers, and the construction of nomograms and prediction of LNM is promising. The interdisciplinary study combining clinical, radiology, and circulating markers can help further improve the predictive performance of nomograms and deserves further investigation.
- probabilistic prediction model,
- nomogram,
- colorectal cancer,
- lymph node metastasis,
- radiomics,
- genomics,
- transcriptomics

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References (36)

References

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