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    Home > Active Ingredient News > Antitumor Therapy > Br J Cancer: The prognostic value of preoperative systemic inflammatory response (SIR) measurement in colon cancer patients

    Br J Cancer: The prognostic value of preoperative systemic inflammatory response (SIR) measurement in colon cancer patients

    • Last Update: 2021-03-30
    • Source: Internet
    • Author: User
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    Approximately 1.
    2 million new colon cancer cases and approximately 500,000 deaths are diagnosed globally each year .
    In the UK, TNM stage II and stage III colon cancer each account for approximately 25% of new cases at diagnosis.
    The long-term outcome of the disease is quite different, so predicting the prognosis of patients based on the overall TNM staging is not ideal.

    Approximately 1.
    2 million new colon cancer cases and approximately 500,000 deaths are diagnosed globally each year .
    Approximately 1.
    2 million new colon cancer cases and approximately 500,000 deaths are diagnosed globally each year .
    Diagnosing colon cancer

    Previous studies have shown that preoperative systemic inflammatory response (SIR) enhancement is a new and well-documented prognostic indicator.
    However, so far, this method has not been fully utilized in routine clinical practice.

    Preoperative enhancement of systemic inflammatory response (SIR) is a new and well-documented prognostic indicator.
    Preoperative enhancement of systemic inflammatory response (SIR) is a new and well-documented prognostic indicator.

    Preoperative systemic inflammatory response (SIR) measured based on the acute phase protein score (mGPS) or differential white blood cell count (neutrophil to lymphocyte ratio, NLR) shows the prognostic significance of colon cancer after resection.
    The purpose of this study is to investigate the complementary use of the above two measurement methods in order to better perform a layered analysis of the results.

    Preoperative systemic inflammatory response (SIR) measured based on the acute phase protein score (mGPS) or differential white blood cell count (neutrophil to lymphocyte ratio, NLR) shows the prognostic significance of colon cancer after resection.
    Preoperative systemic inflammatory response (SIR) measured based on the acute phase protein score (mGPS) or differential white blood cell count (neutrophil to lymphocyte ratio, NLR) shows the prognostic significance of colon cancer after resection.

    Screening of cases

    The researchers used univariate/multivariate analysis (UVA/MVA) to analyze the impact of mGPS and NLR measurements on the survival of patients undergoing radical surgery for colon cancer.
    The systemic inflammation grading (SIG) was used to analyze the synergy of these scores in predicting OS/CSS in patients.

    The overall survival rate of patients stratified by Systemic Inflammation Classification (SIG)

    The study included a total of 178 patients with TNM-I-III stage colon cancer.
    The results of MVA analysis showed that both mGPS and NLR are important for the patient's OS.
    The three-year survival rates of mGPS stratification are 83–58% (TNM-I–III), 87–65% (TNM-II), and 75–49% (TNM-III), while NLR is 84– 62% (TNM-I-III), 88-69% (TNM-II) and 77-49% (TNM-III).
    When the combined SIG classification of mGPS and NLR is 0/1/2/3/4, the patient's 3-year OS is 88%/84%/76%/65%/60%, and CSS is 93%/90% /82%/73%/70%.
    The SIG classification revealed that the OS of TNM stage II/III disease was 93–68%/82–48%, and the CSS was 97–80%/86–58%.


    In summary, the results of the study show that for patients with colon cancer undergoing radical surgery, the SIG score combined with mGPS and NLR before surgery can better determine the patient's SIR response.


    For colon cancer patients undergoing radical surgery, the SIG score combined with mGPS and NLR before surgery can better determine the patient's SIR response.


    For colon cancer patients undergoing radical surgery, the SIG score combined with mGPS and NLR before surgery can better determine the patient's SIR response.



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