A network calculator based on lymphocyte ratio-associated immune-inflammatory response score predicts survival in patients with hepatocellular carcinoma
Shi Limin, Zhang Mingxing, Cai Siqi, Yang Yueyi, Yang Chunyi, Zhang Wenqiong
2024, 11(4):
19-26.
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Objective: To develop a lymphocyte ratio-associated immune-inflammatory response score (IRS) and construct a network calculator to predict prognostic risk in patients with hepatocellular carcinoma (HCC).
Method: HCC patients who were surgically treated in Shanghai Public Health Clinical Center between January 2018 and December 2023 were selected. Neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte to lymphocyte ratio (MLR) and C-reactive protein to lymphocyte ratio (CLR) were collected. IRS was constructed using multifactorial Cox risk regression. Univariate and multifactorial Cox regression models were used to analyse risk factors for mortality in HCC patients. Constructed and assessed nomogram prediction accuracy using R packages such as rms, foreign, readxl, Hmisc and rmda. Development of a mortality risk network calculator for HCC patients using the DynNom package.
Result: 154 patients were followed up from 1 month to 60 months, with a median follow-up of 17 months, in which the 1-, 3- and 5-year mortality rates were 30.5%, 50.6% and 61.0%, respectively. IRS=0.213 × NLR+0.005×PLR+0.042×CLR was constructed based on the multifactorial Cox risk regression coefficient β. IRS was significantly higher in patients who died than in those who survived (P<0.05). Patients in the high-risk group (IRS≥2.88) had significantly lower survival than patients in the low-risk group (IRS<2.88) (P<0.05). Time- receiver operating characteristic (ROC) curves showed areas under the curve (AUCs) of 0.829 (95% confidence interval [95%CI]: 0.760-0.885), 0.901 (95%CI: 0.842-0.943), and 0.898 (95%CI: 0.839-0.941) for 1-year, 3-year, and 5-year risk of death among patients with IRS prediction, respectively. The results of multifactorial Cox risk regression analysis showed that maximum tumour diameter, γ-glutamyl transferase (GGT), alkaline phosphatase (ALP), alpha-fetoprotein (AFP) and IRS were independent factors for the risk of death in HCC patients (P<0.05). Nomogram were constructed based on IRS to predict the risk of death in HCC patients at 1, 3 and 5 years. The calibration curves showed that the C-index of the nomogram predicting the risk of death at 1, 3 and 5 years was 0.836 (95%CI: 0.818-0.912), 0.903 (95%CI: 0.882-0.961) and 0.847 (95%CI: 0.817-0.932), respectively, respectively, and time-decision curve analysis (DCA) revealed that the nomogram provided a significant meaningful clinical net benefit for risk thresholds in the range of 0-1. The web calculator interface is available at https://nomogramdynamic.shinyapps.io/DynNomapp/.
Conclusion: The risk of death in HCC patients can be effectively predicted by evaluating and localising the IRS. The network calculator of the risk of death in HCC patients constructed by the IRS combined with the maximum diameter of the tumour, GGT, ALP, and AFP can provide a more positive basis for the treatment of patients with a poorer prognosis.
