Systemic immune-inflammatory index predict short-term outcome in recurrent/metastatic and locally advanced cervical cancer patients treated with PD-1 inhibitor

This study aims to assess the predictive value of certain markers of inflammation in patients with locally advanced or recurrent/metastatic cervical cancer who are undergoing treatment with anti-programmed death 1 (PD-1) therapy. A total of 105 patients with cervical cancer, who received treatment involving immunocheckpoint inhibitors (ICIs), were included in this retrospective study. We collected information on various peripheral blood indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), and prognostic nutritional index (PNI). To determine the appropriate cutoff values for these inflammatory markers, we performed receiver operating characteristic curve (ROC) analysis. Progression-free survival (PFS) was estimated using the Kaplan-Meier method, and we conducted both univariate and multivariate Cox regression analyses to evaluate the prognostic value of these markers. Out of the 105 patients who received ICI treatment, the median progression-free survival (mPFS) was 19.0 months. We obtained the patients' clinical characteristics, such as age, pathological type, therapy regimen, Figo stage, NLR, PLR, LMR, SII, and PNI from their medical records. The optimal cutoff values for NLR, PLR, LMR, SII, and PNI were determined as 3.76, 218.1, 3.34, 1147.7, 43.75, respectively. In the univariate analysis, age, pathological type, therapy regimen, Figo stage, and LMR were not found to be associated with PFS. However, high NLR(P=0.001), high PLR(P<0.001), high SII(P<0.001), and low PNI (P=0.003)were all associated with shorter PFS. Multivariate analysis indicated that SII (P=0.017) was an independent risk factor for PFS. This study highlights the potential use of SII as a predictor of progression-free survival in cervical cancer patients undergoing immunotherapy.

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Journal
Scientific Reports
Published
2024-12-28
DOI
https://doi.org/10.1038/s41598-024-82976-6
Citations
14
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
Field-Weighted Citation Impact
3.96
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article

Systemic immune-inflammatory index predict short-term outcome in recurrent/metastatic and locally advanced cervical cancer patients treated with PD-1 inhibitor

Haohao Wu, Yingying Xu, Zhengcao Liu, Jingjing Li et al.
14 citations
Scientific Reports
Inflammatory Biomarkers in Disease Prognosis
3.96
article

Systemic immune-inflammatory index predict short-term outcome in recurrent/metastatic and locally advanced cervical cancer patients treated with PD-1 inhibitor

Haohao Wu, Yingying Xu, Zhengcao Liu, Jingjing Li, Qingqing Chen, Shengjun Ji, Baoqian Zhai, Runjun Shi, Hui Wang
article en
14 citations

Abstract

This study aims to assess the predictive value of certain markers of inflammation in patients with locally advanced or recurrent/metastatic cervical cancer who are undergoing treatment with anti-programmed death 1 (PD-1) therapy. A total of 105 patients with cervical cancer, who received treatment involving immunocheckpoint inhibitors (ICIs), were included in this retrospective study. We collected information on various peripheral blood indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), and prognostic nutritional index (PNI). To determine the appropriate cutoff values for these inflammatory markers, we performed receiver operating characteristic curve (ROC) analysis. Progression-free survival (PFS) was estimated using the Kaplan-Meier method, and we conducted both univariate and multivariate Cox regression analyses to evaluate the prognostic value of these markers. Out of the 105 patients who received ICI treatment, the median progression-free survival (mPFS) was 19.0 months. We obtained the patients' clinical characteristics, such as age, pathological type, therapy regimen, Figo stage, NLR, PLR, LMR, SII, and PNI from their medical records. The optimal cutoff values for NLR, PLR, LMR, SII, and PNI were determined as 3.76, 218.1, 3.34, 1147.7, 43.75, respectively. In the univariate analysis, age, pathological type, therapy regimen, Figo stage, and LMR were not found to be associated with PFS. However, high NLR(P=0.001), high PLR(P<0.001), high SII(P<0.001), and low PNI (P=0.003)were all associated with shorter PFS. Multivariate analysis indicated that SII (P=0.017) was an independent risk factor for PFS. This study highlights the potential use of SII as a predictor of progression-free survival in cervical cancer patients undergoing immunotherapy.

Scientific ReportsVol. 14(1)
Nantong University (CN), Soochow University (CN), Affiliated Hospital of Nantong University (CN), Suzhou Municipal Hospital (CN), Yancheng First People's Hospital (CN), Second Affiliated Hospital of Soochow University (CN), Yancheng Third People's Hospital (CN), Nanjing Medical University (CN)
Good health and well-being
Openalex Percentile: Top 5%
Inflammatory Biomarkers in Disease Prognosis
3.96
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