Preoperative systemic immune-inflammation index predicts prognosis and guides clinical treatment in patients with non-small cell lung cancer

Xue, Yan; Li, Guowei

doi:10.1042/bsr20200352

Cited by 21 publications

(20 citation statements)

References 27 publications

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“…Meanwhile, LMR and PLR at post-treatment in the third period seemed to have a more balanced prediction probability for ESCC patients who had responded or no response; thus, there was a more ideal prediction probability in combining LMR with PLR at post-treatment in the third period. Prior studies reported that SII at baseline might predict pCR status for neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer [ 33 ], and non-small cell lung cancer patients with preoperative high SII levels benefit from adjuvant chemotherapy [ 34 ], which suggests a certain degree of consistency with our results. However, we attempted to combine these inflammation indices to determine whether they could predict the efficacy, instead of using a single or dual biomarkers.…”

Section: Discussionsupporting

confidence: 84%

Combining serum inflammation indexes at baseline and post treatment could predict pathological efficacy to anti‑PD‑1 combined with neoadjuvant chemotherapy in esophageal squamous cell carcinoma

Zhang

Gari

et al. 2022

J Transl Med

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Background The neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) have been used to predict therapeutic response in different tumors. However, no assessments of their usefulness have been performed in esophageal squamous cell carcinoma (ESCC) patients receiving anti‑PD‑1 combined with neoadjuvant chemotherapy. Methods The respective data of 64 ESCC patients receiving anti‑PD‑1 combined with neoadjuvant chemotherapy were analyzed. Whether NLR, LMR, PLR, and SII at baseline and post-treatment might predict pathological response to anti‑PD‑1 plus neoadjuvant chemotherapy, and cutoff values of these parameters were all determined by ROC curve analysis. Results NLR (cutoff = 3.173, AUC = 0.644, 95% CI 0.500–0.788, P = 0.124, sensitivity = 1.000, specificity = 0.373), LMR (cutoff = 1.622, AUC = 0.631, 95% CI 0.477–0.784, P = 0.161, sensitivity = 0.917, specificity = 0.137), PLR (cutoff = 71.108, AUC = 0.712, 95% CI 0.575–0.849, P = 0.023, sensitivity = 1.000, specificity = 0.059), and SII at baseline (cutoff = 559.266, AUC = 0.681, 95% CI 0.533–0.830, P = 0.052, sensitivity = 0.373, specificity = 1.000) seemed to be a useful predictor for distinguishing responders from non-responders. Combining NLR with SII at baseline (AUC = 0.729, 95% CI 0.600–0.858, P = 0.014, sensitivity = 0.917, specificity = 0.510), LMR and SII at baseline (AUC = 0.735, 95% CI 0.609–0.861, P = 0.012, sensitivity = 1.000 specificity = 0.471), PLR and SII at baseline (AUC = 0.716, 95% CI 0.584–0.847, P = 0.021, sensitivity = 1.000 specificity = 0.431), and LMR and PLR at post-treatment in the third period (AUC = 0.761, 95% CI 0.605–0.917, P = 0.010, sensitivity = 0.800, specificity = 0.696) might slightly increase the prediction ability to determine patients who have response or no response. Finally, combining LMR at baseline, SII at post-treatment in the second period with PLR at post-treatment in the third period could be considered a better predictor for discriminating responders and non-responders than single or dual biomarkers (AUC = 0.879, 95% CI 0.788–0.969, P = 0.0001, sensitivity = 0.909, specificity = 0.800). Conclusions The models we constructed allowed for the accurate and efficient stratification of ESCC patients receiving anti-PD-1 plus chemotherapy and are easily applicable for clinical practice at no additional cost.

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Section: Discussionsupporting

confidence: 84%

Combining serum inflammation indexes at baseline and post treatment could predict pathological efficacy to anti‑PD‑1 combined with neoadjuvant chemotherapy in esophageal squamous cell carcinoma

Zhang

Gari

et al. 2022

J Transl Med

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“…A total of 23 studies comprising 8361 lung cancer patients were included. 7 - 10 , 12 - 30 Among these patients, 5702 (68%) were males, 4548 were current smokers and 2212 were diagnosed with squamous carcinoma. The main features of the included studies are summarized in Table 1 .…”

Section: Resultsmentioning

confidence: 99%

“… 19 All selected studies analyzed the association between OS and pretreatment LMR. Thirteen studies reported PFS, 5 studies evaluated RR, 17 , 20 , 24 , 26 5 studies evaluated disease-free survival(DFS), 12 , 13 , 19 , 21 , 23 and 1 study analyzed recurrence-free survival (RFS). 16 Chemotherapy, EGFR-TKIs, stereotactic ablative radiotherapy (SABR), chemotherapy plus TKI treatment, chemotherapy plus radiotherapy and surgery were used to treat lung cancer patients in the different studies.…”

Section: Resultsmentioning

confidence: 99%

Prognostic Value of Pretreatment Lymphocyte-to-Monocyte Ratio in Lung Cancer: A Systematic Review and Meta-Analysis

Jin

Yang

Liu

et al. 2021

Technol Cancer Res Treat

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Background: The overall prognosis of lung cancer remains unfavorable and novel prognostic biomarkers of lung cancer are needed warranted. Accumulating evidence indicate that systemic inflammation plays a vital role in lung cancer. The lymphocyte-to-monocyte ratio (LMR) is biomarker that reflects the level of systemic inflammation. Objective: To perform a comprehensive meta-analysis exploring the correlation of pretreatment LMR with the overall survival (OS) and progression-free survival (PFS) of lung cancer patients. Methods: We conducted searches of the PubMed, Embase, Cochrane Library, and Web of Science databases to May 2020 to identify relevant studies and calculated combined hazard ratios (HRs) to evaluate the association between pretreatment LMR and survival time in patients with lung cancer. Results: A total of 23 studies comprising 8361 lung cancer patients were included. Among the patients, 5702 (68%) were males, 4548 were current smokers and 2212 were diagnosed with squamous carcinoma. The pooled analysis revealed that decreased pretreatment LMR was significantly correlated with reduced of PFS (HR = 1.49, 95% CI: 1.34-1.67, p < 0.01) and reduced OS (HR = 1.61, 95% CI: 1.45-1.79, p < 0.01) among lung cancer patients. Furthermore, in the subgroup analyses according to histologic type, a lower level of pretreatment LMR seemed to be unrelated to the poorer OS of small cell lung cancer (SCLC) patients (HR = 1.21, 95%CI: 0.87-1.67, P = 0.25). Conclusions: Decreased pretreatment LMR in peripheral blood was associated with shorter OS and PFS in lung cancer patients, suggesting its potential prognostic value.

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“…An unspecified level of bias also may have been introduced by modeling missing values, although such bias is generally believed to be less than the bias incurred by deleting these data points. In our analysis, we used the median as the cutoff value for SII, given that there is no established uniform cutoff value in literature for this marker [78]. In future studies, a consensus optimal cutoff value for SII should be determined from population-based studies, using appropriate statistical methods to adjust for multiplicity.…”

Section: Discussionmentioning

confidence: 99%

Using the Systemic Immune-Inflammation Index (SII) as a Mid-Treatment Marker for Survival among Patients with Stage-III Locally Advanced Non-Small Cell Lung Cancer (NSCLC)

Biswas

Kang²,

Gawdi

et al. 2020

IJERPH

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The Systemic Immune-Inflammation Index (SII) is an important marker of immune function, defined as the product of neutrophil-to-lymphocyte ratio (NLR) and platelet count (P). Higher baseline SII levels have been associated with improved survival in various types of cancers, including lung cancer. Data were obtained from PROCLAIM, a randomized phase III trial comparing two different chemotherapy regimens pemetrexed + cisplatin (PEM) vs. etoposide + cisplatin (ETO), in combination with radiotherapy (RT) for the treatment of stage III non-squamous non-small cell lung cancer (NSCLC). We aimed to determine if SII measured at the mid-treatment window for RT (weeks 3–4) is a significant predictor of survival, and if the effect of PEM vs. ETO differs by quartile (Q) level of SII. Hazard-ratios (HR) for survival were estimated using a proportional hazards model, accounting for the underlying correlated structure of the data. A total of 548 patients were included in our analysis. The median age at baseline was 59 years. Patients were followed for a median of 24 months. Adjusting for age, body mass index, sex, race, and chemotherapy regimen, SII was a significant mid-treatment predictor of both overall (adjusted HR (aHR) = 1.6, p < 0.0001; OS) and progression-free (aHR = 1.3, p = 0.0072; PFS) survival. Among patients with mid-RT SII values above the median (6.8), those receiving PEM (vs. ETO) had superior OS (p = 0.0002) and PFS (p = 0.0002). Our secondary analysis suggests that SII is an informative mid-treatment marker of OS and PFS in locally advanced non-squamous NSCLC.

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Preoperative systemic immune-inflammation index predicts prognosis and guides clinical treatment in patients with non-small cell lung cancer

Cited by 21 publications

References 27 publications

Combining serum inflammation indexes at baseline and post treatment could predict pathological efficacy to anti‑PD‑1 combined with neoadjuvant chemotherapy in esophageal squamous cell carcinoma

Combining serum inflammation indexes at baseline and post treatment could predict pathological efficacy to anti‑PD‑1 combined with neoadjuvant chemotherapy in esophageal squamous cell carcinoma

Prognostic Value of Pretreatment Lymphocyte-to-Monocyte Ratio in Lung Cancer: A Systematic Review and Meta-Analysis

Using the Systemic Immune-Inflammation Index (SII) as a Mid-Treatment Marker for Survival among Patients with Stage-III Locally Advanced Non-Small Cell Lung Cancer (NSCLC)

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