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Nomogram Based on Systemic Immune-Inflammation Index to Predict Survival of Tongue Cancer Patients Who Underwent Cervical Dissection.

ABSTRACT: Aim: The aim of this study was to evaluate the prognostic significance of the preoperative systemic immune-inflammation index (SII) and to establish a nomogram for prediction of survival of tongue squamous cell carcinoma (TSCC) patients who underwent primary surgery and cervical dissection. Methods: 120 patients diagnosed with TSCC who underwent primary tumor and neck dissection without preoperative treatment were included to develop the nomogram. This model was externally validated in an independent data cohort of 50 TSCC patients. X-tile software was used to identify the optimal cut-off value. Prognostic factors were identified by Univariate and multivariate analyses. A nomogram based on the multivariate analysis results was built to predict the survival rate and calibration curves and concordance index (C-index) were used to determine predictive and discriminatory capacity. Results: The optimal cut-off value was 569×10⁹/L for SII. In the training cohort, a high preoperative SII (>569) was significantly related to tumor size, histological grade, depth of invasion, lymph node density (LND). A Kaplan-Meier survival analysis showed that patients with a lower SII had a significantly better 5-year overall survival (OS) and disease-free survival (DFS) than patients with high SII (80.8% vs. 43.5% and 72.7% vs. 36.2%, respectively, P<0.001). Univariate analyses of training cohort revealed that age, clinical stage, depth of invasion, LND, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and SII were significant prognostic factors for OS. Moreover, the receiver operating characteristics (ROC) curve showed that SII was superior to NLR and PLR for predicting clinical outcomes. However, multivariate analysis found that age, LND, and SII were independent risk factors for OS. The C-index of the nomograms based on independent prognostic factors was 0.716 for OS and 0.723 for DFS. The C-indexes for external validation of OS and DFS were 0.852 and 0.754, respectively. The calibration curves showed good agreement between predicted and actual observations of OS and DFS. Conclusion: SII can serve as a novel independent prognostic factor for OS and DFS of patients with TSCC. The prognostic nomogram based on SII is a reliable model for predicting survival of patients with TSCC after surgery.

SUBMITTER: Lu Z

PROVIDER: S-EPMC7078378 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Nomogram Based on Systemic Immune-Inflammation Index to Predict Survival of Tongue Cancer Patients Who Underwent Cervical Dissection.

Lu Zhiyuan Z Yan Wangxiang W Liang Jianfeng J Yu Mei M Liu Jiayu J Hao Jiansuo J Wan Quan Q Liu Jiameng J Luo Chongdai C Chen Yiyang Y

Frontiers in oncology 20200311

<b>Aim:</b> The aim of this study was to evaluate the prognostic significance of the preoperative systemic immune-inflammation index (SII) and to establish a nomogram for prediction of survival of tongue squamous cell carcinoma (TSCC) patients who underwent primary surgery and cervical dissection. <b>Methods:</b> 120 patients diagnosed with TSCC who underwent primary tumor and neck dissection without preoperative treatment were included to develop the nomogram. This model was externally validate ...[more]

PMID: 32219070

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Project description:Background: The systemic immune-inflammation index (SII) has been identified as a predictor of chemotherapy efficacy for a variety of cancers, and we aimed to determine its ability to predict the response to chemotherapy and its long-term prognosis for patients with cervical squamous cell carcinoma (CSCC) who have underwent platinum-based neoadjuvant chemotherapy (NACT). Methods: The date from 210 patients (133 in the training cohort and 77 in the validation cohort) with CSCC who received NACT were analyzed retrospectively. The association between SII and the pathological complete response (pCR) was determined using Pearson's chi-square test, receiver operating characteristic (ROC) curve, and Logistic regression analysis. The Kaplan-Meier method and Cox proportional regression model were used to assess the relationship between SII and progression-free survival (PFS) or overall survival (OS). Results: The calculated optimal SII cutoff values for pCR and survival were 568.7051 and 600.5683, respectively, and patients were divided into two groups: a low SII group (≤568.7051 or ≤600.5683) and a high SII group (>568.7051 or >600.5683). A high SII was associated significantly with a lower pCR. Further analysis determined that SII was a more efficient predictor of pCR than the prognostic nutritional index, platelet-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio. Upon multivariate logistic analysis, SII proved to be an independent risk factor to predict the pCR of patients with CSCC. Kaplan-Meier analysis demonstrated that PFS and OS rates were significantly higher in the low-SII group compared with those in the high-SII group. Additional multivariate analysis indicated that the SII is an independent prognostic factor for patients with CSCC treated with NACT. Conclusion: The results confirmed that the pre-treatment SII is not only an independent predictor of pCR but also an independent prognostic factor of CSCC patients treated with platinum based NACT.

Project description:BackgroundThe systemic inflammation response index (SIRI) has been reported to associate with survival outcomes in breast cancer patients. However, the effects of baseline SIRI and SIRI change after neoadjuvant chemotherapy (NACT) have not been thoroughly investigated. This study aimed to evaluate the role of baseline SIRI and SIRI change after NACT in predicting survival outcomes, and establish a nomogram based on SIRI.MethodsA total of 260 patients diagnosed with breast cancer who received NACT between January 2014 and December 2018 at our hospital were included. The clinical data were retrospectively collected from the medical records management system. The associations between clinicopathological factors and baseline SIRI, pathological complete response (pCR) were analyzed by Student's t-test, Chi-squared test, or Fisher's exact test. The association between clinicopathological factors and disease-free survival (DFS) was evaluated by univariate and multivariate Cox regression analyses.ResultsPatients with a tumor-node-metastasis (TNM) stage of I, II, and III were 1.9%, 20.0%, and 78.1% respectively. The median follow-up time was 40 months, and 74 (28.5%) patients had cancer recurrence during the follow-up. Both in the univariate and multivariate analysis, Ki-67, pCR, and baseline SIRI were independent factors associated with DFS. Patients with low baseline SIRI had prolonged DFS compared with those with high baseline SIRI [≤1.6×109 vs. >1.6×109, hazard ratio (HR) =0.545, P=0.028]. In addition, SIRI change after NACT was also an independent factor associated with DFS, and patients with minor SIRI change had longer DFS than patients with major SIRI change (>50% or <-30% vs. ≤50% and ≥-30%, HR =1.721, P=0.037). Nomograms were established based on Ki-67, pCR, and baseline SIRI or SIRI change after NACT with a concordance index of 0.665 and 0.663 respectively, and the nomogram provided a convenient tool for predicting the probability of DFS.ConclusionsThe baseline SIRI and SIRI change after NACT could act as potential biomarkers for predicting survival outcomes in breast cancer. Besides, the nomogram with SIRI is an economic and convenient tool for predicting DFS. Larger prospective studies are needed to verify the results.

Project description:Background A novel hematologic parameter, systemic coagulation-inflammation (SCI) index reflecting inflammation and coagulation pathways could be easily obtained from clinically routine laboratory findings. We hypothesize that the SCI index has prognostic implication in predicting operative mortality for patients with acute type A aortic dissection (ATAAD). Objectives This study aims to investigate the prognostic value of the SCI index and to establish an SCI-adding nomogram for mortality prediction in ATAAD patients. Methods A total of 1,967 ATAAD patients surgically repaired were collected from 12 Chinese cardiovascular centers by the 5A (Additive Anti-inflammatory Action for Aortopathy & Arteriopathy [Multicenter Retrospective Study]) study III (2016-2020). SCI index was calculated as platelet count × fibrinogen/white blood cell count on admission. By adding SCI index, a nomogram was developed and evaluated for 90-day mortality prediction with conventional predictors via the Cox model with 10-fold cross-validation. Results Patients were stratified with low SCI (<40), middle SCI (40-100), or high SCI (>100). The 90-day survival rates increased with SCI index (low 86.9%; [95% CI: 84.9%-89.0%], middle 92.7% [95% CI: 90.9%-94.9%], and high 96.4% [95% CI: 94.2%-98.6%]; log-rank P < 0.001). SCI index is independently associated with 90-day mortality (adjusted hazard ratio: 0.549; 95% CI: 0.424-0.710; P < 0.001). The addition of SCI index provided significantly incremental prognostic value to base model including age, serum creatinine, DeBakey class, and location of intimal entry (area under the curve: 0.677; 95% CI: 0.641-0.716 vs 0.724; 95% CI: 0.685-0.760; P = 0.002), which was confirmed by net reclassification improvement index (0.158; 95% CI: 0.065-0.235; P < 0.001) and integrated discrimination improvement index (0.070; 95% CI: 0.007-0.036; P < 0.001). Conclusions SCI index is easily obtainable, performs moderately well as a predictor of short-term mortality in ATAAD patients, and may be useful for risk stratification in emergency settings. (Additive Anti-inflammatory Action for Aortopathy & Arteriopathy [Multicenter Retrospective Study] III NCT04918108) Central Illustration

Project description:It has been confirmed that the systemic inflammation response index (SIRI) based on peripheral blood neutrophil, monocyte and lymphocyte counts can be used for the prognostication of patients with various malignant tumors. However, the prognostic value of SIRI in cervical cancer patients has not yet been reported. This study found that a higher SIRI was related to lymphovascular invasion and was also significantly associated with FIGO stage, radiotherapy, neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and monocyte/lymphocyte ratio (MLR) but not related to other clinical and pathological parameters. According to the Kaplan-Meier survival analysis, a high SIRI was associated with the poor prognosis of cervical cancer patients in the primary and validation groups. SIRI, NLR, PLR, and MLR can all be used to determine the prognosis of patients with operable cervical cancer. Moreover, it was confirmed that only SIRI was an independent prognostic factor for patients with operable cervical cancer. The same result was obtained in the propensity score matching (PSM) analysis. In the ROC curve analysis, SIRI was more accurate in predicting the prognosis of cervical cancer patients. Then, a nomogram was established based on SIRI, FIGO stage and lymphovascular invasion, which could determine the prognosis of cervical cancer patients more accurately than FIGO stage. The validation cohort showed the same results. In addition, the changes in SIRI relative to the baseline value at 4-8 weeks after surgery were closely related to the survival of cervical cancer patients. Compared with those with unchanged SIRI (absolute value of variation <25%), cervical cancer patients with an increase in SIRI > 75% had worse OS (P < 0.001), while patients with a decrease in SIRI > 75% had a better prognosis (P < 0.001). SIRI can serve as a new independent prognostic index and a potential marker for therapeutic response monitoring in patients with curable cervical cancer. Compared with the traditional FIGO staging system, the nomogram integrating SIRI can predict the survival of cervical cancer patients more objectively and reliably after radical surgery.

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Nomogram Based on Systemic Immune-Inflammation Index to Predict Survival of Tongue Cancer Patients Who Underwent Cervical Dissection.

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Nomogram Based on Systemic Immune-Inflammation Index to Predict Survival of Tongue Cancer Patients Who Underwent Cervical Dissection.

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