A Novel Systemic Inflammation Prognostic Score to Stratify Survival in Elderly Patients With Cancer

Ruan, Guo‐Tian; Xie, Hailun; Deng, Li; Ge, Yi‐Zhong; Zhang, Qi; Wang, Ziwen; Zhang, Xi; Zhang, Heyang; Tang, Meng; Song, Mengmeng; Zhang, Xiaowei; Yang, Ming; Pan, Lei; Wang, Kunhua; Ma, Cong; Gong, Yizhen; Wang, Meng-Yan; Shi, Hanping

doi:10.3389/fnut.2022.893753

Cited by 3 publications

(1 citation statement)

References 36 publications

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“…It is unclear which combination of blood features is a strong marker of prognosis in UTUC patients. Some scholars have previously developed new prognostic markers through the combination of various inflammatory indicators, which can more accurately predict the survival of cancer patients [ 26 – 28 ]. Therefore, we also believe that combining these markers can predict clinical survival more accurately than using a single marker.…”

Section: Introductionmentioning

confidence: 99%

Prognostic models for upper urinary tract urothelial carcinoma patients after radical nephroureterectomy based on a novel systemic immune-inflammation score with machine learning

Liu

Lai

et al. 2023

BMC Cancer

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Purpose This study aimed to evaluate the clinical significance of a novel systemic immune-inflammation score (SIIS) to predict oncological outcomes in upper urinary tract urothelial carcinoma(UTUC) after radical nephroureterectomy(RNU). Method The clinical data of 483 patients with nonmetastatic UTUC underwent surgery in our center were analyzed. Five inflammation-related biomarkers were screened in the Lasso-Cox model and then aggregated to generate the SIIS based on the regression coefficients. Overall survival (OS) was assessed using Kaplan-Meier analyses. The Cox proportional hazards regression and random survival forest model were adopted to build the prognostic model. Then we established an effective nomogram for UTUC after RNU based on SIIS. The discrimination and calibration of the nomogram were evaluated using the concordance index (C-index), area under the time-dependent receiver operating characteristic curve (time-dependent AUC), and calibration curves. Decision curve analysis (DCA) was used to assess the net benefits of the nomogram at different threshold probabilities. Result According to the median value SIIS computed by the lasso Cox model, the high-risk group had worse OS (p<0.0001) than low risk-group. Variables with a minimum depth greater than the depth threshold or negative variable importance were excluded, and the remaining six variables were included in the model. The area under the ROC curve (AUROC) of the Cox and random survival forest models were 0.801 and 0.872 for OS at five years, respectively. Multivariate Cox analysis showed that elevated SIIS was significantly associated with poorer OS (p<0.001). In terms of predicting overall survival, a nomogram that considered the SIIS and clinical prognostic factors performed better than the AJCC staging. Conclusion The pretreatment levels of SIIS were an independent predictor of prognosis in upper urinary tract urothelial carcinoma after RNU. Therefore, incorporating SIIS into currently available clinical parameters helps predict the long-term survival of UTUC.

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Section: Introductionmentioning

confidence: 99%

Prognostic models for upper urinary tract urothelial carcinoma patients after radical nephroureterectomy based on a novel systemic immune-inflammation score with machine learning

Liu

Lai

et al. 2023

BMC Cancer

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Real-world practice-based prognostic model for higher-risk myelodysplastic syndromes treated with azacitidine monotherapy: The Kyoto prognostic scoring system

et al. 2023

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Development and validation of a new prognostic immune–inflammatory–nutritional score for predicting outcomes after curative resection for intrahepatic cholangiocarcinoma: A multicenter study

et al. 2023

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BackgroundImmune function, nutrition status, and inflammation influence tumor initiation and progression. This was a retrospective multicenter cohort study that investigated the prognostic value and clinical relevance of immune-, inflammatory-, and nutritional-related biomarkers to develop a novel prognostic immune–inflammatory–nutritional score (PIIN score) for patients with intrahepatic cholangiocarcinoma (ICC).MethodsThe clinical data of 571 patients (406 in the training set and 165 in the validation set) were collected from four large hepato-pancreatico-biliary centers of patients with ICC who underwent surgical resection between January 2011 and September 2017. Twelve blood biomarkers were collected to develop the PIIN score using the LASSO Cox regression model. The predictive value was further assessed using validation datasets. Afterward, nomograms combining the PIIN score and other clinicopathological parameters were developed and validated based on the calibration curve, time-dependent AUC curves, and decision curve analysis (DCA). The primary outcomes evaluated were overall survival (OS) and recurrence-free survival (RFS) from the day of primary resection of ICC.ResultsBased on the albumin–bilirubin (ALBI) grade, neutrophil- to- lymphocyte ratio (NLR), prognostic nutritional index (PNI), and systemic immune- inflammation index (SII) biomarkers, the PIIN score that classified patients into high-risk and low-risk groups could be calculated. Patients with high-risk scores had shorter OS (training set, p < 0.001; validation set, p = 0.003) and RFS (training set, p < 0.001; validation set, p = 0.002) than patients with low-risk scores. The high PIIN score was also associated with larger tumors (≥5 cm), lymph node metastasis (N1 stage), multiple tumors, and high tumor grade or TNM (tumor (T), nodes (N), and metastases (M)) stage. Furthermore, the high PIIN score was a significant independent prognostic factor of OS and RFS in both the training (p < 0.001) and validation (p = 0.003) cohorts, respectively. A PIIN-nomogram for individualized prognostic prediction was constructed by integrating the PIIN score with the clinicopathological variables that yielded better predictive performance than the TNM stage.ConclusionThe PIIN score, a novel immune–inflammatory–nutritional-related prognostic biomarker, predicts the prognosis in patients with resected ICC and can be a reliable tool for ICC prognosis prediction after surgery. Our study findings provide novel insights into the role of cancer-related immune disorders, inflammation, and malnutrition.

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A Novel Systemic Inflammation Prognostic Score to Stratify Survival in Elderly Patients With Cancer

Cited by 3 publications

References 36 publications

Prognostic models for upper urinary tract urothelial carcinoma patients after radical nephroureterectomy based on a novel systemic immune-inflammation score with machine learning

Prognostic models for upper urinary tract urothelial carcinoma patients after radical nephroureterectomy based on a novel systemic immune-inflammation score with machine learning

Real-world practice-based prognostic model for higher-risk myelodysplastic syndromes treated with azacitidine monotherapy: The Kyoto prognostic scoring system

Development and validation of a new prognostic immune–inflammatory–nutritional score for predicting outcomes after curative resection for intrahepatic cholangiocarcinoma: A multicenter study

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