Pre-treatment prognostic nutritional index may serve as a potential biomarker in urinary cancers: a systematic review and meta-analysis

Qi, Feng; Zhou, Xiang; Wang, Yichuan; Wang, Yamin; Wang, Yichun; Zhang, Qijie; Cong, Rong; Yang, Jie; Song, Ninghong

doi:10.1186/s12935-018-0708-7

Cited by 24 publications

(28 citation statements)

References 49 publications

(40 reference statements)

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“…Prognostic value of pretreatment PNI has been confirmed in several human cancers, [ 9 , 10 , 21 , 22 ] however, the agreement on the prognostic significance of preoperative PNI in OC has not been reached for contradictory results and small sample size of existing evidence. [ 12 – 17 ] Komura et al [ 14 ] study analyzed 164 patients with early-stage OC, and authors failed to observe the statistical association of preoperative PNI with PFS ( P = .58) and OS ( P = .99).…”

Section: Discussionmentioning

confidence: 99%

Prognostic significance of preoperative prognostic nutritional index in ovarian cancer

Dai¹,

Liu²,

Li³

et al. 2020

Medicine

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Background: The prognostic significance of preoperative prognostic nutritional index (PNI) in ovarian cancer (OC) is uncertain, and this study is aimed to clarify the prognostic significance. Methods: We used 4 common databases for conducting a systematic review and meta-analysis, and eligible studies were included in the analysis. The association of preoperative PNI with overall survival (OS), progression-free survival (PFS), and clinicopathological parameters was analyzed. Results: A total of 2050 patients with OC receiving the surgical treatment were analyzed in this study. Patients with low PNI tended to have a shorter OS (hazard ratio [HR] = 1.82, 95% CI = 1.30–2.55, P < .01) and PFS (HR = 1.91, 95% CI = 1.53–2.39, P < .01) compared with those with high PNI. Besides, low PNI was significantly associated with more advanced International Federation of Gynecology and Obstetrics stage ( P < .01), the occurrence of ascites ( P < .01), larger residual tumor ( P < .01), insensitive to chemotherapy ( P < .01), and higher CA125 ( P < .01) compared with high PNI in OC. Conclusion: Low preoperative PNI is associated with shorter OS, shorter PFS, and worse clinicopathological parameters in OC. Low preoperative PNI is an unfavorable prognostic indicator of patients with OC.

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Section: Discussionmentioning

confidence: 99%

Prognostic significance of preoperative prognostic nutritional index in ovarian cancer

Dai¹,

Liu²,

Li³

et al. 2020

Medicine

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“…PNI, which combines albumin levels and lymphocyte counts, reflects immune-nutritional status of human body and might predict prognosis of cancer patients (Qi et al, 2018;Yao et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

Prognostic value of prognostic nutritional index and systemic immune‐inflammation index in patients with osteosarcoma

Huang

Zhang

et al. 2019

Journal Cellular Physiology

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The aim of this study was to evaluate the relationship between prognostic nutritional index (PNI) and systemic immune‐inflammation index (SII) and clinical features and prognosis of osteosarcoma patients. We retrospectively investigated 126 patients with surgery for osteosarcoma between 2012 and 2018 at our hospital. The preoperative PNI was calculated as albumin level (g/L) + 5 × total lymphocyte count (10 9/L). The SII was defined as platelet × neutrophil/lymphocyte counts. The optimal cut‐off values for PNI and SII were evaluated with receiver operating curve analysis. Clinical features and PNI and SII were tested with the χ 2 test. The effects of PNI and SII on overall survival (OS) was investigated by Kaplan–Meier method and Cox proportional hazards model. A low preoperative PNI was remarkably correlated with tumor size, Enneking stage, pathological fracture, local recurrence, metastasis, and neoadjuvant chemotherapy ( p < 0.05). Whereas, a high SII was significantly associated with tumor size, histological type, Enneking stage, and neoadjuvant chemotherapy ( p < 0.05). There was a significant negative relationship between the PNI and SII ( r = 0.384; p < 0.001). For univariate analyses, the results revealed that tumor size, local recurrence, metastasis, PNI, and SII were predictors of OS ( p < 0.05). In multivariate analyses, local recurrence ( p = 0.010), metastasis ( p < 0.001), PNI ( p < 0.001), and SII ( p = 0.029) as independent prognostic factors were significantly correlated with OS. This study suggested that PNI and SII could be important prognostic parameters for patients with osteosarcoma.

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“…Contrasted with the previous systems, our study innovatively but not groundlessly included cholesterol in the scoring system. Lipids have been gradually included in the emerging prognostic indices, such as Prognostic Nutritional Index (PNI) [ 35 ], Controlling Nutritional Status (CONUT) score [ 36 ] and Naples prognostic score (NPS) [ 37 ]. In addition, lipid metabolism-related signature also showed prognostic significance for some cancers [ 38 ].…”

Section: Discussionmentioning

confidence: 99%

Derivation and validation of a lipid-covered prognostic model for mature T-cell lymphomas

Lü

Shi

et al. 2021

Cancer Cell Int

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Background Mature T-cell lymphomas (MTCLs), a group of diseases with high aggressiveness and vulnerable prognosis, lack for the accurate prognostic stratification systems at present. Novel prognostic markers and models are urgently demanded. Aberrant lipid metabolism is closely related to the tumor progression but its prognostic significance in MTCLs remains unexplored. This study aims to investigate the relationship between dysregulated lipid metabolism and survival prognosis of MTCLs and establish a novel and well-performed prognostic scoring system for MTCL patients. Methods A total of 173 treatment-naive patients were enrolled in this study. Univariate and multivariate Cox regression analysis were performed to assess the prognostic significance of serum lipid profiles and screen out independent prognostic factors, which constituted a novel prognostic model for MTCLs. The performance of the novel model was assessed in the training and validation cohort, respectively, by examining its calibration, discrimination and clinical utility. Results Among the 173 included patients, 115 patients (01/2006–12/2016) constituted the training cohort and 58 patients (01/2017–06/2020) formed the validation cohort. Univariate analysis revealed declined total cholesterol (TC, P = 0.000), high-density lipoprotein cholesterol (HDL-C, P = 0.000) and increased triglycerides (TG, P = 0.000) correlated to inferior survival outcomes. Multivariate analysis revealed extranodal involved sites ≥ 2 (hazard ratio [HR]: 2.439; P = 0.036), β2-MG ≥ 3 mg/L (HR: 4.165; P = 0.003) and TC < 3.58 mmol/L (HR: 3.338; P = 0.000) were independent predictors. Subsequently, a novel prognostic model, EnBC score, was constructed with these three factors. Harrell’s C-index of the model in the training and validation cohort was 0.840 (95% CI 0.810–0.870) and 0.882 (95% CI 0.822–0.942), respectively, with well-fitted calibration curves. The model divided patients into four risk groups with distinct OS [median OS: not available (NA) vs. NA vs. 14.0 vs. 4.0 months, P < 0.0001] and PFS (median PFS: 84.0 vs. 19.0 vs. 8.0 vs. 1.5 months, P < 0.0001). Time-dependent receiver operating characteristic curve and decision curve analysis further revealed that EnBC score provided higher diagnostic capacity and clinical benefit, compared with International Prognostic Index (IPI). Conclusion Firstly, abnormal serum lipid metabolism was demonstrated significantly related to the survival of MTCL patients. Furthermore, a lipid-covered prognostic scoring system was established and performed well in stratifying patients with MTCLs.

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Pre-treatment prognostic nutritional index may serve as a potential biomarker in urinary cancers: a systematic review and meta-analysis

Cited by 24 publications

References 49 publications

Prognostic significance of preoperative prognostic nutritional index in ovarian cancer

Prognostic significance of preoperative prognostic nutritional index in ovarian cancer

Prognostic value of prognostic nutritional index and systemic immune‐inflammation index in patients with osteosarcoma

Derivation and validation of a lipid-covered prognostic model for mature T-cell lymphomas

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