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Wang Y, Qian C. Prognostic and clinicopathological value of the controlling nutritional status (CONUT) score in patients with head and neck cancer: a meta-analysis. World J Surg Oncol 2024; 22:223. [PMID: 39192261 DOI: 10.1186/s12957-024-03505-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 08/18/2024] [Indexed: 08/29/2024] Open
Abstract
BACKGROUND The efficiency of controlling nutritional status (CONUT) score in detecting the prognosis of head and neck cancer (HNC) patients has been investigated in some works, but no consistent findings are obtained. Therefore, this work focused on evaluating the precise prognostic role of CONUT for HNC patients through meta-analysis. METHODS The effect of CONUT on predicting the prognosis of HNC patients was evaluated through calculating combined hazard ratios (HRs) as well as 95% confidence intervals (CIs). The correlations of CONUT with clinicopathological features of HNC patients were investigated through combined odds ratios (ORs) and 95%CIs. This study used the random-effects model in the case of significant heterogeneity; or else, we selected the fixed-effects model. RESULTS There were eight articles involving 1,478 patients enrolled for the current meta-analysis. We adopted the fixed-effects model for OS and DFS analysis because of the non-significant heterogeneity. As demonstrated by our combined findings, high CONUT score could significantly predict the poor overall survival (OS) (HR = 1.94, 95%CI = 1.55-2.44, p < 0.001) and disease-free survival (DFS) (HR = 1.93, 95%CI = 1.45-2.56, p < 0.001) of HNC. In addition, higher CONUT score was significantly connected to T3-T4 stage (OR = 3.21, 95%CI = 1.94-5.31, p < 0.001) and N1-N3 stage (OR = 3.10, 95%CI = 1.74-5.53, p < 0.001). CONCLUSION According to findings in the present meta-analysis, high CONUT score significantly predicted the prognosis of OS and DFS for HNC patients. Higher CONUT score was also correlated to larger tumor size and LN metastasis in HNC. Due to it is a cost-effective and easily available parameter, CONUT could serve as promising prognostic biomarker for HNC.
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Affiliation(s)
- Yanyan Wang
- Department of Pathology, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, 313000, Zhejiang, China
| | - Caihua Qian
- Nursing Department, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, 313000, Zhejiang, China.
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Pan C, Gu Y, Ni Q. The Prognostic Value of Serum Albumin to Globulin Ratio in Patients with Breast Cancer: A Retrospective Study. BREAST CANCER (DOVE MEDICAL PRESS) 2024; 16:403-411. [PMID: 39081848 PMCID: PMC11287198 DOI: 10.2147/bctt.s471747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Accepted: 07/24/2024] [Indexed: 08/02/2024]
Abstract
Objective This study examined the potential risk value of the serum albumin to globulin ratio (AGR) in patients with breast cancer (BC). Methods This study employed a retrospective design, enrolling 332 patients with BC and 38 patients without BC treated at Taizhou People's Hospital between September 2015 and May 2021. Multivariate Cox proportional hazard regression models were used to identify potential risk factors. A prognostic nomogram was developed based on the multivariate analyses. The receiver operating characteristic curve determined the optimal cutoff value for AGR. Results The results indicated a statistically significant decrease in AGR among patients with BC. Significant disparities were observed in globulin and AGR levels between the two cohorts. AGR was significantly associated with tumor size and stage, with a marked decline in advanced stages of BC. Additionally, AGR and aspartate transaminase/Alanine aminotransferase (AST/ALT) emerged as significant diagnostic indicators for invasive carcinoma and advanced stages (II-IV) of BC. Specifically, AGR exhibited an area under the curve of 0.645 (P < 0.003), highlighting the discriminatory capacity of serum globulin levels in distinguishing between BC and non-BC cohorts. Conclusions The AGR, routinely assessed due to its simplicity, objectivity, and cost-effectiveness, holds promise as a potential risk factor for BC and may have practical implications in clinical settings.
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Affiliation(s)
- Chi Pan
- Department of General Surgery, The Affiliated Taizhou People’s Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, People’s Republic of China
| | - Yawen Gu
- Department of Oncology, The Affiliated Taizhou People’s Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, People’s Republic of China
| | - Qingtao Ni
- Department of Oncology, The Affiliated Taizhou People’s Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, People’s Republic of China
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Dang J, Xu G, Guo G, Zhang H, Shang L. Construction of a prognostic model for extensive-stage small cell lung cancer patients undergoing immune therapy in northernmost China and prediction of treatment efficacy based on response status at different time points. J Cancer Res Clin Oncol 2024; 150:255. [PMID: 38750370 PMCID: PMC11096247 DOI: 10.1007/s00432-024-05767-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Accepted: 04/26/2024] [Indexed: 05/18/2024]
Abstract
BACKGROUND AND PURPOSE Recently, the emergence of immune checkpoint inhibitors has significantly improved the survival of patients with extensive-stage small cell lung cancer. However, not all patients can benefit from immunotherapy; therefore, there is an urgent need for precise predictive markers to screen the population for the benefit of immunotherapy. However, single markers have limited predictive accuracy, so a comprehensive predictive model is needed to better enable precision immunotherapy. The aim of this study was to establish a prognostic model for immunotherapy in ES-SCLC patients using basic clinical characteristics and peripheral hematological indices of the patients, which would provide a strategy for the clinical realization of precision immunotherapy and improve the prognosis of small cell lung cancer patients. METHODS This research retrospectively collected data from ES-SCLC patients treated with PD-1/PD-L1 inhibitors between March 1, 2019, and October 31, 2022, at Harbin Medical University Cancer Hospital. The study data was randomly split into training and validation sets in a 7:3 ratio. Variables associated with patients' overall survival were screened and modeled by univariate and multivariate Cox regression analyses. Models were presented visually via Nomogram plots. Model discrimination was evaluated by Harrell's C index, tROC, and tAUC. The calibration of the model was assessed by calibration curves. In addition, the clinical utility of the model was assessed using a DCA curve. After calculating the total risk score of patients in the training set, patients were stratified by risk using percentile partitioning. The Kaplan-Meier method was used to plot OS and PFS survival curves for different risk groups and response statuses at different milestone time points. Differences in survival time groups were compared using the chi-square test. Statistical analysis software included R 4.1.2 and SPSS 26. RESULTS This study included a total of 113 ES-SCLC patients who received immunotherapy, including 79 in the training set and 34 in the validation set. Six variables associated with poorer OS in patients were screened by Cox regression analysis: liver metastasis (P = 0.001), bone metastasis (P = 0.013), NLR < 2.14 (P = 0.005), LIPI assessed as poor (P < 0.001), PNI < 51.03 (P = 0.002), and LDH ≥ 146.5 (P = 0.037). A prognostic model for immunotherapy in ES-SCLC patients was constructed based on the above variables. The Harrell's C-index in the training and validation sets of the model was 0.85 (95% CI 0.76-0.93) and 0.88 (95% CI 0.76-0.99), respectively; the AUC values corresponding to 12, 18, and 24 months in the tROC curves of the training set were 0.745, 0.848, and 0.819 in the training set and 0.858, 0.904 and 0.828 in the validation set; the tAUC curves show that the overall tAUC is > 0.7 and does not fluctuate much over time in both the training and validation sets. The calibration plot demonstrated the good calibration of the model, and the DCA curve indicated that the model had practical clinical applications. Patients in the training set were categorized into low, intermediate, and high risk groups based on their predicted risk scores in the Nomogram graphs. In the training set, 52 patients (66%) died with a median OS of 15.0 months and a median PFS of 7.8 months. Compared with the high-risk group (median OS: 12.3 months), the median OS was significantly longer in the intermediate-risk group (median OS: 24.5 months, HR = 0.47, P = 0.038) and the low-risk group (median OS not reached, HR = 0.14, P = 0.007). And, the median PFS was also significantly prolonged in the intermediate-risk group (median PFS: 12.7 months, HR = 0.45, P = 0.026) and low-risk group (median PFS not reached, HR = 0.12, P = 0.004) compared with the high-risk group (median PFS: 6.2 months). Similar results were obtained in the validation set. In addition, we observed that in real-world ES-SCLC patients, at 6 weeks after immunotherapy, the median OS was significantly longer in responders than in non-responders (median OS: 19.5 months vs. 11.9 months, P = 0.033). Similar results were obtained at 12 weeks (median OS: 20.7 months vs 11.9 months, P = 0.044) and 20 weeks (median OS: 20.7 months vs 11.7 months, P = 0.015). Finally, we found that in the real world, ES-SCLC patients without liver metastasis (P = 0.002), bone metastasis (P = 0.001) and a total number of metastatic organs < 2 (P = 0.002) are more likely to become long-term survivors after receiving immunotherapy. CONCLUSION This study constructed a new prognostic model based on basic patient clinical characteristics and peripheral blood indices, which can be a good predictor of the prognosis of immunotherapy in ES-SCLC patients; in the real world, the response status at milestone time points (6, 12, and 20 weeks) can be a good indicator of long-term survival in ES-SCLC patients receiving immunotherapy.
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Affiliation(s)
- Junjie Dang
- Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150000, Heilongjiang, China
| | - Gang Xu
- Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150000, Heilongjiang, China
| | - Ge Guo
- Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150000, Heilongjiang, China
| | - Huan Zhang
- Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150000, Heilongjiang, China
| | - Lihua Shang
- Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150000, Heilongjiang, China.
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Fan Z, Shou L. Prognostic and clinicopathological impacts of systemic immune-inflammation index on patients with diffuse large B-cell lymphoma: a meta-analysis. Ther Adv Hematol 2023; 14:20406207231208973. [PMID: 37954483 PMCID: PMC10638869 DOI: 10.1177/20406207231208973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 09/29/2023] [Indexed: 11/14/2023] Open
Abstract
Background The systemic immune-inflammation index (SII) represents the immunoinflammatory score and can be considered as a prognostic marker; however, its relevance to the prognosis in patients with diffuse large B-cell lymphoma (DLBCL) remains unclear. Objectives The present meta-analysis was conducted to comprehensively evaluate the relationship between the SII and prognosis in patients with DLBCL. Design This meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Data sources and methods The PubMed, Web of Science, Embase, and Cochrane Library databases were comprehensively searched from inception to 16 March 2023. We calculated combined hazard ratios (HRs) and 95% confidence intervals (CIs) to estimate the prognostic significance of the SII for overall survival (OS) and progression-free survival (PFS) in DLBCL. In addition, this study determined odds ratios (ORs) and their 95% CIs to evaluate the correlation of SII with the clinicopathological features of DLBCL. Results Five articles including 592 cases were enrolled in the current meta-analysis. According to our combined findings, the higher SII significantly predicted worse OS (HR = 3.87, 95% CI: 2.48-6.04, p < 0.001) together with inferior PFS (HR = 2.38, 95% CI: 1.12-5.08, p = 0.024) in DLBCL. Furthermore, a high SII was significantly correlated with B symptoms (OR = 2.52, 95% CI: 1.66-3.81, p < 0.001), III-IV Ann Arbor stage (OR = 2.86, 95% CI: 1.84-4.45, p < 0.001), high-intermediate/high National Comprehensive Cancer Network International Prognostic Index (OR = 2.25, 95% CI: 1.52-3.31, p < 0.001), increased neutrophil-to-lymphocyte ratio (OR = 33.76, 95% CI: 17.18-66.35, p < 0.001), and increased platelet-to-lymphocyte ratio (OR = 44.65, 95% CI: 5.80-343.59, p < 0.001). Nonetheless, the SII was not significantly related to sex, age, lactic dehydrogenase level, Eastern Cooperative Oncology Group performance status, or histology. Conclusion According to this meta-analysis, the higher SII dramatically predicted inferior OS and PFS of DLBCL. Furthermore, an increased SII significantly correlated with some clinicopathological features representing the disease progression of DLBCL. Trial registration The protocol was registered in INPLASY under the number INPLASY202380106.
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Affiliation(s)
- Zaijing Fan
- Clinical Laboratory, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, The Fifth School of Clinical Medicine Zhejiang Chinese Medical University, Huzhou, Zhejiang, China
| | - Lihong Shou
- Department of Hematology, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, The Fifth School of Clinical Medicine Zhejiang Chinese Medical University, No. 1558, North Sanhuan Road, Huzhou, Zhejiang 313000, China
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Roberts WS, Delladio W, Price S, Murawski A, Nguyen H. The efficacy of albumin-globulin ratio to predict prognosis in cancer patients. Int J Clin Oncol 2023; 28:1101-1111. [PMID: 37421476 DOI: 10.1007/s10147-023-02380-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 06/27/2023] [Indexed: 07/10/2023]
Abstract
The goal of this systematic review was to identify all of the research within the last 10 years that investigated both the Albumin-Globulin Ratio (AGR) and outcomes of solid tumor cancer patients via quantitative prognostic variables. Multiple scientific databases were researched for journal articles that included keywords relating AGR to prognosis. Once isolated from the databases, the articles were de-duplicated and manually screened based on standardized inclusion/exclusion criteria in a blind format via Rayyan. The collective data were sorted by cancer type, corrected for population size, and used to calculate the average cut-off values for the most popular prognostic variables. In total, 18 independent types of cancer have been evaluated to see if AGR is a prognostic indicator based on multivariate analyses. The average cut-off value for AGR in overall survival was 1.356, while the average cut-off value for AGR in progression free survival was 1.292. AGR was found to be significantly associated with at least one prognostic variable in every type of cancer evaluated based on multivariate analyses. The ease of access and affordability of AGR makes it an invaluable tool applicable to nearly all patients. Overall, AGR is a proven prognostic variable that should always be considered in the evaluation of a solid tumor cancer patient's prognosis. Further research needs to be conducted studying the potential prognostic effect in more types of solid tumors.
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Affiliation(s)
- Will S Roberts
- Nova Southeastern University, Dr. Kiran C. Patel College of Osteopathic Medicine, 3400 Gulf to Bay Blvd, Clearwater, FL, 33759, USA.
| | - William Delladio
- Nova Southeastern University, Dr. Kiran C. Patel College of Osteopathic Medicine, 3400 Gulf to Bay Blvd, Clearwater, FL, 33759, USA
| | - Shawn Price
- Nova Southeastern University, Dr. Kiran C. Patel College of Osteopathic Medicine, 3400 Gulf to Bay Blvd, Clearwater, FL, 33759, USA
| | - Alec Murawski
- Nova Southeastern University, Dr. Kiran C. Patel College of Osteopathic Medicine, 3400 Gulf to Bay Blvd, Clearwater, FL, 33759, USA
| | - Hoang Nguyen
- Nova Southeastern University, Dr. Kiran C. Patel College of Osteopathic Medicine, 3400 Gulf to Bay Blvd, Clearwater, FL, 33759, USA
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Mao H, Yang F. Prognostic significance of albumin-to-globulin ratio in patients with renal cell carcinoma: a meta-analysis. Front Oncol 2023; 13:1210451. [PMID: 37538115 PMCID: PMC10394642 DOI: 10.3389/fonc.2023.1210451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 07/03/2023] [Indexed: 08/05/2023] Open
Abstract
Background Whether the albumin-to-globulin ratio (AGR) predicts the prognosis of renal cell carcinoma (RCC) remains controversial. Herein, we performed a meta-analysis to critically evaluate the relationship between the AGR and RCC prognosis, as well as the association between the AGR and the clinicopathological characteristics of RCC. Methods The PubMed, Web of Science, Embase, and Cochrane Library databases were thoroughly and comprehensively searched from their inception until 24 June 2023. To determine the predictive significance of the AGR, hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were calculated from the pooled data. The relationship between the AGR and the clinicopathological features of RCC was evaluated by estimating odds ratios (ORs) and 95% CIs in subgroup analyses. Results The meta-analysis included nine articles involving 5,671 RCC cases. A low AGR significantly correlated with worse overall survival (OS) (HR = 1.82, 95% CI = 1.37-2.41, p <0.001) and progression-free survival (PFS) (HR = 2.44, 95% CI = 1.61-3.70, p <0.001). Analysis of the pooled data also revealed significant associations between a low AGR and the following: female sex (OR = 1.48, 95% CI = 1.31-1.67, p <0.001), pT stage T3-T4 (OR = 4.12, 95% CI = 2.93-5.79, p <0.001), pN stage N1 (OR = 3.99, 95% CI = 2.40-6.64, p <0.001), tumor necrosis (OR = 3.83, 95% CI = 2.23-6.59, p <0.001), and Fuhrman grade 3-4 (OR = 1.82, 95% CI = 1.34-2.42, p <0.001). The AGR was not related to histology (OR = 0.83, 95% CI = 0.60-1.15, p = 0.267). Conclusion In patients with RCC, a low AGR strongly predicted poor OS and PFS and significantly correlated with clinicopathological features indicative of disease progression.
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Affiliation(s)
- Huaying Mao
- Clinical Laboratory, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, Zhejiang, China
| | - Fan Yang
- Clinical Laboratory, Huzhou Maternity and Child Health Care Hospital, Huzhou, Zhejiang, China
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Liu C, Jin B, Liu Y, Juhua O, Bao B, Yang B, Liu X, Yu P, Luo Y, Wang S, Teng Z, Song N, Qu J, Zhao J, Chen Y, Qu X, Zhang L. Construction of the prognostic model for small-cell lung cancer based on inflammatory markers: A real-world study of 612 cases with eastern cooperative oncology group performance score 0-1. Cancer Med 2023; 12:9527-9540. [PMID: 37015898 PMCID: PMC10166948 DOI: 10.1002/cam4.5728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 01/31/2023] [Accepted: 02/10/2023] [Indexed: 04/06/2023] Open
Abstract
OBJECTIVES This research aimed to explore the relationship between pre-treatment inflammatory markers and other clinical characteristics and the survival of small-cell lung cancer (SCLC) patients who received first-line platinum-based treatment and to construct nomograms for predicting overall survival (OS) and progression-free survival (PFS). METHODS A total of 612 patients diagnosed with SCLC between March 2008 and August 2021 were randomly divided into two cohorts: a training cohort (n = 459) and a validation cohort (n = 153). Inflammatory markers, clinicopathological factors, and follow-up information of patients were collected for each case. Cox regression was used to conduct univariate and multivariate analyses and the independent prognostic factors were adopted to develop the nomograms. Harrell's concordance index (C-index) and time-dependent receiver operating characteristic curve were used to verify model differentiation, calibration curve was used to verify consistency, and decision curve analysis was used to verify the clinical application value. RESULTS Our results showed that baseline C-reactive protein/albumin ratio, neutrophil/lymphocyte ratio, NSE level, hyponatremia, the efficacy of first-line chemotherapy, and stage were independent prognostic factors for both OS and PFS in SCLC. In the training cohort, the C-index of PFS and OS was 0.698 and 0.666, respectively. In the validation cohort, the C-index of PFS and OS was 0.727 and 0.747, respectively. The nomograms showed good predictability and high clinical value. Also, our new clinical models were superior to the US Veterans Administration Lung Study Group (VALG) staging for predicting the prognosis of SCLC. CONCLUSIONS The two prognostic nomograms of SCLC including inflammatory markers, VALG stage, and other clinicopathological factors had good predictive value and could individually assess the survival of patients.
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Affiliation(s)
- Chang Liu
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Bo Jin
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Yunpeng Liu
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Ouyang Juhua
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Bowen Bao
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Bowen Yang
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Xiuming Liu
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Ping Yu
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Ying Luo
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Shuo Wang
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Zan Teng
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Na Song
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Jinglei Qu
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Jia Zhao
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Ying Chen
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Xiujuan Qu
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
| | - Lingyun Zhang
- Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China
- Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China
- Liaoning Province Clinical Research Center for Cancer, Shenyang, China
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Oymak E, Guler OC, Onal C. Prognostic significance of albumin and globulin levels in cervical cancer patients treated with chemoradiotherapy. Int J Gynecol Cancer 2023; 33:19-25. [PMID: 36356983 DOI: 10.1136/ijgc-2022-003768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
OBJECTIVE Albumin-globulin ratio or albumin-globulin score predict survival in many cancers, but there are few data on cervical cancer patients. This study examined whether pre-treatment albumin and globulin levels, as well as the albumin-globulin ratio and albumin-globulin score, can predict treatment outcomes in cervical cancer patients undergoing definitive chemoradiotherapy. METHODS A retrospective analysis of cervical cancer patients treated between January 2006 and July 2014 was performed. Receiver operating characteristic curves for serum albumin and globulin levels, as well as albumin-globulin ratio values, were generated in order to determine the cut-off values for these parameters and to predict their sensitivity and specificity for predicting recurrence and survival. Univariate and multivariate analyses were used to identify prognostic factors for overall survival and progression-free survival. RESULTS A total of 139 patients were included. The median follow-up time was 11.5 years. The 5- and 10-year overall survival rates were 54.7% and 39.3%, while the 5- and 10-year progression-free survival rates were 48.9% and 36.4%, respectively. The optimal cut-off points were 3.79 g/dL for albumin, 3.27 g/dL for globulin, and 1.56 for albumin-globulin ratio. In the univariate analysis, significant prognostic factors for overall survival and progression-free survival were albumin-globulin ratio, albumin-globulin score, patient age, International Federation of Gynecology and Obstetrics (FIGO) stage, tumor size, lymph node metastasis, and treatment response. Older age, advanced stage, low albumin-globulin ratio, albumin-globulin score of 2, and inadequate treatment response had poor overall survival and progression-free survival in multivariable analysis. However, serum albumin and globulin levels were not found to be a significantly predictive factor for survival. There was a significant correlation between albumin levels, globulin levels, tumor size, stage, lymph node metastasis, and treatment response. CONCLUSIONS Pre-treatment albumin-globulin ratio and albumin-globulin score are useful prognostic factors in patients with cervical squamous cell cancer treated with definitive chemoradiotherapy, and may be suitable biomarkers for predicting treatment outcomes.
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Affiliation(s)
- Ezgi Oymak
- Division of Radiation Oncology, Iskenderun Gelisim Hospital, Hatay, Turkey
| | - Ozan Cem Guler
- Department of Radiation Oncology, Baskent University Adana Dr Turgut Noyan Research and Treatment Center, Adana, Turkey
| | - Cem Onal
- Department of Radiation Oncology, Baskent University Adana Dr Turgut Noyan Research and Treatment Center, Adana, Turkey .,Department of Radiation Oncology, Baskent University Faculty of Medicine, Ankara, Turkey
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The Predictive Significance of Prognostic Nutritional Index and Serum Albumin/Globulin Ratio on the Overall Survival of Penile Cancer Patients Undergoing Penectomy. Curr Oncol 2022; 29:7569-7578. [PMID: 36290873 PMCID: PMC9599963 DOI: 10.3390/curroncol29100596] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 09/25/2022] [Accepted: 10/04/2022] [Indexed: 11/07/2022] Open
Abstract
Objective: To assess the value of using the prognostic nutritional index (PNI) and serum albumin/globulin ratio (AGR) in predicting the overall survival (OS) of patients with penile cancer (PC) undergoing penectomy. Materials and methods: A retrospective analysis of 123 patients who were admitted to our hospital due to PC from April 2010 to September 2021 and who underwent penectomy were included in the study. The optimal cut-off value of the PNI and AGR was determined by receiver operating characteristic curve analysis. Kaplan-Meier analysis and the Cox proportional hazard model were used to evaluate the correlation between the PNI, AGR, and OS in patients with PC. Results: A total of 16 of the 123 patients died during the follow-up period, and the median follow-up time was 58.0 months. The best cut-off values of the PNI and AGR were set to 49.03 (95% confidence interval 0.705-0.888, Youden index = 0.517, sensitivity = 57.9%, specificity = 93.7%, p < 0.001) and 1.28 (95% confidence interval 0.610-0.860, Youden index = 0.404, sensitivity = 84.1%, specificity = 56.2%, p = 0.003). The Kaplan-Meier analysis showed that the OS of the patients in the high PNI group and the high AGR group was significantly higher than that of the patients in the low PNI group and the low AGR group (p < 0.001). The univariable analysis showed that the aCCI, the clinical N stage, the pathological stage, and the PNI, AGR, SII, and PLR are all predictors of OS in patients with PC (p < 0.05). The multivariable analysis showed that the PNI (risk rate [HR] = 0.091; 95% CI: 0.010-0.853; p = 0.036) and the AGR (risk rate [HR] = 0.171; 95% CI: 0.043-0.680; p = 0.012) are independent prognostic factors for predicting OS in patients with PC undergoing penectomy. Conclusions: Both the PNI score and the serum AGR are independent prognostic factors for predicting OS in patients with PC undergoing penectomy.
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Goins EC, Weber JM, Truong T, Moss HA, Previs RA, Davidson BA, Havrilesky LJ. Malnutrition as a risk factor for post-operative morbidity in gynecologic cancer: Analysis using a national surgical outcomes database. Gynecol Oncol 2022; 165:309-316. [PMID: 35241292 DOI: 10.1016/j.ygyno.2022.01.030] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 01/18/2022] [Accepted: 01/26/2022] [Indexed: 01/17/2023]
Abstract
OBJECTIVE To assess, using a national surgical outcomes database, the association of various malnutrition definitions with post-operative morbidity in three gynecologic malignancies. METHODS Patients undergoing resection of ovarian, uterine, or cervical cancer between 2005 and 2019 were identified using the National Surgical Quality Improvement Program (NSQIP) database. Patients were classified based on specific, pre-defined malnutrition criteria: severe malnutrition (Body Mass Index (BMI) <18.5 + 10% weight loss), European Society for Clinical Nutrition and Metabolism ((ESPEN1); BMI 18.5-22 + 10% weight loss), ESPEN2 (BMI < 18.5), American Cancer Society ((ACS); normal/overweight BMI + 10% weight loss), mild malnutrition (BMI 18.5-22), or albumin (<3.5 g/dL). Outcomes included 30-day major complications, readmission, reoperation. Modified Poisson regression estimated associations between definitions and outcomes. RESULTS Of 76,290 total patients undergoing surgery, those meeting malnutrition definitions were: severe-98 (0.1%), ESPEN1-148 (0.2%), ESPEN2-877 (1.1%), ACS-1028 (1.3%), mild-2853 (3.7%), and albumin (11.1%). Complication rates were: unplanned readmission-5.5%, reoperation-1.7%, major complications-13.5%. For ovarian cancer, ESPEN2 malnutrition was associated with higher readmissions (risk ratio 1.69; 95% confidence interval 1.29-2.20), reoperations (2.53; 1.70-3.77), and complications (1.36; 1.20-1.54). For uterine cancer, ACS malnutrition was associated with readmissions (2.74; 2.09-3.59), reoperations (3.61; 2.29-5.71) and complications (3.92; 3.40-4.53). For cervical cancer, albumin<3.5 g/dL was associated with readmissions (1.48; 1.01-2.19), reoperations (2.25; 1.17-4.34), and complications (2.59; 2.11-3.17). Albumin<3.5 was associated with adverse outcomes in ovarian and uterine cancer. CONCLUSIONS Preoperative risk assessments might be tailored using cancer-specific malnutrition criteria. Major complications, readmissions, and reoperations are all associated with the ESPEN2 definition for ovarian cancer, the ACS definition for uterine cancer, and with albumin<3.5 for all cancers.
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Affiliation(s)
- Emily C Goins
- School of Medicine, Duke University, Durham, North Carolina, United States of America
| | - Jeremy M Weber
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Tracy Truong
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Haley A Moss
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Duke University Health System, Durham, North Carolina, United States of America
| | - Rebecca A Previs
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Duke University Health System, Durham, North Carolina, United States of America
| | - Brittany A Davidson
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Duke University Health System, Durham, North Carolina, United States of America
| | - Laura J Havrilesky
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Duke University Health System, Durham, North Carolina, United States of America
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Li N, Song WJ, Gao J, Xu ZP, Long Z, Liu JY, He LY. The prognostic nutritional index predicts the biochemical recurrence of patients treated with robot-assisted laparoscopic radical prostatectomy. Prostate 2022; 82:221-226. [PMID: 34783377 DOI: 10.1002/pros.24263] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Revised: 10/13/2021] [Accepted: 10/15/2021] [Indexed: 12/24/2022]
Abstract
OBJECTIVE To evaluate the prognostic nutritional index (PNI) in predicting the biochemical recurrence (BCR) of patients treated with robot-assisted laparoscopic radical prostatectomy (RALP). METHODS The clinical data of 136 patients treated with RALP in the Department of Urology, The Third Xiangya Hospital of Central South University were retrospectively analyzed. The endpoint of observation was BCR. The area under the receiver operating characteristic (ROC) curve was evaluated to determine the optimal cutoff value of PNI. The correlation of the PNI with BCR was estimated using Kaplan-Meier analysis and Cox proportional hazards model. RESULTS The optimal cutoff value of the PNI was 46.03 according to the ROC curve. (95% confidence interval: 0.604-0.805, Youden index = 0.401, sensitivity = 82.5%, specificity = 57.6%, p < 0.01). Multivariate Cox analysis showed that clinical staging, prostate-specific antigen, and PNI were independent prognostic factors for predicting BCR in patients treated with RALP. CONCLUSION PNI is an independent prognostic factor for predicting BCR in patients treated with RALP. The incorporation of the PNI into risk assessments may provide additional prognostic information.
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Affiliation(s)
- Nichujie Li
- Department of Urology, The Third Xiangya Hospital, Central South University, Changsha, China
- Institute of Prostate Diseases, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Wei-Jie Song
- Department of Urology, The Third Xiangya Hospital, Central South University, Changsha, China
- Institute of Prostate Diseases, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Jun Gao
- Department of Urology, The Third Xiangya Hospital, Central South University, Changsha, China
- Institute of Prostate Diseases, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Zhi-Peng Xu
- Department of Urology, The Third Xiangya Hospital, Central South University, Changsha, China
- Institute of Prostate Diseases, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Zhi Long
- Department of Urology, The Third Xiangya Hospital, Central South University, Changsha, China
- Institute of Prostate Diseases, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Jian-Ye Liu
- Department of Urology, The Third Xiangya Hospital, Central South University, Changsha, China
- Institute of Prostate Diseases, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Le-Ye He
- Department of Urology, The Third Xiangya Hospital, Central South University, Changsha, China
- Institute of Prostate Diseases, The Third Xiangya Hospital, Central South University, Changsha, China
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