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Duan YY, Deng J, Su DF, Li WQ, Han Y, Li ZX, Huan XZ, Zhu SH, Yang QL, Hu W, Xin MZ, Tang LQ, Mai HQ, Fan YY, He Y. Construction of a comprehensive nutritional index and comparison of its prognostic performance with the PNI and NRI for survival in older patients with nasopharyngeal carcinoma: a retrospective study. Support Care Cancer 2021; 29:5371-5381. [PMID: 33686519 DOI: 10.1007/s00520-021-06128-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 03/03/2021] [Indexed: 12/25/2022]
Abstract
OBJECTIVES To explore the relationship between the Comprehensive Nutritional Index (CNI) and survival in older patients with nasopharyngeal carcinoma (NPC) and to compare the prognostic performance of three nutritional indicators (CNI, Prognostic Nutritional Index (PNI), and Nutritional Risk Index (NRI)) for overall survival (OS). METHODS This retrospective study involved 309 older NPC patients in Guangzhou (China) from November 2006 to November 2017. The CNI comprised five parameters: the body mass index (BMI), usual body weight percentage (UBW%), hemoglobin (Hb) level, albumin level, and total lymphocyte count (TLC). All single nutritional indicators were evaluated before and immediately after treatment. The principal component analysis (PCA) was used for calculation of the CNI by single nutritional indicators after treatment. The cutoff point for the CNI was evaluated and logistic regression used to explore the risk factors for the CNI. Univariable, multivariable Cox regression, and Kaplan-Meier methods were applied for OS and disease-free survival (DFS) analyses. Cox proportional hazards models were used to compare the prognostic value of the CNI, PNI, and NRI for OS. RESULTS All single nutritional indicators decreased significantly after treatment (P < 0.05). The CNI cutoff point for mortality was 0.027, and the logistic regression indicated more complex treatments or higher cancer stage for NPC was associated with a low CNI (HR = 0.179; 95% CI: 0.037-0.856; 0.545, 0.367-0.811, respectively). In multivariable Cox regression, the CNI remained an independent prognostic factor of OS and DFS (HR = 0.468, 95% CI: 0.263-0.832; 0.527, 0.284-0.977, respectively). Kaplan-Meier curves showed that a low CNI was associated with worse OS and DFS (P = 0.001 and 0.013, respectively). The prognostic predictive performance of the CNI was superior to that of the PNI or NRI. CONCLUSIONS The CNI can be recommended as an appropriate indicator reflecting the integrated nutritional status of older NPC patients. A low CNI predicted a poor survival outcome and the prognostic performance of CNI was superior to PNI or NRI.
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Affiliation(s)
- Yu-Yu Duan
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Neurosurgery, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, China
| | - Jun Deng
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Pediatric Oncology, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, China
| | - Dong-Fang Su
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Clinical Nutrition, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China
| | - Wen-Qiong Li
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China
| | - Yuan Han
- School of Nursing, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Zhen-Xiu Li
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China
| | - Xue-Zhen Huan
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China
| | - Shi-Heng Zhu
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China
| | - Qiu-Lan Yang
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China
| | - Wen Hu
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China
| | - Ming-Zhu Xin
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China
| | - Lin-Quan Tang
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China
| | - Hai-Qiang Mai
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China
| | - Yu-Ying Fan
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China.
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China.
| | - Yan He
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, and Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, China.
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China.
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O'Mahony R, Basset C, Holton J, Vaira D, Roitt I. Comparison of image analysis software packages in the assessment of adhesion of microorganisms to mucosal epithelium using confocal laser scanning microscopy. J Microbiol Methods 2005; 61:105-26. [PMID: 15676201 DOI: 10.1016/j.mimet.2004.11.020] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2004] [Revised: 11/09/2004] [Accepted: 11/19/2004] [Indexed: 02/07/2023]
Abstract
We have compared current image analysis software packages in order to find the most useful one for assessing microbial adhesion and inhibition of adhesion to tissue sections. We have used organisms of different sizes, the bacterium Helicobacter pylori and the yeast Candida albicans. Adhesion of FITC-labelled H. pylori and C. albicans was assessed by confocal microscopy. Four different Image analysis software packages, NIH-Image, IP Lab, Image Pro+, and Metamorph, were compared for their ability to quantify adhesion of the two organisms and several quantification methods were devised for each package. For both organisms, the dynamic range that could be detected by the software packages was 1x10(6)-1x10(9) cells/ml. Of the four software packages tested, our results showed that Metamorph software, using our 'Region of Interest' method, with the software's 'Standard Area Method' of counting, was the most suitable for quantifying adhesion of both organisms because of its unique ability to separate clumps of microbial cells. Moreover, fewer steps were required. By pre-incubating H. pylori with the glycoconjugate Lewis b-HSA, an inhibition of binding of 48.8% was achieved using 250 mug/ml Lewis b-HSA. The method we have devised using Metamorph software, provides a simple, quick and accurate way of quantifying adhesion and inhibition of adhesion of microbial cells to the epithelial surface of tissue sections. The method can be applied to organisms ranging in size from small bacteria to larger yeast cells.
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Affiliation(s)
- Rachel O'Mahony
- Centre for Infectious Diseases and International Health, Royal Free and University College London Medical School, The Windeyer Building, 46 Cleveland Street, London W1T 4JF, UK.
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