Literature DB >> 28752926

Prognostic nutritional index predicts initial response to treatment and prognosis in metastatic castration-resistant prostate cancer patients treated with abiraterone.

Liancheng Fan1, Xiao Wang2, Chenfei Chi1, Yanqing Wang1, Wen Cai1, Xiaoguang Shao1, Fan Xu1, Jiahua Pan1, Yinjie Zhu1, Xun Shangguan1, Zhixiang Xin1, Jianian Hu1, Shaowei Xie1, Rui Wang3, Lixin Zhou1, Baijun Dong1, Wei Xue1.   

Abstract

OBJECTIVE: To determine if prognostic nutritional index (PNI) and its variation could predict initial response to treatment and prognosis in metastatic castration-resistant prostate cancer (mCRPC) patients treated with Abiraterone (AA). PATIENTS AND METHODS: One-hundred-twelve chemotherapy pretreated or chemotherapy-naive patients were scheduled for systemic treatment with AA. PNI levels were measured before and after one month of AA treatment. Univariate and multivariate logistic regression analyses were used to identify predictive factors of initial response to AA treatment. Univariable and Multivariable Cox regression analyses were performed to determine prognostic factors that were associated with PSA progression-free survival (PSA-PFS), radiographic PFS (rPFS) and overall survival (OS). The Harrell concordance index with variables only or combined PNI data were used to evaluate the prognostic accuracy.
RESULTS: Eighty-one (72.3%) of 112 patients showed initial response to AA treatment, in which 15 experienced PSA flare during AA treatment. In multivariate logistic regression analyses, high baseline PNI level, PSA level decrease during the first month of AA treatment and PNI level elevation during the first month of AA treatment were significantly correlated with initial response to AA treatment. In multivariate Cox regression analysis, low PNI level remained significant predictors of OS, rPFS and PSA-PFS. The estimated c-index of the multivariate model for OS increased from 0.82 without PNI to 0.83 when PNI added.
CONCLUSION: Independent of PSA level variation, PNI level elevation during the first month of AA treatment and high baseline PNI level were significantly correlated with initial response to AA treatment. In addition, low pretreatment PNI level is a negative independent prognosticator of survival outcomes in mCRPC treated with AA and also increases the accuracy of established prognostic model.
© 2017 The Authors. The Prostate Published by Wiley Periodicals, Inc.

Entities:  

Keywords:  PSA flare; abiraterone acetate; metastatic castration-resistant prostate cancer; prognostic model

Mesh:

Substances:

Year:  2017        PMID: 28752926     DOI: 10.1002/pros.23381

Source DB:  PubMed          Journal:  Prostate        ISSN: 0270-4137            Impact factor:   4.104


  10 in total

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Authors:  Yupeng Guan; Haiyun Xiong; Yupeng Feng; Guolong Liao; Tongyu Tong; Jun Pang
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2.  The prognostic value of pretreatment prognostic nutritional index in patients with small cell lung cancer and it's influencing factors: a meta-analysis of observational studies.

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3.  Prognostic value of prognostic nutritional index in lung cancer: a meta-analysis.

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4.  Pretreatment elevated prognostic nutritional index predicts a favorable prognosis in patients with prostate cancer.

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5.  Abiraterone acetate for chemotherapy-naive metastatic castration-resistant prostate cancer: a single-centre prospective study of efficacy, safety, and prognostic factors.

Authors:  Liancheng Fan; Baijun Dong; Chenfei Chi; Yanqing Wang; Yiming Gong; Jianjun Sha; Jiahua Pan; Xun Shangguan; Yiran Huang; Lixin Zhou; Wei Xue
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6.  Pre-treatment prognostic nutritional index may serve as a potential biomarker in urinary cancers: a systematic review and meta-analysis.

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Authors:  Wenjie Chen; Tao Wei; Zhihui Li; Rixiang Gong; Jianyong Lei; Jingqiang Zhu; Tao Huang
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10.  Serum Pre-Albumin Predicts the Clinical Outcome in Metastatic Castration-Resistant Prostate Cancer Patients Treated With Abiraterone.

Authors:  Liancheng Fan; Chenfei Chi; Sanwei Guo; Yanqing Wang; Wen Cai; Xiaoguang Shao; Fan Xu; Jiahua Pan; Yinjie Zhu; Xun Shangguan; Zhixiang Xin; Jianian Hu; Hongyang Qian; Shaowei Xie; Rui Wang; Lixin Zhou; Baijun Dong; Wei Xue
Journal:  J Cancer       Date:  2017-09-20       Impact factor: 4.207

  10 in total

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