Literature DB >> 32197590

Prognostic value of the bone scan index in patients with metastatic castration-resistant prostate cancer: a systematic review and meta-analysis.

Hualin Song1,2,3, Song Jin4, Peng Xiang5, Shuai Hu6,7,8, Jie Jin9,10,11.   

Abstract

BACKGROUND: Many studies have reported the prognostic significance of the bone scan index (BSI) for metastatic castration-resistant prostate cancer (mCRPC); however, these reports are controversial. This study investigated the BSI in mCRPC and its relationship with prognosis.
METHODS: The PubMed, Cochrane, and Embase databases were searched systematically for relevant articles published before September 1, 2019. Hazard ratios (HRs) were used to investigate the prognostic value.
RESULTS: This study finally identified 9 eligible studies. The results suggested that high baseline BSI predicted poor OS (HR = 1.331, 95% CI: 1.081-1.640) and that elevated ΔBSI also predicted poor OS (HR = 1.220, 95% CI: 1.015-1.467). The subgroup analysis stratified by ethnicity showed that the baseline BSI and ΔBSI predicted poor OS in the Asian population but not in the Caucasian population. We also performed a subgroup analysis based on the different cut-off values of baseline BSI. The subgroup of ≤1 showed a significant association with OS in mCRPC patients.
CONCLUSION: Our study demonstrated that high baseline BSI and elevated ΔBSI predicted poor OS in patients with mCRPC. Hence, the BSI can serve as a prognostic indicator for mCRPC patients and may therefore guide clinical treatment in the future.

Entities:  

Keywords:  BSI; Bone scan index; Meta-analysis; Metastatic castration-resistant prostate cancer; mCRPC

Year:  2020        PMID: 32197590     DOI: 10.1186/s12885-020-06739-y

Source DB:  PubMed          Journal:  BMC Cancer        ISSN: 1471-2407            Impact factor:   4.430


  2 in total

1.  A novel tool for improving the interpretation of isotope bone scans in metastatic prostate cancer.

Authors:  Ali H D Alshehri; Sarah O S Osman; Kevin M Prise; Caoimhghin Campfield; P G Turner; Suneil Frcr PhD Jain; Joe M O'Sullivan; Aidan J Cole
Journal:  Br J Radiol       Date:  2020-09-03       Impact factor: 3.039

2.  Prediction of All-Cause Mortality Based on Stress/Rest Myocardial Perfusion Imaging (MPI) Using Deep Learning: A Comparison between Image and Frequency Spectra as Input.

Authors:  Da-Chuan Cheng; Te-Chun Hsieh; Yu-Ju Hsu; Yung-Chi Lai; Kuo-Yang Yen; Charles C N Wang; Chia-Hung Kao
Journal:  J Pers Med       Date:  2022-07-05
  2 in total

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