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Prognostic value of bone scan index as an imaging biomarker in metastatic prostate cancer: a meta-analysis.

ABSTRACT: The prognostic value of the bone scan index (BSI) in metastatic prostate cancer (mPCa) remained controversial. Therefore, we performed a meta-analysis to determine the predictive value of BSI and survival in patients with mPCa.A literature search was performed in PubMed, Embase, Web of Science and Cochrane library databases. Hazard ratios (HRs), concordance indices (C-indices) were extracted to estimate the relationship between BSI and survival in patients with mPCa. Subgroup analyses were conducted on different types of mPCa, ethnics, cut-off values and sample sizes.14 high quality studies involving 1295 patients with mPCa were included in this meta-analysis. The pooled results indicated that high basline BSI and elevated BSI change on treatment (?BSI) were significantly predictive of poor overall survial (HR = 1.29, P < 0.001; HR = 1.27, P < 0.001, respectively). Baseline BSI was also significantly related to cancer specific survival (HR = 1.65, P = 0.019) and prostate specific antigen recurrence survival (HR = 2.26, P < 0.001). Subgroup analysis supported main results. Moreover, BSI could increase the C-indices of predictive models.Baseline BSI and ?BSI may be beneficial to mPCa prognosis in clinical monitor and treatment. Further high quality studies with larger sample size are required in the future.

SUBMITTER: Li D

PROVIDER: S-EPMC5663610 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Prognostic value of bone scan index as an imaging biomarker in metastatic prostate cancer: a meta-analysis.

Li Dongyang D Lv Hang H Hao Xuanyu X Dong Yudi Y Dai Huixu H Song Yongsheng Y

Oncotarget 20170729 48

<h4>Background</h4>The prognostic value of the bone scan index (BSI) in metastatic prostate cancer (mPCa) remained controversial. Therefore, we performed a meta-analysis to determine the predictive value of BSI and survival in patients with mPCa.<h4>Materials and methods</h4>A literature search was performed in PubMed, Embase, Web of Science and Cochrane library databases. Hazard ratios (HRs), concordance indices (C-indices) were extracted to estimate the relationship between BSI and survival in ...[more]

PMID: 29137438

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Project description:Importance:Prostate cancer commonly metastasizes to bone, and bone metastases are associated with pathologic fractures, pain, and reduced survival. Bone disease is routinely visualized using the technetium Tc 99m (99mTc) bone scan; however, the standard interpretation of bone scan data relies on subjective manual assessment of counting metastatic lesion numbers. There is an unmet need for an objective and fully quantitative assessment of bone scan data. Objective:To clinically assess in a prospectively defined analysis plan of a clinical trial the automated Bone Scan Index (aBSI) as an independent prognostic determinant of overall survival (OS) in men with metastatic castration-resistant prostate cancer (mCRPC). Design, Setting, and Participants:This investigation was a prospectively planned analysis of the aBSI in a phase 3 multicenter randomized, double-blind, placebo-controlled clinical trial of tasquinimod (10TASQ10). Men with bone metastatic chemotherapy-naïve CRPC were recruited at 241 sites in 37 countries between March 2011 and August 2015. The statistical analysis plan to clinically evaluate the aBSI was prospectively defined and locked before unmasking of the 10TASQ10 study. The analysis of aBSI was conducted between May 25, 2016, and June 3, 2017. Main Outcomes and Measures:The associations of baseline aBSI with OS, radiographic progression-free survival (rPFS), time to symptomatic progression, and time to opiate use for cancer pain. Results:Of the total 1245 men enrolled, 721 were evaluable for the aBSI. The mean (SD) age (available for 719 men) was 70.6 (8.0) years (age range, 47-90 years). The aBSI population was representative of the total study population based on baseline characteristics. The aBSI (median, 1.07; range, 0-32.60) was significantly associated with OS (hazard ratio [HR], 1.20; 95% CI, 1.14-1.26; P < .001). The median OS by aBSI quartile (lowest to highest) was 34.7, 27.3, 21.7, and 13.3 months, respectively. The discriminative ability of the aBSI (C index, 0.63) in prognosticating OS was significantly higher than that of the manual lesion counting (C index, 0.60) (P = .03). In a multivariable survival model, a higher aBSI remained independently associated with OS (HR, 1.06; 95% CI, 1.01-1.11; P = .03). A higher aBSI was also independently associated with time to symptomatic progression (HR, 1.18; 95% CI, 1.13-1.23; P < .001) and time to opiate use for cancer pain (HR, 1.21; 95% CI, 1.14-1.30; P < .001). Conclusions and Relevance:To date, this investigation is the largest prospectively analyzed study to validate the aBSI as an independent prognostic imaging biomarker of survival in mCRPC. These data support the prognostic utility of the aBSI as an objective imaging biomarker in the design and eligibility of clinical trials of systemic therapies for patients with mCRPC. Trial Registration:ClinicalTrials.gov Identifier: NCT01234311.

Project description:BackgroundThe lung immune prognostic index (LIPI) was first reported to predict the effectiveness of immune checkpoint inhibitors in patients with metastatic non-small cell lung cancer and there are no studies investigating the predictive value of LIPI for patients with PCa. This study explores the prognostic value of the LIPI in patients with metastatic hormone-sensitive prostate cancer (mHSPC) and metastatic castration-resistant prostate cancer (mCRPC).MethodsData from 502 patients with mHSPC primarily treated with maximal androgen blockade (MAB; 89% of patients received MAB) and 158 patients with mCRPC who received abiraterone were retrospectively analyzed. All cases were classified into LIPI-good, LIPI-intermediate, and LIPI-poor groups based on their LIPI score as calculated with the derived neutrophil-to-lymphocyte ratio and lactate dehydrogenase level. The potential for LIPI to be used in predicting mCRPC-free survival (CFS), prostate-specific antigen (PSA) response, PSA-progression-free survival (PSA-PFS), and overall survival (OS) was analyzed. A propensity score matching (PSM) methodology was performed to balance the baseline factors of the different groups.ResultsIn the mHSPC cohort, patients of the LIPI-good (mCFS: 25.7 months; mOS: 93.3 months), LIPI-intermediate (mCFS: 14.8 months; mOS: 51.9 months), and LIPI-poor group (mCFS: 6.8 months; mOS: 18.5 months) had sequentially worse clinical outcomes (P<0.001 for all pairwise comparisons). The results remained consistent after PSM. Multivariate Cox regression further confirmed that LIPI was an independent predictor of survival outcomes. Subgroup analysis verified that LIPI was associated with an unfavorable prognosis in all subgroups except for cases with visceral metastases or those receiving abiraterone or docetaxel. As for patients with mCRPC receiving abiraterone, LIPI was also an indicator of poor prognosis. Specifically, cases in the LIPI-good, LIPI-intermediate, and LIPI-poor groups had a ladder-shaped worse PSA response [71.4% (50/70) vs. 56.5% (39/69) vs. 36.8% (7/19); P=0.015], PSA-PFS (14.9 vs. 9.3 vs. 3.1 months; P<0.001), and OS (14.6 vs. 32.3 vs. 53.4 months; P<0.001). The results were robust even after PSM. Multivariate Cox regression confirmed that LIPI was an independent prognosticator of PSA-PFS and OS in patients with mCRPC treated with abiraterone.ConclusionsThis study demonstrated that the baseline LIPI was a significant prognostic biomarker for patients with both mHSPC and mCRPC and could potentially facilitate risk classification and clinical decision-making.

Project description:To screen target gene cluster by bioinformatics analysis and verify them by in vitro experiment and clinicopathological correlation analysis. We try to find a new biomarker with prognostic value for prostate cancer (PCa). 42 candidate marker genes were constructed by protein protein interaction (PPI) network and enriched by KEGG pathway to find out the gene cluster we are interested in. Prognostic model was established to preliminarily analyze the prognostic value of this gene cluster in PCa, and Cox risk regression was used for comparative analysis. Immunohistochemistry was used to detect the expression of each gene in clinical tissue microarray. Finally, we analyzed the correlation between each gene and their clinicopathological features of PCa combined with TCGA clinical data. Based on the analysis of PPI and KEGG, we found the target gene cluster (FCGR3A, HAVCR2, CCR7 and CD28). Prognostic model analysis showed that this gene cluster had the ability to predict biochemical recurrence, and the survival rate and ROC analysis showed favorable prediction effect. Univariate Cox regression analysis showed that the risk scores of Gleason score (GS), T stage, N stage and PSA were significantly different (P<0.05), and the risk ratio of high expression was 2.30 times that of low expression (P=0.004). However, it was not statistically significant in multivariate Cox regression analysis (P>0.05). The results of tissue microarray showed that FCGR3A and HAVCR2 were highly expressed in PCa (P<0.01), while the expression of CCR7 and CD28 had no significant difference (P>0.05). Kaplan-Meier analysis showed that there was significant difference in BCR free survival of FCGR3A and HAVCR2 (FCGR3A, P=0.010; HAVCR2, P=0.018), while the expression of CCR7 and CD28 had no significant difference on the survival and prognosis of PCa patients (P>0.05). TCGA clinical data analysis found that the expression of FCGR3A had a unique correlation with the clinicopathological features of PCa, which was closely related to the tumor stage. The expression of FCGR3A is related to BCR free survival of PCa patients. Therefore, FCGR3A is a new biomarker with potential prognostic value of PCa.

Dataset Information

Prognostic value of bone scan index as an imaging biomarker in metastatic prostate cancer: a meta-analysis.

Publications

Prognostic value of bone scan index as an imaging biomarker in metastatic prostate cancer: a meta-analysis.

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