Serum levels of chromogranin A are not predictive of high-grade, poorly differentiated prostate cancer: Results from an Italian biopsy cohort

Nunzio, Cosimo De; Albisinni, Simone; Presicce, Fabrizio; Lombardo, Riccardo; Tubaro, Andrea

doi:10.1016/j.urolonc.2012.07.012

Cited by 12 publications

(18 citation statements)

References 24 publications

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“…The basic characteristics of the included studies20–23,30–35 are described in Table 1. These studies (7 retrospective cohort studies20,21,23,30–33 and 3 prospective cohort studies22,34,35) were published between 2005 and 2018 and involved 3,172 participants. In total, 10 eligible cohorts with 3,172 patients were analyzed for OS outcomes,20–23,30–35 and 3 qualified studies with 139 patients were analyzed for PFS outcomes 21,31,35.…”

Section: Resultsmentioning

confidence: 99%

“…The sample sizes varied from 39 to 1,018. Among the included studies, five were conducted in Italy,20–22,30,31 two in Germany,33,35 two in USA,32,34 and one in UK 23. Furthermore, serum CHGA levels were measured in six studies,21–23,31,32 tissue CHGA levels were measured in one study20 and plasma CHGA levels were measured in three studies,30,33,34 respectively.…”

Section: Resultsmentioning

confidence: 99%

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<p>Chromogranin A is a predictor of prognosis in patients with prostate cancer: a systematic review and meta-analysis</p>

Guo

Wang

Xiang

et al. 2019

CMAR

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Background: The prognostic value of chromogranin-A (CHGA) as a biomarker of prostate cancer (PCa) has been evaluated extensively. However, to date the results still remain controversial. This study aims to perform a meta-analysis on previous studies in order to determine whether CHGA would be a biomarker for survival in PCa patients. Methods: MEDLINE, Embase, Web of Science, and Cochrane Library databases were searched to identify eligible studies published before September 2018, regarding the association of CHGA gene expression with survival outcomes in patients with PCa. Multivariate adjusted HRs and associated 95% CIs were calculated using random effects models. Results: Ten cohort studies involving 3,172 patients were finally included. According to the included studies, circulating CHGA levels were tested in serum, plasma, and tissues. The results showed an association between high CHGA expression and worse overall survival (OS) (HR=1.24, 95% CI: 1.07–1.44; P =0.004; I 2 =77.6%) in PCa patients. However, no significant association was observed between increasing CHGA expression and shorter progression-free survival (HR=1.73, 95% CI: 0.92–3.28; P =0.090; I 2 =73.9%). The results of sensitivity analysis validated the rationality and reliability of our analysis. Conclusion: Current evidence indicates that high CHGA expression is a potential marker for poor OS in PCa. Future studies are needed to explore tailored treatments that directly target CHGA for the improvement of survival in men with PCa.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

<p>Chromogranin A is a predictor of prognosis in patients with prostate cancer: a systematic review and meta-analysis</p>

Guo

Wang

Xiang

et al. 2019

CMAR

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“…Chromogranin-A (CgA), commonly expressed in neuroendocrine tumors, may be associated with poorly differentiated PCa [ 27 ]. However, a large prospective analysis of prostate biopsy specimens showed no link between serum CgA and high-grade PCa, indicating that the predictive role CgA is currently indeterminate [ 19 ].…”

Section: Discussionmentioning

confidence: 99%

“…Patients were identified for analysis if they had complete data available on multiple variables and those include, patient characteristics (age, race, BMI), tumor characteristics (clinical stage, pre-operative GS) as well as preoperative serum biomarkers, which have been shown in previous studies to be predictive of advanced prostate cancer. Markers such as free PSA, total PSA, prostate weight as a surrogate of volume [ 15 ], PTH and calcium [ 16 ], acid phosphatase [PAP] [ 17 ], testosterone [ 18 ], and chromogranin A [CgA]) [ 19 ] were used. Patients whose post-op Gleason score was 4 + 3 or higher or post-op pathologic stage was non-organ confined were classified in high-risk, and otherwise low-risk.…”

Section: Methodsmentioning

confidence: 99%

Predicting clinically significant prostate cancer based on pre-operative patient profile and serum biomarkers

et al. 2017

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Previous studies have reported association of multiple preoperative factors predicting clinically significant prostate cancer with varying results. We assessed the predictive model using a combination of hormone profile, serum biomarkers, and patient characteristics in order to improve the accuracy of risk stratification of patients with prostate cancer. Data on 224 patients from our prostatectomy database were queried. Demographic characteristics, including age, body mass index (BMI), clinical stage, clinical Gleason score (GS) as well as serum biomarkers, such as prostate-specific antigen (PSA), parathyroid hormone (PTH), calcium (Ca), prostate acid phosphatase (PAP), testosterone, and chromogranin A (CgA), were used to build a predictive model of clinically significant prostate cancer using logistic regression methods. We assessed the utility and validity of prediction models using multiple 10-fold cross-validation. Bias-corrected area under the receiver operating characteristics (ROC) curve (bAUC) over 200 runs was reported as the predictive performance of the models. On univariate analyses, covariates most predictive of clinically significant prostate cancer were clinical GS (OR 5.8, 95% CI 3.1–10.8; P < 0.0001; bAUC = 0.635), total PSA (OR 1.1, 95% CI 1.06–1.2; P = 0.0003; bAUC = 0.656), PAP (OR 1.5, 95% CI 1.1–2.1; P = 0.016; bAUC = 0.583), and BMI (OR 1.064, 95% C.I. 0.998, 1.134; P < 0.056; bAUC = 0.575). On multivariate analyses, the most predictive model included the combination of preoperative PSA, prostate weight, clinical GS, BMI and PAP with bAUC 0.771 ([2.5, 97.5] percentiles = [0.76, 0.78]). Our model using preoperative PSA, clinical GS, BMI, PAP, and prostate weight may be a tool to identify individuals with adverse oncologic characteristics and classify patients according to their risk profiles.

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“…Our present data revealed that SgII is a better indicator of PCa grade than the archetypal neuroendocrine marker CgA in the tested cohort. It should be noted that the value of CgA for the diagnosis of localised PCa [27,28] and for predicting time to recurrence and survival in patients with advanced PCa [3,5] is still a matter of debate. In fact, no other neuroendocrine marker (e.g.…”

Section: Discussionmentioning

confidence: 99%

Secretogranin II is overexpressed in advanced prostate cancer and promotes the neuroendocrine differentiation of prostate cancer cells

Courel

Yamani

Dionne‐Laporte

et al. 2014

European Journal of Cancer

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Serum levels of chromogranin A are not predictive of high-grade, poorly differentiated prostate cancer: Results from an Italian biopsy cohort

Cited by 12 publications

References 24 publications

<p>Chromogranin A is a predictor of prognosis in patients with prostate cancer: a systematic review and meta-analysis</p>

<p>Chromogranin A is a predictor of prognosis in patients with prostate cancer: a systematic review and meta-analysis</p>

Predicting clinically significant prostate cancer based on pre-operative patient profile and serum biomarkers

Secretogranin II is overexpressed in advanced prostate cancer and promotes the neuroendocrine differentiation of prostate cancer cells

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