Literature DB >> 19010854

Predictive value of plasma hepatocyte growth factor/scatter factor levels in patients with clinically localized prostate cancer.

Amit Gupta1, Pierre I Karakiewicz, Claus G Roehrborn, Yair Lotan, Alexandre R Zlotta, Shahrokh F Shariat.   

Abstract

PURPOSE: Hepatocyte growth factor/scatter factor (HGF/SF) is a multifunctional cytokine that is involved in cancer growth, motility, invasion, and angiogenesis. We assessed whether preoperative plasma levels of HGF can enhance the accuracy of standard models for predicting pathologic features and clinical outcomes. EXPERIMENTAL
DESIGN: The study comprised 421 consecutive patients treated with radical prostatectomy and bilateral lymphadenectomy for clinically localized prostatic adenocarcinoma. HGF/SF was measured using a commercially available immunoassay. Multivariate logistic regression was used to assess the relationship between plasma HGF/SF and pathologic features. Multivariate Cox regression was used to predict disease recurrence. One thousand bootstrap replicates were created for internal validation and predictive accuracies were estimated for each model.
RESULTS: Plasma HGF/SF levels were significantly elevated in patients with lymph node and/or seminal vesicle invasion (P < 0.0001 and P = 0.007, respectively). Preoperative plasma HGF/SF level was an independent predictor of lymph node invasion [odds ratio (OR) for every 100 pg/mL increase in HGF/SF, 1.82; 95% confidence interval (95% CI), 1.33-2.49] and seminal vesicle invasion (OR, 1.18; 95% CI, 1.06-1.3). Addition of HGF/SF increased the accuracy of a base model that included standard preoperative variables for prediction of lymph node invasion by 6.7% (predictive accuracy, 98.4%). HGF/SF also independently predicted disease recurrence after surgery (hazard ratio, 1.07; 95% CI, 1.0-1.15).
CONCLUSIONS: Preoperative plasma level of HGF/SF is an independent predictor of prostate cancer metastasis to lymph nodes and disease recurrence after surgery. Use of HGF may help in therapeutic decision-making and enrollment into clinical trials.

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Year:  2008        PMID: 19010854     DOI: 10.1158/1078-0432.CCR-07-5110

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  19 in total

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