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Ga-PSMA-11 PET/CT-derived metabolic tumor parameters showed promising results for evaluation of treatment response. Especially, TL-PSMA demonstrated higher agreement rates with biochemical response compared to SUVmax. Larger, ideally prospective trials are needed to help to reveal the full potential of metabolic parameters derived from PET imaging with Ga-PSMA-11.

Summary Background Src kinase-mediated interactions between prostate cancer cells and osteoclasts might promote bone metastasis. Dasatinib inhibits tyrosine kinases, including Src kinases. Data suggests that dasatinib kinase inhibition leads to antitumour activity, affects osteoclasts, and has synergy with docetaxel, a first-line chemotherapy for metastatic castration-resistant prostate cancer. We assessed whether dasatinib plus docetaxel in chemotherapy-naive men with metastatic castration-resistant prostate cancer led to greater efficacy than with docetaxel alone. Methods In this double-blind, randomised, placebo-controlled phase 3 study, we enrolled men of 18 years or older with chemotherapy-naive, metastatic, castration-resistant prostate cancer, and adequate organ function from 186 centres across 25 countries. Eligible patients were randomly assigned (1:1) via an interactive voice response system to receive docetaxel (75 mg/m2 intravenously every 3 weeks, plus oral prednisone 5 mg twice daily), plus either dasatinib (100 mg orally once daily) or placebo until disease progression or unacceptable toxicity. Randomisation was stratified by Eastern Cooperative Oncology Group performance status (0–1 vs 2), bisphosphonate use (yes vs no), and urinary N-telopeptide (uNTx) value (<60 μmol/mol creatinine vs ≥60 μmol/mol creatinine). All patients, investigators, and personnel involved in study conduct and data analyses were blinded to treatment allocation. The primary endpoint was overall survival, analysed by intention to treat. The trial is registered with ClinicalTrials.gov, number NCT00744497. Findings Between Oct 30, 2008, and April 11, 2011, 1522 eligible patients were randomly assigned to treatment; 762 patients were assigned to dasatinib and 760 to placebo. At final analysis, median follow-up was 19.0 months (IQR 11.2–25.1) and 914 patients had died. Median overall survival was 21.5 months (95% CI 20.3–22.8) in the dasatinib group and 21.2 months (20.0–23.4) in the placebo group (stratified hazard ratio [HR] 0.99, 95.5% CI 0.87–1.13; p=0.90). The most common grade 3–4 adverse events included diarrhoea (58 [8%] patients in the dasatinib group vs 27 [4%] patients in the placebo group), fatigue (62 [8%] vs 42 [6%]), and asthenia (40 [5%] vs 23 [3%]); grade 3–4 pleural effusions were uncommon (ten [1%] vs three [<1%]). Interpretation The addition of dasatinib to docetaxel did not improve overall survival for chemotherapy-naive men with metastatic castration-resistant prostate cancer. This study does not support the combination of dasatinib and docetaxel in this population of patients. Funding Bristol-Myers Squibb.

Purpose To critically review and illustrate current methodologic and statistical considerations for bladder cancer biomarker discovery and evaluation. Methods Original, review, and methodological articles, and editorials were reviewed and summarized. Results Biomarkers may be useful at multiple stages of bladder cancer management: early detection, diagnosis, staging, prognosis, and treatment; however, few novel biomarkers are currently used in clinical practice. The reasons for this disjunction are manifold and reflect the long and difficult pathway from candidate biomarker discovery to clinical assay, and the lack of coherent and comprehensive processes (pipelines) for biomarker development. Conceptually, the development of new biomarkers should be a process that is similar to therapeutic drug evaluation - a highly regulated process with carefully regulated phases from discovery to human applications. In a further effort to address the pervasive problem of inadequacies in the design, analysis, and reporting of biomarker prognostic studies, a set of reporting recommendations are discussed. For example, biomarkers should provide unique information that adds to known clinical and pathologic information. Conventional multivariable analyses are not sufficient to demonstrate improved prediction of outcomes. Predictive models, including or excluding any new putative biomarker, needs to show clinically significant improvement of performance in order to claim any real benefit. Towards this end, proper model building, avoidance of overfitting, and external validation are crucial. In addition, it is important to choose appropriate performance measures dependent on outcome and prediction type and to avoid use of cut-points. Biomarkers providing a continuous score provide potentially more useful information than cut-points since risk fits a continuum model. Combination of complementary and independent biomarkers is likely to better capture the biologic potential of a tumor than any single biomarker. Finally, methods that incorporate clinical consequences such as decision curve analysis are crucial to the evaluation of biomarkers. Conclusions Attention to sound design and statistical practice should be delivered as early as possible and will help maximize the promise of biomarkers for patient care. Studies should include a measure of predictive accuracy and clinical decision-analysis. External validation using data from an independent cohort provides the strongest evidence that a model is valid. There is a need for adequately assessed clinical biomarkers in bladder cancer.

ClinicalTrials.gov identifier NCT00732914, www.clinicaltrials.gov.