19
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      What is the optimal systemic treatment of men with metastatic, hormone-naive prostate cancer? A STOPCAP systematic review and network meta-analysis

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Our prior Systemic Treatment Options for Cancer of the Prostate systematic reviews showed improved survival for men with metastatic hormone-naive prostate cancer when abiraterone acetate plus prednisolone/prednisone (AAP) or docetaxel (Doc), but not zoledronic acid (ZA), were added to androgen-deprivation therapy (ADT). Trial evidence also suggests a benefit of combining celecoxib (Cel) with ZA and ADT. To establish the optimal treatments, a network meta-analysis (NMA) was carried out based on aggregate data (AD) from all available studies.

          Methods

          Overall survival (OS) and failure-free survival data from completed Systemic Treatment Options for Cancer of the Prostate reviews of Doc, ZA and AAP and from recent trials of ZA and Cel contributed to this comprehensive AD-NMA. The primary outcome was OS. Correlations between treatment comparisons within one multi-arm, multi-stage trial were estimated from control-arm event counts. Network consistency and a common heterogeneity variance were assumed.

          Results

          We identified 10 completed trials which had closed to recruitment, and one trial in which recruitment was ongoing, as eligible for inclusion. Results are based on six trials including 6204 men (97% of men randomised in all completed trials). Network estimates of effects on OS were consistent with reported comparisons with ADT alone for AAP [hazard ration (HR) = 0.61, 95% confidence interval (CI) 0.53–0.71], Doc (HR = 0.77, 95% CI 0.68–0.87), ZA + Cel (HR = 0.78, 95% CI 0.62–0.97), ZA + Doc (HR = 0.79, 95% CI 0.66–0.94), Cel (HR = 0.94 95% CI 0.75–1.17) and ZA (HR = 0.90 95% CI 0.79–1.03). The effect of ZA + Cel is consistent with the additive effects of the individual treatments. Results suggest that AAP has the highest probability of being the most effective treatment both for OS (94% probability) and failure-free survival (100% probability). Doc was the second-best treatment of OS (35% probability).

          Conclusions

          Uniquely, we have included all available results and appropriately accounted for inclusion of multi-arm, multi-stage trials in this AD-NMA. Our results support the use of AAP or Doc with ADT in men with metastatic hormone-naive prostate cancer. AAP appears to be the most effective treatment, but it is not clear to what extent and whether this is due to a true increased benefit with AAP or the variable features of the individual trials. To fully account for patient variability across trials, changes in prognosis or treatment effects over time and the potential impact of treatment on progression, a network meta-analysis based on individual participant data is in development.

          Related collections

          Most cited references26

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials

          Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Practical methods for incorporating summary time-to-event data into meta-analysis

            Background In systematic reviews and meta-analyses, time-to-event outcomes are most appropriately analysed using hazard ratios (HRs). In the absence of individual patient data (IPD), methods are available to obtain HRs and/or associated statistics by carefully manipulating published or other summary data. Awareness and adoption of these methods is somewhat limited, perhaps because they are published in the statistical literature using statistical notation. Methods This paper aims to 'translate' the methods for estimating a HR and associated statistics from published time-to-event-analyses into less statistical and more practical guidance and provide a corresponding, easy-to-use calculations spreadsheet, to facilitate the computational aspects. Results A wider audience should be able to understand published time-to-event data in individual trial reports and use it more appropriately in meta-analysis. When faced with particular circumstances, readers can refer to the relevant sections of the paper. The spreadsheet can be used to assist them in carrying out the calculations. Conclusion The methods cannot circumvent the potential biases associated with relying on published data for systematic reviews and meta-analysis. However, this practical guide should improve the quality of the analysis and subsequent interpretation of systematic reviews and meta-analyses that include time-to-event outcomes.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial.

              To present some simple graphical and quantitative ways to assist interpretation and improve presentation of results from multiple-treatment meta-analysis (MTM). We reanalyze a published network of trials comparing various antiplatelet interventions regarding the incidence of serious vascular events using Bayesian approaches for random effects MTM, and we explore the advantages and drawbacks of various traditional and new forms of quantitative displays and graphical presentations of results. We present the results under various forms, conventionally based on the mean of the distribution of the effect sizes; based on predictions; based on ranking probabilities; and finally, based on probabilities to be within an acceptable range from a reference. We show how to obtain and present results on ranking of all treatments and how to appraise the overall ranks. Bayesian methodology offers a multitude of ways to present results from MTM models, as it enables a natural and easy estimation of all measures based on probabilities, ranks, or predictions. Copyright © 2011 Elsevier Inc. All rights reserved.
                Bookmark

                Author and article information

                Journal
                Ann Oncol
                Ann. Oncol
                annonc
                Annals of Oncology
                Oxford University Press
                0923-7534
                1569-8041
                May 2018
                23 February 2018
                23 February 2018
                : 29
                : 5
                : 1249-1257
                Affiliations
                [1 ]MRC Clinical Trials Unit at UCL, London
                [2 ]Salford Royal NHS Foundation Trust, Salford, UK
                [3 ]Gustave-Roussy, University of Paris Sud, Villejuif
                [4 ]Department of Medical Oncology, Institut Paoli Calmettes, Marseille, France
                [5 ]Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham
                [6 ]Queen Elizabeth Hospital, Birmingham
                [7 ]School of Medicine, Cardiff University, Cardiff, UK
                [8 ]Dana-Farber Cancer Institute, Harvard Medical School, Boston, USA
                Author notes
                Correspondence to: Dr Claire L. Vale, MRC Clinical Trials Unit at UCL, Meta-analysis Group, 90 High Holborn, 2nd Floor, London WC1V 6LJ, UK. Tel: +44-207-670-4723; E-mail: claire.vale@ 123456ucl.ac.uk

                C. L. Vale and D. J. Fisher authors contributed equally as senior authors.

                Author information
                http://orcid.org/0000-0001-5157-0634
                http://orcid.org/0000-0002-9323-1371
                Article
                mdy071
                10.1093/annonc/mdy071
                5961275
                29788164
                d365dc4c-a04a-43a2-a040-8d61bfba7bbc
                © The Author(s) 2018. Published by Oxford University Press on behalf of the European Society for Medical Oncology.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Pages: 9
                Funding
                Funded by: MRC 10.13039/501100000265
                Categories
                Original Articles
                Urogenital Tumors

                Oncology & Radiotherapy
                prostate cancer,abiraterone,docetaxel,systematic review,network meta-analysis,androgen-deprivation therapy

                Comments

                Comment on this article