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      Use and outcomes of targeted therapies in early and metastatic HER2-positive breast cancer in Australia: protocol detailing observations in a whole of population cohort

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          Abstract

          Background

          The management of human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC) has changed dramatically with the introduction and widespread use of HER2-targeted therapies. However, there is relatively limited real-world information on patterns of use, effectiveness and safety in whole of population cohorts. The research programme detailed in this protocol will generate evidence on the prescribing patterns, safety monitoring and outcomes of patients with BC treated with HER2-targeted therapies in Australia.

          Methods/design

          Our ongoing research programme will involve a series of retrospective cohort studies that include every patient accessing Commonwealth-funded HER2-targeted therapies for the treatment of early BC and advanced BC in Australia. At the time of writing, our cohorts consist of 11 406 patients with early BC and 5631 with advanced BC who accessed trastuzumab and lapatinib between 2001 and 2014. Pertuzumab and trastuzumab emtansine were publicly funded for metastatic BC in 2015, and future data updates will include patients accessing these medicines. We will use dispensing claims for cancer and other medicines, medical service claims and demographics data for each patient accessing HER2-targeted therapies to undertake this research.

          Ethics and dissemination

          Ethics approval has been granted by the Population Health Service Research Ethics Committee and data access approval has been granted by the Australian Department of Human Services (DHS) External Review Evaluation Committee. Our findings will be reported in peer-reviewed publications, conference presentations and policy forums. By providing detailed information on the use and outcomes associated with HER2-targeted therapies in a national cohort treated in routine clinical care, our research programme will better inform clinicians and patients about the real-world use of these treatments and will assist third-party payers to better understand the use and economic costs of these treatments.

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          Most cited references42

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          Association of Pathologic Complete Response to Neoadjuvant Therapy in HER2-Positive Breast Cancer With Long-Term Outcomes: A Meta-Analysis.

          The expense and lengthy follow-up periods for randomized clinical trials (RCTs) of adjuvant systemic therapy in breast cancer make them impractical and even impossible to conduct. Randomized clinical trials of neoadjuvant systemic therapy for breast cancer may help resolve this dilemma.
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            The Australian Pharmaceutical Benefits Scheme data collection: a practical guide for researchers

            Background The Pharmaceutical Benefits Scheme (PBS) is Australia’s national drug subsidy program. This paper provides a practical guide to researchers using PBS data to examine prescribed medicine use. Findings Excerpts of the PBS data collection are available in a variety of formats. We describe the core components of four publicly available extracts (the Australian Statistics on Medicines, PBS statistics online, section 85 extract, under co-payment extract). We also detail common analytical challenges and key issues regarding the interpretation of utilisation using the PBS collection and its various extracts. Conclusions Research using routinely collected data is increasing internationally. PBS data are a valuable resource for Australian pharmacoepidemiological and pharmaceutical policy research. A detailed knowledge of the PBS, the nuances of data capture, and the extracts available for research purposes are necessary to ensure robust methodology, interpretation, and translation of study findings into policy and practice.
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              Construction and characteristics of the RxRisk-V: a VA-adapted pharmacy-based case-mix instrument.

              Assessment of disease burden is the key to many aspects of health care management. Patient diagnoses are commonly used for case-mix assessment. However, issues pertaining to diagnostic data availability and reliability make pharmacy-based strategies attractive. Our goal was to provide a reliable and valid pharmacy-based case-mix classification system for chronic diseases found in the Veterans Health Administration (VHA) population. To detail the development and category definitions of a VA-adapted version of the RxRisk (formerly the Chronic Disease Score); to describe category prevalence and reliability; to check category criterion validity against ICD-9 diagnoses; and to assess category-specific regression coefficients in concurrent and prospective cost models. Clinical and pharmacological review followed by cohort analysis of diagnostic, pharmacy, and utilization databases. 126,075 veteran users of VHA services in Washington, Oregon, Idaho, and Alaska. We used Kappa statistics to evaluate RxRisk category reliability and criterion validity, and multivariate regression to estimate concurrent and prospective cost models. The RxRisk-V classified 70.5% of the VHA Northwest Network 1998 users into an average of 2.61 categories. Of the 45 classes, 33 classes had good-excellent 1-year reliability and 25 classes had good-excellent criterion validity against ICD-9 diagnoses. The RxRisk-V accounts for a distinct proportion of the variance in concurrent (R2 = 0.18) and prospective cost (R2 = 0.10) models. The RxRisk-V provides a reliable and valid method for administrators to describe and understand better chronic disease burden of their treated populations. Tailoring to the VHA permits assessment of disease burden specific to this population.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2017
                24 January 2017
                : 7
                : 1
                : e014439
                Affiliations
                [1 ]Medicines Policy Research Unit, Centre for Big Data Research in Health, UNSW , Sydney, New South Wales, Australia
                [2 ]School of Medicine, University of Notre Dame Australia , Sydney, New South Wales, Australia
                [3 ]NHMRC Clinical Trials Centre, University of Sydney , Sydney, New South Wales, Australia
                [4 ]Sydney School of Public Health, Sydney Medical School, University of Sydney , Sydney, New South Wales, Australia
                [5 ]Centre for Health Economics Research and Evaluation, University of Technology Sydney , Sydney, New South Wales, Australia
                [6 ]Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute , Boston, Massachusetts, USA
                [7 ]University of Queensland , Brisbane, Queensland, Australia
                Author notes
                [Correspondence to ] Professor Sallie-Anne Pearson; sallie.pearson@ 123456unsw.edu.au
                Article
                bmjopen-2016-014439
                10.1136/bmjopen-2016-014439
                5278255
                28119394
                7bfa0030-8fb8-45e2-9d75-86297afb502c
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 27 September 2016
                : 22 December 2016
                : 29 December 2016
                Categories
                Oncology
                Protocol
                1506
                1717
                1692
                1703

                Medicine
                her2,breast cancer,trastuzumab,observational study,pharmacoepidemiology
                Medicine
                her2, breast cancer, trastuzumab, observational study, pharmacoepidemiology

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