{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T18:10:44Z","timestamp":1789409444646,"version":"build-2803163510"},"reference-count":20,"publisher":"CSIRO Publishing","issue":"5","license":[{"start":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T00:00:00Z","timestamp":1763424000000},"content-version":"vor","delay-in-days":2903,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,12,7]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives:<\/jats:title>\n                    <jats:p>Dispensing claims are used increasingly to investigate the real-world use and impact of prescribed medicines. Claims databases, established for payment purposes, lack clinical data and only capture prescriptions for which insurers pay a contribution. We compare Australia\u2019s Pharmaceutical Benefits Scheme (PBS) dispensing claims of HER2-positive early breast cancer patients with medicines prescribed and administered to determine the accuracy of dispensing data to identify treatment protocols, number of treatment cycles and durations of therapy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method:<\/jats:title>\n                    <jats:p>Our cohort comprised 110 female HER2-positive early breast cancer patients who started treatment at four cancer centres in New South Wales, Australia, between 2008 and 2011. Patients consented to retrospective medical chart audit and linkage to PBS claims data. We constructed protocols from prescribing and dispensing records independently, based on the timing of trastuzumab and cytotoxic treatments; and estimated the median number of treatment cycles and duration of therapy by protocol.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Patients\u2019 median age was 53 years (range 21\u201386). Two chemotherapy protocols accounted for 90% of chemotherapy protocols: doxorubicin and cyclophosphamide followed by a paclitaxel or docetaxel and trastuzumab (known as ACTH; 58.2%) and trastuzumab with docetaxel, carboplatin and trastuzumab (known as TCH; 31.2%). Seventy-six patients (69.1%) were assigned the same protocols based on prescribing and claims data. Twenty-six of the protocols that did not match were due to the absence of cyclophosphamide in PBS data because it falls below the patient copayment for general PBS beneficiaries. Compared with prescription data, the number of treatment cycles was underestimated in dispensing data (30 vs 44 for ACTH and 26.5 vs 29 for TCH); however, median durations of therapy were well matched (422 vs 442 days for ACTH and 368 vs 367 for TCH).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>PBS dispensing data provide an alternative option to prescription data for estimating cancer medicine use. Recent changes to PBS data capture that include all medicines costing less than the copayment will strengthen the capacity of PBS data to reflect prescribing practice in all patients, including treatment protocols and duration of therapy in patients with complete ascertainment of PBS dispensing history.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.17061\/phrp2751744","type":"journal-article","created":{"date-parts":[[2017,12,5]],"date-time":"2017-12-05T23:18:41Z","timestamp":1512515921000},"source":"Crossref","is-referenced-by-count":6,"title":["Retrospective comparison of Australia\u2019s Pharmaceutical Benefits Scheme claims data with prescription data in HER2-positive early breast cancer patients, 2008\u20132012"],"prefix":"10.1071","volume":"27","author":[{"given":"Carole","family":"Harris","sequence":"first","affiliation":[{"name":"A Faculty of Medicine, UNSW Sydney, Australia"},{"name":"B Department of Medical Oncology, St George Hospital, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin","family":"Daniels","sequence":"additional","affiliation":[{"name":"C Medicines Policy Research Unit, Centre for Big Data Research in Health, UNSW Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robyn","family":"Ward","sequence":"additional","affiliation":[{"name":"A Faculty of Medicine, UNSW Sydney, Australia"},{"name":"D University of Queensland, Brisbane, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sallie-Anne","family":"Pearson","sequence":"additional","affiliation":[{"name":"C Medicines Policy Research Unit, Centre for Big Data Research in Health, UNSW Sydney, Australia"},{"name":"E Menzies Centre for Health Policy, University of Sydney, NSW, Australia"},{"name":"F Faculty of Pharmacy, University of Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"67","published-online":{"date-parts":[[2017,12,7]]},"reference":[{"key":"2026012916562989300_R1","doi-asserted-by":"crossref","unstructured":"Kelman CW, Pearson SA, Day RO, Holman CD, Kliewer EV, Henry DA. 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