General Practice and Primary Care - Research Publications

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    Data Resource Profile: Victorian Comprehensive Cancer Centre Data Connect
    Lee, A ; McCarthy, D ; Bergin, RJ ; Drosdowsky, A ; Gutierrez, JM ; Kearney, C ; Philip, S ; Rafiq, M ; Venning, B ; Wawryk, O ; Zhang, J ; Emery, J (OXFORD UNIV PRESS, 2023-12-25)
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    Optimization of a Quality Improvement Tool for Cancer Diagnosis in Primary Care: Qualitative Study
    Chima, S ; Martinez-Gutierrez, J ; Hunter, B ; Manski-Nankervis, J-A ; Emery, J (JMIR PUBLICATIONS, INC, 2022-08)
    BACKGROUND: The most common route to a diagnosis of cancer is through primary care. Delays in diagnosing cancer occur when an opportunity to make a timely diagnosis is missed and is evidenced by patients visiting the general practitioner (GP) on multiple occasions before referral to a specialist. Tools that minimize prolonged diagnostic intervals and reduce missed opportunities to investigate patients for cancer are therefore a priority. OBJECTIVE: This study aims to explore the usefulness and feasibility of a novel quality improvement (QI) tool in which algorithms flag abnormal test results that may be indicative of undiagnosed cancer. This study allows for the optimization of the cancer recommendations before testing the efficacy in a randomized controlled trial. METHODS: GPs, practice nurses, practice managers, and consumers were recruited to participate in individual interviews or focus groups. Participants were purposively sampled as part of a pilot and feasibility study, in which primary care practices were receiving recommendations relating to the follow-up of abnormal test results for prostate-specific antigen, thrombocytosis, and iron-deficiency anemia. The Clinical Performance Feedback Intervention Theory (CP-FIT) was applied to the analysis using a thematic approach. RESULTS: A total of 17 interviews and 3 focus groups (n=18) were completed. Participant themes were mapped to CP-FIT across the constructs of context, recipient, and feedback variables. The key facilitators to use were alignment with workflow, recognized need, the perceived importance of the clinical topic, and the GPs' perception that the recommendations were within their control. Barriers to use included competing priorities, usability and complexity of the recommendations, and knowledge of the clinical topic. There was consistency between consumer and practitioner perspectives, reporting language concerns associated with the word cancer, the need for more patient-facing resources, and time constraints of the consultation to address patients' worries. CONCLUSIONS: There was a recognized need for the QI tool to support the diagnosis of cancer in primary care, but barriers were identified that hindered the usability and actionability of the recommendations in practice. In response, the tool has been refined and is currently being evaluated as part of a randomized controlled trial. Successful and effective implementation of this QI tool could support the detection of patients at risk of undiagnosed cancer in primary care and assist in preventing unnecessary delays.
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    The SMARTscreen Trial: a randomised controlled trial investigating the efficacy of a GP-endorsed narrative SMS to increase participation in the Australian National Bowel Cancer Screening Program
    Wood, A ; Emery, JD ; Jenkins, M ; Chondros, P ; Campbell, T ; Wenkart, E ; O'Reilly, C ; Cowie, T ; Dixon, I ; Toner, J ; Khalajzadeh, H ; Martinez Gutierrez, J ; Govan, L ; Buckle, G ; McIntosh, JG (BMC, 2022-01-12)
    BACKGROUND: Increasing participation in the Australian National Bowel Cancer Screening Program (NBCSP) is the most efficient and cost-effective way of reducing mortality associated with colorectal cancer by detecting and treating early-stage disease. Currently, only 44% of Australians aged 50-74 years complete the NBCSP. This efficacy trial aims to test whether this SMS intervention is an effective method for increasing participation in the NBCSP. Furthermore, a process evaluation will explore the barriers and facilitators to sending the SMS from general practice. METHODS: We will recruit 20 general practices in the western region of Victoria, Australia to participate in a cluster randomised controlled trial. General practices will be randomly allocated with a 1:1 ratio to either a control or intervention group. Established general practice software will be used to identify patients aged 50 to 60 years old who are due to receive a NBCSP kit in the next month. The SMS intervention includes GP endorsement and links to narrative messages about the benefits of and instructions on how to complete the NBCSP kit. It will be sent from intervention general practices to eligible patients prior to receiving the NBCSP kit. We require 1400 eligible patients to provide 80% power with a two-sided 5% significance level to detect a 10% increase in CRC screening participation in the intervention group compared to the control group. Our primary outcome is the difference in the proportion of eligible patients who completed a faecal occult blood test (FOBT) between the intervention and control group for up to 12 months after the SMS was sent, as recorded in their electronic medical record (EMR). A process evaluation using interview data collected from general practice staff (GP, practice managers, nurses) and patients will explore the feasibility and acceptability of sending and receiving a SMS to prompt completing a NBCSP kit. DISCUSSION: This efficacy trial will provide initial trial evidence of the utility of an SMS narrative intervention to increase participation in the NBCSP. The results will inform decisions about the need for and design of a larger, multi-state trial of this SMS intervention to determine its cost-effectiveness and future implementation. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12620001020976 . Registered on 17 October 2020.
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    Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Lower Gastrointestinal Cancers: A Systematic Review and Meta-Analysis
    Druce, P ; Calanzani, N ; Snudden, C ; Milley, K ; Boscott, R ; Behiyat, D ; Martinez-Gutierrez, J ; Saji, S ; Oberoi, J ; Funston, G ; Messenger, M ; Walter, FM ; Emery, J (SPRINGER, 2021-06)
    INTRODUCTION: Lower gastrointestinal (GI) cancers are a major cause of cancer deaths worldwide. Prognosis improves with earlier diagnosis, and non-invasive biomarkers have the potential to aid with early detection. Substantial investment has been made into the development of biomarkers; however, studies are often carried out in specialist settings and few have been evaluated for low-prevalence populations. METHODS: We aimed to identify novel biomarkers for the detection of lower GI cancers that have the potential to be evaluated for use in primary care. MEDLINE, Embase, Emcare and Web of Science were systematically searched for studies published in English from January 2000 to October 2019. Reference lists of included studies were also assessed. Studies had to report on measures of diagnostic performance for biomarkers (single or in panels) used to detect colorectal or anal cancers. We included all designs and excluded studies with fewer than 50 cases/controls. Data were extracted from published studies on types of biomarkers, populations and outcomes. Narrative synthesis was used, and measures of specificity and sensitivity were meta-analysed where possible. RESULTS: We identified 142 studies reporting on biomarkers for lower GI cancers, for 24,844 cases and 45,374 controls. A total of 378 unique biomarkers were identified. Heterogeneity of study design, population type and sample source precluded meta-analysis for all markers except methylated septin 9 (mSEPT9) and pyruvate kinase type tumour M2 (TuM2-PK). The estimated sensitivity and specificity of mSEPT9 was 80.6% (95% CI 76.6-84.0%) and 88.0% (95% CI 79.1-93.4%) respectively; TuM2-PK had an estimated sensitivity of 81.6% (95% CI 75.2-86.6%) and specificity of 80.1% (95% CI 76.7-83.0%). CONCLUSION: Two novel biomarkers (mSEPT9 and TuM2-PK) were identified from the literature with potential for use in lower-prevalence populations. Further research is needed to validate these biomarkers in primary care for screening and assessment of symptomatic patients.
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    An RCT of a decision aid to support informed choices about taking aspirin to prevent colorectal cancer and other chronic diseases: a study protocol for the SITA (Should I Take Aspirin?) trial
    Milton, S ; McIntosh, J ; Macrae, F ; Chondros, P ; Trevena, L ; Jenkins, M ; Walter, FM ; Taylor, N ; Boyd, L ; Saya, S ; Karnchanachari, N ; Novy, K ; Forbes, C ; Gutierrez, JM ; Broun, K ; Whitburn, S ; McGill, S ; Fishman, G ; Marker, J ; Shub, M ; Emery, J (BMC, 2021-07-15)
    BACKGROUND: Australian guidelines recommend that all people aged 50-70 years old actively consider taking daily low-dose aspirin (100-300 mg per day) for 2.5 to 5 years to reduce their risk of colorectal cancer (CRC). Despite the change of national CRC prevention guidelines, there has been no active implementation of the guidelines into clinical practice. We aim to test the efficacy of a health consultation and decision aid, using a novel expected frequency tree (EFT) to present the benefits and harms of low dose aspirin prior to a general practice consultation with patients aged 50-70 years, on informed decision-making and uptake of aspirin. METHODS: Approximately five to seven general practices in Victoria, Australia, will be recruited to participate. Patients 50-70 years old, attending an appointment with their general practitioner (GP) for any reason, will be invited to participate in the trial. Two hundred fifty-eight eligible participants will be randomly allocated 1:1 to intervention or active control arms using a computer-generated allocation sequence stratified by general practice, sex, and mode of trial delivery (face-to-face or teletrial). There are two co-primary outcomes: informed decision-making at 1-month post randomisation, measured by the Multi-dimensional Measure of Informed Choice (MMIC), and self-reported daily use of aspirin at 6 months. Secondary outcomes include decisional conflict at 1-month and other behavioural changes to reduce CRC risk at both time points. DISCUSSION: This trial will test the efficacy of novel methods for implementing national guidelines to support informed decision-making about taking aspirin in 50-70-year-olds to reduce the risk of CRC and other chronic diseases. TRIAL REGISTRATION: The Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12620001003965 . Registered on 10 October 2020.
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    Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Upper Gastrointestinal Cancers: A Systematic Review
    Calanzani, N ; Druce, PE ; Snudden, C ; Milley, KM ; Boscott, R ; Behiyat, D ; Saji, S ; Martinez-Gutierrez, J ; Oberoi, J ; Funston, G ; Messenger, M ; Emery, J ; Walter, FM (SPRINGER, 2021-02)
    INTRODUCTION: Detecting upper gastrointestinal (GI) cancers in primary care is challenging, as cancer symptoms are common, often non-specific, and most patients presenting with these symptoms will not have cancer. Substantial investment has been made to develop biomarkers for cancer detection, but few have reached routine clinical practice. We aimed to identify novel biomarkers for upper GI cancers which have been sufficiently validated to be ready for evaluation in low-prevalence populations. METHODS: We systematically searched MEDLINE, Embase, Emcare, and Web of Science for studies published in English from January 2000 to October 2019 (PROSPERO registration CRD42020165005). Reference lists of included studies were assessed. Studies had to report on second measures of diagnostic performance (beyond discovery phase) for biomarkers (single or in panels) used to detect pancreatic, oesophageal, gastric, and biliary tract cancers. We included all designs and excluded studies with less than 50 cases/controls. Data were extracted on types of biomarkers, populations and outcomes. Heterogeneity prevented pooling of outcomes. RESULTS: We identified 149 eligible studies, involving 22,264 cancer cases and 49,474 controls. A total of 431 biomarkers were identified (183 microRNAs and other RNAs, 79 autoantibodies and other immunological markers, 119 other proteins, 36 metabolic markers, 6 circulating tumour DNA and 8 other). Over half (n = 231) were reported in pancreatic cancer studies. Only 35 biomarkers had been investigated in at least two studies, with reported outcomes for that individual marker for the same tumour type. Apolipoproteins (apoAII-AT and apoAII-ATQ), and pepsinogens (PGI and PGII) were the most promising biomarkers for pancreatic and gastric cancer, respectively. CONCLUSION: Most novel biomarkers for the early detection of upper GI cancers are still at an early stage of matureness. Further evidence is needed on biomarker performance in low-prevalence populations, in addition to implementation and health economic studies, before extensive adoption into clinical practice can be recommended.
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    AI Based Cancer Detection Models Using Primary Care Datasets
    Ristanoski, G ; Emery, J ; Martinez Gutierrez, J ; McCarthy, D ; Aickelin, U (ENGINEERING & TECHNOLOGY PUBLISHING, 2022-04)
    Cancer is one of the most common and serious medical conditions with more than 144 000 Australians having been diagnosed with cancer in 2019. The non-specific nature of cancer symptoms and its low prevalence make cancer diagnosis particularly challenging, especially for primary care physicians/general practitioners (GPs). Ongoing research in cancer diagnosis places a heavy focus on understanding the epidemiology of cancer symptoms. With GPs being the first point of contact for most patients, prediction models using the patient’s medical history from primary care data can be a useful decision tool for early cancer detection. Our work both investigates the opportunities to use primary care data, specifically pathology data, for developing such decision tools and tackles the challenges coming from uncertainty in the data such as irregular pathology records. We present opportunities using the results within the frequently ordered full blood count to determine relevance to a future cancer diagnosis. By using several different pathology metrics, we show how we can generate features suitable for AI models that can be used to detect cancer 3 months earlier than current practices. Though the work focuses on patients with lung cancer, the methodology can be adjusted to other types of cancer and other data within the medical records. Our findings demonstrate that even when working with incomplete or obscure patient history, hematological measures contain valuable information that can indicate the potential of cancer diagnosis for up to 8 out of 10 patients. The use of the proposed decision tool presents a way to incorporate pathology data in the current cancer diagnosis practices and to incorporate various pathology tests or other primary care datasets for similar purposes.
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    Handling uncertainty using features from pathology: Opportunities in primary care data for developing high risk cancer survival methods
    Ristanoski, G ; Emery, J ; Martinez Gutierrez, J ; McCarthy, D ; Aickelin, U (ACM, 2021)
    More than 144 000 Australians were diagnosed with cancer in 2019. Diagnosing cancer in primary care is challenging due to the non-specific nature of cancer symptoms and its low prevalence. Understanding the epidemiology of cancer symptoms and patterns of presentation in patient's medical history from primary care data could be important to improve earlier detection and cancer outcomes. As past medical data about a patient can be incomplete, irregular or missing, this creates additional challenges when attempting to use the patient's history for any new diagnosis. Our research aims to investigate the opportunities in a patient's pathology history available to a GP, initially focused on the results within the frequently ordered full blood count to determine relevance to a future high-risk cancer prognosis, and treatment outcome. We investigated how past pathology test results can lead to deriving features that can be used to predict cancer outcomes, with emphasis on patients at risk of not surviving the cancer within 2-year period. This initial work focuses on patients with lung cancer, although the methodology can be applied to other types of cancer and other data within the medical record. Our findings indicate that even in cases of incomplete or obscure patient history, hematological measures can be useful in generating features relevant for predicting cancer risk and survival. The results strongly indicate to add the use of pathology test data for potential high-risk cancer diagnosis, and utilize additional pathology metrics or other primary care datasets even more for similar purposes.