General Practice and Primary Care - Research Publications

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    Patients' Experiences of Using Skin Self-monitoring Apps With People at Higher Risk of Melanoma: Qualitative Study.
    Habgood, E ; McCormack, C ; Walter, FM ; Emery, JD (JMIR Publications Inc., 2021-08-13)
    BACKGROUND: Melanoma is the fourth most commonly diagnosed cancer in Australia. Up to 75% of melanomas are first detected by patients or their family or friends. Many mobile apps for melanoma exist, including apps to encourage skin self-monitoring to improve the likelihood of early detection. Previous research in this area has focused on their development, diagnostic accuracy, or validation. Little is known about patients' views and experiences of using these apps. OBJECTIVE: This study aims to understand patients' views and experiences of using commercially available melanoma skin self-monitoring mobile apps for a period of 3 months. METHODS: This qualitative study was conducted in two populations: primary care (where the MelatoolsQ tool was used to identify patients who were at increased risk of melanoma) and secondary care (where patients had a previous diagnosis of melanoma, stages T0-T3a). Participants downloaded 2 of the 4 mobile apps for skin self-monitoring (SkinVision, UMSkinCheck, Mole Monitor, or MySkinPal) and were encouraged to use them for 3 months. After 3 months, a semistructured interview was conducted with participants to discuss their experiences of using the skin self-monitoring mobile apps. RESULTS: A total of 54 participants were recruited in the study, with 37% (20) of participants from primary care and 62% (34) from secondary care. Interviews were conducted with 34 participants when data saturation was reached. Most participants did not use the apps at all (n=12) or tried them once but did not continue (n=14). Only 8 participants used the apps to assist with skin self-monitoring for the entire duration of the study. Patients discussed the apps in the context of the importance of early detection and their current skin self-monitoring behaviors. A range of features of perceived quality of each app affected engagement to support skin self-monitoring. Participants described their skin self-monitoring routines and potential mismatches with the app reminders. They also described the technical and practical difficulties experienced when using the apps for skin self-monitoring. The app's positioning within existing relationships with health care providers was crucial to understand the use of the apps. CONCLUSIONS: This study of patients at increased risk of melanoma highlights several barriers to engagement with apps to support skin self-monitoring. The results highlight the wide-ranging and dynamic influences on engagement with mobile apps, which extend beyond app design and relate to broader contextual factors about skin self-monitoring routines and relationships with health care providers.
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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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    Using an electronic self-completion tool to identify patients at increased risk of melanoma in Australian primary care
    Habgood, E ; Walter, FM ; O'Hare, E ; McIntosh, J ; McCormack, C ; Emery, JD (WILEY, 2020-08)
    BACKGROUND/OBJECTIVES: Some international guidelines recommend a risk-based approach to screening for melanoma, but few suggest how to account for multiple risk factors or how to implement risk-based screening in practice. This study investigated the acceptability and feasibility of identifying patients at increased risk of melanoma in Australian general practice using a self-completed risk assessment tool. Stratification of risk was based on the validated Williams melanoma risk prediction model. METHODS: Patients and companions aged 18 or older in Australian general practices were approached in the waiting room and invited to enter information about their melanoma risk factors into the tool using an iPad. Acceptability was measured by the proportion of people willing to participate from those invited and feasibility by the number of people able to complete the tool unaided. Risk of developing melanoma was stratified into four risk categories using the Williams model. RESULTS: 1535 (90.4%) participants were recruited from two general practices. Only 200 participants (13%) needed assistance to complete the tool. The mean risk score for participants was 15.2 (±SD 9.8). The Williams model estimated between 5% and 19% of the sample were at increased risk accounting for an estimated 30% to 60% of future incident melanomas. CONCLUSIONS: A risk-stratified tool using the Williams model was acceptable and feasible for patients to self-complete in general practice clinics. This could be an effective way to identify people in primary care for implementing risk-based targeted melanoma screening and prevention.
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    Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review
    Jones, OT ; Calanzani, N ; Saji, S ; Duffy, SW ; Emery, J ; Hamilton, W ; Singh, H ; de Wit, NJ ; Walter, FM (JMIR PUBLICATIONS, INC, 2021-03-03)
    BACKGROUND: More than 17 million people worldwide, including 360,000 people in the United Kingdom, were diagnosed with cancer in 2018. Cancer prognosis and disease burden are highly dependent on the disease stage at diagnosis. Most people diagnosed with cancer first present in primary care settings, where improved assessment of the (often vague) presenting symptoms of cancer could lead to earlier detection and improved outcomes for patients. There is accumulating evidence that artificial intelligence (AI) can assist clinicians in making better clinical decisions in some areas of health care. OBJECTIVE: This study aimed to systematically review AI techniques that may facilitate earlier diagnosis of cancer and could be applied to primary care electronic health record (EHR) data. The quality of the evidence, the phase of development the AI techniques have reached, the gaps that exist in the evidence, and the potential for use in primary care were evaluated. METHODS: We searched MEDLINE, Embase, SCOPUS, and Web of Science databases from January 01, 2000, to June 11, 2019, and included all studies providing evidence for the accuracy or effectiveness of applying AI techniques for the early detection of cancer, which may be applicable to primary care EHRs. We included all study designs in all settings and languages. These searches were extended through a scoping review of AI-based commercial technologies. The main outcomes assessed were measures of diagnostic accuracy for cancer. RESULTS: We identified 10,456 studies; 16 studies met the inclusion criteria, representing the data of 3,862,910 patients. A total of 13 studies described the initial development and testing of AI algorithms, and 3 studies described the validation of an AI algorithm in independent data sets. One study was based on prospectively collected data; only 3 studies were based on primary care data. We found no data on implementation barriers or cost-effectiveness. Risk of bias assessment highlighted a wide range of study quality. The additional scoping review of commercial AI technologies identified 21 technologies, only 1 meeting our inclusion criteria. Meta-analysis was not undertaken because of the heterogeneity of AI modalities, data set characteristics, and outcome measures. CONCLUSIONS: AI techniques have been applied to EHR-type data to facilitate early diagnosis of cancer, but their use in primary care settings is still at an early stage of maturity. Further evidence is needed on their performance using primary care data, implementation barriers, and cost-effectiveness before widespread adoption into routine primary care clinical practice can be recommended.
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    Measuring patient experience of diagnostic care and acceptability of testing
    Forster, AS ; Rubin, G ; Emery, JD ; Thompson, M ; Sutton, S ; de Wit, N ; Walter, FM ; Lyratzopoulos, G (WALTER DE GRUYTER GMBH, 2021-08)
    A positive patient experience has been long recognised as a key feature of a high-quality health service, however, often assessment of patient experience excludes diagnostic care. Experience of diagnostic services and the acceptability of diagnostic tests are often conflated, with lack of clarity about when and how either should be measured. These problems contrast with the growth in the development and marketing of new tests and investigation strategies. Building on the appraisal of current practice, we propose that the experience of diagnostic services and the acceptability of tests should be assessed separately, and describe distinct components of each. Such evaluations will enhance the delivery of patient-centred care, and facilitate patient choice.
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    Electronic clinical decision support tool for assessing stomach symptoms in primary care (ECASS): a feasibility study
    Rubin, G ; Walter, FM ; Emery, J ; Hamilton, W ; Hoare, Z ; Howse, J ; Nixon, C ; Srivastava, T ; Thomas, C ; Ukoumunne, OC ; Usher-Smith, JA ; Whyte, S ; Neal, RD (BMJ PUBLISHING GROUP, 2021)
    OBJECTIVE: To determine the feasibility of a definitive trial in primary care of electronic clinical decision support (eCDS) for possible oesophago-gastric (O-G) cancer. DESIGN AND SETTING: Feasibility study in 42 general practices in two regions of England, cluster randomised controlled trial design without blinding, nested qualitative and health economic evaluation. PARTICIPANTS: Patients aged 55 years or older, presenting to their general practitioner (GP) with symptoms associated with O-G cancer. 530 patients (mean age 68 years, 58% female) participated. INTERVENTION: Practices randomised 1:1 to usual care (control) or to receive a previously piloted eCDS tool for suspected cancer (intervention), for use at the discretion of the GPs, supported by a theory-based implementation package and ongoing support. We conducted semistructured interviews with GPs in intervention practices. Recruitment lasted 22 months. OUTCOMES: Patient participation rate, use of eCDS, referrals and route to diagnosis, O-G cancer diagnoses; acceptability to GPs; cost-effectiveness. Participants followed up 6 months after index encounter. RESULTS: From control and intervention practices, we screened 3841 and 1303 patients, respectively; 1189 and 434 were eligible, 392 and 138 consented to participate. Ten patients (1.9%) had O-G cancer. eCDS was used eight times in total by five unique users. GPs experienced interoperability problems between the eCDS tool and their clinical system and also found it did not fit with their workflow. Unexpected restrictions on software installation caused major problems with implementation. CONCLUSIONS: The conduct of this study was hampered by technical limitations not evident during an earlier pilot of the eCDS tool, and by regulatory controls on software installation introduced by primary care trusts early in the study. This eCDS tool needed to integrate better with clinical workflow; even then, its use for suspected cancer may be infrequent. Any definitive trial of eCDS for cancer diagnosis should only proceed after addressing these constraints. TRIAL REGISTRATION NUMBER: ISRCTN125595588.
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    Identifying Ovarian Cancer in Symptomatic Women: A Systematic Review of Clinical Tools
    Funston, G ; Hardy, V ; Abel, G ; Crosbie, EJ ; Emery, J ; Hamilton, W ; Walter, FM (MDPI, 2020-12)
    In the absence of effective ovarian cancer screening programs, most women are diagnosed following the onset of symptoms. Symptom-based tools, including symptom checklists and risk prediction models, have been developed to aid detection. The aim of this systematic review was to identify and compare the diagnostic performance of these tools. We searched MEDLINE, EMBASE and Cochrane CENTRAL, without language restriction, for relevant studies published between 1 January 2000 and 3 March 2020. We identified 1625 unique records and included 16 studies, evaluating 21 distinct tools in a range of settings. Fourteen tools included only symptoms; seven also included risk factors or blood tests. Four tools were externally validated-the Goff Symptom Index (sensitivity: 56.9-83.3%; specificity: 48.3-98.9%), a modified Goff Symptom Index (sensitivity: 71.6%; specificity: 88.5%), the Society of Gynaecologic Oncologists consensus criteria (sensitivity: 65.3-71.5%; specificity: 82.9-93.9%) and the QCancer Ovarian model (10% risk threshold-sensitivity: 64.1%; specificity: 90.1%). Study heterogeneity precluded meta-analysis. Given the moderate accuracy of several tools on external validation, they could be of use in helping to select women for ovarian cancer investigations. However, further research is needed to assess the impact of these tools on the timely detection of ovarian cancer and on patient survival.
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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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