'ThinkCancer!' - Randomised feasibility trial of a novel practice-based early cancer diagnosis intervention.

BACKGROUND: UK cancer deaths remain high; primary care is key for earlier cancer diagnosis as half of avoidable delays occur here. Improvement is possible through lower referral thresholds, better guideline adherence, and better safety netting systems. Few interventions target whole practice teams. We developed a novel whole practice team intervention to address this. AIM: To test the feasibility and acceptability of a novel, complex behavioural intervention 'ThinkCancer!' for assessment in a subsequent Phase III trial. DESIGN & SETTING: Pragmatic, superiority pilot RCT with an embedded process evaluation and feasibility economic analysis in Welsh general practices. METHOD: Clinical outcome data were collected from practices (the unit of randomisation). Practice characteristics and cancer safety netting systems were assessed. Individual practice staff completed evaluation and feedback forms, and qualitative interviews. The intervention was adapted and refined. RESULTS: Trial recruitment and workshop deliveries took place between March 2020 to May 2021. Trial progression criteria for recruitment, intervention fidelity and routine data collection were met. Staff-level fidelity, retention and individual level data collection processes were reviewed and amended. Interviews highlighted positive participant views on all aspects of the intervention. All practices set out to liberalise referral thresholds appropriately, implement guidelines, and address safety netting plans in detail. CONCLUSION: 'ThinkCancer!' appears feasible and acceptable; the new iteration of the workshops was completed, and the Phase III trial has been funded to assess the effectiveness and cost effectiveness of this novel professional behaviour change intervention. Delivery at scale to multiple practices will likely improve fidelity and reach.

Gender inequalities across ethnicities in primary care cancer referrals: scoping review protocol.

BACKGROUND: Early cancer diagnosis is associated with improved mortality and morbidity; however, studies indicate that women and individuals from ethnic minorities experience longer times to diagnosis and worse prognosis compared to their counterparts for various cancers. In countries with a gatekeeper healthcare system, such as UK, most suspected cancer referrals are initiated in primary care. AIM: To understand the extent of evidence available on the relationship between primary care cancer referral pathways and cancer outcomes in relation to gender across different ethnic groups. This will identify research gaps and enable development of strategies to ease potential inequalities in cancer diagnosis. DESIGN & SETTING: A scoping review based on the Joanna Briggs Institute methodology. PRISMA-ScR will be used. METHOD: Electronic databases and private collections of the team members will be searched for studies. Two independent reviewers will carry out the study selection and data extraction. Based on participants, concept and context framework, this review will consider studies after year 2000 that explored the relationship between gender, across various ethnic groups, and cancer outcomes following primary care cancer referral in countries with gatekeeper healthcare systems (UK, New Zealand, Sweden, Australia, Canada, Denmark, Ireland and Norway). Results will be presented as a narrative analysis. CONCLUSION: The results are expected to provide an overview of the discrepancies in primary care cancer referrals based on gender across ethnic groups, which will be crucial to define an appropriate range of strategies to ease any inequalities in primary healthcare cancer diagnosis. OPEN SCIENCE FRAMEWORK PROTOCOL REGISTRATION: https://osf.io/jvtxb.

The National Health Service urgent cancer referral pathway for suspected urological cancers: early economic evaluation of a risk prediction test.

OBJECTIVES: In the UK, the number of patients urgently referred for suspected cancer is increasing, and providers are struggling to cope with demand. We explore the potential cost-effectiveness of a new risk prediction test - the PinPoint test - to triage and prioritize patients urgently referred with suspected urological cancers. METHODS: Two simulation models were developed to reflect the diagnostic pathways for patients with (i) suspected prostate cancer, and (ii) bladder or kidney cancer, comparing the PinPoint test to current practice. An early economic analysis was conducted from a UK National Health Service (NHS) perspective. The primary outcomes were the percentage of individuals seen within 2 weeks and health care costs. An exploratory analysis was conducted to understand the potential impact of the Pinpoint test on quality-adjusted life years gained. RESULTS: Across both models and applications, the PinPoint test led to more individuals with urological cancer being seen within 2 weeks. Using PinPoint only to prioritize patients led to increased costs overall, whereas using PinPoint to both triage and prioritize patients led to cost savings. The estimated impact on life years gained/lost was very small and highly uncertain. CONCLUSIONS: Using the PinPoint test to prioritize urgent referrals meant that more individuals with urological cancer were seen within 2 weeks, but at additional cost to the NHS. If used as a triage and prioritization tool, the PinPoint test shortens wait times for referred individuals and is cost saving. More data on the impact of short-term delays to diagnosis on health-related quality of life is needed.

Earlier cancer diagnosis in primary care: a feasibility economic analysis of ThinkCancer!

BACKGROUND: UK cancer survival rates are much lower compared with other high-income countries. In primary care, there are opportunities for GPs and other healthcare professionals to act more quickly in response to presented symptoms that might represent cancer. ThinkCancer! is a complex behaviour change intervention aimed at primary care practice teams to improve the timely diagnosis of cancer. AIM: To explore the costs of delivering the ThinkCancer! intervention to expedite cancer diagnosis in primary care. DESIGN & SETTING: Feasibility economic analysis using a micro-costing approach, which was undertaken in 19 general practices in Wales, UK. METHOD: From an NHS perspective, micro-costing methodology was used to determine whether it was feasible to gather sufficient economic data to cost the ThinkCancer! INTERVENTION: Owing to the COVID-19 pandemic, ThinkCancer! was mainly delivered remotely online in a digital format. Budget impact analysis (BIA) and sensitivity analysis were conducted to explore the costs of face-to-face delivery of the ThinkCancer! intervention as intended pre-COVID-19. RESULTS: The total costs of delivering the ThinkCancer! intervention across 19 general practices in Wales was £25 030, with an average cost per practice of £1317 (standard deviation [SD]: 578.2). Findings from the BIA indicated a total cost of £34 630 for face-to-face delivery. CONCLUSION: Data collection methods were successful in gathering sufficient health economics data to cost the ThinkCancer! INTERVENTION: Results of this feasibility study will be used to inform a future definitive economic evaluation alongside a pragmatic randomised controlled trial (RCT).

Machine Learning for Risk Prediction of Oesophago-Gastric Cancer in Primary Care: Comparison with Existing Risk-Assessment Tools.

Oesophago-gastric cancer is difficult to diagnose in the early stages given its typical non-specific initial manifestation. We hypothesise that machine learning can improve upon the diagnostic performance of current primary care risk-assessment tools by using advanced analytical techniques to exploit the wealth of evidence available in the electronic health record. We used a primary care electronic health record dataset derived from the UK General Practice Research Database (7471 cases; 32,877 controls) and developed five probabilistic machine learning classifiers: Support Vector Machine, Random Forest, Logistic Regression, Naïve Bayes, and Extreme Gradient Boosted Decision Trees. Features included basic demographics, symptoms, and lab test results. The Logistic Regression, Support Vector Machine, and Extreme Gradient Boosted Decision Tree models achieved the highest performance in terms of accuracy and AUROC (0.89 accuracy, 0.87 AUROC), outperforming a current UK oesophago-gastric cancer risk-assessment tool (ogRAT). Machine learning also identified more cancer patients than the ogRAT: 11.0% more with little to no effect on false positives, or up to 25.0% more with a slight increase in false positives (for Logistic Regression, results threshold-dependent). Feature contribution estimates and individual prediction explanations indicated clinical relevance. We conclude that machine learning could improve primary care cancer risk-assessment tools, potentially helping clinicians to identify additional cancer cases earlier. This could, in turn, improve survival outcomes.

An exploratory assessment of the impact of a novel risk assessment test on breast cancer clinic waiting times and workflow: a discrete event simulation model.

BACKGROUND: Breast cancer clinics across the UK have long been struggling to cope with high demand. Novel risk prediction tools - such as the PinPoint test - could help to reduce unnecessary clinic referrals. Using early data on the expected accuracy of the test, we explore the potential impact of PinPoint on: (a) the percentage of patients meeting the two-week referral target, and (b) the number of clinic 'overspill' appointments generated (i.e. patients having to return to the clinic to complete their required investigations). METHODS: A simulation model was built to reflect the annual flow of patients through a single UK clinic. Due to current uncertainty around the exact impact of PinPoint testing on standard care, two primary scenarios were assessed. Scenario 1 assumed complete GP adherence to testing, with only non-referred cancerous cases returning for delayed referral. Scenario 2 assumed GPs would overrule 20% of low-risk results, and that 10% of non-referred non-cancerous cases would also return for delayed referral. A range of sensitivity analyses were conducted to explore the impact of key uncertainties on the model results. Service reconfiguration scenarios, removing individual weekly clinics from the clinic schedule, were also explored. RESULTS: Under standard care, 66.3% (95% CI: 66.0 to 66.5) of patients met the referral target, with 1,685 (1,648 to 1,722) overspill appointments. Under both PinPoint scenarios, > 98% of patients met the referral target, with overspill appointments reduced to between 727 (707 to 746) [Scenario 1] and 886 (861 to 911) [Scenario 2]. The reduced clinic demand was sufficient to allow removal of one weekly low-capacity clinic [N = 10], and the results were robust to sensitivity analyses. CONCLUSION: The findings from this early analysis indicate that risk prediction tools could have the potential to alleviate pressure on cancer clinics, and are expected to have increased utility in the wake of heightened pressures resulting from the COVID-19 pandemic. Further research is required to validate these findings with real world evidence; evaluate the broader clinical and economic impact of the test; and to determine outcomes and risks for patients deemed to be low-risk on the PinPoint test and therefore not initially referred.

Early economic evaluation of an intervention to improve uptake of the NHS England Diabetes Prevention Programme.

BACKGROUND: Despite reported increases in referral numbers, a large proportion of those with prediabetes still decline participation in the NHS England Diabetes Prevention Programme (NDPP). The aim of this study was to explore whether investment in interventions to improve uptake of the programme has the potential to be cost-effective. METHODS: An early cost-utility analysis was conducted using a Markov model parameterized based on secondary data sources. We explored different uptake scenarios and the impact that this had on the maximum allowable intervention price based on cost-effectiveness at the UK NICE willingness to pay threshold of £20,000 (US$ 25,913). Value of information analyses were conducted to explore the potential value of further research to resolve uncertainty at each uptake level. RESULTS: As uptake levels increase, the maximum allowable intervention price and overall expected value of removing decision uncertainty increases. For 5 percentage and 50 percentage points increase in uptake levels, the maximum allowable intervention price is £41.86 (US$ 54.23) and £418.59 (US$ 542.34) per person, and the overall expected value of removing decision uncertainty are £361,818,839 (US$ 468,786,625) and £1,468,712,316 (US$ 1,902,921,063) respectively. CONCLUSION: There is headroom for investment in interventions that improve uptake to the NDPP, thereby allowing the programme itself to be delivered in a manner that remains cost-effective.

Randomised controlled trial and economic evaluation of a targeted cancer awareness intervention for adults living in deprived areas of the UK.

BACKGROUND: Cancer outcomes are poor in socioeconomically deprived communities, with low symptom awareness contributing to prolonged help-seeking and advanced disease. Targeted cancer awareness interventions require evaluation. METHODS: This is a randomised controlled trial involving adults aged 40+ years recruited in community and healthcare settings in deprived areas of South Yorkshire and South-East Wales. INTERVENTION: personalised behavioural advice facilitated by a trained lay advisor. CONTROL: usual care. Follow-up at two weeks and six months post-randomisation. PRIMARY OUTCOME: total cancer symptom recognition score two weeks post-randomisation. RESULTS: Two hundred and thirty-four participants were randomised. The difference in total symptom recognition at two weeks [adjusted mean difference (AMD) 0.6, 95% CI: -0.03, 1.17, p = 0.06] was not statistically significant. Intervention participants reported increased symptom recognition (AMD 0.8, 95% CI: 0.18, 1.37, p = 0.01) and earlier intended presentation (AMD -2.0, 95% CI: -3.02, -0.91, p < 0.001) at six months. "Lesser known" symptom recognition was higher in the intervention arm (2 weeks AMD 0.5, 95% CI: 0.03, 0.97 and six months AMD 0.7, 95% CI: 0.16, 1.17). Implementation cost per participant was £91.34, with no significant between-group differences in healthcare resource use post-intervention. CONCLUSIONS: Improved symptom recognition and earlier anticipated presentation occurred at longer-term follow-up. The ABACus Health Check is a viable low-cost intervention to increase cancer awareness in socioeconomically deprived communities. CLINICAL TRIAL REGISTRATION: ISRCTN16872545.

Impact of the COVID-19 pandemic on cancer assessment in primary care: a qualitative study of GP views.

BACKGROUND: Early diagnosis is key to improve cancer outcomes, and most cancers are diagnosed in primary care after initial symptomatic presentation. Emerging evidence suggests an increase in avoidable cancer deaths owing to the COVID-19 pandemic. AIM: To understand GPs' views on the impact of the COVID-19 pandemic on the clinical assessment of possible cancer. DESIGN & SETTING: A qualitative semi-structured interview study with GPs from the East of England. METHOD: GPs were purposively sampled based on age, sex, and years of experience. Interviews were conducted via Zoom or Microsoft Teams in August and September 2020. Transcribed recordings were analysed inductively using thematic analysis. The Model of Pathways to Treatment guided the analysis. RESULTS: Three themes were identified across 23 interviews on GP views on the impact of: (1) changes in patient help-seeking behaviour on symptoms at presentation; (2) remote consultations on managing patients with possible cancer symptoms; and (3) the COVID-19 pandemic on triaging and referring patients with possible cancer. There were positive changes to practice, but concerns were raised about the adequacy of remote consultations for assessing symptoms. Some GPs reported delayed cancer diagnoses, and uncertainty about how backlog in referrals would be managed. CONCLUSION: This study provides new evidence on the impact of the COVID-19 pandemic on assessing symptomatic patients. Recommendations are made to inform safe and effective primary care clinical practice. Urgent action is needed to mitigate the impact of the COVID-19 pandemic, and ensure appropriate symptomatic assessment now and in the future.

Protocol for a feasibility study incorporating a randomised pilot trial with an embedded process evaluation and feasibility economic analysis of ThinkCancer!: a primary care intervention to expedite cancer diagnosis in Wales.

BACKGROUND: Compared to the rest of Europe, the UK has relatively poor cancer outcomes, with late diagnosis and a slow referral process being major contributors. General practitioners (GPs) are often faced with patients presenting with a multitude of non-specific symptoms that could be cancer. Safety netting can be used to manage diagnostic uncertainty by ensuring patients with vague symptoms are appropriately monitored, which is now even more crucial due to the ongoing COVID-19 pandemic and its major impact on cancer referrals. The ThinkCancer! workshop is an educational behaviour change intervention aimed at the whole general practice team, designed to improve primary care approaches to ensure timely diagnosis of cancer. The workshop will consist of teaching and awareness sessions, the appointment of a Safety Netting Champion and the development of a bespoke Safety Netting Plan and has been adapted so it can be delivered remotely. This study aims to assess the feasibility of the ThinkCancer! intervention for a future definitive randomised controlled trial. METHODS: The ThinkCancer! study is a randomised, multisite feasibility trial, with an embedded process evaluation and feasibility economic analysis. Twenty-three to 30 general practices will be recruited across Wales, randomised in a ratio of 2:1 of intervention versus control who will follow usual care. The workshop will be delivered by a GP educator and will be adapted iteratively throughout the trial period. Baseline practice characteristics will be collected via questionnaire. We will also collect primary care intervals (PCI), 2-week wait (2WW) referral rates, conversion rates and detection rates at baseline and 6 months post-randomisation. Participant feedback, researcher reflections and economic costings will be collected following each workshop. A process evaluation will assess implementation using an adapted Normalisation Measure Development (NoMAD) questionnaire and qualitative interviews. An economic feasibility analysis will inform a future economic evaluation. DISCUSSION: This study will allow us to test and further develop a novel evidenced-based complex intervention aimed at general practice teams to expedite the diagnosis of cancer in primary care. The results from this study will inform the future design of a full-scale definitive phase III trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT04823559 .

Electronic clinical decision support tool for assessing stomach symptoms in primary care (ECASS): a feasibility study.

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.

Cancer diagnostic tools to aid decision-making in primary care: mixed-methods systematic reviews and cost-effectiveness analysis.

BACKGROUND: Tools based on diagnostic prediction models are available to help general practitioners diagnose cancer. It is unclear whether or not tools expedite diagnosis or affect patient quality of life and/or survival. OBJECTIVES: The objectives were to evaluate the evidence on the validation, clinical effectiveness, cost-effectiveness, and availability and use of cancer diagnostic tools in primary care. METHODS: Two systematic reviews were conducted to examine the clinical effectiveness (review 1) and the development, validation and accuracy (review 2) of diagnostic prediction models for aiding general practitioners in cancer diagnosis. Bibliographic searches were conducted on MEDLINE, MEDLINE In-Process, EMBASE, Cochrane Library and Web of Science) in May 2017, with updated searches conducted in November 2018. A decision-analytic model explored the tools' clinical effectiveness and cost-effectiveness in colorectal cancer. The model compared patient outcomes and costs between strategies that included the use of the tools and those that did not, using the NHS perspective. We surveyed 4600 general practitioners in randomly selected UK practices to determine the proportions of general practices and general practitioners with access to, and using, cancer decision support tools. Association between access to these tools and practice-level cancer diagnostic indicators was explored. RESULTS: Systematic review 1 - five studies, of different design and quality, reporting on three diagnostic tools, were included. We found no evidence that using the tools was associated with better outcomes. Systematic review 2 - 43 studies were included, reporting on prediction models, in various stages of development, for 14 cancer sites (including multiple cancers). Most studies relate to QCancer® (ClinRisk Ltd, Leeds, UK) and risk assessment tools. DECISION MODEL: In the absence of studies reporting their clinical outcomes, QCancer and risk assessment tools were evaluated against faecal immunochemical testing. A linked data approach was used, which translates diagnostic accuracy into time to diagnosis and treatment, and stage at diagnosis. Given the current lack of evidence, the model showed that the cost-effectiveness of diagnostic tools in colorectal cancer relies on demonstrating patient survival benefits. Sensitivity of faecal immunochemical testing and specificity of QCancer and risk assessment tools in a low-risk population were the key uncertain parameters. SURVEY: Practitioner- and practice-level response rates were 10.3% (476/4600) and 23.3% (227/975), respectively. Cancer decision support tools were available in 83 out of 227 practices (36.6%, 95% confidence interval 30.3% to 43.1%), and were likely to be used in 38 out of 227 practices (16.7%, 95% confidence interval 12.1% to 22.2%). The mean 2-week-wait referral rate did not differ between practices that do and practices that do not have access to QCancer or risk assessment tools (mean difference of 1.8 referrals per 100,000 referrals, 95% confidence interval -6.7 to 10.3 referrals per 100,000 referrals). LIMITATIONS: There is little good-quality evidence on the clinical effectiveness and cost-effectiveness of diagnostic tools. Many diagnostic prediction models are limited by a lack of external validation. There are limited data on current UK practice and clinical outcomes of diagnostic strategies, and there is no evidence on the quality-of-life outcomes of diagnostic results. The survey was limited by low response rates. CONCLUSION: The evidence base on the tools is limited. Research on how general practitioners interact with the tools may help to identify barriers to implementation and uptake, and the potential for clinical effectiveness. FUTURE WORK: Continued model validation is recommended, especially for risk assessment tools. Assessment of the tools' impact on time to diagnosis and treatment, stage at diagnosis, and health outcomes is also recommended, as is further work to understand how tools are used in general practitioner consultations. STUDY REGISTRATION: This study is registered as PROSPERO CRD42017068373 and CRD42017068375. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology programme and will be published in full in Health Technology Assessment; Vol. 24, No. 66. See the NIHR Journals Library website for further project information.

In the UK, people with cancer tend to die sooner than people with cancer in other European countries. This may be because their cancers are caught at a later stage, perhaps after they have spread. Spotting cancer earlier in people, and testing them sooner, may extend people's lives. Researchers have developed 'diagnostic tools', which give the probability of having cancer, based on a patient's symptoms, blood test results and other information. The tools help family doctors decide who needs further testing for possible cancer, including cancers of the digestive, urinary and reproductive systems, and in the blood. We do not know how many family doctors have these tools, or how well the tools work. We systematically reviewed published studies about how these tools were developed, how good and accurate they are, and what effects their use has on patients. We found that many tools have been developed, but there is little evidence that they improve the quality or length of life. We sent surveys to family doctors all over the UK asking if they had the tools at their practice and if they used them. Based on the replies we received, we estimate that the tools are in about one in three practices. They are likely to be used in about half of the practices where they are available. For practices in England only, we looked for, but did not find, any association between using the tools and the number of urgent appointments made for cancer testing. We used a computer model to show what might happen if family doctors used the tools for patients who have symptoms of bowel cancer. In our model, if general practitioners used the tools, patients would need fewer appointments before they were referred to a specialist. This should reduce the time to diagnosis and treatment, compared with not using the tools. However, there is very little evidence as to whether or not this is indeed the case. Therefore, at the moment, we cannot say whether or not the use of such tools by general practitioners is better for patients and the NHS. More research is needed on what effect these tools have on patients, especially as to whether or not quality and length of life are improved.

The Impact of the COVID-19 Pandemic on Genitourinary Cancer Care: Re-envisioning the Future.

CONTEXT: The coronavirus disease 2019 (COVID-19) pandemic necessitated rapid changes in medical practice. Many of these changes may add value to care, creating opportunities going forward. OBJECTIVE: To provide an evidence-informed, expert-derived review of genitourinary cancer care moving forward following the initial COVID-19 pandemic. EVIDENCE ACQUISITION: A collaborative narrative review was conducted using literature published through May 2020 (PubMed), which comprised three main topics: reduced in-person interactions arguing for increasing virtual and image-based care, optimisation of the delivery of care, and the effect of COVID-19 in health care facilities on decision-making by patients and their families. EVIDENCE SYNTHESIS: Patterns of care will evolve following the COVID-19 pandemic. Telemedicine, virtual care, and telemonitoring will increase and could offer broader access to multidisciplinary expertise without increasing costs. Comprehensive and integrative telehealth solutions will be necessary, and should consider patients' mental health and access differences due to socioeconomic status. Investigations and treatments will need to maximise efficiency and minimise health care interactions. Solutions such as one stop clinics, day case surgery, hypofractionated radiotherapy, and oral or less frequent drug dosing will be preferred. The pandemic necessitated a triage of those patients whose treatment should be expedited, delayed, or avoided, and may persist with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in circulation. Patients whose demographic characteristics are at the highest risk of complications from COVID-19 may re-evaluate the benefit of intervention for less aggressive cancers. Clinical research will need to accommodate virtual care and trial participation. Research dissemination and medical education will increasingly utilise virtual platforms, limiting in-person professional engagement; ensure data dissemination; and aim to enhance patient engagement. CONCLUSIONS: The COVID-19 pandemic will have lasting effects on the delivery of health care. These changes offer opportunities to improve access, delivery, and the value of care for patients with genitourinary cancers but raise concerns that physicians and health administrators must consider in order to ensure equitable access to care. PATIENT SUMMARY: The coronavirus disease 2019 (COVID-19) pandemic has dramatically changed the care provided to many patients with genitourinary cancers. This has necessitated a transition to telemedicine, changes in threshold or delays in many treatments, and an opportunity to reimagine patient care to maintain safety and improve value moving forward.

Disparities in prostate cancer survival in Appalachian Kentucky: a population-based study.

INTRODUCTION: Prostate cancer (PC) is the most common male cancer in the USA. When comparing the incidence and mortality rates of PC, the Surveillance Epidemiology and End Results data of 2005-2014 show that Appalachian Kentucky had a lower incidence (113/100 000 v 137/100 000) but a higher mortality rate (23.8% v 21.8%) when compared to non-Appalachian Kentucky. The aim of this study was to further characterize the survival disparities of PC between Appalachian and non-Appalachian Kentucky. METHODS: All stages of PC patients diagnosed between 2007 and 2011 were collected through the Kentucky Cancer Registry. Baseline characteristics and survival outcomes were compared between Appalachian Kentucky and non-Appalachian Kentucky, using Pearson χ2 and Cox regression analyses in this population-based analysis. RESULTS: Of 12 871 patients studied, 3482 (26.8%) were from Appalachian Kentucky whereas 8489 (73.2%) were from non-Appalachian Kentucky. Caucasians predominated in both groups. Most Appalachian Kentucky patients were aged 65-74 years. Appalachian Kentucky patients had a higher Gleason score, higher prostate specific antigen (PSA), more aggressive histologic grade, more distant disease, higher comorbidity score, lower education, and higher poverty compared to patients from non-Appalachian Kentucky. There was a 5-year survival difference between Appalachian Kentucky and non-Appalachian Kentucky in unadjusted analysis (p<0.001) that disappeared after adjusting with Cox regression analysis (p=0.4). However, worsened survival was still seen with higher Gleason score, higher PSA, distant stage disease, higher Charlson comorbidity index, and very low high school education (p<0.001). CONCLUSION: In this population-based analysis, this study shows a significant difference in PC survival between Appalachian and non-Appalachian Kentucky. The difference was not related to geographic location, but rather to high comorbidity score, high poverty rate, and low education. Additional research is needed to understand the healthcare restraints for Appalachian Kentucky.

Trial of personalised care after treatment-Prostate cancer: A randomised feasibility trial of a nurse-led psycho-educational intervention.

OBJECTIVE: The present parallel randomised control trial evaluated the feasibility of a nurse-led psycho-educational intervention aimed at improving the self-management of prostate cancer survivors. METHODS: We identified 305 eligible patients from a district general hospital, diagnosed 9-48 months previously, who completed radical treatment, or were monitored clinically (ineligible for treatment). Ninety-five patients were recruited by blinded selection and randomised to Intervention (N = 48) and Control (N = 47) groups. Participant allocation was revealed to patients and researchers after recruitment was completed. For 36 weeks, participants received augmented usual care (Control) or augmented usual care and additional nurse support (Intervention) provided in two community hospitals and a university clinic, or by telephone. RESULTS: Data from 91 participants (Intervention, N = 45; Control, N = 46) were analysed. All feasibility metrics met predefined targets: recruitment rate (31.15%; 95% CI: 25.95%-36.35%), attrition rate (9.47%; 95% CI: 3.58%-15.36%) and outcome measures completion rates (77%-92%). Forty-five patients received the intervention, with no adverse events. The Extended Prostate Cancer Index Composite can inform the minimum sample size for a future effectiveness trial. The net intervention cost was £317 per patient. CONCLUSIONS: The results supported the feasibility and acceptability of the intervention, suggesting that it should be evaluated in a fully powered trial to assess its effectiveness and cost-effectiveness.

Implementing Prudent Healthcare in the NHS in Wales; what are the barriers and enablers for clinicians?

RATIONALE: Prudent Healthcare is a strategy adopted by the Welsh Government in response to the challenge of improving health care during times of austerity and when needs and demand are rising. Four principles underlie Prudent Healthcare: to achieve health and wellbeing through co production; care for those with the greatest health needs first; do only what is needed; and reduce inappropriate variation. For Prudent Healthcare to be implemented in Wales, it is necessary for health professionals to adopt these principles in practice. OBJECTIVE: This paper reports a qualitative evaluation of clinicians' awareness, experiences, and views about Prudent Healthcare, identifying barriers and enablers to implementation from the clinician's perspective. METHODS: Semi-structured interviews (n = 28) and five focus groups (with 23 participants) were undertaken with a diverse range of health professionals working in primary and secondary care. Analysis was underpinned by the COM-B model which provides a framework to understand behaviour change in context using three domains, Capability, Opportunity, and Motivation. RESULTS: Clinicians reported the importance and challenges of accessing and sharing information and evidence to inform practice (Capability). Reduced staffing levels and service availability were highlighted as possible barriers to Prudent Healthcare implementation while multidisciplinary working and reorganization of staff roles and services were considered enablers (Opportunity). Finally, although the principles of Prudent Healthcare were broadly welcomed (Motivation), a lack of awareness of the initiative and the management of patient expectations presented barriers. CONCLUSION: While there was a positive response and widespread support for the principles of Prudent Healthcare by clinicians, increasing awareness of the initiative and improvement to systems to enable information sharing and the monitoring of patient outcomes could improve the consistency of implementation.

Development of an intervention to expedite cancer diagnosis through primary care: a protocol.

BACKGROUND: GPs can play an important role in achieving earlier cancer diagnosis to improve patient outcomes, for example through prompt use of the urgent suspected cancer referral pathway. Barriers to early diagnosis include individual practitioner variation in knowledge, attitudes, beliefs, professional expectations, and norms. AIM: This programme of work (Wales Interventions and Cancer Knowledge about Early Diagnosis [WICKED]) will develop a behaviour change intervention to expedite diagnosis through primary care and contribute to improved cancer outcomes. DESIGN & SETTING: Non-experimental mixed-method study with GPs and primary care practice teams from Wales. METHOD: Four work packages will inform the development of the behaviour change intervention. Work package 1 will identify relevant evidence-based interventions (systematic review of reviews) and will determine why interventions do or do not work, for whom, and in what circumstances (realist review). Work package 2 will assess cancer knowledge, attitudes, and behaviour of GPs, as well as primary care teams' perspectives on cancer referral and investigation (GP survey, discrete choice experiment [DCE], interviews, and focus groups). Work package 3 will synthesise findings from earlier work packages using the behaviour change wheel as an overarching theoretical framework to guide intervention development. Work package 4 will test the feasibility and acceptability of the intervention, and determine methods for measuring costs and effects of subsequent behaviour change in a randomised feasibility trial. RESULTS: The findings will inform the design of a future effectiveness trial, with concurrent economic evaluation, aimed at earlier diagnosis. CONCLUSION: This comprehensive, evidence-based programme will develop a complex GP behaviour change intervention to expedite the diagnosis of symptomatic cancer, and may be applicable to countries with similar healthcare systems.

Trial of Optimal Personalised Care After Treatment-Gynaecological Cancer (TOPCAT-G): A Randomized Feasibility Trial.

OBJECTIVE: This study aimed to evaluate the feasibility of completing a parallel-group randomized controlled trial to compare usual follow-up care for women who have completed treatment of gynecological cancer against a nurse-led telephone intervention, known as Optimal Personalised Care After Treatment-Gynaecological. METHODS: The unblinded trial aimed to recruit patients who had completed treatment of cervical, endometrial, epithelial ovarian, or vulval cancer within the previous 3 months at 3 North Wales hospitals. We randomized participants to either usual hospital-based follow-up or specialist nurse-led telephone education, empowerment, and structured needs assessment follow-up. The primary outcomes assessed the feasibility of running a larger trial including patient eligibility, recruitment and retention rates, and outcome measure completion. Secondary outcomes were generic and health-related quality of life and a patient self-report health service use (Client Service Receipt Inventory) data collected at 3 time points (baseline, 3 months, and 6 months). RESULTS: Of the 58 women screened, 44 were eligible (76%) and 24 (55%) were recruited and randomized (12:12 to control and intervention, respectively). One participant was lost to follow-up. Recruited participants had a mean (SD) age of 60 (11.2) years and were approximately 5 months from their initial diagnosis (mean [SD], 159 [58] days). Seventeen (71%) of the participants had an endometrial cancer diagnosis. All outcome measure completion rates exceeded 96%. Although not a core feasibility objective, analyses of outcome measures indicated positive changes in quality of life and well-being within the Optimal Personalised Care After Treatment-Gynaecological group; exploratory cost consequence analysis indicated that the nurse-led intervention had a mean total service use cost of £27 per patient (bootstrapped 95% confidence interval, -£290 to £240) lower than did the standard care group. CONCLUSION: Eligibility, recruitment, and retention rates as well as outcome measure completion showed that the trial is feasible.