Abstract Timely diagnosis is critical for improving breast cancer outcomes, especially in resource-limited health systems. This study provides the first real-world evidence from Bosnia and Herzegovina on diagnostic and treatment intervals, adherence, and survival in women with breast cancer. We conducted a retrospective analysis of breast cancer cases diagnosed between 2019 and 2023 at the Clinical Centre University of Sarajevo, the largest cancer center in the country, managing approximately 60% of cases in the Federation of Bosnia and Herzegovina. Most patients (78.1%; 95% CI: 73.8–82.3) were diagnosed through self-referral due to symptoms, with 62.4% of cancers detected at stages 1 and 2. The mean patient and system diagnostic intervals were 38.1 days (95% CI: 23.4–52.8) and 38.6 days (95% CI: 29.9–47.3), respectively, with a total diagnostic interval of 70 days (95% CI: 58.9–82.5). Almost all diagnostic procedures had a waiting time of less than ten days. Among all women undergoing surgery, radical mastectomy was performed in 61% (95% CI: 55–66), while among women with stage 1–2 disease, 55% (95% CI: 48–62) underwent radical mastectomy. Treatment duration averaged 3.7 months for chemotherapy (95% CI: 3.4–4.1) and 0.48 months for radiotherapy (95% CI: 0.26–0.69), with higher compliance for radiotherapy (99.5%; 95% CI: 98–100) than chemotherapy (78%; 95% CI: 72–84). Three-year progression-free survival was 85.7%, and overall three-year survival was 86%. Early breast cancer detection and favorable survival can be achieved even in resource-constrained settings.

Background Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disorder and a major contributor to kidney failure worldwide. However, the impact of ADPKD on health-related quality of life (HRQoL) across chronic kidney disease (CKD) stages and kidney replacement therapies (KRT) is poorly understood. This study aimed to synthesize existing evidence on HRQoL as measured by patient-reported outcome measures (PROMs) in people with ADPKD, stratified by disease stage and KRT modality.Methods A systematic review was conducted using five databases (Medline, Embase, PsycINFO, CINAHL, Web of Science) and Google Scholar to identify studies published between January 2014 and October 2024. Eligible studies reported HRQoL in individuals with ADPKD using generic, kidney-specific, or ADPKD-specific PROMs Study populations were stratified by CKD stage and KRT modality. Scores were adjusted using country-specific population norms matched for age and sex, with population multipliers calculated to express patient-reported outcomes (PROs) as a proportion of the reference population.Results Six studies assessed PROs using the Short-Form-36/12 survey. Physical health worsened with CKD progression, corresponding to lower values relative to matched population norms. Mental health showed smaller deviations from population norms. Dialysis patients had the lowest physical health multipliers, while transplant recipients had better physical health it did not improve to early-stage CKD levels. Two studies using the EuroQual 5-Dimension tool had fewer notable differences between CKD stages. Kidney disease and ADPKD-specific scores showed more pronounced declines across CKD stages than generic PROMs, suggesting greater sensitivity to stage-related changes.Conclusions This review demonstrates that PROs for individuals with ADPKD are lower in later CKD stages compared with earlier stages, with the largest effect on physical health. Mental health scores were less affected suggesting adaptation over time. Our findings suggest generic PROMs may underestimate the impact of ADPKD compared to disease-specific tools.

Introduction Breast cancer is a leading cause of cancer-related death among women. Women with lower income, those living in rural areas and women of Black ethnicity are more likely to be diagnosed at advanced stages and have poorer survival outcomes. Reducing these inequities is an important public health priority. This study aimed to identify a cost-effective strategy for reducing breast cancer-related inequities and to evaluate the equity impact of the intervention across population subgroups.Methods We developed a novel individual-level microsimulation model to assess both the equity impact and cost-effectiveness of a community health worker-led education intervention in rural areas. The model, with annual cycles, simulated rural and urban breast cancer populations in South Africa using data from national and regional cancer datasets and followed individuals over a lifetime horizon. Costs were estimated from the provider perspective and outcomes included life-years, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs) compared with three willingness-to-pay thresholds (ZAR 58 018/ZAR 109 468/ZAR 328 408). Parameter uncertainty was explored using probabilistic sensitivity analysis. Equity impact was evaluated by estimating changes in age-standardised all-cause mortality across subgroups defined by place of residence (rural vs urban) and ethnicity (Black vs non-Black), using both absolute (rate differences) and relative (rate ratios) measures.Results The intervention generated average gains of 0.35 life-years and 0.31 QALYs per patient across the breast cancer population. Inequities by residence decreased, with an absolute reduction of 229.65 per 1000 patients with breast cancer in the age-standardised mortality rate difference, and a relative reduction in the rate ratio of 0.80. By ethnicity, absolute and relative reductions of 110.26 per 1000 patients and 0.27, respectively, were observed between Black and non-Black populations. The intervention was cost-effective, with an ICER of ZAR 44 124 (I$6036) per QALY gained, which is below all three willingness-to-pay thresholds considered.Conclusions Community health worker programmes represent a cost-effective strategy to reduce breast cancer-related inequities. Their integration into national cancer control plans in low-income and middle-income countries should be prioritised and supported.

OBJECTIVES:To assess the cost-effectiveness of expanding the current opportunistic screening strategy to an organised and feasible population-based breast cancer screening strategy from the healthcare system perspective in Jordan. DESIGN:A probabilistic, state-transition cohort decision-analytic model was developed to estimate the expected incremental life years (LYs), quality-adjusted life years (QALYs) and costs. PARTICIPANTS:The model includes a hypothetical cohort of average-risk asymptomatic Jordanian women aged 40 years and above. INTERVENTIONS:The base case comparison was between organised mammography with a 50% attendance rate and opportunistic mammography for asymptomatic women aged 40-70 years and older over a lifetime horizon. Multiple organised mammogram screening strategies were assessed that varied in screening interval and start and end age (strategy 1: 40-60 biennial, strategy 2: 50-65 annual, strategy 3: 50-65 biennial, strategy 4: 40-70 biennial, strategy 5: 50-70 biennial and strategy 6: 40-49 annual). SETTING:This model-based economic evaluation study was conducted to reflect the context of the Jordanian healthcare system. MEASUREMENT:We identified, measured and valued resources and outcomes to populate the model. Transition probabilities were estimated from the literature, the cancer registry or through calibration. The screening test's specificity and sensitivity were obtained from the literature. Costs and utility weights were extracted from national databases and literature. Both costs and outcomes were discounted using an annual discount rate of 3%. The model's uncertainty was tested using deterministic and probabilistic sensitivity analysis. RESULTS:Over a lifetime horizon, strategy 3 (50-65 biennial, 50% attendance rate) resulted in a mean discounted LYs of 22.077, a mean discounted QALYs of 16.993 and a mean discounted cost of US$994 compared with opportunistic screening, which resulted in a mean discounted LYs of 22.062, a mean discounted QALYs of 16.980 and a mean discounted cost of US$889. The incremental cost-utility ratio (ICUR) relative to opportunistic screening is US$6734 per QALY. Strategy 3 ranks first as the most cost-effective organised screening strategy for the Jordanian healthcare system, followed by strategy 4 with an ICUR of US$18 024 per QALY and strategy 6 with an ICUR of US$62 418 per QALY. The three strategies were presented on the cost-effectiveness frontier. The deterministic sensitivity analysis showed that the results were sensitive to the cost of the screening package and the annual discount rate. CONCLUSION:At a willingness-to-pay cost-effectiveness threshold of US$42000-56000 per QALY, strategy 3 (50-65 biennial, 50% attendance rate) and strategy 4 (40-70 biennial, 50% attendance rate) are likely to be cost-effective in Jordan. However, prior to implementation, the affordability of each strategy and the availability of required infrastructure must be carefully evaluated.

Modelling the cost effectiveness of screening interventions presents unique challenges. These relate to a lack of knowledge about underlying health states and disease progression in the absence of screening, added costs arising from incidental findings, screening recall and follow-up diagnostics, imperfect uptake, potential harms to otherwise healthy people, and impacts on resource capacity and equity. No specific but generalisable advice currently exists to help guide health economic modellers working in this area. There is a need for tailored recommendations beyond the widely used, health economic modelling frameworks. We aimed to develop a set of recommendations for modelling the cost effectiveness of screening programmes. In our iterative process, we first drafted a conceptual document outlining key issues requiring recommendations. This framework was then expanded based on additional themes identified through a survey of screening modelling experts. Next, the draft recommendations were shared with a broader international expert group, which included modellers, health economists and policy specialists. Finally, the core concepts were refined and agreed upon during a virtual stakeholder meeting. A set of ten recommendations and a checklist are presented. The document provides guidance on critical methodological requirements for modelling screening interventions. These guidelines are intended to help health economic modellers and screening policy makers working to evaluate screening interventions across a wide range of diseases and jurisdictions with clarity, rigour and consistency.

Introduction: The potential for multi-cancer early detection (MCED) tests to detect cancer at earlier stages is currently being evaluated in screening clinical trials. Once trial evidence becomes available, modelling will be necessary to predict impacts on final outcomes (benefits and harms), account for heterogeneity in determining clinical and cost-effectiveness, and explore alternative screening programme specifications. The natural history of disease (NHD) component of a MCED model will use statistical, mathematical or calibration methods. Methods: Modelling approaches for MCED screening that include an NHD component were identified from the literature, reviewed and critically appraised. Purposively selected (non-MCED) cancer screening models were also reviewed. The appraisal focussed on the scope, data sources, evaluation approaches and the structure and parameterisation of the models. Results: Five different MCED NHD models were identified and reviewed, alongside four additional (non-MCED) models. The critical appraisal highlighted several features of this literature. In the absence of trial evidence, MCED effects are based on predictions derived from test accuracy. These predictions rely on simplifying assumptions with unknown impacts, such as the stage-shift assumption used to estimate mortality impacts from predicted stage-shifts. None of the MCED models fully characterised uncertainty in the NHD or examined uncertainty in the stage-shift assumption. Conclusion: MCED technologies are developing rapidly, and large and costly clinical studies are being designed and implemented across the globe. Currently there is no modelling approach that can integrate clinical study evidence and therefore, in support of policy, it is important that similar efforts are made in the development of MCED models that make best use of the available data on benefits and harms.

Introduction:Fecal immunochemical testing (FIT) at a threshold of 10 mg haemaglobin (Hb)/g is used in English primary care to prioritise urgent referral for colorectal cancer (CRC) investigation in symptomatic patients. The COLOFIT algorithm, based on FIT score, age, sex and blood results, performs better than FIT alone for identifying CRC. We assessed the cost-effectiveness of COLOFIT compared with FIT and investigated optimal risk thresholds. Methods:An individual patient-level simulation model was developed, with synthetic populations constructed from data used to validate COLOFIT. Referral criteria based on different FIT scores and COLOFIT-assessed risk thresholds were modelled using probabilistic and scenario analyses. Outcomes included costs, quality-adjusted life years (QALYs) and cost-effectiveness measured using incremental net monetary benefit (INMB) based on a willingness to pay threshold of £20 000/QALY. Results:COLOFIT at a CRC risk threshold of 0.64% has a 98% probability of being more cost-effective than FIT 10 mg Hb/g (INMB is £5.67 per person), while detecting similar numbers of cancers. Cost-effectiveness is achieved by cost savings from reducing referrals outweighing QALYs lost through reorienting expedited CRC diagnoses from younger (<50) to older (≥70) patients. Cost-effectiveness improves as risk thresholds rise. High structural uncertainty around cancer progression during diagnostic delay and diagnosis of other serious bowel diseases considerably affects cost-effectiveness. Conclusions:COLOFIT is likely to be more cost-effective than FIT alone and could help alleviate pressure on diagnostic services. However, strategies to improve diagnosis in the under 50s would be necessary to mitigate potential harm. Further research should assess how COLOFIT impacts cancer survival and diagnosis of other serious bowel diseases.

Testing high-risk populations for non-visible haematuria may enable earlier detection of bladder cancer, potentially decreasing mortality. This research aimed to assess the cost-effectiveness of urine dipstick screening for bladder cancer in high-risk populations in England. A microsimulation model developed in R software was calibrated to national incidence data by age, sex and stage, and validated against mortality data. Individual risk factors included age, sex, smoking status and factory employment. We evaluated three one-time screening scenarios: (1) current and former smokers of different ages within the 55–70 years range, (2) a mixed-age cohort of smokers aged 55–80 years and (3) individuals aged 65–79 years from high-risk regions. Probabilistic and scenario analyses evaluated uncertainty. The incremental cost-effectiveness ratio (ICER) was calculated and compared with the standard £20,000/quality-adjusted life year (QALY) threshold using payer’s perspective and 2022 year of evaluation with 3.5

OBJECTIVES:The World Health Organization emphasizes screening and early diagnosis to reduce advanced cancer incidence and mortality. In low-to-middle-income countries, breast cancer (BC) survival rates are low because of late detection. South Africa's policy recommends twice-yearly clinical breast examinations (CBEs) for asymptomatic women aged 40 to 69. We assessed the impact of scaling up CBE screening on mortality and cost-effectiveness. METHODS:Using trial data on downstaging, we compared the current baseline (5% coverage) with scenario 1 (25% coverage by year 5 [ie, 5% increase annually]) and scenario 2 (75% coverage by year 5, [ie, 17.5% increase annually]). A cohort model tracked women from screening to diagnosis, estimating downstaging's impact on BC cases over their lifetime. Costs from the healthcare payer's perspective are presented in 2022 US dollars. RESULTS:Five-year screen detection rates were 2.39 and 2.08 per 1000 women screened for scenarios 1 and 2, respectively. Scenario 1 reduced BC mortality by 0.7% and scenario 2 by 2.3%. Compared with no screening, the current baseline screening program averts 1645 disability-adjusted life years (DALYs) at $20 341/DALY averted. Scenario 1 averted 3823 DALYs with economic efficiency improving to $17 776/DALY averted, whereas scenario 2 averted 12 165 DALYs at $19 552/DALY averted. CONCLUSIONS:CBE scale-up effectively saves life years but is not cost-effective under the country's opportunity cost-derived threshold of $3015/DALY averted. However, decisions on the best screening policy are not solely based on cost-effectiveness. They involve careful consideration of budgetary constraints and competing healthcare priorities. Scale-up should consider system capacity, minimum care standards and cost-effective early detection strategies.

BackgroundThe online nature of decision aids (DAs) and related e-tools supporting women’s decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs. ObjectiveThis systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy. MethodsWe followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023. We included studies reporting on populations at average risk of breast cancer, which utilized DAs or related e-tools, and assessed women’s participation in BCS by mammography or other key cognitive determinants of decision-making as primary or secondary outcomes. We conducted meta-analyses on the identified randomized controlled trials, which were assessed using the revised Cochrane Risk of Bias 2 (RoB 2) tool. We further explored intermediate and high heterogeneity between studies to enhance the validity of our results. ResultsIn total, 22 different e-tools were identified across 31 papers. The degree of tailoring in the e-tools, specifically whether the tool was fully tailored or featured with tailoring, was the most influential factor in women’s decision-making regarding BCS. Compared with control groups, tailored e-tools significantly increased women’s long-term participation in BCS (risk ratio 1.14, 95% CI 1.07-1.23, P<.001, I2=0%). Tailored-to-breast-cancer-risk e-tools increased women’s level of worry (mean difference 0.31, 95% CI 0.13-0.48, P<.001, I2=0%). E-tools also improved women’s adequate knowledge of BCS, with features-with-tailoring e-tools designed and tested with the general population being more effective than tailored e-tools designed for or tested with non-BCS participants (χ21=5.1, P=.02). Features-with-tailoring e-tools increased both the rate of women who intended not to undergo BCS (risk ratio 1.88, 95% CI 1.43-2.48, P<.001, I2=0%) and the rate of women who had made an informed choice regarding their intention to undergo BCS (risk ratio 1.60, 95% CI 1.09-2.33, P=.02, I2=91%). Additionally, these tools decreased the proportion of women with decision conflict (risk ratio 0.77, 95% CI 0.65-0.91, P=.002, I2=0%). Shared decision-making was not formally evaluated. This review is limited by small sample sizes, including only a few studies in the meta-analysis, some with a high risk of bias, and high heterogeneity between the studies and e-tools. ConclusionsFeatures-with-tailoring e-tools could potentially negatively impact BCS programs by fostering negative intentions and attitudes toward BCS participation. Conversely, tailored e-tools may increase women’s participation in BCS but, when tailored to risk, they may elevate their levels of worry. To maximize the effectiveness of e-tools while minimizing potential negative impacts, we advocate for an “on-demand” layered approach to their design.

Nephrology has benefited from a growing body of high-quality clinical evidence, including clinical trials of pharmacological therapies and health service research on alternative care approaches. Consequently, there is an increasing need to perform economic evaluations in kidney disease to inform reimbursement decisions and optimise healthcare spending, thereby improving patient care within budget constraints. Cost-effectiveness assesses if the additional health gains are worth any additional costs by estimating differences in the quality and quantity of life, and the costs, from the point of intervention over observed but also longer (even lifetime) timelines, capturing the entire patient pathway through healthcare, e.g. from early-stage chronic kidney disease (CKD) through to dialysis or transplantation. Working with stakeholders to define the decision problem, merging evidence from a range of sources, including clinical trials complicated by limited follow-up and non-generalisable participants, surrogacy studies to estimate the intervention's impact on longer-term kidney failure risk, quality of life data collected ideally using instruments sensitive to kidney disease progression and other real-world data are required to make extrapolations sufficiently far into the patient's lifetime to capture kidney failure. Consideration of disadvantaged populations and how interventions may operate differently in certain groups may be indicated. Failure to capture competing risks of cardiovascular disease and death will bias estimates of kidney failure. Application of our tips, combined with an understanding of how decision-makers use cost-effectiveness results and information about factors like rarity and disease severity maximises the likelihood of new kidney treatments and care approaches being adopted.

Background:Genomic and ultrasound tests can provide diagnostic and prognostic information on autosomal-dominant polycystic kidney disease (ADPKD), and can screen first-degree relatives in whom early diagnosis can be advantageous. We conducted a systematic mapping review on test accuracy and characteristics over time. Methods:Medline, Embase, and Cochrane were searched (August 2023) for studies in first-degree relatives/individuals clinically diagnosed with ADPKD receiving genomic or ultrasound tests. Acceptable reference standards for sensitivity/detection rate and specificity were definitive imaging or genomic confirmation. Genomic studies were categorized by technology and read length. Relationships between sensitivity, specificity, genomic technology, diagnostic criteria/reference standard, and genes tested were compared. Results:From 1029 non-duplicate titles retrieved, 51 genomic and 7 ultrasound studies were included. There were no genomic studies in first-degree relatives. Among studies in patients with clinical diagnoses, genomic sequencing methodologies were highly heterogeneous [next generation (short read (n = 20), long read (n = 1)), targeted Sanger (n = 19), whole exome (n = 1) with additional multi-ligation probe analysis (n = 13)]. Median sensitivity was 78% (Interquartile range 65% to 88%). Ultrasound sensitivity and specificity generally improved with age and were worse in PKD2 patients compared to PKD1 (lowest reported 31% and 88%, respectively, in polycystic kidney disease (PKD) 2 patients aged 5-14; highest 100% and 100%, respectively, in multiple gene/age categories). Conclusions:Despite technological advances, sensitivity of genomic tests appeared static between 2000 and 2023. Possible explanations include clinical diagnostic criteria (and hence populations recruited) widening from PKD1 to include PKD2 and atypical phenotypes, and small incremental gains of testing genes other than PKD1 and PKD2. For people at risk of ADPKD in genetically unresolved families, the accuracy of ultrasound is uncertain. Unified genomic test taxonomies would facilitate future reviews. Registration: PROSPERO CRD42023456727.

ImportancePrevious research has shown good discrimination of short-term risk using an artificial intelligence (AI) risk prediction model (Mirai). However, no studies have been undertaken to evaluate whether this might translate into economic gains.ObjectiveTo assess the cost-effectiveness of incorporating risk-stratified screening using a breast cancer AI model into the United Kingdom (UK) National Breast Cancer Screening Program.Design, Setting, and ParticipantsThis study, conducted from January 1, 2023, to January 31, 2024, involved the development of a decision analytical model to estimate health-related quality of life, cancer survival rates, and costs over the lifetime of the female population eligible for screening. The analysis took a UK payer perspective, and the simulated cohort consisted of women aged 50 to 70 years at screening.ExposuresMammography screening at 1 to 6 yearly screening intervals based on breast cancer risk and standard care (screening every 3 years).Main Outcomes and MeasuresIncremental net monetary benefit based on quality-adjusted life-years (QALYs) and National Health Service (NHS) costs (given in pounds sterling; to convert to US dollars, multiply by 1.28).ResultsArtificial intelligence–based risk-stratified programs were estimated to be cost-saving and increase QALYs compared with the current screening program. A screening schedule of every 6 years for lowest-risk individuals, biannually and triennially for those below and above average risk, respectively, and annually for those at highest risk was estimated to give yearly net monetary benefits within the NHS of approximately £60.4 (US $77.3) million and £85.3 (US $109.2) million, with QALY values set at £20 000 (US $25 600) and £30 000 (US $38 400), respectively. Even in scenarios where decision-makers hesitate to allocate additional NHS resources toward screening, implementing the proposed strategies at a QALY value of £1 (US $1.28) was estimated to generate a yearly monetary benefit of approximately £10.6 (US $13.6) million.Conclusions and RelevanceIn this decision analytical model study of integrating risk-stratified screening with a breast cancer AI model into the UK National Breast Cancer Screening Program, risk-stratified screening was likely to be cost-effective, yielding added health benefits at reduced costs. These results are particularly relevant for health care settings where resources are under pressure. New studies to prospectively evaluate AI-guided screening appear warranted.

BACKGROUND:Breast cancer is the most diagnosed cancer in the world, with a worse prognosis documented in low- and middle-income countries. Inequalities pertaining to breast cancer outcomes are observed at within-country level, with demographics and socioeconomic status as major drivers. AIM:This review aims to aggregate all available evidence from low- and middle-income countries on public health interventions that can be utilized to reduce breast cancer inequalities within the breast cancer continuum. METHODS:The study was a systematic review and narrative synthesis of available literature, with the literature search conducted between September and October 2021. The search was re-run in September 2022 to update the review. PubMed, Scopus, Embase, African Index Medicus and LILACS were searched, based on predetermined criteria. Randomized controlled trials, cohort studies and quasi-experimental studies were included for review, while studies without an intervention and comparator group were excluded. The Joanna Briggs Institute family of checklists was used for quality assessment of the included studies. Data pertaining to study design, quality control and intervention effectiveness was extracted. RESULTS:A total of 915 studies were identified for screening and 21 studies met the selection criteria. Only one study specifically evaluated the impact of an intervention on breast cancer inequalities. Diverse, multi-level interventions that can be utilized to address breast cancer inequalities through targeted application to disadvantaged subpopulations were identified. Educational interventions were found to be effective in improving screening rates, downstaging through early presentation as well as improving time to diagnosis. Interventions aimed at subsidizing or eliminating screening payments resulted in improved screening rates. Patient navigation was highlighted to be effective in improving outcomes throughout the breast cancer continuum. CONCLUSION:Findings from the systematic review underline the importance of early detection in breast cancer management for low- and middle-income countries. This can be achieved through a variety of interventions, including population education, and addressing access barriers to public health services such as screening, particularly among under-served populations. This study provides a comprehensive database of public health interventions relevant to low- and middle-income countries that can be utilized for planning and decision-making purposes. Findings from the review highlight an important research gap in primary studies on interventions aimed at reducing breast cancer inequalities in low- and middle-income countries. SYSTEMATIC REVIEW REGISTRATION:PROSPERO registration number: CRD42021289643.

Screening aims to detect cancer in asymptomatic populations. In oral cancer, clinical oral examination is the current standard method for screening. Oral cancer screening may be performed by a physician or a healthcare workers and is an affordable and feasible method. There is some evidence that this low-cost method is effective in decreasing mortality from oral cancer in high risk population. The cluster-randomised trial in India that had 15 years of follow-up reported an 81 % mortality reduction in high-risk populations of tobacco and/or alcohol users who adhered to four screening rounds. The observational studies similarly reported 21-22 % reduction in advanced oral cancer and 24-26 % reduction in oral cancer mortality among high risk population. Implementation and evaluation of oral cancer screening programmes in high risk population will support the goals of the World Health Organisation on global oral health.

Background and ObjectiveBladder cancer is common among current and former smokers. High bladder cancer mortality may be decreased through early diagnosis and screening. The aim of this study was to appraise decision models used for the economic evaluation of bladder cancer screening and diagnosis, and to summarise the main outcomes of these models.MethodsMEDLINE via PubMed, Embase, EconLit and Web of Science databases was systematically searched from January 2006 to May 2022 for modelling studies that assessed the cost effectiveness of bladder cancer screening and diagnostic interventions. Articles were appraised according to Patient, Intervention, Comparator and Outcome (PICO) characteristics, modelling methods, model structures and data sources. The quality of the studies was also appraised using the Philips checklist by two independent reviewers.ResultsSearches identified 3082 potentially relevant studies, which resulted in 18 articles that met our inclusion criteria. Four of these articles were on bladder cancer screening, and the remaining 14 were diagnostic or surveillance interventions. Two of the four screening models were individual-level simulations. All screening models (n = 4, with three on a high-risk population and one on a general population) concluded that screening is either cost saving or cost effective with cost-effectiveness ratios lower than $53,000/life-years saved. Disease prevalence was a strong determinant of cost effectiveness. Diagnostic models (n = 14) assessed multiple interventions; white light cystoscopy was the most common intervention and was considered cost effective in all studies (n = 4). Screening models relied largely on published evidence generalised from other countries and did not report the validation of their predictions to external data. Almost all diagnostic models (n = 13 out of 14) had a time horizon of 5 years or less and most of the models (n = 11) did not incorporate health-related utilities. In both screening and diagnostic models, epidemiological inputs were based on expert elicitation, assumptions or international evidence of uncertain generalisability. In modelling disease, seven models did not use a standard classification system to define cancer states, others used risk-based, numerical or a Tumour, Node, Metastasis classification. Despite including certain components of disease onset or progression, no models included a complete and coherent model of the natural history of bladder cancer (i.e. simulating the progression of asymptomatic primary bladder cancer from cancer onset, i.e. in the absence of treatment).ConclusionsThe variation in natural history model structures and the lack of data for model parameterisation suggest that research in bladder cancer early detection and screening is at an early stage of development. Appropriate characterisation and analysis of uncertainty in bladder cancer models should be considered a priority.

Introduction Around 25% of patients with bladder cancer (BCa) present with invasive disease. Non-randomised studies of population-based screening have suggested reductions in BCa-specific mortality are possible through earlier detection. The low prevalence of lethal disease in the general population means screening is not cost-effective and there is no consensus on the best strategy. Yorkshire has some of the highest mortality rates from BCa in England. We aim to test whether population screening in a region of high mortality risk will lead to a downward stage-migration of aggressive BCa, improved survival and is cost-effective.Methods and analysis YORKSURe is a tiered, randomised, multicohort study to test the feasibility of a large BCa screening randomised controlled trial. In three parallel cohorts, participants will self-test urine (at home) up to six times. Results are submitted via a mobile app or freephone. Those with a positive result will be invited for further investigation at community-based early detection clinics or within usual National Health Service (NHS) pathways. In Cohort 1, we will post self-testing kits to research engaged participants (n=2000) embedded within the Yorkshire Lung Screening Trial. In Cohort 2, we will post self-testing kits to 3000 invitees. Cohort 2 participants will be randomised between haematuria and glycosuria testing using a reveal/conceal design. In Cohort 3, we will post self-testing kits to 500 patients within the NHS pathway for investigation of haematuria. Our primary outcomes are rates of recruitment and randomisation, rates of positive test and acceptability of the design. The study is currently recruiting and scheduled to finish in June 2023.Ethics and dissemination The study has received the following approvals: London Riverside Research Ethics Committee (22/LO/0018) and Health Research Authority Confidentiality Advisory Group (20/CAG/0009). Results will be made available to providers and researchers via publicly accessible scientific journals.Trial registration number ISRCTN34273159.

ObjectiveWe report NHS England data for patients with bladder cancer (BC), upper tract urothelial cancer (UTUC: renal pelvic and ureteric), and urethral cancers from 2013 to 2019.Materials and MethodsHospital episode statistics, waiting times, and cancer registrations were extracted from NHS Digital.ResultsRegistrations included 128 823 individuals with BC, 16 018 with UTUC, and 2533 with urethral cancer. In 2019, 150 816 persons were living with a diagnosis of BC, of whom 113 067 (75.0%) were men, 85 117 (56.5%) were aged >75 years, and 95 553 (91.7%) were Caucasian. Incidence rates were stable (32.7–34.3 for BC, 3.9–4.2 for UTUC and 0.6–0.7 for urethral cancer per 100 000 population). Most patients 52 097 (mean [range] 41.3% [40.7–42.0%]) were referred outside the 2‐week‐wait pathway and 15 340 (mean [range] 12.2% [11.7–12.6%]) presented as emergencies. Surgery, radiotherapy, chemotherapy, or multimodal treatment use varied with disease stage, patient factors and Cancer Alliance. Between 27% and 29% (n = 6616) of muscle‐invasive BCs did not receive radical treatment. Survival rates reflected stage, grade, location, and tumour histology. Overall survival rates did not improve over time (relative change: 0.97, 95% confidence interval 0.97–0.97) at 2 years in contrast to other cancers.ConclusionThe diagnostic pathway for BC needs improvement. Increases in survival might be delivered through greater use of radical treatment. NHS Digital data offers a population‐wide picture of this disease but does not allow individual outcomes to be matched with disease or patient features and key parameters can be missing or incomplete.

Oral cancer (OC) is a debilitating disease with a high mortality rate when diagnosed in advanced stage. Conversely, early-stage OC has a high survival rate, supporting a need for early detection programmes. A previous systematic review of clinical trials evaluating efficacy of screening for OC was inconclusive. This systematic review aimed to determine the impact of screening for oral lesions on reducing mortality and incidence of OC by looking at a broader spectrum of evidence. The search for randomized controlled trials and observational studies with a control group was conducted in PubMed, OVID, Cochrane, CINAHL and grey literature sources. Risk of bias for included studies was assessed with the tools developed by the Cochrane collaboration. Six out of two identified randomized trials and five observational studies had moderate to high risk of bias. Nevertheless, the predictions on impact of OC screening on incidence and mortality were similar across the majority of the studies. The meta-analysis concluded on a 26% decrease in OC mortality, and an 19% decrease in advanced OC cases as a result of OC screening in high-risk population. Three out of four studies did not identify an impact of screening on OC incidence. No positive impact of OC screening on incidence or mortality among general population was identified in the only available randomized trial. Consistency in the outcomes and the limitations of the few available studies suggest a need for real-life setting research to evaluate the overall effectiveness of screening for OC in high-risk population.

Although BRCA1/2 genetic testing in developed countries is part of the reality for high-risk patients for hereditary breast and ovarian cancer (HBOC), the same is not true for upper-middle-income countries. For that reason, this study aimed to evaluate whether the BRCA1/2 genetic test and preventive strategies for women at high risk for HBOC are cost-effective compared to not performing these strategies in an upper-middle-income country. Adopting a payer perspective, a Markov model with a time horizon of 70 years was built to delineate the health states for a cohort of healthy women aged 30 years that fulfilled the BRCA1/2 testing criteria according to the guidelines. Transition probabilities were calculated based on real-world data of women tested for BRCA1/2 germline mutations in a cancer reference hospital from 2011 to 2020. We analyzed 275 BRCA mutated index cases and 356 BRCA mutation carriers that were first- or second-degree relatives of the patients. Costs were based on the Brazilian public health system reimbursement values. Health state utilities were retrieved from literature. The BRCA1/2 genetic test and preventive strategies result in more quality-adjusted life years (QALYs) and costs with an incremental cost-effectiveness ratio of R$ 11,900.31 (U$ 5,504.31)/QALY. This result can represent a strong argument in favor of implementing genetic testing strategies for high-risk women even in countries with upper-middle income, considering not only the cancer prevention possibilities associated with the genetic testing but also its cost-effectiveness to the health system. These strategies are cost-effective, considering a willingness-to-pay threshold of R$ 25,000 (U$ 11,563.37)/QALY, indicating that the government should consider offering them for women at high risk for HBOC. The results were robust in deterministic and probabilistic sensitivity analyses.