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BACKGROUND: Our prototype smoking cessation chatbot, Quin, provides evidence-based, personalized support delivered via a smartphone app to help people quit smoking. We developed Quin using a multiphase program of co-design research, part of which included focus group evaluation of Quin among stakeholders prior to clinical testing. OBJECTIVE: This study aimed to gather and compare feedback on the user experience of the Quin prototype from end users and smoking cessation professionals (SCPs) via a beta testing process to inform ongoing chatbot iterations and refinements. METHODS: Following active and passive recruitment, we conducted web-based focus groups with SCPs and end users from Queensland, Australia. Participants tested the app for 1-2 weeks prior to focus group discussion and could also log conversation feedback within the app. Focus groups of SCPs were completed first to review the breadth and accuracy of information, and feedback was prioritized and implemented as major updates using Agile processes prior to end user focus groups. We categorized logged in-app feedback using content analysis and thematically analyzed focus group transcripts. RESULTS: In total, 6 focus groups were completed between August 2022 and June 2023; 3 for SCPs (n=9 participants) and 3 for end users (n=7 participants). Four SCPs had previously smoked, and most end users currently smoked cigarettes (n=5), and 2 had quit smoking. The mean duration of focus groups was 58 (SD 10.9; range 46-74) minutes. We identified four major themes from focus group feedback: (1) conversation design, (2) functionality, (3) relationality and anthropomorphism, and (4) role as a smoking cessation support tool. In response to SCPs' feedback, we made two major updates to Quin between cohorts: (1) improvements to conversation flow and (2) addition of the "Moments of Crisis" conversation tree. Participant feedback also informed 17 recommendations for future smoking cessation chatbot developments. CONCLUSIONS: Feedback from end users and SCPs highlighted the importance of chatbot functionality, as this underpinned Quin's conversation design and relationality. The ready accessibility of accurate cessation information and impartial support that Quin provided was recognized as a key benefit for end users, the latter of which contributed to a feeling of accountability to the chatbot. Findings will inform the ongoing development of a mature prototype for clinical testing.
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Grupos Focales , Cese del Hábito de Fumar , Humanos , Cese del Hábito de Fumar/métodos , Cese del Hábito de Fumar/psicología , Queensland , Masculino , Adulto , Femenino , Persona de Mediana Edad , Aplicaciones MóvilesRESUMEN
OBJECTIVE: This scoping review synthesises Australian evidence on associations between tobacco and vape retailer density/proximity and various population measures and smoking behaviour to identify research gaps and inform future policy and strategies. DATA SOURCES: Following Joanna Briggs Institute methodology, relevant studies published in English since 2003 were identified via searches of eight databases in March and August 2023. STUDY SELECTION: Two reviewers independently completed screening procedures. Eligible studies were from Australia and described associations between tobacco or vape retailer density/proximity and adult or youth smoking/vaping prevalence or behaviours, neighbourhood socioeconomic status, geographic location, school locations and/or Indigenous status. DATA EXTRACTION: Results are reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. DATA SYNTHESIS: Of 794 publications screened, 12 studies from 6 Australian states were included. Six studies from five states reported statistically significant associations between neighbourhood-level socioeconomic disadvantage and tobacco retailer density, yet only two studies from two states found a significant relationship between retailer density and adult smoking prevalence. Increasing retailer density was consistently significantly associated with increasing geographical remoteness in three states. No studies explored associations with tobacco retailer proximity or vape retailer density/proximity. CONCLUSIONS: Despite a moderate number of studies overall, state-level evidence is limited, and unknown for Australian territories. Evidence from five Australian states reflects the international evidence that increasing retailer density is significantly associated with increasing socioeconomic disadvantage and remoteness, supporting the need for tobacco supply-based policies. Further research is required to understand the impact of retailer density and adult and youth smoking prevalence in Australia.
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BACKGROUND: Lung cancer is the most common type of cancer. Detection of lung cancer at an early stage can reduce mortality rates. Pulmonary nodules may represent early cancer and can be identified through computed tomography (CT) scans. Malignant risk can be estimated based on attributes like size, shape, location, and density. PURPOSE: Deep learning algorithms have achieved remarkable advancements in this domain compared to traditional machine learning methods. Nevertheless, many existing anchor-based deep learning algorithms exhibit sensitivity to predefined anchor-box configurations, necessitating manual adjustments to obtain optimal outcomes. Conversely, current anchor-free deep learning-based nodule detection methods normally adopt fixed-size nodule models like cubes or spheres. METHODS: To address these technical challenges, we propose a multiscale 3D anchor-free deep learning network (M3N) for pulmonary nodule detection, leveraging adjustable nodule modeling (ANM). Within this framework, ANM empowers the representation of target objects in an anisotropic manner, with a novel point selection strategy (PSS) devised to accelerate the learning process of anisotropic representation. We further incorporate a composite loss function that combines the conventional L2 loss and cosine similarity loss, facilitating M3N to learn nodules' intensity distribution in three dimensions. RESULTS: Experiment results show that the M3N achieves 90.6% competitive performance metrics (CPM) with seven predefined false positives per scan on the LUNA 16 dataset. This performance appears to exceed that of other state-of-the-art deep learning-based networks reported in their respective publications. Individual test results also demonstrate that M3N excels in providing more accurate, adaptive bounding boxes surrounding the contours of target nodules. CONCLUSIONS: The newly developed nodule detection system reduces reliance on prior knowledge, such as the general size of objects in the dataset, thus it should enhance overall robustness and versatility. Distinct from traditional nodule modeling techniques, the ANM approach aligns more closely with the morphological characteristics of nodules. Time consumption and detection results demonstrate promising efficiency and accuracy which should be validated in clinical settings.
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BACKGROUND AND OBJECTIVE: Unwarranted variations in lung cancer care have been well described in both Australia and Aotearoa New Zealand, with shortfalls in hospital-based workforce and infrastructure previously demonstrated. A survey of lung cancer clinicians was performed to gain an updated understanding of current workforce and infrastructure. METHODS: An online Qualtrics survey included questions on institutional demographics, estimated lung cancer case load, multidisciplinary team (MDT) characteristics including workforce and local infrastructure. We sought to obtain one response from every institution treating lung cancer in Australia and Aotearoa New Zealand. RESULTS: Responses were received from 89 institutions, estimated to include 85% centres treating lung cancer in Australia and 100% of public hospitals in Aotearoa New Zealand. Lung cancer nurse specialist and Nuclear Medicine are poorly represented in multidisciplinary teams (MDTs) with just 34/88 (38%) institutions fulfilling recommended core workforce for MDT meetings. Case presentation is low with 32/88 (36%) regularly discussing all lung cancer patients at MDT. Metropolitan institutions appear to have a more comprehensive range of services on site, compared to non-metropolitan institutions. Few (4/88) institutions have embedded smoking cessation services. Compared to the previous 2021 Landscape Survey, thoracic surgery representation and core MDT workforce have improved, with modest change in specialist nurse numbers. CONCLUSION: This wide-reaching survey has identified persistent deficiencies and variations in lung cancer workforce and gaps in infrastructure. Multidisciplinary collaboration and care coordination are needed to ensure all patients can access timely and equitable lung cancer care.
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Neoplasias Pulmonares , Humanos , Neoplasias Pulmonares/epidemiología , Neoplasias Pulmonares/terapia , Nueva Zelanda/epidemiología , Encuestas y Cuestionarios , Pulmón , Australia/epidemiologíaRESUMEN
Background: Low dose computed tomography (LDCT) screening, targeted at those at high-risk, has been shown to significantly reduce lung cancer mortality and detect cancers at an early stage. Practical, attitudinal and demographic factors can inhibit screening participation in high-risk populations. This study aimed to explore stakeholders' views about barriers and enablers (determinants) to participation in lung cancer screening (LCS) in Australia. Methods: Twenty-four focus groups (range 2-5 participants) were conducted in 2021 using the Zoom platform. Participants were 84 health professionals, researchers, policy makers and program managers of current screening programs. Focus groups consisted of a structured presentation with facilitated discussion lasting about 1 hour. The content was analysed thematically and mapped to the Consolidated Framework for Implementation Research (CFIR). Results: Screening determinants were identified across each stage of the proposed screening and assessment pathway. Challenges included participant factors such as encouraging participation for individuals at high-risk, whilst ensuring that access and equity issues were carefully considered in program design. The development of awareness campaigns that engaged LCS participants and health professionals, as well as streamlined referral processes for initial entry and follow-up, were strongly advocated for. Considering practical factors included the use of mobile vans in convenient locations. Conclusions: Participants reported that LCS in Australia was acceptable and feasible. Participants identified a complex set of determinants across the proposed screening and assessment pathway. Strategies that enable the best chance for program success must be identified prior to implementation of a national LCS program.
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Introduction: Physical activity (PA) is a potentially modifiable risk factor for lung cancer, with previous research revealing that people who engage in more PA have lower risk of developing lung cancer. PA levels of lung cancer screening participants have not previously been explored. Methods: Participants at a single Australian International Lung Screen Trial site were eligible for assessment of self-reported PA levels (International Physical Activity Questionnaire and Physical Activity Scale for the Elderly) and physical assessments (6-min walk distance, hand grip muscle strength, daily step count, and body composition) at a single time point during lung cancer screening. Statistics were predominantly descriptive, with parametric data presented as mean and SD and nonparametric data presented as median and interquartile range (IQR). Results: A total of 178 participants were enrolled in this study, with a median age of 61 years. Of the participants, 61% were men and 51% were people who currently smoke. The median total International Physical Activity Questionnaire score was 1756 MET/min/wk (IQR 689, 4049). Mean total Physical Activity Scale for the Elderly score was 160 (SD 72), higher than described in healthy sedentary adults. The median daily step count was 7237 steps (IQR 5353, 10,038) and mean 6-minute walk distance was 545 m (SD 92). Median grip strengths were within predicted normal range, with an elevated median percentage body fat and low skeletal muscle mass found on body composition. Conclusion: Almost a quarter of International Lung Screen Trial participants assessed reported low levels of PA and have a potentially modifiable risk factor to improve health outcomes. Larger studies are needed to characterize the burden of inactivity among high-risk lung cancer screening populations.
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BACKGROUND: Evaluation of psychosocial consequences of lung cancer screening with LDCT in high-risk populations has generally been performed using generic psychometric instruments. Such generic instruments have low coverage and low power to detect screening impacts. This study aims to validate an established lung cancer screening-specific questionnaire, Consequences Of Screening Lung Cancer (COS-LC), in Australian-English and describe early results from the baseline LDCT round of the International Lung Screen Trial (ILST). METHODS: The Danish-version COS-LC was translated to Australian-English using the double panel method and field tested in Australian-ILST participants to examine content validity. A random sample of 200 participants were used to assess construct validity using Rasch item response theory models. Reliability was assessed using classical test theory. The COS-LC was administered to ILST participants at prespecified timepoints including at enrolment, dependent of screening results. RESULTS: Minor linguistic alterations were made after initial translation of COS-LC to English. The COS-LC demonstrated good content validity and adequate construct validity using psychometric analysis. The four core scales fit the Rasch model, with only minor issues in five non-core scales which resolved with modification. 1129 Australian-ILST participants were included in the analysis, with minimal psychosocial impact observed shortly after baseline LDCT results. CONCLUSION: COS-LC is the first lung cancer screening-specific questionnaire to be validated in Australia and has demonstrated excellent psychometric properties. Early results did not demonstrate significant psychosocial impacts of screening. Longer-term follow-up is awaited and will be particularly pertinent given the announcement of an Australian National Lung Cancer Screening Program. TRIAL REGISTRATION: NCT02871856.
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Neoplasias Pulmonares , Humanos , Australia , Detección Precoz del Cáncer/métodos , Detección Precoz del Cáncer/psicología , Pulmón , Neoplasias Pulmonares/diagnóstico , Neoplasias Pulmonares/psicología , Calidad de Vida , Reproducibilidad de los Resultados , Encuestas y CuestionariosRESUMEN
Telephone-based services are a practical and effective behavioral support for smoking cessation, yet no in-depth analyses of this counseling have been conducted. Understanding the general content of Quitline conversations can help to improve current practices and may inform future interventions. Therefore, we aimed to independently explore conversation themes, topics, and client questions during Quitline counseling sessions with Quitline clients in Queensland, Australia. A purposive sample of 30 recorded counseling sessions, completed between January and March 2019, were de-identified, transcribed, and thematically analyzed. Seven themes, encompassing 35 topics, were derived from 26 initial calls and four follow-up calls: (1) Client details and building rapport; (2) Client history and motivation to quit; (3) Pharmacotherapy; (4) Behavioral aspects of quitting and relationship with smoking; (5) Understanding nicotine dependence and other important considerations; (6) Additional support and smoking cessation resources; and (7) Planning, goal setting and follow-up. Three themes emerged from 18 client questions including (1) Pharmacotherapy safety and contraindications; (2) Pharmacotherapy instructions and mechanism of action; and (3) Physiology of nicotine dependence. This is the first qualitative analysis of the content of Quitline counseling sessions in Australia. Counselors collect and deliver a breadth of information to provide tailored, evidence-based health care, while building rapport and trust. Findings may be translatable into personalized self-help interventions that are more accessible or appealing to people reluctant to contact Quitline. Harnessing educational opportunities regarding pharmacotherapy adherence and misconceptions can improve client confidence in the product and smoking cessation outcomes. Further research will map conversations to motivational interviewing and behavior change techniques.
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Cese del Hábito de Fumar , Tabaquismo , Humanos , Cese del Hábito de Fumar/métodos , Queensland , Consejo/métodos , AustraliaRESUMEN
PURPOSE: To evaluate the association between localised vascular and retinal nerve fibre layer (RNFL) loss and genetic risk for glaucoma and cardiovascular disease using polygenic risk scores (PRS). METHODS: 858 eyes were included from 455 individuals with suspect and early manifest primary open angle glaucoma. Eyes were characterised as having localised vascular and/or RNFL wedge-shaped defects by scrutiny of optical coherence tomography angiography (OCTA) and OCT images, respectively. Investigations included associations with pre-established scores for genetic risk of glaucoma and cardiovascular disease in the context of glaucoma risk factors and systemic vascular disease outcomes. RESULTS: Higher genetic risk for glaucoma was associated with both vascular wedge defects and RNFL defects (p < 0.001 and p = 0.020, respectively). A greater genetic risk of glaucoma was associated with the presence of multiple vascular wedges per eye (p = 0.005). Glaucoma progression based on global RNFL loss was associated with vascular and RNFL wedge defects (p ≤ 0.001 and p = 0.008, respectively). The glaucoma PRS was significantly associated with vascular, but not RNFL, wedge defects after controlling for disc haemorrhage (p = 0.007 and p = 0.070, respectively). Vascular wedge defects were not related to the cardiovascular PRS. CONCLUSION: Individuals with a higher genetic risk of glaucoma based on the PRS were more likely to have retinal vascular defects, as well as structural glaucomatous loss, but this did not relate to systemic cardiovascular risk. This possibly implies a local pathophysiology for the vascular defects in some cases, which may have clinical relevance in the early stages of glaucoma and in individuals at high genetic risk.
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Enfermedades Cardiovasculares , Glaucoma de Ángulo Abierto , Glaucoma , Disco Óptico , Enfermedades de la Retina , Humanos , Glaucoma de Ángulo Abierto/diagnóstico , Glaucoma de Ángulo Abierto/genética , Glaucoma de Ángulo Abierto/complicaciones , Enfermedades Cardiovasculares/diagnóstico , Enfermedades Cardiovasculares/genética , Enfermedades Cardiovasculares/complicaciones , Células Ganglionares de la Retina , Presión Intraocular , Glaucoma/complicaciones , Fibras Nerviosas , Enfermedades de la Retina/complicaciones , Factores de Riesgo , Tomografía de Coherencia Óptica/métodosRESUMEN
Lung cancer (LC) is the leading cause of cancer death. Detecting LC at the earliest stage facilitates curative treatment options and will improve mortality rates. Computer-aided detection (CAD) systems can help improve LC diagnostic accuracy. In this work, we propose a deep-learning-based lung nodule detection method. The proposed CAD system is a 3D anchor-free nodule detection (AFND) method based on a feature pyramid network (FPN). The deep learning-based CAD system has several novel properties: (1) It achieves region proposal and nodule classification in a single network, forming a one-step detection pipeline and reducing operation time. (2) An adaptive nodule modelling method was designed to detect nodules of various sizes. (3) The proposed AFND also establishes a novel center point selection mechanism for better classification. (4) Based on the new nodule model, a composite loss function integrating cosine similarity (CS) loss and SmoothL1loss was designed to further improve the nodule detection accuracy. Experimental results show that the AFND outperforms other similar nodule detection systems on the LUNA 16 dataset.
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Neoplasias Pulmonares , Nódulo Pulmonar Solitario , Humanos , Redes Neurales de la Computación , Nódulo Pulmonar Solitario/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodos , Neoplasias Pulmonares/diagnóstico por imagenRESUMEN
Background: Conversational artificial intelligence (chatbots and dialogue systems) is an emerging tool for tobacco cessation that has the potential to emulate personalised human support and increase engagement. We aimed to determine the effect of conversational artificial intelligence interventions with or without standard tobacco cessation interventions on tobacco cessation outcomes among adults who smoke, compared to no intervention, placebo intervention or an active comparator. Methods: A comprehensive search of six databases was completed in June 2022. Eligible studies included randomised controlled trials published since 2005. The primary outcome was sustained tobacco abstinence, self-reported and/or biochemically validated, for at least 6 months. Secondary outcomes included point-prevalence abstinence and sustained abstinence of less than 6 months. Two authors independently extracted data on cessation outcomes and completed the risk of bias assessment. Random effects meta-analysis was conducted. Results: From 819 studies, five randomised controlled trials met inclusion criteria (combined sample size n = 58,796). All studies differed in setting, methodology, intervention, participants and end-points. Interventions included chatbots embedded in multi- and single-component smartphone apps (n = 3), a social media-based (n = 1) chatbot, and an internet-based avatar (n = 1). Random effects meta-analysis of three studies found participants in the conversational artificial intelligence enhanced intervention were significantly more likely to quit smoking at 6-month follow-up compared to control group participants (RR = 1.29, 95% CI (1.13, 1.46), p < 0.001). Loss to follow up was generally high. Risk of bias was high overall. Conclusion: We found limited but promising evidence on the effectiveness of conversational artificial intelligence interventions for tobacco cessation. Although all studies found benefits from conversational artificial intelligence interventions, results should be interpreted with caution due to high heterogeneity. Given the rapid evolution and potential of artificial intelligence interventions, further well-designed randomised controlled trials following standardised reporting guidelines are warranted in this emerging area.
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INTRODUCTION: Chatbots emulate human-like interactions and may usefully provide on-demand access to tailored smoking cessation support. We have developed a prototype smartphone application-based smoking cessation chatbot, named Quin, grounded in real-world, evidence- and theory-based smoking cessation counselling sessions. METHOD: Conversation topics and interactions in Quitline counselling sessions (N=30; 18 hours) were characterised using thematic, content, and proponent analyses of transcripts. Quin was created by programming this content using a chatbot framework which interacts with users via speech-to-text. Reiterative changes and additions were made to the conversation structure and dialogue following regular consultation with a multidisciplinary team from relevant fields, and from evidence-based resources. RESULTS: Chatbot conversations were encoded into initial and scheduled follow-up 'appointments'. Collection of demographic information, and smoking and quit history, informed tailored discussion about pharmacotherapy preferences, behavioural strategies, and social and professional support to form a quit plan. Follow-up appointments were programmed to check in on user progress, review elements of the quit plan, answer questions and solve issues. Quin was programmed to include teachable moments and educational content to enhance health literacy and informed decision-making. Personal agency is encouraged through exploration and self-reflection of users' personal behaviours, experiences, preferences and ideas. CONCLUSION: Quin's successful development represents a movement towards improving access to personalised smoking cessation support. Qualitative foundations of Quin provide greater insight into the smoking cessation counselling relationship and enhances the conversational ability of the technology. The prototype chatbot will be refined through beta-testing with end-users and stakeholders prior to evaluation in a clinical trial. IMPLICATIONS: Our novel study provides transparent description of the translation of qualitative evidence of real-world smoking cessation counselling sessions into the design and development of a prototype smoking cessation chatbot. The successful iterative development of Quin not only embodies the science and art of health promotion, but also a step-forward in expanding the reach of tailored, evidence based, in-pocket support for people who want to quit smoking.
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Background and Objective: Lung cancer is the leading cause of cancer-related mortality worldwide, partially attributed to late-stage diagnoses. In order to mitigate this, lung cancer screening (LCS) of high-risk patients is performed using low dose computed tomography (CT) scans, however this method is burdened by high false-positive rates and radiation exposure for patients. Further, screening programs focus on individuals with heavy smoking histories, and as such, never-smokers who may otherwise be at risk of lung cancer are often overlooked. To resolve these limitations, biomarkers have been posited as potential supplements or replacements to low-dose CT, and as such, a large body of research in this area has been produced. However, comparatively little information exists on their clinical efficacy and how this compares to current LCS strategies. Methods: Here we conduct a search and narrative review of current literature surrounding biomarkers of lung cancer to supplement LCS, and biomarkers of lung cancer in never-smokers (LCINS). Key Content and Findings: Many potential biomarkers of lung cancer have been identified with varying levels of sensitivity, specificity, clinical efficacy, and supporting evidence. Of the markers identified, multi-target panels of circulating microRNAs, lipids, and metabolites are likely the most clinically efficacious markers to aid current screening programs, as these provide the highest sensitivity and specificity for lung cancer detection. However, circulating lipid and metabolite levels are known to vary in numerous systemic pathologies, highlighting the need for further validation in large cohort randomised studies. Conclusions: Lung cancer biomarkers is a fast-expanding area of research and numerous biomarkers with potential clinical applications have been identified. However, in all cases the level of evidence supporting clinical efficacy is not yet at a level at which it can be translated to clinical practice. The priority now should be to validate existing candidate markers in appropriate clinical contexts and work to integrating these into clinical practice.
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BACKGROUND: Lung cancer screening in high-risk populations with low-dose computed tomography is supported by international associations and recommendations. Overdiagnosis is considered a risk of screening with associated harms. The aim of this paper is to determine the prevalence of subclinical lung cancer diagnosed post-mortem to better understand the reservoir of subclinical lung cancer. METHODS: We searched EMBASE, PubMed, and MEDLINE databases from inception until March 2022 with no language restrictions. We considered all studies with ≥100 autopsies in adults. Two reviewers independently assessed eligibility of studies, extracted data, and assessed risk of bias of included studies. We performed a meta-analysis using a random-effects model for prevalence of subclinical lung cancer diagnosed post-mortem with sensitivity and subgroup analyses. RESULTS: A total of 13 studies with 16 730 autopsies were included. Pooled prevalence was 0.4% (95% CI 0.20 to 0.82%, I2 = 84%, tau2 = 1.19, low certainty evidence,16 730 autopsies). We performed a sensitivity analysis excluding studies which did not specify exclusion of children in their cohort, with a pooled prevalence of subclinical lung cancer of 0.87% (95% CI 0.48 to 1.57%, I2 = 71%, tau2 = 0.38, 6998 autopsies, 8 studies). CONCLUSIONS: This is the first published systematic review to evaluate the prevalence of post-mortem subclinical lung cancer. Compared to autopsy systematic reviews in breast, prostate and thyroid cancers, the pooled prevalence is lower in lung cancer for subclinical cancer. This result should be interpreted with caution due to the included studies risk of bias and heterogeneity, with further high-quality studies required in target screening populations.
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Neoplasias Pulmonares , Adulto , Niño , Masculino , Humanos , Neoplasias Pulmonares/epidemiología , Autopsia , Detección Precoz del Cáncer , Prevalencia , MamaRESUMEN
Lung cancer screening can significantly reduce mortality from lung cancer. Further evidence about how to optimize lung cancer screening for specific populations, including Aotearoa New Zealand (NZ)'s Indigenous Maori (who experience disproportionately higher rates of lung cancer), is needed to ensure it is equitable. This community-based, pragmatic cluster randomized trial aims to determine whether a lung cancer screening invitation from a patient's primary care physician, compared to from a centralized screening service, will optimize screening uptake for Maori. Participating primary care practices (clinics) in Auckland, Aotearoa NZ will be randomized to either the primary care-led or centralized service for delivery of the screening invitation. Clinic patients who meet the following criteria will be eligible: Maori; aged 55-74 years; enrolled in participating clinics in the region; ever-smokers; and have at least a 2% risk of developing lung cancer within six years (determined using the PLCOM2012 risk prediction model). Eligible patients who respond positively to the invitation will undertake shared decision-making with a nurse about undergoing a low dose CT scan (LDCT) and an assessment for Chronic Obstructive Pulmonary Disease (COPD). The primary outcomes are: 1) the proportion of eligible population who complete a risk assessment and 2) the proportion of people eligible for a CT scan who complete the CT scan. Secondary outcomes include evaluating the contextual factors needed to inform the screening process, such as including assessment for Chronic Obstructive Pulmonary Disease (COPD). We will also use the RE-AIM framework to evaluate specific implementation factors. This study is a world-first, Indigenous-led lung cancer screening trial for Maori participants. The study will provide policy-relevant information on a key policy parameter, invitation method. In addition, the trial includes a nested analysis of COPD in the screened Indigenous population, and it provides baseline (T0 screen round) data using RE-AIM implementation outcomes.
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Neoplasias Pulmonares , Enfermedad Pulmonar Obstructiva Crónica , Humanos , Pueblo Maorí , Detección Precoz del Cáncer/métodos , Nueva Zelanda , Neoplasias Pulmonares/diagnóstico por imagen , Ensayos Clínicos Controlados Aleatorios como AsuntoRESUMEN
OBJECTIVES: Compare accuracy of vertebral Hounsfield Unit (VHU) attenuation and FRAX and Garvan Fracture Risk Calculators in identifying low bone mineral density (BMD) and prevalent vertebral compression fractures (VF) in lung cancer screening (LCS) participants. METHODS: Baseline CT scans from a single site of the International Lung Screen Trial were analysed. BMD was measured using VHU (of the most caudally imaged vertebra) and quantitative CT (QCT) (low BMD defined as <110 HU and <120 mg/cm3, respectively). Prevalent VF were classified semi-quantitatively. 10-year FRAX and Garvan fracture risks were calculated using dual energy X-ray absorptiometry (DXA) femoral neck T-score where available. Discrimination was assessed by area under receiver-operating characteristic curves (AUC). RESULTS: 535 LCS participants were included; 41% had low VHU-BMD, 56% had low QCT-BMD and 10% had ≥1 VF with ≥25% vertebral height loss. VHU demonstrated 94% specificity and 70% sensitivity in identifying low QCT-BMD. VHU was superior to fracture risk tools in discriminating low QCT-BMD (AUC: VHU 0.94 vs FRAX 0.67, Garvan 0.64 [p < 0.05]). In 64 participants with recent DXA scans, VHU was superior to FRAXT-score and GarvanT-score in discriminating low QCT-BMD (AUC: VHU 0.99, FRAXT-score 0.71, GarvanT-score 0.71 [p < 0.05]). VHU was non-inferior to FRAXT-score and GarvanT-score in discriminating VF (AUC: VHU 0.65, FRAXT-score 0.53, GarvanT-score 0.61). CONCLUSIONS: VHU outperforms clinical risk calculators in detecting low BMD and discriminates prevalent VF equally well as risk calculators with T-scores, yet is significantly simpler to perform. ADVANCES IN KNOWLEDGE: VHU measurement could aid osteoporosis assessment in high-risk smokers undergoing LCS.
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Fracturas por Compresión , Neoplasias Pulmonares , Fracturas Osteoporóticas , Fracturas de la Columna Vertebral , Humanos , Fracturas Osteoporóticas/diagnóstico por imagen , Densidad Ósea , Detección Precoz del Cáncer , Fracturas de la Columna Vertebral/diagnóstico por imagen , Neoplasias Pulmonares/diagnóstico por imagen , Columna Vertebral , Absorciometría de Fotón/métodos , Tomografía Computarizada por Rayos XRESUMEN
Purpose: To elucidate a potential association between the apolipoprotein E (APOE) E4 allele and glaucoma prevalence in large cohorts. Design: A cross-sectional analysis of baseline and prospectively collected cohort data. Participants: UK Biobank (UKBB) participants of genetically determined European ancestry (n = 438 711). Replication analyses were performed using clinical and genotyping data collected from European participants recruited to the Canadian Longitudinal Study of Aging (CLSA; n = 18 199), the Australian and New Zealand Registry of Advanced Glaucoma (ANZRAG; n = 1970), and the Blue Mountains Eye Study (BMES; n = 2440). Methods: Apolipoprotein E alleles and genotypes were determined, and their distributions were compared on the basis of glaucoma status. Similar analyses were performed using positive control outcomes associated with the APOE E4 allele (death, dementia, age-related macular degeneration) and negative control outcomes not associated with the APOE E4 allele (cataract, diabetic eye disease). Outcome phenotypes were also correlated with Alzheimer's dementia (AD), a clinical outcome highly associated with the APOE E4 allele. Main Outcome Measures: Results of APOE E4 genotype-phenotype comparisons were reported as odds ratios (ORs) with 95% confidence intervals (CIs). Replication analyses investigated APOE E4 associations in 2 replication cohorts (CLSA and ANZRAG/BMES). Results: The APOE E4 allele was inversely associated with glaucoma (OR, 0.96; 95% CI, 0.93-0.99; P = 0.016) and both negative controls (cataract: OR, 0.98; 95% CI, 0.96-0.99; P = 0.015; diabetic eye disease: OR, 0.92; 95% CI, 0.87-0.97; P = 0.003) in the UKBB cohort. A paradoxical positive association was observed between AD and both glaucoma (OR, 1.30; 95% CI, 1.08-1.54; P < 0.01) and cataract (OR, 1.15; 1.04-1.28; P = 0.018). No association between the APOE E4 allele and glaucoma was observed in either replication cohort (CLSA: OR, 1.03; 95% CI, 0.89-1.19; P = 0.66; ANZRAG/BMES: OR, 0.97; 95% CI, 0.84-1.12; P = 0.65). Conclusions: A small negative association observed between APOE E4 and glaucoma within the UKBB was not evident in either replication cohort and may represent an artifact of glaucoma underdiagnosis in APOE E4 carriers. Financial Disclosures: The author(s) have no proprietary or commercial interest in any materials discussed in this article.
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BACKGROUND: Lung cancer is the number one cause of cancer death worldwide. Although international trials demonstrate that targeted screening using low dose computed tomography (LDCT) significantly reduces lung cancer mortality, implementation of screening in the high-risk population presents complex health system challenges that need to be thoroughly understood to support policy change. AIM: To elicit health care providers' and policymakers' views about the acceptability and feasibility of lung cancer screening (LCS) and barriers and enablers to implementation in the Australian setting. METHODS: We conducted 24 focus groups and three interviews (22 focus groups and all interviews online) in 2021 with 84 health professionals, researchers, and current cancer screening program managers and policy makers across all Australian states and territories. Focus groups included a structured presentation about lung cancer and screening and lasted approximately one hour each. A qualitative approach to analysis was used to map topics to the Consolidated Framework for Implementation Research. RESULTS: Nearly all participants considered LCS to be acceptable and feasible but identified a wide range of implementation challenges. Topics (five specific to health systems and five cross-cutting with participant factors) identified were mapped to CFIR constructs, of which 'readiness for implementation', 'planning' and 'executing' were most salient. Health system factor topics included delivery of the LCS program, cost, workforce considerations, quality assurance and complexity of health systems. Participants strongly advocated for streamlined referral processes. Practical strategies to address equity and access, such as using mobile screening vans, were emphasised. CONCLUSIONS: Key stakeholders readily identified the complex challenges associated with the acceptability and feasibility of LCS in Australia. The barriers and facilitators across health system and cross-cutting topics were clearly elicited. These findings are highly relevant to the scoping of a national LCS program by the Australian Government and a subsequent recommendation for implementation.