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D Bond-Smith,1 R Seth,1 N de Klerk,1,2 L Nedkoff,1 M Anderson,3 J Hung,1 J Cannon,1,2 K Griffiths,4,5 JM Katzenellenbogen1,2 1School of Population and Global Health, The University of Western Australia, Perth, Australia; 2Telethon Kids Institute, Perth, Australia; 3Queensland Health, Brisbane, Australia; 4Centre for Big Data Research, The University of New South Wales, Sydney, Australia; 5Menzies School of Health Research, Charles Darwin University, Darwin, AustraliaCorrespondence: D Bond-Smith Email daniela.bond-smith@uwa.edu.auBackground: Previous research has raised substantial concerns regarding the validity of the International Statistical Classification of Diseases and Related Health Problems (ICD) codes (ICD-10 I05–I09) for rheumatic heart disease (RHD) due to likely misclassification of non-rheumatic valvular disease (non-rheumatic VHD) as RHD. There is currently no validated, quantitative approach for reliable case ascertainment of RHD in administrative hospital data.Methods: A comprehensive dataset of validated Australian RHD cases was compiled and linked to inpatient hospital records with an RHD ICD code (2000– 2018, n=7555). A prediction model was developed based on a generalized linear mixed model structure considering an extensive range of demographic and clinical variables. It was validated internally using randomly selected cross-validation samples and externally. Conditional optimal probability cutpoints were calculated, maximising discrimination separately for high-risk versus low-risk populations.Results: The proposed model reduced the false-positive rate (FPR) from acute rheumatic fever (ARF) cases misclassified as RHD from 0.59 to 0.27; similarly for non-rheumatic VHD from 0.77 to 0.22. Overall, the model achieved strong discriminant capacity (AUC: 0.93) and maintained a similar robust performance during external validation (AUC: 0.88). It can also be used when only basic demographic and diagnosis data are available.Conclusion: This paper is the first to show that not only misclassification of non-rheumatic VHD but also of ARF as RHD yields substantial FPRs. Both sources of bias can be successfully addressed with the proposed model which provides an effective solution for reliable RHD case ascertainment from hospital data for epidemiological disease monitoring and policy evaluation.Keywords: rheumatic heart disease, international classification of diseases, prediction, case ascertainment, acute rheumatic fever, non-rheumatic valvular heart disease, administrative data, validation, discrimination, receiver operating curve, Australia

Judith M Katzenellenbogen,1,2,* Daniela Bond-Smith,1,* Rebecca J Seth,1 Karen Dempsey,3 Jeffrey Cannon,2 Lee Nedkoff,1 Frank M Sanfilippo,1 Nicholas de Klerk,1,2 Joe Hung,1 Elizabeth Geelhoed,4 Daniel Williamson,5 Rosemary Wyber,2,6,7 Anna P Ralph,3 Dawn Bessarab1 On behalf of the ERASE Collaboration Study Group1School of Population and Global Health, The University of Western Australia, Perth, WA, Australia; 2Group A Streptococcus Research Group, Telethon Kids Institute, Perth, WA, Australia; 3Global and Tropical Health, Menzies School of Health Research, Charles Darwin University, Darwin, NT, Australia; 4School of Allied Health, The University of Western Australia, Perth, WA, Australia; 5Aboriginal and Torres Strait Islander Health Branch, Queensland Health, Brisbane, QLD, Australia; 6Office of the Chief Scientist, The George Institute for Global Health, Sydney, NSW, Australia; 7The University of Sydney, Sydney, NSW, Australia*These authors contributed equally to this workCorrespondence: Judith M KatzenellenbogenSchool of Population and Global Health, The University of Western Australia, M431 35 Stirling Highway, Crawley, Perth, WA 6009, AustraliaTel +61 8 6488 1001Fax +61 8 6488 1188Email Judith.katzenellenbogen@uwa.edu.auPurpose: Acute rheumatic fever (ARF) and rheumatic heart disease (RHD) persist as public health issues in developing countries and among disadvantaged communities in high-income countries, with rates in Aboriginal and Torres Strait Islander peoples in Australia among the highest recorded globally. A robust evidence base is critical to support policy recommendations for eliminating RHD, but available data are fragmented and incomplete. The End RHD in Australia: Study of Epidemiology (ERASE) Project aims to provide a comprehensive database of ARF and RHD cases in Australia as a basis for improved monitoring and to assess prevention and treatment strategies. The objective of this paper is to describe the process for case ascertainment and profile of the study cohort.Patients and methods: The ERASE database has been built using linked administrative data from RHD registers, inpatient hospitalizations, and death registry data from 2001 to 2017 (mid-year). Additional linked datasets are available. The longitudinal nature of the data is harnessed to estimate onset and assess the progression of the disease. To accommodate systematic limitations in diagnostic coding for RHD, hospital-only identified RHD has been determined using a purposefully developed prediction model.Results: Of 132,053 patients for whom data were received, 42,064 are considered true cases of ARF or RHD in the study period. The patient population under 60 years in the compiled dataset is more than double the number of patients identified in ARF/RHD registers (12,907 versus 5049). Non-registered patients were more likely to be older, non-Indigenous, and at a later disease stage.Conclusion: The ERASE Project has created an unprecedented linked administrative database on ARF and RHD in Australia. These data provide a critical baseline for efforts to end ARF/RHD in Australia. The methodological work conducted to compile this database resulted in significant improvements in the robustness of epidemiological estimates and entails valuable lessons for ARF/RHD research globally.Keywords: rheumatic fever, rheumatic heart disease, indigenous, epidemiology, linked data

Background: The relationship between OSA and cancer is unclear., Research Question: What is the association between OSA and cancer prevalence and incidence in a large Western Australian sleep clinic cohort (N = 20,289)?, Study Design and Methods: OSA severity was defined by apnea-hypopnea index (AHI) and nocturnal hypoxemia (duration and percentage at oxygen saturation < 90%) measured by in-laboratory polysomnogram. Measures of potential confounding included age, sex, BMI, smoking status, socioeconomic status, and BP. Outcomes were determined from the Western Australian cancer and death registries. Analyses were confined within periods using consistent AHI scoring criteria: January 1, 1989, to July 31, 2002 (American Sleep Disorders Association criteria), and August 1, 2002, to June 30, 2013 (Chicago criteria). We examined associations of AHI and nocturnal hypoxemia with cancer prevalence using logistic regression and cancer incidence using Cox regression analyses., Results: Cancer prevalence at baseline was 329 of 10,561 in the American Sleep Disorders Association period and 633 of 9,728 in the Chicago period. Nocturnal hypoxemia but not AHI was independently associated with prevalent cancer following adjustment for participant age, sex, BMI, smoking status, socioeconomic status, and BP. Of those without prevalent cancer, cancer was diagnosed in 1,950 of 10,232 (American Sleep Disorders Association) and 623 of 9,095 (Chicago) participants over a median follow-up of 11.2 years. Compared with the reference category (no OSA, AHI < 5 events per hour), univariable models estimated higher hazard ratios for cancer incidence for mild (AHI 5-15 events per hour), moderate (AHI 15.1-30 events per hour), and severe (AHI > 30 events per hour) OSA. Multivariable analyses consistently revealed associations between age and, in some cases, sex, BMI, and smoking status, with cancer incidence. After adjusting for confounders, multivariable models showed no independent association between OSA severity and increased cancer incidence., Interpretation: Nocturnal hypoxemia is independently associated with prevalent cancer. OSA severity is associated with incident cancer, although this association seems secondary to other risk factors for cancer development. OSA is not an independent risk factor for cancer incidence., (Copyright © 2023 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Multimorbidity is of an increasing importance for the health of both children and adults but research has hitherto focused on adult multimorbidity. Hence, public awareness, practice, and policy lack vital information about multimorbidity in childhood and adolescence. We convened an international and interdisciplinary group of experts from six nations to identify key priorities supported by published evidence to strengthen research for children and adolescent with multimorbidity. Future research is encouraged (1) to develop a conceptual framework to capture unique aspects of child and adolescent multimorbidity-including definitions, characteristic patterns of conditions for different age groups, its dynamic nature through childhood and adolescence, and understanding of severity and trajectories for different clusters of multiple chronic conditions, (2) to define new indices to classify the presence of multimorbidity in children and adolescents, (3) to improve the availability and linkage of data across countries, (4) to synthesize evidence on the global phenomenon of multimorbidity in childhood and adolescence and health inequalities, and (5) to involve children and adolescents in research relevant to their health., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Introduction: We aimed to analyze long-term trends in characteristics of patients undergoing diagnostic polysomnography (PSG) and subsequently diagnosed with obstructive sleep apnea (OSA) to inform delivery of sleep services., Material and Methods: We studied 24,510 consecutive patients undergoing PSG at a tertiary-care sleep service between 1989 and 2013. OSA was defined by an apnea hypopnea index (AHI)≥ 5 events/hour. Changes to hypopnea definition and flow sensing techniques in 2002 created two distinct AHI scoring periods: American Sleep Disorders Association (ASDA) 1989 - July 2002 and American Academy of Sleep Medicine (Chicago) from August 2002., Results: Over 23.5 years there was a steady increase in proportion of females (15% to 45%), small increases in average age and BMI, and a small decline in socioeconomic status in the overall group. AHI varied between scoring periods both overall [ASDA 10.8/h (3.2-29.6), Chicago 24.3/h (11.8-48.1)] and in the large subgroup (80.7%) diagnosed with OSA [ASDA 20.7/h (10.6-44.1), Chicago 27.4/h (14.8-51.5)]. OSA diagnosis rates increased in the Chicago period (ASDA 66%, Chicago 91%). Increases in AHI and proportion diagnosed appeared better explained by changes in scoring methods than key OSA risk factors., Conclusion: Temporal increases in proportion of females and decreases in socioeconomic status of people undergoing PSG may reflect greater community awareness of sleep disorders. Temporal increases in age and obesity are consistent with secular trends. Changes in scoring methods have major impacts on OSA diagnosis and judgement of disease severity, with important implications for contemporary resourcing of sleep services and interpretation of historical OSA data.

Aims : Rheumatic heart disease (RHD) is a major contributor to cardiac morbidity and mortality globally. This study aims to estimate the probability and predictors of progressing to non-fatal cardiovascular complications and death in young Australians after their first RHD diagnosis., Methods and Results : This retrospective cohort study used linked RHD register, hospital, and death data from five Australian states and territories (covering 70% of the whole population and 86% of the Indigenous population). Progression from uncomplicated RHD to all-cause death and non-fatal cardiovascular complications (surgical intervention, heart failure, atrial fibrillation, infective endocarditis, and stroke) was estimated for people aged <35 years with first-ever RHD diagnosis between 2010 and 2018, identified from register and hospital data. The study cohort comprised 1718 initially uncomplicated RHD cases (84.6% Indigenous; 10.9% migrant; 63.2% women; 40.3% aged 5-14 years; 76.4% non-metropolitan). The composite outcome of death/cardiovascular complication was experienced by 23.3% (95% confidence interval: 19.5-26.9) within 8 years. Older age and metropolitan residence were independent positive predictors of the composite outcome; history of acute rheumatic fever was a negative predictor. Population group (Indigenous/migrant/other Australian) and sex were not predictive of outcome after multivariable adjustment., Conclusion : This study provides the most definitive and contemporary estimates of progression to major cardiovascular complication or death in young Australians with RHD. Despite access to the publically funded universal Australian healthcare system, one-fifth of initially uncomplicated RHD cases will experience one of the major complications of RHD within 8 years supporting the need for programmes to eradicate RHD., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)

■The RHD Endgame Strategy: the blueprint to eliminate rheumatic heart disease in Australia by 2031 (the Endgame Strategy) is the blueprint to eliminate rheumatic heart disease (RHD) in Australia by 2031. Aboriginal and Torres Strait Islander people live with one of the highest per capita burdens of RHD in the world. ■The Endgame Strategy synthesises information compiled across the 5-year lifespan of the End Rheumatic Heart Disease Centre of Research Excellence (END RHD CRE). Data and results from priority research projects across several disciplines of research complemented literature reviews, systematic reviews and narrative reviews. Further, the experiences of those working in acute rheumatic fever (ARF) and RHD control and those living with RHD to provide the technical evidence for eliminating RHD in Australia were included. ■The lived experience of RHD is a critical factor in health outcomes. All future strategies to address ARF and RHD must prioritise Aboriginal and Torres Strait Islander people's knowledge, perspectives and experiences and develop co-designed approaches to RHD elimination. The environmental, economic, social and political context of RHD in Australia is inexorably linked to ending the disease. ■Statistical modelling undertaken in 2019 looked at the economic and health impacts of implementing an indicative strategy to eliminate RHD by 2031. Beginning in 2019, the strategy would include: reducing household crowding, improving hygiene infrastructure, strengthening primary health care and improving secondary prophylaxis. It was estimated that the strategy would prevent 663 deaths and save the health care system $188 million. ■The Endgame Strategy provides the evidence for a new approach to RHD elimination. It proposes an implementation framework of five priority action areas. These focus on strategies to prevent new cases of ARF and RHD early in the causal pathway from Streptococcus pyogenes exposure to ARF, and strategies that address the critical systems and structural changes needed to support a comprehensive RHD elimination strategy., (& 2020 AMPCo Pty Ltd.)

Background In 2018, the World Health Organization prioritized control of acute rheumatic fever (ARF) and rheumatic heart disease (RHD), including disease surveillance. We developed strategies for estimating contemporary ARF/RHD incidence and prevalence in Australia (2015-2017) by age group, sex, and region for Indigenous and non-Indigenous Australians based on innovative, direct methods. Methods and Results This population-based study used linked administrative data from 5 Australian jurisdictions. A cohort of ARF (age <45 years) and RHD cases (<55 years) were sourced from jurisdictional ARF/RHD registers, surgical registries, and inpatient data. We developed robust methods for epidemiologic case ascertainment for ARF/RHD. We calculated age-specific and age-standardized incidence and prevalence. Age-standardized rate and prevalence ratios compared disease burden between demographic subgroups. Of 1425 ARF episodes, 72.1% were first-ever, 88.8% in Indigenous people and 78.6% were aged <25 years. The age-standardized ARF first-ever rates were 71.9 and 0.60/100 000 for Indigenous and non-Indigenous populations, respectively (age-standardized rate ratio=124.1; 95% CI, 105.2-146.3). The 2017 Global Burden of Disease RHD prevalent counts for Australia (<55 years) underestimate the burden (1518 versus 6156 Australia-wide extrapolated from our study). The Indigenous age-standardized RHD prevalence (666.3/100 000) was 61.4 times higher (95% CI, 59.3-63.5) than non-Indigenous (10.9/100 000). Female RHD prevalence was double that in males. Regions in northern Australia had the highest rates. Conclusions This study provides the most accurate estimates to date of Australian ARF and RHD rates. The high Indigenous burden necessitates urgent government action. Findings suggest RHD may be underestimated in many high-resource settings. The linked data methods outlined here have potential for global applicability.

In Australia, disease registers for acute rheumatic fever (ARF) and rheumatic heart disease (RHD) were previously established to facilitate disease surveillance and control, yet little is known about the extent of case-ascertainment. We compared ARF/RHD case ascertainment based on Australian ARF/RHD register records with administrative hospital data from the Northern Territory (NT), South Australia (SA), Queensland (QLD) and Western Australia (WA) for cases 3-59 years of age. Agreement across data sources was compared for persons with an ARF episode or first-ever RHD diagnosis. ARF/RHD registers from the different jurisdictions were missing 26% of Indigenous hospitalised ARF/RHD cases overall (ranging 17-40% by jurisdiction) and 10% of non-Indigenous hospitalised ARF/RHD cases (3-28%). The proportion of hospitalised RHD cases (36%) was half the proportion of hospitalised ARF cases (70%) notified to the ARF/RHD registers. The registers were found to capture few RHD cases in metropolitan areas (SA Metro: 13%, QLD Metro: 35%, WA Metro: 14%). Indigenous status, older age, comorbidities, drug/alcohol abuse and disease severity were predictors of cases appearing in the hospital data only ( p < 0.05); sex was not a determinant. This analysis confirms that there are biases associated with the epidemiological analysis of single sources of case ascertainment for ARF/RHD using Australian data.

Objective This study investigated the delivery of guideline-recommended services for the management of acute rheumatic fever (ARF) and rheumatic heart disease (RHD) in Australian primary healthcare centres participating in the Audit and Best Practice for Chronic Disease (ABCD) National Research Partnership project. Methods ARF and RHD clinical audit data were collected from 63 Aboriginal centres in four Australian jurisdictions using the ABCD ARF/RHD audit tool. Records of up to 30 patients treated for ARF and/or RHD were analysed per centre from the most recent audit conducted between 2009 and 2014. The main outcome measure was a quality of ARF and RHD care composite indicator consisting of nine best-practice service items. Results Of 1081 patients, most were Indigenous (96%), female (61%), from the Northern Territory and Queensland (97%) and <25 years of age (49%). The composite indicator was highest in the 0-14 year age group (77% vs 65-67% in other age groups). Timely injections and provision of client education are important specific areas for improvement. Multiple regression showed age >15 years to be a significant negative factor for several care indicators, particularly for the delivery of long-acting antibiotic injections and specialist services in the 15-24 year age group. Conclusions The results suggest that timely injection and patient education are priorities for managing ARF and RHD, particularly focusing on child-to-adult transition care. What is known about the topic? The burden of rheumatic fever and RHD in some Aboriginal communities is among the highest documented globally. Guideline-adherent RHD prevention and management in primary health care (PHC) settings are critically important to reduce this burden. Continuous quality improvement (CQI) is a proven strategy to improve guideline adherence, using audit cycles and proactive engagement of PHC end users with their own data. Previously, such CQI strategies using a systems approach were shown to improve delivery of ARF and RHD care in six Aboriginal health services (three government and three community controlled). What does this paper add? This paper focuses on the variation across age groups in the quality of ARF and/or RHD care according to nine quality of care indicators across 63 PHC centres serving the Aboriginal population in the Northern Territory, Queensland, South Australia and Western Australia. These new findings provide insight into difference in quality of care by life stage, indicating particular areas for improvement of the management of ARF and RHD at the PHC level, and can act as a baseline for monitoring of care quality for ARF and RHD into the future. What are the implications for practitioners? Management plans and innovative strategies or systems for improving adherence need to be developed as a matter of urgency. PHC professionals need to closely monitor adherence to secondary prophylaxis at both the clinic and individual level. RHD priority status needs to be assigned and recorded as a tool to guide management. Systems strengthening needs to particularly target child-to-adult transition care. Practitioners are urged to keep a quick link to the RHDAustralia website to access resources and guidelines pertaining to ARF and RHD (https://www.rhdaustralia.org.au/arf-rhd-guideline, accessed 3 October 2019). CQI strategies can assist PHC centres to improve the care they provide to patients.

Introduction: For women of the same age and body mass index, increased mammographic density is one of the strongest predictors of breast cancer risk. There are multiple methods of measuring mammographic density and other features in a mammogram that could potentially be used in a screening setting to identify and target women at high risk of developing breast cancer. However, it is unclear which measurement method provides the strongest predictor of breast cancer risk., Methods and Analysis: The measurement challenge has been established as an international resource to offer a common set of anonymised mammogram images for measurement and analysis. To date, full field digital mammogram images and core data from 1650 cases and 1929 controls from five countries have been collated. The measurement challenge is an ongoing collaboration and we are continuing to expand the resource to include additional image sets across different populations (from contributors) and to compare additional measurement methods (by challengers). The intended use of the measurement challenge resource is for refinement and validation of new and existing mammographic measurement methods. The measurement challenge resource provides a standardised dataset of mammographic images and core data that enables investigators to directly compare methods of measuring mammographic density or other mammographic features in case/control sets of both raw and processed images, for the purposes of the comparing their predictions of breast cancer risk., Ethics and Dissemination: Challengers and contributors are required to enter a Research Collaboration Agreement with the University of Melbourne prior to participation in the measurement challenge. The Challenge database of collated data and images are stored in a secure data repository at the University of Melbourne. Ethics approval for the measurement challenge is held at University of Melbourne (HREC ID 0931343.3)., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Mammographic density (MD) is an established predictor of breast cancer risk. However, there is limited information on the robustness of the risk associations for different study designs and the associated methodologic challenges. Our analysis includes 165 samples from studies published since 2006. We use a weakly informative Bayesian approach to avoid unduly optimistic estimates of uncertainty, as found in the previous literature. We find that the existing consensus from previous review studies has underestimated the strength and precision of MD as a risk marker. Moreover, although much of the published literature is based on categorical measurement of MD, there are tangible advantages in using continuous data in terms of estimate precision and relevance for different patient populations. Estimates based on the percentage of MD are more precise for lower density women, whereas absolute MD has advantages for higher density. We show that older results might not be a good proxy for current and future findings, and it would be pertinent to adjust clinical interpretations based on the older data. Using an appropriate estimation method cognizant of the importance of heterogeneity is critical to obtaining reliable and robust clinical findings that are relevant for broad patient populations., (©2018 American Association for Cancer Research.)