Survival of People with Cystic Fibrosis in Australia

Survival of People with Cystic Fibrosis in Australia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Help Center Sign In Submit a Preprint Cite Share Download PDF Article Survival of People with Cystic Fibrosis in Australia Rasa Ruseckaite, Farhad Salimi, Arul Earnest, Scott C Bell, Tonia Douglas, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2079022/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Survival statistics, estimated using data from national cystic fibrosis (CF) registries, inform the CF community and monitor disease progression. This study aimed to estimate survival among people with CF in Australia and to identify factors associated with survival. This population-based cohort study used prospectively collected data from 23 Australian CF centres participating in the Australian CF Data Registry (ACFDR) from 2005-2020. Period survival analysis was used to calculate median age of survival estimates for each 5-year window from 2005-2009 until 2016-2020. The overall median survival was estimated using the Kaplan-Meier method. Between 2005-2020 the ACFDR followed 4,601 people with CF, noting 516 (11.2%) deaths including 195 following lung transplantation. Out of the total sample, more than half (52.5%) were male and 395 (8.6%) had undergone lung transplantation. Two thirds of people with CF (66.1%) were diagnosed before six weeks of age or by newborn/prenatal screening. The overall median age of survival was estimated as 54.0 years (95% CI: 51.0–57.04). Estimated median survival increased from 48.9 years (95% CI: 44.7–53.5) for people with CF born in 2005-2009, to 56.3 years (95% CI: 51.2–60.4) for those born in 2016-2020. Factors independently associated with reduced survival include being F508del homozygous, receiving a lung transplant, having low FEV1pp and BMI. Median survival estimates are increasing in CF in Australia. This likely reflects multiple factors, including newborn screening, improvement in diagnosis, refinements in CF management and centre-based multidisciplinary care. Cystic Fibrosis Registry Survival Risk factors Figures Figure 1 Figure 2 Introduction Cystic fibrosis (CF) is the most common autosomal recessive-inherited life-limiting condition, affecting approximately 90,000 individuals worldwide 1 . People with CF require support from healthcare services from diagnosis onwards; and respiratory failure is the commonest cause of premature death 2 . Although life expectancy for people with CF has increased substantially, the disease continues to result in reduced life expectancy, poorer quality of life, and a large burden of care for people with CF, their families and health care providers 3 . Prognosis continues to improve due to advancements in CF care 4 , such as the availability of new inhaled antibiotics, newborn screening (NBS), P. aeruginosa eradication therapy, mucolytic treatment, better growth and nutrition, lung transplantation and lifetime multidisciplinary care in specialised CF centres 5 . Although CF survival estimates have greatly improved globally, survival continues to be influenced by various individual factors 6 . A recent study of UK registry data demonstrated that male sex was associated with better survival, as was later diagnosis in adulthood, but only in non-F508del homozygotes. Survival did not differ by genotype among individuals diagnosed in early infancy 2 . In the recent study of Durda-Masny et al 7 , the shortest life expectancy was observed in adult patients with a severe mutation on both alleles, Forced Expiratory Volume in one second percent predicted (FEV 1 pp) < 40%, patients infected with extensively drug-resistant P. aeruginosa , and body mass index (BMI) < 18.5 kg/m 2 . Most of the deaths in these people occurred between 30 and 40 years of age. Providing up-to-date estimates of survival is helpful for counselling people with CF and their families on life expectancy, planning social and healthcare needs, optimising educational and occupational opportunities, guiding genetic counselling, the development of new therapies and evaluating the effectiveness of health interventions. Survival data is important in the development of evidence-based guidelines and standards of care for CF management and workforce planning, including screening, monitoring and management of age-related co-morbidities and complications. Further, comparisons of survival internationally promote equitable global health outcomes. Using a standardised approach to data processing and survival calculations will provide greater confidence in international comparisons and in the identification of factors that may contribute to the observed differences 2 , 8 . The objectives of this study were to use a standardised approach for estimating survival among patients participating in the Australian CF registry. Specific aims of this study were to:1) estimate median survival for Australian people with CF, 2) identify factors associated with survival, and 3) estimate median age of survival in successive 5-year cohorts beginning with the period 2005–2009 up until 2016–2020. Material And Methods Data Source This population-based cohort study used prospectively collected Australian Cystic Fibrosis Data Registry (ACFDR) data from 2005 to 2020 inclusive. The available data spanned 1998–2020, but analyses were limited to a cohort eligible from January 2005 through July 2021 to reflect completeness of data variables selected for this analysis. The ACFDR contains detailed demographic and clinical information about people with a confirmed diagnosis of CF, receiving clinical care at 23 CF centres in Australia 9 . It captures > 90% of all Australians with CF via enrolment in the registry, and at the end of 2020 there were 3,538 Australians diagnosed with CF whose records were registered with the ACFDR 9 . Data including age, sex, age of diagnosis, symptoms at presentation, diagnosis by NBS/prenatal screening, date of transplantation, date and cause of death, as well as anthropometric measurements, lung function, microbiology, CF-related complications, and pancreatic status were collected. Data were censored at the time of transplantation. A detailed description of the registry is provided elsewhere 9 – 11 . Definitions of key variables Diagnosis was categorized as: those detected with meconium ileus symptoms; diagnosed before 6 weeks of age or by NBS/prenatal screening; diagnosed 6 weeks – <2 years of age; 2–17 years and ≥ 18 years of age. Genotype was classified as F508del homozygous or other. Lung function, specifically the forced expiratory volume in one second (FEV 1 ), was recorded in litres and the percent predicted (FEV 1 pp) was calculated using Global Lung Function Initiative (GLI) reference equations 12 . BMI was calculated using weight/height 2 . Adult individuals (≥ 18 years) were classified into BMI categories based on World Health Organization guidelines as underweight (< 18.5 kg/m 2 ), adequate weight status (18.5–24.9 kg/m 2 ), or overweight (≥ 25.0 kg/m 2 ) 13 . Children were classified into BMI percentile categories based on Australian New Zealand CF Nutrition guidelines as underweight ( 85th percentile) 14 . Pancreatic insufficiency (PI) was determined by pancreatic enzyme use at the first data entry into the registry. Missing values were included as a separate category in the regression models. Statistical analyses Descriptive statistics were used to describe the study population. Demographic and clinical variables were summarised with categorical variables expressed as frequency and proportion and continuous variables summarised as mean, standard deviation (SD) and range. Overall survival probability was estimated using Kaplan-Meier survival curve 15 . Period survival analysis was used to calculate median age of survival estimates over time 16 . Median age of survival was calculated for each 5-year window beginning with the period 2005–2009 and ending with 2016–2020. Univariate and multivariable Cox proportional hazard models with age as the underlying time were used to assess the associations between personal and clinical characteristics and mortality 17 . Data were left truncated at the age on the 1 January of the year individuals were enrolled in the ACFDR and right censored at the date on which they were last seen. Death was defined as the event. Date of diagnosis was set at 30 days post date of birth for people with missing date of diagnosis. Any post-lung transplantation FEV 1 and BMI measurements were removed from the analyses. The following personal and clinical characteristics were included in the model: sex (male vs female, time-independent variable), diagnosis category ((i) with meconium ileus symptoms, (ii) under < 6weeks or by NBS/prenatal screening, (iii) 6 weeks – <2 years, (iv) 2–17 years and (v) ≥ 18 years groups, time-independent variable), genotype ( F508del homozygous or not, time-independent variable), pancreatic status (sufficient vs insufficient, time-independent variable), BMI (underweight, adequate weight status or overweight, categorical time-dependent variable), lung transplantation (binary, time-dependent variable), and FEV 1 pp (≥ 70, 40–69, or < 40), categorical time-dependent variable). FEV 1 data were not recorded in those < 6 years of age. All the analyses were performed in R version 4.1.1 and survival library 3.2 ( https://www.R-project.org ). Ethics approval The study had ethics approval from the Alfred Health Human Research Ethics Committees, Melbourne, Victoria, Australia (Project Number HREC/16/Alfred/187). Informed consent was obtained from individuals and parents/guardians of those < 18 years of age, and for sites where local ethics committee required this, and an opt-out model was applied to the other sites where patients had the opportunity to contact the registry and opt out from the registry. All methods were carried out in accordance with relevant guidelines and regulations. Results There were 4,601 people with CF observed over the period of 2005–2020 in the ACFDR. Table 1 shows basic demographic and clinical characteristics of the study sample. Table 1 Demographic and clinical variables of the study population, 2005–2020 Survived, N (%) Died, N (%) Total, N (%) p 4,085 (88.8%) 516 (11.2%) 4,601 (100%) Sex 0.840 1 Female 1,943 (47.6%) 243 (47.1%) 2,186 (47.5%) Male 2,142 (52.4%) 273 (52.9%) 2,415 (52.5%) Diagnosis category < 0.001 1 Diagnosed with meconium ileus 480 (11.8%) 48 (9.3%) 528 (11.5%) Age < 6 weeks or through NBS/Prenatal screening 2,747 (67.2%) 296 (57.4%) 3,043 (66.1%) Age 6 weeks - <2 years 376 (9.2%) 97 (18.8%) 473 (10.3%) Age 2–17 years 325 (8.0%) 46 (8.9%) 371 (8.1%) Age ≥ 18 years 157 (3.8%) 29 (5.6%) 186 (4.0%) F508del homozygous 0.864 1 No 2,223 (54.4%) 275 (54.1%) 2,498 (54.4%) Yes 1860 (45.6%) 233 (45.9%) 2,093 (45.6%) Lung transplant < 0.001 2 No 3,885 (95.1%) 321 (62.2%) 4,206 (91.4%) Yes 200 (4.9%) 195 (37.8%) 395 (8.6%) Pancreatic exocrine status < 0.436 1 Insufficient 2,836 (69.4%) 368 (71.3%) 3,204 (69.6%) Sufficient 972 (23.8%) 110 (21.3%) 1,082 (23.5%) Missing 277 (6.8%) 38 (7.4%) 315 (6.8%) Mean FEV 1 pp < 0.001 2 Not assessed, age < 6 years 3 516 (12.6%) 3 (0.6%) 519 (11.3%) Mean (SD) 83.1 (21.0) 55.7 (19.7) 79.7 (22.7) Range 17.0–130.0 10.0–111.6 10.0–130.0 Missing 138 (3.9%) 27 (0.6%) 165 (3.6%) Last recorded BMI 4 < 0.001 1 Underweight 182 (4.5%) 134 (26.0%) 316 (6.9%) Adequate weight status 2,670 (65.4%) 312 (60.5%) 2,982 (64.8%) Overweight 1,076 (26.3%) 47 (9.1%) 1,123 (24.4%) Missing 157 (3.8%) 23 (4.5%) 180 (3.9%) Mean last recorded BMI Adults (N) 2,359 462 2,821 < 0.001 2 BMI, Mean (SD) 23.5 (4.9) 20.6 (3.5) 23.0 (4.8) Range 13.9–167.5 12.5–35.8 12.5- 157.5 Missing 89 21 110 Children (N) 1,726 54 1,780 < 0.001 2 BMI percentile, Mean (SD) 0.6 (0.3) 0.4 (0.3) 0.6 (0.3) Range 0.0–1.0 0.0–1.0 0.0–1.0 Missing 68 2 70 Abbreviations: BMI=body mass index, FEV 1 pp =percent predicted forced expiratory volume in one second 1 Pearson’s Chi-squared test 2 Linear Model ANOVA 3 Lung function not captured for those <6 years of age 4 Adult individuals (≥18 years) were classified into BMI categories based on World Health Organization guidelines as underweight (<18.5 kg/m2), adequate weight (18.5-24.9 kg/m2), or overweight (≥ 25.0 kg/m2). Children were classified as underweight (85th percentile). [Table 1 about here please] There were more males (52.5%). Nearly half (45.6%) of all individuals with CF were F508del homozygous. Two thirds of people with CF (66.1%) were diagnosed < 6 weeks of age or by NBS/prenatal screening. Less than a third (23.5%) of the study population were pancreatic sufficient. Participants who survived were more likely to be diagnosed before 6 weeks of age, via NBS/prenatal screening (67.2% vs 57.4%) and to have not received a transplant (95.1% vs 62.2%). Mean (SD) FEV 1 pp across the lifetime in survivors was 83.1% (21.0), significantly higher than in those who died (55.7% (19.7), p < 0.001). Mean BMI for adults and BMI percentile for children were similar in survivors compared to non-survivors. Overall median survival age of individuals with CF in Australia was estimated as 54.0 years (95% CI: 51.0–57.4) (Fig. 1 A). Survival analysis using the Kaplan-Meier method shows the survival of people with CF is almost 100% up to the age of 12 and then starts to gradually decline. Of those people followed to the end of 2020, 648 (14.1%) were aged 40 years or more or had reached > 40 years at age of death. At the time of the data analysis, 69 (1.5%) of those followed were aged > 60 years or had reached > 60 years at death. Of those aged > 60 years, 38 (55%) were diagnosed when they were adults. [Fig. 1 . about here please] The Kaplan-Meier curves varied significantly depending on individual characteristics such as age at diagnosis (p-value of the log-rank score test = 0.001 (Fig. 1 B), lung function (p-value < 0.001) (Fig. 1 C), and BMI (p-value < 0.001) (Fig. 1 D). Table 2 displays the univariate and multivariable hazards ratios (HR) with 95% CIs, assessing the effects of the predictors of death. Table 2 Univariate and multivariable Cox proportional hazard models for death adjusted for demographic and clinical characteristics (2005–2020) Univariate model Multivariable model Hazard Ratio 95% CI Hazard Ratio 95% CI Sex Female 1.00 – 1.00 – Male 0.91 0.77–1.09 1.00 0.83–1.19 Diagnosis category Diagnosed with meconium ileus 1.00 – 1.00 – Age < 6 weeks or through NBS/Prenatal screening 1.06 0.78–1.45 1.37 1.00–1.88* Age 6 weeks - <2 years 1.12 0.79–1.59 1.12 0.79–1.59 Age 2–17 years 0.74 0.49–1.12 0.85 0.56–1.29 Age ≥ 18 years 0.60 0.37–1.00* 0.88 0.52–1.50 F508del homozygous No 1.00 – 1.00 – Yes 1.12 0.93–1.33 1.09 0.91–1.30 Lung transplant No 1.00 – 1.00 – Yes 9.49 7.83–11.51** 3.56 2.84–4.47** Pancreatic exocrine status Sufficient 1.00 – 1.00 – Insufficient 1.33 1.07–1.64* 1.13 0.91–1.40 Missing 1.17 0.80–1.69 1.14 0.78–1.66 FEV 1 pp ≥ 70 1.00 – 1.00 – 40–69 5.49 3.98–7.56** 4.60 3.33–6.36** < 40 22.32 16.2–30.75** 9.77 6.84–13.96** Missing 3.71 2.3–5.98** 4.95 1.76–13.88* BMI 1 Adequate weight status 1.00 – 1.00 – Underweight 4.42 3.6–5.42** 1.93 1.54– 2.41** Overweight 0.41 0.3–0.56** 0.79 0.57–1.08 Missing 0.7 0.46–1.08 0.61 0.21–1.77 Abbreviations: BMI=body mass index, FEV1pp =percent predicted forced expiratory volume in one second 1 Adult individuals (≥18 years) were classified into BMI categories based on World Health Organization guidelines as underweight (<18.5 kg/m2), adequate weight (18.5-24.9 kg/m2), or overweight (≥ 25.0 kg/m2). Children were classified as underweight (85th percentile). * p<0.05. **p<0.001. [Table 2 about here please] In the multivariable model which was adjusted for individual characteristics, no difference in survival between males and females was observed (HR 1.00, 95% CI: 0.83–1.19). Compared to those who were diagnosed with meconium ileus symptoms, the risk of death was 37% higher in those who were diagnosed aged < 6 weeks or by NBS/prenatal screening (HR 1.37, 95% CI: 1.00–1.88). This effect was observed in the multivariable model only. The risk of death was highest in those who underwent lung transplant (HR 3.56, 95% CI: 2.84–4.47). In the model adjusted for both demographic characteristics and clinical factors, the risk of death remained significantly higher in those with lifetime average FEV 1 pp of 40–69% (HR 4.60 95% CI 3.33–6.36) and with lifetime average FEV 1 pp of < 40% (HR 9.77, 95% CI 6.84–13.96). In terms of BMI, those who were underweight (reference category) were at higher risk of death. In the multivariable model pancreatic status was not associated with death. Table 3 (represented in Fig. 2 ), shows that the estimated median 5-year survival has increased over a 5-year period from 48.9 (95% CI: 44.7–53.5) years for people born in 2005–2009, to 56.3 (95% CI: 53.0–60.4) years for those born in 2016–2020. Table 3 Median survival of people with CF in Australia (2005–2020) Period 1 Year Median Age, years 95% CI N at risk N death 2005–2009 2009 48.9 44.7–53.5 3,002 129 2006–2010 2010 49.0 44.7–62.8 3,101 128 2007–2011 2011 49.7 44.7–56.1 3,196 139 2008–2012 2012 47.0 43.8–51.5 3,285 159 2009–2013 2013 46.8 43.2–49.9 3,365 180 2010–2014 2014 47.4 45.5–54.3 3,402 171 2011–2015 2015 47.4 45.6–54.3 3,479 170 2012–2016 2016 48.0 45.5–55.6 3,542 176 2013–2017 2017 53.0 47.4–59.8 3,568 169 2014–2018 2018 54.0 49.7–59.8 3,707 166 2015–2019 2019 53.0 48.9–59.8 3,772 171 2016–2020 2020 56.3 53.0–60.4 3,802 162 1 Refers to the cohort born in this period [Table 3 about here please] Figure 2 shows median survival of people with CF in Australia. Each dot and line represent the estimated median survival age and 95% CI, respectively, shown from 2005 to 2020. [Fig. 2 . about here please] Discussion This is the first study to describe estimated survival of people with CF in Australia with survival in those born in 2016–2020 emerging as 56.3 years (95% CI: 51.2–60.4). Our data demonstrates the increase in median estimated survival among Australian people with CF over the past 15 years, with survival estimates that are comparable with international estimates. According to our study findings, the greatest risk factors for worse survival were low lung function and poorer nutritional status, emphasising the need for ongoing targeted interventions that slow the progression of lung disease and improve nutrition. National CF registries are valuable tools for performing quality survival analyses and have been instrumental in demonstrating improved survival 6 . Many CF registries show the median age at death, supplemented by a graph representing the distribution of ages at death or the time trends in this median age at death. The Canadian, Irish, UK and US registries determine the estimated median age of survival based on the period approach 2 , 8 , 16 , 18 . Our results present overall and period survival of people with CF in Australia and the factors associated with survival. In 2012, the median age of survival varied between countries: 47.0 years in Australia (95% CI: 43.8–51.5), 49.7 years in Canada (95% CI: 46.1–52.2) 5 , 43.5 years in the UK (95% CI: 37.6–49.9) 19 and 41.1 years in the US (95% CI: 37.4–43.1) 20 . In recent years the estimated median age of survival in Australia was not dissimilar to that reported by other registries. For example, in 2019 the median age of survival was estimated to be 54.3 years of age in Canada 21 and the Cystic Fibrosis Foundation Registry Report from the US calculated the predicted median survival age of a child born that year with CF to be 53 years 22 . Factors associated with worse survival in the Australian CF population include being F508del homozygous, receiving a lung transplant, lower lung function, and low BMI. In contrast to previous studies, an unexpected association between survival and earlier age of diagnosis was observed in our study. This effect could be explained by a potentially higher proportion of those with severe genotypes identified via NBS or presenting very early, the poorer quality of the diagnosis data captured in earlier years of the data registry, or a chance finding. Sex and pancreatic status were not found to be independently associated with the survival probability. This finding is different from the previously reported registry survival studies 2 . The study by MacKenzie et al 23 reported that sex, F508del status and increasing age at diagnosis were independently associated with survival in the US, and female sex has long been associated with worse survival in CF compared to males 2 , 24 . It is possible that the gender gap in Australia is narrowing through improvements in treatment, diagnosis and lung function trajectory in females 25 26 , although further studies are required to confirm this. Published data suggest that receiving a lung transplant is associated with earlier death 27 . This finding was also observed in our study. Similarly, poorer lung function and lower BMI were also found to be associated with increased odds of mortality 6–8,27−29 . The results of our study and previous studies 6 , 27 , 30 confirm the impact of lung function and nutritional status on the survival of people with CF, showing that severe and moderate pulmonary impairment and undernutrition have a major impact on survival. These findings justify the emphasis on interventions aimed at optimising pulmonary function and nutritional status in CF guidelines and standards of care 31 . Improving median survival age in CF can be attributed to many different factors including NBS, nutritional interventions, proactive disease surveillance at both individual and population levels (including via the ACFDR), management of respiratory infections, access to novel therapies and improved standards of care 16 , 32 , 33 . The impact of NBS on survival estimates would not be evident for several decades until babies screened at birth reached an age where they would be at risk for death. NBS programmes for CF were first implemented in the early 1970s in the Royal Gwent Hospital in UK 34 . In Australia, NBS started in 1981and was progressively implemented across different states/jurisdictions becoming universal in 2001 35 , potentially explaining increased age of survival in recent years. Those identified by NBS have improved nutritional status and growth compared to people who are diagnosed by symptoms later in life 36 , and some studies indicate improved pulmonary function 37 . People identified at an early age benefit from early interventions to optimize nutrition, prevent and treat lung disease, and early monitoring for liver disease and other complications 38 . CFTR modulator therapies have the potential to reduce symptoms and increase survival for an increasing number of people with CF 6 . In Australia, the first CFTR modulator (ivacaftor) was approved for use from December 2014, with lumacaftor/ivacaftor (Orkambi R ) tezacaftor/ivacaftor (Symdeko R ) and elexacaftor/tezacaftor/ivacaftor (Trikafta R ) available for patients from October 2018, December 2019 and April 2022 respectively 9 . It is too soon to see the impact of these novel therapies on survival although the estimated median age of survival of people with CF in Australia is expected to continue to improve. The Australian CF registry data is an essential tool to evaluate the impact of CFTR modulator therapies on future clinical outcomes including survival long-term 6 . Strengths and Limitations The strengths of our study include the large sample size, the longitudinal data within the ACFDR, the consistency of our results across multiple sub-groups and the unified approach to the analysis. There is a very high participation rate at the centre level as well as in the registry as since mid-2019 participating centres receive payment for data submission which results in a comprehensive national picture of the CF population in Australia 11 . In addition, this study is of the longest running cohort of patients diagnosed via NBS 35 . As the ACFDR does not capture identifiable data, some death and transplant data could not be verified through national linkages. In addition, data pertaining to CF co-morbidities, such as CF-related diabetes and chronic infections with P. aeruginosa were not analysed separately, and could influence survival outcomes. Certain data elements were incompletely recorded for the earlier years for this analysis (i.e. microbiology, CF-related diabetes and socioeconomic status) thus we were unable to account for these factors in our analyses. The differentiation of NBS diagnosis and clinical diagnosis based on meconium ileus /failure to thrive in first few weeks is not absolutely clear and could affect the quality of the diagnosis data. A database redesign conducted in 2018, and a new format of the registry will enable better quality and completeness of the registry records and greater accuracy of future analyses arising from the registry data 9 , 10 . Conclusions We have demonstrated successive improvements in survival among people with CF in Australia over the last 15 years and identified factors influencing survival. Further research is needed to understand the complex interactions between biological and epidemiological factors not examined in this current study on the severity of disease and survival. The increase in survival and longevity requires an evolution in models of CF care towards prevention and management of age-related comorbidities such as diabetes, metabolic and cardiovascular disease, malignancies and osteoporosis alongside nutritional and respiratory care 39 . Increasing longevity must be coupled with increasing quality of life and the ability for people with CF to actively participate in a broad range of personal, community and work-based activities. Accordingly, these survival data presented highlight the need for future care models to incorporate a greater focus on the psychological, social, educational and occupational potential of people with CF as they live into old age. Declarations Acknowledgments The authors thank the participating CF centres, data entry personnel, survey participants, patients and their families. Author contributions RR, SA, AE and SB conceived the study. RR, AE and FS performed data processing and statistical analysis. RR, FS and SA were responsible for the creation of the original draft of the manuscript that was revised and approved by all authors for important intellectual content. TD, KF, LK, SK, TK, PGM, SM, SM, AS, CW, NW and PW contributed to the development of the final manuscript. All authors read and approved the final manuscript. Data availability The datasets generated during and/or analysed during the current study are available from the corresponding author on request and pending approval to the ACFDR Data Access and Research Publishing Committee. Funding This study was supported by Cystic Fibrosis Australia. Competing Interests The authors declare no competing interests. References Schmidt, B. Z., Haaf, J. B., Leal, T. & Noel, S. Cystic fibrosis transmembrane conductance regulator modulators in cystic fibrosis: current perspectives. Clin Pharmacol 8 , 127–140, doi: 10.2147/cpaa.S100759 (2016). Keogh, R. H., Szczesniak, R., Taylor-Robinson, D. & Bilton, D. 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Available online : https://www.cysticfibrosis.ca/uploads/RegistryReport2019/2019RegistryAnnualDataReport.pdf . Cystic Fibrosis Foundation Patient Registry. 2021 CYSTIC FIBROSIS FOUNDATION PATIENT REGISTRY HIGHLIGHTS Cystic Fibrosis Foundation. https://www.cff.org/medical-professionals/patient-registry . MacKenzie, T. et al. Longevity of patients with cystic fibrosis in 2000 to 2010 and beyond: survival analysis of the Cystic Fibrosis Foundation patient registry. Annals of internal medicine 161 , 233–241, doi: 10.7326/m13-0636 (2014). Calella, P., Valerio, G., Brodlie, M., Donini, L. M. & Siervo, M. Cystic fibrosis, body composition, and health outcomes: a systematic review. Nutrition (Burbank, Los Angeles County, Calif.) 55–56 , 131–139, doi: 10.1016/j.nut.2018.03.052 (2018). Lai, H. C., Kosorok, M. R., Laxova, A., Makholm, L. M. & Farrell, P. M. Delayed diagnosis of US females with cystic fibrosis. American journal of epidemiology 156 , 165–173, doi: 10.1093/aje/kwf014 (2002). Viviani, L., Bossi, A. & Assael, B. M. Absence of a gender gap in survival. An analysis of the Italian registry for cystic fibrosis in the paediatric age. Journal of cystic fibrosis: official journal of the European Cystic Fibrosis Society 10 , 313–317, doi: 10.1016/j.jcf.2011.03.007 (2011). Stephenson, A. L. et al. Clinical and demographic factors associated with post-lung transplantation survival in individuals with cystic fibrosis. J Heart Lung Transplant 34 , 1139–1145, doi: 10.1016/j.healun.2015.05.003 (2015). Keogh, R. H., Seaman, S. R., Barrett, J. K., Taylor-Robinson, D. & Szczesniak, R. Dynamic Prediction of Survival in Cystic Fibrosis: A Landmarking Analysis Using UK Patient Registry Data. Epidemiology 30 , 29–37, doi: 10.1097/ede.0000000000000920 (2019). McKone, E. F. et al. Survival estimates in European cystic fibrosis patients and the impact of socioeconomic factors: a retrospective registry Cohort study. The European respiratory journal 10 . 1183 / 13993003 . 02288 -2020, doi: 10.1183/13993003.02288-2020 (2021). Szwed, A. et al. Survival of Patients with Cystic Fibrosis Depending on Mutation Type and Nutritional Status. Adv Exp Med Biol 1023 , 65–72, doi: 10.1007/5584_2017_66 (2018). Cystic Fibrosis Australia. Cystic Fibrosis Standards of Care, Australia. Sydney: Cystic Fibrosis Australia, 2008. Goss, C. H. et al. Comparison of nutrition and lung function outcomes in patients with cystic fibrosis living in Canada and the United States. American journal of respiratory and critical care medicine 197 , 768–775, doi: 10.1164/rccm.201707-1541OC (2017). Zampoli, M. et al. Trends in cystic fibrosis survival over 40 years in South Africa: An observational cohort study. Pediatric pulmonology 10 . 1002 / ppul . 25810 , doi: 10.1002/ppul.25810 (2021). Prosser, R. et al. Screening for cystic fibrosis by examination of meconium. Archives of disease in childhood 49 , 597–601, doi: 10.1136/adc.49.8.597 (1974). Waters, D. L. et al. Clinical outcomes of newborn screening for cystic fibrosis. Arch Dis Child Fetal Neonatal Ed 80 , F1-7, doi: 10.1136/fn.80.1.f1 (1999). Farrell, P. M. et al. Early diagnosis of cystic fibrosis through neonatal screening prevents severe malnutrition and improves long-term growth. Wisconsin Cystic Fibrosis Neonatal Screening Study Group. Pediatrics 107 , 1–13, doi: 10.1542/peds.107.1.1 (2001). Grosse, S. D. et al. Newborn screening for cystic fibrosis: evaluation of benefits and risks and recommendations for state newborn screening programs. MMWR Recomm Rep 53 , 1–36 (2004). McBennett, K. A., Davis, P. B. & Konstan, M. W. Increasing life expectancy in cystic fibrosis: Advances and challenges. Pediatric pulmonology 57 Suppl 1 , S5-s12, doi: 10.1002/ppul.25733 (2022). McDonald, C. M. et al. Academy of Nutrition and Dietetics: 2020 Cystic Fibrosis Evidence Analysis Center Evidence-Based Nutrition Practice Guideline. Journal of the Academy of Nutrition and Dietetics 121 , 1591–1636.e1593, doi: 10.1016/j.jand.2020.03.015 (2021). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 21 Oct, 2022 Reviews received at journal 22 Sep, 2022 Reviewers agreed at journal 19 Sep, 2022 Reviewers invited by journal 19 Sep, 2022 Editor assigned by journal 19 Sep, 2022 Editor invited by journal 19 Sep, 2022 Submission checks completed at journal 19 Sep, 2022 First submitted to journal 18 Sep, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2079022","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":137769505,"identity":"a6a2a979-73e8-480c-b8dc-627bd5a4a7a2","order_by":0,"name":"Rasa Ruseckaite","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIie2OMWrDMBRAv5d4cryqpCRXSBAogZj6Kt8E7MU5Qw0Fe0n35BCFTKZDBxWBvYjOytYQaJcO7mZPrZrZIu3WQQ++EOg/ngAslv/NAAABxue7k+mD/0pBoH9UdCbKLinzoj42zpMIfbeKmmMbJA/F/fNn9wjjocJe5VqmlMCbiHabWBDEeF3Kl9XIk0CvDAqBVA8XOFVuphWxLlU6HTk5RHuT4r+fWq2EoXLvWsSvhKmUdl0Ot0aFIPupOHsyqHSFo1YY8XLQXZPywRbIk2gr43iB8WpWSsmWXk5mO/lq+FhyUg1fhn5R0UMb3ExYvaGHLg8mw7q/cqbviZjXLRaLxXKRb+DMZGmL1iSrAAAAAElFTkSuQmCC","orcid":"","institution":"Monash University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Rasa","middleName":"","lastName":"Ruseckaite","suffix":""},{"id":137769508,"identity":"14992094-3132-45c4-b13a-69a554dbcc7c","order_by":1,"name":"Farhad Salimi","email":"","orcid":"","institution":"Monash University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Farhad","middleName":"","lastName":"Salimi","suffix":""},{"id":137769511,"identity":"086e2644-415c-473a-b31a-a759534d33fe","order_by":2,"name":"Arul Earnest","email":"","orcid":"","institution":"Monash University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Arul","middleName":"","lastName":"Earnest","suffix":""},{"id":137769514,"identity":"9204ae7a-4b09-4b22-97d6-2a40bce08915","order_by":3,"name":"Scott C Bell","email":"","orcid":"","institution":"The Prince Charles Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Scott","middleName":"C","lastName":"Bell","suffix":""},{"id":137769518,"identity":"89066c6e-55d8-4cbd-8c42-ffd775cd0ab2","order_by":4,"name":"Tonia Douglas","email":"","orcid":"","institution":"The University of Queensland","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tonia","middleName":"","lastName":"Douglas","suffix":""},{"id":137769523,"identity":"fcd7216e-d357-4700-9f65-c574d902144b","order_by":5,"name":"Katherine Frayman","email":"","orcid":"","institution":"Royal Children’s Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Katherine","middleName":"","lastName":"Frayman","suffix":""},{"id":137769526,"identity":"ef9c5339-285b-4ac2-8633-1b45247a5e93","order_by":6,"name":"Lucy Keatley","email":"","orcid":"","institution":"Westmead Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lucy","middleName":"","lastName":"Keatley","suffix":""},{"id":137769529,"identity":"6101d261-1b01-4c18-820a-c28626c78685","order_by":7,"name":"Susannah King","email":"","orcid":"","institution":"The Alfred","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Susannah","middleName":"","lastName":"King","suffix":""},{"id":137769532,"identity":"cb8b47b2-43cd-4e12-972e-147734bce53f","order_by":8,"name":"Tom Kotsimbos","email":"","orcid":"","institution":"Monash University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tom","middleName":"","lastName":"Kotsimbos","suffix":""},{"id":137769537,"identity":"9b53df6e-e1f1-4735-9d31-4761375490ca","order_by":9,"name":"Peter G Middleton","email":"","orcid":"","institution":"Westmead Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Peter","middleName":"G","lastName":"Middleton","suffix":""},{"id":137769541,"identity":"65e1e6e6-820a-4124-ab22-5d6d71c1068e","order_by":10,"name":"Sue Morey","email":"","orcid":"","institution":"Sir Charles Gairdner Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sue","middleName":"","lastName":"Morey","suffix":""},{"id":137769545,"identity":"b11923f4-df44-4d6e-885e-f9dc3bc0016d","order_by":11,"name":"Siobhain Mulrennan","email":"","orcid":"","institution":"Sir Charles Gairdner Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Siobhain","middleName":"","lastName":"Mulrennan","suffix":""},{"id":137769548,"identity":"7a8cd825-56a4-4fd3-977d-6b7dfe904da3","order_by":12,"name":"Andre Schultz","email":"","orcid":"","institution":"Perth Children's Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Andre","middleName":"","lastName":"Schultz","suffix":""},{"id":137769549,"identity":"aadc0fe1-8e50-4e4b-8f22-be91245874ac","order_by":13,"name":"Claire Wainwright","email":"","orcid":"","institution":"The University of Queensland","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Claire","middleName":"","lastName":"Wainwright","suffix":""},{"id":137769551,"identity":"aeeecdb3-1ed0-4c78-ba4d-5264b26e3764","order_by":14,"name":"Nathan Ward","email":"","orcid":"","institution":"Royal Adelaide Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nathan","middleName":"","lastName":"Ward","suffix":""},{"id":137769553,"identity":"9563a6d9-23ec-4911-8562-c49c21f724b4","order_by":15,"name":"Peter Wark","email":"","orcid":"","institution":"Perth Children's Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Wark","suffix":""},{"id":137769555,"identity":"4c8c07ba-3341-4c7d-bcea-9f5dd1518e72","order_by":16,"name":"Susannah Ahern","email":"","orcid":"","institution":"Monash University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Susannah","middleName":"","lastName":"Ahern","suffix":""}],"badges":[],"createdAt":"2022-09-19 02:59:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2079022/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2079022/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":26895939,"identity":"5bc4d917-6784-4d3b-bd41-d496f27873f2","added_by":"auto","created_at":"2022-09-23 18:25:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":169293,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Overall survival curve for people with cystic fibrosis, based on Kaplan-Meier estimates. (B) Probability functions depicting the age of people with cystic fibrosis by diagnosis category (with meconium ileus symptoms, under \u0026lt;6weeks or by NBS/prenatal screening, 6 weeks – \u0026lt;2 years, 2 - 17 years and ≥18 years groups).\u003cstrong\u003e (\u003c/strong\u003eC\u003cstrong\u003e) \u003c/strong\u003eProbability functions depicting the age of people with CF by average lifetime lung function (FEV1 pp categories ≥70, 40-69, \u0026lt;40). (D) Probability functions depicting the age of people with cystic fibrosis by BMI. Adult individuals (≥8 years) were classified into BMI categories based on World Health Organization guidelines as underweight (\u0026lt;18.5 kg/m2), adequate weight (18.5-24.9 kg/m2), or overweight (≥25.0 kg/m2). Children were classified as underweight (\u0026lt;10th percentile), adequate weight (10-85th percentile), or overweight (\u0026gt;85th percentile).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2079022/v1/2bc44b5d7df8922f0a3f7b5a.jpg"},{"id":26895938,"identity":"e538b5db-cd5f-4a73-9000-c5082a5e2536","added_by":"auto","created_at":"2022-09-23 18:25:05","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":62952,"visible":true,"origin":"","legend":"\u003cp\u003eMedian survival of people with cystic fibrosis in Australia (5-year cohorts), 2005-2020. Black circles indicate median age data. Error bars represent 95% confidence intervals data. Summary statistics are provided in Table 3.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2079022/v1/c9d7b616e99316de50415a2c.jpg"},{"id":26895941,"identity":"3fa58999-e930-47e0-abd8-3090377198db","added_by":"auto","created_at":"2022-09-23 18:25:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":486427,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2079022/v1/482fe4d5-2145-47d8-92fe-1b150301bd92.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Survival of People with Cystic Fibrosis in Australia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCystic fibrosis (CF) is the most common autosomal recessive-inherited life-limiting condition, affecting approximately 90,000 individuals worldwide\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. People with CF require support from healthcare services from diagnosis onwards; and respiratory failure is the commonest cause of premature death\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Although life expectancy for people with CF has increased substantially, the disease continues to result in reduced life expectancy, poorer quality of life, and a large burden of care for people with CF, their families and health care providers\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Prognosis continues to improve due to advancements in CF care\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, such as the availability of new inhaled antibiotics, newborn screening (NBS), \u003cem\u003eP. aeruginosa\u003c/em\u003e eradication therapy, mucolytic treatment, better growth and nutrition, lung transplantation and lifetime multidisciplinary care in specialised CF centres\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlthough CF survival estimates have greatly improved globally, survival continues to be influenced by various individual factors\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. A recent study of UK registry data demonstrated that male sex was associated with better survival, as was later diagnosis in adulthood, but only in non-F508del homozygotes. Survival did not differ by genotype among individuals diagnosed in early infancy\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. In the recent study of Durda-Masny et al\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, the shortest life expectancy was observed in adult patients with a severe mutation on both alleles, Forced Expiratory Volume in one second percent predicted (FEV\u003csub\u003e1\u003c/sub\u003epp)\u0026thinsp;\u0026lt;\u0026thinsp;40%, patients infected with extensively drug-resistant \u003cem\u003eP. aeruginosa\u003c/em\u003e, and body mass index (BMI)\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e. Most of the deaths in these people occurred between 30 and 40 years of age.\u003c/p\u003e \u003cp\u003eProviding up-to-date estimates of survival is helpful for counselling people with CF and their families on life expectancy, planning social and healthcare needs, optimising educational and occupational opportunities, guiding genetic counselling, the development of new therapies and evaluating the effectiveness of health interventions. Survival data is important in the development of evidence-based guidelines and standards of care for CF management and workforce planning, including screening, monitoring and management of age-related co-morbidities and complications. Further, comparisons of survival internationally promote equitable global health outcomes. Using a standardised approach to data processing and survival calculations will provide greater confidence in international comparisons and in the identification of factors that may contribute to the observed differences\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe objectives of this study were to use a standardised approach for estimating survival among patients participating in the Australian CF registry. Specific aims of this study were to:1) estimate median survival for Australian people with CF, 2) identify factors associated with survival, and 3) estimate median age of survival in successive 5-year cohorts beginning with the period 2005\u0026ndash;2009 up until 2016\u0026ndash;2020.\u003c/p\u003e"},{"header":"Material And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source\u003c/h2\u003e \u003cp\u003eThis population-based cohort study used prospectively collected Australian Cystic Fibrosis Data Registry (ACFDR) data from 2005 to 2020 inclusive. The available data spanned 1998\u0026ndash;2020, but analyses were limited to a cohort eligible from January 2005 through July 2021 to reflect completeness of data variables selected for this analysis.\u003c/p\u003e \u003cp\u003eThe ACFDR contains detailed demographic and clinical information about people with a confirmed diagnosis of CF, receiving clinical care at 23 CF centres in Australia\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. It captures\u0026thinsp;\u0026gt;\u0026thinsp;90% of all Australians with CF via enrolment in the registry, and at the end of 2020 there were 3,538 Australians diagnosed with CF whose records were registered with the ACFDR\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eData including age, sex, age of diagnosis, symptoms at presentation, diagnosis by NBS/prenatal screening, date of transplantation, date and cause of death, as well as anthropometric measurements, lung function, microbiology, CF-related complications, and pancreatic status were collected. Data were censored at the time of transplantation.\u003c/p\u003e \u003cp\u003eA detailed description of the registry is provided elsewhere\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDefinitions of key variables\u003c/h2\u003e \u003cp\u003eDiagnosis was categorized as: those detected with meconium ileus symptoms; diagnosed before 6 weeks of age or by NBS/prenatal screening; diagnosed 6 weeks \u0026ndash; \u0026lt;2 years of age; 2\u0026ndash;17 years and \u0026ge;\u0026thinsp;18 years of age. Genotype was classified as F508del homozygous or other. Lung function, specifically the forced expiratory volume in one second (FEV\u003csub\u003e1\u003c/sub\u003e), was recorded in litres and the percent predicted (FEV\u003csub\u003e1\u003c/sub\u003epp) was calculated using Global Lung Function Initiative (GLI) reference equations\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. BMI was calculated using weight/height\u003csup\u003e2\u003c/sup\u003e. Adult individuals (\u0026ge;\u0026thinsp;18 years) were classified into BMI categories based on World Health Organization guidelines as underweight (\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e), adequate weight status (18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e), or overweight (\u0026ge;\u0026thinsp;25.0 kg/m\u003csup\u003e2\u003c/sup\u003e)\u003csup\u003e13\u003c/sup\u003e. Children were classified into BMI percentile categories based on Australian New Zealand CF Nutrition guidelines as underweight (\u0026lt;\u0026thinsp;10th percentile), adequate weight (10-85th percentile), or overweight (\u0026gt;\u0026thinsp;85th percentile)\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Pancreatic insufficiency (PI) was determined by pancreatic enzyme use at the first data entry into the registry. Missing values were included as a separate category in the regression models.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eDescriptive statistics were used to describe the study population. Demographic and clinical variables were summarised with categorical variables expressed as frequency and proportion and continuous variables summarised as mean, standard deviation (SD) and range.\u003c/p\u003e \u003cp\u003eOverall survival probability was estimated using Kaplan-Meier survival curve\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Period survival analysis was used to calculate median age of survival estimates over time\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Median age of survival was calculated for each 5-year window beginning with the period 2005\u0026ndash;2009 and ending with 2016\u0026ndash;2020. Univariate and multivariable Cox proportional hazard models with age as the underlying time were used to assess the associations between personal and clinical characteristics and mortality\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eData were left truncated at the age on the 1 January of the year individuals were enrolled in the ACFDR and right censored at the date on which they were last seen. Death was defined as the event. Date of diagnosis was set at 30 days post date of birth for people with missing date of diagnosis. Any post-lung transplantation FEV\u003csub\u003e1\u003c/sub\u003e and BMI measurements were removed from the analyses. The following personal and clinical characteristics were included in the model: sex (male vs female, time-independent variable), diagnosis category ((i) with meconium ileus symptoms, (ii) under \u0026lt;\u0026thinsp;6weeks or by NBS/prenatal screening, (iii) 6 weeks \u0026ndash; \u0026lt;2 years, (iv) 2\u0026ndash;17 years and (v)\u0026thinsp;\u0026ge;\u0026thinsp;18 years groups, time-independent variable), genotype (\u003cem\u003eF508del homozygous\u003c/em\u003e or not, time-independent variable), pancreatic status (sufficient vs insufficient, time-independent variable), BMI (underweight, adequate weight status or overweight, categorical time-dependent variable), lung transplantation (binary, time-dependent variable), and FEV\u003csub\u003e1\u003c/sub\u003epp (\u0026ge;\u0026thinsp;70, 40\u0026ndash;69, or \u0026lt;\u0026thinsp;40), categorical time-dependent variable). FEV\u003csub\u003e1\u003c/sub\u003e data were not recorded in those\u0026thinsp;\u0026lt;\u0026thinsp;6 years of age.\u003c/p\u003e \u003cp\u003eAll the analyses were performed in R version 4.1.1 and survival library 3.2 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.R-project.org\u003c/span\u003e\u003cspan address=\"https://www.R-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eEthics approval\u003c/h2\u003e \u003cp\u003eThe study had ethics approval from the Alfred Health Human Research Ethics Committees, Melbourne, Victoria, Australia (Project Number HREC/16/Alfred/187). Informed consent was obtained from individuals and parents/guardians of those\u0026thinsp;\u0026lt;\u0026thinsp;18 years of age, and for sites where local ethics committee required this, and an opt-out model was applied to the other sites where patients had the opportunity to contact the registry and opt out from the registry. All methods were carried out in accordance with relevant guidelines and regulations.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThere were 4,601 people with CF observed over the period of 2005\u0026ndash;2020 in the ACFDR. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows basic demographic and clinical characteristics of the study sample.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic and clinical variables of the study population, 2005\u0026ndash;2020\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSurvived, N (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDied, N (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal, N (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,085 (88.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e516 (11.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,601 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.840\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,943 (47.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e243 (47.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,186 (47.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,142 (52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e273 (52.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,415 (52.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiagnosis category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiagnosed with meconium ileus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e480 (11.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e528 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u0026thinsp;\u0026lt;\u0026thinsp;6 weeks or through NBS/Prenatal screening\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,747 (67.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e296 (57.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,043 (66.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge 6 weeks - \u0026lt;2 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e376 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97 (18.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e473 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge 2\u0026ndash;17 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e325 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e371 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u0026thinsp;\u0026ge;\u0026thinsp;18 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e157 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e186 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF508del homozygous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.864\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,223 (54.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e275 (54.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,498 (54.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1860 (45.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e233 (45.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,093 (45.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLung transplant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,885 (95.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e321 (62.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,206 (91.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 (4.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e195 (37.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e395 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePancreatic exocrine status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.436\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInsufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,836 (69.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e368 (71.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,204 (69.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e972 (23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 (21.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,082 (23.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e277 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e315 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean FEV\u003csub\u003e1\u003c/sub\u003epp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot assessed, age\u0026thinsp;\u0026lt;\u0026thinsp;6 years\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e516 (12.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e519 (11.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83.1 (21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55.7 (19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79.7 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.0\u0026ndash;130.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.0\u0026ndash;111.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.0\u0026ndash;130.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e165 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLast recorded BMI\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnderweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e182 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e134 (26.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e316 (6.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdequate weight status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,670 (65.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e312 (60.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,982 (64.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,076 (26.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,123 (24.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e157 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e180 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean last recorded BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdults (N)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI, Mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.5 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.6 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.0 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.9\u0026ndash;167.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.5\u0026ndash;35.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.5- 157.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChildren (N)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI percentile, Mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0\u0026ndash;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0\u0026ndash;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0\u0026ndash;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e BMI=body mass index, FEV\u003csub\u003e1\u003c/sub\u003epp =percent predicted forced expiratory volume in one second\u003c/p\u003e\n\u003cp\u003e1 Pearson\u0026rsquo;s Chi-squared test\u003c/p\u003e\n\u003cp\u003e2 Linear Model ANOVA\u003c/p\u003e\n\u003cp\u003e3\u0026nbsp;Lung function not captured for those \u0026lt;6 years of age\u003c/p\u003e\n\u003cp\u003e4 Adult individuals (\u0026ge;18 years) were classified into BMI categories based on World Health Organization guidelines as underweight (\u0026lt;18.5 kg/m2), adequate weight (18.5-24.9 kg/m2), or overweight (\u0026ge; 25.0 kg/m2). Children were classified as underweight (\u0026lt; 10th percentile), adequate weight (10-85th percentile), or overweight (\u0026gt;85th percentile).\u003c/p\u003e\n\u003cp\u003e[Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e about here please]\u003c/p\u003e\n\u003cp\u003eThere were more males (52.5%). Nearly half (45.6%) of all individuals with CF were F508del homozygous. Two thirds of people with CF (66.1%) were diagnosed\u0026thinsp;\u0026lt;\u0026thinsp;6 weeks of age or by NBS/prenatal screening. Less than a third (23.5%) of the study population were pancreatic sufficient. Participants who survived were more likely to be diagnosed before 6 weeks of age, via NBS/prenatal screening (67.2% vs 57.4%) and to have not received a transplant (95.1% vs 62.2%).\u003c/p\u003e\n\u003cp\u003eMean (SD) FEV\u003csub\u003e1\u003c/sub\u003epp across the lifetime in survivors was 83.1% (21.0), significantly higher than in those who died (55.7% (19.7), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Mean BMI for adults and BMI percentile for children were similar in survivors compared to non-survivors. Overall median survival age of individuals with CF in Australia was estimated as 54.0 years (95% CI: 51.0\u0026ndash;57.4) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA). Survival analysis using the Kaplan-Meier method shows the survival of people with CF is almost 100% up to the age of 12 and then starts to gradually decline. Of those people followed to the end of 2020, 648 (14.1%) were aged 40 years or more or had reached\u0026thinsp;\u0026gt;\u0026thinsp;40 years at age of death. At the time of the data analysis, 69 (1.5%) of those followed were aged\u0026thinsp;\u0026gt;\u0026thinsp;60 years or had reached\u0026thinsp;\u0026gt;\u0026thinsp;60 years at death. Of those aged\u0026thinsp;\u0026gt;\u0026thinsp;60 years, 38 (55%) were diagnosed when they were adults.\u003c/p\u003e\n\u003cp\u003e[Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. about here please]\u003c/p\u003e\n\u003cp\u003eThe Kaplan-Meier curves varied significantly depending on individual characteristics such as age at diagnosis (p-value of the log-rank score test\u0026thinsp;=\u0026thinsp;0.001 (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB), lung function (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC), and BMI (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e displays the univariate and multivariable hazards ratios (HR) with 95% CIs, assessing the effects of the predictors of death.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUnivariate and multivariable Cox proportional hazard models for death adjusted for demographic and clinical characteristics (2005\u0026ndash;2020)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eUnivariate model\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMultivariable model\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHazard\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRatio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHazard\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRatio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u0026ndash;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83\u0026ndash;1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnosis category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiagnosed with meconium ileus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u0026thinsp;\u0026lt;\u0026thinsp;6 weeks or through NBS/Prenatal screening\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78\u0026ndash;1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u0026ndash;1.88*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge 6 weeks - \u0026lt;2 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.79\u0026ndash;1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.79\u0026ndash;1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge 2\u0026ndash;17 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.49\u0026ndash;1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.56\u0026ndash;1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u0026thinsp;\u0026ge;\u0026thinsp;18 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.37\u0026ndash;1.00*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52\u0026ndash;1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eF508del homozygous\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.93\u0026ndash;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u0026ndash;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLung transplant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.83\u0026ndash;11.51**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.84\u0026ndash;4.47**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePancreatic exocrine status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInsufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.07\u0026ndash;1.64*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u0026ndash;1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.80\u0026ndash;1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78\u0026ndash;1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFEV\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sub\u003e \u003cstrong\u003epp\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026ndash;69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.98\u0026ndash;7.56**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.33\u0026ndash;6.36**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.2\u0026ndash;30.75**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.84\u0026ndash;13.96**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3\u0026ndash;5.98**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.76\u0026ndash;13.88*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdequate weight status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnderweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.6\u0026ndash;5.42**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.54\u0026ndash; 2.41**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u0026ndash;0.56**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u0026ndash;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.46\u0026ndash;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u0026ndash;1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e BMI=body mass index, FEV1pp =percent predicted forced expiratory volume in one second\u003c/p\u003e\n\u003cp\u003e1 Adult individuals (\u0026ge;18 years) were classified into BMI categories based on World Health Organization guidelines as underweight (\u0026lt;18.5 kg/m2), adequate weight (18.5-24.9 kg/m2), or overweight (\u0026ge; 25.0 kg/m2).\u0026nbsp;Children were classified as underweight (\u0026lt; 10th percentile), adequate weight (10-85th percentile), or overweight (\u0026gt;85th percentile).\u003c/p\u003e\n\u003cp\u003e* p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e**p\u0026lt;0.001.\u003c/p\u003e\n\u003cp\u003e[Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e about here please]\u003c/p\u003e\n\u003cp\u003eIn the multivariable model which was adjusted for individual characteristics, no difference in survival between males and females was observed (HR 1.00, 95% CI: 0.83\u0026ndash;1.19). Compared to those who were diagnosed with meconium ileus symptoms, the risk of death was 37% higher in those who were diagnosed aged\u0026thinsp;\u0026lt;\u0026thinsp;6 weeks or by NBS/prenatal screening (HR 1.37, 95% CI: 1.00\u0026ndash;1.88). This effect was observed in the multivariable model only. The risk of death was highest in those who underwent lung transplant (HR 3.56, 95% CI: 2.84\u0026ndash;4.47). In the model adjusted for both demographic characteristics and clinical factors, the risk of death remained significantly higher in those with lifetime average FEV\u003csub\u003e1\u003c/sub\u003epp of 40\u0026ndash;69% (HR 4.60 95% CI 3.33\u0026ndash;6.36) and with lifetime average FEV\u003csub\u003e1\u003c/sub\u003epp of \u0026lt;\u0026thinsp;40% (HR 9.77, 95% CI 6.84\u0026ndash;13.96). In terms of BMI, those who were underweight (reference category) were at higher risk of death. In the multivariable model pancreatic status was not associated with death.\u003c/p\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e (represented in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), shows that the estimated median 5-year survival has increased over a 5-year period from 48.9 (95% CI: 44.7\u0026ndash;53.5) years for people born in 2005\u0026ndash;2009, to 56.3 (95% CI: 53.0\u0026ndash;60.4) years for those born in 2016\u0026ndash;2020.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMedian survival of people with CF in Australia (2005\u0026ndash;2020)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePeriod\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedian Age,\u003c/p\u003e\n \u003cp\u003eyears\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN at risk\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN death\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2005\u0026ndash;2009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44.7\u0026ndash;53.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2006\u0026ndash;2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44.7\u0026ndash;62.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2007\u0026ndash;2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44.7\u0026ndash;56.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2008\u0026ndash;2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43.8\u0026ndash;51.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2009\u0026ndash;2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43.2\u0026ndash;49.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2010\u0026ndash;2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.5\u0026ndash;54.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2011\u0026ndash;2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.6\u0026ndash;54.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2012\u0026ndash;2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.5\u0026ndash;55.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2013\u0026ndash;2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47.4\u0026ndash;59.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e169\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2014\u0026ndash;2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49.7\u0026ndash;59.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2015\u0026ndash;2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.9\u0026ndash;59.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2016\u0026ndash;2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.0\u0026ndash;60.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e1 Refers to the cohort born in this period\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e[Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e about here please]\u003c/p\u003e\n\u003cp\u003eFigure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows median survival of people with CF in Australia. Each dot and line represent the estimated median survival age and 95% CI, respectively, shown from 2005 to 2020.\u003c/p\u003e\n\u003cp\u003e[Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. about here please]\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is the first study to describe estimated survival of people with CF in Australia with survival in those born in 2016\u0026ndash;2020 emerging as 56.3 years (95% CI: 51.2\u0026ndash;60.4). Our data demonstrates the increase in median estimated survival among Australian people with CF over the past 15 years, with survival estimates that are comparable with international estimates. According to our study findings, the greatest risk factors for worse survival were low lung function and poorer nutritional status, emphasising the need for ongoing targeted interventions that slow the progression of lung disease and improve nutrition.\u003c/p\u003e \u003cp\u003eNational CF registries are valuable tools for performing quality survival analyses and have been instrumental in demonstrating improved survival\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Many CF registries show the median age at death, supplemented by a graph representing the distribution of ages at death or the time trends in this median age at death. The Canadian, Irish, UK and US registries determine the estimated median age of survival based on the period approach\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur results present overall and period survival of people with CF in Australia and the factors associated with survival. In 2012, the median age of survival varied between countries: 47.0 years in Australia (95% CI: 43.8\u0026ndash;51.5), 49.7 years in Canada (95% CI: 46.1\u0026ndash;52.2)\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, 43.5 years in the UK (95% CI: 37.6\u0026ndash;49.9)\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e and 41.1 years in the US (95% CI: 37.4\u0026ndash;43.1)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. In recent years the estimated median age of survival in Australia was not dissimilar to that reported by other registries. For example, in 2019 the median age of survival was estimated to be 54.3 years of age in Canada \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e and the Cystic Fibrosis Foundation Registry Report from the US calculated the predicted median survival age of a child born that year with CF to be 53 years\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFactors associated with worse survival in the Australian CF population include being F508del homozygous, receiving a lung transplant, lower lung function, and low BMI. In contrast to previous studies, an unexpected association between survival and earlier age of diagnosis was observed in our study. This effect could be explained by a potentially higher proportion of those with severe genotypes identified via NBS or presenting very early, the poorer quality of the diagnosis data captured in earlier years of the data registry, or a chance finding.\u003c/p\u003e \u003cp\u003eSex and pancreatic status were not found to be independently associated with the survival probability. This finding is different from the previously reported registry survival studies\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The study by MacKenzie et al\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e reported that sex, F508del status and increasing age at diagnosis were independently associated with survival in the US, and female sex has long been associated with worse survival in CF compared to males\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. It is possible that the gender gap in Australia is narrowing through improvements in treatment, diagnosis and lung function trajectory in females\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e 26\u003c/sup\u003e, although further studies are required to confirm this.\u003c/p\u003e \u003cp\u003ePublished data suggest that receiving a lung transplant is associated with earlier death\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. This finding was also observed in our study. Similarly, poorer lung function and lower BMI were also found to be associated with increased odds of mortality\u003csup\u003e6\u0026ndash;8,27\u0026minus;29\u003c/sup\u003e. The results of our study and previous studies\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e confirm the impact of lung function and nutritional status on the survival of people with CF, showing that severe and moderate pulmonary impairment and undernutrition have a major impact on survival. These findings justify the emphasis on interventions aimed at optimising pulmonary function and nutritional status in CF guidelines and standards of care\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eImproving median survival age in CF can be attributed to many different factors including NBS, nutritional interventions, proactive disease surveillance at both individual and population levels (including via the ACFDR), management of respiratory infections, access to novel therapies and improved standards of care\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. The impact of NBS on survival estimates would not be evident for several decades until babies screened at birth reached an age where they would be at risk for death. NBS programmes for CF were first implemented in the early 1970s in the Royal Gwent Hospital in UK\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. In Australia, NBS started in 1981and was progressively implemented across different states/jurisdictions becoming universal in 2001\u003csup\u003e35\u003c/sup\u003e, potentially explaining increased age of survival in recent years. Those identified by NBS have improved nutritional status and growth compared to people who are diagnosed by symptoms later in life\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, and some studies indicate improved pulmonary function\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. People identified at an early age benefit from early interventions to optimize nutrition, prevent and treat lung disease, and early monitoring for liver disease and other complications\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCFTR modulator therapies have the potential to reduce symptoms and increase survival for an increasing number of people with CF\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. In Australia, the first CFTR modulator (ivacaftor) was approved for use from December 2014, with lumacaftor/ivacaftor (Orkambi\u003csup\u003eR\u003c/sup\u003e) tezacaftor/ivacaftor (Symdeko\u003csup\u003eR\u003c/sup\u003e) and elexacaftor/tezacaftor/ivacaftor (Trikafta\u003csup\u003eR\u003c/sup\u003e) available for patients from October 2018, December 2019 and April 2022 respectively\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. It is too soon to see the impact of these novel therapies on survival although the estimated median age of survival of people with CF in Australia is expected to continue to improve. The Australian CF registry data is an essential tool to evaluate the impact of CFTR modulator therapies on future clinical outcomes including survival long-term\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThe strengths of our study include the large sample size, the longitudinal data within the ACFDR, the consistency of our results across multiple sub-groups and the unified approach to the analysis. There is a very high participation rate at the centre level as well as in the registry as since mid-2019 participating centres receive payment for data submission which results in a comprehensive national picture of the CF population in Australia\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In addition, this study is of the longest running cohort of patients diagnosed via NBS\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAs the ACFDR does not capture identifiable data, some death and transplant data could not be verified through national linkages. In addition, data pertaining to CF co-morbidities, such as CF-related diabetes and chronic infections with \u003cem\u003eP. aeruginosa\u003c/em\u003e were not analysed separately, and could influence survival outcomes. Certain data elements were incompletely recorded for the earlier years for this analysis (i.e. microbiology, CF-related diabetes and socioeconomic status) thus we were unable to account for these factors in our analyses. The differentiation of NBS diagnosis and clinical diagnosis based on meconium ileus /failure to thrive in first few weeks is not absolutely clear and could affect the quality of the diagnosis data. A database redesign conducted in 2018, and a new format of the registry will enable better quality and completeness of the registry records and greater accuracy of future analyses arising from the registry data\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe have demonstrated successive improvements in survival among people with CF in Australia over the last 15 years and identified factors influencing survival. Further research is needed to understand the complex interactions between biological and epidemiological factors not examined in this current study on the severity of disease and survival.\u003c/p\u003e \u003cp\u003eThe increase in survival and longevity requires an evolution in models of CF care towards prevention and management of age-related comorbidities such as diabetes, metabolic and cardiovascular disease, malignancies and osteoporosis alongside nutritional and respiratory care\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Increasing longevity must be coupled with increasing quality of life and the ability for people with CF to actively participate in a broad range of personal, community and work-based activities. Accordingly, these survival data presented highlight the need for future care models to incorporate a greater focus on the psychological, social, educational and occupational potential of people with CF as they live into old age.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the participating CF centres, data entry personnel, survey participants, patients and their families.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRR, SA, AE and SB conceived the study. RR, AE and FS performed data processing and statistical analysis. RR, FS and SA were responsible for the creation of the original draft of the manuscript that was revised and approved by all authors for important intellectual content. TD, KF, LK, SK, TK, PGM, SM, SM, AS, CW, NW and PW contributed to the development of the final manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on request and pending approval to the ACFDR Data Access and Research Publishing Committee.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Cystic Fibrosis Australia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSchmidt, B. Z., Haaf, J. B., Leal, T. \u0026amp; Noel, S. 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Journal of the Academy of Nutrition and Dietetics \u003cb\u003e121\u003c/b\u003e, 1591\u0026ndash;1636.e1593, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jand.2020.03.015\u003c/span\u003e\u003cspan address=\"10.1016/j.jand.2020.03.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cystic Fibrosis, Registry, Survival, Risk factors","lastPublishedDoi":"10.21203/rs.3.rs-2079022/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2079022/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSurvival statistics, estimated using data from national cystic fibrosis (CF) registries, inform the CF community and monitor disease progression. This study aimed to estimate survival among people with CF in Australia and to identify factors associated with survival. This population-based cohort study used prospectively collected data from 23 Australian CF centres participating in the Australian CF Data Registry (ACFDR) from 2005-2020. Period survival analysis was used to calculate median age of survival estimates for each 5-year window from 2005-2009 until 2016-2020. The overall median survival was estimated using the Kaplan-Meier method. Between 2005-2020 the ACFDR followed 4,601 people with CF, noting 516 (11.2%) deaths including 195 following lung transplantation. Out of the total sample, more than half (52.5%) were male and 395 (8.6%) had undergone lung transplantation. Two thirds of people with CF (66.1%) were diagnosed before six weeks of age or by newborn/prenatal screening. The overall median age of survival was estimated as 54.0 years (95% CI: 51.0–57.04). Estimated median survival increased from 48.9 years (95% CI: 44.7–53.5) for people with CF born in 2005-2009, to 56.3 years (95% CI: 51.2–60.4) for those born in 2016-2020. Factors independently associated with reduced survival include being F508del homozygous, receiving a lung transplant, having low FEV1pp and BMI.\u003cstrong\u003e \u003c/strong\u003eMedian survival estimates are increasing in CF in Australia. This likely reflects multiple factors, including newborn screening, improvement in diagnosis, refinements in CF management and centre-based multidisciplinary care.\u003c/p\u003e","manuscriptTitle":"Survival of People with Cystic Fibrosis in Australia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-09-23 18:25:03","doi":"10.21203/rs.3.rs-2079022/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-10-21T19:25:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-09-23T00:09:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1f08f6cf-987b-4864-8d5e-49928f9a976f","date":"2022-09-19T15:05:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-09-19T13:48:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-09-19T09:51:38+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-09-19T09:46:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-09-19T09:43:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2022-09-19T02:45:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b1bfee53-f6c2-4cc4-8faf-425395829358","owner":[],"postedDate":"September 23rd, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-11-14T17:29:28+00:00","versionOfRecord":[],"versionCreatedAt":"2022-09-23 18:25:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2079022","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2079022","identity":"rs-2079022","version":["v1"]},"buildId":"re_ckhLnmML6MCF96OHNJ","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}