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Background & objectives: Information on recent cancer statistics is important for planning, monitoring and evaluating cancer control activities. This article aims to provide an update on the cancer incidence estimates in India by sex, age groups and anatomical sites for the year 2022. Methods: The National Cancer Registry Programme Report 2020, reported the cancer incidence from 28 Population-Based Cancer Registries (PBCRs) for the years 2012-2016. This was used as the basis to calculate cancer estimates in India. Information pertaining to the population at risk was extracted from the Census of India (2001 and 2011) for the estimation of age-sex stratified population. PBCRs were categorised into the respective State and regions of the country to understand the epidemiology of cancer. The age-specific incidence rate for each specific anatomical site of cancer was applied to the estimated population to derive the number of cancer cases in India for 2022. Results: The estimated number of incident cases of cancer in India for the year 2022 was found to be 14,61,427 (crude rate:100.4 per 100,000). In India, one in nine people are likely to develop cancer in his/her lifetime. Lung and breast cancers were the leading sites of cancer in males and females, respectively. Among the childhood (0-14 yr) cancers, lymphoid leukaemia (boys: 29.2% and girls: 24.2%) was the leading site. The incidence of cancer cases is estimated to increase by 12.8 per cent in 2025 as compared to 2020. Interpretation & conclusions: The cancer incidence is continuing to increase in India. The new estimates will be helpful in planning cancer prevention and control activities through the intervention of early detection, risk reduction and management.

Background According to the International Rare Diseases Research Consortium (IRDiRC), a known rare disease (RD) should be diagnosable within a year. This study sought: firstly, to ascertain how long it takes to obtain the diagnosis of a RD in Spain, along with its associated time trend; and secondly, to identify and measure diagnostic delay (defined by the IRDiRC as any period exceeding a year) by reference to the characteristics of RDs and the persons affected by them. Methods Using data sourced from the Spanish Rare Diseases Patient Registry, we performed a descriptive analysis of the time elapsed between symptom onset and diagnosis of each RD, by sex, age and date of symptom onset, and type of RD. We analysed the time trend across the period 1960–2021 and possible change points, using a Joinpoint regression model and assuming a Poisson distribution. The multivariate analysis was completed with backward stepwise logistic regression. Results Detailed information was obtained on 3304 persons with RDs: 56.4% had experienced delay in diagnosis of their RDs, with the mean time taken being 6.18 years (median = 2; IQR 0.2–7.5). Both the percentage of patients with diagnostic delay and the average time to diagnosis underwent a significant reduction across the study period (p < 0.001). There was a higher percentage of diagnostic delays: in women (OR 1.25; 95% CI 1.07–1.45); in cases with symptom onset at age 30–44 years (OR 1.48; 95% CI 1.19–1.84): and when analysed by type of RD, in mental and behavioural disorders (OR 4.21; 95% CI 2.26–7.85), followed by RDs of the nervous system (OR 1.39; 95% CI 1.02–1.88). Conclusions This is the first study to quantify time to diagnosis of RDs in Spain, based on data from a national registry open to any RD. Since over half of all persons affected by RDs experience delay in diagnosis, new studies are needed to ascertain the factors associated with this delay and the implications this has on the lives of patients and their families.

Background Clinical complexity, as the interaction between ageing, frailty, multimorbidity and polypharmacy, is an increasing concern in patients with AF. There remains uncertainty regarding how combinations of comorbidities influence management and prognosis of patients with atrial fibrillation (AF). We aimed to identify phenotypes of AF patients according to comorbidities and to assess associations between comorbidity patterns, drug use and risk of major outcomes. Methods From the prospective GLORIA-AF Registry, we performed a latent class analysis based on 18 diseases, encompassing cardiovascular, metabolic, respiratory and other conditions; we then analysed the association between phenotypes of patients and (i) treatments received and (ii) the risk of major outcomes. Primary outcome was the composite of all-cause death and major adverse cardiovascular events (MACE). Secondary exploratory outcomes were also analysed. Results 32,560 AF patients (mean age 70.0 ± 10.5 years, 45.4% females) were included. We identified 6 phenotypes: (i) low complexity (39.2% of patients); (ii) cardiovascular (CV) risk factors (28.2%); (iii) atherosclerotic (10.2%); (iv) thromboembolic (8.1%); (v) cardiometabolic (7.6%) and (vi) high complexity (6.6%). Higher use of oral anticoagulants was found in more complex groups, with highest magnitude observed for the cardiometabolic and high complexity phenotypes (odds ratio and 95% confidence interval CI): 1.76 [1.49–2.09] and 1.57 [1.35–1.81], respectively); similar results were observed for beta-blockers and verapamil or diltiazem. We found higher risk of the primary outcome in all phenotypes, except the CV risk factor one, with highest risk observed for the cardiometabolic and high complexity groups (hazard ratio and 95%CI: 1.37 [1.13–1.67] and 1.47 [1.24–1.75], respectively). Conclusions Comorbidities influence management and long-term prognosis of patients with AF. Patients with complex phenotypes may require comprehensive and holistic approaches to improve their prognosis.

Background China has made tremendous progresses in serving the needs of its people living with rare diseases in the past decade, especially over the last 5 years. The Chinese government’s systematic approach included a series of coordinated initiatives, amongst these are: forming the Rare Disease Expert Committee (2016), funding the “Rare Diseases Cohort Study” (2016–2020), and publishing its first “Rare Disease Catalog” (2018). Herein, we present the National Rare Diseases Registry System (NRDRS)—China’s first national rare diseases registry, and the analysis of cases registered in the first 5 years ending Dec 31, 2020. Results The total 62,590 cases covered 166 disease/disease types, forming 183 disease cohorts. The data from nearly 22% of them (13,947 cases) is also linked to valuable biological samples. The average age of definitive diagnosis was 30.88 years; 36.07% of cases were under 18 years of age. Regional distribution analysis showed 60% of cases were from the more developed, wealthier East and North China, suggesting the local availability of quality care and patients’ financial status were key access factors. Finally, 82.04% of cases were registered from the five clinical departments: Neurology, Endocrine, Hematology, Cardiovascular, and Nephrology, suggesting that either these are most affected by rare diseases, or that there were disease non-specific ascertainment factors. Conclusions The preliminary analysis of the first 5-year’s data provides unique and valuable insight on rare disease distribution in China, and higlights the directions for enhancing equity, scale and utility.

Background The EURO-NMD Registry collects data from all neuromuscular patients seen at EURO-NMD's expert centres. In-kind contributions from three patient organisations have ensured that the registry is patient-centred, meaningful, and impactful. The consenting process covers other uses, such as research, cohort finding and trial readiness. Results The registry has three-layered datasets, with European Commission-mandated data elements (EU-CDEs), a set of cross-neuromuscular data elements (NMD-CDEs) and a dataset of disease-specific data elements that function modularly (DS-DEs). The registry captures clinical, neuromuscular imaging, neuromuscular histopathology, biological and genetic data and patient-reported outcomes in a computer-interpretable format using selected ontologies and classifications. The EURO-NMD registry is connected to the EURO-NMD Registry Hub through an interoperability layer. The Hub provides an entry point to other neuromuscular registries that follow the FAIR data stewardship principles and enable GDPR-compliant information exchange. Four national or disease-specific patient registries are interoperable with the EURO-NMD Registry, allowing for federated analysis across these different resources. Conclusions Collectively, the Registry Hub brings together data that are currently siloed and fragmented to improve healthcare and advance research for neuromuscular diseases.

Background Patient data registries that are FAIR—Findable, Accessible, Interoperable, and Reusable for humans and computers—facilitate research across multiple resources. This is particularly relevant to rare diseases, where data often are scarce and scattered. Specific research questions can be asked across FAIR rare disease registries and other FAIR resources without physically combining the data. Further, FAIR implies well-defined, transparent access conditions, which supports making sensitive data as open as possible and as closed as necessary. Results We successfully developed and implemented a process of making a rare disease registry for vascular anomalies FAIR from its conception—de novo. Here, we describe the five phases of this process in detail: (i) pre-FAIRification, (ii) facilitating FAIRification, (iii) data collection, (iv) generating FAIR data in real-time, and (v) using FAIR data. This includes the creation of an electronic case report form and a semantic data model of the elements to be collected (in this case: the “Set of Common Data Elements for Rare Disease Registration” released by the European Commission), and the technical implementation of automatic, real-time data FAIRification in an Electronic Data Capture system. Further, we describe how we contribute to the four facets of FAIR, and how our FAIRification process can be reused by other registries. Conclusions In conclusion, a detailed de novo FAIRification process of a registry for vascular anomalies is described. To a large extent, the process may be reused by other rare disease registries, and we envision this work to be a substantial contribution to an ecosystem of FAIR rare disease resources.

Background The Italian Clinical network for FSHD (ICNF) has established the Italian National Registry for FSHD (INRF), collecting data from patients affected by Facioscapulohumeral dystrophy (FSHD) and their relatives. The INRF has gathered data from molecular analysis, clinical evaluation, anamnestic information, and family history from more than 3500 participants. Methods A data management framework, called Mediator Environment for Multiple Information Sources (MOMIS) FSHD Web Platform, has been developed to provide charts, maps and search tools customized for specific needs. Patients’ samples and their clinical information derives from the Italian Clinical network for FSHD (ICNF), a consortium consisting of fourteen neuromuscular clinics distributed across Italy. The tools used to collect, integrate, and visualize clinical, molecular and natural history information about patients affected by FSHD and their relatives are described. Results The INRF collected the molecular data regarding FSHD diagnosis conducted on 7197 subjects and identified 3362 individuals carrying a D4Z4 Reduced Allele (DRA): 1634 were unrelated index cases. In 1032 cases the molecular testing has been extended to 3747 relatives, 1728 carrying a DRA. Since 2009 molecular analysis has been accompanied by clinical evaluation based standardized evaluation protocols. In the period 2009–2020, 3577 clinical forms have been collected, 2059 follow the Comprehensive Clinical Evaluation form (CCEF). The integration of standardized clinical information and molecular data has made possible to demonstrate the wide phenotypic variability of FSHD. The MOMIS (Mediator Environment for Multiple Information Sources) data integration framework allowed performing genotype–phenotype correlation studies, and generated information of medical importance either for clinical practice or genetic counseling. Conclusion The platform implemented for the FSHD Registry data collection based on OpenClinica meets the requirement to integrate patient/disease information, as well as the need to adapt dynamically to security and privacy concerns. Our results indicate that the quality of data collection in a multi-integrated approach is fundamental for clinical and epidemiological research in a rare disease and may have great value in allowing us to redefine diagnostic criteria and disease markers for FSHD. By extending the use of the MOMIS data integration framework to other countries and the longitudinal systematic collection of standardized clinical data will facilitate the understanding of disease natural history and offer valuable inputs towards trial readiness. This approach is of high significance to FSHD medical community and also to rare disease research in general.

Background X-linked hypophosphatemia (XLH) is a rare, hereditary, progressive, renal phosphate-wasting disorder characterized by a pathological increase in FGF23 concentration and activity. Due to its rarity, diagnosis may be delayed, which can adversely affect outcomes. As a chronic disease resulting in progressive accumulation of musculoskeletal manifestations, it is important to understand the natural history of XLH over the patient’s lifetime and the impact of drug treatments and other interventions. This multicentre, international patient registry (International XLH Registry) was established to address the paucity of these data. Here we present the findings of the first interim analysis of the registry. Results The International XLH Registry was initiated in August 2017 and includes participants of all ages diagnosed with XLH, regardless of their treatment and management. At the database lock for this first interim analysis (29 March 2021), 579 participants had entered the registry before 30 November 2020 and are included in the analysis (360 children [62.2%], 217 adults [37.5%] and 2 whose ages were not recorded [0.3%]; 64.2% were female). Family history data were available for 319/345 (92.5%) children and 145/187 (77.5%) adults; 62.1% had biological parents affected by XLH. Genetic testing data were available for 341 (94.7%) children and 203 (93.5%) adults; 370/546 (67.8%) had genetic test results; 331/370 (89.5%) had a confirmed PHEX mutation. A notably longer time to diagnosis was observed in adults ≥ 50 years of age (mean [median] duration 9.4 [2.0] years) versus all adults (3.7 [0.1] years) and children (1.0 [0.2] years). Participants presented with normal weight, shorter length or height and elevated body mass index (approximately − 2 and + 2 Z-scores, respectively) versus the general population. Clinical histories were collected for 349 participants (239 children and 110 adults). General data trends for prevalence of bone, dental, renal and joint conditions in all participants were aligned with expectations for a typical population of people with XLH. Conclusion The data collected within the International XLH Registry, the largest XLH registry to date, provide substantial information to address the paucity of natural history data, starting with demographic, family history, genetic testing, diagnosis, auxology and baseline data on clinical presentation.

Background Rare diseases (RDs) affect approximately 8% of all people or > 400 million people globally. The Australian Government’s National Strategic Action Plan for Rare Diseases has identified the need for a national, coordinated, and systematic approach to the collection and use of RD data, including registries. Rare disease registries (RDRs) are established for epidemiological, quality improvement and research purposes, and they are critical infrastructure for clinical trials. The aim of this scoping review was to review literature on the current state of RDRs in Australia; to describe how they are funded; what data they collect; and their impact on patient outcomes. Methods We conducted a literature search on MEDLINE, EMBASE, CINAHL and PsychINFO databases, in addition to Google Scholar and grey literature. Dissertations, government reports, randomised control trials, conference proceedings, conference posters and meeting abstracts were also included. Articles were excluded if they did not discuss RDs or if they were written in a language other than English. Studies were assessed on demographic and clinical patient characteristics, procedure or treatment type and health-related quality of life captured by RDRs or databases that have been established to date. Results Seventy-four RDRs were identified; 19 were global registries in which Australians participated, 24 were Australian-only registries, 10 were Australia and New Zealand based, and five were Australian jurisdiction-based registries. Sixteen “umbrella” registries collected data on several different conditions, which included some RDs, and thirteen RDRs stored rare cancer-specific information. Most RDRs and databases captured similar types of information related to patient characteristics, comorbidities and other clinical features, procedure or treatment type and health-related quality of life measures. We found considerable heterogeneity among existing RDRs in Australia, especially with regards to data collection, scope and quality of registries, suggesting a national coordinated approach to RDRs is required. Conclusion This scoping review highlights the current state of Australian RDRs, identifying several important gaps and opportunities for improvement through national coordination and increased investment.

Background Myasthenia gravis (MG) is a rare autoimmune disorder. Several new treatment concepts have emerged in recent years, but access to these treatments varies due to differing national reimbursement regulations, leading to disparities across Europe. This highlights the need for high-quality data collection by stakeholders to establish MG registries. A European MG registry could help bridge the treatment access gap across different countries, offering critical data to support regulatory decisions, foster international collaborations, and enhance clinical and epidemiological research. Several national MG registries already exist or are in development. To avoid duplication and ensure harmonization in data collection, a modified Delphi procedure was implemented to identify essential data elements for inclusion in national registries. Results Following a literature review, consultations with patient associations and pharmaceutical companies, and input from multiple European MG experts, 100 data elements were identified. Of these, 62 reached consensus for inclusion and classification, while only 1 item was agreed for exclusion. 30 items failed to reach the ≥ 80% agreement threshold and were excluded. Among the 62 accepted items, 21 were classified as mandatory data elements, 32 optional, and 9 items pertained to the informed consent form. Conclusions Through a modified Delphi procedure, consensus was successfully achieved. This consensus-based approach represents a crucial step toward harmonizing MG registries across Europe. The resulting dataset will facilitate the sharing of knowledge and enhance European collaborations. Furthermore, the harmonized data may assist in regulatory or reimbursement decisions regarding novel therapies, as well as address treatment access disparities between European countries.