Overall mortality among patients with systemic autoinflammatory diseases in France

Overall mortality among patients with systemic autoinflammatory diseases in France | 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 Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Overall mortality among patients with systemic autoinflammatory diseases in France Julie Teillet, Clémence Deshuille, Léa Savey, Véronique Hentgen, and 19 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8609629/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Introduction Systemic autoinflammatory diseases (SAIDs) are rare disorders of the innate immune system for which limited data on overall mortality or life expectancy. The aim of this study was to assess overall mortality among patients with familial Mediterranean fever (FMF), cryopyrin-associated periodic syndrome (CAPS), TNFR-associated periodic syndrome (TRAPS), and mevalonate kinase deficiency (MKD) in France. Methods Patients with a confirmed diagnosis of FMF, CAPS, TRAPS, or MKD were identified through the French National Rare Disease Registry (BNDMR). Data were contributed by rare disease reference centres within the FAI2R network, following approval by the BNDMR institutional review board. Mortality data were obtained from the BNDMR and supplemented with individual death records from the French National Institute of Statistics and Economic Studies (INSEE). Mortality between January 2010 and December 31 2024 was analysed using age- and sex-specific mortality rates from the Human Mortality Database. Comparative mortality indices (CMIs) were calculated. Results A total of 2010 patients were included between 2010 and 2024: 1647 with FMF, 199 with CAPS, 100 with TRAPS, and 64 with MKD. Estimated prevalence in 2024 was 23.6 per million (95% CI [22.5–24.8]) for FMF, 2.8 per million (95% CI [2.5–3.3]) for CAPS, 1.4 per million (95% CI [1.2–1.7]) for TRAPS, and 0.9 per million (95% CI [0.7–1.2]) for MKD. A total of 36 deaths were observed between 2010 and 2024: 27 among FMF patients, 4 among CAPS patients, 3 among TRAPS patients, and 2 among MKD patients. Over the study period, the comparative mortality index (CMI) was 425 (95% CI [385.55–467.39]), indicating a mortality rate 4.3 times higher than expected compared with the French general population. The lowest CMI was observed in the FMF cohort (385), whereas the highest CMI was observed in the MKD cohort (738). Conclusion These findings highlight a significant public health concern, particularly for the rarest and most difficult-to-treat disease, MKD, but also for FMF, which is the most prevalent SAID. Our results support the need for in-depth analyses of the causes of death to better inform preventive and therapeutic strategies. Mortality Autoinflammatory diseases Familial Mediterranean fever mevalonate kinase deficiency cryopyrin-associated periodic syndrome TNFR1-associated periodic syndrome Figures Figure 1 INTRODUCTION Systemic autoinflammatory diseases (SAIDs) are a group of disorders linked to dysfunctional innate immunity. They have been characterized over the past 30 years, with familial Mediterranean fever (FMF) being the most common and longest-standing entity [1–3]. The canonical SAIDs are monogenic disorders, namely FMF (familial Mediterranean fever), mevalonate kinase deficiency (MKD), TNF receptor 1-associated periodic syndrome (TRAPS), and cryopyrin-associated periodic syndrome (CAPS), and are characterized by excessive secretion of interleukin-1 and interleukin-18 [4–7]. These diseases typically present at a young age, sometimes as early as the first year of life. Their lifelong course substantially impairs patients’ quality of life and may lead to organ damage, including central nervous system involvement with cognitive and neurosensory impairment in CAPS, and renal involvement due to AA amyloidosis across all entities [9–11]. To date, few data are available regarding overall mortality in these patient populations. Lane et al. [12] described a cohort of 24 patients with SAIDs complicated by AA amyloidosis (TRAPS, CAPS, MKD, and FMF) and reported 11 deaths, with a mean age at death of 69 years and a mean survival of 19 years following the diagnosis of amyloidosis. Most available studies have focused on mortality within specific subgroups of SAID patients, often related to particular causes such as AA amyloidosis or SARS-CoV-2 infection [13–21]. A study based on the Israeli military service registry comparing adolescents with FMF to matched controls showed excess mortality among young male patients, mainly related to AA amyloidosis before the age of 40. This excess mortality was subsequently confirmed in both men and women through comparisons with other disease-related registries, including kidney transplant registries, demonstrating increased all-cause mortality in FMF [22]. However, to date, no studies have compared mortality in SAID patients with that of the general population matched for age, limiting accurate assessment of their public health impact. A comprehensive evaluation of mortality in patients with SAIDs is therefore essential to inform therapeutic strategies, particularly to justify the use of costly, highly targeted, or more burdensome treatments such as hematopoietic stem cell transplantation or gene therapy [23–26]. The aim of the present study was to estimate prevalence and comparative mortality indices in patients with FMF, CAPS, TRAPS, and MKD, and to compare these estimates with mortality in the general population in France. PATIENTS AND METHODS Patient selection Patients with a diagnosis of FMF, CAPS, TRAPS, or MKD were included in the French National Rare Disease Registry (BNDMR). Included patients had at least one follow-up visit and a diagnosis registered as confirmed by their physician, and did not object to the reuse of their data for research purposes. Patients who had objected to the reuse of their data for research purposes were excluded. Vital status was enriched using the national public death registry maintained by the French National Institute of Statistics and Economic Studies (INSEE), which provides civil status information for each deceased individual. Medical causes of death were not available. Data for this study were collected between January 1, 2010, and December 31, 2024. Statistical analysis Prevalence in 2024 was estimated by dividing the number of patients alive in 2024 for each disease by the size of the French population in 2024, according to INSEE data. Confidence intervals were calculated using a chi-squared test. Patient characteristics were described using frequencies for sex and medians for age at inclusion and follow-up duration. Comparisons between diseases were performed using a chi-squared test for sex and a Kruskal–Wallis test for age at inclusion and follow-up duration. Mortality data from the BNDMR were consolidated using INSEE mortality data. For mortality analyses, age- and sex-specific mortality tables from the Human Mortality Database were used. As mortality data were available only up to 2023 at the time of analysis, and given the absence of major epidemiological events and the typically small year-to-year variations, 2023 mortality rates were applied to 2024 to allow analyses over the 2010–2024 period, in line with the other analyses. The expected number of deaths was calculated by determining the number of patients by sex, age group, and year, and multiplying these counts by the corresponding age-specific mortality rates from the Human Mortality Database. The comparative mortality index (CMI) was defined as the ratio of observed to expected deaths, multiplied by 100. Confidence intervals were calculated assuming a Poisson distribution with a 95% confidence level. All statistical analyses were performed using R software (version 4.1.2), with a significance level set at 0.05. RESULTS Study population After excluding patients whose diagnosis was uncertain and those who refused data reuse, a total of 2010 patients were included between 2010 and 2024, of whom 1647 were affected by FMF, 199 by CAPS, 100 by TRAPS, and 64 by MKD (Fig. 1 ). The respective prevalence of these SAIDs in 2024 was estimated at 23.6 per million for FMF, 2.8 per million for CAPS, 1.4 per million for TRAPS, and 0.9 per million for MKD. Population characteristics Women represented 52% (853/1647), 59% (117/199), 61% (61/100), and 47% (30/64) of the FMF, CAPS, TRAPS, and MKD cohorts, respectively (Table 1 ). No significant difference in sex ratio was observed across disease cohorts (p = 0.07), whereas a significant difference was observed in follow-up duration (p = 0.01). Table 1 BNDMR study population characteristics Variables Total N = 2010 FMF N = 1647 CAPS N = 199 TRAPS N = 100 MKD N = 64 P **value= Sex, n (%) Female Male 1061(52.8%) 949(47.2%) 853 (51.8%) 794(48.2%) 117 (58.8%) 82 (41.2%) 61(61%) 39 (39%) 30 (46.9%) 34(53.1%) 0.07 Age * of living patients (years) , Median [Q1-Q3] Mean +/- SD 1974 28 [16–44] 33.4+/-18.9 1620 27 [16–42] 30.9+/-18.3 195 30 [17–52] 34.3+/-22 97 40 [21–57] 40+/-20.7 62 16 [10–30] 21.4+/-15.2 < 0.001 Number of deaths Age at death (years (n%) Median (Q1-Q3) Mean +/-ET 36 (1.8%) 65 (50–76) 59.8 +/-2.6 27 (1.6%) 69 (58–77) 63.6 +/-20.9 4 (2%) / / 3 (3%) / / 2 (3%) / / 0.14 Age at study inclusion (years), n Median [Q1-Q3] Mean +/- SD 2010 23 [10–41] 27+/-20.1 1647 23 [10–39] 26.8+/-19.5 199 23 [8–48] 28.8+/-23.2 100 36[15–50 35.6+/-21.2 64 7 [3–21] 14.9+/-16.5 0.001 Patients follow up time (years) Median [Q1-Q3] Mean +/- SD 2010 4 [2–6] 4.9+/-4.1 1647 4 [2–6] 4.7+/3.8 199 4 [2–8] 5.9+/-5.5 100 4 [3–6] 5 +/-3.8 64 5 [3–9] 6.8+/-5.4 0.01 *Calculated relative to 31/12/2024 **Pearson's Chi-squared Test for qualitative variables, Kruskal-Wallis Test for quantitative variables Follow-up period = date of death or 31/12/2024 - first date of activity (inclusion in the BNDMR) The median follow-up duration was 5 years (3–9; SD 6.8 ± 5.4) in the MKD cohort and 4 years in the FMF (2–6; 4.7 ± 3.8), CAPS (2–8; 5.9 ± 5.5), and TRAPS (3–6; 5.0 ± 3.8) cohorts (Table 1 ). The median age at inclusion in rare disease centres was 23 years in the FMF and CAPS cohorts, 36 years in the TRAPS cohort, and 7 years in the MKD cohort (p < 0.001) (Table 1 ). Mortality results During the 2010–2024 period, 27 deaths were reported in the FMF cohort, 4 in the CAPS cohort, 3 in the TRAPS cohort, and 2 in the MKD cohort (Table 1 ). The comparative mortality index (CMI) for each cohort was 385, 522, 730, and 739, respectively. The number of observed deaths exceeded the expected number of deaths based on age- and sex-specific mortality rates from the Human Mortality Database for a population of similar age and sex followed over the same period, with 7.02, 0.766, 0.411, and 0.271 expected deaths in the FMF, CAPS, TRAPS, and MKD cohorts, respectively. Analysis of death seasonality showed no significant differences (p = 0.32; data not shown). The median age at death was 65 years overall and 69 years in the FMF cohort. DISCUSSION Understanding mortality in rare diseases helps to better assess their overall severity and the need for exceptional or intensified treatments. To our knowledge, this study is the first to assess overall mortality across the four historical SAIDs in France and to allow comparisons between them. The use of the BNDMR network, which brings together the most specialized centres for rare diseases, made it possible to include a sufficient number of patients to perform statistical analyses, although the sample size and duration of follow-up remain limited. Comparison with mortality data from the Human Mortality Database further strengthens the robustness of the analyses. However, this approach also has inherent limitations and is susceptible to several sources of bias. In particular, underreporting of diseases—especially during the early years of BAMARA deployment before 2018—and potential misclassification by reporting physicians cannot be excluded. The mortality rates observed in the BNDMR may therefore have been underestimated because of incomplete reporting, but they may also have been overestimated, particularly in the FMF cohort, as patients with milder phenotypes may be managed by general practitioners or in less specialized centres that do not fully report to the registry. Additional limitations include patient refusal to allow data reuse, potential loss to follow-up, limited follow-up duration, and the absence of information on causes of death, which precluded assessment of whether deaths were directly related to SAIDs or to associated comorbidities. Our results showed an overall excess mortality in all four cohorts compared with the general population. While the burden of these diseases on daily life is well recognized, deaths have also been reported in several cohorts, particularly among patients with FMF, CAPS, TRAPS, and MKD complicated by AA amyloidosis, including those who underwent kidney transplantation [11–21]. In our study, no clear impact of the COVID-19 pandemic on mortality was observed, with death rates remaining stable between 2020 and 2022. Nevertheless, deaths—especially among FMF patients—were reported during the pandemic period, most often in individuals with comorbidities known to increase the risk of COVID-19-related mortality [15–21]. Our study did not demonstrate a reduction in mortality associated with the introduction of biologic therapies since 2009. This finding should be interpreted with caution, as more than half of the cohort was included after 2018, and underreporting of both cases and deaths is likely to have occurred before that date. Comparative analysis across the four cohorts showed that mortality was highest in the MKD cohort, which also included the youngest patients, and, to a lesser extent, in the CAPS cohort. MKD differs from other SAIDs in that it can be associated with rapidly fatal complications such as severe infections, liver failure, or macrophage activation syndrome. The available literature on mortality in MKD remains limited. An international MKD registry reported 3 deaths among 103 patients (due to suicide, cerebral hemorrhage, and pneumococcal infection), while a Franco-Belgian study reported 3 early deaths among 50 patients due to multiorgan failure with infection [27]. These studies are relatively old, incomplete, and predate the widespread use of biologic therapies. In addition, 4 of 11 patients with mevalonic aciduria died during follow-up in a separate cohort [11]. High mortality rates (41%) have also been reported among 86 patients with CAPS-related AA amyloidosis across all phenotypes in a French cohort enriched by a literature review [28]. Similarly, among 30 patients with CINCA syndrome, 8 deaths were reported, due to bacterial infection, hematologic disease, trauma, gangrene of the extremities, or amyloidosis [8]. Median ages at death were not provided in these studies. A French study also reported 5 deaths among 36 patients with TRAPS complicated by AA amyloidosis over a 23-month follow-up period [13]. Although lower than in other cohorts, the excess mortality observed in the FMF cohort is concerning, as FMF is by far the most prevalent SAID. In France, FMF-related deaths have predominantly been associated with secondary AA amyloidosis and end-stage renal disease [14]. In our study, FMF was associated with a reduction in life expectancy, particularly from the age of 50 years onwards. Mortality associated with FMF outside France remains incompletely understood. A Turkish study of 630 patients with FMF reported a mortality rate of 2.3% and an overall survival rate not significantly different from that of the age- and sex-matched general population; amyloidosis was the only factor independently associated with mortality in multivariate analyses [29]. In contrast, a large population-based cohort study from Israel involving 1,225 individuals with FMF showed significantly higher mortality compared with matched controls (p = 0.002), with mortality rates of 8.73/10⁴ and 4.32/10⁴, respectively [22]. Mortality was increased in both sexes, particularly among men, and was largely attributable to renal amyloidosis. Deaths were not associated with an increased risk of cancer. Another Israeli registry-based study conducted in 2019 confirmed excess mortality in FMF, with 345 deaths among 7,670 FMF patients compared with 271 deaths among matched controls (p = 0.002); amyloidosis remained the only significant predictor of mortality after adjustment for age and cardiovascular risk factors [30]. Several studies have examined the protective effect of colchicine, particularly with respect to cardiovascular mortality, which is a leading cause of death in FMF, often related to amyloidosis. For example, Langevitz et al. found no difference in cardiac mortality between colchicine-treated FMF patients and healthy controls [31]. Overall, mortality in FMF appears closely linked to associated comorbidities, including cardiovascular, hepatic, and renal disease, with secondary renal amyloidosis remaining the most consistently identified determinant of mortality across studies [17,22,32]. CONCLUSION Compared with the general population in France, patients with FMF, CAPS, TRAPS, and MKD appear to have an increased risk of mortality across all age groups. Our data indicate that MKD is associated with the highest mortality rate among the four diseases studied. An in-depth analysis of the causes of death in patients with SAIDs would help to better tailor preventive measures, treatment strategies, and long-term follow-up. Declarations ACKNOWLEDGEMENTS The authors are grateful to the members of the French Rare Diseases Expert Network (FAI2R) who are collecting the data. They are also grateful to the French Rare Diseases Data Registry (BNDMR) operational team, operating from Assistance Publique – Hôpitaux de Paris (AP-HP). This work was supported as part of the national plan for rare diseases by the Directorate of Health Care Supply of the French Ministry of Health (DGOS), with no role in the research process or conclusions drawn. FUNDING The BNDMR operational team is funded by the French Ministry of Health as part of its public interest policy. AUTHORS CONTRIBUTIONS Study design: CD, ASJ, JT, and IKP. Data acquisition: IKP, SGL, and the FAI2R network. Statistical analysis: ASJ and CD. Data analysis and interpretation: all authors. Manuscript drafting and editing: JT and IKP. Approval of the final manuscript: all authors. ETHICS DECLARATION The CNIL authorized the creation of the BNDMR data warehouse in September 2019 (decision no. 2019-113 amended on September 28, 2023: decision no. 2023-098). According to the French ethical regulations, all patients received an information sheet about the BNDMR, and only data from patients who did not object to the processing of their data were included in the analyses. DATA SHARING STATEMENT In accordance with French regulations, access to the data supporting the findings of this study may be granted upon approval by the BNDMR Institutional Review Board. 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Langevitz P, Livneh A, Neumann L, Buskila D, Amolsky D, Pras M. Prevalence of ischemic heart disease in patients with familial Mediterranean fever, Isr Med Assoc J. 2001;3(1):9–12. Delplanque M, Amiot X, Wendum D, Rodrigues F, Aknouche Z, Bourguiba R, et al Liver Disease Complicating Familial Mediterranean Fever: A Study on 66 Patients Out of 533 Adult From the JIR Cohort. Liver Int. 2025;45(2):e16232. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 25 Feb, 2026 Reviewers agreed at journal 10 Feb, 2026 Reviewers invited by journal 10 Feb, 2026 Editor invited by journal 10 Feb, 2026 Editor assigned by journal 21 Jan, 2026 First submitted to journal 20 Jan, 2026 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 Our Team In Review Editorial Policies Advisory Board 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-8609629","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588869244,"identity":"c5d4867e-3717-4c49-a6d2-08dd385b4d0f","order_by":0,"name":"Julie Teillet","email":"","orcid":"","institution":"APHP: Assistance Publique - Hopitaux de Paris","correspondingAuthor":false,"prefix":"","firstName":"Julie","middleName":"","lastName":"Teillet","suffix":""},{"id":588869245,"identity":"456fd61d-c659-43d2-8fe3-398fb042bbe6","order_by":1,"name":"Clémence Deshuille","email":"","orcid":"","institution":"AP-HP: Assistance Publique - Hopitaux de Paris","correspondingAuthor":false,"prefix":"","firstName":"Clémence","middleName":"","lastName":"Deshuille","suffix":""},{"id":588869246,"identity":"f9f73370-c912-479e-a6bd-4535e129daab","order_by":2,"name":"Léa Savey","email":"","orcid":"","institution":"AP-HP: Assistance Publique - 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Hopitaux de Paris","correspondingAuthor":false,"prefix":"","firstName":"Ulrich","middleName":"","lastName":"Meinzer","suffix":""},{"id":588869251,"identity":"35bf3439-160a-4f78-94b8-68e25bab25a5","order_by":7,"name":"Eric Hachulla","email":"","orcid":"","institution":"CHRU de Lille: Centre Hospitalier Universitaire de Lille","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"","lastName":"Hachulla","suffix":""},{"id":588869252,"identity":"43ae7426-a57b-48ac-8bad-76a248e1abcc","order_by":8,"name":"Alexandre Belot","email":"","orcid":"","institution":"HCL: Hospices Civils de Lyon","correspondingAuthor":false,"prefix":"","firstName":"Alexandre","middleName":"","lastName":"Belot","suffix":""},{"id":588869253,"identity":"04ddfb1d-a5a4-4014-b934-f65eda8548d8","order_by":9,"name":"Karine Retornaz","email":"","orcid":"","institution":"Public Assistance Hospitals Marseille: Assistance Publique Hopitaux de Marseille","correspondingAuthor":false,"prefix":"","firstName":"Karine","middleName":"","lastName":"Retornaz","suffix":""},{"id":588869254,"identity":"ba7b61c1-0363-40cb-af38-dd5fd51b1e4f","order_by":10,"name":"Eric Jeziorski","email":"","orcid":"","institution":"CHU de Montpellier: Centre Hospitalier Universitaire de Montpellier","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"","lastName":"Jeziorski","suffix":""},{"id":588869255,"identity":"e430e364-7a86-4a87-b845-17dc0512d7fb","order_by":11,"name":"Vincent Jachiet","email":"","orcid":"","institution":"Assistance Publique - Hopitaux de Paris","correspondingAuthor":false,"prefix":"","firstName":"Vincent","middleName":"","lastName":"Jachiet","suffix":""},{"id":588869256,"identity":"61cd9e01-b908-4d49-ab07-f63ee7dbf6cb","order_by":12,"name":"Arsène Mekinian","email":"","orcid":"","institution":"Assistance Publique - Hopitaux de Paris","correspondingAuthor":false,"prefix":"","firstName":"Arsène","middleName":"","lastName":"Mekinian","suffix":""},{"id":588869257,"identity":"1b3c5f09-1337-4c6f-9cca-27f90fd17a53","order_by":13,"name":"Gilles Kaplanski","email":"","orcid":"","institution":"AP-HM: Assistance Publique Hopitaux de Marseille","correspondingAuthor":false,"prefix":"","firstName":"Gilles","middleName":"","lastName":"Kaplanski","suffix":""},{"id":588869258,"identity":"60f4f12f-089e-4b6e-b012-7f8d98610e59","order_by":14,"name":"Marie-Élise Truchetet","email":"","orcid":"","institution":"CHU Bordeaux GH Pellegrin: Centre Hospitalier Universitaire de Bordeaux Groupe hospitalier Pellegrin","correspondingAuthor":false,"prefix":"","firstName":"Marie-Élise","middleName":"","lastName":"Truchetet","suffix":""},{"id":588869259,"identity":"3d048a79-df3e-4470-8e18-09b5cb00728a","order_by":15,"name":"David Saadoun","email":"","orcid":"","institution":"Assistance Publique Hopitaux de Paris: Assistance Publique - Hopitaux de Paris","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Saadoun","suffix":""},{"id":588869260,"identity":"01dc65fb-5173-4fc8-ac79-56e470a622d4","order_by":16,"name":"Achille Aouba","email":"","orcid":"","institution":"CHU Caen: Centre Hospitalier Universitaire de Caen","correspondingAuthor":false,"prefix":"","firstName":"Achille","middleName":"","lastName":"Aouba","suffix":""},{"id":588869261,"identity":"11353de6-8d10-4a83-a2f9-d9afd51fc50f","order_by":17,"name":"Christine Pajot","email":"","orcid":"","institution":"CHU Toulouse: Centre Hospitalier Universitaire de Toulouse","correspondingAuthor":false,"prefix":"","firstName":"Christine","middleName":"","lastName":"Pajot","suffix":""},{"id":588869262,"identity":"e385424f-cc53-49af-b847-45cd43965a78","order_by":18,"name":"Thierry Martin","email":"","orcid":"","institution":"CHU Strasbourg: Les Hopitaux Universitaires de Strasbourg","correspondingAuthor":false,"prefix":"","firstName":"Thierry","middleName":"","lastName":"Martin","suffix":""},{"id":588869263,"identity":"795c8597-6356-45de-9136-3efdc3b6a9e6","order_by":19,"name":"Anne-Sophie Jannot","email":"","orcid":"","institution":"Assistance Publique - Hopitaux de Paris","correspondingAuthor":false,"prefix":"","firstName":"Anne-Sophie","middleName":"","lastName":"Jannot","suffix":""},{"id":588869264,"identity":"917c7fe6-8d6f-4920-9c11-bf796b326b38","order_by":20,"name":"FAI2R NETWORK","email":"","orcid":"","institution":"CHU de Bordeaux: Centre Hospitalier Universitaire de Bordeaux","correspondingAuthor":false,"prefix":"","firstName":"FAI2R","middleName":"","lastName":"NETWORK","suffix":""},{"id":588869265,"identity":"0a3ab946-6701-4c45-acf7-da61a49edb40","order_by":21,"name":"Sophie Georgin-Lavialle","email":"","orcid":"","institution":"Assistance Publique - Hopitaux de Paris","correspondingAuthor":false,"prefix":"","firstName":"Sophie","middleName":"","lastName":"Georgin-Lavialle","suffix":""},{"id":588869266,"identity":"2f66ea77-18a7-400b-9461-741c4c108ed9","order_by":22,"name":"Isabelle Koné-Paut","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIie3PsUrDQBzH8V8pnMs/zXpy0LzCBSEKKn2VlEJcOtjJbmbKFHRt3iIgiGPg4Lr4BgYMFDJXBClYxJihrdBER5H7chx/Dj7cHWAy/cFYvS5PANqcdTN0QuAgbCOS7xDG/JpQ1nbRd0KylfRsVRZLyfsgpYslckc+xy+vk4ccJPYbxoNjdyb5Eazowp2hdFNt3YnksQT1/AYCT5Dkw9AmT1gfqlORVFiRwoD2CjB7/ibWkl/XZA01SDUt3r8INRGMPVF934cVVwPUsCJMtBI+vnJjyd2IdHAYoxwlOvBOk6ikJuLczu+L1fTMsWmk+Qr5+Y1Si6dJlPebyM4L67J671bDT2DTlvxWmEwm0//vE36FVHwY6zrmAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-8939-5763","institution":"Assistance Publique - Hopitaux de Paris","correspondingAuthor":true,"prefix":"","firstName":"Isabelle","middleName":"","lastName":"Koné-Paut","suffix":""}],"badges":[],"createdAt":"2026-01-15 10:45:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8609629/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8609629/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102760308,"identity":"d1c474d9-ca39-42c7-996b-cc2a6b3bc5ba","added_by":"auto","created_at":"2026-02-16 10:26:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":98507,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow chart\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8609629/v1/902d1c1ef390237ca4e45db4.png"},{"id":102962270,"identity":"938a12e8-902c-42ea-8355-f9066804b308","added_by":"auto","created_at":"2026-02-19 04:06:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":783237,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8609629/v1/5ef4c730-34c7-4f3a-8fc0-096d02bceb4d.pdf"}],"financialInterests":"","formattedTitle":"Overall mortality among patients with systemic autoinflammatory diseases in France","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSystemic autoinflammatory diseases (SAIDs) are a group of disorders linked to dysfunctional innate immunity. They have been characterized over the past 30 years, with familial Mediterranean fever (FMF) being the most common and longest-standing entity [1\u0026ndash;3].\u003c/p\u003e \u003cp\u003eThe canonical SAIDs are monogenic disorders, namely FMF (familial Mediterranean fever), mevalonate kinase deficiency (MKD), TNF receptor 1-associated periodic syndrome (TRAPS), and cryopyrin-associated periodic syndrome (CAPS), and are characterized by excessive secretion of interleukin-1 and interleukin-18 [4\u0026ndash;7]. These diseases typically present at a young age, sometimes as early as the first year of life. Their lifelong course substantially impairs patients\u0026rsquo; quality of life and may lead to organ damage, including central nervous system involvement with cognitive and neurosensory impairment in CAPS, and renal involvement due to AA amyloidosis across all entities [9\u0026ndash;11].\u003c/p\u003e \u003cp\u003eTo date, few data are available regarding overall mortality in these patient populations. Lane et al. [12] described a cohort of 24 patients with SAIDs complicated by AA amyloidosis (TRAPS, CAPS, MKD, and FMF) and reported 11 deaths, with a mean age at death of 69 years and a mean survival of 19 years following the diagnosis of amyloidosis. Most available studies have focused on mortality within specific subgroups of SAID patients, often related to particular causes such as AA amyloidosis or SARS-CoV-2 infection [13\u0026ndash;21].\u003c/p\u003e \u003cp\u003eA study based on the Israeli military service registry comparing adolescents with FMF to matched controls showed excess mortality among young male patients, mainly related to AA amyloidosis before the age of 40. This excess mortality was subsequently confirmed in both men and women through comparisons with other disease-related registries, including kidney transplant registries, demonstrating increased all-cause mortality in FMF [22]. However, to date, no studies have compared mortality in SAID patients with that of the general population matched for age, limiting accurate assessment of their public health impact.\u003c/p\u003e \u003cp\u003eA comprehensive evaluation of mortality in patients with SAIDs is therefore essential to inform therapeutic strategies, particularly to justify the use of costly, highly targeted, or more burdensome treatments such as hematopoietic stem cell transplantation or gene therapy [23\u0026ndash;26]. The aim of the present study was to estimate prevalence and comparative mortality indices in patients with FMF, CAPS, TRAPS, and MKD, and to compare these estimates with mortality in the general population in France.\u003c/p\u003e"},{"header":"PATIENTS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient selection\u003c/h2\u003e \u003cp\u003ePatients with a diagnosis of FMF, CAPS, TRAPS, or MKD were included in the French National Rare Disease Registry (BNDMR). Included patients had at least one follow-up visit and a diagnosis registered as confirmed by their physician, and did not object to the reuse of their data for research purposes. Patients who had objected to the reuse of their data for research purposes were excluded.\u003c/p\u003e \u003cp\u003eVital status was enriched using the national public death registry maintained by the French National Institute of Statistics and Economic Studies (INSEE), which provides civil status information for each deceased individual. Medical causes of death were not available. Data for this study were collected between January 1, 2010, and December 31, 2024.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003ePrevalence in 2024 was estimated by dividing the number of patients alive in 2024 for each disease by the size of the French population in 2024, according to INSEE data. Confidence intervals were calculated using a chi-squared test.\u003c/p\u003e \u003cp\u003ePatient characteristics were described using frequencies for sex and medians for age at inclusion and follow-up duration. Comparisons between diseases were performed using a chi-squared test for sex and a Kruskal\u0026ndash;Wallis test for age at inclusion and follow-up duration.\u003c/p\u003e \u003cp\u003eMortality data from the BNDMR were consolidated using INSEE mortality data. For mortality analyses, age- and sex-specific mortality tables from the Human Mortality Database were used. As mortality data were available only up to 2023 at the time of analysis, and given the absence of major epidemiological events and the typically small year-to-year variations, 2023 mortality rates were applied to 2024 to allow analyses over the 2010\u0026ndash;2024 period, in line with the other analyses.\u003c/p\u003e \u003cp\u003eThe expected number of deaths was calculated by determining the number of patients by sex, age group, and year, and multiplying these counts by the corresponding age-specific mortality rates from the Human Mortality Database. The comparative mortality index (CMI) was defined as the ratio of observed to expected deaths, multiplied by 100. Confidence intervals were calculated assuming a Poisson distribution with a 95% confidence level.\u003c/p\u003e \u003cp\u003eAll statistical analyses were performed using R software (version 4.1.2), with a significance level set at 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eAfter excluding patients whose diagnosis was uncertain and those who refused data reuse, a total of 2010 patients were included between 2010 and 2024, of whom 1647 were affected by FMF, 199 by CAPS, 100 by TRAPS, and 64 by MKD (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The respective prevalence of these SAIDs in 2024 was estimated at 23.6 per million for FMF, 2.8 per million for CAPS, 1.4 per million for TRAPS, and 0.9 per million for MKD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePopulation characteristics\u003c/h3\u003e\n\u003cp\u003eWomen represented 52% (853/1647), 59% (117/199), 61% (61/100), and 47% (30/64) of the FMF, CAPS, TRAPS, and MKD cohorts, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). No significant difference in sex ratio was observed across disease cohorts (p\u0026thinsp;=\u0026thinsp;0.07), whereas a significant difference was observed in follow-up duration (p\u0026thinsp;=\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBNDMR study population characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFMF\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1647\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCAPS\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;199\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTRAPS N\u0026thinsp;=\u0026thinsp;100\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMKD\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;64\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP **value=\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex, n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1061(52.8%)\u003c/p\u003e \u003cp\u003e949(47.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e853 (51.8%)\u003c/p\u003e \u003cp\u003e794(48.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e117 (58.8%)\u003c/p\u003e \u003cp\u003e82 (41.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61(61%)\u003c/p\u003e \u003cp\u003e39 (39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30 (46.9%)\u003c/p\u003e \u003cp\u003e34(53.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge * of living patients (years)\u003c/b\u003e,\u003c/p\u003e \u003cp\u003eMedian [Q1-Q3]\u003c/p\u003e \u003cp\u003eMean +/- SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1974\u003c/b\u003e\u003c/p\u003e \u003cp\u003e28 [16\u0026ndash;44]\u003c/p\u003e \u003cp\u003e33.4+/-18.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1620\u003c/b\u003e\u003c/p\u003e \u003cp\u003e27 [16\u0026ndash;42]\u003c/p\u003e \u003cp\u003e30.9+/-18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e195\u003c/b\u003e\u003c/p\u003e \u003cp\u003e30 [17\u0026ndash;52]\u003c/p\u003e \u003cp\u003e34.3+/-22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e97\u003c/b\u003e\u003c/p\u003e \u003cp\u003e40 [21\u0026ndash;57]\u003c/p\u003e \u003cp\u003e40+/-20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e62\u003c/b\u003e\u003c/p\u003e \u003cp\u003e16 [10\u0026ndash;30]\u003c/p\u003e \u003cp\u003e21.4+/-15.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of deaths\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAge at death (years (n%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eMedian (Q1-Q3)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e +/-ET\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e36 (1.8%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e65 (50\u0026ndash;76)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e59.8\u003c/b\u003e+/-2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e27 (1.6%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e69 (58\u0026ndash;77)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e63.6\u003c/b\u003e+/-20.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e4 (2%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3 (3%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2 (3%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at study inclusion (years), n\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMedian [Q1-Q3]\u003c/p\u003e \u003cp\u003eMean +/- SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003cp\u003e23 [10\u0026ndash;41]\u003c/p\u003e \u003cp\u003e27+/-20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1647\u003c/p\u003e \u003cp\u003e23 [10\u0026ndash;39]\u003c/p\u003e \u003cp\u003e26.8+/-19.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e199\u003c/p\u003e \u003cp\u003e23 [8\u0026ndash;48]\u003c/p\u003e \u003cp\u003e28.8+/-23.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003cp\u003e36[15\u0026ndash;50\u003c/p\u003e \u003cp\u003e35.6+/-21.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64\u003c/p\u003e \u003cp\u003e7 [3\u0026ndash;21]\u003c/p\u003e \u003cp\u003e14.9+/-16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePatients follow up time (years)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMedian [Q1-Q3]\u003c/p\u003e \u003cp\u003eMean +/- SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2010\u003c/b\u003e\u003c/p\u003e \u003cp\u003e4 [2\u0026ndash;6]\u003c/p\u003e \u003cp\u003e4.9+/-4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1647\u003c/b\u003e\u003c/p\u003e \u003cp\u003e4 [2\u0026ndash;6]\u003c/p\u003e \u003cp\u003e4.7+/3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e199\u003c/b\u003e\u003c/p\u003e \u003cp\u003e4 [2\u0026ndash;8]\u003c/p\u003e \u003cp\u003e5.9+/-5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e \u003cp\u003e4 [3\u0026ndash;6]\u003c/p\u003e \u003cp\u003e5 +/-3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e64\u003c/b\u003e\u003c/p\u003e \u003cp\u003e5 [3\u0026ndash;9]\u003c/p\u003e \u003cp\u003e6.8+/-5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Calculated relative to 31/12/2024\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e**Pearson's Chi-squared Test for qualitative variables, Kruskal-Wallis Test for quantitative variables\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eFollow-up period\u0026thinsp;=\u0026thinsp;date of death or 31/12/2024 - first date of activity (inclusion in the BNDMR)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe median follow-up duration was 5 years (3\u0026ndash;9; SD 6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4) in the MKD cohort and 4 years in the FMF (2\u0026ndash;6; 4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8), CAPS (2\u0026ndash;8; 5.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5), and TRAPS (3\u0026ndash;6; 5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8) cohorts (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The median age at inclusion in rare disease centres was 23 years in the FMF and CAPS cohorts, 36 years in the TRAPS cohort, and 7 years in the MKD cohort (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMortality results\u003c/h2\u003e \u003cp\u003eDuring the 2010\u0026ndash;2024 period, 27 deaths were reported in the FMF cohort, 4 in the CAPS cohort, 3 in the TRAPS cohort, and 2 in the MKD cohort (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The comparative mortality index (CMI) for each cohort was 385, 522, 730, and 739, respectively.\u003c/p\u003e \u003cp\u003eThe number of observed deaths exceeded the expected number of deaths based on age- and sex-specific mortality rates from the Human Mortality Database for a population of similar age and sex followed over the same period, with 7.02, 0.766, 0.411, and 0.271 expected deaths in the FMF, CAPS, TRAPS, and MKD cohorts, respectively.\u003c/p\u003e \u003cp\u003eAnalysis of death seasonality showed no significant differences (p\u0026thinsp;=\u0026thinsp;0.32; data not shown). The median age at death was 65 years overall and 69 years in the FMF cohort.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eUnderstanding mortality in rare diseases helps to better assess their overall severity and the need for exceptional or intensified treatments. To our knowledge, this study is the first to assess overall mortality across the four historical SAIDs in France and to allow comparisons between them. The use of the BNDMR network, which brings together the most specialized centres for rare diseases, made it possible to include a sufficient number of patients to perform statistical analyses, although the sample size and duration of follow-up remain limited. Comparison with mortality data from the Human Mortality Database further strengthens the robustness of the analyses. However, this approach also has inherent limitations and is susceptible to several sources of bias.\u003c/p\u003e \u003cp\u003eIn particular, underreporting of diseases\u0026mdash;especially during the early years of BAMARA deployment before 2018\u0026mdash;and potential misclassification by reporting physicians cannot be excluded. The mortality rates observed in the BNDMR may therefore have been underestimated because of incomplete reporting, but they may also have been overestimated, particularly in the FMF cohort, as patients with milder phenotypes may be managed by general practitioners or in less specialized centres that do not fully report to the registry. Additional limitations include patient refusal to allow data reuse, potential loss to follow-up, limited follow-up duration, and the absence of information on causes of death, which precluded assessment of whether deaths were directly related to SAIDs or to associated comorbidities.\u003c/p\u003e \u003cp\u003eOur results showed an overall excess mortality in all four cohorts compared with the general population. While the burden of these diseases on daily life is well recognized, deaths have also been reported in several cohorts, particularly among patients with FMF, CAPS, TRAPS, and MKD complicated by AA amyloidosis, including those who underwent kidney transplantation [11\u0026ndash;21]. In our study, no clear impact of the COVID-19 pandemic on mortality was observed, with death rates remaining stable between 2020 and 2022. Nevertheless, deaths\u0026mdash;especially among FMF patients\u0026mdash;were reported during the pandemic period, most often in individuals with comorbidities known to increase the risk of COVID-19-related mortality [15\u0026ndash;21].\u003c/p\u003e \u003cp\u003eOur study did not demonstrate a reduction in mortality associated with the introduction of biologic therapies since 2009. This finding should be interpreted with caution, as more than half of the cohort was included after 2018, and underreporting of both cases and deaths is likely to have occurred before that date. Comparative analysis across the four cohorts showed that mortality was highest in the MKD cohort, which also included the youngest patients, and, to a lesser extent, in the CAPS cohort. MKD differs from other SAIDs in that it can be associated with rapidly fatal complications such as severe infections, liver failure, or macrophage activation syndrome.\u003c/p\u003e \u003cp\u003eThe available literature on mortality in MKD remains limited. An international MKD registry reported 3 deaths among 103 patients (due to suicide, cerebral hemorrhage, and pneumococcal infection), while a Franco-Belgian study reported 3 early deaths among 50 patients due to multiorgan failure with infection [27]. These studies are relatively old, incomplete, and predate the widespread use of biologic therapies. In addition, 4 of 11 patients with mevalonic aciduria died during follow-up in a separate cohort [11]. High mortality rates (41%) have also been reported among 86 patients with CAPS-related AA amyloidosis across all phenotypes in a French cohort enriched by a literature review [28]. Similarly, among 30 patients with CINCA syndrome, 8 deaths were reported, due to bacterial infection, hematologic disease, trauma, gangrene of the extremities, or amyloidosis [8]. Median ages at death were not provided in these studies. A French study also reported 5 deaths among 36 patients with TRAPS complicated by AA amyloidosis over a 23-month follow-up period [13].\u003c/p\u003e \u003cp\u003eAlthough lower than in other cohorts, the excess mortality observed in the FMF cohort is concerning, as FMF is by far the most prevalent SAID. In France, FMF-related deaths have predominantly been associated with secondary AA amyloidosis and end-stage renal disease [14]. In our study, FMF was associated with a reduction in life expectancy, particularly from the age of 50 years onwards.\u003c/p\u003e \u003cp\u003eMortality associated with FMF outside France remains incompletely understood. A Turkish study of 630 patients with FMF reported a mortality rate of 2.3% and an overall survival rate not significantly different from that of the age- and sex-matched general population; amyloidosis was the only factor independently associated with mortality in multivariate analyses [29]. In contrast, a large population-based cohort study from Israel involving 1,225 individuals with FMF showed significantly higher mortality compared with matched controls (p\u0026thinsp;=\u0026thinsp;0.002), with mortality rates of 8.73/10⁴ and 4.32/10⁴, respectively [22]. Mortality was increased in both sexes, particularly among men, and was largely attributable to renal amyloidosis. Deaths were not associated with an increased risk of cancer. Another Israeli registry-based study conducted in 2019 confirmed excess mortality in FMF, with 345 deaths among 7,670 FMF patients compared with 271 deaths among matched controls (p\u0026thinsp;=\u0026thinsp;0.002); amyloidosis remained the only significant predictor of mortality after adjustment for age and cardiovascular risk factors [30].\u003c/p\u003e \u003cp\u003eSeveral studies have examined the protective effect of colchicine, particularly with respect to cardiovascular mortality, which is a leading cause of death in FMF, often related to amyloidosis. For example, Langevitz et al. found no difference in cardiac mortality between colchicine-treated FMF patients and healthy controls [31]. Overall, mortality in FMF appears closely linked to associated comorbidities, including cardiovascular, hepatic, and renal disease, with secondary renal amyloidosis remaining the most consistently identified determinant of mortality across studies [17,22,32].\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eCompared with the general population in France, patients with FMF, CAPS, TRAPS, and MKD appear to have an increased risk of mortality across all age groups. Our data indicate that MKD is associated with the highest mortality rate among the four diseases studied. An in-depth analysis of the causes of death in patients with SAIDs would help to better tailor preventive measures, treatment strategies, and long-term follow-up.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to the members of the French Rare Diseases Expert Network (FAI2R) who are collecting the data. They are also grateful to the French Rare Diseases Data Registry (BNDMR) operational team, operating from Assistance Publique – Hôpitaux de Paris (AP-HP). This work was supported as part of the national plan for rare diseases by the Directorate of Health Care Supply of the French Ministry of Health (DGOS), with no role in the research process or conclusions drawn.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe BNDMR operational team is funded by the French Ministry of Health as part of its public interest policy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHORS CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy design: CD, ASJ, JT, and IKP.\u003c/p\u003e\n\u003cp\u003eData acquisition: IKP, SGL, and the FAI2R network.\u003c/p\u003e\n\u003cp\u003eStatistical analysis: ASJ and CD.\u003c/p\u003e\n\u003cp\u003eData analysis and interpretation: all authors.\u003c/p\u003e\n\u003cp\u003eManuscript drafting and editing: JT and IKP.\u003c/p\u003e\n\u003cp\u003eApproval of the final manuscript: all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICS DECLARATION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe CNIL authorized the creation of the BNDMR data warehouse in September 2019 (decision no. 2019-113 amended on September 28, 2023: decision no. 2023-098). According to the French ethical regulations, all patients received an information sheet about the BNDMR, and only data from patients who did not object to the processing of their data were included in the analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA SHARING STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn accordance with French regulations, access to the data supporting the findings of this study may be granted upon approval by the BNDMR Institutional Review Board.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePATIENTS AND PUBLIC INVOLVEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients and the public were not involved in the design, conduct, reporting, or dissemination plans of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eA Tufan, Lachmann HJ. Familial Mediterranean fever, from pathogenesis to treatment: a contemporary review, Turk J Med Sci. 2020;50(SI-2):1591–1610.\u003c/li\u003e\n\u003cli\u003eFrench FMF Consortium. A candidate gene for familial Mediterranean fever. Nat Genet. 1997;17(1):25–31.\u003c/li\u003e\n\u003cli\u003eInternational FMF Consortium. Ancient missense mutations in a new member of the RoRet gene family are likely to cause familial Mediterranean fever. Cell. 1997;90:797–807\u003c/li\u003e\n\u003cli\u003eZhang J, Lee PY, Aksentijevich I, Zhou Q. How to Build a Fire: The Genetics of Autoinflammatory Diseases. Annu Rev Genet. 2023; 57:245–274.\u003c/li\u003e\n\u003cli\u003eHouten SM, Kuis W, Duran M, de Koning TJ, van Royen-Kerhof A, Romeijn GJ, et al. Mutations in MVK, encoding mevalonate kinase, cause hyperimmunoglobulinaemia D and periodic fever syndrome. Nat Genet. 1999;22:175–177.\u003c/li\u003e\n\u003cli\u003eHoffman HM, Mueller JL, Broide DH, Wanderer AA, Kolodner RD. Mutation of a new gene encoding a putative pyrin-like protein causes familial cold autoinflammatory syndrome and Muckle-Wells syndrome. Nat Genet. 2001;29:301–305.\u003c/li\u003e\n\u003cli\u003eGalon J, Aksentijevich I, McDermott MF, O’Shea JJ, Kastner DL. TNFRSF1A mutations and autoinflammatory syndromes. Curr Opin Immunol. 2000 ;12:479–486. -\u003c/li\u003e\n\u003cli\u003ePrieur AM, Griscelli C, Lampert F, Truckenbrodt H, Guggenheim MA, Lovell DJ, et al. A chronic, infantile, neurological, cutaneous and articular (CINCA) syndrome. A specific entity analysed in 30 patients. Scand J Rheumatol Suppl. 1987; 66:57–68.\u003c/li\u003e\n\u003cli\u003eKuemmerle-Deschner JB, Quartier P, Kone-Paut I, Hentgen V, Marzan KA, Dedeoglu F, et al A. Burden of illness in hereditary periodic fevers: a multinational observational patient diary study. Clin Exp Rheumatol. 2020;38 Suppl 127(5):26–34\u003c/li\u003e\n\u003cli\u003eVasse M, Reumaux H, Koné-Paut I, Quartier P, Hachulla E. Socio-professional impact and quality of life of cryopyrin-associated periodic syndromes in 54 patients in adulthood. Clin Exp Rheumatol. 2023;41(10):2039–2043.\u003c/li\u003e\n\u003cli\u003evan der Hilst JCH, Bodar EJ, Barron KS, Frenkel J, Drenth JPH, van der Meer JWM, Simon A; International HIDS Study Group. Long-term follow-up, clinical features, and quality of life in a series of 103 patients with hyperimmunoglobulinemia D syndrome. Medicine (Baltimore). 2008;87(6):301–310\u003c/li\u003e\n\u003cli\u003eLane T, Loeffler JM, Rowczenio DM.Gilbertson JA, Bybee A, Russell TL and al. AA amyloidosis complicating the hereditary periodic fever syndromes. Arthritis Rheum. 2013;65(4):1116-21.\u003c/li\u003e\n\u003cli\u003eDelaleu J, Deshayes S, Rodrigues F, Savey L, Rivière E, Martin Silva N and al Tumour necrosis factor receptor-1 associated periodic syndrome (TRAPS)-related AA amyloidosis: a national case series and systematic review, Rheumatology (Oxford). 2021;60(12):5775–5784.\u003c/li\u003e\n\u003cli\u003eTerré A, Deshayes S, Savey L, Grateau G, Georgin-Lavialle S. Cause of death and risk factors for mortality in AA amyloidosis: A French retrospective study. Eur J Intern Med. 2020;82:130–132.\u003c/li\u003e\n\u003cli\u003eBourguiba R, Terré A, Savey L, Oziol E, Hanslik T, Kahn JE, Borie R, Cez A, Buob D, Grateau G, Boffa JJ, Georgin-Lavialle S. Symptomatic SARS-CoV2 infection associated with high mortality in AA amyloidosis. 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COVID-19 in patients with autoinflammatory diseases: real-life data from the AIDA network. Rheumatology. 2022.\u003c/li\u003e\n\u003cli\u003ePeet CJ, Papadopoulou C, Sombrito BRM, Wood MR, Lachmann HJ. COVID-19 and autoinflammatory diseases: prevalence and outcomes of infection and early experience of vaccination in patients on biologics. Rheumatol Adv Pract. 2021;5(2):rkab043\u003c/li\u003e\n\u003cli\u003eBourguiba R, Kyheng M, Koné-Paut I, et al. COVID-19 infection among patients with autoinflammatory diseases: a study on 117 French patients compared with 1545 from the French RMD COVID-19 cohort: COVIMAI. RMD Open. 2022;8:e002063.\u003c/li\u003e\n\u003cli\u003eTwig G, Livneh A, Vivante A, Afek A, Shamiss A, Deranze E and al. 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PW03-021 - HSCT in mevalonate kinase deficiency. Pediatr Rheumatol Online J. 2013;11(Suppl 1):A247\u003c/li\u003e\n\u003cli\u003eBader-Meunier B, Florkin B, Sibilia J, Acquaviva C, Hachulla E, Grateau G, et al. SOFREMIP (Société Francophone pour la Rhumatologie et les Maladies Inflammatoires en Pédiatrie); CRI (Club Rhumatismes et Inflammations). Mevalonate kinase deficiency: a survey of 50 patients. Pediatrics. 2011;128(1):e152-9.\u003c/li\u003e\n\u003cli\u003eRodrigues F, Cuisset L, Cador-Rousseau B, Giurgea I, Neven B, Buob D, et al. AA amyloidosis complicating cryopyrin-associated periodic syndrome: a study of 86 cases including 23 French patients and systematic review. Rheumatology (Oxford). 2022;61(12):4827–4834.\u003c/li\u003e\n\u003cli\u003eEra Servet A, Yuksel F, Tunca M, Soysal O, Solmaz D, Gerdan V and al. 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Liver Int. 2025;45(2):e16232.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mortality, Autoinflammatory diseases, Familial Mediterranean fever, mevalonate kinase deficiency, cryopyrin-associated periodic syndrome, TNFR1-associated periodic syndrome","lastPublishedDoi":"10.21203/rs.3.rs-8609629/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8609629/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction\u003c/h2\u003e \u003cp\u003eSystemic autoinflammatory diseases (SAIDs) are rare disorders of the innate immune system for which limited data on overall mortality or life expectancy. The aim of this study was to assess overall mortality among patients with familial Mediterranean fever (FMF), cryopyrin-associated periodic syndrome (CAPS), TNFR-associated periodic syndrome (TRAPS), and mevalonate kinase deficiency (MKD) in France.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePatients with a confirmed diagnosis of FMF, CAPS, TRAPS, or MKD were identified through the French National Rare Disease Registry (BNDMR). Data were contributed by rare disease reference centres within the FAI2R network, following approval by the BNDMR institutional review board. Mortality data were obtained from the BNDMR and supplemented with individual death records from the French National Institute of Statistics and Economic Studies (INSEE). Mortality between January 2010 and December 31 2024 was analysed using age- and sex-specific mortality rates from the Human Mortality Database. Comparative mortality indices (CMIs) were calculated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 2010 patients were included between 2010 and 2024: 1647 with FMF, 199 with CAPS, 100 with TRAPS, and 64 with MKD. Estimated prevalence in 2024 was 23.6 per million (95% CI [22.5\u0026ndash;24.8]) for FMF, 2.8 per million (95% CI [2.5\u0026ndash;3.3]) for CAPS, 1.4 per million (95% CI [1.2\u0026ndash;1.7]) for TRAPS, and 0.9 per million (95% CI [0.7\u0026ndash;1.2]) for MKD. A total of 36 deaths were observed between 2010 and 2024: 27 among FMF patients, 4 among CAPS patients, 3 among TRAPS patients, and 2 among MKD patients. Over the study period, the comparative mortality index (CMI) was 425 (95% CI [385.55\u0026ndash;467.39]), indicating a mortality rate 4.3 times higher than expected compared with the French general population. The lowest CMI was observed in the FMF cohort (385), whereas the highest CMI was observed in the MKD cohort (738).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThese findings highlight a significant public health concern, particularly for the rarest and most difficult-to-treat disease, MKD, but also for FMF, which is the most prevalent SAID. Our results support the need for in-depth analyses of the causes of death to better inform preventive and therapeutic strategies.\u003c/p\u003e","manuscriptTitle":"Overall mortality among patients with systemic autoinflammatory diseases in France","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-16 10:24:31","doi":"10.21203/rs.3.rs-8609629/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2026-02-25T23:02:50+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2026-02-10T10:34:31+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-10T10:07:25+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Orphanet Journal of Rare Diseases","date":"2026-02-10T10:05:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-21T18:27:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"Orphanet Journal of Rare Diseases","date":"2026-01-20T06:15:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"82807e50-a15b-44be-9e65-4097339ac9b2","owner":[],"postedDate":"February 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-08T11:39:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-16 10:24:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8609629","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8609629","identity":"rs-8609629","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}