A Systems Medicine approach to multimorbidity. Towards personalised care for patients with Chronic Obstructive Pulmonary Disease

[eng] BACKGROUND: Multimorbidity (i.e. the presence of more than one chronic disease in the same patient) and comorbidity (i.e. the presence of more than one chronic disease in the presence of an index disease) are main sources of dysfunction in chronic patients and avoidable costs in conventional health systems worldwide. By affecting a majority of elderly population worldwide, multimorbidity prompts the need for revisiting the single disease approach followed by contemporary clinical practice and elaborate strategies that target shared mechanisms of associated diseases with the potential of preventing, decelerating or even halting multimorbid disease progression. However, our current understanding on disease interactions is rather limited, and although many disorders have been associated based on their shared molecular traits and their observed co-occurrence in different populations, no comprehensive approach has been outlined to translate this knowledge into clinical practice. The advent of novel measurement technologies (e.g. omics) and recent initiatives on digital health (e.g. registries, electronic health records) are facilitating access to an enormous amount of patient-related information from whole populations to molecular levels. State-of-the art computational models and machine learning tools demonstrate high potential for health prediction and together with systems biology are shaping the practicalities of systems medicine. Given the extremely long and expensive bench to clinics cycles of the biomedical sector, systems medicine promises a fast track approach where scientific evidence support clinical care, while simultaneously collected insights from daily clinical practice promote new scientific discoveries and optimize healthcare. The PhD thesis aims to explore multimorbidity from a systems medicine perspective on the concrete and practical use case of chronic obstructive pulmonary disease (COPD). COPD constitutes an ideal use case due to several factors, including: i) its high impact on healthcare and its ever-increasing burden; ii) its heterogeneous disease manifestations, and progress, often involving extra-pulmonary effects, including highly prevalent comorbidities (e.g. type 2 diabetes mellitus, cardiovascular disorders, anxiety-depression and lung cancer); and, iii) its well described systemic effects that are suggested associations with comorbidities in terms of underlying mechanisms. HYPOTHESIS: The central hypothesis of the PhD thesis builds on the emerging biological evidence that clustering of comorbid conditions, a phenomenon seen in complex chronic patients, could be due to shared abnormalities in relevant biological pathways (i.e. bioenergetics, inflammation and tissue remodelling). It is assumed that a systems understanding of the patient conditions may help to uncover the molecular mechanisms and lead to the design of preventive and targeted therapeutic strategies aiming at modulating patient prognosis. The PhD thesis focuses on non-pulmonary phenomena of COPD; that is, systemic effects and comorbidities, often observed in patients with COPD as a paradigm of complex chronic disease. OBJECTIVES: The general objective of the PhD thesis is threefold: i) to investigate molecular disturbances at body systems level that may lead to a better understanding of characteristic systemic effects and comorbidities of patients with COPD; ii) to analyse population level patterns of COPD comorbidities and investigate their role in the health risk of patients with COPD; and, iii) to explore technological strategies and tools that facilitate the transfer of the collected knowledge on comorbidity into clinical practice. MAIN FINDINGS: Firstly, the PhD thesis introduced a novel knowledge management tool for targeted molecular analysis of underlying disease mechanisms of skeletal muscle dysfunction in patients with COPD. Second, a network analysis approach was outlined to further study this systemic effect, as well as the causes of abnormal adaptation of COPD muscle to exercise training. Furthermore, this work together with three other studies also aimed to reveal the general underlying causes of comorbidity clustering in COPD, using different modelling approaches. Overarching outcome of these studies indicates abnormalities in the complex co-regulation of core biological pathways (i.e. bioenergetics, inflammation, oxidative stress and tissue remodelling) both on muscle and body systems level (blood, lung), which paves the way for the development of novel pharmacological and non-pharmacological preventive interventions on non- pulmonary phenomena in patients with COPD. Furthermore, results indicated strong relation of muscle related dysregulations to aerobic capacity, in opposed to pulmonary severity of COPD. These findings have far reaching potential in COPD care, starting from defining the need for better characterization of exercise performance in the clinic practice and the promotion of physical activity from early stages of the disease. This PhD thesis also generated outcomes with respect to the risk of multimorbidity in patients with COPD using a population health approach. The thesis validated that patients with COPD are in increased risk to co-occur with other diseases compared to non-COPD patients, regardless of the population and healthcare system specificities of different regions (i.e. Catalonia, US). These findings indicated the potential role of multimorbidity as a risk factor for COPD, that was evaluated in the PhD thesis by constructing health risk assessment models to predict unexpected medical events in patients with COPD. The promising performance of the models and the prominent role of multimorbidity in these models presented a powerful argument for its role in clinical staging of the disease and their potential in clinical decision support. CONCLUSIONS: The PhD thesis achieved main points of the general objectives, namely: i) to perform a systems analysis of patients with COPD by investigating molecular disturbances at body systems level leading to a better understanding of characteristic systemic effects and comorbidities of patient with COPD; ii) to analyse population level patterns of COPD comorbidities and investigate their role in the health risk of patients with COPD; and iii) to explore technological strategies and tools that facilitate the transfer of the collected knowledge on comorbidity into clinical practice. Accordingly, the following conclusions arise: 1. Non-pulmonary manifestations in patients with Chronic Obstructive Pulmonary Disease (COPD) have a major negative impact on: highly relevant clinical events, use of healthcare resources and prognosis. Accordingly, the following indications were made: a. Actionable insights on non-pulmonary phenomena should be included in the clinical staging of these patients in an operational manner. b. Management of patients with COPD should be revisited to incorporate an integrative approach to non-pulmonary phenomena. c. Innovative cost-effective interventions, and pharmacological and non- pharmacological treatments targeting prevention of non-pulmonary manifestations in patients with COPD should be developed, and properly assessed. 2. Abnormal co-regulation of core biological pathways (i.e. bioenergetics, inflammation, tissue remodelling and oxidative stress), both in skeletal muscle and at body systems level, are common characteristics of patients with COPD, which potentially play a major role in comorbidity clustering. 3. Consistent relationships between cardiovascular health, skeletal muscle dysfunction and clinical outcomes in patients with COPD was identified, which makes it a priority to characterize patient exercise performance and physical activity in the clinic, and to adopt early cardiopulmonary rehabilitation strategies to modulate prognosis and prevent comorbidity clustering in these patients. 4. Multimorbidity is a strong predictor of unplanned medical events in patients with COPD and shows high potential to be used for personalized health risk prediction and service workflow selection. 5. Personalized health risk prediction was identified as a high potential tool for the integration and transfer of scientific evidence on multimorbidity to daily clinical practice. Limiting factors of its present applicability were explored and implementation strategies based on cloud computing solutions were proposed.[cat] INTRODUCCIÓ: Tant la multimorbiditat (la presència de més d'una malaltia crònica en el mateix pacient), com la comorbiditat (la presència de més d'una malaltia crònica quan hi ha una malaltia de referència) són una font important de disfuncions en l’atenció sanitària dels pacients crònics i generen importants despeses evitables en sistemes de salut arreu del món. La multimorbiditat/comorbiditat afecta la majoria de població de més de 65 anys. El seu gran impacte sanitari i social fa necessària la revisió d’aspectes essencials de la pràctica mèdica convencional, molt enfocada al tractament de cada malaltia de forma aïllada. En aquest sentit, cal elaborar estratègies que considerin els mecanismes biològics comuns entre patologies, per tal de prevenir, retardar o fins i tot aturar la progressió del fenomen. Malauradament, el poc coneixement dels mecanismes biològics que modulen les interaccions entre malalties és un factor limitant important. Hi ha estudis sobre els mecanismes moleculars comuns entre malalties i s’han realitzat anàlisis poblacionals de la multimorbiditat, però no existeix encara una aproximació holística per tal de traduir aquest coneixement a la pràctica clínica. L’aparició de noves tecnologies òmiques, així com iniciatives recents en l’àmbit de la salut digital, han facilitat l'accés a una quantitat enorme d'informació dels pacients, tant a nivell poblacional com a nivell molecular. A més, les eines computacionals i d'aprenentatge automàtic existents estan demostrant un gran potencial predictiu que, conjuntament amb les metodologies de la biologia de sistemes, estan conformant els aspectes pràctics del desplegament de la medicina de sistemes. De forma progressiva, aquesta última esdevé una via efectiva per accelerar el rol de l’evidència científica com a suport a la atenció clínica. De forma recíproca, la digitalització sistemàtica de la pràctica clínica diària, permet la generació de noves descobertes científiques i la optimització de l’assistència sanitària. Aquesta tesis doctoral pretén explorar la multimorbiditat des d’una perspectiva de medicina de sistemes, considerant com a cas d'ús concret i pràctic la malaltia pulmonar obstructiva crònica (MPOC). La MPOC constitueix un cas d'ús ideal a causa de diversos factors: i) el seu alt impacte a nivell sanitari; ii) la heterogeneïtat en quant a manifestacions i progrés, sovint amb efectes extra-pulmonars, incloent de forma freqüent comorbiditats com la diabetis mellitus tipus 2, trastorns cardiovasculars, l'ansietat-depressió i el càncer de pulmó; i, iii) els efectes sistèmics de la malaltia pulmonar, que podrien presentar mecanismes biològics comuns a algunes comorbiditats. HIPÒTESIS: La hipòtesi central d’aquesta tesis doctoral considera que la multimorbiditat podria explicar-se per alteracions en les xarxes de regulació de mecanismes biològics rellevants com la bioenergètica, inflamació i remodelació de teixits. En aquest sentit, l’anàlisi holística del problema podria millorar la comprensió dels mecanismes moleculars que modulen les associacions entre malalties i, per tant, facilitar el disseny d'estratègies terapèutiques preventives i dirigides a modular el pronòstic dels pacients. Aquesta tesis doctoral estudia els fenòmens extra-pulmonars de la MPOC; és a dir, efectes sistèmics (disfunció del múscul esquelètic) i comorbiditats, com a paradigma de malalties cròniques complexes. OBJECTIUS: L'objectiu general d’aquesta tesis doctoral és triple: i) l’anàlisi holístic de pacients amb MPOC amb focus en la disfunció muscular i les comorbiditats; ii) avaluar el paper de les comorbiditats en el risc de salut dels pacients amb MPOC, tant a nivell poblacional com individual; i, iii) explorar estratègies tecnològiques i eines de salut digital que facilitin la transferència de coneixement a la pràctica clínica diària. RESULTATS: El primer manuscrit de la tesi descriu una nova eina de gestió del coneixement per l’anàlisi molecular dels mecanismes de disfunció del múscul esquelètic en pacients amb MPOC. També dins el primer objectiu de la tesi, s’efectua un anàlisi de xarxes orientat a la identificació de mòduls biològics explicatius de la disfunció muscular i de l’adaptació anòmala d’aquests malalts a l’entrenament físic, tal com es descriu en el segon manuscrit. Els tres articles següents exploren, des de diferents perspectives, l’impacte i mecanismes de les comorbiditats en els pacients amb MPOC. Els principals resultats d'aquests estudis indiquen una complexa i anormal regulació de vies biològiques principals, com es el cas de la bioenergètica, inflamació, estrès oxidatiu i remodelació de teixits, tant a nivell del múscul com a nivell sistèmic (sang, pulmó). Aquests resultats obren noves vies per a intervencions preventives, tant farmacològiques com no farmacològiques, sobre els fenòmens no pulmonars que presenten els pacients amb MPOC. Els resultats indiquen una associació de les alteracions musculars amb la capacitat aeròbica, i no pas amb la gravetat de la malaltia pulmonar. Aquestes troballes tenen un gran potencial en la millora de la gestió dels pacients amb MPOC, començant per la necessitat d’una millor caracterització de la capacitat aeròbica en la pràctica clínica i la promoció d'activitat física des de les primeres etapes de la malaltia. La tesi també ha generat resultats d’interès en relació amb el risc de multimorbiditat en pacients amb MPOC, mitjançant un enfocament de salut poblacional. Els resultats evidencien que els pacients amb MPOC presenten un risc mes elevat de comorbiditat que els pacients sense MPOC, independentment de les especificitats de la població i del sistema sanitari de les àrees analitzades (Catalunya, EUA). La tesi també demostra el paper de la multimorbiditat com a factor modulador del risc clínic dels pacients amb MPOC. Aquests resultats indiquen l’interès de l’ús de la multimobiditat en l’estadiatge dels pacients amb MPOC i en l’elaboració d’eines de suport al procés de decisió clínica. CONCLUSIONS: Aquesta tesi doctoral ha assolit els objectius generals plantejats i proposa les següents conclusions: 1. Les manifestacions no pulmonars en els pacients amb malaltia pulmonar obstructiva crònica (MPOC) tenen un impacte negatiu respecte a esdeveniments de gran rellevància clínica, ús de recursos sanitaris i pronòstic. En conseqüència, es fan les següents recomanacions: a. Els fenòmens no pulmonars de la MPOC s’haurien d’incloure de manera operativa en l’estadiatge d'aquests pacients. b. S’hauria de redefinir la gestió clínica dels pacients amb MPOC tot incorporant un enfocament holístic dels fenòmens no pulmonars. c. S’haurien de desenvolupar i avaluar correctament noves intervencions, farmacològiques i no farmacològiques, per a la prevenció de les manifestacions no pulmonars en pacients amb MPOC. 2. Les alteracions de la regulació de vies biològiques rellevants com la bioenergètica, inflamació, estrès oxidatiu i la remodelació de teixits a nivell del múscul esquelètic, i també a nivell sistèmic, s’observa en els pacients amb MPOC i pot tenir un paper important en les co-morbiditats. 3. Les relacions entre alteracions cardiovasculars, disfunció del múscul esquelètic i altres aspectes clínics dels pacients amb MPOC, indiquen la necessitat de caracteritzar la capacitat aeròbica i els nivells d'activitat física en la pràctica clínica, així com la implementació d’estratègies de rehabilitació cardiopulmonar en les primeres etapes de la malaltia, per tal de modular la prognosis dels malalts i prevenir l’aparició de comorbiditats. 4. La multimorbiditat és un bon predictor d’esdeveniments clínics rellevants en pacients amb MPOC i mostra un gran potencial per a personalitzar l’estimació de risc i la selecció de serveis. 5. La predicció de risc de forma personalitzada s’ha identificat com una eina amb molt potencial per a la gestió de la multimorbiditat en la pràctica clínica diària. S’han explorat els factors limitants de la seva aplicabilitat i s’han proposat estratègies d'implementació d’eines predictives adients, basades en solucions de computació en el núvol.[spa] INTRODUCCIÓN: Tanto la multimorbilidad (la presencia de más de una enfermedad crónica en un mismo paciente) como la comorbilidad (la presencia de más de una enfermedad crónica en presencia de una enfermedad de referencia) son una fuente importante de disfunciones en la atención sanitaria de los pacientes crónicos y generan importantes costes evitables en los sistemas de salud de todo el mundo. La multimorbilidad/comorbilidad afecta a la mayoría de la población de más de 65 años. Debido a su gran impacto sanitario y social, resulta necesaria la revisión de aspectos esenciales de la práctica médica convencional, muy enfocada en el tratamiento de cada enfermedad de forma aislada. En este sentido, es necesario elaborar estrategias que consideren mecanismos biológicos comunes entre patologías, con el fin de prevenir, retrasar o incluso detener la progresión del fenómeno. Desgraciadamente, el escaso conocimiento de los mecanismos biológicos que modulan las interacciones entre enfermedades es un factor limitante importante. Existen estudios sobre los mecanismos moleculares comunes entre enfermedades y se han realizados análisis poblaciones de la multimorbilidad, pero no existe aún una aproximación holística que permita traducir este conocimiento a la práctica clínica. La aparición de nuevas tecnologías ómicas, así como recientes iniciativas en el ámbito de la salud digital, han facilitado el acceso a una cantidad enorme de información sobre los pacientes, tanto a nivel poblacional como a nivel molecular. Además, las herramientas computacionales y de aprendizaje automático existentes demuestran un gran potencial predictivo que, conjuntamente con las metodologías de biología de sistemas, están conformando los aspectos prácticos de la medicina de sistemas. De manera progresiva esta última se está convirtiendo en una vía efectiva para acelerar el papel de la evidencia científica como soporte a la atención clínica. De forma recíproca, la digitalización sistemática de la práctica clínica diaria permite la generación de nuevos descubrimientos científicos y la optimización de la asistencia sanitaria. Esta tesis doctoral pretende explorar la multimorbilidad desde una perspectiva de medicina de sistemas, considerando como caso de uso concreto y práctico la enfermedad pulmonar obstructiva crónica (EPOC). La EPOC constituye un caso de uso ideal debido a diversos factores: i) su alto impacto a nivel sanitario; ii) la heterogeneidad en cuanto a manifestaciones y progreso, a menudo con efectos extra pulmonares, incluyendo de forma frecuente comorbilidades como la diabetes mellitus tipo 2, trastornos cardiovasculares, la ansiedad-depresión y el cáncer de pulmón; y, iii) los efectos sistémicos de la enfermedad pulmonar, que podrían presentar mecanismos biológicos comunes a algunas comorbilidades. HIPÓTESIS: La hipótesis central de esta tesis doctoral considera que la multimorbilidad podría explicarse por alteraciones en las redes de regulación de mecanismos biológicos relevantes como la bioenergética, inflamación y remodelación de tejidos. En este sentido, el análisis holístico del problema podría mejorar la comprensión de los mecanismos moleculares que modulan las asociaciones entre enfermedades y, por tanto, facilitar el diseño de estrategias terapéuticas preventivas y dirigidas a modular el pronóstico de los pacientes. Esta tesis doctoral estudia los fenómenos extra pulmonares de la EPOC; es decir, efectos sistémicos (disfunción del músculo esquelético) y comorbilidades, como paradigma de enfermedades crónicas complejas. OBJETIVOS: El objetivo general de esta tesis doctoral es triple: i) el análisis holístico de pacientes con EPOC focalizando en la disfunción muscular y la comorbilidades; ii) evaluar el papel de las comorbilidades en el riesgo de salud de los pacientes con EPOC, tanto a nivel poblacional como individual; y, iii) explorar estrategias tecnológicas y herramientas de salud digital que faciliten la transferencia de conocimiento a la práctica clínica diaria. RESULTADOS: El primer manuscrito de la tesis describe una nueva herramienta de gestión del conocimiento para el análisis molecular de los mecanismos de disfunción del músculo esquelético en pacientes con EPOC. Incluido en el primer objetivo de la tesis, se efectúa un análisis de redes orientado a la identificación de módulos biológicos que explican la disfunción muscular y la adaptación anómala de estos pacientes al entrenamiento físico, tal y cómo se describe en el segundo manuscrito. Los tres artículos siguientes exploran, desde perspectivas diferentes, el impacto y mecanismos de las comorbilidades en los pacientes con EPOC. Los principales resultados de estos estudios indican una compleja y anormal regulación de vías biológicas principales, como es el caso de la bioenergética, inflamación, estrés oxidativo y remodelación de tejidos, tanto a nivel del músculo como a nivel sistémico (sangre, pulmón). Estos resultados abren nuevas vías para intervenciones preventivas, tanto farmacológicas como no farmacológicas, sobre los fenómenos no pulmonares que presentan los pacientes con E

Can Lessons from Public Health Disease Surveillance Be Applied to Environmental Public Health Tracking?

Disease surveillance has a century-long tradition in public health, and environmental data have been collected at a national level by the U.S. Environmental Protection Agency for several decades. Recently, the Centers for Disease Control and Prevention announced an initiative to develop a national environmental public health tracking (EPHT) network with “linkage” of existing environmental and chronic disease data as a central goal. On the basis of experience with long-established disease surveillance systems, in this article we suggest how a system capable of linking routinely collected disease and exposure data should be developed, but caution that formal linkage of data is not the only approach required for an effective EPHT program. The primary operational goal of EPHT has to be the “treatment” of the environment to prevent and/or reduce exposures and minimize population risk for developing chronic diseases. Chronic, multifactorial diseases do not lend themselves to data-driven evaluations of intervention strategies, time trends, exposure patterns, or identification of at-risk populations based only on routinely collected surveillance data. Thus, EPHT should be synonymous with a dynamic process requiring regular system updates to a) incorporate new technologies to improve population-level exposure and disease assessment, b) allow public dissemination of new data that become available, c) allow the policy community to address new and emerging exposures and disease “threads,” and d) evaluate the effectiveness of EPHT over some appropriate time interval. It will be necessary to weigh the benefits of surveillance against its costs, but the major challenge will be to maintain support for this important new system

Causes and consequences of temporomandibular joint diseases

Temporomandibular joint disorders (TMJD), a subgroup of Temporomandibular disorders (TMD), has a multifactorial etiology with still largely unknown pathophysiology. Although many risk factors have been proposed, few population-based studies have been conducted. There are known associations between TMJD and mental and behavioral disorders (MBD) and musculoskeletal diseases (MSD). MBD and MSD cause high work disability and are the leading causes for sick leave (SL) and disability pension (DP) both globally and in Sweden. However, no studies have investigated work disability among patients with TMJD (pwTMJD) or the effect of MBD and MSD comorbidity on work disability among pwTMJD. This thesis includes all Swedish citizens aged ≥18 registered between 1998 and 2016 in the National Patient Registry with a TMJD diagnosis or TMJD surgical procedure code. These pwTMJD (n=33 316) were matched to a comparison cohort (n=333 160) from the Total Population Registry. pwTMJD were categorized depending on whether they had received surgical treatment or not, and on the number of surgical procedures. Study I shows that pwTMJD have 2–3 times more mean annual days of SL and DP than the general population and that patients who had undergone several surgical treatments were most dependent on these benefits. The increased work disability among pwTMJD was noticeable as early as five years before first time diagnosis or treatment. Study II and Study III investigate the probability of developing TMJD among individuals with and without MBD/MSD. Study II shows that many MBD increase the probability of TMJD and that individuals with MBD had a higher risk of needing repeated surgical procedures compared to individuals with no MBD. Study III shows that virtually all MSD increase the probability of TMJD, especially TMJD that require repeated surgical procedures. Study IV further examines the impact of MBD and MSD comorbidity on mean annual days of SL and DP among pwTMJD compared to the general population, by using strata of comorbidity. The results show that both MBD and MSD comorbidity by themselves have a large impact on the use of social insurance benefits but that combined MBD/MSD comorbidity had the largest impact on SL and DP. Regardless of comorbidity, pwTMJD displayed the highest mean annual days of SL and DP in almost all strata of comorbidity. In conclusion, the results in this thesis show that MBD and MSD are strong predictors for the development of TMJD. The results also show that pwTMJD have more work disability than the general population, and that this increased dependence on social insurance benefits is strongly influenced by comorbidities. These findings emphasize how pwTMJD are suffering from their condition and that a multimodal approach is warranted, preferably steered by national guidelines designed by specialists in orofacial pain and function, oral and maxillofacial surgeons, and colleagues from the medical field

Depression in Rheumatoid Arthritis and an Estimation of the Bi-directional Association of Depression and Disease Burden: A Dissertation

Depression is a common comorbidity in rheumatoid arthritis (RA), yet it may not be adequately recognized during routine clinical care. RA symptoms may confer a risk for depression, and vice versa; depression may affect RA disease activity and response to treatment. The study aims were to compare patient- and physician-reported depression measures, evaluate the temporal bi-directional association between RA disease activity and depressive symptomology, and assess depression as a moderator of RA treatment. Patients were identified using a national RA registry sample (Consortium of Rheumatology Researchers of North America; CORRONA). Depression prevalence and incidence rates were estimated, and concordance and disagreement using measures reported separately by patients and physicians, as well as baseline cross-sectional associations between RA disease and a history of depression. A survival analysis was conducted to temporally predict the incident onset of self-reported depressive symptoms using the different metrics of RA disease activity. Also, mixed effects models were used to assess prospective changes in RA disease activity by prevalent and incident depressive symptom status. Lastly, logistic regression models compared the likelihood of clinical response to RA treatment during follow-up in those with and without depression when starting biologic disease modifying anti-rheumatic drug (DMARD) therapy. Patient-reported depression rates were much higher and significantly different from physician based comorbidity estimates. Patient and physician RA disease activity measures were associated with an increased risk for depression onset, but not laboratory-reported serum biomarkers. Similarly, depression was temporally associated with significantly slower rates of decline regarding every patient-reported disease activity measure, some physician-reported metrics, but not acute phase reactants. Moreover, there was a significantly lower probability of achieving clinical remission among those with depression on a biologic DMARD after 6 months and an analogous effect at 12-months that was slightly lower in magnitude, which did not reach statistical significance. Rheumatologists under-reported the occurrence of prevalent and incident depressive symptoms, and thus are likely unaware of its presence in their RA patients. Further, the results suggest the bi-directional effects between these conditions are related to the cognitive and behavioral aspects of depression and their interactions with disease activity, rather than shared immunological mechanisms in the context of cell-mediated immunity. When also considering the impact on clinical response to biologic DMARDS, the findings collectively imply that rheumatologists must address any challenges due to depression to provide the best care to their patients

Type 1 diabetes

Type 1 diabetes is a chronic autoimmune disease characterised by insulin deficiency and resultant hyperglycaemia. Knowledge of type 1 diabetes has rapidly increased over the past 25 years, resulting in a broad understanding about many aspects of the disease, including its genetics, epidemiology, immune and β-cell phenotypes, and disease burden. Interventions to preserve β cells have been tested, and several methods to improve clinical disease management have been assessed. However, wide gaps still exist in our understanding of type 1 diabetes and our ability to standardise clinical care and decrease disease-associated complications and burden. This Seminar gives an overview of the current understanding of the disease and potential future directions for research and care

The impact of socioeconomic status on the risk and prognosis of venous thromboembolism

Venøs tromboembolisme (VTE), bestående av dyp venetrombose (DVT) og lungeemboli (PE), er en utbredt og multifaktoriell sykdom med langtidskomplikasjoner som negativt påvirker fysisk funksjon og livskvalitet. Sosioøkonomisk status (SES) er kjent for å påvirke både risiko og prognose for helsemessige og helserelaterte utfall. Selv om assosiasjoner mellom VTE og fysisk helse er godt dokumentert, finnes det lite forskning på psykososiale risikofaktorer og konsekvenser relatert til VTE. I denne avhandlingen ønsket vi å studere sammenhengen mellom SES og VTE i en befolkning i arbeidsfør alder. Vi ville videre se på sammenhengen mellom VTE og påfølgende uføretrygd i befolkningen i arbeidsfør alder, samt å vurdere om SES var assosiert med økt risiko for uføretrygd etter VTE. Vi ville også vurdere risikoen for depresjon etter VTE. Denne avhandlingen er basert på data samlet inn fra 1995 til 2016 fra danske nasjonale medisinske og administrative registre. Studiepopulasjonen inkluderte nesten 125 000 individer med VTE, i tillegg til en sammenligningskohorte fra den generelle befolkningen. Vi fant at at høyt utdanningsnivå, høy inntekt og høy sysselsettingsstatus, samt en høy sammensatt SES score, var assosiert med en 30-40% redusert risiko for VTE, samt at SES score modellen var bedre til å vurdere VTE risikoen sammenlignet med de individuelle indikatorene. Videre fant vi at VTE var assosiert med en 2 til 3 ganger forhøyet risiko for påfølgende uføretrygd, og at interaksjon stod for 45,6% av forekomsten av uføretrygd hos personer med lav SES og VTE. Avslutningsvis fant vi at VTE var assosiert med en 1.9-ganger forhøyet risiko for fremtidig depresjon. Våre funn kan bidra til en forbedret forståelse av psykososiale risikofaktorer og konsekvenser for VTE, og de kan danne grunnlag for helsemessige anbefalinger og nye strategier for identifisering av høyrisikogrupper for forebygging, oppfølging eller behandlingsprogrammer etter en VTE.Venous thromboembolism (VTE) is a prevalent and multifactorial disease with long-term complications that negatively affect physical functioning and quality of life. Socioeconomic status (SES) is known to affect the risk and prognosis of health and health behavioral outcomes. In this thesis, we used data collected from 1995 through 2016 from Danish national registries to investigate socioeconomic and psychosocial risk factors for and outcomes of VTE. We found that low SES increases the risk of VTE, that individuals with VTE, particularly those with low SES, are at increased risk of disability pension, and that VTE increases the risk of subsequent depression. Our findings provide an improved understanding of the psychosocial impact of VTE, and they can form the basis for health recommendations and novel strategies to identify high-risk groups that would benefit from programs for prevention, follow-up, or treatment after a VTE

Identifying and appraising promising sources of UK clinical, health and social care data for use by NICE

This report aimed to aid the National Institute of Health and Care Excellence (NICE) in identifying opportunities for greater use of real-world data within its work. NICE identified five key ways in which real-world data was currently informing its work, or could do so in the future through: (i) researching the effectiveness of interventions or practice in real-world (UK) settings (ii) auditing the implementation of guidance (iii) providing information on resource use and evaluating the potential impact of guidance (iv) providing epidemiological information (v) providing information on current practice to inform the development of NICE quality standards. This report took a broad definition of ‘real-world’ data and created a map of UK sources, informed by a number of experts in real-world data, as well as a literature search, to highlight where some of the opportunities may lie for NICE within its clinical, public health and social care remit. The report was commissioned by the NICE, although the findings are likely to be of wider interest to a range of stakeholders interested in the role of real-world data in informing clinical, social care and public health decision-making. Most of the issues raised surrounding the use and appraisal of real-world data are likely to be generic, although the choice of datasets that were profiled in-depth reflected the interests of NICE. We discovered 275 sources that were named as real-world data sources for clinical, social care or public health investigation, 233 of which were deemed as active. The real-world data landscape therefore is highly complex and heterogeneous and composed of sources with different purposes, structures and collection methods. Some real-world data sources are purposefully either set-up or re-developed to enhance their data linkages and to examine the presence/absence/effectiveness of integrated patient care; however, such sources are in the minority. Furthermore, the small number of real-world data sources that are designed to enable the monitoring of care across providers, or at least have the capability to do so at a national level, have been utilised infrequently for this purpose in the literature. Data that offer the capacity to monitor transitions between health and social care do not currently exist at a national level, despite the increasing recognition of the interdependency between these sectors. Among the data sources we included, it was clear that no one data source represented a panacea for NICE’s real world data needs. This does highlight the merits and importance of data linkage projects and is suggestive of a need to triangulate evidence across different data, particularly in order to understand the feasibility and impact of guidance. There exists no overall catalogue or repository of real-world data sources for health, public health and social care, and previous initiatives aimed at creating such a resource have not been maintained. As much as there is a need for enhanced usage of the data, there is also a need for taking stock, integration, standardisation, and quality assurance of different sources. This research highlights a need for a systematic approach to creating an inventory of sources with detailed metadata and the funding to maintain this resource. This would represent an essential first step to support future initiatives aimed at enhancing the use of real-world data