1,721,049 research outputs found
Lifespan variation among people with a given disease or condition
Full text linkIn addition to fundamental mortality metrics such as mortality rates and mortality rate ratios, life expectancy is also commonly used to investigate excess mortality among a group of individuals diagnosed with specific diseases or conditions. However, as an average measure, life expectancy ignores the heterogeneity in lifespan. Interestingly, the variation in lifespan-a measure commonly used in the field of demography-has not been estimated for people with a specific condition. Based on recent advances in methodology in research within epidemiology and demography, we discuss two metrics, namely, the average life disparity and average lifetable entropy after diagnosis, which estimate the variation in lifespan for time-varying conditions in both absolute and relative aspects. These metrics are further decomposed into early and late components, separated by their threshold ages. We use mortality data for women with mental disorders from Danish registers to design a population-based study and measure such metrics. Compared with women from the general population, women with a mental disorder had a shorter average remaining life expectancy after diagnosis (37.6 years vs. 44.9 years). In addition, women with mental disorders also experienced a larger average lifespan variation, illustrated by larger average life disparity (9.5 years vs 9.1 years) and larger average lifetable entropy (0.33 vs 0.27). More specifically, we found that women with a mental disorder had a larger early average life disparity but a smaller late average life disparity. Unlike the average life disparity, both early and late average lifetable entropy were higher for women with mental disorders compared to the general population. In conclusion, the metric proposed in our study complements the current research focusing merely on life expectancy and further provides a new perspective into the assessment of people's health associated with time-varying conditions
Using Gumbel copula to assess the efficiency of the main endpoint in a randomized clinical trial and comparison with Frank copula
Full text linkIn time-to-event randomized clinical trials, it is common to use composite endpoints as the main endpoint when comparing two treatment groups. A new statistical methodology has been recently developed in order to derives guidelines for deciding whether to expand the use a single or composite endpoint. This methodology, developed by Gómez and Lagakos, is based on the asymptotic relative efficiency (ARE) of a logrank test for comparing two treatment groups with respect to a relevant endpoint versus the composite endpoint. In order to compute the ARE, it is necessary to have the joint law of the time to the relevant and additional endpoints and it is obtained using Frank copula. The main aim of this master thesis is to develop this methodology using Gumbel copula and to compare it with the results obtained using Frank copula. This project shows that the results obtained using Gumbel copula are similar to the ones obtained using Frank copula and, therefore, we conclude that the ARE method is robust for the choice of the copula when restricted to Frank and Gumbel copulas.Gómez i Lagakos calculen l'eficiència relativa (ARE) del logrank per comparar dos tractaments A i B usant el temps T1 fins E1 o T* fins E*= E1 U E2. L'ARE s'obté fixant la llei de (T1, T2) i es modela via la còpula de Frank. L'objectiu és modelar la llei amb altres còpulas i estudiar les repercussions que aquest canvi té en el càlcul del ARE. L'estudiant haurà d'estudiar la metodologia de GL; estudiar les propietats de les còpules; escollir una còpula diferent de la de Frank i programar l'ARE; i discutir quan robust és l'ARE en front d'un canvi de còpula
Using Gumbel copula to assess the efficiency of the main endpoint in a randomized clinical trial and comparison with Frank copula
No full textIn time-to-event randomized clinical trials, it is common to use composite endpoints as the main endpoint when comparing two treatment groups. A new statistical methodology has been recently developed in order to derives guidelines for deciding whether to expand the use a single or composite endpoint. This methodology, developed by Gómez and Lagakos, is based on the asymptotic relative efficiency (ARE) of a logrank test for comparing two treatment groups with respect to a relevant endpoint versus the composite endpoint. In order to compute the ARE, it is necessary to have the joint law of the time to the relevant and additional endpoints and it is obtained using Frank copula. The main aim of this master thesis is to develop this methodology using Gumbel copula and to compare it with the results obtained using Frank copula. This project shows that the results obtained using Gumbel copula are similar to the ones obtained using Frank copula and, therefore, we conclude that the ARE method is robust for the choice of the copula when restricted to Frank and Gumbel copulas.Gómez i Lagakos calculen l'eficiència relativa (ARE) del logrank per comparar dos tractaments A i B usant el temps T1 fins E1 o T* fins E*= E1 U E2. L'ARE s'obté fixant la llei de (T1, T2) i es modela via la còpula de Frank. L'objectiu és modelar la llei amb altres còpulas i estudiar les repercussions que aquest canvi té en el càlcul del ARE. L'estudiant haurà d'estudiar la metodologia de GL; estudiar les propietats de les còpules; escollir una còpula diferent de la de Frank i programar l'ARE; i discutir quan robust és l'ARE en front d'un canvi de còpula
Using Gumbel copula to assess the efficiency of the main endpoint in a randomized clinical trial and comparison with Frank copula
No full textIn time-to-event randomized clinical trials, it is common to use composite endpoints as the main endpoint when comparing two treatment groups. A new statistical methodology has been recently developed in order to derives guidelines for deciding whether to expand the use a single or composite endpoint. This methodology, developed by Gómez and Lagakos, is based on the asymptotic relative efficiency (ARE) of a logrank test for comparing two treatment groups with respect to a relevant endpoint versus the composite endpoint. In order to compute the ARE, it is necessary to have the joint law of the time to the relevant and additional endpoints and it is obtained using Frank copula. The main aim of this master thesis is to develop this methodology using Gumbel copula and to compare it with the results obtained using Frank copula. This project shows that the results obtained using Gumbel copula are similar to the ones obtained using Frank copula and, therefore, we conclude that the ARE method is robust for the choice of the copula when restricted to Frank and Gumbel copulas.Gómez i Lagakos calculen l'eficiència relativa (ARE) del logrank per comparar dos tractaments A i B usant el temps T1 fins E1 o T* fins E*= E1 U E2. L'ARE s'obté fixant la llei de (T1, T2) i es modela via la còpula de Frank. L'objectiu és modelar la llei amb altres còpulas i estudiar les repercussions que aquest canvi té en el càlcul del ARE. L'estudiant haurà d'estudiar la metodologia de GL; estudiar les propietats de les còpules; escollir una còpula diferent de la de Frank i programar l'ARE; i discutir quan robust és l'ARE en front d'un canvi de còpula
Síndrome metabólico e incidencia y mortalidad por cáncer entre la población catalana
Full text linkLa síndrome metabòlica (SM), caracteritzat per obesitat, dislipèmia, hipertensió arterial i resistència a la insulina, representa un desafiament global en salut pública. Aquesta tesi analitza el seu impacte en la incidència, supervivència i esperança de vida restant (RLE) en 13 tipus de càncer (colorectal, pròstata, fetge, bufeta, endometri, pàncrees, mama, pulmó, ronyó, tiroide, limfoma de Hodgkin, limfoma no Hodgkin i leucèmia). S'empren dades poblacionals de Catalunya (SIDIAP) i de l'Institut Nacional d'Estadística (INE). A través de dissenys epidemiològics avançats, s'obté una anàlisi sòlida d'aquestes interaccions. Els resultats mostren que l'SM augmenta significativament el risc de càncer, especialment en endometri, fetge, ronyó, pàncrees, tiroide, leucèmia, bufeta, colorectal, limfoma no Hodgkin, pulmó i mama postmenopàusic. A més, l'acumulació de components del SM eleva el risc més que els factors individuals, la qual cosa reforça la necessitat d'abordar-lo com una entitat integrada. L'anàlisi revela que unes certes combinacions de factors del SM influeixen significativament en la incidència de càncer. La combinació de baix colesterol HDL i glucèmia elevada és especialment rellevant. En homes, l'associació més forta és "HDL+Glucèmia", mentre que en dones destaca "HDL+Hipertensió Arterial". En termes de supervivència, l'SM redueix significativament la RLE després d'un diagnòstic de càncer, amb diferències segons el sexe. En homes, els càncers de fetge, pulmó i bufeta presenten les majors reduccions en la RLE, mentre que en dones els més afectats són els càncers ginecològics, com el d'endometri i mama. Aquestes troballes subratllen la importància de considerar diferències biològiques i hormonals en la gestió del càncer en pacients amb SM. L'ús de mètriques com els anys de vida perduts (LYL) permet una avaluació més precisa de l'impacte del SM en la supervivència. S'observa un augment en els LYL per càncer a mesura que s'incrementa el nombre de components del SM, mentre que els LYL per altres causes disminueixen. En combinar aquestes mètriques amb eines com les corbes de Kaplan-Meier, s'obté una visió detallada de l'impacte del SM a curt i llarg termini, facilitant estratègies d'intervenció més personalitzades. Des d'una perspectiva de salut pública, aquestes troballes reforcen la necessitat d'estratègies preventives que abordin l'SM en el seu conjunt. Les diferències entre homes i dones ressalten la importància d'adaptar les intervencions segons el sexe, considerant variacions biològiques i d'estil de vida. Així mateix, integrar la salut metabòlica en les polítiques de prevenció del càncer podria reduir la càrrega de totes dues malalties. Aquesta recerca emfatitza la importància de la prevenció i detecció precoç en individus amb SM, donat el seu impacte en la progressió del càncer i la reducció de l'esperança de vida. Estratègies com a modificacions en l'estil de vida, tractament farmacològic per al control metabòlic i monitoratge oncològic primerenc poden ser clau per a reduir la mortalitat en aquest grup de pacients. En conclusió, a mesura que s'incrementa el nombre de components del SM, també augmenten el risc i la incidència de càncer, així com disminueix l'esperança de vida en persones amb diagnòstic oncològic. La combinació de major risc de càncer, tant en homes com en dones, és "HDL+Glucèmia+Hipertensió Arterial". Aquesta tesi aporta evidència sòlida sobre l'impacte del SM en la incidència i progressió del càncer. En integrar anàlisis innovadores amb dades poblacionals d'alta qualitat, aquest treball proporciona una base per a millorar les estratègies de salut pública i les pràctiques clíniques, ajudant en última instància a mitigar l'impacte dual del SM i les malalties oncològiques.El síndrome metabólico (SM), caracterizado por obesidad, dislipidemia, hipertensión arterial y resistencia a la insulina, representa un desafío global en salud pública. Esta tesis analiza su impacto en la incidencia, supervivencia y esperanza de vida restante (RLE) en 13 tipos de cáncer (colorrectal, próstata, hígado, vejiga, endometrio, páncreas, mama, pulmón, riñón, tiroides, linfoma de Hodgkin, linfoma no Hodgkin y leucemia). Se emplean datos poblacionales de Cataluña (SIDIAP) y del Instituto Nacional de Estadística (INE). A través de diseños epidemiológicos avanzados, se obtiene un análisis sólido de estas interacciones. Los resultados muestran que el SM aumenta significativamente el riesgo de cáncer, especialmente en endometrio, hígado, riñón, páncreas, tiroides, leucemia, vejiga, colorrectal, linfoma no Hodgkin, pulmón y mama postmenopáusico. Además, la acumulación de componentes del SM eleva el riesgo más que los factores individuales, lo que refuerza la necesidad de abordarlo como una entidad integrada. El análisis revela que ciertas combinaciones de factores del SM influyen significativamente en la incidencia de cáncer. La combinación de bajo colesterol HDL y glucemia elevada es especialmente relevante. En hombres, la asociación más fuerte es "HDL+Glucemia", mientras que en mujeres destaca "HDL+Hipertensión Arterial". En términos de supervivencia, el SM reduce significativamente la RLE tras un diagnóstico de cáncer, con diferencias según el sexo. En hombres, los cánceres de hígado, pulmón y vejiga presentan las mayores reducciones en la RLE, mientras que en mujeres los más afectados son los cánceres ginecológicos, como el de endometrio y mama. Estos hallazgos subrayan la importancia de considerar diferencias biológicas y hormonales en la gestión del cáncer en pacientes con SM. El uso de métricas como los años de vida perdidos (LYL) permite una evaluación más precisa del impacto del SM en la supervivencia. Se observa un aumento en los LYL por cáncer a medida que se incrementa el número de componentes del SM, mientras que los LYL por otras causas disminuyen. Al combinar estas métricas con herramientas como las curvas de Kaplan-Meier, se obtiene una visión detallada del impacto del SM a corto y largo plazo, facilitando estrategias de intervención más personalizadas. Desde una perspectiva de salud pública, estos hallazgos refuerzan la necesidad de estrategias preventivas que aborden el SM en su conjunto. Las diferencias entre hombres y mujeres resaltan la importancia de adaptar las intervenciones según el sexo, considerando variaciones biológicas y de estilo de vida. Asimismo, integrar la salud metabólica en las políticas de prevención del cáncer podría reducir la carga de ambas enfermedades. Esta investigación enfatiza la importancia de la prevención y detección temprana en individuos con SM, dado su impacto en la progresión del cáncer y la reducción de la esperanza de vida. Estrategias como modificaciones en el estilo de vida, tratamiento farmacológico para el control metabólico y monitoreo oncológico temprano pueden ser clave para reducir la mortalidad en este grupo de pacientes. En conclusión, a medida que se incrementa el número de componentes del SM, también aumentan el riesgo y la incidencia de cáncer, así como disminuye la esperanza de vida en personas con diagnóstico oncológico. La combinación de mayor riesgo de cáncer, tanto en hombres como en mujeres, es "HDL+Glucemia+Hipertensión Arterial". Esta tesis aporta evidencia sólida sobre el impacto del SM en la incidencia y progresión del cáncer. Al integrar análisis innovadores con datos poblacionales de alta calidad, este trabajo proporciona una base para mejorar las estrategias de salud pública y las prácticas clínicas, ayudando en última instancia a mitigar el impacto dual del SM y las enfermedades oncológicas.Metabolic Syndrome (MS), characterized by obesity, dyslipidemia, hypertension, and insulin resistance, represents a global public health challenge. This thesis examines its impact on the incidence, survival, and remaining life expectancy (RLE) in 13 types of cancer (colorectal, prostate, liver, bladder, endometrial, pancreatic, breast, lung, kidney, thyroid, Hodgkin's lymphoma, non-Hodgkin's lymphoma, and leukemia). Population data from Catalonia (SIDIAP) and the National Institute of Statistics (INE) were used. Through advanced epidemiological designs, this study provides a robust analysis of these interactions. The results show that MS significantly increases cancer risk, particularly in endometrial, liver, kidney, pancreatic, thyroid, leukemia, bladder, colorectal, non-Hodgkin's lymphoma, lung, and postmenopausal breast cancer. Additionally, the accumulation of MS components raises cancer risk more than individual factors, reinforcing the need to address it as an integrated entity. The analysis reveals that specific combinations of MS factors significantly influence cancer incidence. The combination of low HDL cholesterol and high glucose levels is particularly relevant. In men, the strongest association is "HDL+Glucose", whereas in women, "HDL+Hypertension" stands out. In terms of survival, MS significantly reduces RLE after a cancer diagnosis, with differences based on sex. In men, cancers of the liver, lung, and bladder show the greatest reductions in RLE, while in women, the most affected are gynecological cancers, such as endometrial and breast cancer. These findings highlight the importance of considering biological and hormonal differences in cancer management for MS patients. The use of metrics such as life years lost (LYL) provides a more precise evaluation of MS's impact on survival. An increase in LYL due to cancer is observed as the number of MS components rises, while LYL from other causes decreases. By combining these metrics with tools such as Kaplan-Meier curves, this study offers a detailed view of MS's impact in both the short and long term, facilitating more personalized intervention strategies. From a public health perspective, these findings reinforce the need for preventive strategies that address MS as a whole. The differences observed between men and women highlight the importance of adapting interventions based on sex, considering biological and lifestyle variations. Additionally, integrating metabolic health into cancer prevention policies could reduce the burden of both diseases. This research emphasizes the importance of prevention and early detection in individuals with MS, given its impact on cancer progression and reduced life expectancy. Strategies such as lifestyle modifications, pharmacological treatment for metabolic control, and early oncological monitoring may be key in reducing mortality in this patient group. In conclusion, as the number of MS components increases, so does the risk and incidence of cancer, while life expectancy decreases in individuals with a cancer diagnosis. The highest-risk combination for cancer, in both men and women, is "HDL+Glucose+Hypertension". This thesis provides strong evidence on the impact of MS on cancer incidence and progression. By integrating innovative analyses with high-quality population data, this work establishes a foundation for improving public health strategies and clinical practices, ultimately helping to mitigate the dual impact of MS and oncological diseases
Addressing bias in statistical inference based on epidemiological registry data
Full text linkHospital’s registry data is a widely used resource in Nordic countries to estimate parameters of interest in the
public health and in epidemiology. This data allows the researcher to have an unbiased representation of the
population, since it is collected for all the individuals that visit the hospitals in the country, and it is stored in
databases that are available for the researchers. Despite being a powerful tool, this data has some drawbacks
that have to be taken into account before making the study.
This project aims to expose the problems that arise when hospital’s registers are used for estimating the
incidence of a disease, and explain what it is usually done to correct (or partially correct) them.
First, we provide an introduction (Chapter 1) where we discuss the importance of getting good estimations
to study the incidence of mental disorders, why registers are a powerful tool to make population-wide research
and the main problem we encounter in this type of data: the delayed entries.
We continue with a summary on the methodologies that will be used during the rest of the project (Chapter
2). In Chapter 3 we develop further the strengths and limitations of using registration data to estimate the
incidence of a disease, providing a self-derived theoretical description of the delayed-entries problematic.
In this chapter we also include the methodology that it is usually applied to deal with this problematic: the
washout-period method, and we relate this methodology with the provided theoretical description. We finish
the chapter with an introduction to the history of the registration system in Denmark and its structure.
Lastly, we provide a simulation study based on the data of women diagnosed with depression in Denmark.
We have simulated a hospital register and studied the incidence in terms of the cumulative incidence function
applying the washout period method
Selecting the primary endpoint in a randomized clinical trial: the ARE method
Full text linkThe decision on the primary endpoint in a randomized clinical trial is of paramount importance and the combination of several endpoints might be a reasonable choice. Gómez and Lagakos (2013) have developed a method that quantifies how much more efficient it could be to use a composite instead of an individual relevant endpoint. From the information provided by the frequencies of observing the component endpoints in the control group and by the relative treatment effects on each individual endpoint, the asymptotic relative efficiency (ARE) can be computed. This article presents the applicability of the ARE method as a practical and objective tool to evaluate which components, among the plausible ones, are more efficient in the construction of the primary endpoint. The method is illustrated with two real cardiovascular clinical trials and is extended to allow for different dependence structures between the times to the individual endpoints. The influence of this choice on the recommendation on whether or not to use the composite endpoint as the primary endpoint for the investigation is studied. We conclude that the recommendation between using the composite or the relevant endpoint only depends on the frequencies of the endpoints and the relative effects of the treatment.Peer ReviewedPostprint (author's final draft
Effect of changing the copular when choosing the primary endpoint in a Randomized Clinical Trial
Full text linkPeer ReviewedPostprint (published version
Selecting the primary endpoint in a randomized clinical trial: the ARE method
No full textThe decision on the primary endpoint in a randomized clinical trial is of paramount importance and the combination of several endpoints might be a reasonable choice. Gómez and Lagakos (2013) have developed a method that quantifies how much more efficient it could be to use a composite instead of an individual relevant endpoint. From the information provided by the frequencies of observing the component endpoints in the control group and by the relative treatment effects on each individual endpoint, the asymptotic relative efficiency (ARE) can be computed. This article presents the applicability of the ARE method as a practical and objective tool to evaluate which components, among the plausible ones, are more efficient in the construction of the primary endpoint. The method is illustrated with two real cardiovascular clinical trials and is extended to allow for different dependence structures between the times to the individual endpoints. The influence of this choice on the recommendation on whether or not to use the composite endpoint as the primary endpoint for the investigation is studied. We conclude that the recommendation between using the composite or the relevant endpoint only depends on the frequencies of the endpoints and the relative effects of the treatment.Peer Reviewe
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