Antipsychotic drugs in first-episode psychosis: A target trial emulation in the FEP-CAUSAL Collaboration
Am J Epidemiol. 2024 Apr 3:kwae029. doi: 10.1093/aje/kwae029. Online ahead of print.ABSTRACTGood adherence to antipsychotic therapy helps prevent relapses in First Episode Psychosis (FEP). We used data from the FEP-CAUSAL Collaboration, an international consortium of observational cohorts to emulate a target trial comparing antipsychotics with treatment discontinuation as the primary outcome. Other outcomes included all-cause hospitalization. We benchmarked our results to estimates from EUFEST, a randomized trial conducted in the 2000s. We included 1097 patients with a psychotic disorder and less than 2 years since psychos...
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Alejandro G Szmulewicz Gonzalo Mart ínez-Alés Roger Logan Maria Ferrara Christian Kelly Diane Fredrikson Juan Gago Sarah Conderino Covadonga M D íaz-Caneja Joaqu ín Galvañ Lorna Thorpe Vinod Srihari Lakshmi Yatham Deepak K Sarpal Ann K Shinn Celso Ar Source Type: research
Invited Commentary: Where Do the Causal DAGs Come From?
In conclusion I find that expert- or theory-driven model building might benefit from some more checking against the data and causal discovery could bring new ideas into old theories.PMID:38576172 | DOI:10.1093/aje/kwae028 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Vanessa Didelez Source Type: research
Using unsupervised clustering approaches to identify common mental health profiles and associated mental healthcare service use patterns in Ontario, Canada
This study aims to use unsupervised clustering approaches to identify multidimensional mental health profiles that exist in the population, and their associated service use patterns. The data source for this study is the 2012 Canadian Community Health Survey- Mental Health linked to administrative healthcare data holdings, included were all Ontario adult respondents. We used a Partioning Around Medoids clustering algorithm with Gower's proximity to identify groups with distinct combinations of mental health indicators and described them by their sociodemographic and service use characteristics. We identified four groups wi...
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Christa Orchard Elizabeth Lin Laura Rosella Peter M Smith Source Type: research
Multiple Prenatal Exposures and Acute Care Clinical Encounters for Asthma among Children Born to Mothers Living near a Superfund Site
We examined the association between prenatal exposures and the risk of childhood asthma acute care clinical encounters (hospitalization, emergency department visit, observational stay) using conditional logistic regression with a multivariable smooth to model the interaction between continuous variables, adjusted for maternal characteristics, and stratified by sex. All births near the New Bedford Harbor (NBH) Superfund site (2000-2006) were followed through 2011 using the Massachusetts Pregnancy to Early Life Longitudinal data system to identify children ages 5-11 with asthma acute care clinical encounters (265 cases among...
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Roxana Khalili Jesselle M Legaspi M Patricia Fabian Jonathan I Levy Susan A Korrick Ver ónica M Vieira Source Type: research
Characterizing multimorbidity in ALIVE: Comparing single and ensemble clustering methods
Am J Epidemiol. 2024 Apr 3:kwae031. doi: 10.1093/aje/kwae031. Online ahead of print.ABSTRACTMultimorbidity, defined as having 2 or more chronic conditions, is a growing public health concern, but research in this area is complicated by the fact that multimorbidity is a highly heterogenous outcome. Individuals in a sample may have a differing number and varied combinations of conditions. Clustering methods, such as unsupervised machine learning algorithms, may allow us to tease out the unique multimorbidity phenotypes. However, many clustering methods exist and choosing which to use is challenging because we do not know the...
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Jacqueline E Rudolph Bryan Lau Becky L Genberg Jing Sun Gregory D Kirk Shruti H Mehta Source Type: research
Avanzando Caminos (Leading Pathways): Design and Procedures of The Hispanic/Latino Cancer Survivorship Study
CONCLUSIONS: Avanzando Caminos will fill critical gaps in knowledge to guide future secondary and tertiary prevention efforts to mitigate cancer disparities and optimize health-related quality of life among Hispanic/Latino cancer survivors.PMID:38576195 | DOI:10.1093/aje/kwae033 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Frank J Penedo Patricia I Moreno Magela Pons Paulo S Pinheiro Michael H Antoni Gilberto Lopes Carmen Calfa Patricia Chalela Luz Garcini Chen-Pin Wang Yidong Chen Adolfo Diaz Steve Cole Amelie G Ramirez Source Type: research
Power to the People: Why person-generated health data is important for pharmacoepidemiology
Am J Epidemiol. 2024 Apr 3:kwae035. doi: 10.1093/aje/kwae035. Online ahead of print.ABSTRACTPerson-generated health data (PGHD) are valuable to study outcomes relevant to everyday living, to obtain information not otherwise available, for long-term follow-up and in situations where decisions cannot wait for traditional clinical research to be completed. While there is no dispute that these data are subject to bias, insights gained may be better than an information void, provided the biases are understood and acknowledged. People will share information known uniquely to them about exposures that may affect drug tolerance, s...
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Nancy A Dreyer Stella C F Blackburn Source Type: research
Gallbladder cancer mortality in Chile: Has the government program targeting young gallstone patients had an impact?
Am J Epidemiol. 2024 Apr 3:kwae027. doi: 10.1093/aje/kwae027. Online ahead of print.NO ABSTRACTPMID:38576158 | DOI:10.1093/aje/kwae027 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Vicente Cid Claudio Vargas Iris Delgado Mauricio Apablaza Meredith S Shiels Allan Hildesheim Jill Koshiol Catterina Ferreccio Source Type: research
Antipsychotic drugs in first-episode psychosis: A target trial emulation in the FEP-CAUSAL Collaboration
Am J Epidemiol. 2024 Apr 3:kwae029. doi: 10.1093/aje/kwae029. Online ahead of print.ABSTRACTGood adherence to antipsychotic therapy helps prevent relapses in First Episode Psychosis (FEP). We used data from the FEP-CAUSAL Collaboration, an international consortium of observational cohorts to emulate a target trial comparing antipsychotics with treatment discontinuation as the primary outcome. Other outcomes included all-cause hospitalization. We benchmarked our results to estimates from EUFEST, a randomized trial conducted in the 2000s. We included 1097 patients with a psychotic disorder and less than 2 years since psychos...
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Alejandro G Szmulewicz Gonzalo Mart ínez-Alés Roger Logan Maria Ferrara Christian Kelly Diane Fredrikson Juan Gago Sarah Conderino Covadonga M D íaz-Caneja Joaqu ín Galvañ Lorna Thorpe Vinod Srihari Lakshmi Yatham Deepak K Sarpal Ann K Shinn Celso Ar Source Type: research
Invited Commentary: Where Do the Causal DAGs Come From?
In conclusion I find that expert- or theory-driven model building might benefit from some more checking against the data and causal discovery could bring new ideas into old theories.PMID:38576172 | DOI:10.1093/aje/kwae028 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Vanessa Didelez Source Type: research
Using unsupervised clustering approaches to identify common mental health profiles and associated mental healthcare service use patterns in Ontario, Canada
This study aims to use unsupervised clustering approaches to identify multidimensional mental health profiles that exist in the population, and their associated service use patterns. The data source for this study is the 2012 Canadian Community Health Survey- Mental Health linked to administrative healthcare data holdings, included were all Ontario adult respondents. We used a Partioning Around Medoids clustering algorithm with Gower's proximity to identify groups with distinct combinations of mental health indicators and described them by their sociodemographic and service use characteristics. We identified four groups wi...
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Christa Orchard Elizabeth Lin Laura Rosella Peter M Smith Source Type: research
Multiple Prenatal Exposures and Acute Care Clinical Encounters for Asthma among Children Born to Mothers Living near a Superfund Site
We examined the association between prenatal exposures and the risk of childhood asthma acute care clinical encounters (hospitalization, emergency department visit, observational stay) using conditional logistic regression with a multivariable smooth to model the interaction between continuous variables, adjusted for maternal characteristics, and stratified by sex. All births near the New Bedford Harbor (NBH) Superfund site (2000-2006) were followed through 2011 using the Massachusetts Pregnancy to Early Life Longitudinal data system to identify children ages 5-11 with asthma acute care clinical encounters (265 cases among...
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Roxana Khalili Jesselle M Legaspi M Patricia Fabian Jonathan I Levy Susan A Korrick Ver ónica M Vieira Source Type: research
Characterizing multimorbidity in ALIVE: Comparing single and ensemble clustering methods
Am J Epidemiol. 2024 Apr 3:kwae031. doi: 10.1093/aje/kwae031. Online ahead of print.ABSTRACTMultimorbidity, defined as having 2 or more chronic conditions, is a growing public health concern, but research in this area is complicated by the fact that multimorbidity is a highly heterogenous outcome. Individuals in a sample may have a differing number and varied combinations of conditions. Clustering methods, such as unsupervised machine learning algorithms, may allow us to tease out the unique multimorbidity phenotypes. However, many clustering methods exist and choosing which to use is challenging because we do not know the...
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Jacqueline E Rudolph Bryan Lau Becky L Genberg Jing Sun Gregory D Kirk Shruti H Mehta Source Type: research
Avanzando Caminos (Leading Pathways): Design and Procedures of The Hispanic/Latino Cancer Survivorship Study
CONCLUSIONS: Avanzando Caminos will fill critical gaps in knowledge to guide future secondary and tertiary prevention efforts to mitigate cancer disparities and optimize health-related quality of life among Hispanic/Latino cancer survivors.PMID:38576195 | DOI:10.1093/aje/kwae033 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Frank J Penedo Patricia I Moreno Magela Pons Paulo S Pinheiro Michael H Antoni Gilberto Lopes Carmen Calfa Patricia Chalela Luz Garcini Chen-Pin Wang Yidong Chen Adolfo Diaz Steve Cole Amelie G Ramirez Source Type: research
Power to the People: Why person-generated health data is important for pharmacoepidemiology
Am J Epidemiol. 2024 Apr 3:kwae035. doi: 10.1093/aje/kwae035. Online ahead of print.ABSTRACTPerson-generated health data (PGHD) are valuable to study outcomes relevant to everyday living, to obtain information not otherwise available, for long-term follow-up and in situations where decisions cannot wait for traditional clinical research to be completed. While there is no dispute that these data are subject to bias, insights gained may be better than an information void, provided the biases are understood and acknowledged. People will share information known uniquely to them about exposures that may affect drug tolerance, s...
Source: Am J Epidemiol - April 5, 2024 Category: Epidemiology Authors: Nancy A Dreyer Stella C F Blackburn Source Type: research
