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Nguyen B, Clare P, Mielke GI, Brown WJ, Ding D. Physical activity across midlife and health-related quality of life in Australian women: A target trial emulation using a longitudinal cohort. PLoS Med 2024; 21:e1004384. [PMID: 38696367 PMCID: PMC11065283 DOI: 10.1371/journal.pmed.1004384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 03/25/2024] [Indexed: 05/04/2024] Open
Abstract
BACKGROUND There is little long-term causal evidence on the effect of physical activity on health-related quality of life. This study aimed to examine the associations between longitudinal patterns of physical activity over 15 years and health-related quality of life in both the physical and mental health domains, in a cohort of middle-aged Australian women. METHODS AND FINDINGS We used data collected at 3-year intervals (1998 to 2019) from 11,336 participants in the Australian Longitudinal Study on Women's Health (ALSWH) (1946 to 1951 birth cohort). Primary outcomes were the physical (PCS) and mental health component summary (MCS) scores (range from 0 to 100; higher scores indicate higher perceived physical/mental health) from the SF-36 in 2019 (when women aged 68 to 73 years). Using target trial emulation to imitate a randomized controlled trial (RCT), we tested 2 interventions: (1) meeting the World Health Organization (WHO) physical activity guidelines consistently throughout the 15-year "exposure period" (2001 to 2016; when women aged 50-55 to 65-70 years; physical activity assessed every 3 years); and (2) not meeting the guidelines at the beginning of the exposure period but starting to first meet the guidelines at age 55, 60, or 65; against the control of not meeting the guidelines throughout the exposure period. Analysis controlled for confounding using marginal structural models which were adjusted for sociodemographic and health variables and conditions. Consistent adherence to guidelines during the exposure period (PCS: 46.93 [99.5% confidence interval [CI]: 46.32, 47.54]) and first starting to meet the guidelines at age 55 (PCS: 46.96 [99.5% CI: 45.53, 48.40]) were associated with three-point higher PCS (mean score difference: 3.0 [99.5% CI: 1.8, 4.1] and 3.0 [99.5% CI:1.2, 4.8]) than consistent non-adherence (PCS: 43.90 [99.5% CI: 42.79, 45.01]). We found a similar pattern for most SF-36 subscales but no significant effects of the interventions on MCS. The main limitations of the study were that it may not account for all underlying health conditions and/or other unmeasured or insufficiently measured confounders, the use of self-reported physical activity and that findings may not be generalizable to all mid-age women. CONCLUSIONS Results from the emulated RCT suggest women should be active throughout mid-age, ideally increasing activity levels to meet the guidelines by age 55, to gain the most benefits for physical health in later life.
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Affiliation(s)
- Binh Nguyen
- Prevention Research Collaboration, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Camperdown, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, Australia
| | - Philip Clare
- Prevention Research Collaboration, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Camperdown, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, Australia
- National Drug and Alcohol Research Centre, UNSW Sydney, Sydney, Australia
| | - Gregore I. Mielke
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Wendy J. Brown
- Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Australia
- School of Human Movement and Nutrition Sciences, Faculty of Health and Behavioural Sciences, University of Queensland, Brisbane, Australia
| | - Ding Ding
- Prevention Research Collaboration, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Camperdown, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, Australia
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Cavallaro F, Clery A, Gilbert R, van der Meulen J, Kendall S, Kennedy E, Phillips C, Harron K. Evaluating the real-world implementation of the Family Nurse Partnership in England: a data linkage study. HEALTH AND SOCIAL CARE DELIVERY RESEARCH 2024; 12:1-223. [PMID: 38784984 DOI: 10.3310/bvdw6447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2024]
Abstract
Background/objectives The Family Nurse Partnership is an intensive home visiting programme for adolescent mothers. We aimed to evaluate the effectiveness of the Family Nurse Partnership on outcomes up to age 7 using national administrative data. Design We created a linked cohort of all mothers aged 13-19 using data from health, educational and children's social care and defined mothers enrolled in the Family Nurse Partnership or not using Family Nurse Partnership system data. Propensity scores were used to create matched groups for analysis. Setting One hundred and thirty-six local authorities in England with active Family Nurse Partnership sites between 2010 and 2017. Participants Mothers aged 13-19 at last menstrual period with live births between April 2010 and March 2019, living in a Family Nurse Partnership catchment area and their firstborn child(ren). Interventions The Family Nurse Partnership includes up to 64 home visits by a family nurse from early pregnancy until the child's second birthday and is combined with usual health and social care. Controls received usual health and social care. Main outcome measures Indicators of child maltreatment (hospital admissions for injury/maltreatment, referral to social care services); child health and development (hospital utilisation and education) outcomes and maternal hospital utilisation and educational outcomes up to 7 years following birth. Data sources Family Nurse Partnership Information System, Hospital Episode Statistics, National Pupil Database. Results Of 110,520 eligible mothers, 25,680 (23.2%) were enrolled in the Family Nurse Partnership. Enrolment rates varied across 122 sites (range: 11-68%). Areas with more eligible mothers had lower enrolment rates. Enrolment was higher among mothers aged 13-15 (52%), than 18-19 year-olds (21%). Indicators of child maltreatment: we found no evidence of an association between the Family Nurse Partnership and indicators of child maltreatment, except for an increased rate of unplanned admissions for maltreatment/injury-related diagnoses up to age 2 for children born to Family Nurse Partnership mothers (6.6% vs. 5.7%, relative risk 1.15; 95% confidence interval 1.07 to 1.24). Child health and developmental outcomes: there was weak evidence that children born to Family Nurse Partnership mothers were more likely to achieve a Good Level of Development at age 5 (57.5% vs. 55.4%, relative risk 1.05; 95% confidence interval 1.00 to 1.09). Maternal outcomes: There was some evidence that Family Nurse Partnership mothers were less likely to have a subsequent delivery within 18 months of the index birth (8.4% vs. 9.3%, relative risk 0.92; 95% confidence interval 0.88 to 0.97). Younger and more vulnerable mothers received higher numbers of visits and were more likely to achieve fidelity targets. Meeting the fidelity targets was associated with some outcomes. Limitations Bias by indication and variation in the intervention and usual care over time and between areas may have limited our ability to detect effects. Multiple testing may have led to spurious, significant results. Conclusions This study supports findings from evaluations of the Family Nurse Partnership showing no evidence of benefit for maltreatment outcomes measured in administrative data. Amongst all the outcomes measured, we found weak evidence that the Family Nurse Partnership was associated with improvements in child development at school entry, a reduction in rapid repeat pregnancies and evidence of increased healthcare-seeking in the mother and child. Future work Future evaluations should capture better measures of Family Nurse Partnership interventions and usual care, more information on maternal risk factors and additional outcomes relating to maternal well-being. Study registration The study is registered as NIHR CRN Portfolio (42900). Funding This award was funded by the National Institute of Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/99/19) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 11. See the NIHR Funding and Awards website for further award information.
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Affiliation(s)
| | - Amanda Clery
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - Ruth Gilbert
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - Jan van der Meulen
- UCL Great Ormond Street Institute of Child Health, London, UK
- London School of Hygiene and Tropical Medicine, London, UK
| | - Sally Kendall
- UCL Great Ormond Street Institute of Child Health, London, UK
- Centre for Health Services Studies, University of Kent, Canterbury, UK
| | - Eilis Kennedy
- UCL Great Ormond Street Institute of Child Health, London, UK
- Eilis Kennedy, Tavistock and Portman NHS Foundation Trust, London, UK
| | - Catherine Phillips
- UCL Great Ormond Street Institute of Child Health, London, UK
- Centre for Health Services Studies, University of Kent, Canterbury, UK
| | - Katie Harron
- UCL Great Ormond Street Institute of Child Health, London, UK
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Goldfeld S, Downes M, Gray S, Pham C, Guo S, O'Connor E, Redmond G, Azpitarte F, Badland H, Woolfenden S, Williams K, Priest N, O'Connor M, Moreno-Betancur M. Household income supplements in early childhood to reduce inequities in children's development. Soc Sci Med 2024; 340:116430. [PMID: 38048739 DOI: 10.1016/j.socscimed.2023.116430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 10/03/2023] [Accepted: 11/12/2023] [Indexed: 12/06/2023]
Abstract
BACKGROUND Early childhood interventions have the potential to reduce children's developmental inequities. We aimed to estimate the extent to which household income supplements for lower-income families in early childhood could close the gap in children's developmental outcomes and parental mental health. METHODS Data were drawn from a nationally representative birth cohort, the Longitudinal Study of Australian Children (N = 5107), which commenced in 2004 and conducted follow-ups every two years. Exposure was annual household income (0-1 year). Outcomes were children's developmental outcomes, specifically social-emotional, physical functioning, and learning (bottom 15% versus top 85%) at 4-5 years, and an intermediate outcome, parental mental health (poor versus good) at 2-3 years. We modelled hypothetical interventions that provided a fixed-income supplement to lower-income families with a child aged 0-1 year. Considering varying eligibility scenarios and amounts motivated by actual policies in the Australian context, we estimated the risk of poor outcomes for eligible families under no intervention and the hypothetical intervention using marginal structural models. The reduction in risk under intervention relative to no intervention was estimated. RESULTS A single hypothetical supplement of AU$26,000 (equivalent to ∼USD$17,350) provided to lower-income families (below AU$56,137 (∼USD$37,915) per annum) in a child's first year of life demonstrated an absolute reduction of 2.7%, 1.9% and 2.6% in the risk of poor social-emotional, physical functioning and learning outcomes in children, respectively (equivalent to relative reductions of 12%, 10% and 11%, respectively). The absolute reduction in risk of poor mental health in eligible parents was 1.0%, equivalent to a relative reduction of 7%. Benefits were similar across other income thresholds used to assess eligibility (range, AU$73,329-$99,864). CONCLUSIONS Household income supplements provided to lower-income families may benefit children's development and parental mental health. This intervention should be considered within a social-ecological approach by stacking complementary interventions to eliminate developmental inequities.
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Affiliation(s)
- Sharon Goldfeld
- Centre for Community Child Health, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Australia; Department of Pediatrics, University of Melbourne, Melbourne, Australia.
| | - Marnie Downes
- Department of Pediatrics, University of Melbourne, Melbourne, Australia; Clinical Epidemiology and Biostatistics Unit, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Sarah Gray
- Centre for Community Child Health, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Australia; Department of Pediatrics, University of Melbourne, Melbourne, Australia
| | - Cindy Pham
- Centre for Community Child Health, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Australia; Department of Pediatrics, University of Melbourne, Melbourne, Australia
| | - Shuaijun Guo
- Centre for Community Child Health, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Australia; Department of Pediatrics, University of Melbourne, Melbourne, Australia
| | - Elodie O'Connor
- Centre for Community Child Health, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Australia; Department of Pediatrics, University of Melbourne, Melbourne, Australia
| | - Gerry Redmond
- College of Business, Government and Law, Flinders University, Adelaide, Australia
| | - Francisco Azpitarte
- School of Social Sciences, Loughborough University, Loughborough, United Kingdom
| | - Hannah Badland
- Social and Global Studies Centre, RMIT University, Melbourne, Australia
| | - Sue Woolfenden
- Sydney Medical School, The Faculty of Medicine and Health, University of Sydney, Australia; Discipline of Pediatrics, University of New South Wales, Sydney, Australia
| | - Katrina Williams
- Department of Pediatrics, University of Melbourne, Melbourne, Australia; Department of Pediatrics, Monash University, Melbourne, Australia; Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia
| | - Naomi Priest
- Centre for Community Child Health, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Australia; Centre for Social Research & Methods, The Australian National University, Canberra, Australia
| | - Meredith O'Connor
- Department of Pediatrics, University of Melbourne, Melbourne, Australia; Melbourne Children's LifeCourse Initiative, Murdoch Children's Research Institute, Melbourne, Australia; Faculty of Education, University of Melbourne, Melbourne, Australia
| | - Margarita Moreno-Betancur
- Department of Pediatrics, University of Melbourne, Melbourne, Australia; Clinical Epidemiology and Biostatistics Unit, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Australia
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Smith MJ, Phillips RV, Luque-Fernandez MA, Maringe C. Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review. Ann Epidemiol 2023; 86:34-48.e28. [PMID: 37343734 DOI: 10.1016/j.annepidem.2023.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 05/24/2023] [Accepted: 06/06/2023] [Indexed: 06/23/2023]
Abstract
PURPOSE The targeted maximum likelihood estimation (TMLE) statistical data analysis framework integrates machine learning, statistical theory, and statistical inference to provide a least biased, efficient, and robust strategy for estimation and inference of a variety of statistical and causal parameters. We describe and evaluate the epidemiological applications that have benefited from recent methodological developments. METHODS We conducted a systematic literature review in PubMed for articles that applied any form of TMLE in observational studies. We summarized the epidemiological discipline, geographical location, expertize of the authors, and TMLE methods over time. We used the Roadmap of Targeted Learning and Causal Inference to extract key methodological aspects of the publications. We showcase the contributions to the literature of these TMLE results. RESULTS Of the 89 publications included, 33% originated from the University of California at Berkeley, where the framework was first developed by Professor Mark van der Laan. By 2022, 59% of the publications originated from outside the United States and explored up to seven different epidemiological disciplines in 2021-2022. Double-robustness, bias reduction, and model misspecification were the main motivations that drew researchers toward the TMLE framework. Through time, a wide variety of methodological, tutorial, and software-specific articles were cited, owing to the constant growth of methodological developments around TMLE. CONCLUSIONS There is a clear dissemination trend of the TMLE framework to various epidemiological disciplines and to increasing numbers of geographical areas. The availability of R packages, publication of tutorial papers, and involvement of methodological experts in applied publications have contributed to an exponential increase in the number of studies that understood the benefits and adoption of TMLE.
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Affiliation(s)
- Matthew J Smith
- Inequalities in Cancer Outcomes Network, London School of Hygiene and Tropical Medicine, London, UK.
| | - Rachael V Phillips
- Division of Biostatistics, School of Public Health, University of California at Berkeley, Berkeley, CA
| | - Miguel Angel Luque-Fernandez
- Inequalities in Cancer Outcomes Network, London School of Hygiene and Tropical Medicine, London, UK; Department of Statistics and Operations Research, University of Granada, Granada, Spain
| | - Camille Maringe
- Inequalities in Cancer Outcomes Network, London School of Hygiene and Tropical Medicine, London, UK
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Price A, Bryson H, Mensah FK, Kenny B, Wang X, Orsini F, Gold L, Kemp L, Bruce T, Dakin P, Noble K, Makama M, Goldfeld S. Embedding nurse home visiting in universal healthcare: 6-year follow-up of a randomised trial. Arch Dis Child 2023; 108:824-832. [PMID: 37399321 DOI: 10.1136/archdischild-2023-325662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 06/09/2023] [Indexed: 07/05/2023]
Abstract
OBJECTIVE Nurse home visiting (NHV) is designed to redress child and maternal health inequities. Of the previous trials to investigate NHV benefits beyond preschool, none were designed for populations with universal healthcare. To address this evidence gap, we investigated whether the Australian 'right@home' NHV programme improved child and maternal outcomes when children turned 6 and started school. METHODS A screening survey identified pregnant women experiencing adversity from antenatal clinics across two states (Victoria, Tasmania). 722 were randomised: 363 to the right@home programme (25 visits promoting parenting and home learning environment) and 359 to usual care. Child measures at 6 years (first school year): Strengths and Difficulties Questionnaire (SDQ), Social Skills Improvement System (SSIS), Childhood Executive Functioning Inventory (CHEXI) (maternal/teacher-reported); general health and paediatric quality of life (maternal-reported) and reading/school adaptation items (teacher-reported). Maternal measures: Personal Well-being Index (PWI), Depression Anxiety Stress Scales, warm/hostile parenting, Child-Parent Relationship Scale (CPRS), emotional abuse and health/efficacy items. Following best-practice methods for managing missing data, outcomes were compared between groups (intention-to-treat) using regression models adjusted for stratification factors, baseline variables and clustering (nurse/site level). RESULTS Mothers reported on 338 (47%) children, and teachers on 327 (45%). Patterns of group differences favoured the programme arm, with small benefits (effect sizes ranging 0.15-0.26) evident for SDQ, SSIS, CHEXI, PWI, warm parenting and CPRS. CONCLUSIONS Four years after completing the right@home programme, benefits were evident across home and school contexts. Embedding NHV in universal healthcare systems from pregnancy can offer long-term benefits for families experiencing adversity. TRIAL REGISTRATION NUMBER ISRCTN89962120.
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Affiliation(s)
- Anna Price
- Centre for Community Child Health, The Royal Children's Hospital, Parkville, Vic, Australia
- Population Health, Murdoch Children's Research Institute, Parkville, Vic, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Vic, Australia
| | - Hannah Bryson
- Centre for Community Child Health, The Royal Children's Hospital, Parkville, Vic, Australia
- Population Health, Murdoch Children's Research Institute, Parkville, Vic, Australia
| | - Fiona K Mensah
- Population Health, Murdoch Children's Research Institute, Parkville, Vic, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Vic, Australia
| | - Bridget Kenny
- Centre for Community Child Health, The Royal Children's Hospital, Parkville, Vic, Australia
- Population Health, Murdoch Children's Research Institute, Parkville, Vic, Australia
| | - Xiaofang Wang
- Clinical Epidemiology and Biostatistics Unit, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Melbourne Children's Trials Centre, Murdoch Children's Research Institute, Parkville, Vic, Australia
| | - Francesca Orsini
- Clinical Epidemiology and Biostatistics Unit, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Melbourne Children's Trials Centre, Murdoch Children's Research Institute, Parkville, Vic, Australia
| | - Lisa Gold
- School of Health and Social Development, Deakin University, Geelong, Vic, Australia
| | - Lynn Kemp
- Ingham Institute, Western Sydney University, Penrith South, New South Wales, Australia
| | - Tracey Bruce
- Ingham Institute, Western Sydney University, Penrith South, New South Wales, Australia
| | - Penny Dakin
- Policy & Projects, Australian Research Alliance for Children and Youth, Canberra, Australian Capital Territory, Australia
| | - Kristy Noble
- Policy & Projects, Australian Research Alliance for Children and Youth, Canberra, Australian Capital Territory, Australia
| | - Maureen Makama
- Centre for Community Child Health, The Royal Children's Hospital, Parkville, Vic, Australia
- Population Health, Murdoch Children's Research Institute, Parkville, Vic, Australia
| | - Sharon Goldfeld
- Centre for Community Child Health, The Royal Children's Hospital, Parkville, Vic, Australia
- Population Health, Murdoch Children's Research Institute, Parkville, Vic, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Vic, Australia
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Hansford HJ, Cashin AG, Jones MD, Swanson SA, Islam N, Douglas SRG, Rizzo RRN, Devonshire JJ, Williams SA, Dahabreh IJ, Dickerman BA, Egger M, Garcia-Albeniz X, Golub RM, Lodi S, Moreno-Betancur M, Pearson SA, Schneeweiss S, Sterne JAC, Sharp MK, Stuart EA, Hernán MA, Lee H, McAuley JH. Reporting of Observational Studies Explicitly Aiming to Emulate Randomized Trials: A Systematic Review. JAMA Netw Open 2023; 6:e2336023. [PMID: 37755828 PMCID: PMC10534275 DOI: 10.1001/jamanetworkopen.2023.36023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/22/2023] [Indexed: 09/28/2023] Open
Abstract
Importance Observational (nonexperimental) studies that aim to emulate a randomized trial (ie, the target trial) are increasingly informing medical and policy decision-making, but it is unclear how these studies are reported in the literature. Consistent reporting is essential for quality appraisal, evidence synthesis, and translation of evidence to policy and practice. Objective To assess the reporting of observational studies that explicitly aimed to emulate a target trial. Evidence Review We searched Medline, Embase, PsycINFO, and Web of Science for observational studies published between March 2012 and October 2022 that explicitly aimed to emulate a target trial of a health or medical intervention. Two reviewers double-screened and -extracted data on study characteristics, key predefined components of the target trial protocol and its emulation (eligibility criteria, treatment strategies, treatment assignment, outcome[s], follow-up, causal contrast[s], and analysis plan), and other items related to the target trial emulation. Findings A total of 200 studies that explicitly aimed to emulate a target trial were included. These studies included 26 subfields of medicine, and 168 (84%) were published from January 2020 to October 2022. The aim to emulate a target trial was explicit in 70 study titles (35%). Forty-three studies (22%) reported use of a published reporting guideline (eg, Strengthening the Reporting of Observational Studies in Epidemiology). Eighty-five studies (43%) did not describe all key items of how the target trial was emulated and 113 (57%) did not describe the protocol of the target trial and its emulation. Conclusion and Relevance In this systematic review of 200 studies that explicitly aimed to emulate a target trial, reporting of how the target trial was emulated was inconsistent. A reporting guideline for studies explicitly aiming to emulate a target trial may improve the reporting of the target trial protocols and other aspects of these emulation attempts.
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Affiliation(s)
- Harrison J. Hansford
- School of Health Sciences, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, Australia
| | - Aidan G. Cashin
- School of Health Sciences, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, Australia
| | - Matthew D. Jones
- School of Health Sciences, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, Australia
| | - Sonja A. Swanson
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania
- CAUSALab, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Nazrul Islam
- Oxford Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom
- Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Susan R. G. Douglas
- School of Health Sciences, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
| | - Rodrigo R. N. Rizzo
- School of Health Sciences, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, Australia
| | - Jack J. Devonshire
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, Australia
| | - Sam A. Williams
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, Australia
| | - Issa J. Dahabreh
- CAUSALab, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Barbra A. Dickerman
- CAUSALab, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Matthias Egger
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Centre for Infectious Disease Epidemiology and Research, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Xabier Garcia-Albeniz
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- RTI Health Solutions, Barcelona, Spain
| | - Robert M. Golub
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Sara Lodi
- CAUSALab, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Margarita Moreno-Betancur
- Clinical Epidemiology & Biostatistics Unit, Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
| | - Sallie-Anne Pearson
- School of Population Health, Faculty of Medicine and Health, UNSW Sydney, New South Wales, Australia
| | - Sebastian Schneeweiss
- Division of Pharmacoepidemiology, Department of Medicine, Brigham & Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jonathan A. C. Sterne
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- NIHR Bristol Biomedical Research Centre, Bristol, United Kingdom
- Health Data Research UK South-West, Bristol, United Kingdom
| | - Melissa K. Sharp
- Department of Public Health and Epidemiology, RCSI University of Medicine and Health Sciences, Dublin, Ireland
| | - Elizabeth A. Stuart
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Miguel A. Hernán
- CAUSALab, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Hopin Lee
- University of Exeter Medical School, Exeter, United Kingdom
| | - James H. McAuley
- School of Health Sciences, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, Australia
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