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Schwarz S, Braitmaier M, Pox C, Kollhorst B, Didelez V, Haug U. 13-Year colorectal cancer risk after lower-quality, higher-quality and no screening colonoscopy: a cohort study. J Clin Epidemiol 2024; 176:111571. [PMID: 39447995 DOI: 10.1016/j.jclinepi.2024.111571] [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: 12/11/2023] [Revised: 10/07/2024] [Accepted: 10/10/2024] [Indexed: 10/26/2024]
Abstract
OBJECTIVES A lower-quality colonoscopy has been shown to be less effective in reducing colorectal cancer (CRC) incidence than a higher-quality colonoscopy, but the comparison with no-screening colonoscopy (noSC) is lacking. We aimed to compare the 13-year risk of developing CRC between persons with I) a higher-quality screening colonoscopy (higherQualSC), II) a lower-quality screening colonoscopy (lowerQualSC), and III) without a screening colonoscopy. STUDY DESIGN AND SETTING A health-care database (∼20% of the German population) was used to emulate a target trial with three arms: higherQualSC vs lowerQualSC vs noSC at baseline. The quality of screening colonoscopy was categorized based on the polyp detection rate of the examining physician (cut-off: 21.8%). We included persons aged 55-69 years at average CRC risk and CRC screening naïve at baseline. We estimated adjusted cumulative CRC incidence over 13 years of follow-up. RESULTS The higherQualSC arm comprised 142,960 persons, the lowerQualSC arm 62,338 persons, and the noSC arm 124,040 persons. The adjusted 13-year CRC risk was 1.77% in the higherQualSC arm, 2.09% in the lowerQualSC arm, and 2.74% in the noSC arm. Compared to the noSC arm, the adjusted relative risk was 0.76 (95% CI: 0.70-0.84) in the lowerQualSC arm and 0.65 (95% CI: 0.60-0.69) in the higherQualSC arm. CONCLUSION Our study shows that a lowerQualSC is also effective in reducing CRC incidence compared to noSC. However, the effect is about one-third less than that of a higherQualSC.
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Affiliation(s)
- Sarina Schwarz
- Department of Clinical Epidemiology, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
| | - Malte Braitmaier
- Department of Biometry and Data Management, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Christian Pox
- Department of Medicine, St. Joseph-Stift Bremen, Bremen, Germany
| | - Bianca Kollhorst
- Department of Biometry and Data Management, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Vanessa Didelez
- Department of Biometry and Data Management, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany; Faculty of Mathematics and Computer Science, University of Bremen, Bremen, Germany
| | - Ulrike Haug
- Department of Clinical Epidemiology, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany; Faculty of Human and Health Sciences, University of Bremen, Bremen, Germany
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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: 20] [Impact Index Per Article: 10.0] [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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Laurent T, Lambrelli D, Wakabayashi R, Hirano T, Kuwatsuru R. Strategies to Address Current Challenges in Real-World Evidence Generation in Japan. Drugs Real World Outcomes 2023:10.1007/s40801-023-00371-5. [PMID: 37178273 PMCID: PMC10182751 DOI: 10.1007/s40801-023-00371-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/19/2023] [Indexed: 05/15/2023] Open
Abstract
The generation of real-world evidence (RWE), which describes patient characteristics or treatment patterns using real-world data (RWD), is rapidly growing more popular as a tool for decision-making in Japan. The aim of this review was to summarize challenges to RWE generation in Japan related to pharmacoepidemiology, and to propose strategies to address some of these challenges. We first focused on data-related issues, including the lack of transparency of RWD sources, linkage across different care settings, definitions of clinical outcomes, and the overall assessment framework of RWD when used for research purposes. Next the study reviewed methodology-related challenges. As lack of design transparency impairs study reproducibility, transparent reporting of study design is critical for stakeholders. For this review, we considered different sources of biases and time-varying confounding, along with potential study design and methodological solutions. Additionally, the implementation of robust assessment of definition uncertainty, misclassification, and unmeasured confounders would enhance RWE credibility in light of RWD source-related limitations, and is being strongly considered by task forces in Japan. Overall, the development of guidance for best practices on data source selection, design transparency, and analytical methods to address different sources of biases and robustness in the process of RWE generation will enhance credibility for stakeholders and local decision-makers.
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Affiliation(s)
- Thomas Laurent
- Real-World Evidence and Data Assessment (READS), Graduate School of Medicine, Juntendo University, Hongo 2-1-1, Bunkyo-ku, Tokyo, 113-8421, Japan
- Clinical Study Support Inc., 2F Daiei Bldg., 1-11-20 Nishiki Naka-ku, Nagoya, 460-0003, Japan
| | - Dimitra Lambrelli
- Real-World Evidence and Data Assessment (READS), Graduate School of Medicine, Juntendo University, Hongo 2-1-1, Bunkyo-ku, Tokyo, 113-8421, Japan
- Real-World Evidence, Evidera, The Ark, 2nd Floor, 201 Talgarth Road, London, W6 8BJ, UK
| | - Ryozo Wakabayashi
- Real-World Evidence and Data Assessment (READS), Graduate School of Medicine, Juntendo University, Hongo 2-1-1, Bunkyo-ku, Tokyo, 113-8421, Japan
- Clinical Study Support Inc., 2F Daiei Bldg., 1-11-20 Nishiki Naka-ku, Nagoya, 460-0003, Japan
| | - Takahiro Hirano
- Real-World Evidence and Data Assessment (READS), Graduate School of Medicine, Juntendo University, Hongo 2-1-1, Bunkyo-ku, Tokyo, 113-8421, Japan.
- Clinical Study Support Inc., 2F Daiei Bldg., 1-11-20 Nishiki Naka-ku, Nagoya, 460-0003, Japan.
| | - Ryohei Kuwatsuru
- Real-World Evidence and Data Assessment (READS), Graduate School of Medicine, Juntendo University, Hongo 2-1-1, Bunkyo-ku, Tokyo, 113-8421, Japan
- Department of Radiology, School of Medicine, Juntendo University, Hongo 2-1-1, Bunkyo-ku, Tokyo, 113-8421, Japan
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Colorectal Cancer After Screening Colonoscopy: 10-Year Incidence by Site and Detection Rate at First Repeat Colonoscopy. Clin Transl Gastroenterol 2022; 14:e00535. [PMID: 36201667 PMCID: PMC9875972 DOI: 10.14309/ctg.0000000000000535] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 09/09/2022] [Indexed: 01/31/2023] Open
Abstract
INTRODUCTION We aimed to describe cumulative colorectal cancer (CRC) incidence after screening colonoscopy stratified by tumor location, age, and sex as well as CRC detection rate at first repeat colonoscopy. METHODS Using the German Pharmacoepidemiological Research Database, we included persons with screening colonoscopy and assessed cumulative CRC incidence after baseline screening colonoscopy with snare polypectomy (cohort 1) and without polypectomy (cohort 2). We also determined the CRC detection rate at first repeat colonoscopy by time since screening colonoscopy. RESULTS Overall, 1,095,381 persons were included. The 10-year cumulative CRC incidence was 1.5% in cohort 1 and 0.6% in cohort 2. The proportion of proximal CRC increased with age: In women of cohort 1, 47% of CRCs in the age group 55-64 years were proximal (men: 42%) while in the age group 65-74 years, this proportion was 55% (men: 49%). In cohort 2, similar patterns were observed. In cohort 1, the CRC detection rate at first repeat colonoscopy among persons examined within 6-8 years after screening colonoscopy was more than twice as high compared with those examined within 4-6 years (1.7% vs 0.8%). DISCUSSION Among persons followed up after screening colonoscopy, we observed a steadily increasing predominance of proximal CRC, and this shift showed distinct patterns by age and sex. Because our study suggests higher CRC detection rates among persons with a later repeat colonoscopy, the role of delayed surveillance and the benefit of a reminder system should be explored.
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