Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration

Editor's Note: In order to encourage dissemination of the STROBE Statement, this article is being published simultaneously in Annals of Internal Medicine, Epidemiology, and PLoS Medicine. It is freely accessible on the Annals of Internal Medicine Web site ( www.annals.org ) and will also be published on the Web sites of Epidemiology and PLoS Medicine. The authors jointly hold the copyright of this article. For details on further use, see the STROBE Web site (www.strobe-statement.org). Rational health care practices require knowledge about the etiology and pathogenesis, diagnosis, prognosis, and treatment of diseases. Randomized trials provide valuable evidence about treatments and other interventions. However, much of clinical or public health knowledge comes from observational research (1). About 9 of 10 research papers published in clinical specialty journals describe observational research (2, 3). The STROBE Statement Reporting of observational research is often not detailed and clear enough to assess the strengths and weaknesses of the investigation (4, 5). To improve the reporting of observational research, we developed a checklist of items that should be addressed: the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement (Appendix Table). Items relate to the title, abstract, introduction, methods, results, and discussion sections of articles. The STROBE Statement has recently been published in several journals (6). Our aim is to ensure clear presentation of what was planned, done, and found in an observational study. We stress that the recommendations are not prescriptions for setting up or conducting studies, nor do they dictate methodology or mandate a uniform presentation. Appendix Table. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Checklist of Items That Should Be Addressed in Reports of Observational Studies STROBE provides general reporting recommendations for descriptive observational studies and studies that investigate associations between exposures and health outcomes. STROBE addresses the 3 main types of observational studies: cohort, casecontrol, and cross-sectional studies. Authors use diverse terminology to describe these study designs. For instance, follow-up study and longitudinal study are used as synonyms for cohort study, and prevalence study as a synonym for cross-sectional study. We chose the present terminology because it is in common use. Unfortunately, terminology is often used incorrectly (7) or imprecisely (8). In Box 1, we describe the hallmarks of the 3 study designs. Box 1. Main Study Designs Covered by STROBE The Scope of Observational Research Observational studies serve a wide range of purposes, from reporting a first hint of a potential cause of a disease to verifying the magnitude of previously reported associations. Ideas for studies may arise from clinical observations or from biological insight. Ideas may also arise from informal looks at data that lead to further explorations. Like a clinician who has seen thousands of patients and notes 1 that strikes her attention, the researcher may note something special in the data. Adjusting for multiple looks at the data may not be possible or desirable (9), but further studies to confirm or refute initial observations are often needed (10). Existing data may be used to examine new ideas about potential causal factors, and may be sufficient for rejection or confirmation. In other instances, studies follow that are specifically designed to overcome potential problems with previous reports. The latter studies will gather new data and will be planned for that purpose, in contrast to analyses of existing data. This leads to diverse viewpoints, for example, on the merits of looking at subgroups or the importance of a predetermined sample size. STROBE tries to accommodate these diverse uses of observational researchfrom discovery to refutation or confirmation. Where necessary, we will indicate in what circumstances specific recommendations apply. How to Use this Paper This paper is linked to the shorter STROBE paper that introduced the items of the checklist in several journals (6), and forms an integral part of the STROBE Statement. Our intention is to explain how to report research well, not how research should be done. We offer a detailed explanation for each checklist item. Each explanation is preceded by an example of what we consider transparent reporting. This does not mean that the study from which the example was taken was uniformly well reported or well done; nor does it mean that its findings were reliable, in the sense that they were later confirmed by others: It only means that this particular item was well reported in that study. In addition to explanations and examples, we included boxes with supplementary information. These are intended for readers who want to refresh their memories about some theoretical points or be quickly informed about technical background details. A full understanding of these points may require studying the textbooks or methodological papers that are cited. STROBE recommendations do not specifically address topics, such as genetic linkage studies, infectious disease modeling, or case reports and case series (11, 12). As many of the key elements in STROBE apply to these designs, authors who report such studies may nevertheless find our recommendations useful. For authors of observational studies that specifically address diagnostic tests, tumor markers, and genetic associations, STARD (13), REMARK (14), and STREGA (15) recommendations may be particularly useful. The Items in the STROBE Checklist We now discuss and explain the 22 items in the STROBE checklist (Appendix Table) and give published examples for each item. Some examples have been edited by removing citations or spelling out abbreviations. Eighteen items apply to all 3 study designs, whereas 4 are design-specific. Starred items (for example, item 8) indicate that the information should be given separately for cases and controls in casecontrol studies, or exposed and unexposed groups in cohort and cross-sectional studies. We advise authors to address all items somewhere in their paper, but we do not prescribe a precise location or order. For instance, we discuss the reporting of results under a number of separate items, while recognizing that authors might address several items within a single section of text or in a table. Title and Abstract 1(a) Indicate the study's design with a commonly used term in the title or the abstract. Example Leukaemia incidence among workers in the shoe and boot manufacturing industry: a casecontrol study (18). Explanation Readers should be able to easily identify the design that was used from the title or abstract. An explicit, commonly used term for the study design also helps ensure correct indexing of articles in electronic databases (19, 20). 1(b) Provide in the abstract an informative and balanced summary of what was done and what was found. Example Background: The expected survival of HIV-infected patients is of major public health interest. Objective: To estimate survival time and age-specific mortality rates of an HIV-infected population compared with that of the general population. Design: Population-based cohort study. Setting: All HIV-infected persons receiving care in Denmark from 1995 to 2005. Patients: Each member of the nationwide Danish HIV Cohort Study was matched with as many as 99 persons from the general population according to sex, date of birth, and municipality of residence. Measurements: The authors computed KaplanMeier life tables with age as the time scale to estimate survival from age 25 years. Patients with HIV infection and corresponding persons from the general population were observed from the date of the patient's HIV diagnosis until death, emigration, or 1 May 2005. Results: 3990 HIV-infected patients and 379 872 persons from the general population were included in the study, yielding 22 744 (median, 5.8 y/person) and 2 689 287 (median, 8.4 y/person) person-years of observation. Three percent of participants were lost to follow-up. From age 25 years, the median survival was 19.9 years (95% CI, 18.5 to 21.3) among patients with HIV infection and 51.1 years (CI, 50.9 to 51.5) among the general population. For HIV-infected patients, survival increased to 32.5 years (CI, 29.4 to 34.7) during the 2000 to 2005 period. In the subgroup that excluded persons with known hepatitis C coinfection (16%), median survival was 38.9 years (CI, 35.4 to 40.1) during this same period. The relative mortality rates for patients with HIV infection compared with those for the general population decreased with increasing age, whereas the excess mortality rate increased with increasing age. Limitations: The observed mortality rates are assumed to apply beyond the current maximum observation time of 10 years. Conclusions: The estimated median survival is more than 35 years for a young person diagnosed with HIV infection in the late highly active antiretroviral therapy era. However, an ongoing effort is still needed to further reduce mortality rates for these persons compared with the general population (21). Explanation The abstract provides key information that enables readers to understand a study and decide whether to read the article. Typical components include a statement of the research question, a short description of methods and results, and a conclusion (22). Abstracts should summarize key details of studies and should only present information that is provided in the article. We advise presenting key results in a numerical form that includes numbers of participants, estimates of associations, and appropriate measures of variability and uncertainty (for example, odds ratios with confidence intervals). We regard it insufficient to state only that an exposure is or is not significantly associated with an outcom