Observational Studies in Orthopaedic Surgery: The STROBE Statement as a Tool for Transparent Reporting
2013; Wolters Kluwer; Volume: 95; Issue: 3 Linguagem: Inglês
10.2106/jbjs.l.00484
ISSN1535-1386
AutoresLindsey C. Sheffler, Brad Yoo, Mohit Bhandari, Tania A. Ferguson,
Tópico(s)Hip disorders and treatments
ResumoEvidence-based medicine in orthopaedic surgery comprises predominantly observational studies. While the gold standard of study methodology is considered to be randomized controlled trials (RCTs), observational studies provide valuable information regarding disease prevalence and etiology, rare outcomes, and adverse treatment effects. Orthopaedic surgeons care for many diseases and injuries that are rare and will likely never be the subject of an RCT. Given the bias to which observational studies are prone, however, transparent reporting is imperative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement is a checklist of items that can help clinician-scientists to improve the transparency with which observational studies are reported. We offer the following guidelines and examples for how the STROBE statement can be applied to reporting observational studies in orthopaedic surgery. Observational Studies Observational studies inform clinicians about disease etiology, natural history, prognostic factors, and treatment effectiveness1,2. The most common observational study designs include cohort, case-control, and cross-sectional studies. In a cohort study, subjects are divided into two groups, or cohorts: those with an exposure of interest and those without. The groups are then followed prospectively and are observed for an outcome of interest. In a case-control study, subjects who have experienced an outcome (cases) are matched with subjects who have not experienced an outcome (controls). The two groups are then studied retrospectively to determine a causal relationship between unmatched risk factors and the outcome of interest. In a cross-sectional study, each subject in a population is evaluated at a single point in time, often to calculate the prevalence of disease or to establish an association between risk factors and outcome. Observational studies, specifically, case series, predominate the surgical literature in both general surgery (46%) and orthopaedic surgery (88%)2-4. One reason for the high prevalence of observational studies is that, unlike in other fields of medicine, many questions in surgical subspecialties cannot feasibly or ethically be answered with RCTs. A candidate for surgery may not wish to be randomized to operative or nonoperative care, and a surgeon cannot feasibly be blinded to an operative procedure. Furthermore, surgical experience may affect the outcome of a new procedure and randomizing patients to surgeons with varying levels of experience may pose an ethical dilemma. While observational studies are more suitable than RCTs for studying rare outcomes, adverse treatment effects, and disease etiology, the clinician-scientist must recognize the limitations and biases of nonrandomized study designs. Observational studies are prone to bias, most notably confounding, sampling bias, and recall bias (Table I)5. Bias is any systematic error that causes an incorrect estimate of the association between an exposure and an outcome of interest. Unlike RCTs, observational studies do not benefit from the process of randomization, which balances confounders between groups. In case-control studies, unevenly balanced groups also may be the result of inherent differences between each group due to sampling bias. Cohort study designs are also susceptible to sampling bias in cases in which the sample does not represent the population from which it was drawn or the population at large. Retrospective observational studies are further prone to recall bias, which increases the potential for incomplete or biased data collection. Checklists that provide recommendations for how to report observational studies ensure that confounding, sampling bias, and recall bias are clearly recognized so that the strengths of nonrandomized studies can be appreciated. TABLE I - Confounding, Sampling Bias, Recall Bias5 Confounding factors: variables associated with both the exposure and outcome of interest Effect: May misrepresent the relationship between exposure and outcome Example: A clinician-scientist aims to study the effects of alcohol use (exposure) on time to fracture-healing (outcome). She includes fifty individuals who drink an average of more than two alcoholic beverages a day (cases) and fifty individuals who do not drink alcohol (controls). She finds that subjects who drink alcohol have an increased time to fracture-healing than the controls do. However, the subjects who drank alcohol were also more likely to smoke cigarettes. Smoking, which has been reported to increase fracture-healing time, is a confounding factor associated with both the exposure (alcohol use) and the outcome of interest (fracture-healing). Sampling bias: systematic error due to selection of study participants that do not represent the population from which they were drawn or the population at large Effect: Groups may have inherent differences due to how subjects were recruited; results may not be applicable to other populations Example 1: A clinician-scientist aims to study the association between activity level and osteoarthritis. He recruits high-activity-level subjects (cases) from a local fitness club and low-activity-level subjects (controls) by advertising in the local newspaper. During data analysis, he learns that the high-activity-level group was, on average, younger in age and had fewer comorbidities than the low-activity-level group. These inherent differences between groups may affect the results of his study. Example 2: An investigator reports the incidence of reverse shoulder arthroplasty with use of a database from one academic hospital. To estimate the incidence of reverse shoulder arthroplasty in the United States, a multicenter database with information from both private and academic hospitals in rural and urban locations throughout the country would more accurately represent the population at large. Recall bias: systematic error due to differences in the accuracy of or extent to which subjects recall a previous event Effect: May overestimate or underestimate the effect size of a risk factor Example: An investigator is interested in studying potential risk factors of osteosarcoma. He recruits 100 subjects with osteosarcoma and asks them to complete a detailed questionnaire about prior health habits. Some of the subjects cannot recall of the details of their prior health habits; others provide biased answers because they are worried that their actions were responsible for the development of osteosarcoma. Checklist for Observational Studies: The STROBE Statement In order to practice evidence-based orthopaedic surgery, a reader must critically appraise the published research, understand the strengths and weaknesses of the study, and determine if the reported results and conclusions apply to other clinical situations. The research paper must clearly describe the research question, the study population, how the study was designed to answer the question, and whether the research methodology and analysis were appropriate to reach the author’s conclusions. As described above, observational studies are prone to bias, and it is often challenging for readers to understand if a study population (and therefore the study’s conclusion) is truly representative of clinical practice. Authors of observational studies not only must clearly report their research design and conduct but also must examine and disclose potential factors that may threaten the validity and applicability of their findings. The STROBE initiative was established in 2004 in an effort to improve the quality of reporting of observational research (Table II). A multinational group of methodologists, researchers, and journal editors met to develop recommendations intended to help investigators write “a clear presentation of what was planned, done, and found in an observational study.”6 The STROBE initiative further aimed to assist reviewers and editors when evaluating such studies for publication and to guide readers when interpreting and applying a published study’s results and conclusions. The resulting checklist has been adopted by many of the current orthopaedic journals, including The Journal of Bone and Joint Surgery, which included the STROBE statement in its instructions to authors in 20077. TABLE II - The STROBE Statement—Checklist of Items That Should be Included in Reports of Observational Studies Item No Recommendation Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract (b) Provide in the abstract an informative and balanced summary of what was done and what was found Introduction Background/rationale 2 Explain the scientific background and rationale for the investigation being reported Objectives 3 State specific objectives, including any prespecified hypotheses Methods Study design 4 Present key elements of study design early in the paper Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-upCase-control study—Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the rationale for the choice of cases and controlsCross-sectional study—Give the eligibility criteria, and the sources and methods of selection of participants (b) Cohort study—For matched studies, give matching criteria and number of exposed and unexposedCase-control study—For matched studies, give matching criteria and the number of controls per case Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if applicable Data sources/measurement 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability of assessment methods if there is more than one group Bias 9 Describe any efforts to address potential sources of bias Study size 10 Explain how the study size was arrived at Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding (b) Describe any methods used to examine subgroups and interactions (c) Explain how missing data were addressed (d) Cohort study—If applicable, explain how loss to follow-up was addressedCase-control study—If applicable, explain how matching of cases and controls was addressedCross-sectional study—If applicable, describe analytical methods taking account of sampling strategy (e) Describe any sensitivity analyses Results Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and analyzed (b) Give reasons for non-participation at each stage (c) Consider use of a flow diagram Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential confounders (b) Indicate number of participants with missing data for each variable of interest (c) Cohort study—Summarize follow-up time (eg average and total amount) Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over time Case-control study—Report numbers in each exposure category, or summary measures of exposure Cross-sectional study—Report numbers of outcome events or summary measures Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and why they were included (b) Report category boundaries when continuous variables were categorized (c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses Discussion Key results 18 Summarize key results with reference to study objectives Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidence Generalisability 21 Discuss the generalizability (external validity) of the study results Other information Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the present article is based *Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely available on the web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.(Reproduced, with permission of Elsevier, from: von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative. J Clin Epidemiol. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. 2008 Apr;61(4):344-9. Copyright [2008]. http://www.sciencedirect.com/science/article/pii/S0895435607004362) The STROBE statement is an itemized checklist of twenty-two recommendations that are considered essential for transparent reporting of cohort, case-control, and cross-sectional studies. Of the twenty-two items, eighteen are general to all three categories of observational studies and four are study-design-specific. Recommendations include a description of study aims, identification of potential confounders and bias, and guidelines for reporting study limitations and generalizability. Guide to Investigators: How to Use the STROBE Statement The STROBE statement is not intended as a tool for investigators aiming to improve study design; rather it is a guideline for authors aiming to improve the quality and clarity of presenting research findings. Adherence to the STROBE statement assists the author in disclosing potential bias inherent to the study design and allows the reader to recognize the limitations of the study’s results and conclusions. The following checklist is a guide intended to assist investigators in preparing manuscripts of observational studies. Timing Although the checklist is aimed at the development of a well-written manuscript, we recommend using the checklist during the preparation of the study proposal and in funding applications. Specifying categorical variables and subgroup analyses after data have been collected and reviewed can increase Type-I (alpha) error. Public disclosure of hypotheses and statistical methods prior to data examination may increase the validity of observational studies. Adherence to the STROBE checklist in the design of a study will aid in the development of a suitable working title and will help authors to define objectives, hypotheses, study and target populations, variables, research methodology, and statistical methods. Applying the Items We include an explanation of STROBE statement items, including examples from recently published observational studies in The Journal of Bone and Joint Surgery that we consider to be suitable examples of select checklist items. The articles referenced below may not, in their entirety, adhere to the STROBE checklist; however, we believe that the excerpts provided demonstrate transparent reporting. The following sections provide explanations and examples of checklist items. Title and Abstract Item 1: Title and Abstract (a) Title Indicate the study’s design with a commonly used term in the title or abstract. Explanation: The research title should tell the reader exactly what research method was used to investigate a topic (cohort, case-control, or cross-sectional). Example: “Surgical Compared with Nonoperative Treatment for Lumbar Degenerative Spondylolisthesis. Four-Year Results in the Spine Patient Outcomes Research Trial (SPORT) Randomized and Observational Cohorts.”8 (b) Abstract Provide in the abstract an informative and balanced summary of what was done and what was found. Explanation: The abstract is commonly a reader’s first exposure to the study and must clearly and succinctly depict the key details of the study. Sections of the abstract should be demarcated with subheadings. The Introduction section should tell the reader what the study is about and why it is important, the Methods section should briefly explain the study approach, the Results section should report the findings of the study in numerical format, and the Conclusion section should restate the pertinent findings and relevance of the study. Introduction Section Item 2. Background/Rationale Explain the scientific background and rationale for the investigation being reported. Explanation: The introduction of the paper should be limited to the pertinent information: Why did you do this study? What question did you hope to answer, and why is this question important? When you set out on this investigation, what was your hypothesis? This should not be a review of the literature or a citation of your previous work, but rather an explanation of the genesis of your investigation. Item 3. Objectives State specific objectives, including any prespecified hypotheses. Explanation: A study’s specific aims and/or hypotheses identify the goals and expectations of the study. Clearly stating the study’s objectives allows the reader to judge if the study methods were suitable to test the hypotheses. Example: “The purpose of this study was to investigate further the correlation between brachial plexus birth palsy and glenohumeral deformity…We hypothesized that ratios between internal and external rotator muscle cross-sectional areas would differ when the affected shoulder was compared with the unaffected shoulder and that the magnitude of these differences would correlate with greater glenohumeral deformity.”9 Methods Section Item 4. Study Design Present key elements of study design early in the paper. Explanation: According to the STROBE statement, key study design elements should be presented at the end of the introduction or at the beginning of the Methods section. The type of observational study (cohort, case-control, or cross-sectional) should be clearly stated. Cohort studies should include the exposure status of the subjects, case-control studies should include information regarding the population from which the subjects were drawn, and cross-sectional studies should include the point in time during which the study took place. Example 1: “The aim of the present study was to determine whether patients with a diagnosis of diabetes mellitus have an increased rate of infection following foot and ankle surgery compared with a cohort of patients without diabetes…Furthermore, we sought to demonstrate whether patients with complicated diabetes (associated with the presence of neuropathy, a history of ulcers, Charcot neuroarthropathy, or vascular disease) are at a greater risk for postoperative wound infection than are patients with uncomplicated diabetes or patients without diabetes.”10 Example 2: “Databases of patients who underwent operation at either of two specialized centers were used to identify all primary total knee arthroplasties that were performed for end-stage degenerative joint disease…All opioid medications and dosages were converted to a morphine-equivalent dose with use of ratios published by Labby et al, with only those patients using a minimum equivalent dose of 20 mg/day included in the preoperative opioid group (equivalent to approximately four hydrocodone or three oxycodone tablets per day)…This opioid cohort group was matched to a group of patients who had primary total knee arthroplasty at the same centers over a similar time period, but who were not treated with chronic opioids prior to surgery.”11 Item 5. Setting Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection. Explanation: A detailed report of where, when, and how data were collected provides a historical context so that readers can determine if the results are applicable to other settings and populations. Example: “The study was conducted in the Departments of Orthopaedic Surgery and Traumatology at the University Hospital Basel in Switzerland, an 800-bed tertiary health-care center. Between May 2006 and October 2007, we prospectively included consecutive hospitalized patients who were eighteen years of age or older with a new onset of fever…Patient records were prospectively abstracted with use of a standardized data-collection case report form to retrieve demographic, clinical, microbiological, radiographic, and laboratory data.”12 Item 6. Participants (a) Eligibility Criteria Explanation: Include information regarding eligibility criteria (both inclusion and exclusion criteria), the group from which the population was selected (general population versus subgroup or location), and the methods of recruitment and follow-up. Case-control studies should include the rationale for choosing case and control groups. Example: “A computerized database search for paraplegic patients was performed in the Department of Orthopaedic Surgery and Rehabilitation Medicine…An advertisement was placed in our regional newspaper in order to include a representative sample from the normal population as controls for the study. Because of cost constraints, we only included one control per case…A patient was included in the study if he or she (1) had been wheelchair-dependent for a minimum of thirty years; (2) was not morbidly obese (body mass index <40)…and (9) did not present with any contraindications for undergoing magnetic resonance imaging studies…With the exception of wheelchair dependence, the inclusion and exclusion criteria were the same for the spinal cord injury group and the control cohort.”13 (b) Matching Criteria Explanation: Matching ensures that the case and control groups and the exposed and unexposed groups are equal and comparable. Matching criteria should be explicitly stated, and the number of subjects in each group should be reported. Example: “Between October 2005 and May 2007, 100 paraplegic patients (200 shoulders) who had been paraplegic and wheelchair-dependent for a mean of thirty-three years entered the study and were matched with a cohort of 100 able-bodied volunteers (200 shoulders). The matching was done on the basis of age within five years and sex. The control cohort of able-bodied volunteers was selected in the order in which they responded to our invitation and advertisement. By virtue of the inclusion and exclusion criteria, the matching criteria seemed to be adequate for establishing comparable groups.”13 Item 7. Variables Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if applicable. Explanation: A clear definition of variables such as outcomes, exposures, and confounding variables allows the reader to understand the author’s intentions and to determine if the results of the study are applicable to other populations. Example: “A postoperative infection was defined as an infection that occurred within thirty days after surgery…Mild infection was defined as purulent drainage with <2 cm of peri-incisional erythema and outpatient treatment with oral antibiotics. Severe infection was defined as purulent drainage with ≥2 cm of peri-incisional erythema and/or treatment by inpatient hospitalization or surgical intervention…Postoperative infection was chosen as the primary dependent variable, and various medical risk factors (age, Charcot neuroarthropathy, diabetes…) were considered potential independent variables.”10 Item 8. Data Sources/Measurement For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe the comparability of assessment methods if there is more than one group. Explanation: The way in which a variable is collected and measured will affect the validity of the study. The source of the data and the method used to evaluate the data must be clearly described, such that a reader could repeat your method and reach the same result. The potential for confounding and bias is considerable in observational studies, and the author should aim to expose and mitigate these effects. For example, radiographic outcome measures (length, alignment, rotation) will vary with the precision of the film acquisition, and small changes in the orientation of the x-ray beam will change the measurement of the outcome variables. Thus, authors should describe the methods that were used to standardize image acquisition and measurement. The data itself may be flawed if the source (patient chart, database, or registry) contains inaccurate data. The authors should describe the estimated validity or reliability of the data source and measurement techniques and should describe any efforts to cross-validate their measures or adjust their analysis for errors. Example: “The effective dose was calculated for standard computerized tomographic examinations of the upper and lower extremities as well as the cervical, thoracic, and lumbar spines…In order to validate our methodology, the effective dose of computerized tomographic studies of the chest, abdomen, and pelvis were also estimated and compared with the corresponding values previously reported in the literature.”14 Item 9. Bias Describe any efforts to address potential sources of bias. Explanation: As stated above, observational studies are prone to bias due to features inherent in the methodology. Biased studies produce results that differ from truth in a systematic way. Methodological variation in the enrollment of patients and errors in data entry may introduce bias when data extracted from registries or databases are used. Inappropriate assignment of a patient into a cohort or control group can lead to inaccurate assessment of risk. For example, if a patient’s weight is entered into a total joint registry as 350 lb when indeed the patient weighed only 150 lb, this low-risk patient may be inappropriately included in a cohort of morbidly obese patients selected on the basis of weight and decrease the observed risk of the cohort. Authors should anticipate potential sources of bias and should estimate the probable direction and magnitude of the effect on the results. Example 1: “All studies that had been ordered were evaluated by the staff radiologists at the time of the injury…Results were systematically logged by the author (M.W.S.). A second radiologist (J.D.R.), who was not the original interpreter…, reviewed and reinterpreted all radiographic examinations. Each imaging modality was reviewed separately to minimize bias in interpretation.”15 Example 2: “Finally, as all physical examinations were performed by the treating orthopaedic surgeon…a potential observer bias was introduced that could have been avoided had an independent blinded examiner performed the examinations.”16 Item 10. Study Size Explain how the study size was established. Explanation: The sample size must be large enough to detect differences or associations if they exist. If sample size calculations are performed, they should be included. If other factors dictated sample size, such as a fixed available sample, this should be elucidated. Example 1: “The sample size could not be calculated as the preexisting evidence was insufficient. However, assuming the incidence of rotator cuff tear in the controls to be 15% and the estimate of the relative risk (odds ratio) for the patients to be increased threefold, a sample size of seventy-five individuals per group would be sufficient to detect these risk increases.”13 Example 2: “A power analysis revealed that a minimum sample size of nine patients for each of the five glenoid types would provide 80% power (two-tailed α = 0.05, β = 0.20) to detect a mean difference of 20% in the PM/ER ratio among the types.”9 Item 11. Quantitative Variables Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why. Explanation: For continuous variables, linearity or nonlinearity of the data must be described. If the continuous variable is divided into groups, these groups must be defined, as grouping may have implications in the statistical analysis of the data. Example: “The body mass index was calculated, and patients were categorized according to the system of the National Institutes of Health (NIH)…as normal weight if the body mass index was 30 kg/m2.”17 Item 12. Statistical Methods Explanation: The STROBE statement includes a sub-itemized list of seven recommendations for reporting the statistical methods used to collec
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