Methods: Study Design (4)

The items from STROBE state that you should report:
- Present key elements of study design early in the paper

The Methods section should describe what was planned and what was done in sufficient detail to allow others to understand the essential aspects of the study, to judge whether the methods were adequate to provide reliable and valid answers, and to assess whether any deviations from the original plan were reasonable.(Vandenbroucke et al., 2007)

Some key items to consider adding:
- The reason why the specific sampling method was chosen

Box 1. Study designs covered

Cohort, case-control, and cross-sectional designs represent different approaches of investigating the occurrence of health-related events in a given population and time period. These studies may address many types of health-related events, including disease or disease remission, disability or complications, death or survival, and the occurrence of risk factors.

In cohort studies, the investigators follow people over time. They obtain information about people and their exposures at baseline, let time pass, and then assess the occurrence of outcomes. Investigators commonly make contrasts between individuals who are exposed and not exposed or among groups of individuals with different categories of exposure. Investigators may assess several different outcomes, and examine exposure and outcome variables at multiple points during follow-up. Closed cohorts (for example birth cohorts) enroll a defined number of participants at study onset and follow them from that time forward, often at set intervals up to a fixed end date. In open cohorts the study population is dynamic: people enter and leave the population at different points in time (for example inhabitants of a town). Open cohorts change due to deaths, births, and migration, but the composition of the population with regard to variables such as age and gender may remain approximately constant, especially over a short period of time. In a closed cohort cumulative incidences (risks) and incidence rates can be estimated; when exposed and unexposed groups are compared, this leads to risk ratio or rate ratio estimates. Open cohorts estimate incidence rates and rate ratios.

In case-control studies, investigators compare exposures between people with a particular disease outcome (cases) and people without that outcome (controls). Investigators aim to collect cases and controls that are representative of an underlying cohort or a cross-section of a population. That population can be defined geographically, but also more loosely as the catchment area of health care facilities. The case sample may be 100% or a large fraction of available cases, while the control sample usually is only a small fraction of the people who do not have the pertinent outcome. Controls represent the cohort or population of people from which the cases arose. Investigators calculate the ratio of the odds of exposures to putative causes of the disease among cases and controls (see Box 7). Depending on the sampling strategy for cases and controls and the nature of the population studied, the odds ratio obtained in a case-control study is interpreted as the risk ratio, rate ratio or (prevalence) odds ratio (Rodrigues & Kirkwood, 1990; K. Rothman, 1998). The majority of published case-control studies sample open cohorts and so allow direct estimations of rate ratios.

In cross-sectional studies, investigators assess all individuals in a sample at the same point in time, often to examine the prevalence of exposures, risk factors or disease. Some cross-sectional studies are analytical and aim to quantify potential causal associations between exposures and disease. Such studies may be analysed like a cohort study by comparing disease prevalence between exposure groups. They may also be analysed like a case-control study by comparing the odds of exposure between groups with and without disease. A difficulty that can occur in any design but is particularly clear in cross-sectional studies is to establish that an exposure preceded the disease, although the time order of exposure and outcome may sometimes be clear. In a study in which the exposure variable is congenital or genetic, for example, we can be confident that the exposure preceded the disease, even if we are measuring both at the same time. (Vandenbroucke et al., 2007)

Explanation

We advise presenting key elements of study design early in the methods section (or at the end of the introduction) so that readers can understand the basics of the study. For example, authors should indicate that the study was a cohort study, which followed people over a particular time period, and describe the group of persons that comprised the cohort and their exposure status. Similarly, if the investigation used a case-control design, the cases and controls and their source population should be described. If the study was a cross-sectional survey, the population and the point in time at which the cross-section was taken should be mentioned.

When a study is a variant of the three main study types, there is an additional need for clarity. For instance, for a casecrossover study, one of the variants of the case-control design, a succinct description of the principles was given in the example above.(McEvoy et al., 2005)

We recommend that authors refrain from simply calling a study ‘prospective’ or ‘retrospective’ because these terms are ill defined. (Vandenbroucke et al., 2007) One usage sees cohort and prospective as synonymous and reserves the word retrospective for case-control studies.(Last, 2000) A second usage distinguishes prospective and retrospective cohort studies according to the timing of data collection relative to when the idea for the study was developed.31 A third usage distinguishes prospective and retrospective case-control studies depending on whether the data about the exposure of interest existed when cases were selected.(K. Rothman, 1998) Some advise against using these terms,(MacMahon & Trichopoulos, 1996) or adopting the alternatives ‘concurrent’ and ‘historical’ for describing cohort studies.(Lilienfeld, 1976) In STROBE, we do not use the words prospective and retrospective, nor alternatives such as concurrent and historical. We recommend that, whenever authors use these words, they define what they mean. Most importantly, we recommend that authors describe exactly how and when data collection took place.

The first part of the methods section might also be the place to mention whether the report is one of several from a study. If a new report is in line with the original aims of the study, this is usually indicated by referring to an earlier publication and by briefly restating the salient features of the study. However, the aims of a study may also evolve over time. Researchers often use data for purposes for which they were not originally intended, including, for example, official vital statistics that were collected primarily for administrative purposes, items in questionnaires that originally were only included for completeness, or blood samples that were collected for another purpose. For example, the Physicians’ Health Study, a randomized controlled trial of aspirin and carotene, was later used to demonstrate that a point mutation in the factor V gene was associated with an increased risk of venous thrombosis but not of myocardial infarction or stroke.(Ridker et al., 1995) The secondary use of existing data is a creative part of observational research and does not necessarily make results less credible or less important. However, briefly restating the original aims might help readers understand the context of the research and possible limitations in the data.(Vandenbroucke et al., 2007)

Example

• “We used a case-crossover design, a variation of a case-control design that is appropriate when a brief exposure (driver’s phone use) causes a transient rise in the risk of a rare outcome (a crash). We compared a driver’s use of a mobile phone at the estimated time of a crash with the same driver’s use during another suitable time period. Because drivers are their own controls, the design controls for characteristics of the driver that may affect the risk of a crash but do not change over a short period of time. As it is important that risks during control periods and crash trips are similar, we compared phone activity during the hazard interval (time immediately before the crash) with phone activity during control intervals (equivalent times during which participants were driving but did not crash) in the previous week” (McEvoy et al., 2005; Vandenbroucke et al., 2007).
  
  
  

Field-specific guidance

Molecular epidemiology (Gallo et al., 2012)
- Describe the special study designs for molecular epidemiology (in particular, nested case ⁄control and case ⁄cohort) and how they were implemented
- Report on the setting of the biological sample collection; amount of sample; nature of collecting procedures; participant conditions; time between sample collection and relevant clinical or physiological endpoints
- Report the half-life of the biomarker and chemical and physical characteristics (e.g. solubility)
- Describe sample processing (centrifugation, timing, additives, etc.)
- Describe sample storage until biomarker analysis (storage, thawing, manipulation, etc.)

Infectious disease molecular epidemiology (Field et al., 2014)
- Define or cite definitions for key molecular terms used within the study (eg, strain, isolate, and clone)
- Clearly define the molecular markers that were used with a standard nomenclature
- Clearly state the infectious-disease case definitions
- Describe sample collection and laboratory methods, including any methods used to minimise and measure cross-contamination, and give the criteria used to interpret strain classification

Seroepidemiologic studies for influenza (Horby et al., 2017)
- State which specific seroepidemiologic study design was chosen and why (see Table 1 of Horby et al 2007)

Neonatal infections (Fitchett et al., 2016)
- Clearly state case ascertainment methods (eg, physician diagnosis, clinical algorithm), documenting individual clinical signs used for diagnosis of possible serious bacterial infection
- Give microbiological and/or laboratory and/or radiological criteria for other infectious syndromes (eg, meningitis, sepsis, pneumonia)
- Include indications for clinical investigations (eg, lumbar puncture)
- Give criteria used to differentiate between new infection episodes and relapses
- For facility-based studies, indicate if the study is of community and/ or hospital-acquired infections (HAI), defining HAI using an international standard and presenting specific HAI clinical syndromes separately
- State whether this is an outbreak study, and if so define an outbreak, with reference to an international standard
- Describe sampling strategy (eg, clinical indication vs routine surveillance) and sampling details (eg, minimum volumes; timing in relation to antimicrobial administration
- Describe conventional and/or molecular microbiological methods used, with details (eg, automation, enrichment steps), and the use of controls
- List pathogens that are likely to be identified by microbiological methods used
- Describe antimicrobial susceptibility tests and thresholds used, with reference to an international standard (eg, CLSI or EUCAST)

Resources

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References

Field, N., Cohen, T., Struelens, M. J., Palm, D., Cookson, B., Glynn, J. R., Gallo, V., Ramsay, M., Sonnenberg, P., MacCannell, D., Charlett, A., Egger, M., Green, J., Vineis, P., & Abubakar, I. (2014). Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID): An extension of the STROBE statement. The Lancet Infectious Diseases, 14(4), 341–352. https://doi.org/10.1016/S1473-3099(13)70324-4

Fitchett, E. J. A., Seale, A. C., Vergnano, S., Sharland, M., Heath, P. T., Saha, S. K., Agarwal, R., Ayede, A. I., Bhutta, Z. A., Black, R., Bojang, K., Campbell, H., Cousens, S., Darmstadt, G. L., Madhi, S. A., Meulen, A. S.-t., Modi, N., Patterson, J., Qazi, S., … Lawn, J. E. (2016). Strengthening the Reporting of Observational Studies in Epidemiology for Newborn Infection (STROBE-NI): An extension of the STROBE statement for neonatal infection research. The Lancet Infectious Diseases, 16(10), e202–e213. https://doi.org/10.1016/S1473-3099(16)30082-2

Gallo, V., Egger, M., McCormack, V., Farmer, P. B., Ioannidis, J. P. A., Kirsch-Volders, M., Matullo, G., Phillips, D. H., Schoket, B., Stromberg, U., Vermeulen, R., Wild, C., Porta, M., & Vineis, P. (2012). STrengthening the Reporting of OBservational studies in Epidemiology Molecular Epidemiology (STROBE-ME): An extension of the STROBE statement. European Journal of Clinical Investigation, 42(1), 1–16. https://doi.org/10.1111/j.1365-2362.2011.02561.x

Horby, P. W., Laurie, K. L., Cowling, B. J., Engelhardt, O. G., Sturm-Ramirez, K., Sanchez, J. L., Katz, J. M., Uyeki, T. M., Wood, J., Van Kerkhove, M. D., & the CONSISE Steering Committee. (2017). CONSISE statement on the reporting of Seroepidemiologic Studies for influenza (ROSES-I statement): An extension of the STROBE statement. Influenza and Other Respiratory Viruses, 11(1), 2–14. https://doi.org/10.1111/irv.12411

Last, J. (2000). A Dictionary of Epidemiology. Oxford University Press.

Lilienfeld, A. (1976). Foundations of Epidemiology. Oxford University Press.

MacMahon, B., & Trichopoulos, D. (1996). Epidemiology, principles and methods (2nd edition). Brown Little.

McEvoy, S. P., Stevenson, M. R., McCartt, A. T., Woodward, M., Haworth, C., Palamara, P., & Cercarelli, R. (2005). Role of mobile phones in motor vehicle crashes resulting in hospital attendance: A case-crossover study. BMJ, 331(7514), 428. https://doi.org/10.1136/bmj.38537.397512.55

Ridker, P. M., Hennekens, C. H., Lindpaintner, K., Stampfer, M. J., Eisenberg, P. R., & Miletich, J. P. (1995). Mutation in the Gene Coding for Coagulation Factor V and the Risk of Myocardial Infarction, Stroke, and Venous Thrombosis in Apparently Healthy Men. New England Journal of Medicine, 332(14), 912–917. https://doi.org/10.1056/NEJM199504063321403

Rodrigues, L., & Kirkwood, B. R. (1990). Case-Control Designs in the Study of Common Diseases: Updates on the Demise of the Rare Disease Assumption and the Choice of Sampling Scheme for Controls. International Journal of Epidemiology, 19(1), 205–213. https://doi.org/10.1093/ije/19.1.205

Rothman, K. (1998). Types of Epidemiologic Studies. In Modern epidemiology (2nd ed., pp. 74–75). Lippincott Raven.

Vandenbroucke, J. P., Elm, E. von, Altman, D. G., Gotzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., & Egger, M. (2007). Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration. Epidemiology, 18(6), 805–835. https://doi.org/10.1097/EDE.0b013e3181577511