Design Review 2016 Crack File Only 64 Bit
Antipas Zorn
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We systematically selected all reports in this field involving case-only designs from MEDLINE and EMBASE up to September 15, 2010. Data were extracted using a standardized form. The analysis included 93 reports 50 (54%) of CC and 45 (48%) SCCS, 2 reports combined both designs. In 12 (24%) CC and 18 (40%) SCCS articles, all applicable validity assumptions of the designs were fulfilled, respectively. Fifty (54%) articles (15 CC (30%) and 35 (78%) SCCS) adequately addressed the specificities of the case-only analyses in the way they reported results.
Among existing case-only designs, 5 have been used in pharmacoepidemiology: the case-crossover design (CC) [1], the case-time-control design (CTC) [2], the self-controlled case series design (SCCS), originally called case series analysis [3], the screening method [4] and the prescription sequence symmetry analysis (PSSA) also called the symmetry principle [5] (See Appendix S1, for a description of the designs). Of those designs, CC and SCCS have been used the most.
CC and SCCS designs are considered suitable tools in post-licensure pharmacoepidemiological studies. With the development of health information technology and the use of large healthcare databases to retrieve real-life data of exposure/event occurrence, these designs seem particularly appropriate to analyze pharmacovigilance data. However, medication use patterns may not correspond to the exposure characteristics for which these designs were developed. For instance, a medication may be a chronic rather than transient exposure. Also, adverse events may be permanent or generate chronic consequences that might influence further exposure [10]. Applicability of the design to specific settings is a key issue to be addressed by investigators and authors. Furthermore, case-only statistical methods have specificities and differ from conventional ones such as case-control or cohort analyses (See Appendix S1). Reporting has to present adequate specific information for the consistency of the study results to be assessed.
We performed a systematic review of the use and reporting of case-only designs in the pharmacoepidemiology literature, focusing on design applicability and reporting, in studies involving the two most widely used case-only designs, CC (including its extension CTC) and SCCS.
Two of the authors (SN and LB) screened titles and abstracts to identify potentially relevant articles. A final selection was made after reading the full texts. Articles were included if CC, CTC or SCCS case-only designs were used and if the purpose of the study was pharmacoepidemiology, i.e. the objective was to assess either human safety or efficacy of drugs, or medical devices. Reviews, meta-analyses, letters to the editor, reports of randomized trials, articles reporting methodological issues only and reports of cost-effectiveness studies were not included. In the case of duplicate publication (the same study using the same design described in several articles), only the article that was published first was selected.
A flowchart of the selection of articles is included in Figure 1. A search of MEDLINE yielded 664 citations and 627 were found in EMBASE. In addition, 43 reports were identified on the SCCS method website. After excluding 640 duplicates, 694 articles remained from the 3 sources, among which 164 reports were considered eligible, based on titles and abstracts. Finally, 93 reports were included for analysis after reading the full texts: 50 articles reporting studies using CC or CTC (7 studies used CTC designs) and 45 using SCCS. Two articles reported both CC and SCCS designs. (See Appendix S3 for a list of complete references for the reports included).
Regarding the general characteristics of the studies included (Table 1), the first article using a case-only design in pharmacoepidemiology was published in 1995. The annual number of published articles reporting case-only studies increased over time until 2005. Since then, SCCS design use has remained stable, but CC use has continued to rise (Figure 2). In 39 reports (42%), several designs were combined; 4 reports involved 3 designs (CC, CTC and case-control) and 2 reported combined CC and SCCS designs. The rationale for using a case-only design was reported in 75 articles (81%). In 55%, the purpose was to limit bias (confounding or selection biases).
Concerning statistical issues, a sample size calculation [17], [18] was reported in 10 articles (11%) (Table 5). Administrative databases usually provide large sample sizes and may be considered somewhat satisfying with regard to power considerations. Also, when a study presents a case-only design as exploratory analysis, the main design (cohort, case-control) may have provided a sample size calculation. Among the 54 studies that did not combine a case-only design with other(s), only 2 (6%) reported a sample size calculation. In this review, 6 articles (6%) did not correspond to either of those situations (administrative database or multiple designs). None of them reported a sample size calculation. Forty-one (82%) CC and 23 (51%) SCCS articles reported using the adequate statistical model [1], [18], [19] (Table 5). Overall, the statistical model was unclear in almost one-third of the articles. However, most articles reported the appropriate risk estimator: CC, 48 (96%); and SCCS, 44 (98%). Sensitivity analyses were reported in 37 articles (40%).
We conducted a systematic review of case-only studies in pharmacoepidemiology published up to September 15, 2010, on MEDLINE, EMBASE and the SCCS method website [13]. We focused on CC and SCCS designs, the most popular case-only designs. Indeed, in the articles we screened, we only found 11 articles reporting a PSSA design and 8 using a screening method that fulfilled our eligibility criteria. In pharmacoepidemiology, case-only designs are predominantly used to assess safety. SCCS was originally developed to study adverse events of vaccines and is still mostly used for this purpose (76% of our articles). In contrast, CC has been used in a wider range of therapeutic areas.
For the same reason, reporting relevant information in the results section is important. Solely reporting the risk estimate and its confidence interval does not provide adequate information to fully understand the specificity of a case-only analysis. However, adequate information will allow a comprehensive interpretation of the analysis, as well as the assessment of the internal validity of the study. In addition to the risk estimate, stating the count of subjects with discordant periods (exposed/unexposed) in CC studies, and the count of events in risk and control periods separately in SCCS studies, provides the reader with adequate information to appreciate how the analysis was performed. In half of the articles included, this information was partially missing or inadequate counts were provided, such as the count of exposed and non-exposed risk periods in CC design and the count of events, irrespective of risk/control periods in SCCS. This issue has recently been discussed by the team of the SCCS developers [25]. They stressed the importance of reporting the numbers of events in risk and control periods and of disclosing potential biases.
In case-only designs, specifying the risk period requires particular caution [26]: if the risk period is too long, too short or does not cover the true period at risk, the estimator may be biased toward the null [1], [9]. We found that 36% and 51% of CC and SCCS reports, respectively, adequately defined the risk period. In addition, sensitivity analyses are recommended to check the robustness of the risk period and control period choice, by modifying the onset, end or duration of the period. Only 17% of the reports described sensitivity analyses based on variation in the risk period, and 16% in the control period. In certain settings the event occurrence is only possible during specific periods at risk (eg pregnancy, hospitalization, driving, working). Therefore, time restrictions are required and, when appropriate, similar in risk and control periods. In our review, few reports described time restrictions for risk or control periods.
Our results highlight some issues to be improved on in planning and reporting case-only studies. These issues are: the applicability of the design to the context of the study, justification of risk and control periods (onset, time and duration), performing sensitivity analyses including those related to the risk and control period characteristics, reporting of sample size calculation and power discussion, statistical models and risk estimators, and reporting of adequate information regarding the analysis performed and results.
Background: Quantitative research designs are broadly classified as either experimental or quasi-experimental. The main distinguishing feature of the quasi-experiment is the manipulation of the independent variable without randomisation. When randomisation or use of a control group is unfeasible, a researcher can choose from a range of quasi-experimental designs.
Discussion: This paper provides an overview of the non-equivalent control group post-test-only design in terms of its design features, applications and statistical analysis, as well as its advantages and disadvantages.
Conclusion: The non-equivalent control group post-test-only design can be used in natural settings, where randomisation cannot be conducted for ethical or practical reasons. Although the design is less complex than some other designs, with low error propagation, it is vulnerable to threats to internal validity.
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