Case Control - Study Design

 

matched case control study

In contrast, the matched case-control study has linked a case to a control based on matching of one or more ipvcitysa.cf summary table will differ for a matched case-control study. Let's look at an example. Suppose we plan to match cases to controls by gender and age (+/- 5 years). Matched Pair Case-Control Study Pairs of Cases and Controls matched on defined characteristics are evaluated for exposure to a risk factor and distributed into the four cells of the table representing the four possible combinations of outcome in a pair. A case-control study is usually conducted before a cohort from the Women’s Health Study, controls were matched using random digit dialing with frequency matching on ethnicity, the three age groups (, , and ), and the seven health planning districts.


- Case-Control Study Design | STAT


Case-control studies are a common and efficient means of studying rare diseases or illnesses with long latency periods. Matching of cases and controls is frequently employed to control the effects of known potential confounding variables.

The analysis of matched data requires specific statistical methods. The objective of this study was to determine the proportion of published, peer-reviewed matched case-control studies that used statistical methods appropriate for matched data.

Using a comprehensive set of search criteria we identified 37 matched case-control studies for detailed analysis. The findings of this study raise concern that the majority of matched case-control studies report results that are derived from improper statistical analyses.

This may lead matched case control study errors in estimating the relationship between a disease and exposure, as well as the incorrect adaptation of emerging medical literature. Case-control studies provide a quick and efficient means of studying diseases with long latency periods or with low incidence in the population.

Although they are convenient and common, there are several important considerations in the design of case-control studies. The analysis of matched dependent data is different from unmatched independent data and is described in detail by Breslow and Day. They also describe conditional logistic regression to handle all forms of matching as well as the consideration of modification and other potential confounding.

We recently published a study wherein matching was employed to control for known potential confounding variables. Data analyses that employ incorrect statistical methods will commonly result in inappropriate conclusions. Therefore, the current study was designed to evaluate the statistical methodology in a collection of matched case-control studies.

A literature review was conducted using PubMed from January 1, to December 1, with the goal of identifying articles that employed a matched case-control design. This search strategy was chosen to yield a representative sample of case-control studies in a variety of subject areas, published in peer-reviewed, mainstream journals.

One of the authors screened all the abstracts for relevance and appropriate full-length matched case control study were subsequently retrieved for appraisal. To maintain relative homogeneity among the final collection of articles, it was decided, a priori, to exclude articles that focused on subjects in the pediatric age group under 18 years of age. We also excluded studies that used matching methods other than simple, individual criteria-based matching, ie, frequency-matching, and propensity-matching, as this type of data is analyzed with different statistical methods.

Each full length article was independently reviewed in detail by two of the authors. The goal of this review was to evaluate the appropriateness of the statistical methodology. Disagreements between the reviewers were resolved by the independent evaluation of a senior biostatistician.

Inter- observer agreement was quantified using the kappa statistic, wherein a kappa value of 0. Following the review of their statistical methodology, the collection of matched case-control articles were reviewed a second time for factors that may be associated with the use of statistical methods appropriate for matched data. These factors included items that form common issues in the design of matched case-control studies, namely the case population definition, the number of matching variables, and the control-to-case ratio, matched case control study.

In addition, we used the Journal Citation Reports JCR index to determine whether the appropriateness of the statistical methodology was associated with the impact factor of the publishing journal. Using the JCR index, we determined that an impact factor of at least Data was analyzed using Stata v The initial search strategy yielded 74 articles Figure 1. Upon review of these abstracts, matched case control study, 36 articles were excluded for reasons outlined in Figure 1. The remaining 38 articles were reviewed in detail.

Table 1 provides a summary of these 37 studies. Given the low number of studies with correctly analyzed data, each of the 37 articles was reviewed for factors that may be associated with the use of correct statistical tests Table 2, matched case control study.

From this table, it is clear that matched case-control articles published in the British Medical Journal BMJ were consistently analyzed with correct statistical techniques.

This is in contrast to articles published in Archives of Otolaryngology- Head and Neck Surgery, Journal of Clinical Endocrinology and Metabolism, and Neurology wherein the data was frequently analyzed incorrectly. Moreover, matched case-control studies published in Lancet were notably inconsistent in their statistical methodology. The median interquartile range [IQR] impact factor among studies that were correctly analyzed was A list of the publishing journals and impact factors among the collection of articles reviewed in this study.

To our knowledge, this matched case control study the first study to assess the appropriateness of the statistical methodology used in a published series of matched case-control studies. From this structured review of studies published in a number of diverse mainstream, peer-reviewed journals it is clear that matched case-control studies are not consistently analyzed using appropriate statistical methods.

For many of these studies, this may simply change the strength of the association between the disease and exposure of interest; however, for studies with small numbers of discordant sets, the use of appropriate statistical methods may alter the significance of the findings. Unfortunately, none of the articles reviewed in this study with incorrect statistical methodology provided the data in a format whereby the magnitude of the difference between a proper and improper analysis could be assessed.

This is important, as it is clear from recent reviews of the literature that the use of statistics in medical literature is increasing over time. Although this study appears to be the first to evaluate the quality of the statistical methods employed in a series of matched case-control studies, it is not the first study to review the quality of statistical methods in medical journals. They consistently found that a minority of studies reported unacceptable methods of data analysis and concluded that this is likely due to the fact that individuals leading these medical publications may not have a solid grasp on basic statistical concepts.

The study design characteristics and their relation to the proper analysis of matched data as shown in Table 2generate a few interesting hypotheses. First, studies involving case populations with cancer or cardiovascular disease were more matched case control study to employ statistical techniques that account for dependent data than studies involving other case definitions.

The reason for this is not clear but it may be a reflection of the rigor with which these studies were designed. Second, a greater number of studies in the incorrectly analyzed collection focused on a surgical topic, compared to studies in the correctly analyzed collection. Although the reasons for this finding are unclear, one potential explanation might be that the use of inferential statistics in surgical studies is a more recent development when compared to studies focusing on other medical topics.

Older surgical research involved smaller sample sizes and very few of these studies employed inferential statistics, matched case control study.

The decision to match more than one control per case may increase the power of case-control studies, 1 which, matched case control study, in turn, increases the strength of the study and reflects a thoughtful, systematic approach to the study design. This same thought was likely extended to the analysis phase and resulted in the correct application of statistical methodology. Similarly, Kuroki et al investigated the potential link between research methodology and statistical reporting in medical journals with a high impact factor compared to moderate-impact-factor obstetrics and gynecology journals.

Therefore, our finding of an increased impact factor in the correct statistical analysis group aligns with trends observed in similar studies. This study has a number of pertinent strengths and limitations that warrant discussion. First, this study is novel; as to our knowledge, this is the first review of matched case control study appropriateness of the statistical methodology employed in a collection of matched case-control studies. Second, the studies selected for review focused on a broad range of topics in a number of different peer-reviewed journals, so, although we reviewed only 37 studies, this sample is representative of the much larger population of available articles.

Furthermore, matched case control study of matched case control study articles were published in mainstream journals read by individuals from a variety of backgrounds such as the British Medical Journalthe Canadian Medical Association Journalmatched case control study, and the Lancet. The major limitation of this study is that the methodology of the articles was not assessed with a validated scoring system.

Matched case control study suggests that the scoring system used in this study was applied in a consistent manner, and our conclusion regarding inconsistent use of proper statistical methods in matched case-control studies is valid. Another important limitation is the inability to determine whether the use of proper statistics would change the conclusions presented by studies that used improper statistical methods. This is due to the fact that very few case-control studies presented tables outlining the number of discordant sets.

This limitation notwithstanding, it is possible that the matched case control study of proper statistical methods will at least decrease the strength of the association between the outcome and exposure variables when compared to that obtained from improper statistical methodology.

The majority of matched case-control studies reviewed in this investigation used improper statistical methods. Although matching cases to controls provides a means of controlling for known potential confounding variables, it is a complicated process that requires a great deal of thought in order to be effective. The acceptance of invalid conclusions and subsequent adaptation into medical practice may lead to the inappropriate matched case control study of resources and even worse, harm to individuals.

The results of the current study suggest that although the STROBE checklist includes recommendations for outlining the matching methodology when reporting a matched case-control study, these comprehensive epidemiologic guidelines may require an additional section that outlines the proper statistical techniques to be employed when conducting a matched case-control study.

Daniel J Niven carried out the literature search, screened all relevant abstracts, matched case control study, and independently evaluated each study selected for the detailed review of the reported statistical methodology, matched case control study.

Daniel J Niven also analyzed the data, and drafted the manuscript. Luc R Berthiaume independently evaluated the statistical methodology of the included studies, and contributed to manuscript revision.

Gordon H Fick is a senior biostatistician and settled discrepancies between Daniel J Niven and Luc R Berthiaume during the review of the selected studies. Kevin B Laupland contributed to manuscript revision, matched case control study. All authors approved the final manuscript for publication. As this study did not involve collecting data from patients, formal approval from the regional ethics board was not required.

National Center for Biotechnology InformationU. Journal List Clin Epidemiol v. Clin Epidemiol. Published online Apr Author information Copyright and License information Disclaimer. This is an Open Access article which permits unrestricted noncommercial use, matched case control study, provided the original work is properly cited.

This article has been cited by other articles in PMC. Abstract Background Case-control studies are a common and efficient means of studying rare diseases or illnesses with long latency periods. Methods The objective of this study was to determine the proportion of published, peer-reviewed matched case-control studies that used statistical methods appropriate for matched data. Conclusion The findings of this study raise concern that the majority of matched case-control studies report results that are derived from improper statistical analyses.

Keywords: case-control, matched, dependent data, statistics, matched case control study. Introduction Case-control studies provide a quick and efficient means of studying diseases with long latency periods or with low incidence in the population. Methods A literature review was conducted using PubMed from January 1, to December 1, with the goal of identifying articles that employed a matched case-control design.

Open in a separate window. Results The initial search strategy yielded 74 articles Figure 1, matched case control study. Figure 1. Table 1 Details of studies included in statistical methodology analysis. Table 2 Study matched case control study and publication characteristics. Table 3 A list of the publishing journals and impact factors among the collection of articles reviewed in this study.

Discussion To our knowledge, this is the first study to assess the appropriateness of the statistical methodology used in a published series of matched case-control studies.

Conclusion The majority of matched case-control studies reviewed in this investigation used improper matched case control study methods. Ethics As this study did not involve collecting data from matched case control study, formal approval from the regional ethics board was not required. Disclosure The authors report no conflicts of interest in this work.

References 1.

 

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matched case control study

 

A case-control study is usually conducted before a cohort from the Women’s Health Study, controls were matched using random digit dialing with frequency matching on ethnicity, the three age groups (, , and ), and the seven health planning districts. Matched Pair Case-Control Study Pairs of Cases and Controls matched on defined characteristics are evaluated for exposure to a risk factor and distributed into the four cells of the table representing the four possible combinations of outcome in a pair. In contrast, the matched case-control study has linked a case to a control based on matching of one or more ipvcitysa.cf summary table will differ for a matched case-control study. Let's look at an example. Suppose we plan to match cases to controls by gender and age (+/- 5 years).