Traditional Case-control Design Research Articles

Translational potential of human brain charts.

Translational potential of human brain charts.

Current Approaches to Vaccine Safety Using Observational Data: A Rationale for the EUMAEUS (Evaluating Use of Methods for Adverse Events Under Surveillance-for Vaccines) Study Design.

Post-marketing vaccine safety surveillance aims to detect adverse events following immunization in a population. Whether certain methods of surveillance are more precise and unbiased in generating safety signals is unclear. Here, we synthesized information from existing literature to provide an overview of the strengths, weaknesses, and clinical applications of epidemiologic and analytical methods used in vaccine monitoring, focusing on cohort, case-control and self-controlled designs. These designs are proposed to be evaluated in the EUMAEUS (Evaluating Use of Methods for Adverse Event Under Surveillance–for vaccines) study because of their widespread use and potential utility. Over the past decades, there have been an increasing number of epidemiological study designs used for vaccine safety surveillance. While traditional cohort and case-control study designs remain widely used, newer, novel designs such as the self-controlled case series and self-controlled risk intervals have been developed. Each study design comes with its strengths and limitations, and the most appropriate study design will depend on availability of resources, access to records, number and distribution of cases, and availability of population coverage data. Several assumptions have to be made while using the various study designs, and while the goal is to mitigate any biases, violations of these assumptions are often still present to varying degrees. In our review, we discussed some of the potential biases (i.e., selection bias, misclassification bias and confounding bias), and ways to mitigate them. While the types of epidemiological study designs are well established, a comprehensive comparison of the analytical aspects (including method evaluation and performance metrics) of these study designs are relatively less well studied. We summarized the literature, reporting on two simulation studies, which compared the detection time, empirical power, error rate and risk estimate bias across the above-mentioned study designs. While these simulation studies provided insights on the analytic performance of each of the study designs, its applicability to real-world data remains unclear. To bridge that gap, we provided the rationale of the EUMAEUS study, with a brief description of the study design; and how the use of real-world multi-database networks can provide insights into better methods evaluation and vaccine safety surveillance.

Theoretical Framework for Retrospective Studies of the Effectiveness of SARS-CoV-2 Vaccines.

Observational studies of the effectiveness of vaccines to prevent COVID-19 are needed to inform real-world use. Such studies are now underway amid the ongoing rollout of SARS-CoV-2 vaccines globally. Although traditional case-control and test-negative design studies feature prominently among strategies used to assess vaccine effectiveness, such studies may encounter important threats to validity. Here, we review the theoretical basis for estimation of vaccine direct effects under traditional case-control and test-negative design frameworks, addressing specific natural history parameters of SARS-CoV-2 infection and COVID-19 relevant to these designs. Bias may be introduced by misclassification of cases and controls, particularly when clinical case criteria include common, nonspecific indicators of COVID-19. When using diagnostic assays with high analytical sensitivity for SARS-CoV-2 detection, individuals testing positive may be counted as cases even if their symptoms are due to other causes. The traditional case-control design may be particularly prone to confounding due to associations of vaccination with healthcare-seeking behavior or risk of infection. The test-negative design reduces but may not eliminate this confounding, for instance, if individuals who receive vaccination seek care or testing for less-severe illness. These circumstances indicate the two study designs cannot be applied naively to datasets gathered through public health surveillance or administrative sources. We suggest practical strategies to reduce bias in vaccine effectiveness estimates at the study design and analysis stages.

The Development of Anxiety in Youth Study (DAYS): A Prospective Study of Trajectories of Brain Maturation among Youth at Risk for Anxiety

Anxiety disorders are common across development and are associated with significant functional impairment and distress. Despite neuroimaging advancements in uncovering key brain regions, including the amygdala and prefrontal regions, implicated in anxiety, there is a need to characterize the role of the ventral striatum given its well-documented link to several key anxiety processes. This study aims to characterize specific neural mechanisms that underlie the evolution of illness and impairment using a longitudinal design and to move beyond traditional case control designs to provide a more comprehensive view of the developmental psychopathology of pediatric anxiety.

A comparison of the test-negative and traditional case-control study designs with respect to the bias of estimates of rotavirus vaccine effectiveness

Estimation of the effectiveness of rotavirus vaccines via the test-negative control study design has gained popularity over the past few years. In this study design, children with severe diarrhea who test positive for rotavirus infection are considered as cases, while children who test negative serve as controls. We use a simple probability model to evaluate and compare the test-negative control and the traditional case-control designs with respect to the bias of resulting estimates of rotavirus vaccine effectiveness (VE). Comparisons are performed under two scenarios, corresponding to studies performed in high-income and low-income countries. We consider two potential sources of bias: (a) misclassification bias resulting from imperfect sensitivity and specificity of the test used to diagnose rotavirus infection, and (b) selection bias associated with possible effect of rotavirus vaccination on the probability of contracting severe non-rotavirus diarrhea.Our results suggest that both sources of bias may produce VE estimates with substantial bias. Particularly, lack of perfect specificity is associated with severe negative bias. For example, if the specificity of the diagnostic test is 90% then VE estimates from both types of case-control studies may under-estimate the true VE by more than 20%. If the vaccine protects children against non-rotavirus diarrhea then VE estimates from test-negative control studies may be close to zero even though the true VE is 50%. However, the sensitivity and specificity of the enzyme immunoassay test currently used to diagnose rotavirus infections are both over 99%, and there is no solid evidence that the existing rotavirus vaccines affect the rates of non-rotavirus diarrhea. We therefore conclude that the test-negative control study design is a convenient and reliable alternative for estimation of rotavirus VE.

Effectiveness of inactivated quadrivalent influenza vaccine in the 2015/2016 season as assessed in both a test-negative case-control study design and a traditional case-control study design.

Both studies confirmed significant VE against influenza A, significant two-dose VE against influenza B, and better two-dose VE than one-dose VE. What is Known: • Influenza vaccine effectiveness (VE) varies from year to year. • Observational studies are conventionally used for VE assessment. However, they are inherently susceptible to bias and confounding. What is New: • This is the first report of influenza VE assessment using more than one observational study and performed in a specific area during the same season. • VE estimates obtained in our traditional case-control study were lower than those in our test-negative case-control study, but both studies found significant VE against influenza.

A comparison of the test-negative and the traditional case-control study designs for estimation of influenza vaccine effectiveness under nonrandom vaccination

BackgroundAs annual influenza vaccination is recommended for all U.S. persons aged 6 months or older, it is unethical to conduct randomized clinical trials to estimate influenza vaccine effectiveness (VE). Observational studies are being increasingly used to estimate VE. We developed a probability model for comparing the bias and the precision of VE estimates from two case-control designs: the traditional case-control (TCC) design and the test-negative (TN) design. In both study designs, acute respiratory illness (ARI) patients seeking medical care testing positive for influenza infection are considered cases. In the TN design, ARI patients seeking medical care who test negative serve as controls, while in the TCC design, controls are randomly selected individuals from the community who did not contract an ARI.MethodsOur model assigns each study participant a covariate corresponding to the person’s health status. The probabilities of vaccination and of contracting influenza and non-influenza ARI depend on health status. Hence, our model allows non-random vaccination and confounding. In addition, the probability of seeking care for ARI may depend on vaccination and health status. We consider two outcomes of interest: symptomatic influenza (SI) and medically-attended influenza (MAI).ResultsIf vaccination does not affect the probability of non-influenza ARI, then VE estimates from TN studies usually have smaller bias than estimates from TCC studies. We also found that if vaccinated influenza ARI patients are less likely to seek medical care than unvaccinated patients because the vaccine reduces symptoms’ severity, then estimates of VE from both types of studies may be severely biased when the outcome of interest is SI. The bias is not present when the outcome of interest is MAI.ConclusionsThe TN design produces valid estimates of VE if (a) vaccination does not affect the probabilities of non-influenza ARI and of seeking care against influenza ARI, and (b) the confounding effects resulting from non-random vaccination are similar for influenza and non-influenza ARI. Since the bias of VE estimates depends on the outcome against which the vaccine is supposed to protect, it is important to specify the outcome of interest when evaluating the bias.

Hyperactivity of the default-mode network in first-episode, drug-naive schizophrenia at rest revealed by family-based case-control and traditional case-control designs.

Abnormal regional activity and functional connectivity of the default-mode network (DMN) have been reported in schizophrenia. However, previous studies may have been biased by unmatched case-control design. To limit such bias, the present study used both the family-based case-control design and the traditional case-control design to investigate abnormal regional activity of the DMN in patients with schizophrenia at rest.Twenty-eight first-episode, drug-naive patients with schizophrenia, 28 age-, sex-matched unaffected siblings of the patients (family-based controls, FBC), and 40 healthy controls (HC) underwent resting-state functional magnetic resonance imaging (fMRI) scans. The group-independent component analysis and fractional amplitude of low-frequency fluctuation (fALFF) methods were used to analyze the data.Patients with schizophrenia show increased fALFF in an overlapped region of the right superior medial prefrontal cortex (MPFC) relative to the FBC and the HC. Compared with the HC, the patients and the FBC exhibit increased fALFF in an overlapped region of the left posterior cingulate cortex/precuneus (PCC/PCu). Furthermore, the z values of the 2 overlapped regions can separate the patients from the FBC/HC, and separate the patients/FBC from the HC with relatively high sensitivity and specificity.Both the family-based case-control and traditional case-control designs reveal hyperactivity of the DMN in first-episode, drug-naive patients with paranoid schizophrenia, which highlights the importance of the DMN in the neurobiology of schizophrenia. Family-based case-control design can limit the confounding effects of environmental factors in schizophrenia. Combination of the family-based case-control and traditional case-control designs may be a viable option for the neuroimaging studies.

A probability model for evaluating the bias and precision of influenza vaccine effectiveness estimates from case-control studies.

As influenza vaccination is now widely recommended, randomized clinical trials are no longer ethical in many populations. Therefore, observational studies on patients seeking medical care for acute respiratory illnesses (ARIs) are a popular option for estimating influenza vaccine effectiveness (VE). We developed a probability model for evaluating and comparing bias and precision of estimates of VE against symptomatic influenza from two commonly used case-control study designs: the test-negative design and the traditional case-control design. We show that when vaccination does not affect the probability of developing non-influenza ARI then VE estimates from test-negative design studies are unbiased even if vaccinees and non-vaccinees have different probabilities of seeking medical care against ARI, as long as the ratio of these probabilities is the same for illnesses resulting from influenza and non-influenza infections. Our numerical results suggest that in general, estimates from the test-negative design have smaller bias compared to estimates from the traditional case-control design as long as the probability of non-influenza ARI is similar among vaccinated and unvaccinated individuals. We did not find consistent differences between the standard errors of the estimates from the two study designs.

Genetic discoveries in AD using CSF amyloid and tau.

The use of cerebrospinal fluid levels of Aβ42 and pTau181 as endophenotypes for genetic studies of Alzheimer's disease (AD) has led to successful identification of both rare and common AD risk variants. In addition, this approach has provided meaningful hypotheses for the biological mechanisms by which known AD risk variants modulate the disease process. In this article we discuss these successes and outline challenges to effective and continued applications of this approach. We contrast the statistical power of this approach with traditional case-control designs and discuss solutions to address challenges in quality control and data analysis for these phenotypes. Finally, we discuss the potential for the use of this approach with larger samples as well as the incorporation of next generation sequencing and for future work with other endophenotypes for AD.

A comparison of pharmacoepidemiological study designs in medication use and traffic safety research

In order to explore how the choice of different study designs could influence the risk estimates, a case–crossover and case–time–control study were carried out and their outcomes were compared with those of a traditional case–control study design that evaluated the association between the exposure to psychotropic medications and the risk of having a motor vehicle accident (MVA). A record-linkage database availing data for 3,786 cases and 18,089 controls during the period 2000–2007 was used. The study designs (i.e., case–crossover and case–time–control) were derived from published literature, and the following psychotropic medicines were examined: antipsychotics, anxiolytics, hypnotics and sedatives, and antidepressants, stratified in the two groups selective serotonin reuptake inhibitors (SSRIs) and other antidepressants. Moreover, in order to further investigate the effects of frequency of psychoactive medication exposure on the outcomes of the case–crossover analysis, the data were also stratified by the number of defined daily doses (DDDs) and days of medication use in the 12 months before the motor vehicle accident. Three-thousand seven-hundred fifty-two cases were included in this second part of the case–crossover analysis. The case–crossover design did not show any statistically significant association between psychotropic medication exposure and MVA risk [e.g., SSRIs—Adj. OR = 1.00 (95 % CI: 0.69–1.46); Anxiolytics—Adj. OR = 0.95 (95 % CI: 0.68–1.31)]. The case–time–control design only showed a borderline statistically significant increased traffic accident risk in SSRI users [Adj. OR = 1.16 (95 % CI: 1.01–1.34)]. With respect to the stratifications by the number of DDDs and days of medication use, the analyses showed no increased traffic accident risk associated with the exposure to the selected medication groups [e.g., SSRIs, <20 DDDs—Adj. OR = 0.65 (95 % CI: 0.11–3.87); SSRIs, 16–150 days—Adj. OR = 0.55 (95 % CI: 0.24–1.24)]. In contrast to the above-mentioned results, our recent case–control study found a statistically significant association between traffic accident risk and exposure to anxiolytics [Adj. OR = 1.54 (95 % CI: 1.11–2.15)], and SSRIs [Adj. OR = 2.03 (95 % CI: 1.31–3.14)]. Case–crossover and case–time–control analyses produced different results than those of our recent case–control study (i.e., case–crossover and case–time–control analyses did not show any statistically significant association whereas the case–control analysis showed an increased traffic accident risk in anxiolytic and SSRI users). These divergent results can probably be explained by the differences in the study designs. Given that the case–crossover design is only appropriate for short-term exposures and the case–time–control design is an elaboration of this latter, it can be concluded that, probably, these two approaches are not the most suitable ones to investigate the relation between MVA risk and psychotropic medications, which, on the contrary, are often use chronically.

Using offspring-parent triads to study complex traits: A tutorial based on orofacial clefts

Health investigators routinely collect DNA and environmental data from study participants in order to assess the impact of genetic and environmental risk factors on an outcome of interest. When planning a study, alternate study designs are evaluated to minimize bias and achieve a large enough sample size from available resources. With the enormous volumes of high-quality biomedical data housed within its numerous biobanks, Norway is particularly well-suited to spearhead the investigation of a wide array of exposures and outcomes in a systematic manner. The rich array of longitudinal phenotypic data also permits an assessment of geneenvironment- timing interactions. Maximizing the research potential inherent in Norwegian biobanks is the overarching aim of Biobank Norway, an infrastructure project recently funded by the Norwegian Research Council. The development of advanced statistical tools for the analysis of high-throughput genomic data is critical to fulfill this aim and biostatistics platforms have been key elements of major biobank harmonization initiatives. However, many of these approaches have focused on traditional case-control designs. To exploit the particular advantages inherent in the Norwegian Mother and Child Cohort Study (MoBa), we describe here models to analyze the special data configurations available with offspring-parent designs. These models and the statistical tools outlined in this review were developed through the support of Biohealth Norway, a biobank platform funded by the Norwegian Functional Genomics Research Program (FUGE).

Differing risk factors for vancomycin-resistant and vancomycin-sensitive enterococcal bacteraemia

Enterococcus is an important cause of bacteraemia. Previous epidemiological studies examining risk factors for enterococcal bacteraemia have used traditional case-control study designs, which can be potentially biased. This case-case-control study examining risk factors for enterococcal bacteraemia was conducted over 10 years (January 2000 to December 2009) in a tertiary, university-affiliated hospital. There were 440 episodes of enterococcal bacteraemia, 80 of which were caused by vancomycin-resistant Enterococcus (VRE). Two multivariable models were generated, comparing VRE and vancomycin-susceptible Enterococcus (VSE) with the same control group. VRE bacteraemia was associated with central venous catheter use (OR 11.6, 95% CI 2.6–51.5), neutropenia (OR 16.9, 95% CI 2.4–120.2), and allogenic bone marrow transplantation (OR 18.0, 95% CI 2.4–133.4). In contrast, VSE bacteraemia risk factors included: age (OR 1.0, 95% CI 1.0–1.1), exposure to metronidazole (OR 8.7, 95% CI 1.7–43.5), and gastrointestinal disease (OR 6.4, 95% CI 1.2–34.5). Meropenem use decreased the risk of VSE bacteraemia (OR 0.3, 95% CI 0.1–0.9). Hypoalbuminaemia was the only factor identified in both models (VRE, OR 6.0, 95% CI 1.7–21.1; VSE, OR 3.3, 95% CI 1.4–7.7). The absence of substantial overlap of risk factors for VRE and VSE argues in favour of differences in pathogenesis. These data suggest that environmental sources are more important in VRE bacteraemia. Endogenous sources, particularly the gastrointestinal tract, play a pivotal role in VSE bacteraemia. This study highlights the importance of infection control protocols to reduce the risk of VRE bacteraemia.

Candidate gene analysis of spontaneous preterm delivery: New insights from re-analysis of a case-control study using case-parent triads and control-mother dyads

BackgroundSpontaneous preterm delivery (PTD) has a multifactorial etiology with evidence of a genetic contribution to its pathogenesis. A number of candidate gene case-control studies have been performed on spontaneous PTD, but the results have been inconsistent, and do not fully assess the role of how two genotypes can impact outcome. To elucidate this latter point we re-analyzed data from a previously published case-control candidate gene study, using a case-parent triad design and a hybrid design combining case-parent triads and control-mother dyads. These methods offer a robust approach to genetic association studies for PTD compared to traditional case-control designs.MethodsThe study participants were obtained from the Norwegian Mother and Child Cohort Study (MoBa). A total of 196 case triads and 211 control dyads were selected for the analysis. A case-parent triad design as well as a hybrid design was used to analyze 1,326 SNPs from 159 candidate genes. We compared our results to those from a previous case-control study on the same samples. Haplotypes were analyzed using a sliding window of three SNPs and a pathway analysis was performed to gain biological insight into the pathophysiology of preterm delivery.ResultsThe most consistent significant fetal gene across all analyses was COL5A2. The functionally similar COL5A1 was significant when combining fetal and maternal genotypes. PON1 was significant with analytical approaches for single locus association of fetal genes alone, but was possibly confounded by maternal effects. Focal adhesion (hsa04510), Cell Communication (hsa01430) and ECM receptor interaction (hsa04512) were the most constant significant pathways.ConclusionThis study suggests a fetal association of COL5A2 and a combined fetal-maternal association of COL5A1 with spontaneous PTD. In addition, the pathway analysis implied interactions of genes affecting cell communication and extracellular matrix.

Challenges and directions: an analysis of Genetic Analysis Workshop 17 data by collapsing rare variants within family data

Recent studies suggest that the traditional case-control study design does not have sufficient power to discover rare risk variants. Two different methods—collapsing and family data—are suggested as alternatives for discovering these rare variants. Compared with common variants, rare variants have unique characteristics. In this paper, we assess the distribution of rare variants in family data. We notice that a large number of rare variants exist only in one or two families and that the association result is largely shaped by those families. Therefore we explore the possibility of integrating both the collapsing method and the family data method. This combinational approach offers a potential power boost for certain causal genes, including VEGFA, VEGFC, SIRT1, SREBF1, PIK3R3, VLDLR, PLAT, and FLT4, and thus deserves further investigation.

Value of the small cohort study including a physical examination for minor structural defects in identifying new human teratogens

Most known human teratogens are associated with a unique or characteristic pattern of major and minor malformations and this pattern helps to establish the causal link between the teratogenic exposure and the outcome. Although traditional case-control and cohort study designs can help identify potential teratogens, there is an important role for small cohort studies that include a dysmorphological examination of exposed and unexposed infants for minor structural defects. In combination with other study design approaches, the small cohort study with a specialized physical examination fulfills a necessary function in screening for new potential teratogens and can help to better delineate the spectrum and magnitude of risk for known teratogens.

The Case-Crossover Study: A Novel Design in Evaluating Transient Fatigue as a Risk Factor for Road Traffic Accidents

The Case-Crossover Study: A Novel Design in Evaluating Transient Fatigue as a Risk Factor for Road Traffic Accidents

Disease Associations and Family‐Based Tests

This unit describes the statistical techniques necessary for performing family-based association studies (such as the TDT) for genetic polymorphisms. Such studies have become increasingly important in the identification of genes that confer an increased risk to disease, particularly for common diseases with a complex etiology. The family-based approach avoids some of the problems often encountered when applying the traditional case-control design to genetic studies. The unit includes the Sib TDT (S-TDT) method, which allows application of the principle of the TDT to sibships without parental data, and several related tests.

The use of primary care databases: case-control and case-only designs

Study designs based on the identification of cases are frequently utilized when undertaking epidemiological research. Traditionally these have been mainly based on identification of cases from hospital records. This paper discusses the use of study designs based on the identification of cases focusing on their application to research data derived from primary care. The designs are discussed in the context of using computerized clinical data derived from primary care. The traditional case-control design is considered, with emphasis on the identification of cases and the selection of controls. A common problem when using primary care research databases is that information about potential confounding variables is often limited. Case-only designs, specifically the case-crossover and the within-person case-series, offer alternative designs that aim to overcome problems with confounding. The principles underlying these case-only designs are presented along with examples of their use. The advantages and limitations of the different designs are discussed.

Apolipoprotein E genotype frequency patterns in aged Danes as revealed by logistic regression models.

Although the ApoE gene has been intensively studied in aging research, most of the studies conducted so far have been based on the traditional case-control design with subjects consisting of young controls and long-lived cases. The genotype frequency pattern in and between the two age-groups has been rarely investigated due to limitations in either research design or data analytical method. In this study, we genotyped 748 individuals (including both twin pairs and unrelated individuals) aged from 73 to 95 with aim at examining the genotype frequency trajectory of ApoE gene at high ages. Binomial and multinomial logistic regression models have been applied to model the gene frequency as a function of age and to investigate the modes of gene function (dominant, recessive, additive). The generalized estimation equations (GEEs) are introduced to account for the intra-pair genotype correlation in the twin pairs included in the data. Both the observed and the fitted frequencies show a constantly declining pattern of ApoE epsilon4 allele as age advances indicating a significant and steadily deleterious effect of the dominant allele that increases the hazard of death at high ages.