Cross-Sectional Clinical Study

A Cross-Sectional Clinical Study is an observational clinical study that consists of assessing a population sampled at a single point in time and which the main clinical measure studied is the population prevalence.

• AKA: Prevalence Clinical Study.
• Context:
  • It is (often) a retrospective study in which the risk measures are odds ratio, prevalence odds ratio, prevalence ratio, and prevalence difference.
  • Strengths/Advantages:
    • Inexpensive;
    • timely;
    • individualized data;
    • ability to control for multiple confounders;
    • can assess multiple outcomes.
  • Weaknesses/Disadvantages:
    • no temporality;
    • not good for rare diseases;
    • poor for diseases of short duration;
    • no demonstrated temporality.
• Example(s):
  • a Diagnostic Accuracy Clinical Study,
  • NCT05059184: Long-term Sequelae of COVID-19 (Myalgic Encephalomyelitis): An International Cross-Sectional Study,
  • NCT04915911: A Multi-center, Cross-sectional Observational Study on Nutritional Status and Body Composition of Adult Patients With Crohn's Disease,
  • NCT01628523: Mechanical Ventilation in the Emergency Department: A Prospective Cross-Sectional Study,
  • NCT01564953: Serum Magnesium and Nit Vitamin D is Associated With Better QoL in COPD: A Cross-sectional Study,
  • …
• Counter-Example(s):
  • Case-Control Clinical Study,
  • Case-Crossover Clinical Study,
  • Cohort Clinical Study,
  • Ecological Clinical Study,
  • Proportional Mortality Ratio (PMR) Clinical Study.
• See: Disease Exposure Measure, Health Outcome Measure, Descriptive Clinical Trial, Interventional Clinical Trial, Uncontrolled Clinical Intervention Study.

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References

2022

• (ClinicalTrials.gov, 2022) ⇒ https://clinicaltrials.gov/ct2/about-studies/glossary Retrieved:2022-02-13.
  • QUOTE: Observational study model: The general design of the strategy for identifying and following up with participants during an observational study. Types of observational study models include cohort, case-control, case-only, case-cross-over, ecologic or community studies, family-based, and other.

2016

• (Grant, 2016) ⇒ William B. Grant (2016). "The role of geographical ecological studies in identifying diseases linked to UVB exposure and/or vitamin D". In: Dermato Endocrinology 8(1):e1137400. DOI:10.1080/19381980.2015.1137400.
  • QUOTE: Observational studies come in several forms:
    • Case–control. Risk-modifying factors measured at the time of disease diagnosis.
    • Cohort and nested case–control. Subjects are enrolled in a study, risk-modifying factors are assessed, and then the cohort is monitored (for up to many years). Those who develop diseases are compared with like individuals who did not.
    • Cross-sectional. An entire population is sampled, with health status and health parameters and risk-modifying factors measured.

2014

• (Thiese, 2014) ⇒ Matthew S. Thiese. (2014). “Observational and Interventional Study Design Types; An Overview.” In: Biochemia Medica (Zagreb). Journal, 24(2).
  • QUOTE: Cross-sectional studies are also called prevalence studies because one of the main measures available is study population prevalence (...). These studies consist of assessing a population, as represented by the study sample, at a single point in time. A common cross-sectional study type is the diagnostic accuracy study, which is discussed later. Cross-sectional study samples are selected based on their exposure status, without regard for their outcome status. Outcome status is obtained after participants are enrolled. Ideally, a wider distribution of exposure will allow for a higher likelihood of finding an association between the exposure and outcome if one exists (...). Cross-sectional studies are retrospective in nature. An example of a cross-sectional study would be enrolling participants who are either current smokers or never smokers, and assessing whether or not they have respiratory deficiencies. Random sampling of the population being assessed is more important in cross-sectional studies as compared to other observational study designs. Selection bias from non-random sampling may result in flawed measure of prevalence and calculation of risk. The study sample is assessed for both exposure and outcome at a single point in time. Because both exposure and outcome are assessed at the same time, temporality cannot be demonstrated, i.e. it cannot be demonstrated that the exposure preceded the disease (...). Point prevalence and period prevalence can be calculated in cross-sectional studies. Measures of risk for the exposure-outcome relationship that can be calculated in cross-sectional study design are odds ratio, prevalence odds ratio, prevalence ratio, and prevalence difference. Cross-sectional studies are relatively inexpensive and have data collected on an individual which allows for more complete control for confounding. Additionally, cross-sectional studies allow for multiple outcomes to be assessed simultaneously.

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