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ISSN: 2161-1165
Epidemiology: Open Access
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Epidemiology Concepts for Clinical Trials

Praneeth Kamarapu*

Department of Clinical Research, Texila American University, Guyana, South America

*Corresponding Author:
Praneeth Kamarapu
Department of clinical research
Texila American University, Guyana
South America
Tel: 9247622152
E-mail: Praneeth_chakravarthi@rediff.com

Received date: December 12, 2016; Accepted date: December 20, 2016; Published date: December 27, 2016

Citation: Kamarapu P (2016) Epidemiology Concepts for Clinical Trials. Epidemiology (Sunnyvale) 6:284. doi: 10.4172/2161-1165.1000284

Copyright: © 2016 Kamarapu P. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

This article will encompass the discussion around the ideas of affiliation and results for present standard epidemiological ideas of rate and commonness characterize and portray the observational methods. In this paper we have shown that there are many possible sources of Error that can result in systematic distortions of study results.

Keywords

Epidemiology; Cross-sectional; Case-control studies; Lung cancer

Introduction

The study of epidemiology refers to the investigation of illness, diseases and causative reasons in populations, epidemiology serves as the gold standard of population health assessment. Epidemiological studies varies from routine medical procedures although remains the major impactful assessment for a probable or particular disease in a reasonably large population. Powerful epidemic predictions may provide preparatory time for the whole medical community. Accomplice, cross sectional, and case-control studies are altogether indicated as observational studies. Regularly these studies are the main practical technique for considering different issues, Cohort studies are utilized to study rate, reasons, and anticipation. Cross-sectional studies are used to determine prevalence. They are quite quick and convenient but do not permit difference between cause and effect. Case-control studies compare organizations retrospectively. They seek to identify possible predictors of outcome and are useful for studying rare diseases or outcomes. The crucial point of a clinical trial is the aim of investigating the difference of the patient groups caused only by the treatment procedures that are applied [1-10].

In modern times, classical epidemiological methods gradually evolved and rendered support from the case-control study to demonstrate an association between the cause and the effect of the diseases in a quantitative manner, such as, smoking and lung cancer, use of the prospective cohort study to determine risk factors for cardiovascular disease in the Framingham Heart Study, and use of the randomized clinical trial for the poliomyelitis vaccine 1. The evidencebased medicine and patient-derived outcomes assessment movements burst onto the scene of clinical medicine in the 1980s and 1990s as a result of contemporaneous medical, societal, and economic influences [11-24].

Cohort Studies

Cohort report describes incidence or common historical past. They analyse predictors (hazard causes) thereby enabling calculation of relative risk. Cohort reports measure interests in temporal sequence thereby distinguishing factors from effects. Confounding variables are the predominant concern in analysing cohort studies [25-33].

Advantages and disadvantages of cohort studies

Using cohorts is by and large obligatory as a randomised managed trial could also be unethical. The other advantage is that a single study can examine quite a lot of effects of the considered variables. These strategies actually remain in contrast with case-control reports as they determine only one effective variable. Cohorts allow calculation of the effect of every variable on the likelihood of setting up the final result of interest. However, where a distinctive outcome is infrequent, in such cases, a prospective cohort learning is inefficient. Yet another obstacle with potential cohort experiences is the lack of subjects to follow up the study. This vastly affects the final result of the study along with lower level of confidence limit [34-38].

Nevertheless, it's not likely that bronchial asthma in itself confers any protection against lung cancer. It is probable that the incidence of lung melanoma is shrinking in people with bronchial asthma when we consider that fewer asthmatics smoke cigarettes (confounding variable). The one option to eliminate all likelihood of a confounding variable is through a prospective randomised managed trial to be trained.

Cross-Sectional Studies

Cross sectional studies are the best way to determine prevalence and are relatively quick. Moreover, this type of studies is able to produce multiple outcomes. This study type does not themselves differentiate between cause and effect or the sequence of events [39-44].

Advantages and disadvantages

The essential advantage of cross sectional studies is that it is very economical to conduct and follows a fast process. In this type of study there is no monitoring, only smaller amount of resource required. Cross sectional studies are only solution to find out prevalence and are also helpful in the case of identifying associations which may be rigorously studied by a cohort study. “The major problem in gaining knowledge with this type of study is to differentiate the cause and the observed result from simple association”. Although, Moreover, male homosexuality is associated with each but motives neither. This is another instance of a confounding variable and its relevance. As a rule, there are quantities of believable explanations. Rare conditions cannot effectively be studied making use of pass sectional reviews when we consider that even in giant samples there could also be nobody with the ailment. In this problem it is higher to be taught a go sectional sample of sufferers who already have the disease (a case series). On this way it was discovered in 1983 that of a thousand patients with AIDS, 727 had been gay or bisexual guys and 236 had been intravenous drug abusers. the conclusion that participants in these two groups had a bigger relative risk was once inescapable. The natural history of HIV infection was once then studied utilizing cohort stories and efficacy of therapies by way of case-controlled stories and randomized clinical trials [45-51].

Case-Control Studies

Compared to the cohort and cross-sectional studies, case-control studies are usually retrospective. Case-control studies are simple to organize, retrospectively compare two groups to find out the predictors of an outcome. Permit assessment of the influence of predictors on outcome via calculation of an odds ratio [52-55].

Advantages and disadvantages of case-control studies

When conditions are uncommon, case-control studies generate a lot of information from relatively few subjects. When there is a long latent period between an exposure and the disease, case-control studies are the only feasible option. With less than 300 demonstrated case a cross sectional be taught would need about 200 000 objects to include one symptomatic patient. Given a postulated latency of 10 to 30 years a cohort be taught would require each a significant sample size and take iteration to entire. In case-control reports comparatively few topics are required so more assets are on hand for finding out each and every. As a result an enormous quantity of variables can also be regarded. This form of learn is for this reason priceless for producing hypotheses that may then be proven utilizing other types of study. This flexibility of the variables studied comes at the cost of the restrained outcomes. The one final result is the presence or absence of the sickness or whatever criteria have been chosen to select the instances. The most important issues with case-control reports are the familiar ones of confounding variables and bias [56-60].

Discussion and Conclusion

Our discussion and examples above have shown that there are many possible sources of error that can result in systematic distortions of study results. These distortions are a problem, especially when the epidemiologist is estimating the association between a risk factor and a health problem. Whether a risk factor or a protective factor goes undetected, or a normal behavior or condition is misidentified as a risk or protective factor, the implications may bring serious consequences for the public. An erroneously identified risk element may cause unnecessary fear among the public or possibly a needless diversion of the limited study funds. Epidemiologists conducting observational studies (cohort, go-sectional and in particular case–manipulate need to be conscious of the expertise for biases and exert additional care to do away with or slash their outcome. As an interpreter of reports we, the general public, have to be mindful of the viable biases in such reviews after we overview their conclusions as suggested by the mass media.

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