Case-Control Studies

2019 ◽  
pp. 169-186
Author(s):  
Daniel Westreich

In contrast to an observational cohort study in which participants are identified, exposures are measured, and then outcomes status is measured after follow-up, a case-control study is an observational study in which researchers sample participants based on their outcome status, often only after all outcomes have already occurred. This chapter echoes the structure of the previous two chapters in the discussion of case-control studies. In this chapter, the author’s focus is on understanding the relationship between cohort studies and case-control studies and on how the interpretation of the odds ratio estimated from the case-control study depends on the relationship of the case-control study to a cohort study.

2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
Hui Liu

Objective. Although the relative risk from a prospective cohort study is numerically approximate to the odds ratio from a case-control study for a low-probability event, a definite relationship between case-control and cohort studies cannot be confirmed. In this study, we established a different model to determine the relationship between case-control and cohort studies. Methods. Two analysis models (the cross-sectional model and multiple pathogenic factor model) were established. Incidences in both the exposure group and the nonexposure group in a cohort study were compared with the frequency of the observed factor in each group (diseased and nondiseased) in a case-control study. Results. The relationship between the results of a case-control study and a cohort study is as follows: Pe=Pd∗m/Pc∗1−m+Pd∗m; Pn=m∗1−Pd/1−Pc∗1−m−Pd∗m, where Pe and Pn represent the incidence in the exposed group and nonexposed group, respectively, from the cohort study, while Pd and Pc represent the observed frequencies in the disease group and the control group, respectively, for the case-control study; finally, m represents the incidence in the total population. Conclusions. There is a definite relationship between the results of case-control and cohort studies assessing the same exposure. The outcomes of case-control studies can be translated into cohort study data.


2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Jiakai Jiang ◽  
Sheng Zhang ◽  
Weifeng Tang ◽  
Zhiyuan Qiu

Abstract Previous studies suggested that miR-146a rs2910164 (C/G) locus was predicted to influence the risk of cancer. However, the relationship of miR-146a rs2910164 locus with colorectal cancer (CRC) susceptibility was controversial. We recruited 1003 CRC patients and 1303 controls, and performed a case–control study to clarify the correlation of miR-146a rs2910164 locus with CRC risk. Subsequently, a comprehensive meta-analysis was conducted to verify our findings. In the case–control study, we suggested that miR-146a rs2910164 variants did not alter CRC risk (CG vs. CC: adjusted P=0.465; GG vs. CC: adjusted P=0.436, CG/GG vs. CC: adjusted P=0.387 and GG vs. CC/CG: adjusted P=0.589), even in subgroup analysis. Next, we conducted a pooled-analysis to identify the correlation of miR-146a rs2910164 locus with CRC risk. In this pooled-analysis, 7947 CRC cases and 12,168 controls were included. We found that miR-146a rs2910164 polymorphism did not influence the risk of CRC (G vs. C: P=0.537; GG vs. CC: P=0.517, CG/GG vs. CC: P=0.520 and GG vs. CC/CG: P=0.167). Our findings suggest that miR-146a rs2910164 C/G polymorphism is not correlated with the susceptibility of CRC. In the future, more case–control studies are needed to confirm our results.


2020 ◽  
pp. 159-180
Author(s):  
Bendix Carstensen

This chapter addresses Case-control and case-cohort studies. In a Case-control study, one samples persons based on their disease outcome, so the fraction of diseased persons in a Case-control study is usually known (at least approximately) before data collection. In a cohort (follow-up) study, the relationship between some exposure and disease incidence is investigated by following the entire cohort and measuring the rate of occurrence of new cases in the different exposure groups. The follow-up records all persons who develop the disease during the study period. Implicit in this is that the relevant exposure information is available at all times for all persons under follow-up. The chapter then looks at the statistical model for the odds ratio, before differentiating between odds ratio and rate ratio. It also considers confounding and stratified sampling; individually matched studies; and nested Case-control studies.


2017 ◽  
Vol 1 (2) ◽  
pp. 6
Author(s):  
NFN Jahiroh ◽  
Nurhayati Prihartono

Abstrak : Tuberkulosis (TB) dan stunting masih menjadi masalah kesehatan di Indonesia. Tujuan penelitian adalah mengetahui hubungan stunting dengan kejadian TB pada anak usia 1-59 bulan. Penelitian ini menggunakan desain kasus-kontrol. Kasus adalah anak usia 1-59 bulan yang berobat di puskesmas yang didiagnosis TB oleh dokter menggunakan sistem skoring. Kontrol adalah anak usia 1-59 bulan yang berkunjung ke puskesmas yang sama dengan kasus, didiagnosis bukan TB. Pemilihan kontrol menggunakan teknik sampling acak sederhana. Balita dengan TB dan bukan TB terdistribusi yang hampir sama menurut jenis kelamin dan ventilasi rumah. Jika dibandingkan dengan balita gizi normal, balita gizi stunting mempunyai risiko yang lebih tinggi sakit TB. Balita pendek dan sangat pendek mempunyai risiko masing-masing 3,5 kali dan 9 kali sakit TB [adjusted odds ratio (OR = 3.54; P = 0,004 and and OR = 9.06; P = 0.001) respectively. Ditinjau dari segi imunisasi BCG, balita yang tidak diimunisasi dibandingkan yang diimunisasi BCG mempunyai risiko 4 kali sakit TB. Pada kontak serumah dengan pasien TB, balita yang mempunyai kontak dibandingkan tidak mempunyai kontak serumah dengan pasien TB berisiko hampir 12 kali sakit TB (OR = 11.96; P = 0.000). Sedangkan jika ditinjau dari usia balita, balita usia < 24 bulan dibandingkan balita usia > 24 bulan mempunyai risiko 2,8 kali sakit TB OR = 2.84; P = 0.011). Balita stunting, yang tidak diimunisasi, dan yang mempunyai kontak TB serumah TB mempunyai risiko lebih besar sakit TB. Abstract : Tuberculosis (TB) and stunting remain a health problem in Indonesia. The objective orf this study was to identify the relationship of stunting with the incidence of TB in children aged 1-59 months. This case-control study in district of West Bandung (West Java). Cases were children aged 1-59 months who visited at clinic health center diagnosed TB by a doctor using a scoring system. Controls were the same age who visited the same clinic with the case, not diagnosed TB. Balita dengan TB dan bukan TB terdistribusi yang hampir sama menurut jenis kelamin dan ventilasi rumah. Jika dibandingkan dengan balita gizi normal, balita gizi stunting mempunyai risiko yang lebih tinggi sakit TB. Balita pendek dan sangat pendek mempunyai risiko masing-masing 3,5 kali dan 9 kali sakit TB [adjusted odds ratio (OR = 3.54; P = 0,004 and and OR = 9.06; P = 0.001) respectively. Ditinjau dari segi imunisasi BCG, balita yang tidak diimunisasi dibandingkan yang diimunisasi BCG mempunyai risiko 4 kali sakit TB. Pada kontak serumah dengan pasien TB, balita yang mempunyai kontak dibandingkan tidak mempunyai kontak serumah dengan pasien TB berisiko hampir 12 kali sakit TB (OR = 11.96; P = 0.000). Sedangkan jika ditinjau dari usia balita, balita usia < 24 bulan dibandingkan balita usia lebih 24 bulan mempunyai risiko 2,8 kali sakit TB OR = 2.84; P = 0.011). Stunting toddler, not immunized, and had TB contact at home had higher risk to be TB.


2017 ◽  
Vol 1 (2) ◽  
pp. 85-92
Author(s):  
Maya Sofiyani ◽  
M Imron Mawardi ◽  
P Sigit Purnomo ◽  
Hariza Adnani

The effort of leptospirosis prevention in Sleman currently only limited to counseling and treatment of the patient, while the patient search, ways of transmission of leptospirosis from rats to humans, have never implemented in an integrated manner. The study aimed to investigated the relationship between the environmental residential condition with the risk of leptospirosis in Sleman Regency. The research used a survey method  with case control study design. The results showed that environmental factors, which are not proved to have a relationship with the risk of leptospirosis were residential condition ({p=0,108} OR=3,818 {95%CI:0,922–15,811}), the trash bin condition ({p=1,000} OR=1,138 {95%CI:0,420–3,081}) and the sewer condition ({p=0,415} OR=0,551 {95%CI:0,187–1,624}). Environmental factors that associated with the risk of leptospirosis was the presence of rats ({p=0,001} OR=13,594 {95%CI:2,754–67,107}). The effort should be made in order to prevent the increasement of Leptospirosis cases by sanitation improvement and avoiding direct contact with rats as well as it litter. The Government should be pay more attention in the vector control programs, especially in leptospirosis prone areas so the prevention effort to be able run effectively and efficiently.


2021 ◽  
Vol Volume 17 ◽  
pp. 903-908
Author(s):  
Muhammad Asif Syed ◽  
Aneela Atta Ur Rahman ◽  
Muhammad Nadeem Shah Syed ◽  
Naveed Masood Memon

1996 ◽  
Vol 17 (4) ◽  
pp. 249-255
Author(s):  
Jonathan Freeman

AbstractWe provide guidance for new practitioners in the vocabulary of modern epidemiology and the application of quantitative methods. Most hospital epidemiology involves surveillance (observational) data that were not part of a planned experiment, so the rubric and logic of controlled experimental studies cannot be applied. Forms of incidence and prevalence often are confused. The names “cohort study” and “case-control study” are unfortunate, as cohort studies rarely involve cohorts and case-control studies allow no active control by the investigator. Either type of study can be prospective or retrospective. Results of studies with discrete outcomes (infected or not, lived or died) often are represented best by a form of the risk ratio with 95% confidence intervals. The potential distorting effects of selection bias, misclassification, and confounding need to be considered.


Sign in / Sign up

Export Citation Format

Share Document