1. Bortz J, Döring N. Forschungsmethoden und Evaluation. Springer: Berlin, Heidelberg, New York; 2002. pp. 39–84.
2. Bortz J, Döring N. Forschungsmethoden und Evaluation. Berlin, Heidelberg, New York: Springer; 2002. 37 pp.
3. Fletcher RH, Fletcher SW. Klinische Epidemiologie. Grundlagen und Anwendung. Bern: Huber; 2007. pp. 1–327.
4. Altman DG. Practical statistics for medical research. 1. Aufl. Boca Raton, London, New York, Washington D.C.: Chapman & Hall; 1991. pp. 1–499.
5. Schumacher M, Schulgen G. Methodik klinischer Studien. 2. Aufl. Berlin, Heidelberg, New York: Springer; 2007. pp. 1–436.
6. Machin D, Campbell MJ, Fayers PM, Pinol APY. Sample size tables for clinical studies. 2. Aufl. Oxford, London, Berlin: Blackwell Science Ltd.; 1987. pp. 1–303.
7. Randomization.com: Welcome to randomization.com. http://www.randomization.com/; letzte Version: 16. 7. 2008.
8. Zelen M. The randomization and stratification of patients to clinical trials. J Chronic Dis. 1974;27:365–375.[PubMed]
9. Altman DG. Randomisation: potential for reducing bias. BMJ. 1991;302:1481–1482.[PMC free article][PubMed]
10. Fleiss JL. The design and analysis of clinical experiments. New York, Chichester, Brisbane, Toronto, Singapore: John Wiley & Sons; 1986. pp. 120–148.
11. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. Types of epidemiologic studies: clinical trials. 3rd edition. Philadelphia: LIPPINCOTT Williams & Wilkins; 2008. pp. 89–92.
12. Eng J. Sample size estimation: how many individuals should be studied? Radiology. 2003;227:309–313.[PubMed]
13. Schäfer H, Berger J, Biebler K-E, et al. Empfehlungen für die Erstellung von Studienprotokollen (Studienplänen) für klinische Studien. Informatik, Biometrie und Epidemiologie in Medizin und Biologie. 1999;30:141–154.
14. Moher D, Schulz KF, Altman DG. The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomized trials. Ann Intern Med. 2001;134:657–662.[PubMed]
15. Machin D, Campbell MJ. Design of studies for medical research. Chichester: Wiley; 2005. pp. 1–286.
16. Beaglehole R, Bonita R, Kjellström T. Einführung in die Epidemiologie. Bern: Verlag Hans Huber; 1997. pp. 1–240.
17. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. Types of epidemiologic studies. 3rd Edition. Philadelphia: LIPPINCOTT Williams & Wilkins; 2008. pp. 87–99.
18. Fleiss JL. The design and analysis of clinical experiments. New York, Chichester, Brisbane, Toronto, Singapore: John Wiley & Sons; 1986. pp. 149–185.
19. Fleiss JL. The design and analysis of clinical experiments. New York, Chichester, Brisbane, Toronto, Singapore: John Wiley & Sons; 1986. pp. 186–219.
20. Moher D, Schulz KF, Altman DG. Das CONSORT-Statement: Überarbeitete Empfehlungen zur Qualitätsverbesserung von Reports randomisierter Studien im Parallel-Design. Dtsch Med Wochenschr. 2004;129:16–20.
21. Bossuyt PM, Reitsma JB, Bruns DE, et al. Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. Clin Chem. 2003;49:1–6.[PubMed]
22. Wald N, Cuckle H. Reporting the assessment of screening and diagnostic tests. Br J Obstet Gynaecol. 1989;96:389–396.[PubMed]
23. von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370:1453–1457.[PubMed]
24. International Committee of Medical Journals (ICMJE) Clinical trial registration: a statement from the International Committee of Medical Journal Editors. http://www.icmje.org/clin_trial.pdf; letzte Version: 22.05.2007.
25. Altman DG, Gore SM, Gardner MJ, Pocock SJ. Statistical guidelines for contributors to medical journals. Br Med J (Clin Res Ed) 1983;286:1489–1493.[PMC free article][PubMed]
e1. Neugebauer E, Rothmund M, Lorenz W. The concept, structure and practice of prospective clinical studies. Chirurg. 1989;60:203–213.[PubMed]
e2. ICH Harmonised Tripartite Guideline. The International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH).2008. [PubMed]
e3. ICH 6: Good Clinical Practice. International Conference on Harmonization; London UK. 1996. adopted by CPMP July 1996 (CPMP/ICH/135/95)
e4. ICH 9: Statisticlal Principles for Clinical Trials. International Conference on Harmonization; London UK. 1998. adopted by CPMP July 1998 (CPMP/ICH/363/96)
e5. ICH 10: Choice of control group and related issues in clinical trails. International Conference on Harmonization; London UK. 2000. adopted by CPMP July 2000 (CPMP/ICH/363/96)
e6. Blettner M, Zeeb H, Auvinen A, et al. Mortality from cancer and other causes among male airline cockpit crew in Europe. Int J Cancer. 2003;106:946–952.[PubMed]
e7. Doll R, Peto R, Boreham J, Sutherland I. Mortality in relation to smoking: 50 years’ observations on male British doctors. BMJ. 2004;328:1519–1527.[PMC free article][PubMed]
e8. Blettner M, Heuer C, Razum O. Critical reading of epidemiological papers. A guide. Eur J Public Health. 2001;11:97–101.[PubMed]
e9. Juni P, Altman DG, Egger M. Systematic reviews in health care: assessing the quality of controlled clinical trials. BMJ. 2001;323:42–46.[PMC free article][PubMed]
e10. Begg C, Cho M, Eastwood S, et al. Improving the quality of reporting of randomized controlled trials. The CONSORT statement. JAMA. 1996;276:637–639.[PubMed]
e11. Novack GD. The CONSORT statement for publication of controlled clinical trials. Ocul Surf. 2004;2:45–46.[PubMed]
e12. Bossuyt PM, Reitsma JB, Bruns DE, et al. The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration. Clin Chem. 2003;49:7–18.[PubMed]
e13. Vandenbroucke JP, von Elm E, Altman DG, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Epidemiology. 2007;18:805–835.[PubMed]
e14. DeAngelis CD, Razen JM, Frizelle FA, et al. Is this clinical trial fully registered: a statement from the International Committee of Medical Journal Editors. JAMA. 2005;293:2908–2917.[PubMed]
e15. Altman DG, Gore SM, Gardner MJ, Pocock SJ. Statistical guidelines for contributors to medical journals. Br Med J (Clin Res Ed) 1983;286:1489–1493.[PMC free article][PubMed]
The word cohort means a group of people. These types of studies look at groups of people. They can be forward-looking (prospective) or backward-looking (retrospective).
Prospective" studies are planned in advance and carried out over a future period of time.
Retrospective cohort studies look at data that already exist and try to identify risk factors for particular conditions. Interpretations are limited because the researchers cannot go back and gather missing data.
These long-term studies are sometimes called longitudinal studies.
- Cohort studies typically observe large groups of individuals, recording their exposure to certain risk factors to find clues as to the possible causes of disease.
- They can be prospective studies and gather data going forward, or retrospective cohort studies, which look at data already collected.
- The Nurses' Health Study is one example of a large cohort study, and it has produced many important links between lifestyle choices and health by following hundreds of thousands of women across North America.
- Such research can also help identify social factors that influence health.
Cohort studies look at large groups of people to try to find out what might cause a disease.
The cohort study design is the best available scientific method for measuring the effects of a suspected risk factor.
In a prospective cohort study, researchers raise a question and form a hypothesis about what might cause a disease.
Then they observe a group of people, known as the cohort, over a period of time. This may take several years. They collect data that may be relevant to the disease.
In this way, they aim to detect any changes in health linked to the possible risk factors they have identified.
For example, scientists may ask participants to record specific lifestyle details over the course of a study. Then, they can analyze any possible correlations between lifestyle factors and disease.
Comparing with other study types
Randomized controlled trials (RCT) are considered the best, most rigorous way of investigating interventional medicine, such as new drugs, but it is not possible to use them to test for the causes of disease.
Cohort studies are observational. The researchers observe what happens without intervening.
In experimental studies, such as RCTs, the scientists intervene, for example, by giving participants a new drug and assessing the outcomes.
When looking for the causes of disease, it would be unethical to deliberately expose participants to a suspected risk factor, as would be the case in an RCT. Instead a prospective cohort study is observational rather than interventional.
For drug testing, RCTs are the best option. Humans are used to test the safety and potential benefit of a treatment.
While the harms of a treatment sometimes outweigh the benefits, this form of testing is considered acceptable because the drug has already been tested many times and the researchers are quite sure that it is safe enough to try.
In addition, participants agree to join the trial, sometimes because they have a condition and there is a good chance the drug will improve their health.
Case-control studies are another type of observational study, also used to investigate the causes of disease.
Cohort studies are considered to be better than case-control studies because they are usually prospective. Case studies are limited because they are usually retrospective and involve a smaller number of people.
Some cohort studies have been very large and continued for a long time, producing a good deal of data that serves researchers in different fields.
Nurses Health Study
One famous example of a cohort study is the Nurses' Health Study, a large, long-running analysis of women's health, originally set up in 1976 to investigate the potential long term consequences of the use of oral contraceptives.
This study recruited its second generation cohort for the Nurses' Health Study II in 1989, and its third-generation cohort of nurses from across the United States and Canada in 2010.
The nurses in the first NHS were married women aged 30 to 55 years. The NHS II and III aimed to look at a more diverse cohort including women aged between 20 and 46 years.
Numerous and important insights into health and wellbeing have already been gained by researchers using data from the Nurses' Health Study, which is run by the Harvard School of Public Health, and the Brigham and Women's Hospital, both based in Boston, MA.
The following headlines are from news stories published recently by MNT. They report on some of the findings from this huge study of hundreds of thousands of women:
Because the Nurses' Health Study asks participants about their lifestyle choices, it has yielded much information about the harms and benefits of various factors, including specific types of food in the diet.
Cohort studies are also good at finding relationships between health and environmental factors such as chemicals in the air, water and food. These are issues that the World Health Organization (WHO) helps researchers to investigate with large-scale cohort studies.
Pooling data from different studies can increase the sample size, and this can make the results more reliable, especially for rare conditions such as some types of cancer.
Framingham Heart Study
Another example is the Framingham Heart Study, which recruited over 5,209 male and female participants in 1948 from around the area of Framingham, MA. It has continued to serve as a source of data for cardiovascular risk factors.
A second cohort was recruited in 1971 and a third in 2002. The study has made important contributions to the understanding of heart health. The researchers are now looking into how genetic factors may affect cardiovascular risk.
Big cohorts of babies
A birth cohort study is a long-term follow-up of people born in the same year. One has followed 17,000 people all born in the same week in 1958.
In 1958, researchers in the UK launched a large-scale cohort study that has followed 17,000 people all born in the same week in different regions of the United Kingdom.
Since then, researchers from the UK's Centre for Longitudinal Studies have launched more studies with new large groups of babies.
The latest, the Millennium Cohort Study, is following 19,000 millennium babies, children born in the UK between 2000 and 2001. In addition to data on the health of these children and their parents, the study is also looking into child behavior and cognitive development, as well as a range of social factors.
Cohort studies are graded as the most robust form of medical research after experiments such as randomized controlled trials, but they are not always the best form of observational work.
Cohort studies do have some limitations:
- They are less suited to finding clues about rare diseases. A case-control study identifies cases of disease first and then analyzes exposure to risk factors, whereas cohort studies follow exposure data and watch for any emerging cases of disease.
- They are typically unsuitable for identifying the causes of a sudden outbreak of disease. A case-control study can give quicker results.
- They are expensive to run and usually take many years, often decades, to produce results.
- They can only offer clues about the causes of disease, rather than definitive proof of links between risk factors and health. This is true of any observational medical research.
- Participants may leave the cohort, perhaps move away, lose touch, or die from a cause that is not being studied. This can bias the results.