Cohorts for studying cancer: a brief panorama Cyrille Delpierre, INSERM UMR 1027, Université...

Cohorts for studying cancer:a brief panorama

Cyrille Delpierre,

INSERM UMR 1027, Université Toulouse III

Cyrille Delpierre, Markov model workshop, Toulouse October 18-19

http://www.inserm.fr/

A little background

• Term used for the first time in 1930 by Frost and Andvord to describe death associated with tuberculosis

• Majority of “big” cohorts implemented after second world war

• Simultaneously in United Kingdom and USA

• Need to collect data prospectively because of the limitations of case control studies

• Focused on specific disease or exposure to – Compare occurrence of an event in several groups initially

free of the studied event and defined according to their exposure to one or several risk factors suspected in the occurrence of this event


First cohorts

• 1946 Birth cohort (Great Britain)– 5 362 participants– From birth till present– Objective: first to understand the decrease of fertility in Great Britain by studying

availability, usefulness and efficacy of maternities. Then to study the impact of social conditions on child development

• Framingham (1948, USA): – 5 209 participants, between 30 and 62 years old– Ran from 1949 to now: “third generation”– To identify the common factors or characteristics that contribute to CVD by

following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke

• First cohort in France– Etude prospective parisienne (1967): 7 434 men working in public sector, 43-53

years old, ran from 1967 to 1977 to determine incidence and prevalence of ischemic cardiopathies, and identify risk factors


First “big” cohorts studying cancer

• British doctor’s study (1951, GB)– 40 634 participants born between before 1900, in 1900-1909, in 1910-19, and in

1920-30– Ran from 1951 to 2001 – To study the link between tobacco and cancer– First results in 1954 showing that tobacco was a risk factor of lung cancer

• The American Cancer Society (ACS) Cancer Prevention Studies– The Hammond-Horn Study (1952):188 000 men aged from 50 to 69 years, ran

from 1952 to 1955 to to examine the association between cigarette smoking and death rates from cancer and other diseases

– Cancer prevention study I (1959): 1 078 894 men and women; ran from 1959 tot September 1972 to study mortality and diseases caused by tobacco use

• These cohorts played a critical role in establishing the causal link between smoking and several diseases


Definition of cohort

• From the Research Institute in Public Health (IRESP)– A cohort is a group of individuals sharing a number of

characteristics and who are followed longitudinally– Based on the collection of information on the characteristics

and exposures of subjects, prior to the time of occurrence of the health event of interest.

– Based on compliance with a pre-established protocol, for monitoring people and collecting information.

– Information gathering can be done through questionnaires, clinical examinations and biological samples, or by obtaining data collected from other sources.


prospective cohort

cohortExposed

Not exposed

Sick

SickNot sick

Not sick

measure of exposure

Occurrence of disease

exposed – unexposed studyMeasure of exposureretro / prospective


7

• Prospective cohort and historical cohort– Define from start of the study

– If exposure already occurred at the beginning of the study (retrospective measure), and endpoint measured during the study (prospective measurement) then mixed cohort

2004

1980 1990 2005 2010 …

Historical cohort Prospective cohort


8

• Specialised cohort – On a specific disease (cancer)– On specific characteristics– Number of subjects relatively small– Data frequently well documented and various (biological and

clinical data)

• General cohort – In general population– Large number of subject– Large coverage regarding health problems and exosures

allowing studying various research questions– Less detailed data– Often mixed cohort


Modern cohorts

• Huge development from the 70s and not possible to list all the cohorts– For example in 2004, at least 47 cohorts contributed to prove the

role of tobacco on various cancers

• To manage the multiple exposures involved in many chronic diseases: – Environment, psychosocial conditions, occupation, nutrition,

biology

• New statistical methods allowing to deal with longitudinal data

• Opportunities to study various health outcomes– By linking these cohorts with other databases like mortality

registries or cancer registries– By collected numerous data mainly through questionnaires by

period of time, plus clinical examination or even biological samples


Some modern cohorts in the world (1)

• Whitehall cohorts (GB)– Whitehall 1 (1967): 19 018 participants of the British Civil Service, 20-64 years,

ran from 1967 to study cardiovascular risk factors – Whitehall 2 (1985): 3 413 women and 6 895 men, 35-55 years to analyse

determinants of health inequalities

• Nurses’ Health Studies (USA)– Nurses’ health study I (1976): 121 700 women, 30-55 years old, ran from 1976

to initially study long term effect of oral contraceptive pill on health then used to assess risk factors for cancer and cardiovascular disease

– Nurses’ Health Study II (1989, USA): 116 000 women, 25-42 years old, to study diet and lifestyle risk factors in women who were younger than the NHS1 participants

– Nurses’ Health Study III: ongoing (100 000 women)

• Physicians’ Health studies (USA)– Physicians’ Health study I (1982): randomized clinical trial included 33 223 male

physicians, 40-84 years old, ran from 1982 to 1995, to study the role of aspirin and B carotene on cardiovascular diseases and cancer

– Physicians’ Health study II (1997): randomized clinical trial included 14 642 male physicians, older than 50 years, ran from 1997 to now, to study the role of some vitamins (C, E) on cardiovascular diseases and cancer


Some modern cohorts in the world (2)

• The Cancer Prevention Studies (USA)– CPS II (1982): 1 200 000 men and women, ran from 1982 to examine

the impact of environmental and lifestyle factors on cancer deaths

– CPS II Nutrition Cohort (1992): subgroup of 84 000 men and 97 000 women from 1992 to investigate the relation between diet and other lifestyle factors and exposures and the risk of cancer, mortality, and survival

– CPS II Biospecimen Repository (1998): initiated to obtain blood samples for epidemiologic investigations, including the role of nutritional, hormonal, and genetic factors regarding cancer and other diseases; blood sample from 39 380 cohort members of the CPS-II Nutrition Cohort; approximately 67 000 cohort members from those participants who were unable or unwilling to give a blood sample gave buccal cell samples by mail

– CPS III (2006): currently being established from 2006, 500 000 participants to explore the effects of changing exposures and to provide greater opportunity to integrate biological measurements into studies of genetic and environmental risk factors


Some modern cohorts in France

• Etude Epidémiologique auprès de femmes de la MGEN (E3N, 1990): – 100 000 voluntary French women born between 1925 and 1950, ran

from 1990 to analyze the role of certain factors, including hormonal, dietary and genetic, in the occurrence of cancers, especially breast and colon cancers

• SUVIMAX (1994): – Randomized control trial on 13 017 voluntary men and women followed

8 years to test the impact of micronutrient antioxidants (vitamin C, E, beta-carotene, selenium and zinc) at nutritional doses on the incidence of cancer, ischemic heart disease and mortality

• Gazel cohort (1989): – 20 600 voluntary men and women (EDF-GDF), followed since 1989 and

designed to potentially analyze a wide range of scientific problems, and be accessible to the community of researchers

• Agrican (2005): – 180 000 individuals from the Mutuelle Sociale Agricole to study the link

between cancers and agricultural activities


Present day cohorts

• To have sufficient power to detect small effects of numerous exposures, and to define in more detail effects of exposures on biology and genetics:– Development of mega cohorts (more than 100 mega cohorts

around the world) mainly focused on chronic diseases, collecting data through questionnaires, medical examination, blood sample, linked with other databases, implementing biobanks and an open access to researchers


Mega cohorts (1)

• The cohort of Norway (CONOR cohort, 1994): 200 000 participants to study aetiological factors for a wide range of diseases

• The Norwegian Mother and Child Cohort Study (MoBA cohort, 1999): 100000 women, 100 000 childs, 70000 fathers to study the role of environmental and other exposures on the health of women and their children

• One million women study (1996, GB): 1 million of women older than 50 years to investigate how various reproductive and lifestyle factors affect women’s health. In particular, the study is looking at how hormone replacement therapy affects a woman’s breasts and other aspects of her health

• UK biobank (2006): 500 000 participants aged 40-69 years the aim of improving the prevention, diagnosis and treatment of a wide range of serious and life-threatening illnesses – including cancer, heart diseases, stroke, diabetes, arthritis, osteoporosis, eye disorders, depression and forms of dementia


Mega cohorts (2)

• Understanding society (2009): world leading study of the socio-economic circumstances and attitudes of 100,000 individuals in 40,000 British households (100,000 individuals)

• LifeGene (Sweden, 2010): 500 000 participants, 0-45 years old

• LifeLines (Netherlands, 2006): 1 650 000 participants, 25-50 years old

• In France– Nutrinet (2009): 500 000 participants recruited via the internet

(233369 in August 2012), followed at least five years to evaluate and assess the relationship between nutrition and health and to understand the determinants of eating behaviour

– Constances (France, 2012): 200 000 participants, 18-69 years old, linked with large administrative health databases


Present day cohorts

• To have sufficient power to detect small effects of numerous exposures, and to define in more detail effects of exposures on biology and genetics:– Development of a mega cohort (more than 100 mega cohorts

around the world) mainly focused on chronic diseases, collecting data through questionnaires, medical examination, blood sample, linked with other databases, implementing biobanks and an open access to researchers

• Creation of a consortium of big or mega cohorts– European Prospective Investigation into Cancer and Nutrition

(EPIC, 1993-1999): 520 000 participants older than 20 years in 10 countries (Denmark, France, Germany, Greece, Italy, Netherlands, Norway, Spain, Sweden, United Kingdom)



Robert N. Hoover, MD, ScD, Director Epidemiology and Biostatistics Program Division of Cancer Epidemiology and Genetics, National Cancer Institute

Present day cohorts

• To have sufficient power to detect small effects of numerous exposures, and to define in more detail effects of exposures on biology and genetics:

– Development of a mega cohort (more than 100 mega cohorts around the world) mainly focused on chronic diseases, collecting data through questionnaires, medical examination, blood sample, linked with other databases, implementing biobanks and an open access to researchers

• Creation of a consortium of big or mega cohorts– European Prospective Investigation into Cancer and Nutrition (EPIC, 1993-

1999): 520 000 participants older than 20 years in 10 countries (Denmark, France, Germany, Greece, Italy, Netherlands, Norway, Spain, Sweden, United Kingdom)

• In France, cohorts recognized as “Très grandes infractructures de recherche” with a national coordination of French cohorts, founded as “investissments d’avenir” (le Grand Emprunt)

– Inventory of French cohorts: more than 200 cohorts, 6 focused on cancer and 19 in general population

– Pooling of skills and resources – Development of European consortia


Implications of life course processes in epidemiology and public health

• The understanding of mechanisms involved over the life course – Allows a better understanding of how the psychosocial

becomes biological – Give some targets for intervention aiming at reducing social

inequalities in health

• Many interests of life course approach but also important practical issues– Regarding data and study requirements with this approach– The need to think and model the mechanisms by which

various factors influence health in a more relevant way


Cohorts used for life course studies:the Holy Grail

• Prospective design

• Multiple measures– Socioeconomic factors: housing, social class, education, income,

occupational exposures– Psychosocial factors– Health behaviours– Health measures: subjective measures and objective measures

(clinical examination)– Access to care

• Biological samples

• Repeated collection of data over time

• Long follow-up, from the birth to adulthood

Birth cohort studies+++


Birth Cohort Studies: some examples (1)

• In Great Britain:– 1946 National Survey of Health and Development (NHSD): N=5 362– 1958 National Child Development Study (NCDS): N=17 773– 1970 British Cohort Study (BCS): N=16 135– 1991-1992 The Avon Longitudinal Study of Parents and Children (ALSPAC):

N=14 541– 2000-2001 Millennium Study: N=18 819

• In United States– The Child health and development Study (1959-1966): N=around 20000– The Early Childhood Longitudinal Study (ECLS-B), 2001: N=14 000

• In New Zealand– The Dunedin Cohort (1972-73): N=1 037

• In Australia– The longitudinal Mater University Study of Pregnancy (MUSP), 1981-1984:

N=around 8 000


Birth Cohort Studies: some examples (2)

• In Scandinavia– The Norwegian Mother and Child Cohort Study (MoBa),

1999: N=100 000 – The Danish Cohort Study (1996): N=around 60 000– The Stockholm Birth Cohort (1953): N=14 292

• Also in “emerging countries”– In Brazil: The 1982 Pelotas birth cohort study: N=5 914

• In France – EDEN cohort (2003): N=1 900 – ELFE (2011): N=18 000


Some issues with birth cohort studies

• Different follow-up– Relevancy for some chronic diseases?

• Various number of participants– Power?

• Data collection at different times in life course– Impact for studying sensitive period?

• Included variables changed according objectives• Biological samples are not always available, standardized (urine,

blood, serum) and collected repeatedly• Ask questions about generalizations

– Over time : relevancy to use results from 1958 NCDS cohort showing link between adversity and cancer for now? Definition of adversity still relevant?

– Across countries: relevancy to use results observed in UK to characterize the French situation

• Expensive and long time before results– Request to think to alternative method


Alternatives to birth cohort studies (1)

• Using existing cohorts or databases– Less expensive– Less time to have results– Solution to increase power of study– Solution to manage follow-up– Solution to have create database including biological sample

• The main point is then to “rebuild” life course – Data from archives

• Dependant on the quality and the availability of variables collected in archives

– Retrospectives Studies• Recall bias• key question: which variables are relevant to characterize life course in a

retrospective approach?– Databases linkage (Scandinavia+++, Constances cohort)

• Interesting if various databases available: biological, clinical, social, administrative

• Need a easy, feasible linkage• Questions of confidentiality


But important issues with cohorts

• Methodological issues– Mediation

• Difficulty to measure direct and indirect effect– Need to know variables of confusion at least the important ones– Need to collect them, repeatedly

• Difficulty to analyse mediation– What methods? In longitudinal situation?

– How to disentangle mechanisms involved over time

• Practical issues– Follow-up

• Attrition bias: how to manage missing values, particularly when missing at random assumption wrong

– Boot strap methodology– Hidden Markov model

– Quality of the measures: declarative vs objective • Recall bias, measurement errors

– Non random exposures (indication bias)

• Risk of bias by using cohorts that can lead to false conclusions


Conclusion

• Cohorts play an increasing role in epidemiology and represent an investment for society

• Lead to important findings by giving opportunities to – Test the effect of multiples exposures in various diseases– To consider the life course in analyses and thus increase our

understanding on mechanisms and chains of causality

• But cohorts present important limitations that can have a huge impact on conclusions in particular– Attrition bias, missing data and measurements errors

• Need – People and money – Standardised processes in particular to follow people – Strong development regarding biostatistical methodology to control

limitations of cohorts


Bibliographie française

• Actualité et dossier en santé publique (adsp), revue trimestrielle du Haut Conseil de la santé publique – Numéro spécial

Apport des cohortes à la connaissance de la santé (mars 2012)

• Base « épigramme » (IReSP) (http://www.iresp.net/index.php?goto=actions&rub=el)– Objectif: rassembler pour la première fois des données issues

de différentes institutions afin d’avoir un panorama complet des études de cohortes portant sur la santé.

– Liste des cohortes françaises avec informations sur les responsables scientifiques, la méthodologie, les effectifs, les principales données collectées…


http://www.hcsp.fr/explore.cgi/adsp?ae=adsp&clef=118&menu=11

http://www.iresp.net/index.php?goto=actions&rub=el

Cohorts for studying cancer: a brief panorama Cyrille Delpierre, INSERM UMR 1027, Université...

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