Measures of familial aggregation depend on definition of family history: meta-analysis for colorectal cancer

Journal of Clinical Epidemiology 59 (2006) 114–124

Measures of familial aggregation depend on definition of familyhistory: meta-analysis for colorectal cancer

Laura Bagliettoa,b,*, Mark A. Jenkinsb, Gianluca Severia,b, Graham G. Gilesa,b,D. Timothy Bishopc, Peter Boyled, John L. Hopperb

aCancer Epidemiology Centre, The Cancer Council of Victoria, 100 Rathdowne Street, Carlton, Melbourne, Victoria 3053, AustraliabCentre for Molecular, Environmental, Genetic and Analytic Epidemiology, The University of Melbourne, Melbourne, Victoria, AustraliacGenetic Epidemiology Division, Cancer Research UK Clinical Centre in Leeds, St. James’s University Hospital, Leeds, United Kingdom

dInternational Agency for Research on Cancer, Lyon, France

Accepted 14 July 2005

Abstract

Objective: Familial aggregation, a primary theme in genetic epidemiology, can be estimated from family studies based on an indexperson. The excess risk due to the presence of affected family members can be classified according to whether disease in the relativesis considered a risk factor for the index person (type I relative risk) or whether the disease status of the index person is considered a riskfactor for the relatives (type II relative risk).

Study Design and Setting: A meta-analysis of published colorectal cancer studies reporting a measure of familial association wasperformed and application of multilevel linear regression to model age-specific relative risks presented.

Results: The pooled type I relative risk of colorectal cancer given any affected first-degree relative (based on 20 studies) was 2.26 (95%confidence interval CI5 1.86, 2.73) and decreased with the age of the consultand. The pooled type II estimate (based on seven studies) was2.81 (95% CI 5 2.05, 3.85).

Conclusion: Type I relative risks are useful in clinical counseling settings when a consultand wants to know his/her disease risk givenhis or her family history. Type II relative risks can be used to quantify the risk of disease to relatives of an affected individual and thenidentify subjects eligible for screening. � 2006 Elsevier Inc. All rights reserved.

Keywords: Family history; Risk; Meta-analysis; Colorectal neoplasms

1. Introduction

Familial aggregation of a disease exists when the diseaseoccurs at a higher frequency in the relatives of an affectedperson than in the general population [1]. Familial aggrega-tion is a primary theme of genetic epidemiology, a disci-pline that uses family-based designs to assess the roles ofgenes and environment in the etiology of disease in thepopulation. Determining how risk of disease is dependenton family history is necessary to develop referral guidelinesto services, such as screening and genetic counseling. Forcomplex disorders, such as the common cancers, studiesof familial aggregation may contribute to disease taxonomyin that they help identifying characteristics that distinguishhereditary from nonfamilial forms and thereby recognizingcausal factors.

* Corresponding author. Tel.:161-3-9635-5644; fax:161-3-9635-5330.

E-mail address: [email protected] (L. Baglietto).

0895-4356/06/$ – see front matter � 2006 Elsevier Inc. All rights reserved.

doi: 10.1016/j.jclinepi.2005.07.018

1.1. Family data: sampling scheme and analysis

The sampling scheme for family studies typically con-sists of starting with an individual (called the index personor proband) and collecting information about his or her rel-atives. Note that the index person need not be affected. Forexample, the case–control–family design [2] consists ofsampling cases and controls on a population basis as the in-dex persons, and then sampling their relatives. Reports ofcancers, both for the index persons and their relatives, areideally confirmed by reviewing pathology reports, medicalrecords, and death certificates. Cancer registries can beused to identify affected index persons (case probands)and to verify any reports of cancer in the relatives.

As clarified by Susser and Susser in their seminal articlepublished in 1989 in the American Journal of Epidemiology[1], two different estimates of excess risk are possible whendealing with family data, through (i) treating the presence ofdisease in relatives as a risk factor and evaluating whetherit confers an excess risk by comparing its prevalence in

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115L. Baglietto et al. / Journal of Clinical Epidemiology 59 (2006) 114–124

affected versus unaffected index persons (here termed typeI relative risk) and (ii) evaluating whether the relatives of anaffected index person have an excess risk of disease in com-parison to an appropriately defined population (here termedtype II relative risk) (Table 1). Type I and type II relativerisks are both expressions of the probability that an individ-ual (termed the consultand in genetic counseling terminol-ogy) will develop the disease, given the distribution ofdisease or diseases among his or her relatives. Estimationcan be made according to the disease in question, the char-acteristic of the consultand (e.g., age; sex) and his or herfamily characteristics (e.g., definition of the disease con-sidered to be risk factors, subsets of relatives whose diseasesare evaluated, the age and sex distribution of the relatives,and the age at onset of disease in relatives). Notably, theonly situation in which the type I and the type II estimateswould be equivalent is when the consultand has only onerelative for consideration; for example, (i) risk of prostatecancer in a man with just one brother given his diseasestatus (type I) and risk to the only brother of an affectedman (type II); (ii) risk of breast cancer in a woman giventhat her mother got breast cancer (type I) and risk to thedaughters of an affected woman (type II). In practice, thedistinction between type I and type II estimates has beenignored [3–6] and often misunderstood [7,8]

Traditional epidemiological study designs provide auseful framework for evaluating familial aggregation ofdisease, provided that some concepts are modified or ex-tended for the collection and analysis of family data. Inclassical epidemiology, in which unrelated individuals arestudied, the most commonly used methods to address as-sociations between diseases and exposures are the case–control design and the cohort design. In family studies, inwhich the association between a disease and its distributionin pedigrees is studied, the distinction between case–controland cohort designs is not clear, mainly because family his-tory is not an attribute of any single individual, and also be-cause the causal criterion of temporal sequence betweenexposure and disease does not hold [1]. A direct measureof the relative risk may be obtained by analyzing the datafrom a cohort study perspective, in which the cohort is

composed of initially unaffected individuals, classified asexposed or not exposed according to the disease status oftheir relatives, followed up prospectively over time. Theratio of the incidence of disease in exposed subjects to thatin the unexposed is an estimate of type I relative risk. Thetype II relative risk is estimated by following up (usuallyretrospectively) the cohort of relatives for whom the expo-sure status is defined by the disease status of the index per-son. This study design is sometimes termed the kin–cohortdesign. In studies that recruit solely families of affectedindividuals (i.e., the index person is a case proband), theincidence of disease in the cohort of the probands’ relativesis compared with the incidence in the general population(external comparison). In this situation, the relative riskcan be measured in the form of a standardized incidenceratio. Conversely, when relatives of both affected andunaffected index persons (i.e., case probands and controlprobands) are studied, the incidence of disease in relativesof the case proband can be compared with the incidence inthose of the control proband (an internal comparison). Thesame data can also be analyzed from a case–control per-spective, in which the relative risk is estimated as an oddsratio of the exposure between affected and unaffected sub-jects, with the exposure being the presence of disease inrelatives, as well as an odds ratio of exposure betweenaffected and unaffected relatives of case probands and con-trol probands (i.e., by a case–control study nested in thecohort of relatives). Under the rare disease assumption,the corresponding odds ratios are a close approximationof type I and type II relative risks.

The type I relative risk is a measure of the excess risk ofdisease for an individual, given the distribution of diseaseamong his or her relatives (family history). The type IIrelative risk is a measure of the excess risk of disease foran individual given the disease status of a selected memberof his or her family. In estimating the type I relative risk,the sampling of subjects is independent of their exposurestatus (which is the disease status of the relatives). In esti-mating the type II relative risk, the sampling procedure isnot independent of the exposure (which in this case is thedisease status of the index person). A potential problem

Table 1

Dataa, design, analysis, and interpretation of family data

Design Classic case-control Classic cohort Kin-cohort Nested case-control

Outcomes Disease in the index person Time to disease in the

index person

Time to disease in relatives Disease in relatives

Exposure Disease distribution in relatives Disease distribution in relatives Disease status of the

index person

Disease status of the index

person

Analysis Logistic regression of independent

outcomes

Survival analysis of independent

outcomes

Survival analysis of clustered

outcomes

Logistic regression of

clustered outcomes

Parameters being

estimated

Type I relative riskb Type I relative riskb Type II relative riskc Type II relative riskc

a Set of independent families (index person and his or her relatives).b Type I relative risk is risk of disease in a consultand (index person) given a specific family history of disease.c Type II relative risk is risk of disease in a consultand (relative) given a specific individual (index person) is affected.

116 L. Baglietto et al. / Journal of Clinical Epidemiology 59 (2006) 114–124

related to the type II approach is that the cohort is of rela-tives, and therefore is not of independent individuals when-ever it is composed of more than one member of the samefamily (e.g., cohort of siblings). As a consequence, anystandard error estimate based on the assumption of inde-pendence within exposure sets will be an underestimate,by an amount dependent on the strength of the familial ag-gregation and the size and structure of the families withinthe cohort, and the analysis should be modified accordinglyto take the clustering into account.

1.2. Familial aggregation of colorectal cancer

Colorectal cancer (CRC) is one of the most commonlydiagnosed cancers and one of the most important causesof cancer mortality [9–11]. Given that |1 in 20 men andwomen are diagnosed with CRC in their lifetime, a familyhistory of CRC is also common.

The estimated proportion of CRC that is caused bya dominantly inherited gene ranges from 5% to 13%[12,13]. Known CRC susceptibility genes include theAPC gene associated with familial adenomatous polyposis(FAP) and attenuated familial adenomatous polyposis(AFAP) [14–17] and the mismatch repair genes, in particu-lar MSH2 and MLH1 (formerly hMSH2 and hMLH1), thatare implicated in a large proportion of the hereditary non-polyposis colorectal cancer (HNPCC) syndrome [18–21].

The mechanisms leading to CRC are complex and likelyinvolve not only the currently known major genes, butmany other genetic and environmental risk factors sharedby family members. Evidence for this comes from studiesthat have shown substantial residual unexplained familialaggregation after excluding families suspected of carryingmutations in mismatch repair genes and in the APC gene[22–31]. A population-based study conducted on familiesascertained via an early-onset case of CRC showed that, af-ter removing families found to be carrying mutations inMSH2 andMLH1 genes, first-degree relatives of CRC caseswere still at increased risk of the disease [32].

The first report of familial aggregation of CRC in thegeneral population was made in 1960, when Macklin [33]published the results of a study of 145 patients withCRC, with a greater than expected number of deaths attrib-utable to CRC in first- and second-degree relatives. Manystudies of the association between CRC and family historyhave been published since then; a review and meta-analysisof the literature from 1966 to 1999 appeared in 2001 [34].

Here, we review the publications reporting a measure offamilial aggregation of CRC, classify the estimates basedon the study design and analytical approach, and estimatethe overall type I and type II increased risk by combiningthe findings of all studies. A method based on multilevellinear regression is also applied to model relative risks asa function of ages.

2. Methods

2.1. Search methods

Studies reporting a measure of familial aggregation ofCRC based on incidence data were identified througha Medline search employing the following algorithm:(‘‘colorectal neoplasm’’ or ‘‘colon neoplasm’’ or ‘‘rectalneoplasm’’) and (‘‘case–control’’ or ‘‘cohort’’) and ‘‘famil*’’,where the wildcard asterisk means that any word startingwith ‘‘famil’’ is selected. Additional articles were ascer-tained by searching the references cited in publications.Studies were limited to those published in English from1966 to 2003 inclusive. Only studies estimating familialrisk from incidence data were included; those based onmortality data alone were excluded. To limit the effectsof recall bias, data on family history were restricted tofirst-degree relatives only [35,36]. Because family historyis typically ascertained from the index person alone, itwas often not possible to distinguish from the publicationbetween reports of colon cancer and rectal cancer in rela-tives; for this reason, only those studies that were notrestricted to colorectal subsites in relatives were included.

2.2. Design of the meta-analysis

The estimates of familial aggregation are presented asrelative risks (RR). According to the analytical approachadopted, each estimate was classified as type I or type IIas described above. Where available, age- and sex-adjustedestimates or estimates adjusted for other potential con-founders were preferred; otherwise, crude estimates wereused. In all studies where both were presented, estimateswere similar. If the relative risk estimates and their 95%confidence intervals (CI) were not provided, they were cal-culated from the published data, whenever possible, as fol-lows: the crude odds ratio and its 95% CI were calculatedfrom the frequencies of the exposed and unexposed amongcases and controls [37], or the relative risk was computed asthe ratio between the observed and expected cases and its95% CI was calculated using the Byar approximation [38].

The overall estimates of the type I and the type II rela-tive risks with their 95% CI were calculated using a ran-dom-effect model for combining relative risks [39,40].This random-effect model combines the logarithms of theRRs using weights that include the common sampling var-iance, as well as a term accounting for interstudy heteroge-neity. The combined relative risk estimates were obtainedby pooling together relative risks and odds ratios, underthe assumption that CRC can be considered a rare diseasefor which the odds ratio provides a good approximationof the relative risk.

A typical characteristic of diseases with a familial com-ponent that has at least in part been shown to be due to in-herited genetic factors is that the relative risk associatedwith having a family history is higher at younger ages[3,6,34]. Many studies provide estimates of age-specific


relative risks associated with the presence of disease in rel-atives, but the age ranges to which they refer differ. A typ-ical approach to this problem is to combine those estimatescorresponding to the maximum overlap between their ageranges [3,6,34]. To optimize the contribution of informationfrom multiple studies, we used a method based on multilev-el linear regression. The method applied in combining esti-mates of age-specific relative risks consisted of fitting thelogarithms of the age-specific relative risks with a mixedlinear model with the intercept fitted at a random level[41]. To account for the size of each study, the contributionof each measure was weighted by the inverse of its sam-pling variance.

3. Results

Thirty-three articles reporting a measure of familial ag-gregation of CRC were identified [22–24,26–31,42–65].The main characteristics of the studies are presented inTable 2. Publication dates ranged over three decades: 6articles were published in the 1980s, with the earliestpublished in 1982 [22,28,47,48,56,60]; 21 articles werepublished in the 1990s [23,24,26,27,29–31,44,45,49–52,54,55,57–59,62,64,65]; the remainder were publishedbetween 2000 and 2003 [42,43,46,53,61,63]. Thirteen stud-ies were conducted in Europe [22,23,31,42,44,45,47,49,52,54,56–58], 12 in the United States [24,26,29,46,50,53,55,59,60,62–64], 2 in Canada [43,51], 3 in Australia [28,30,48], 2 in Japan [27,65], and 1 in China [61]. Twenty-sixstudies adopted the type I approach to present their find-ings; 2 of the studies followed up the cohort of probandscomparing the incidence of CRC in those with a familyhistory of CRC with the incidence in those with no familyhistory of CRC [50,64]; the other 24 studies analyzed thedata from a case–control perspective [22–24,27–29,31,43,45–49,51,53,54,56,58–63,65]. Five studies adopted the typeII approach to present their findings; two analyzed the datafrom a case–control perspective [55,57] and three from acohort perspective, comparing the incidence of CRC inthe cohort of relatives of cases with the incidence in thepopulation from which the cases were derived [42,44,52].Two studies presented both type I and type II estimates,analyzing the data from the case–control perspective [30]and from a case–control and kin–cohort perspective [26].Modica et al. [57] reported the results of two independentstudies, one of which had been previously described byPonz de Leon et al. [56]. (Note that, although Modicaet al. and Ponz de Leon et al. analyzed the same set of data,we included both studies in this meta-analysis because theyadopted two different approaches.) In nine studies, theauthors attempted to verify the diagnoses of cancer in rela-tives through medical records [30,31,42,44,47,48,57,60,62].

The type I relative risks of CRC associated with differ-ent family histories reported by the studies included inTable 2 are summarized in Table 3, along with the

corresponding pooled estimates. The pooled measure ofthe relative risk of CRC associated with having at leastone first-degree relative affected was 2.26 (95% CI 5

1.86, 2.73). The variation among studies of the relative riskof CRC associated with having at least one CRC affectedfirst-degree relative is shown in Fig. 1a.

The estimated relative risk increased with the number ofaffected relatives from 2.03 (95% CI 5 1.66, 2.49) for hav-ing just one relative affected to 3.95 (95% CI 5 2.49, 6.26)for having two or more relatives affected (P 5 .005). Therewas a suggestion that the risk for having at least one siblingaffected (RR5 2.52; 95% CI5 2.01, 3.15) was higher thanthe risk for having at least one parent affected (RR 5 2.15;95% CI 5 1.74, 2.65), although the difference was notnominally statistically significant (P 5 .16). No differencein the excess risk was observed between males and females(P 5 .4).

Of the articles reporting familial aggregation of CRC,four provided age-specific relative risk estimates[28,50,54,58]. The relative risk of CRC associated withhaving at least one affected first-degree relative was esti-mated to decrease exponentially with the age of the indexperson (Fig. 2) but was still significantly higher than unityat 70 years of age. The mean relative risks of CRC at theages of 40, 50, 60, and 70 predicted by the model were3.73 (95% CI 5 2.71, 5.14), 2.81 (95% CI 5 2.16, 3.66),2.11 (95% CI 5 1.64, 2.71), and 1.59 (95% CI 5 1.20,2.10), respectively.

For the risk associated with having at least one first-degree relative affected, the pooled estimate for colon can-cer (RR 5 2.20; 95% CI 5 1.94, 2.50; Fig. 1b) was higherthan the pooled estimate for rectal cancer (RR 5 1.79; 95%CI 5 1.41, 2.26; Fig. 1c) (P 5 .06).

Table 4 summarizes the estimates of the type II relativerisks. Three of these seven studies adjusted for the correla-tion among family members [30,55,57]. The pooled relativerisk of CRC to any first-degree relative of an affected pro-band was about three times the risk to first-degree relativesof an unaffected proband (RR5 2.81; 95% CI5 2.05, 3.85).The corresponding relative risk to siblings (RR5 3.47; 95%CI 5 2.24, 5.40) was significantly higher than the risk toparents (RR 5 1.85; 95% CI 5 1.63, 2.09; P 5 .003).

4. Discussion

We have focused on the interpretation of estimates of fa-milial aggregation of disease provided by epidemiologicalstudies. Because of the growing interest in identifying sub-jects at genetic risk of developing cancer, those measureswith a clear clinical meaning have a greater importancefor counseling purposes. Type I estimates refer to situationswhere an individual (consultand) presents at a geneticcounseling clinic and wants to know his or her risk of de-veloping a disease given his or her family history. Type IIestimates refer to situations where a relative of an affected


Table 2

Characteristics of the studies on familial aggregation of colorectal cancer

Study Place (perioda of study) Groups under comparison Estimates

Bonelli et al., 1988 [22] Italy (1980–1986) 414 CA vs. 855 CO ORI

Boutron et al., 1988 [23] France (1985–1990) 171 CA vs. 309 CO ORI

Freedman et al., 1996 [24] USA (1982–1993) 163 CA vs. 326 CO ORI

Kerber et al., 1998 [26] USA (1991–1994) 1,993 CA vs. 2,410 CO ORI

FDR of 1,993 CA vs. FDR of 2,410 CO RRII

Kotake et al., 1995 [27] Japan (1992–1994) 363 CA vs. 363 CO ORI

Kune et al., 1989 [28] Australia (1980–1981) 702 CA vs. 710 CO ORI

Longnecker, 1990 [29] USA (1986–1988) 644 CA vs. 992 CO ORI

St John et al., 1993 [30] Australia (1952–1985) 523 CA vs. 523 CO ORI

FDR of 523 CA vs. FDR of 523 CO ORII

Stephenson et al., 1991 [31] United Kingdom 100 CA vs. 100 CO ORI

Andrieu et al., 2003 [42] France (1993–1998) FDR of 761 CA vs. French population RRII

Brauer et al., 2002 [43] Canada (1993–1996) 157 CA vs. 282 CO ORI

Carstensen et al., 1996 [44] Denmark (1982–1984) FDRs of 1,513 CA vs. Danish population RRII

Centonze et al., 1993 [45] Italy (1987–1989) 119 CA vs. 119 CO ORI

Coogan et al., 2000 [46] USA (1992–1994) 1,201 CA vs. 1,201 CO ORI

Duncan and Kyle, 1982 [47] Scotland 50 CA vs. 50 CO ORI

Fisher and Armstrong, 1989 [48] Australia (1979–1984) 128 CA vs. 128 CO ORI

Fredrikson et al., 1996 [49] Sweden (1972–1986) 70 CA vs. 801 CO ORI

Fuchs et al., 1994 [50] USA (males: 1986–1992;

females: 1982–1990)

11,734 probands with FDR affected vs. 107,382

probands with FDR unaffected

RRI

Ghadirian et al., 1998 [51] Canada (1989–1993) 402 CA vs. 668 CO ORI

Karner-Hanusch et al., 1997 [52] Austria FDR of 100 CA vs. Austrian population RRII

Keku et al., 2003 [53] USA (1996–2000) 676 CA vs. 1,049 CO ORI

La Vecchia et al., 1992 [54] Italy (1985–1991) 1,222 CA vs. 1,766 CO ORI

Le Marchand et al., 1996 [55] USA (1987–1991) FDR of 1,192 CA vs. FDR of 1,192 CO ORII

Ponz de Leon et al., 1989 [56]b;

Modica et al. 1995 [57]bItaly, Modena (1984–1986) 389 CA vs. 389 CO ORI

FDR of 389 CA vs. FDR of 389 CO ORII

Modica et al., 1995 [57] Italy, Ragusa (1988–1990) FDR of 213 CA vs. FDR of 213 CO ORII

Negri et al., 1998 [58] Italy (1992–1996) 1,953 CA vs. 4,154 CO ORI

Newcomb et al., 1999 [59] USA (1990–1991) 702 CA vs. 2,274CO ORI

Pickle et al., 1984 [60] USA (1970–1977) 86 CA vs. 176 CO ORI

Seow et al., 2002 [61] China (1999–2000) 121 CA vs. 222 CO ORI

Slattery and Kerber, 1994 [62] USA (1966–1989) 2,473 CA vs. 7,419 CO ORI

Slattery et al., 2003 [63] USA (1997–2001) 952 CA vs. 1,205 CO ORI

Will et al., 1998 [64] USA (1959–1972) 30,195 probands with FDR affected vs. 833,504

probands with FDR unaffected

RRI

Yoo et al., 1999 [65] Japan (1988–1995) 372 CA vs. 31,061 CO ORI

Abbreviations: CA, case; CO, control; FDR, first-degree relatives; ORI, type I odds ratio; ORII, type II odds ratio; RRI, type I relative risk; RRII, type II

relative risk.a For studies sampling affected and unaffected probands it is the period of diagnosis of cases; for studies sampling healthy probands it is the period of

recruitment.b Ref. [56] reports details of the data subsequently analyzed in ref. [57] that allow calculating ORI.

individual asks for his or her risk of disease, independentlyof the disease status of the other family members. The for-mer scenario is currently more common because the major-ity of individuals self-present for genetic counseling due toconcerns about their family history. The latter scenario willbecome more common as mutation testing becomes stan-dard for selected subsets of newly diagnosed cases, suchas individuals with early-onset CRC and tumor characteris-tics suggestive of a germline mutation in a mismatch repairgene [66], or breast cancer cases with tumor characteristicssuggesting a germline mutation in BRCA1 or BRCA2 [67].As genetic testing becomes increasingly sophisticated andavailable, more people will have access to genetic

information that could have implications for their relatives’health. It is likely that the quantification of the risk of dis-ease in relatives of subjects carrying a high risk mutationwill be required for optimal treatment [68–70]. Kin–cohortstudies and case–cohort studies nested within the cohort ofthe relatives of the index subjects not only provide meas-ures of familial aggregation of disease, but these measuresmay also have significance from the clinical point of viewin the not too distant future.

The difference between the estimates obtained from thetype I and the type II approach has been discussed byKhoury and Flanders [7]. They compared the odds ratio de-rived from case–control studies in which the increased risk

Table 3

Type I estim in 28 studies

Cancer/

consultand’s [56] [58] [59] [60] [61] [62] [63] [64] [65] Na RRb 95% CI

Colorectal c

Either A A d A A d d B d 20 2.26 1.86, 2.73

Male d A d d d d d B d 5 2.02 1.61, 2.53

Female d A A d d d d B A 6 2.10 1.79, 2.46

Either d A d d d d d d d 7 2.15 1.74, 2.65




Colon cance

Either d A d A d A d d d 11 2.20 1.94, 2.50

Male d A d d d A d d d 5 2.25 1.79, 2.82

Female d A A d d A d d d 5 2.18 1.81, 2.63





Rectal canc

Either d A d A d d A d d 8 1.79 1.41, 2.26

Male d A d d d d A d d 4 1.60 1.25, 2.05

Female d A A d d d A d d 4 1.61 1.14, 2.28



Either d A d d d d A d d 3 1.72 1.30, 2.28

Either d A d d d d A d d 3 1.68 0.62, 4.57

Abbrevia study references.a Numbb Relati

119

L.Baglietto

etal./JournalofClin

icalEpidem

iology59(2006)114–124

ates of the relative risk of cancer for a consultand given a family history based on case–control (A) and cohort analysis (B)

sex Family history

Study

[22] [23] [24] [26] [27] [28] [29] [30] [31] [43] [45] [46] [47] [48] [49] [50] [51] [53] [54]

ancer

>1 FDR with CRC A A A d A A d A A A A A A A A B d d A

>1 FDR with CRC A d d d d d A d d d d d d d d B d d d

>1 FDR with CRC A d d d d d d d d d d d d d d B d d d

>1 parent with

CRC

A d d d d A d d d d A A A d d d d d A

>1 sibling with

CRC

d d d d A d d d d A A d d d d d A

1 FDR with CRC A d d d d d d A d d d d d A d B d d A

>2 FDR with CRC A d d d d d d A d d d d d d d B d d A

r

>1 FDR with CRC d d d A A A d d d d d A d d d B A A A

>1 FDR with CRC d d d A d d A d d d d d d d d B d d d>1 FDR with CRC d d d A d d d d d d d d d d d B d d d

>1 parent with

CRC

d d d d d A d d d d d d d d d d d d A

>1 sibling with

CRC


1 FDR with CRC d d d d d d d d d d d d d d d d A d A

>2 FDR with CRC d d d d d d d d d d d d d d d d A d A

er

>1 FDR with CRC d d d d A A d d d d d A d d d B d d A

>1 FDR with CRC d d d d d d A d d d d d d d d B d d d

>1 FDR with CRC d d d d d d d d d d d d d d d B d d d>1 parent with

CRC


>1 sibling with

CRC


1 FDR with CRC d d d d d d d d d d d d d d d d d d A

>2 FDR with CRC d d d d d d d d d d d d d d d d d d A

tions: CI, confidence interval; CRC, colorectal cancer; FDR, first-degree relative; RR, relative risk. Numbers in brackets are

er of estimates combined to obtain the pooled relative risk.

ve risk obtained pooling the published estimates.


Type I RR of colorectal cancer0.1 0.5 1.0 5.0 10.0 50.0 100.0

0.1 0.5 1.0 5.0 10.0 50.0 100.0

0.1 0.5 1.0 5.0 10.0 50.0 100.0

Duncan et al. 1982Pickle et al. 1984Bonelli et al. 1988Fisher et al. 1989Kune et al. 1989

Ponz de Leon et al. 1989Stephenson et al. 1991La Vecchia et al. 1992Centonze et al. 1993St John et al. 1993Fuchs et al. 1994

Boutron et al. 1995Kotake et al. 1995

Fredrikson et al. 1996Freedman et al. 1996

Negri et al. 1998Will et al. 1998

Coogan et al. 2000Seow et al. 2002Brauer et al. 2002

RR (95% CI) = 2.26 (1.86, 2.73)

Type I RR of colon cancer

Pickle et al. 1984Kune et al. 1989

La Vecchia et al. 1992Fuchs et al. 1994

Slattery et al. 1994Kotake et al. 1995

Ghadirian et al. 1998Kerber et al. 1998Negri et al. 1998

Coogan et al. 2000Keku et al. 2003

RR (95% CI) = 2.20 (1.95, 2.50)

Type I RR of rectal cancer

Pickle et al. 1984

Kune et al. 1989

La Vecchia et al. 1992

Fuchs et al. 1994

Kotake et al. 1995

Negri et al. 1998

Coogan et al. 2000

Slattery et al. 2003

RR (95% CI) = 1.79 ( 1.42, 2.26)

a

b

c

Fig. 1. Type I relative risks (RR) of (a) colorectal, (b) colon, and (c) rectal cancer given the presence of at least one first-degree relative affected by colorectal

cancer. The dashed lines represent the pooled estimates. CI, confidence interval.

of disease in the index subjects is evaluated according tothe distribution of disease among their relatives (type I)with measures of relative risk derived from comparing thelifetime risk of disease among first-degree relatives of casesubjects with that among first-degree relatives of controlsubjects (type II). They concluded that the first measureis always higher than the second one, the differencedepending on family variables, such as the number ofrelatives, and on disease characteristics, such as its preva-lence and its age at onset. However, differences betweenthe two measures should be expected, given that the two

estimates are effectively estimating a different parameter,as discussed above [8].

The meta-analysis we have conducted gives a summaryof the current knowledge about familial aggregation ofCRC. Particular attention was paid to the meaning of theestimates provided by the studies, attempting to extract in-formation that would be most useful in clinical settings.The great majority of studies reporting a measure of famil-ial aggregation have not been designed with familial aggre-gation as the primary end-point. In most epidemiologicalstudies, only a minimal family history is usually collected


from the index person; questions about disease in relativesare often general, the pedigree details usually do not in-volve a complete identification of relatives, and reports ofdisease in relatives are rarely validated. Very often theyhave been case–control studies in which information aboutdisease in relatives was collected as additional informationto the primary objectives, and included as a potential con-founder being the presence of a family history a well estab-lished risk factor. Although in principle this approachallows one to obtain estimates of the risk of disease formany distributions of disease within the family, usuallythe information about relatives’ disease status is not de-tailed enough, and the only estimate provided by the major-ity of the studies is the relative risk associated with havingat least one affected relative.

age

Type

I R

R o

f CR

C

40 50 60 70

1

2

3

4

5

6

7

Fig. 2. Type I relative risk (RR) of colorectal cancer (CRC) by age of the

index person given the presence of at least one first-degree relative affected

by CRC. Dotted lines join estimates from the same article. The size of each

point is inversely related to the variance of the estimate. The continuous

line corresponds to the fitted values as resulting from the weighted linear

mixed-effect model.

When estimates of the excess risk of disease due to thepresence of disease in relatives are combined, as in a meta-analysis, the validity of the pooled estimate depends on theaccuracy of the single measures. Possible limitations of theoriginal single estimates include misreporting of the familycancer history, heterogeneity in the underlying cancer inci-dence rates, and for type II RR, lack of adjustment for thecorrelation among individuals in the same family. For CRC,misclassification of exposure (family history of cancer)should not be high. Although in only 30% of the studiesdid the authors attempt to verify the reported diagnosesof colorectal cancer in first-degree relatives through medi-cal records, there is evidence showing that report of colo-rectal cancer in first-degree relatives is quite accurate[71]. When the studies were grouped according to the geo-graphical area in order to account for possible differencesbetween the underlying cancer incidence rates, we did notfind any heterogeneity (data not shown); however, the smallnumber of studies did not allow any more detailed investi-gations. Finally, the adjustment for the correlation amongindividuals belonging to the same family, properly donein three of the seven studies reporting type II RRs, is some-thing that is not possible to control in a meta-analysis un-less specific correlation data are available for all studies.

Our systematic literature review and meta-analysis leadsto the conclusion that having at least one affected first-degree relative approximately doubles the risk of develop-ing CRC and the increased risk increases with having morethan one affected relative. No difference was observed be-tween males and females, suggesting that the risk factorsshared by individuals within a family are not sex-related.The risk associated with having an affected sibling wasonly slightly higher than the risk associated with havingan affected parent, and more studies are required to deter-mine the etiological significance of this difference. Havinga relative with CRC appears to be associated with a greater

Table 4

Type II estimates of the relative risk of colorectal cancer in a relative (consultand) of an individuals affected by cancer based on case–control (A)

and cohort analysis (B) in seven studies

Consultand’s relationship

to the index person

Family history (cancer

in the index person)

Study

[26] [30] [42] [44] [52] [55] [57] Na RRb 95% CI

Any FDR CRC d A B B B A A 7 2.81 2.05, 3.85

Siblings CRC d A d B d A A 5 3.47 2.24, 5.40

Parents CRC d A d B d A A 5 1.85 1.63, 2.09

Any FDR CC B A B B d A d 5 2.04 1.84, 2.27

Siblings CC d d d B d d d 1 2.82 2.21, 3.54

Parents CC d d d B d d d 1 1.91 1.59, 2.26

Any FDR RC d A B B d A d 4 1.87 1.37, 2.54

Siblings RC d d d B d d d 1 1.60 1.27, 2.00

Parents RC d d d B d d d 1 2.41 1.75, 3.24

Abbreviations: CC, colon cancer; CI, confidence interval; CRC, colorectal cancer; FDR, first-degree relatives; RC, rectal cancer. Numbers in brackets are

study references.a Number of estimates combined to obtain the pooled relative risk. Modica et al. [57] reported the estimates from two independent studies.b Relative risk obtained pooling the published estimates.


increased risk of cancer of the colon than cancer of the rec-tum. Differences in the etiologies of the cancers at the twosubsites are possible, but the issue can be addressed only bystudies that treat cancers of the colon and rectum separatelyfor both the probands and their relatives. This was the ap-proach taken in the study by Goldgar et al. [72], wherethe familial risk associated with rectal cancer appeared tobe smaller than that associated with colon cancer, but theconfidence intervals were large and the difference was notstatistically significant.

A method based on multilevel linear regression was ap-plied to combine estimates of age-specific relative risks.The risk decreased with age, but it remained significantlyabove unity at 70 years of age. The method that was appliedtests for trend in relative risks by age adjusting for withinstudy correlation at different ages and has the advantageof overcoming the problem of combining estimates whentheir age ranges do not correspond. Moreover, it allowed in-ferences to be made about the strength of the effect of fam-ily history at any age, thus going beyond the limits of theindividual studies with evident advantages from the clinicalpoint of view. Few studies estimated the risk to relatives ofyoung cases [25,32]; however data were not available toevaluate how the risk to probands varied with the age atdiagnosis of CRC in relatives.

Pooled estimates of type II relative risks were calculat-ed. These estimates have to be considered as measures offamilial aggregation but they are not directly comparablewith type I relative risks.

Another meta-analysis on familial aggregation of CRChas recently been published by Johns and Houlston [34].In this analysis, the authors distinguished between case–control studies and cohort studies, but did not attempt tofurther classify the estimates and combined type I and typeII estimates together. The results obtained in our meta-analysis for type I relative risks do not differ substantiallyfrom those reported [34]. A possible explanation for thissimilarity is that the great majority of published studieshave estimated type I relative risks, with only 7 studiesout of 33 estimating type II relative risks. It is probable thatthe expected difference between the estimates of type I andtype II lies within the range of variation of their estimates.Nevertheless, the proposed method is more rigorous andcertainly to be preferred, especially when the number ofstudies available for pooling becomes greater.

Acknowledgments

This study was supported by The Cancer Council Victo-ria and funded by NHMRC program grant ECHIDNAS(Epidemiology of Chronic Disease, Health Interventionsand DNA studies) (209057); NHMRC capacity-buildinggrant PLATYPUSES [Platform for young public healthresearchers to upgrade their scientific training experienceand independent status] (251533); NIH Australasian

Colorectal Cancer Family Study. (1U01CA97735-01).The contributions of L.B. and G.S. were supported in partby fellowships from the UICC (ICRETT).

References

[1] Susser E, Susser M. Familial aggregation studies: a note on their

epidemiologic properties. Am J Epidemiol 1989;129:23–30.

[2] Hopper JL, Bishop DT, Easton DF. Population-based family studies

in genetic epidemiology. Lancet 2005;366:1397–406.

[3] Pharoah PD, Day NE, Duffy S, Easton DF, Ponder BA. Family

history and the risk of breast cancer: a systematic review and meta-

analysis. Int J Cancer 1997;71:800–9.

[4] Johns LE, Kee F, Collins BJ, Patterson CC, Houlston RS. Colorectal

cancer mortality in first-degree relatives of early-onset colorectal

cancer cases. Dis Colon Rectum 2002;45:681–6.

[5] Bruner DW, Moore D, Parlanti A, Dorgan J, Engstrom P. Relative

risk of prostate cancer for men with affected relatives: systematic

review and meta-analysis. Int J Cancer 2003;107:797–803.

[6] Johns LE, Houlston RS. A systematic review and meta-analysis of

familial prostate cancer risk. BJU Int 2003;91:789–94.

[7] Khoury MJ, Flanders WD. Bias in using family history as a risk

factor in case–control studies of disease. Epidemiology 1995;6:

511–9.

[8] Hopper JL. Different, not biased. Epidemiology 1996;7:330.

[9] Parkin DM, Pisani P, Ferlay J. Estimates of the worldwide incidence

of 25 major cancers in 1990. Int J Cancer 1999;80:827–41.

[10] Pisani P, Parkin DM, Bray F, Ferlay J. Estimates of the worldwide

mortality from 25 cancers in 1990. Int J Cancer 1999;83:18–29.

[11] Parkin DM, Bray F, Ferlay J, Pisani P. Estimating the world cancer

burden: Globocan 2000. Int J Cancer 2001;94:153–6.

[12] Aaltonen LA, Peltomaki P, Mecklin JP, Jarvinen H, Jass JR,

Green JS, et al. Replication errors in benign and malignant tumors

from hereditary nonpolyposis colorectal cancer patients. Cancer Res

1994;54:1645–8.

[13] Bishop DT, Thomas HJ. The genetics of colorectal cancer. Cancer

Surv 1990;9:585–604.

[14] Bussey H. Familial polyposis coli: family studies, histopathology,

differential diagnosis, and results of treatment. Baltimore, MD: Johns

Hopkins University Press; 1975.

[15] Herrera L, editor. Familial adenomatous polyposis. New York: Alan

R. Liss, Inc.; 1990.

[16] Bulow S. Familial polyposis coli. Dan Med Bull 1987;34:1–15.

[17] Lynch HT, Smyrk TC. Classification of familial adenomatous

polyposis: a diagnostic nightmare. Am J Hum Genet 1998;62:

1288–9.

[18] Bishop DT, Hall NR. The genetics of colorectal cancer. Eur J Cancer

1994;30A:1946–56.

[19] Boland C. Hereditary nonpolyposis colorectal cancer. In:

Vogelstein B, Kinzler KW, editors. The genetic basis of human

cancer. 1st ed. New York: McGraw-Hill; 1998.

[20] Lynch HT, Smyrk TC, Watson P, Lanspa SJ, Lynch JF, Lynch PM,

et al. Genetics, natural history, tumor spectrum, and pathology of

hereditary nonpolyposis colorectal cancer: an updated review.

Gastroenterology 1993;104:1535–49.

[21] Lynch HT, Smyrk T. Hereditary nonpolyposis colorectal cancer

(Lynch syndrome): an updated review. Cancer 1996;78:1149–67.

[22] Bonelli L, Martines H, Conio M, Bruzzi P, Aste H. Family history of

colorectal cancer as a risk factor for benign and malignant tumours of

the large bowel: a case–control study. Int J Cancer 1988;41:513–7.

[23] Boutron MC, Faivre J, Quipourt V, Senesse P, Michiels C. Family his-

tory of colorectal tumours and implications for the adenoma-carcino-

ma sequence: a case control study. Gut 1995;37:830–4.

[24] Freedman AN, Michalek AM, Marshall JR, Mettlin CJ, Petrelli NJ,

Black JD, et al. Familial and nutritional risk factors for p53


overexpression in colorectal cancer. Cancer Epidemiol Biomarkers

Prev 1996;5:285–91.

[25] Hall NR, Finan PJ, Ward B, Turner G, Bishop DT. Genetic suscepti-

bility to colorectal cancer in patients under 45 years of age. Br J Surg

1994;81:1485–9.

[26] Kerber RA, Slattery ML, Potter JD, Caan BJ, Edwards SL. Risk of

colon cancer associated with a family history of cancer or colorectal

polyps: the diet, activity, and reproduction in colon cancer study. Int J

Cancer 1998;78:157–60.

[27] Kotake K, Koyama Y, Nasu J, Fukutomi T, Yamaguchi N. Relation of

family history of cancer and environmental factors to the risk of co-

lorectal cancer: a case–control study. Jpn J Clin Oncol 1995;25:

195–202.

[28] Kune GA, Kune S, Watson LF. The role of heredity in the etiology of

large bowel cancer: data from the Melbourne Colorectal Cancer

Study. World J Surg 1989;13:124–9.

[29] Longnecker MP. A case–control study of alcoholic beverage con-

sumption in relation to risk of cancer of the right colon and rectum

in men. Cancer Causes Control 1990;1:5–14.

[30] St John DJ, McDermott FT, Hopper JL, Debney EA, Johnson WR,

Hughes ES. Cancer risk in relatives of patients with common colorec-

tal cancer. Ann Intern Med 1993;118:785–90.

[31] Stephenson BM, Finan PJ, Gascoyne J, Garbett F, Murday VA,

Bishop DT. Frequency of familial colorectal cancer. Br J Surg 1991;

78:1162–6.

[32] Jenkins MA, Baglietto L, Dite GS, Jolley DJ, Southey MC, Whitty J,

et al. After hMSH2 and hMLH1dwhat next? Analysis of three-

generational, population-based, early-onset colorectal cancer fami-

lies. Int J Cancer 2002;102:166–71.

[33] Macklin MT. Inheritance of cancer of the stomach and large intestine

in man. J Natl Cancer Inst 1960;24:551–71.

[34] Johns LE, Houlston RS. A systematic review and meta-analysis of

familial colorectal cancer risk. Am J Gastroenterol 2001;96:2992–

3003.

[35] Love RR, Evans AM, Josten DM. The accuracy of patient reports of

a family history of cancer. J Chronic Dis 1985;38:289–93.

[36] Theis B, Boyd N, Lockwood G, Tritchler D. Accuracy of family can-

cer history in breast cancer patients. Eur J Cancer Prev 1994;3:321–7.

[37] Breslow N, Day N. Statistical methods in cancer research. Vol. 1. The

analysis of case–control studies. Lyon, France: International Agency

for Research on Cancer; 1980.

[38] Breslow N, Day N. Statistical methods in cancer research. Vol. 2. The

design and analysis of cohort studies. Lyon, France: International

Agency for Research on Cancer; 1987.

[39] Fleiss JL. The statistical basis of meta-analysis. Stat Methods Med

Res 1993;2:121–45.

[40] DerSimonian R, Laird N. Meta-analysis in clinical trials. Control

Clin Trials 1986;7:177–88.

[41] Goldstein H. Multilevel statistical models. London: Edward Arnold;

1995.

[42] Andrieu N, Launoy G, Guillois R, Ory-Paoletti C, Gignoux M.

Familial relative risk of colorectal cancer: a population-based study.

Eur J Cancer 2003;39:1904–11.

[43] Brauer PM, McKeown-Eyssen GE, Jazmaji V, Logan AG,

Andrews DF, Jenkins D, et al. Familial aggregation of diabetes and

hypertension in a case–control study of colorectal neoplasia. Am J

Epidemiol 2002;156:702–13.

[44] Carstensen B, Soll-Johanning H, Villadsen E, Sondergaard JO,

Lynge E. Familial aggregation of colorectal cancer in the general

population. Int J Cancer 1996;68:428–35.

[45] Centonze S, Boeing H, Leoci C, Bonfiglio C, Guerra V, Misciagna G.

Familial risk of colo-rectal cancer in a low incidence area in southern

Italy. Eur J Epidemiol 1993;9:26–32.

[46] Coogan PF, Rosenberg L, Louik C, Zauber AG, Stolley PD,

Strom BL, et al. NSAIDs and risk of colorectal cancer according to

presence or absence of family history of the disease. Cancer Causes

Control 2000;11:249–55.

[47] Duncan JL, Kyle J. Family incidence of carcinoma of the colon and

rectum in north-east Scotland. Gut 1982;23:169–71.

[48] Fisher G, Armstrong B. Familial colorectal cancer and the screening

of family members. Med J Aust 1989;150:22–5.

[49] Fredrikson M, Axelson O, Sun XF, Arbman G, Nilsson E,

Nordenskjold B, et al. A pilot study on risk factors and p53 gene

expression in colorectal cancer. Br J Cancer 1996;73:1428–30.

[50] Fuchs CS, Giovannucci EL, Colditz GA, Hunter DJ, Speizer FE,

Willett WC. A prospective study of family history and the risk of

colorectal cancer. New Engl J Med 1994;331:1669–74.

[51] Ghadirian P, Maisonneuve P, Perret C, Lacroix A, Boyle P. Epidemi-

ology of sociodemographic characteristics, lifestyle, medical history,

and colon cancer: a case–control study among French Canadians in

Montreal. Cancer Detect Prev 1998;22:396–404.

[52] Karner-Hanusch J, Mittlbock M, Fillipitsch T, Herbst F. Family his-

tory as a marker of risk for colorectal cancer: Austrian experience.

World J Surg 1997;21:205–9.

[53] Keku TO, Millikan RC, Martin C, Rahkra-Burris TK, Sandler RS.

Family history of colon cancer: what does it mean and how is it use-

ful? Am J Prev Med 2003;24:170–6.

[54] La Vecchia C, Negri E, Franceschi S, Gentile A. Family history and

the risk of stomach and colorectal cancer. Cancer 1992;70:50–5.

[55] Le Marchand L, Zhao LP, Quiaoit F, Wilkens LR, Kolonel LN. Fam-

ily history and risk of colorectal cancer in the multiethnic population

of Hawaii. Am J Epidemiol 1996;144:1122–8.

[56] Ponz de Leon M, Sassatelli R, Sacchetti C, Zanghieri G, Scalmati A,

Roncucci L. Familial aggregation of tumors in the three-year experi-

ence of a population-based colorectal cancer registry. Cancer Res

1989;49:4344–8.

[57] Modica S, Roncucci L, Benatti P, Gafa L, Tamassia MG,

Dardanoni L, et al. Familial aggregation of tumors and detection of

hereditary non-polyposis colorectal cancer in 3-year experience of

2 population-based colorectal-cancer registries. Int J Cancer 1995;62:

685–90.

[58] Negri E, Braga C, La Vecchia C, Franceschi S, Filiberti R,

Montella M, et al. Family history of cancer and risk of colorectal can-

cer in Italy. Br J Cancer 1998;77:174–9.

[59] Newcomb PA, Taylor JO, Trentham-Dietz A. Interactions of familial

and hormonal risk factors for large bowel cancer in women. Int J

Epidemiol 1999;28:603–8.

[60] Pickle LW, Greene MH, Ziegler RG, Toledo A, Hoover R, Lynch HT,

et al. Colorectal cancer in rural Nebraska. Cancer Res 1984;44:

363–9.

[61] Seow A, Quah SR, Nyam D, Straughan PT, Chua T, Aw TC. Food

groups and the risk of colorectal carcinoma in an Asian population.

Cancer 2002;95:2390–6.

[62] Slattery ML, Kerber RA. Family history of cancer and colon cancer

risk: the Utah Population Database. J Natl Cancer Inst 1994;86:

1618–26 [Erratum in: J Natl Cancer Inst 1994;86:1802].

[63] Slattery ML, Levin TR, Ma K, Goldgar D, Holubkov R, Edwards S.

Family history and colorectal cancer: predictors of risk. Cancer

Causes Control 2003;14:879–87.

[64] Will JC, Galuska DA, Vinicor F, Calle EE. Colorectal cancer: another

complication of diabetes mellitus? Am J Epidemiol 1998;147:

816–25.

[65] Yoo KY, Tajima K, Inoue M, Takezaki T, Hirose K, Hamajima N,

et al. Reproductive factors related to the risk of colorectal cancer

by subsite: a case–control analysis. Br J Cancer 1999;79:1901–6.

[66] Hopper JL. Application of genetics to the prevention of colorectal

cancer. Recent Results Cancer Res 2005;166:17–33.

[67] Armes JE, Egan AJ, Southey MC, Dite GS, McCredie MR, Giles GG,

et al. The histologic phenotypes of breast carcinoma occurring before

age 40 years in women with and without BRCA1 or BRCA2 germ-

line mutations: a population-based study. Cancer 1998;83:2335–45.

[68] Bianchi F, Rosati S, Belvederesi L, Loretelli C, Ferretti B, Bearzi I,

et al. ‘Secrets and lies’dthe difficulties of communicating within

families with inherited cancer syndromes. Clin Genet 2004;66:476–7.


[69] Forrest K, Simpson SA, Wilson BJ, van Teijlingen ER, McKee L,

Haites N, et al. To tell or not to tell: barriers and facilitators in

family communication about genetic risk. Clin Genet 2003;64:

317–26.

[70] Hamilton RJ, Bowers BJ, Williams JK. Disclosing genetic test results

to family members. J Nurs Scholarsh 2005;37:18–24.

[71] Kerber RA, Slattery ML. Comparison of self-reported and database-

linked family history of cancer data in a case–control study. Am J

Epidemiol 1997;146:244–8.

[72] Goldgar DE, Easton DF, Cannon-Albright LA, Skolnick MH.

Systematic population-based assessment of cancer risk in first-degree

relatives of cancer probands. J Natl Cancer Inst 1994;86:1600–8.

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Measures of familial aggregation depend on definition of family history: meta-analysis for colorectal cancer