Dataset Information

Determining the familial risk distribution of colorectal cancer: a data mining approach.

ABSTRACT: This study was aimed to characterize the distribution of colorectal cancer risk using family history of cancers by data mining. Family histories for 10,066 colorectal cancer cases recruited to population cancer registries of the Colon Cancer Family Registry were analyzed using a data mining framework. A novel index was developed to quantify familial cancer aggregation. Artificial neural network was used to identify distinct categories of familial risk. Standardized incidence ratios (SIRs) and corresponding 95% confidence intervals (CIs) of colorectal cancer were calculated for each category. We identified five major, and 66 minor categories of familial risk for developing colorectal cancer. The distribution the major risk categories were: (1) 7% of families (SIR = 7.11; 95% CI 6.65-7.59) had a strong family history of colorectal cancer; (2) 13% of families (SIR = 2.94; 95% CI 2.78-3.10) had a moderate family history of colorectal cancer; (3) 11% of families (SIR = 1.23; 95% CI 1.12-1.36) had a strong family history of breast cancer and a weak family history of colorectal cancer; (4) 9 % of families (SIR = 1.06; 95 % CI 0.96-1.18) had strong family history of prostate cancer and weak family history of colorectal cancer; and (5) 60% of families (SIR = 0.61; 95% CI 0.57-0.65) had a weak family history of all cancers. There is a wide variation of colorectal cancer risk that can be categorized by family history of cancer, with a strong gradient of colorectal cancer risk between the highest and lowest risk categories. The risk of colorectal cancer for people with the highest risk category of family history (7% of the population) was 12-times that for people in the lowest risk category (60%) of the population. Data mining was proven an effective approach for gaining insight into the underlying cancer aggregation patterns and for categorizing familial risk of colorectal cancer.

SUBMITTER: Chau R

PROVIDER: S-EPMC4803603 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Determining the familial risk distribution of colorectal cancer: a data mining approach.

Chau Rowena R Jenkins Mark A MA Buchanan Daniel D DD Ait Ouakrim Driss D Giles Graham G GG Casey Graham G Gallinger Steven S Haile Robert W RW Le Marchand Loic L Newcomb Polly A PA Lindor Noralane M NM Hopper John L JL Win Aung Ko AK

Familial cancer 20160401 2

This study was aimed to characterize the distribution of colorectal cancer risk using family history of cancers by data mining. Family histories for 10,066 colorectal cancer cases recruited to population cancer registries of the Colon Cancer Family Registry were analyzed using a data mining framework. A novel index was developed to quantify familial cancer aggregation. Artificial neural network was used to identify distinct categories of familial risk. Standardized incidence ratios (SIRs) and co ...[more]

PMID: 26681340

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Project description:ObjectiveTo explore the risk of colorectal cancer in family members of patients with colorectal cancer, with an emphasis on subtypes of second degree relatives, especially half siblings, which were lacking in the literature.DesignAmbidirectional cohort study.SettingNationwide Swedish Family Cancer Data (record linkage).ParticipantsAll people residing in Sweden and born after 1931, with their biological parents, totalling >16 million individuals (follow-up: 1958-2015); of those with clear genealogy, 173 796 developed colorectal cancer.Main outcome measuresLifetime (0-79 years) cumulative risk and standardised incidence ratio of colorectal cancer among first degree relatives and second degree relatives.ResultsThe overall lifetime cumulative risk of colorectal cancer in siblings of patients was 7%, which represents a 1.7-fold (95% confidence interval 1.6 to 1.7; n=2089) increase over the risk in those without any family history of colorectal cancer. A similarly increased lifetime cumulative risk (6%) was found among half siblings (standardised incidence ratio 1.5, 95% confidence interval 1.3 to 1.8; n=140). The risk in people with colorectal cancer in both a parent and a half sibling (standardised incidence ratio 3.6, 2.4 to 5.0; n=32) was close to the risk in those with both an affected parent and an affected sibling (2.7, 2.4 to 3.0; n=396). Family history of colorectal cancer in only one second degree relative other than a half sibling (without any affected first degree relatives), such as a grandparent, uncle, or aunt, showed minor association with the risk of colorectal cancer.ConclusionFamily history of colorectal cancer in half siblings is similarly associated with colorectal cancer risk to that in siblings. The increase in risk of colorectal cancer among people with one affected second degree relative was negligible, except for half siblings, but the risk was substantially increased for a combination of family history in one affected second degree relative and an affected first degree relative (or even another second degree relative). These evidence based findings provide novel information to help to identify people at high risk with a family history of colorectal cancer that can potentially be used for risk adapted screening.

Project description:BACKGROUND & AIMS:We analyzed data from twins to determine how much the familial risk of colorectal cancer can be attributed to genetic factors vs environment. We also examined whether heritability is distinct for colon vs rectal cancer, given evidence of distinct etiologies. METHODS:Our data set included 39,990 monozygotic and 61,443 same-sex dizygotic twins from the Nordic Twin Study of Cancer. We compared each cancer's risk in twins of affected co-twins relative to the cohort risk (familial risk ratio [FRR]). We then estimated the proportion of variation in risk that could be attributed to genetic factors (heritability). RESULTS:From earliest registration in 1943 through 2010, there were 1861 individuals diagnosed with colon cancer and 1268 diagnosed with rectal cancer. Monozygotic twins of affected co-twins had an FRR for colorectal cancer of 3.1 (95% confidence interval [CI], 2.4-3.8) relative to the cohort risk. Dizygotic twins of affected co-twins had an FRR for colorectal cancer of 2.2 (95% CI, 1.7-2.7). We estimated that 40% (95% CI, 33%-48%) of the variation in colorectal cancer risk could be attributed to genetic factors; unique environment only accounted for the remaining liability. For colon cancer, the FRR was 3.3 (95% CI, 2.1-4.5) for monozygotic twins and 2.6 (95% CI, 1.7-3.5) for dizygotic twins. For rectal cancer, comparable estimates were 3.3 (95% CI, 1.5-5.1) for monozygotic twins and 2.6 (95% CI, 1.2-4.0) for dizygotic twins. Heritability estimates for colon and rectal cancer were 16% (95% CI, 0-46%) and 15% (95% CI, 0-50%), common environment estimates were 15% (95% CI, 0-38%) and 11% (95% CI, 0-38%), and unique environment estimates were 68% (95% CI, 57%-79%) and 75% (95% CI, 61%-88%), respectively. CONCLUSIONS:Interindividual genetic differences could account for 40% of the variation in susceptibility to colorectal cancer; risk for colon and rectal cancers might have less of a genetic component than risk for colorectal cancer. Siblings, and particularly monozygotic co-twins, of individuals with colon or rectal cancer should consider personalized screening.

Dataset Information

Determining the familial risk distribution of colorectal cancer: a data mining approach.

Publications

Determining the familial risk distribution of colorectal cancer: a data mining approach.

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