Segregation and linkage analysis of nine Utah breast cancer pedigrees

The analysis of nine Utah families that were ascertained for clusters of breast cancer cases is reported. Segregation analysis of an inherited susceptibility to breast cancer shows two distinct maximum likelihood solutions that have almost equal likelihood. One model indicates that most females had zero risk for breast cancer, but 10% of the female population had risks much greater than the Utah age-specific incidence rates. The other model indicates that most females have a risk defined by the Utah rates for breast cancer, but a rare dominant gene is segregating for increased susceptibility to breast cancer. Our analysis shows that linkage results under the two models are consistent in sign but not in magnitude. No evidence for linkage was found with the 14 marker loci examined. In addition to demonstrating distortion of linkage results from ignoring sporadic cases, this analysis shows the inherent difficulty of obtaining parameter estimates for segregation analysis when families are ascertained from a cluster of cases.     

Genetic epidemiology of breast cancer: segregation analysis of 389 Icelandic pedigrees

A genetic epidemiologic investigation of breast cancer involving 389 breast cancer pedigrees including information on 14,721 individuals from the Icelandic population-based cancer registry is presented. Probands were women born in or after 1920 and reported to have breast cancer in the cancer registry. The average age of the 389 probands was 45.5 years (SD 8.92). Segregation analyses was performed evaluating residual maternal effects, a dichotomous cohort effect, and assuming the age at diagnosis followed a logistic distribution after log-transformation. Familial aggregation could be best explained by the inheritance of a high-risk allele leading to early onset breast cancer among the homozygotes, which represent approximately 2.6% of the population. A Mendelian codominant model was selected as the best fitting model, with an estimated age at diagnosis of 51.8 years among these high-risk homozygotes, 64.0 years for heterozygotes and 76.3 years for the low-risk genotype. The predicted cumulative risk for homozygote carriers of the high-risk allele is 32.2% by age 60, compared to 16.4% for heterozygotes and 5.0% for non-carriers of the same age. These predicted age profiles in the current study complement recent reports from Iceland of a majority of BRCA2 mutation carriers being diagnosed with breast cancer below the age of 50 years, and 60 years being the mean age at diagnosis for non-carriers. This model also predicted a high background risk of breast cancer for women in this population (estimated susceptibility gamma = 0.44 +/- 0.08). This implies that if carriers and non-carriers did not die of competing causes, the estimated risk of being diagnosed with breast cancer by age 80 years irrespective of carrier status is 11.4%.     

Genetic epidemiology of breast cancer: segregation analysis of 200 Danish pedigrees

An investigation of the genetic epidemiology of breast cancer involving complex segregation analysis of 200 breast cancer pedigrees of Danish extraction is presented. The observed distribution of breast cancer is compatible with transmission of an autosomal-dominant gene with no evidence for residual family resemblance. The gene frequency of the abnormal allele is 0.00756, and the displacement between the homozygous genotype means is 1.695. The gene frequency accounts for a significant proportion of breast cancer in young women, whereas by an advanced age a majority (87%) of affected women are phenocopies. Genetic modeling of other breast cancer families and results of linkage studies are reviewed.     

Cost-effectiveness analysis of prostate cancer screening

To determine the optimal strategy for prostate cancer screening, the cost-effectiveness of screening was analyzed using a medical decision model. One hundred thousand asymptomatic males between the ages of 40 and 69 were modeled with and without screening. The subjects were divided into three 10-year age groups. We used a 5-year survival rate as an effectiveness point and assumed after 5 year survival free from prostate cancer. We considered three potential programs: 1) screening with digital rectal examination (DRE), 2) screening with prostate specific antigen (PSA), and 3) screening with a combination of DRE and PSA. The study was analyzed from the payer’s perspective, and only direct medical costs were included. For each of the three age groups, PSA screening was more cost-effective than either DRE screening or a combination of DRE and PSA screening. The cost-effectiveness ratio for the combination of DRE and PSA screening was 1.1–2.3 times more expensive dian that of PSA screening. If the compliance rate for work-up exams is 80%, the cost-effectiveness of prostate cancer screening is approximate to that of gastric cancer screening. In conclusion, PSA screening is the most cost-effective strategy for prostate cancer screening when compared with both DRE and the combination of DRE and PSA screening. But prostate cancer screening should be carefully conducted, taking the cost-effectiveness of the different strategies and target groups into consideration.     

Genetic analysis of families with nonsmoking lung cancer probands

As part of a genetic epidemiologic study of lung cancer among nonsmokers, we investigated the role of genetic predisposition in familial aggregation. Cases were identified from the Metropolitan Detroit Cancer Surveillance System. Information on lung cancer occurrence, smoking habits (active or passive), and chronic respiratory diseases in first-degree relatives was obtained for 257 nonsmoking lung cancer probands (71 males, 186 females) diagnosed at ages 40–84 years. Among the 2,021 first-degree relatives, 24 (2.6%) males and 10 (1.1%) females were reported as having lung cancer. The occurrence of lung cancer among smoking and nonsmoking relatives was 4.5% and 1.1% in males and 2.8% and 0.4% in females, respectively. To evaluate the role of a putative Mendelian gene (one locus, two alleles) in the presence of other risk factors, we performed complex segregation analyses on the data using two different regressive model approaches [Segregation Analysis of a Discrete Trait Under a Class A Regressive Logistic Model, V4.0 (REGD) and Segregation Analysis of a Truncated Trait, V2.0, Model I (REGTL)] as implemented in the Statistical Analysis for Genetic Epidemiology (SAGE) program. Using either approach, an environmental model best explained the observed lung cancer aggregation in families ascertained through nonsmoking probands. Based on our final model, only 0.04% of this population had a very high risk and 4.2% had a moderate risk of lung cancer. The rest of the population had virtually no risk of lung cancer during their lifetime unless they have multiple risk factors. Among the high-risk individuals without any risk factor under study, the estimated risks at ages 40,60, and 80 years in males were 16.7%, 83.6%, and 95.4%, and in females were 14.0%, 72.2%, and 88.0%, respectively. Among at-moderate-risk smokers the estimated risks at the same age and gender groups were essentially the same as in the high-risk nonsmokers. Our results suggest that the pattern of lung cancer occurrence in families of nonsmoking lung cancer patients differs from that in families of smoking lung cancer patients. Despite the profound effect of smoking on the risk of lung cancer, other environmental and/or genetic risk factors need to be identified. Genet. Epidemiol. 14:181–197,1997. © 1997 Wiley-Liss, Inc.     

Choice of time-scale in Cox's model analysis of epidemiologic cohort data: a simulation study

Cox's regression model is widely used for assessing associations between potential risk factors and disease occurrence in epidemiologic cohort studies. Although age is often a strong determinant of disease risk, authors have frequently used time-on-study instead of age as the time-scale, as for clinical trials. Unless the baseline hazard is an exponential function of age, this approach can yield different estimates of relative hazards than using age as the time-scale, even when age is adjusted for. We performed a simulation study in order to investigate the existence and magnitude of bias for different degrees of association between age and the covariate of interest. Age to disease onset was generated from exponential, Weibull or piecewise Weibull distributions, and both fixed and time-dependent dichotomous covariates were considered. We observed no bias upon using age as the time-scale. Upon using time-on-study, we verified the absence of bias for exponentially distributed age to disease onset. For non-exponential distributions, we found that bias could occur even when the covariate of interest was independent from age. It could be severe in case of substantial association with age, especially with time-dependent covariates. These findings were illustrated on data from a cohort of 84,329 French women followed prospectively for breast cancer occurrence. In view of our results, we strongly recommend not using time-on-study as the time-scale for analysing epidemiologic cohort data.     

Segregation analysis of plasma lipoprotein(a) levels in pedigrees with molecularly defined familial hypercholesterolemia

The role of genetic and environmental factors in determining the variability in plasma lipoprotein(a) [Lp(a)] levels was investigated in 220 members of 14 families with familial hypercholesterolemia (FH) whose plasma Lp(a) levels were previously reported [Leitersdorf et al. (1991) J Lipid Res 32:1513–1519]. One hundred four subjects harbored a mutant low density lipoprotein (LDL) receptor allele as confirmed by the identification of the specific mutations in addition to the haplo-type analysis reported before. Four different mutant alleles were identified, each in a defined genetic group—Druze, Christian-Arabs, Ashkenazi, and Sephardic Jews. Sex- and age-adjusted mean plasma Lp(a) levels were significantly higher in FH family members (34.0 mg/dl) than in non-FH family members (21.1 mg/dl). Lp(a) levels were further adjusted for lipid levels and apo(a) isoforms. A mixture of two normal distributions fitted the adjusted Lp(a) levels better than did a single normal distribution. Segregation analysis indicated that a major effect of a non-transmitted environmental factor explained the mixture of distributions in addition to polygenic loci which influenced Lp(a) levels within each distribution. The major environmental factor and the polygenic loci accounted for 45% and 20% of the adjusted Lp(a) variation, respectively. Furthermore, sex, age, lipid levels, apo(a) isoform, the major environmental effect, and the unmeasured polygenes could account for 80% of the unadjusted variation of plasma Lp(a) in these families. © 1995 Wiley-Liss, Inc.     

Increased cancer risk among relatives of nonsmoking lung cancer cases

Lung cancer has been shown to aggregate in families of nonsmoking lung cancer cases with an earlier age at onset. The current study evaluates whether relatives of nonsmoking lung cancer cases are at increased risk of cancers at sites other than lung. Families were identified through 257 population‐based, nonsmoking lung cancer cases and 277 population‐based, nonsmoking controls residing in metropolitan Detroit. Data were collected for 2,252 relatives of cases and 2,408 relatives of controls. First‐degree relatives of nonsmoking lung cancer cases were at 1.52‐fold (95% CI, 1.02–2.27) increased risk of cancer of the digestive system after adjustment for each relative's age, race, sex, and smoking status. Relative risk estimates also were elevated, but not significantly, for tobacco‐related cancers (RR = 1.39) and breast cancer (RR = 1.72). Among first‐degree relatives of younger probands (age 40–59), risk was non‐significantly increased 72% (95% CI 0.95–3.10) for all cancers combined and 3.14‐fold for cancers of the digestive system (95% CI 0.76–12.9). Nonsmoking relatives of cases were at increased risk of all cancer sites combined (RR = 1.32; 95% CI 1.003–1.73), cancers other than lung (RR = 1.37; 95% CI 1.03–1.82), and digestive system cancers (RR = 2.01; 95% CI 1.20–3.37). These findings of moderate familial aggregation for cancers of the lung, digestive system, breast, and tobacco‐related sites suggest that common susceptibility genes may act to increase risk for a variety of cancers in families. Genet. Epidemiol. 17:1–15, 1999. © 1999 Wiley‐Liss, Inc.     

Treatment results of radiotherapy to both the prostate and metastatic sites in patients with bone metastatic prostate cancer

Although systemic therapy is the standard treatment for metastatic prostate cancer, a randomized controlled trial showed radiotherapy to the prostate improved overall survival of metastatic prostate cancer patients with the low metastatic burden. Additionally, a randomized phase II trial showed that metastasis-directed therapy for oligo-recurrent prostate cancer improved androgen-deprivation therapy (ADT)-free survival. Therefore, administering radiotherapy to both prostate and metastatic regions might result in better outcomes. Thus, we report the treatment results of radiotherapy to both prostate and metastatic regions. Our institutional database was searched for patients who received radiotherapy to the prostate and metastatic regions. We summarized patient characteristics and treatment efficacy and performed statistical analysis to find possible prognostic factors. A total of 35 patients were included in this study. The median age was 66 years, and the median initial prostate-specific antigen (PSA) level was 32 ng/ml. The Gleason score was 7 in 10 patients, 8 in 13 patients, and 9 in 12 patients. The median radiotherapy dose was 72 Gy to the prostate and 50 Gy to the metastatic bone region. The 8-year overall survival, cause-specific survival, progression-free survival, and freedom from biochemical failure rate were 81, 85, 53, and 57%. Among the 35 patients, 12 were disease-free even after ADT was discontinued. In selected patients with metastatic prostate cancer, ADT and radiotherapy to the prostate and metastatic sites were effective. Patients with good response to ADT may benefit from radiotherapy to both prostate and metastatic regions.     

Diet and survival after prostate cancer diagnosis

Prostate cancer is the most commonly diagnosed non-skin cancer in men in the United States. Among environmental factors, diet may play a particularly important role in its incidence, progression, and clinical outcome. This article reviews the findings of eight observational studies and 17 intervention or laboratory trials on the effect of plant-based diets and plant nutrients on both the progression and clinical outcome of prostate cancer as well as additional studies examining mechanisms that may explain dietary effects. While additional long-term therapeutic clinical trials are needed to further elucidate the role of diet, these early investigations suggest that a recommendation for individual patients to shift their diets toward plant foods may serve as an important component of the tertiary treatment of prostate cancer.     

Detection of prostate cancer with multiparametric MRI utilizing the anatomic structure of the prostate

Multiparametric magnetic resonance imaging (mpMRI), which combines traditional anatomic and newer quantitative MRI methods, has been shown to result in improved voxel‐wise classification of prostate cancer as compared with any single MRI parameter. While these results are promising, substantial heterogeneity in the mpMRI parameter values and voxel‐wise prostate cancer risk has been observed both between and within regions of the prostate. This suggests that classification of prostate cancer can potentially be improved by incorporating structural information into the classifier. In this paper, we propose a novel voxel‐wise classifier of prostate cancer that accounts for the anatomic structure of the prostate by Bayesian hierarchical modeling, which can be combined with post hoc spatial Gaussian kernel smoothing to account for residual spatial correlation. Our proposed classifier results in significantly improved area under the ROC curve (0.822 vs 0.729, P < .001) and sensitivity corresponding to 90% specificity (0.599 vs 0.429, P < .001), compared with a baseline model that does not account for the anatomic structure of the prostate. Furthermore, the classifier can also be applied on voxels with missing mpMRI parameters, resulting in similar performance, which is an important practical consideration that cannot be easily accommodated using regression‐based classifiers. In addition, our classifier achieved high computational efficiency with a closed‐form solution for the posterior predictive cancer probability.     

Segregation analysis of height-adjusted weight with generation- and age-dependent effects: the Nancy Family Study.

A segregation analysis using a regressive model with generation- and age-dependent effects was applied to familial data of height-adjusted weight to investigate the major gene hypothesis. The sample included 629 nuclear families with 2,534 members volunteering for a free health check-up in the Preventive Medicine Center of Vandoeuvre-lès-Nancy, France. The familial correlations were 0.094 +/- 0.040 between spouses, 0.198 +/- 0.023 between parent and offspring, and 0.327 +/- 0.034 between siblings. The variability of the trait was higher in parents than in offspring. The most parsimonious genetic model indicated a codominant major effect increasing with age in childhood, then stabilizing in adulthood. The same data were analyzed using the classical mixed model, assuming equality of variances between parents and offspring, no resemblance between spouses, similar parent-offspring and sib-sib correlations, and identical effects in parents and offspring. This analysis indicated a recessive solution. In both analyses, mendelian transmission was rejected. However, the mixture of two distributions in the recessive model, instead of three in the codominant one, was less constraining with respect to the test of transmission probabilities, and the rejection of mendelian transmission was due to a single family in the recessive case, instead of several families in the codominant one. This could possibly explain why previous studies, all using the mixed model, found evidence for a recessive major gene. Although the major gene hypothesis cannot be definitely ruled out from our results, the mechanism appears more complex than the effect of one single gene.     

Occupational risk factors for prostate cancer

BACKGROUND: Occupational risk factors for prostate cancer have been investigated with inconsistent findings. METHODS: This was a population-based case-control study of men in Northeastern Ontario, Canada. Cases (n = 760) were from the Ontario Cancer Registry, 50 to 84 years old, and diagnosed with prostate cancer between 1995 and 1998. Age-frequency matched controls (n = 1,632) were obtained from telephone listings. A questionnaire yielded information on occupational history and self-reported exposures to a list of occupational hazards. Exposures to these hazards were assessed by an occupational hygienist. RESULTS: An odds ratio estimate (OR) of 1.21 (95 percent confidence interval (% CI) 1.01, 1.46) was found for employment in trades, transport and equipment operators and related occupations, possibly related to exposure to whole-body vibration (OR = 1.38, 95% CI 1.07, 1.78). For the highest quartile of lifetime cumulative workplace physical activity an OR of 1.33 (95% CI 1.02, 1.74) was found. No statistically significant associations were found for any other occupational category or exposure. CONCLUSIONS: This study does not provide strong evidence for significant occupational risk factors for prostate cancer. However, whole-body vibration exposures, as well as physical activity, may be worth pursuing in future occupational studies.     

Meta-analyses of prostate cancer and farming

Articles published in peer-reviewed journals between January 1983 and June 1994 were reviewed for inclusion in a meta-analysis designed to estimate the relative risk of prostate cancer in farmers. Three analyses were performed: (1) an analysis including all articles written during the specified time period that listed an estimate of the relative risk of prostate cancer in farmers; (2) an analysis that included only retrospective studies; and (3) an analysis that included only studies reporting a standardized mortality ratio. Positive associations between prostate cancer and farming were found by the analysis including all studies and the analysis limited to the retrospective studies. No association was found with the analysis that included only studies reporting a standard mortality ratio. The most plausible explanation for the positive association between prostate cancer and farming is exposure to hormonally active agricultural chemicals. Am. J. Ind. Med: 31:580–586, 1997. © 1997 Wiley-Liss, Inc.     

Segregation analysis of hereditary nonpolyposis colorectal cancer

Segregation analysis of eleven families comprising 2762 individuals indicated compatibility of the data with segregation of a major autosomal dominant gene for hereditary nonpolyposis colorectal cancer. It was estimated that between 71% and 79% of the gene carriers were susceptible and had age of onset that was normally distributed with mean about 47 and standard deviation about 10 years. There was a low frequency of sporadic cases at the older ages, a little less than four percent of nongene carriers being affected by age 80. No significant differences were found between the families exhibiting endometrial cancer (cancer family syndrome) and those not exhibiting endometrial cancer (hereditary site-specific nonpolyposis colonic cancer).     

A population model of prostate cancer incidence

Introduction of screening for prostate cancer using the prostate-specific antigen (PSA) marker of the disease led to remarkable dynamics of the incidence of the disease observed in the last two decades. A statistical model is used to provide a link between dissemination of PSA and the observed transient population responses. The model is used to estimate lead time, overdiagnosis and other relevant characteristics of prostate cancer screening.     

Regressive logistic and proportional hazards disease models for within-family analyses of measured genotypes,with application to a CYP17 polymorphism and breast cancer

Various statistical methods have been proposed to evaluate associations between measured genetic variants and disease, including some using family designs. For breast cancer and rare variants, we applied a modified segregation analysis method that uses the population cancer incidence and population-based case families in which a mutation is known to be segregating. Here we extend the method to a common polymorphism, and use a regressive logistic approach to model familial aggregation by conditioning each individual on their mother's breast cancer history. We considered three models: 1) class A regressive logistic model; 2) age-of-onset regressive logistic model; and 3) proportional hazards familial model. Maximum likelihood estimates were calculated using the software MENDEL. We applied these methods to data from the Australian Breast Cancer Family Study on the CYP17 5'UTR T-->C MspA1 polymorphism measured for 1,447 case probands, 787 controls, and 213 relatives of case probands found to have the CC genotype. Breast cancer data for first- and second-degree relatives of case probands were used. The three methods gave consistent estimates. The best-fitting model involved a recessive inheritance, with homozygotes being at an increased risk of 47% (95% CI, 28-68%). The cumulative risk of the disease up to age 70 years was estimated to be 10% or 22% for a CYP17 homozygote whose mother was unaffected or affected, respectively. This analytical approach is well-suited to the data that arise from population-based case-control-family studies, in which cases, controls and relatives are studied, and genotype is measured for some but not all subjects.     

A risk prediction algorithm based on family history and common genetic variants: application to prostate cancer with potential clinical impact

Genome wide association studies have identified several single nucleotide polymorphisms (SNPs) that are independently associated with small increments in risk of prostate cancer, opening up the possibility for using such variants in risk prediction. Using segregation analysis of population‐based samples of 4,390 families of prostate cancer patients from the UK and Australia, and assuming all familial aggregation has genetic causes, we previously found that the best model for the genetic susceptibility to prostate cancer was a mixed model of inheritance that included both a recessive major gene component and a polygenic component (P) that represents the effect of a large number of genetic variants each of small effect, where . Based on published studies of 26 SNPs that are currently known to be associated with prostate cancer, we have extended our model to incorporate these SNPs by decomposing the polygenic component into two parts: a polygenic component due to the known susceptibility SNPs, , and the residual polygenic component due to the postulated but as yet unknown genetic variants, . The resulting algorithm can be used for predicting the probability of developing prostate cancer in the future based on both SNP profiles and explicit family history information. This approach can be applied to other diseases for which population‐based family data and established risk variants exist. Genet. Epidemiol. 2011. © 2011 Wiley‐Liss, Inc. 35: 549‐556, 2011