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We propose a cost-effective sampling design and estimating procedure for validating personal risk models using right-censored cohort data. Validation involves using each subject's covariates, as ascertained at cohort entry, in a risk model (specified independently of the data) to assign him/her a probability of an adverse outcome within a future time period. Subjects are then grouped according to the magnitudes of their assigned risks, and within each group, the mean assigned risk is compared with the probability of outcome occurrence as estimated using the follow-up data. Such validation presents two complications. First, in the presence of right-censoring, estimating the probability of developing the outcomes before death requires competing risk analysis. Second, for rare outcomes, validation using the full cohort requires assembling covariates and assigning risks to thousands of subjects. This can be costly when some covariates involve analyzing biological specimens. A two-stage sampling design addresses this problem by assembling covariates and assigning risks only to those subjects most informative for estimating key parameters. We use this design to estimate the outcome probabilities needed to evaluate model performance and we provide theoretical and bootstrap estimates of their variances. We also describe how to choose two-stage designs with minimal efficiency loss for a parameter of interest when the quantities determining optimality are unknown at the time of design. We illustrate these methods by using subjects in the California Teachers Study to validate ovarian cancer risk models. We find that a design with optimal efficiency for one performance parameter need not be so for others, and trade-offs will be required. A two-stage design that samples all outcome-positive subjects and more outcome-negative than censored subjects will perform well in most circumstances. The methods are implemented in Risk Model Assessment Program, an R program freely available at http://med.stanford.edu/epidemiology/two-stage.html. [ABSTRACT FROM AUTHOR]

Background: Clinical guidelines for breast cancer chemoprevention and MRI screening involve estimates of remaining lifetime risk (RLR); in the United States, women with an RLR of 20% or higher meet "high-risk" criteria for MRI screening. Methods: We prospectively followed 1764 women without breast cancer to compare the RLRs and 10-year risks assigned by the risk models International Breast Cancer Intervention Study (IBIS) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) and to compare both sets of model-assigned 10-year risks to subsequent incidence of breast cancer in the cohort. We used chi-square statistics to assess calibration and the area under the receiver operating characteristic curve (AUC) to assess discrimination. All statistical tests are two-sided. Results: The models classified different proportions of women as high-risk (IBIS = 59.3% vs BOADICEA = 20.1%) using the RLR threshold of 20%. The difference was smaller (IBIS = 52.9% vs BOADICEA = 43.2%) using a 10-year risk threshold of 3.34%. IBIS risks (mean = 4.9%) were better calibrated to observed breast cancer incidence (5.2%, 95% confidence interval (CI) = 4.2% to 6.4%) than were those of BOADICEA (mean = 3.7%) overall and within quartiles of model risk (P = .20 by IBIS and P = .07 by BOADICEA). Both models gave similar discrimination, with AUCs of 0.67 (95% CI = 0.61 to 0.73) using IBIS and 0.68 (95% CI = 0.62 to 0.74) using BOADICEA. Model sensitivities at thresholds for a 20% false-positive rate were also similar, with 41.8% using IBIS and 38.0% using BOADICEA. Conclusion: RLR-based guidelines for high-risk women are limited by discordance between commonly used risk models. Guidelines based on short-term risks would be more useful, as models are generally developed and validated under a short fixed time horizon (≤10 years). [ABSTRACT FROM AUTHOR]

Interest in targeted disease prevention has stimulated development of models that assign risks to individuals, using their personal covariates. We need to evaluate these models and quantify the gains achieved by expanding a model to include additional covariates. This paper reviews several performance measures and shows how they are related. Examples are used to show that appropriate performance criteria for a risk model depend upon how the model is used. Application of the performance measures to risk models for hypothetical populations and for US women at risk of breast cancer illustrate two additional points. First, model performance is constrained by the distribution of risk-determining covariates in the population. This complicates the comparison of two models when applied to populations with different covariate distributions. Second, all summary performance measures obscure model features of relevance to its utility for the application at hand, such as performance in specific subgroups of the population. In particular, the precision gained by adding covariates to a model can be small overall, but large in certain subgroups. We propose new ways to identify these subgroups and to quantify how much they gain by measuring the additional covariates. Those with largest gains could be targeted for cost-efficient covariate assessment. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

After diagnosis with prostate cancer, Black men in the United States have poorer survival than White men, even after controlling for differences in cancer stage. The extent to which these racial survival differences are due to biologic versus non-biologic factors is unclear, and it has been hypothesized that differences associated with socioeconomic status (SES) might account for much of the observed survival difference. The authors examined this hypothesis in a cohort study, using cancer registry and US Census data for White and Black men with incident prostate cancer (n = 23,334) who resided in 1,005 census tracts in the San Francisco Bay Area during 1973–1993. Separate analyses were conducted using two endpoints: death from prostate cancer and death from other causes. For each endpoint, death rate ratios (Blacks vs. Whites) were computed for men diagnosed at ages <65 years and at ages ≧65 years. These data suggest that differences associated with SES do not explain why Black men die from prostate cancer at a higher rate when compared with White men with this condition. However, among men with prostate cancer, SES-associated differences appear to explain almost all of the racial difference in risk of death from other causes. Am J Epidemiol 2000;151:409–16. [ABSTRACT FROM PUBLISHER]

Objective: Chloral hydrate, used as a hypnosedative in adults and children, has been shown to be genotoxic and carcinogenic in animal studies. We investigated the potential causal association between chloral hydrate exposure and cancer risk in humans.Methods: Cancer incidence was previously determined via biennial screening analyses of the 215 most commonly used drugs between 1976 and 1998 for a cohort of 143,574 outpatients at Kaiser Permanente who had prescriptions filled between 1969 and 1973. Among users of chloral hydrate, statistically significant elevations in standardised morbidity ratios were observed during various years for cancer at five anatomical sites, including the lung, stomach, prostate, skin melanoma and mouth floor. In this analysis, these associations were investigated using: (i) a dose-response analysis among exposed subjects; and (ii) a two-stage design with exposed and non-exposed persons.Results: There was evidence of an increasing risk of prostate cancer with increasing number of dispensings of chloral hydrate, which persisted after controlling for benign prostatic hypertrophy, vasectomy and obesity; however, the trend was not statistically significant. There was no evidence of a dose-response relationship between chloral hydrate and risk of any of the other four cancers. In the two-stage design, analyses comparing exposed and unexposed subjects showed no increased risk of cancer after controlling for confounding variables; however, the data were suggestive for prostate cancer, where the increased risk associated with chloral hydrate exposure after adjustment for confounding variables persisted. No dose-response relationship was seen for any of the other four cancer sites.Conclusions: To our knowledge, this is the first study to examine the relationship between chloral hydrate exposure and cancer risk in humans. There was no persuasive evidence to support a causal relationship between chloral hydrate exposure in humans and the development of cancer. However, statistical power was low for weak associations, particularly for some of the individual cancer sites. Although animal data using much higher doses of chloral hydrate have demonstrated its genotoxicity and carcinogenicity, the effects of chloral hydrate in humans are still uncertain. [ABSTRACT FROM AUTHOR]

We consider the problem of estimating a parameter θ reflecting association between a disease and genotypes of a genetic polymorphism, using nuclear family data. In many applications, some parental genotypes are missing, and the distribution of these genotypes is unknown. Since misspecification of this distribution can bias estimators for θ, we consider estimating functions that are unbiased, regardless of how the distribution is specified. We call the resulting estimators parental‐genotype‐robust. Rabinowitz (2002) has proposed a constrained optimisation method for obtaining locally optimal unbiased tests of the null hypothesis of no association. We use a similar method to derive estimating functions that yield parental‐genotype‐robust estimators with minimum variance in the class of all such estimators. We extend the estimating functions to obtain parental‐genotype‐robust estimators when θ is a vector of unknown parameters, and show that the estimating functions enjoy a certain optimality property. [ABSTRACT FROM AUTHOR]

Examines the problem of defining the proportion of all hereditary families with multiple cases of disease that segregate mutations of a particular gene of interest. Assumptions needed for the interpretation of heterogeneity; Problems in estimating the proportion from linkage data; Conclusion.

The prevalence of chronic obstructive pulmonary disease was evaluated i 12 980 lifelong nonsmoking adults who participated in one of three National US Health and Nutrition National US Health and Nutrition Examination Surveys. Also evaluated were the relationships between chronic obstructive pulmonary disease and age, sex, ethnicity, education, income, and certain environmental and occupational factors. Overall, 4% of men and 5% of women reported physician-diagnosed chronic obstructive pulmonary disease. Prevalence increased with age and with decreasing household income, was higher in Whites than in non-Whites, and was particularly high in Hispanic women, Further research is needed to explain the excess risk for chronic obstructive pulmonary disease in economically disadvantaged nonsmokers, and to assess the role of environmental tobacco smoke in nonsmokers' risk for the disease. [ABSTRACT FROM AUTHOR]

Presents a study which was conducted to test the hypothesis that black men and white men with prostate cancer have equal stage-specific survival in health care systems. Use of cancer registry data from all cases of prostate cancer in a San Francisco Bay Area region; Comparison of stage-specific survival in black and white men; Analysis of racial differences in the the use of therapies for prostate cancer.

Examines the differences in the incidence of prostate cancer in the Japanese American men in the United States. Environmental risk factors of the disease; Prostate-specific antigen levels determined in community-based samples of serum from men without prostate cancer; Estimated number of Japanese-Americans with.

Assesses the association of vasectomy with increased prostate cancer risk on the basis of data collected in a large multiethnic case-control study of prostate cancer that was conducted in the United States and Canada. Finding that a history of vasectomy was not significantly associated with prostate cancer risk among all racial/ethnic groups combined.

Reports on a population-based case-control study of prostate cancer among blacks, whites, and Asian-Americans in Los Angeles, San Francisco, Hawaii, Vancouver and Toronto. Goal of evaluating the roles of diet, physical activity patterns, body size, and migration characteristics on risk in ethnic groups.

Evaluates age-specific serum concentrations of prostate-specific antigen (PSA) in three to six serial serum samples each from samples of black men and white men. Differences in PSA concentrations; Use of a nested case-control design.

Describes a way to test the covariance structure of a multivariate distribution parameterized by a vector. Application of quadratic extensions and quadratic score statistics to censored data; Use of quadratic score statistics to evaluate genetic models for family disease data; Result of the simulation data done to examine the tests' performance.

Examines the relationship of survival among breast-cancer patients to the time since diagnosis and to the stage of the disease at diagnosis. Description of the data; Analysis; Exponential model using Expectation-Maximization (EM) algorithm for estimation of test for model fit; Results of the analysis using EM algorithm; Simulations; Convergence results; Conclusions.

The effect of covariate measurement error on maximum likelihood and maximum quasilikelihood estimates (MLE's or MQLE's) of regression parameters is considered. The naive estimates, obtained by ignoring error, are modified to account for it. The modified estimates can be computed explicitly from the naive ones, and have less bias for small error. They are particularly useful for Berkson error models. Examples illustrate their application to linear and nonlinear regression, errors in continuous covariates, and misclassification of discrete covariates. The estimates are applied to data relating air pollution to respiratory disease in children. Analytic methods and simulations are used to compare the estimates to others that have been proposed for dealing with covariate measurement errors. The basic idea is that the MLE or MQLE of the parameter θ is a function θ(δ) of the size δ of the error. When δ = 0 and there is no error, θ(0) is the usual MLE or MQLE. For δ small, an improvement over θ(0) is θ[sup *] = θ(0) + δ part θ(0)/part δ. In many cases of practical interest θ[sup *] can be computed in terms of the mean and variance of the error conditional on the erroneously observed covariates. These conditional moments may be available for Berkson error models. The advantage of using θ[sup *] is that it has less bias than 0(0). Furthermore, its use does not require either knowledge of the error distribution or solution of the likelihood or quasilikelihood equations, both of which are necessary to find θ(δ). Its disadvantage is that it loses accuracy as δ becomes large. In addition, for structural error models its use requires knowledge of the covariate distribution. [ABSTRACT FROM AUTHOR]

The Fisher information matrix for the estimated parameters in a multiple logistic regression can be approximated by the augmented Hessian matrix of the moment-generating function for the covariates. The approximation is valid when the probability of response is small. With its use one can obtain a simple closed-form estimate of the asymptotic covariance matrix of the maximum likelihood parameter estimates, and thus approximate sample sizes needed to test hypotheses about the parameters. The method is developed for selected distributions of a single covariate and for a class of exponential-type distributions of several covariates. It is illustrated with an example concerning risk factors for coronary heart disease. [ABSTRACT FROM AUTHOR]

Abstract: Daily asthma attack diaries of 16 panels of asthmatics residing in the Los Angeles area were collected by the Environmental Protection Agency for 34-week periods during the years 1972-1975. These date are examined here for the relationship between daily attack occurrence and daily levels of photochemical oxidant. Total suspended particulates, minimum temperature, relative humidity, and average wind speed. A separate multiple logistic regression is used for each panelist's attack data. Variables representing the presence or absence of attack on the preceding day, as well as day of week and time since the start of the study, are included in the regressions. The most significant predictor of attacks was the presence of an attack on the preceding day. On the average, the panelists tended to have increased attacks on days with high oxidant and particulate pollution on cool days, and during the first two months of the study. Panelists' attack propensity also differed by day of week in particular they had more attacks on Saturdays (the last day of the weekly reporting period) than on Sundays. Each panelist's regression coefficients are classified according to age, sex, hay fever status, and self-assessed attack precursors: this classification is used to examine subgroups among the panelists with high co-efficients corresponding to the above factors. (Am J Public Health 1980: 70:687-696.) [ABSTRACT FROM AUTHOR]

The article presents an editorial looking at the prevention and early diagnosis of hereditary colorectal cancer. Lynch syndrome, or hereditary nonpolyposis colorectal cancer, is caused by germline mutations in the mismatch DNA repair genes MLH1, MSH2, MSH6, and PMS2. While the authors see genetic testing and counseling as appropriate for at-risk individuals, they state that genetic testing for mismatch repair gene mutations is costly and not super sensitive. Two studies published in this issue, including "Prediction of MLH1 and MSH2 mutations in Lynch syndrome," by J. Balmaña, et al. and "Prediction of germline mutations and cancer risk in the Lynch syndrome," by S. Chen, et al., are examined. The article discusses genetic algorithms.

Background: Independent validation is essential to justify use of models of breast cancer risk prediction and inform decisions about prevention options and screening. Few independent validations had been done using cohorts for common breast cancer risk prediction models, and those that have been done had small sample sizes and short follow-up periods, and used earlier versions of the prediction tools. We aimed to validate the relative performance of four commonly used models of breast cancer risk and assess the effect of limited data input on each one's performance.Methods: In this validation study, we used the Breast Cancer Prospective Family Study Cohort (ProF-SC), which includes 18 856 women from Australia, Canada, and the USA who did not have breast cancer at recruitment, between March 17, 1992, and June 29, 2011. We selected women from the cohort who were 20-70 years old and had no previous history of bilateral prophylactic mastectomy or ovarian cancer, at least 2 months of follow-up data, and information available about family history of breast cancer. We used this selected cohort to calculate 10-year risk scores and compare four models of breast cancer risk prediction: the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm model (BOADICEA), BRCAPRO, the Breast Cancer Risk Assessment Tool (BCRAT), and the International Breast Cancer Intervention Study model (IBIS). We compared model calibration based on the ratio of the expected number of breast cancer cases to the observed number of breast cancer cases in the cohort, and on the basis of their discriminatory ability to separate those who will and will not have breast cancer diagnosed within 10 years as measured with the concordance statistic (C-statistic). We did subgroup analyses to compare the performance of the models at 10 years in BRCA1 or BRCA2 mutation carriers (ie, BRCA-positive women), tested non-carriers and untested participants (ie, BRCA-negative women), and participants younger than 50 years at recruitment. We also assessed the effect that limited data input (eg, restriction of the amount of family history and non-genetic information included) had on the models' performance.Findings: After median follow-up of 11·1 years (IQR 6·0-14·4), 619 (4%) of 15 732 women selected from the ProF-SC cohort study were prospectively diagnosed with breast cancer after recruitment, of whom 519 (84%) had histologically confirmed disease. BOADICEA and IBIS were well calibrated in the overall validation cohort, whereas BRCAPRO and BCRAT underpredicted risk (ratio of expected cases to observed cases 1·05 [95% CI 0·97-1·14] for BOADICEA, 1·03 [0·96-1·12] for IBIS, 0·59 [0·55-0·64] for BRCAPRO, and 0·79 [0·73-0·85] for BRCAT). The estimated C-statistics for the complete validation cohort were 0·70 (95% CI 0·68-0·72) for BOADICEA, 0·71 (0·69-0·73) for IBIS, 0·68 (0·65-0·70) for BRCAPRO, and 0·60 (0·58-0·62) for BCRAT. In subgroup analyses by BRCA mutation status, the ratio of expected to observed cases for BRCA-negative women was 1·02 (95% CI 0·93-1·12) for BOADICEA, 1·00 (0·92-1·10) for IBIS, 0·53 (0·49-0·58) for BRCAPRO, and 0·97 (0·89-1·06) for BCRAT. For BRCA-positive participants, BOADICEA and IBIS were well calibrated, but BRCAPRO underpredicted risk (ratio of expected to observed cases 1·17 [95% CI 0·99-1·38] for BOADICEA, 1·14 [0·96-1·35] for IBIS, and 0·80 [0·68-0·95] for BRCAPRO). We noted similar patterns of calibration for women younger than 50 years at recruitment. Finally, BOADICEA and IBIS predictive scores were not appreciably affected by limiting input data to family history for first-degree and second-degree relatives.Interpretation: Our results suggest that models that include multigenerational family history, such as BOADICEA and IBIS, have better ability to predict breast cancer risk, even for women at average or below-average risk of breast cancer. Although BOADICEA and IBIS performed similarly, further improvements in the accuracy of predictions could be possible with hybrid models that incorporate the polygenic risk component of BOADICEA and the non-family-history risk factors included in IBIS.Funding: US National Institutes of Health, National Cancer Institute, Breast Cancer Research Foundation, Australian National Health and Medical Research Council, Victorian Health Promotion Foundation, Victorian Breast Cancer Research Consortium, Cancer Australia, National Breast Cancer Foundation, Queensland Cancer Fund, Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and Cancer Foundation of Western Australia. [ABSTRACT FROM AUTHOR]

Compares the trends of prostate cancer incidence and mortality rate among men in the U.S. and Great Britain. Treatment of the early-stage prostate cancer; Use of prostate-specific antigen; Improvement of the treatment.

Background: Clinical guidelines for breast cancer chemoprevention and MRI screening involve estimates of remaining lifetime risk (RLR); in the United States, women with an RLR of 20% or higher meet "high-risk" criteria for MRI screening.Methods: We prospectively followed 1764 women without breast cancer to compare the RLRs and 10-year risks assigned by the risk models International Breast Cancer Intervention Study (IBIS) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) and to compare both sets of model-assigned 10-year risks to subsequent incidence of breast cancer in the cohort. We used chi-square statistics to assess calibration and the area under the receiver operating characteristic curve (AUC) to assess discrimination. All statistical tests are two-sided.Results: The models classified different proportions of women as high-risk (IBIS = 59.3% vs BOADICEA = 20.1%) using the RLR threshold of 20%. The difference was smaller (IBIS = 52.9% vs BOADICEA = 43.2%) using a 10-year risk threshold of 3.34%. IBIS risks (mean = 4.9%) were better calibrated to observed breast cancer incidence (5.2%, 95% confidence interval (CI) = 4.2% to 6.4%) than were those of BOADICEA (mean = 3.7%) overall and within quartiles of model risk (P = .20 by IBIS and P = .07 by BOADICEA). Both models gave similar discrimination, with AUCs of 0.67 (95% CI = 0.61 to 0.73) using IBIS and 0.68 (95% CI = 0.62 to 0.74) using BOADICEA. Model sensitivities at thresholds for a 20% false-positive rate were also similar, with 41.8% using IBIS and 38.0% using BOADICEA.Conclusion: RLR-based guidelines for high-risk women are limited by discordance between commonly used risk models. Guidelines based on short-term risks would be more useful, as models are generally developed and validated under a short fixed time horizon (≤10 years). [ABSTRACT FROM AUTHOR]

Background: The immune system has been implicated in the pathophysiology of cutaneous squamous cell carcinoma (cSCC) as evidenced by the substantially increased risk of cSCC in immunosuppressed individuals. Associations between cSCC risk and single nucleotide polymorphisms (SNPs) in the HLA region have been identified by genome-wide association studies (GWAS). The translation of the associated HLA SNPs to structural amino acids changes in HLA molecules has not been previously elucidated.Methods: Using data from a GWAS that included 7238 cSCC cases and 56,961 controls of non-Hispanic white ancestry, we imputed classical alleles and corresponding amino acid changes in HLA genes. Logistic regression models were used to examine associations between cSCC risk and genotyped or imputed SNPs, classical HLA alleles, and amino acid changes.Results: Among the genotyped SNPs, cSCC risk was associated with rs28535317 (OR = 1.20, p = 9.88 × 10− 11) corresponding to an amino-acid change from phenylalanine to leucine at codon 26 of HLA-DRB1 (OR = 1.17, p = 2.48 × 10− 10). An additional independent association was observed for a threonine to isoleucine change at codon 107 of HLA-DQA1 (OR = 1.14, p = 2.34 × 10− 9). Among the classical HLA alleles, cSCC was associated with DRB1*01 (OR = 1.18, p = 5.86 × 10− 10). Conditional analyses revealed additional independent cSCC associations with DQA1*05:01 and DQA1*05:05. Extended haplotype analysis was used to complement the imputed haplotypes, which identified three extended haplotypes in the HLA-DR and HLA-DQ regions.Conclusions: Associations with specific HLA-DR and -DQ alleles are likely to explain previously observed GWAS signals in the HLA region associated with cSCC risk. [ABSTRACT FROM AUTHOR]

Corrections to articles "Logistic regression for autocorrelated data with application to repeated measures," by A. Azzalini in the 1994 issue and "Logistic regression of family data from case-control studies," by Alice S. Whittemore in the 1995 issue are presented.

Studies the possible link between ovulation, p53 and ovarian cancer. Inducing effect of ovulation on mitotic activity in the ovarian epithelium; Development of cancer expressing p53 mutant among women with many ovulatory cycles; Common types of p53 mutations.

Children from households served by the contaminated wells had significantly greater leukemia rates than did children from other households. The article does not tell much about the consistency of the leukemia-drinking water association in relation to other epidemiological studies. It is provocative that unexplained clusters of childhood leukemias have been found in many parts of the world. There is biological plausibility to associations between ingested carcinogens and any one of the malignancies collectively called leukemia. The theory that stem cells become malignant after withstanding damage to the genome caused by chemical binding to cellular macromolecules has received ample support from experimental and observational data. The coherence of the drinking water-leukemia association measures its agreement with other facts known about leukemias, including their natural history. There is good evidence that in utero exposure to ionizing radiation causes leukemia during childhood. This fact suggests that prenatal exposures to other carcinogens can cause leukemia and, therefore, it supports the present association. Also supportive of causality is the increased risk for leukemia among those with Down's syndrome, since the Woburn study also found an association between the well water and birth defect.

Presents a letter to the editor referencing articles and topics on the differences in screening implementation among women with late-stage and early-stage breast cancer, published in previous issues.

Presents a class of likelihood-based score statistics that accommodate genotypes of both unrelated individuals and families. Approach in detecting a disease gene; Application of the components of score statistics; Comparison of nonfounder anf founder statistics; Limitation of the approach.

Examines the association and linkage tests in unobserved disease alleles. Alternative genomewide linkage scans for the detection of small-effect genes in complex diseases; Effects of different allele frequencies on association tests; Use of statistical techniques to compare significant results.

A letter to the editor is presented in response to the article "The Risk of Cancer Associated with Specific Mutations of BRCA1 and BRCA2 among Ashkenazi Jews," by Jeffrey P. Struewing, Patricia Hartge, Sholom Wacholder, Sonya M. Baker, Martha Berlin, Mary McAdams, Michelle M. Timmerman, Lawrence C. Brody, and Margaret A. Tucker and "Differential Contributions of BRCA1 and BRCA2 to Early-Onset Breast Cancer," by Michael Krainer, Sandra Silva-Arrieta, Michael G. Fitzgerald, Akira Shimada, Chikashi Ishioka, Ryunosuke Kanamaru, Deborah J. MacDonald, Hilal Unsal, Dianne M. Finkelstein, Anne Bowcock, Kurt J. Isselbacher, and Daniel A. Haber in the May 15, 1997 issue.

Editorial. Comments on an article by Rossing, et al, in the September 22, 1994 issue of the `New England Journal of Medicine,' dealing with the question of whether there is a causal link between fertility medications and ovarian cancer.

BACKGROUND The contribution of family history to cutaneous squamous cell carcinoma (SCC) risk has not been systematically quantified. OBJECTIVE To examine the association between self-reported family history of skin cancer and SCC risk. METHODS AND MATERIALS Cases (n = 415) with a pathology-verified SCC and 415 age-, gender-, and racematched controls were identified within a large integrated health care delivery system. Family history and skin cancer risk factors were ascertained by survey. Odds ratios (ORs) for associations of SCC with family history of skin cancer were estimated using conditional logistic regression adjusted for environmental and innate SCC risk factors. RESULTS Any known family history of skin cancer was associated with a four-fold higher risk of SCC, adjusting for known environmental and innate SCC risk factors (OR, 4.0; confidence interval [CI]: 2.5-6.5). An unknown family history of skin cancer showed similar risk for SCC (OR, 3.9; CI: 2.4-6.5). In models including skin cancer type, the strongest association was for family history of basal cell carcinoma (OR, 9.8; CI: 2.6-36.8) and for multiple skin cancer types (OR, 10.5; CI: 3.7-29.6). CONCLUSION Family history of skin cancer is an important independent risk factor for cutaneous SCCs. [ABSTRACT FROM AUTHOR]

The digital SNP method has been proposed for identifying loss of heterozygosity (LOH) in tumour tissue and correlating it with patients' clinical characteristics. The method evaluates a tumour's allelic count at a single nucleotide polymorphism (SNP) for which the patient's normal tissue is heterozygous. The count is used to classify the tumour as positive or negative for LOH, using the sequential probability ratio test (SPRT). However, the SPRT was not developed for analysing digital SNP experiments. When applied to digital SNP data, the SPRT has several anomalies that can result in both loss of data and tumour misclassification. The anomalies are caused by discrepancies between the design of digital SNP experiments and the setting for which SPRT was developed. We propose an alternative classification scheme based on the false discovery rate, and show that it outperforms the SPRT when applied to Digital SNP data. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Using a cross-sectional, exploratory design, this pilot study analyzed the relationships between familial history of breast cancer and psychological distress in order to evaluate who is more distressed and to assess the possible need for intervention. Coping style, social support, and family relations were investigated as potential moderators of these relationships. Participants were 45 women with a familial history of breast cancer recruited from the Family Registry for Breast Cancer (FRBC) at the Northern California Cancer Center (NCCC). Contrary to previous reports of similar cohorts, the overall level of psychological distress in this cohort was comparable to normative samples. The number of relatives with breast cancer was related to distress as measured by the State-Trait Anxiety Inventory (STAI) scale, but there was no significant differentiation in distress associated with the number of first-degree as compared to second- and third-degree relatives with breast cancer. Having more relatives that had died from breast cancer was associated with greater distress on a number of measures. The number of first-degree relative deaths, including maternal death, was also associated with distress. Positive and network support, disengagement coping responses, and family cohesion were each significant moderators of the impact of family history on distress. This association between distress and disengagement is similar to that found in metastatic breast cancer patients themselves, and the findings suggest a subgroup that merits and might respond to more intensive intervention to provide support and facilitate emotional expression. [ABSTRACT FROM AUTHOR]

Abstract: Many families with multiple cases of ovarian cancer, breast cancer, or both segregate inherited mutations in one allele of the tumor suppressor gene BRCA1. Genetic testing is used to assess cancer risk; however, testing can detect missense DNA alterations, called unclassified variants, of unknown functional and biological significance with uncertain risk implications. Some missense variants at the transcriptional activation domain of BRCA1 of cancer patients inactivate transcriptional activity of BRCA1, providing evidence that they are deleterious. We identified the variants V1804D and M1628T at the transcriptional activation domain of BRCA1 of two ovarian cancer patients without a family history of ovarian or breast cancer. To test if these residues are critical for transcriptional activation, we created V1804D and M1628T independently in BRCA1 cDNA via site-directed mutagenesis in a mammalian expression vector, pcDNA3.1. Wild-type, mutant, and empty vector constructs were tested in human kidney 293 cells using a p53-responsive luciferase reporter. M1628T had the same transcriptional activity as wild-type BRCA1 but V1804D and the empty vector control showed a 60% reduction. This indicates that V1804D is deleterious but M1628T is not. [Copyright &y& Elsevier]

Objective. Invasive epithelial ovarian cancer is a highly fatal disease, diagnosed at advanced stages when survival is poor. Relatively little is known about the variation in survival across U.S. women of different race/ethnicities. To investigate this issue, we evaluated pathological characteristics and death rates due to invasive epithelial ovarian cancer in a population-based sample of patients from six racial/ethnic groups.Methods. The analysis included 38,012 women diagnosed with primary invasive epithelial ovarian cancer between 1973 and 1997 in the Surveillance, Epidemiology and End Results Program of the National Cancer Institute.Results. Filipina patients were younger at diagnosis, more likely to have localized disease, and had more mucinous cancers than whites. African-Americans were more likely than whites to be diagnosed at older ages, with distant disease and with undifferentiated/unclassified cancers. After adjusting for age at diagnosis, stage of disease at diagnosis, and cancer histology, we found that, compared to whites, death rates were significantly elevated among African-Americans and significantly reduced among Hispanics and Filipina. We also found that death rates declined significantly with time since diagnosis among women with advanced disease.Conclusion. The declining death rates in women with advanced disease suggest the presence of considerable prognostic heterogeneity among these women, which could reflect differences in quality of care. This issue, as well as the survival disadvantage for African-American women and survival advantages for Hispanic and Filipina women, needs investigation. [Copyright &y& Elsevier]

Background: Clinical guidelines often use predicted lifetime risk from birth to define criteria for making decisions regarding breast cancer screening rather than thresholds based on absolute 5-year risk from current age.Methods: We used the Prospective Family Cohort Study of 14 657 women without breast cancer at baseline in which, during a median follow-up of 10 years, 482 women were diagnosed with invasive breast cancer. We examined the performances of the International Breast Cancer Intervention Study (IBIS) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk models when using the alternative thresholds by comparing predictions based on 5-year risk with those based on lifetime risk from birth and remaining lifetime risk. All statistical tests were 2-sided.Results: Using IBIS, the areas under the receiver-operating characteristic curves were 0.66 (95% confidence interval = 0.63 to 0.68) and 0.56 (95% confidence interval = 0.54 to 0.59) for 5-year and lifetime risks, respectively (Pdiff < .001). For equivalent sensitivities, the 5-year incidence almost always had higher specificities than lifetime risk from birth. For women aged 20-39 years, 5-year risk performed better than lifetime risk from birth. For women aged 40 years or older, receiver-operating characteristic curves were similar for 5-year and lifetime IBIS risk from birth. Classifications based on remaining lifetime risk were inferior to 5-year risk estimates. Results were similar using BOADICEA.Conclusions: Our analysis shows that risk stratification using clinical models will likely be more accurate when based on predicted 5-year risk compared with risks based on predicted lifetime and remaining lifetime, particularly for women aged 20-39 years. [ABSTRACT FROM AUTHOR]

Family history of prostate cancer (PCa) is a well-known risk factor, and both common and rare genetic variants are associated with the disease. To detect new genetic variants associated with PCa, capitalizing on the role of family history and more aggressive PCa. A two-stage design was used. In stage one, whole-exome sequencing was used to identify potential risk alleles among affected men with a strong family history of disease or with more aggressive disease (491 cases and 429 controls). Aggressive disease was based on a sum of scores for Gleason score, node status, metastasis, tumor stage, prostate-specific antigen at diagnosis, systemic recurrence, and time to PCa death. Genes identified in stage one were screened in stage two using a custom-capture design in an independent set of 2917 cases and 1899 controls. Frequencies of genetic variants (singly or jointly in a gene) were compared between cases and controls. Eleven genes previously reported to be associated with PCa were detected (ATM , BRCA2 , HOXB13 , FAM111A , EMSY, HNF1B, KLK3, MSMB , PCAT1 , PRSS3 , and TERT), as well as an additional 10 novel genes (PABPC1 , QK1 , FAM114A1 , MUC6 , MYCBP2 , RAPGEF4 , RNASEH2B , ULK4 , XPO7 , and THAP3). Of these 10 novel genes, all but PABPC1 and ULK4 were primarily associated with the risk of aggressive PCa. Our approach demonstrates the advantage of gene sequencing in the search for genetic variants associated with PCa and the benefits of sampling patients with a strong family history of disease or an aggressive form of disease. Multiple genes are associated with prostate cancer (PCa) among men with a strong family history of this disease or among men with an aggressive form of PCa. Family history of prostate cancer (PCa) is a well-known risk factor. By capitalizing on affected men with a strong family history of disease or with more aggressive disease, we identified 10 novel genes, with eight of these primarily associated with aggressive PCa. [ABSTRACT FROM AUTHOR]

Background: Parity is associated with decreased risk of invasive ovarian cancer; however, the relationship between incomplete pregnancies and invasive ovarian cancer risk is unclear. This relationship was examined using 15 case-control studies from the Ovarian Cancer Association Consortium (OCAC). Histotype-specific associations, which have not been examined previously with large sample sizes, were also evaluated.Methods: A pooled analysis of 10 470 invasive epithelial ovarian cancer cases and 16 942 controls was conducted. Odds ratios (ORs) and 95% confidence intervals (CIs) for the association between incomplete pregnancies and invasive epithelial ovarian cancer were estimated using logistic regression. All models were conditioned on OCAC study, race and ethnicity, age, and education level and adjusted for number of complete pregnancies, oral contraceptive use, and history of breastfeeding. The same approach was used for histotype-specific analyses.Results: Ever having an incomplete pregnancy was associated with a 16% reduction in ovarian cancer risk (OR = 0.84, 95% CI = 0.79 to 0.89). There was a trend of decreasing risk with increasing number of incomplete pregnancies (2-sided Ptrend < .001). An inverse association was observed for all major histotypes; it was strongest for clear cell ovarian cancer.Conclusions: Incomplete pregnancies are associated with a reduced risk of invasive epithelial ovarian cancer. Pregnancy, including incomplete pregnancy, was associated with a greater reduction in risk of clear cell ovarian cancer, but the result was broadly consistent across histotypes. Future work should focus on understanding the mechanisms underlying this reduced risk. [ABSTRACT FROM AUTHOR]

The performance of breast cancer risk models for women with a family history but negative BRCA1 and/or BRCA2 mutation test results is uncertain. We calculated the cumulative 10-year invasive breast cancer risk at cohort entry for 14 657 unaffected women (96.1% had an affected relative) not known to carry BRCA1 or BRCA2 mutations at baseline using three pedigree-based models (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, BRCAPRO, and International Breast Cancer Intervention Study). During follow-up, 482 women were diagnosed with invasive breast cancer. Mutation testing was conducted independent of incident cancers. All models underpredicted risk by 26.3%-56.7% for women who tested negative but whose relatives had not been tested (n = 1363; 63 breast cancers). Although replication studies with larger sample sizes are needed, until these models are recalibrated for women who test negative and have no relatives tested, caution should be used when considering changing the breast cancer risk management intensity of such women based on risk estimates from these models. [ABSTRACT FROM AUTHOR]

Editorial. Compares the experiment conducted by Mukherjee and others addressing the relationship between fat and energy intakes and prostate cancer. Ways which energy intakes were restricted; Implications; Conclusions.

Genome-wide sequencing enables evaluation of associations between traits and combinations of variants in genes and pathways. But such evaluation requires multi-locus association tests with good power, regardless of the variant and trait characteristics. And since analyzing families may yield more power than analyzing unrelated individuals, we need multi-locus tests applicable to both related and unrelated individuals. Here we describe such tests, and we introduce SKAT-X, a new test statistic that uses genome-wide data obtained from related or unrelated subjects to optimize power for the specific data at hand. Simulations show that: a) SKAT-X performs well regardless of variant and trait characteristics; and b) for binary traits, analyzing affected relatives brings more power than analyzing unrelated individuals, consistent with previous findings for single-locus tests. We illustrate the methods by application to rare unclassified missense variants in the tumor suppressor gene BRCA2, as applied to combined data from prostate cancer families and unrelated prostate cancer cases and controls in the Multi-ethnic Cohort (MEC). The methods can be implemented using open-source code for public use as the R-package GATARS (Genetic Association Tests for Arbitrarily Related Subjects) . [ABSTRACT FROM AUTHOR]

Breast density is a modifiable factor that is strongly associated with breast cancer risk. We sought to understand the influence of newer technologies of full-field digital mammography (FFDM) on breast density research and to determine whether results are comparable across studies using FFDM and previous studies using traditional film-screen mammography. We studied 24,840 screening-age (40–74 years) non-Hispanic white women who were participants in the Research Program on Genes, Environment and Health of Kaiser Permanente Northern California and underwent screening mammography with either Hologic (Hologic, Inc. Marlborough, Massachusetts) or General Electric (General Electric Company, Boston, Massachusetts) FFDM machines between 2003 and 2013. We estimated the associations of parity, age at first birth, age at menarche, and menopausal status with percent density and dense area as measured by a single radiological technologist using Cumulus software (Canto Software, Inc. San Francisco, California). We found that associations between reproductive factors and mammographic density measured using processed FFDM images were generally similar in magnitude and direction to those from prior studies using film mammography. Estimated associations for both types of FFDM machines were in the same direction. There was some evidence of heterogeneity in the magnitude of the effect sizes by machine type, which we accounted for using random-effects meta-analysis when combining results. Our findings demonstrate the robustness of quantitative mammographic density measurements across FFDM and film mammography platforms. [ABSTRACT FROM AUTHOR]

Personal predictive models for disease development play important roles in chronic disease prevention. The performance of these models is evaluated by applying them to the baseline covariates of participants in external cohort studies, with model predictions compared to subjects' subsequent disease incidence. However, the covariate distribution among participants in a validation cohort may differ from that of the population for which the model will be used. Since estimates of predictive model performance depend on the distribution of covariates among the subjects to which it is applied, such differences can cause misleading estimates of model performance in the target population. We propose a method for addressing this problem by weighting the cohort subjects to make their covariate distribution better match that of the target population. Simulations show that the method provides accurate estimates of model performance in the target population, while un-weighted estimates may not. We illustrate the method by applying it to evaluate an ovarian cancer prediction model targeted to US women, using cohort data from participants in the California Teachers Study. The methods can be implemented using open-source code for public use as the R-package RMAP (Risk Model Assessment Package) available at http://stanford.edu/~ggong/rmap/ . [ABSTRACT FROM AUTHOR]

Background: Metabolomics is emerging as an important tool for detecting differences between diseased and non-diseased individuals. However, prospective studies are limited.Methods: We examined the detectability, reliability, and distribution of metabolites measured in pre-diagnostic plasma samples in a pilot study of women enrolled in the Northern California site of the Breast Cancer Family Registry. The study included 45 cases diagnosed with breast cancer at least one year after the blood draw, and 45 controls. Controls were matched on age (within 5 years), family status, BRCA status, and menopausal status. Duplicate samples were included for reliability assessment. We used a liquid chromatography/gas chromatography mass spectrometer platform to measure metabolites. We calculated intraclass correlations (ICCs) among duplicate samples, and coefficients of variation (CVs) across metabolites.Results: Of the 661 named metabolites detected, 338 (51%) were found in all samples, and 490 (74%) in more than 80% of samples. The median ICC between duplicates was 0.96 (25th - 75th percentile: 0.82-0.99). We observed a greater than 20% case-control difference in 24 metabolites (p < 0.05), although these associations were not significant after adjusting for multiple comparisons.Conclusions: These data show that assays are reproducible for many metabolites, there is a minimal laboratory variation for the same sample, and a large between-person variation. Despite small sample size, differences between cases and controls in some metabolites suggest that a well-powered large-scale study is likely to detect biological meaningful differences to provide a better understanding of breast cancer etiology. [ABSTRACT FROM AUTHOR]

Background: Clustering of breast and colorectal cancer has been observed within some families and cannot be explained by chance or known high-risk mutations in major susceptibility genes. Potential shared genetic susceptibility between breast and colorectal cancer, not explained by high-penetrance genes, has been postulated. We hypothesized that yet undiscovered genetic variants predispose to a breast-colorectal cancer phenotype. Methods: To identify variants associated with a breast-colorectal cancer phenotype, we analyzed genome-wide association study (GWAS) data from cases and controls that met the following criteria: cases (n = 985) were women with breast cancer who had one or more first- or second-degree relatives with colorectal cancer, men/women with colorectal cancer who had one or more first- or second-degree relatives with breast cancer, and women diagnosed with both breast and colorectal cancer. Controls (n = 1769), were unrelated, breast and colorectal cancer-free, and age- and sex- frequency-matched to cases. After imputation, 6,220,060 variants were analyzed using the discovery set and variants associated with the breast-colorectal cancer phenotype at P<5.0E-04 (n = 549, at 60 loci) were analyzed for replication (n = 293 cases and 2,103 controls). Results: Multiple correlated SNPs in intron 1 of the ROBO1 gene were suggestively associated with the breast-colorectal cancer phenotype in the discovery and replication data (most significant; rs7430339, Pdiscovery = 1.2E-04; rs7429100, Preplication = 2.8E-03). In meta-analysis of the discovery and replication data, the most significant association remained at rs7429100 (P = 1.84E-06). Conclusion: The results of this exploratory analysis did not find clear evidence for a susceptibility locus with a pleiotropic effect on hereditary breast and colorectal cancer risk, although the suggestive association of genetic variation in the region of ROBO1, a potential tumor suppressor gene, merits further investigation. [ABSTRACT FROM AUTHOR]

Motivation: Interpreting genetic variation in noncoding regions of the genome is an important challenge for personal genome analysis. One mechanism by which noncoding single nucleotide variants (SNVs) influence downstream phenotypes is through the regulation of gene expression. Methods to predict whether or not individual SNVs are likely to regulate gene expression would aid interpretation of variants of unknown significance identified in whole-genome sequencing studies. Results: We developed FIRE (Functional Inference of Regulators of Expression), a tool to score both noncoding and coding SNVs based on their potential to regulate the expression levels of nearby genes. FIRE consists of 23 random forests trained to recognize SNVs in cis-expression quantitative trait loci (cis-eQTLs) using a set of 92 genomic annotations as predictive features. FIRE scores discriminate cis-eQTL SNVs from non-eQTL SNVs in the training set with a cross-validated area under the receiver operating characteristic curve (AUC) of 0.807, and discriminate cis-eQTL SNVs shared across six populations of different ancestry from non-eQTL SNVs with an AUC of 0.939. FIRE scores are also predictive of cis-eQTL SNVs across a variety of tissue types. [ABSTRACT FROM AUTHOR]

Cutaneous squamous cell carcinoma (cSCC) is the second most common cancer among Caucasians in the United States, with rising incidence over the past decade. Treatment for non-melanoma skin cancer, including cSCC, in the United States was estimated to cost $4.8 billion in 2014. Thus, an understanding of cSCC pathogenesis could have important public health implications. Immune function impacts cSCC risk, given that cSCC incidence rates are substantially higher in patients with compromised immune systems. We report a systematic review of published associations between cSCC risk and the human leukocyte antigen (HLA) system. This review includes studies that analyze germline class I and class II HLA allelic variation as well as HLA cell-surface protein expression levels associated with cSCC risk. We propose biological mechanisms for these HLA-cSCC associations based on known mechanisms of HLA involvement in other diseases. The review suggests that immunity regulates the development of cSCC and that HLA-cSCC associations differ between immunocompetent and immunosuppressed patients. This difference may reflect the presence of viral co-factors that affect tumorigenesis in immunosuppressed patients. Finally, we highlight limitations in the literature on HLA-cSCC associations, and suggest directions for future research aimed at understanding, preventing and treating cSCC. [ABSTRACT FROM AUTHOR]

The benefits of radiotherapy for inoperable biliary tract cancer remain unclear due to the lack of randomized data. We evaluated the impact of radiotherapy on survival in elderly patients using the SEER-Medicare database. Patients in the SEER-Medicare database with inoperable biliary tract tumors diagnosed between 1998 and 2011 were included. We used multivariate logistic regression to evaluate factors associated with treatment selection, and multivariate Cox regression and propensity score matching to evaluate treatment selection in relation to subsequent survival. Of the 2343 patients included, 451 (19%) received radiotherapy within 4 months of diagnosis. The use of radiotherapy declined over time, and was influenced by receipt of chemotherapy and patient age, race, marital status, poverty status, and tumor stage and type. Median survival was 9.3 (95% CI 8.7-9.7) months among patients who did not receive radiation and 10.0 (95% CI 9.1-11.3) months among those who received radiation, conditional on having survived 4 months. In patients who received chemotherapy ( n = 1053), receipt of radiation was associated with improved survival, with an adjusted hazard ratio of 0.82 (95% 0.70-0.97, P = 0.02). In patients who did not receive chemotherapy ( n = 1290), receipt of radiation was not associated with improved survival, with an adjusted hazard ratio of 1.09 (95% 0.91-1.30, P = 0.34). Propensity-scored matched analyses showed similar results. Despite the survival benefit associated with the addition of radiotherapy to chemotherapy, the use of radiation for unresectable biliary tract cancers has declined over time. [ABSTRACT FROM AUTHOR]