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Background It is unclear whether genetic variants affecting vitamin D metabolism are associated with melanoma prognosis. Two functional missense variants in the vitamin D–binding protein gene (GC), rs7041 and rs4588, determine 3 common haplotypes, Gc1s, Gc1f, and Gc2, of which Gc1f may be associated with decreased all-cause death among melanoma patients based on results of a prior study, but the association of Gc1f with melanoma-specific death is unclear. Methods We investigated the association of the Gc1s, Gc1f, and Gc2 haplotypes with melanoma-specific and all-cause death among 4490 individuals with incident, invasive primary melanoma in 2 population-based studies using multivariable Cox-proportional hazards regression. Results In the pooled analysis of both datasets, the patients with the Gc1f haplotype had a 37% lower risk of melanoma-specific death than the patients without Gc1f (hazard ratio [HR] = 0.63, 95% confidence interval [CI] = 0.47 to 0.83, P  =  .001), with adjustments for age, sex, study center, first- or higher-order primary melanoma, tumor site, pigmentary phenotypes, and Breslow thickness. Associations were similar in both studies. In pooled analyses stratified by Breslow thickness, the corresponding melanoma-specific death HRs for those patients with the Gc1f haplotype compared with those without Gc1f were 0.89 (95% CI = 0.63 to 1.27) among participants with tumor Breslow thickness equal to or less than 2.0 mm and 0.40 (95% CI = 0.25 to 0.63) among participants with tumor Breslow thickness greater than 2.0 mm (P interaction   =  .003). Conclusions Our findings suggest that individuals with the GC haplotype Gc1f may have a lower risk of dying from melanoma—specifically from thicker, higher-risk melanoma—than individuals without this Gc1f haplotype. [ABSTRACT FROM AUTHOR]

It is increasingly common clinically for cancer specimens to be examined using techniques that identify somatic mutations. In principle, these mutational profiles can be used to diagnose the tissue of origin, a critical task for the 3% to 5% of tumors that have an unknown primary site. Diagnosis of primary site is also critical for screening tests that employ circulating DNA. However, most mutations observed in any new tumor are very rarely occurring mutations, and indeed the preponderance of these may never have been observed in any previous recorded tumor. To create a viable diagnostic tool we need to harness the information content in this "hidden genome" of variants for which no direct information is available. To accomplish this we propose a multilevel meta‐feature regression to extract the critical information from rare variants in the training data in a way that permits us to also extract diagnostic information from any previously unobserved variants in the new tumor sample. A scalable implementation of the model is obtained by combining a high‐dimensional feature screening approach with a group‐lasso penalized maximum likelihood approach based on an equivalent mixed‐effect representation of the multilevel model. We apply the method to the Cancer Genome Atlas whole‐exome sequencing data set including 3702 tumor samples across seven common cancer sites. Results show that our multilevel approach can harness substantial diagnostic information from the hidden genome. [ABSTRACT FROM AUTHOR]

A common task for the cancer pathologist is to determine, in a patient suffering from cancer, whether a new tumor in a distinct anatomic site from the primary is an independent occurrence of cancer or a metastasis. As mutational profiling of tumors becomes more widespread in routine clinical practice, this diagnostic task can be greatly enhanced by comparing mutational profiles of the tumors to determine if they are sufficiently similar to conclude that the tumors are clonally related, that is, one is a metastasis of the other. We present here a likelihood ratio test for clonal relatedness in this setting and provide evidence of its validity. The test is unusual in that there are two possible alternative hypotheses, representing the two anatomic sites from which the single clonal cell could have initially emerged. Although evidence for clonal relatedness is largely provided by the presence of exact mutational matches in the two tumors, we show that it is possible to observe data where the test is statistically significant even when no matches are observed. This can occur when the mutational profile of one of the tumors is closely aligned with the anatomic site of the other tumor, suggesting indirectly that the tumor originated in that other site. We exhibit examples of this phenomenon and recommend a strategy for interpreting the results of these tests in practice. [ABSTRACT FROM AUTHOR]

Recently, a controversy has erupted regarding the use of statistical significance tests and the associated P values. Prominent academic statisticians have recommended that the use of statistical tests be discouraged or not used at all. This has naturally led to a lot of confusion among research investigators about the support in the academic statistical community for statistical methods in general. In fact, the controversy surrounding the use of P values has a long history. Critics of P values argue that their use encourages bad scientific practice, leading to the publication of far more false-positive and false-negative findings than the methodology would imply. The thesis of this commentary is that the problem is really human nature, the natural proclivity of scientists to believe their own theories and present data in the most favorable light. This is strongly encouraged by a celebrity culture that is fueled by academic institutions, the scientific journals, and the media. The importance of the truth-seeking tradition of the scientific method needs to be reinforced, and this is being helped by current initiatives to improve transparency in science and to encourage reproducible and replicable research. Statistical testing, used correctly, has an important and valuable place in the scientific tradition. [ABSTRACT FROM AUTHOR]

Summary The Clonality R package is a practical tool to assess the clonal relatedness of two tumors from the same patient. We have previously presented its functionality for testing tumors using loss of heterozygosity data or copy number arrays. Since then somatic mutation data have been more widely available through next generation sequencing and we have developed new methodology for comparing the tumors' mutational profiles. We thus extended the package to include these two new methods for comparing tumors as well as the mutational frequency estimation from external data required for their implementation. The first method is a likelihood ratio test that is readily available on a patient by patient basis. The second method employs a random-effects model to estimate both the population and individual probabilities of clonal relatedness from a group of patients with pairs of tumors. The package is available on Bioconductor. Availability and implementation Bioconductor (http://bioconductor.org/packages/release/bioc/html/Clonality.html). Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Summary: Next generation sequencing panels are being used increasingly in cancer research to study tumor evolution. A specific statistical challenge is to compare the mutational profiles in different tumors from a patient to determine the strength of evidence that the tumors are clonally related, that is, derived from a single, founder clonal cell. The presence of identical mutations in each tumor provides evidence of clonal relatedness, although the strength of evidence from a match is related to how commonly the mutation is seen in the tumor type under investigation. This evidence must be weighed against the evidence in favor of independent tumors from non‐matching mutations. In this article, we frame this challenge in the context of diagnosis using a novel random effects model. In this way, by analyzing a set of tumor pairs, we can estimate the proportion of cases that are clonally related in the sample as well as the individual diagnostic probabilities for each case. The method is illustrated using data from a study to determine the clonal relationship of lobular carcinoma in situ with subsequent invasive breast cancers, where each tumor in the pair was subjected to whole exome sequencing. The statistical properties of the method are evaluated using simulations, demonstrating that the key model parameters are estimated with only modest bias in small samples in most configurations. [ABSTRACT FROM AUTHOR]

Factors known to affect melanoma survival include age at presentation, sex and tumor characteristics. Polymorphisms also appear to modulate survival following diagnosis. Result from other studies suggest that vitamin D receptor (VDR) polymorphisms (SNPs) impact survival in patients with glioma, renal cell carcinoma, lung, breast, prostate and other cancers; however, a comprehensive study of VDR polymorphisms and melanoma-specific survival is lacking. We aimed to investigate whether VDR genetic variation influences survival in patients with cutaneous melanoma. The analysis involved 3566 incident single and multiple primary melanoma cases enrolled in the international population-based Genes, Environment, and Melanoma Study. Melanoma-specific survival outcomes were calculated for each of 38 VDR SNPs using a competing risk analysis after adjustment for covariates. There were 254 (7.1%) deaths due to melanoma during the median 7.6 years follow-up period. VDR SNPs rs7299460, rs3782905, rs2239182, rs12370156, rs2238140, rs7305032, rs1544410 (BsmI) and rs731236 (TaqI) each had a statistically significant (trend P values < 0.05) association with melanoma-specific survival in multivariate analysis. One functional SNP (rs2239182) remained significant after adjustment for multiple testing using the Monte Carlo method. None of the SNPs associated with survival were significantly associated with Breslow thickness, ulceration or mitosis. These results suggest that the VDR gene may influence survival from melanoma, although the mechanism by which VDR exerts its effect does not seem driven by tumor aggressiveness. Further investigations are needed to confirm our results and to understand the relationship between VDR and survival in the combined context of tumor and host characteristics. [ABSTRACT FROM AUTHOR]

Contemporary searches for new risk factors frequently involve genome-wide explorations of very large numbers of candidate risk variants. Given that diseases can often be classified into subtypes that possess evidence of etiologic heterogeneity, the question arises as to whether or not a search for new risk factors would be improved by looking separately within subtypes. Etiologic risk heterogeneity inevitably increases the signal in at least one of the subtypes, but this advantage may be offset by smaller sample sizes and the increased chances of false discovery. In this article, the authors show that only a relatively modest degree of etiologic heterogeneity is necessary for the subtyping strategies to have improved statistical power. In practice, effective exploitation of etiologic heterogeneity requires strong evidence that the subtypes selected are likely to exhibit substantial heterogeneity. Further, defining the subtypes that demonstrate the most heterogeneous profiles is important for optimizing the search for new risk factors. The concepts are illustrated by using data from a breast cancer study in which results are available separately for estrogen receptor-positive (ER+) and -negative (ER−) tumors. [ABSTRACT FROM AUTHOR]

The purpose of this study was to quantify the risk of cancers other than melanoma among family members of CDKN2A mutation carriers using data from the Genes, Environment and Melanoma study. Relative risks (RRs) of all non-melanoma cancers among first-degree relatives (FDRs) of melanoma patients with CDKN2A mutations (n = 65) and FDRs of melanoma patients without mutations (n = 3537) were calculated as the ratio of estimated event rates (number of cancers/total person-years) in FDRs of carriers vs noncarriers with exact Clopper–Pearson-type tests and 95% confidence intervals (CIs). All statistical tests were two-sided. There were 56 (13.1%) non-melanoma cancers reported among 429 FDRs of mutation carriers and 2199 (9.4%) non-melanoma cancers in 23 452 FDRs of noncarriers. The FDRs of carriers had an increased risk of any cancer other than melanoma (56 cancers among 429 FDRs of carrier probands vs 2199 cancers among 23 452 FDRs of noncarrier probands; RR = 1.5, 95% CI = 1.2 to 2.0, P = .005), gastrointestinal cancer (20 cancers among 429 FDRs of carrier probands vs 506 cancers among 23 452 FDRs of noncarrier probands; RR = 2.4, 95% CI = 1.4 to 3.7, P = .001), and pancreatic cancer (five cancers among 429 FDRs of carrier probands vs 41 cancers among 23 452 FDRs of noncarrier probands; RR = 7.4, 95% CI = 2.3 to 18.7, P = .002). Wilms tumor was reported in two FDRs of carrier probands and three FDRs of noncarrier probands (RR = 40.4, 95% CI = 3.4 to 352.7, P = .005). The lifetime risk of any cancer other than melanoma among CDKN2A mutation carriers was estimated as 59.0% by age 85 years (95% CI = 39.0% to 75.4%) by the kin-cohort method, under the standard assumptions of Mendelian genetics on the genotype distribution of FDRs conditional on proband genotype. [ABSTRACT FROM PUBLISHER]

Many major genes have been identified that strongly influence the risk of cancer. However, there are typically many different mutations that can occur in the gene, each of which may or may not confer increased risk. It is critical to identify which specific mutations are harmful, and which ones are harmless, so that individuals who learn from genetic testing that they have a mutation can be appropriately counseled. This is a challenging task, since new mutations are continually being identified, and there is typically relatively little evidence available about each individual mutation. In an earlier article, we employed hierarchical modeling (, Statistics in Medicine , 1973-1992) using the pseudo-likelihood and Gibbs sampling methods to estimate the relative risks of individual rare variants using data from a case-control study and showed that one can draw strength from the aggregating power of hierarchical models to distinguish the variants that contribute to cancer risk. However, further research is needed to validate the application of asymptotic methods to such sparse data. In this article, we use simulations to study in detail the properties of the pseudo-likelihood method for this purpose. We also explore two alternative approaches: pseudo-likelihood with correction for the variance component estimate as proposed by (1996, Journal of the American Statistical Association , 1007-1016) and a hybrid pseudo-likelihood approach with Bayesian estimation of the variance component. We investigate the validity of these hierarchical modeling techniques by looking at the bias and coverage properties of the estimators as well as at the efficiency of the hierarchical modeling estimates relative to that of the maximum likelihood estimates. The results indicate that the estimates of the relative risks of very sparse variants have small bias, and that the estimated 95% confidence intervals are typically anti-conservative, though the actual coverage rates are generally above 90%. The widths of the confidence intervals narrow as the residual variance in the second-stage model is reduced. The results also show that the hierarchical modeling estimates have shorter confidence intervals relative to estimates obtained from conventional logistic regression, and that these relative improvements increase as the variants become more rare. [ABSTRACT FROM AUTHOR]

In a recent article Begg et al. (2007, Biometrics 63, 522–530) proposed a statistical test to determine whether or not a diagnosed second primary tumor is biologically independent of the original primary tumor, by comparing patterns of allelic losses at candidate genetic loci. The proposed concordant mutations test is a conditional test, an adaptation of Fisher's exact test, that requires no knowledge of the marginal mutation probabilities. The test was shown to have generally good properties, but is susceptible to anticonservative bias if there is wide variation in mutation probabilities between loci, or if the individual mutation probabilities of the parental alleles for individual patients differ substantially from each other. In this article, a likelihood ratio test is derived in an effort to address these validity issues. This test requires prespecification of the marginal mutation probabilities at each locus, parameters for which some information will typically be available in the literature. In simulations this test is shown to be valid, but to be considerably less efficient than the concordant mutations test for sample sizes (numbers of informative loci) typical of this problem. Much of the efficiency deficit can be recovered, however, by restricting the allelic imbalance parameter estimate to a prespecified range, assuming that this parameter is in the prespecified range. [ABSTRACT FROM AUTHOR]

Background: Results from randomized trials indicate that treatment with tamoxifen or chemotherapy for primary breast cancer reduces the risk for contralateral breast cancer. However, less is known about how long the risk is reduced and the impact of factors such as age and menopausal status. Methods: The study included 634 women with contralateral breast cancer (case patients) and 1158 women with unilateral breast cancer (control subjects) from the Women's Environment, Cancer and Radiation Epidemiology Study. The women were younger than age 55 when they were first diagnosed with breast cancer during 1985- 1999. Rate ratios (RRs) and 95% confidence intervals (CIs) for contralateral breast cancer after treatment with chemotherapy or tamoxifen were assessed by multivariable adjusted conditional logistic regression analyses. Results: Chemotherapy was associated with a lower risk for contralateral breast cancer (RR = 0.57, 95% Cl = 0.42 to 0.75) than no chemotherapy. A statistically significant association between chemotherapy and reduced risk for contralateral breast cancer persisted up to 10 years after the first breast cancer diagnosis and was stronger among women who became postmenopausal within 1 year of the first breast cancer diagnosis (RR = 0.28, 95% Cl = 0.11 to 0.76). Tamoxifen use was also associated with reduced risk for contralateral breast cancer (RR = 0.66, 95% Cl = 0.50 to 0.88) compared with no use, and the association was statistically significant for 5 years after the first diagnosis. Conclusion: The associations between chemotherapy and tamoxifen treatment and reduced risk for contralateral breast cancer appear to continue for 10 and 5 years, respectively, after the initial breast cancer is diagnosed. Ovarian suppression may have a role in the association between chemotherapy and reduced risk for contralateral breast cancer. [ABSTRACT FROM AUTHOR]

Cancer investigators frequently conduct studies to examine tumor samples from pairs of apparently independent primary tumors with a view to determine whether they share a “clonal” origin. The genetic fingerprints of the tumors are compared using a panel of markers, often representing loss of heterozygosity (LOH) at distinct genetic loci. In this article we evaluate candidate significance tests for this purpose. The relevant information is derived from the observed correlation of the tumors with respect to the occurrence of LOH at individual loci, a phenomenon that can be evaluated using Fisher's exact test. Information is also available from the extent to which losses at the same locus occur on the same parental allele. Data from these combined sources of information can be evaluated using a simple adaptation of Fisher's exact test. The test statistic is the total number of loci at which concordant mutations occur on the same parental allele, with higher values providing more evidence in favor of a clonal origin for the two tumors. The test is shown to have high power for detecting clonality for plausible models of the alternative (clonal) hypothesis, and for reasonable numbers of informative loci, preferably located on distinct chromosomal arms. The method is illustrated using studies to identify clonality in contralateral breast cancer. Interpretation of the results of these tests requires caution due to simplifying assumptions regarding the possible variability in mutation probabilities between loci, and possible imbalances in the mutation probabilities between parental alleles. Nonetheless, we conclude that the method represents a simple, powerful strategy for distinguishing independent tumors from those of clonal origin. [ABSTRACT FROM AUTHOR]

Background: Germline mutations in the CDKN2A gene have been linked to melanoma incidence in many families with multiple cases of the disease. Previous studies of multiple-case families have indicated that the lifetime risk (i.e., penetrance) of melanoma in CDKN2A mutation carriers is very high, ranging from 58% in Europe to 91% in Australia by age 80 years. In this study, we examined lifetime melanoma risk among CDKN2A mutation carriers using carriers who were identified in a population-based study of melanoma. Methods: Probands for the study were incident case patients with either first or subsequent melanoma who were identified in nine geographic regions in Australia, Canada, the United States, and Italy. A total of 3626 probands (53% participation rate) with adequate DNA for analysis were recruited and genotyped for CDKN2A mutations. From the 3550 probands whose DNA could be amplified by polymerase chain reaction of CDKN2A exons 1α, 2, and 3 and surrounding regions, 65 mutation carriers were identified. Melanoma histories in first-degree relatives of these probands were used to calculate the lifetime risk in CDKN2A mutation carriers using the kin-cohort method. Results: The risk of melanoma in CDKN2A mutation carriers was approximately 14% (95% CI = 8% to 22%) by age 50 years, 24% (95% CI = 15% to 34%) by age 70 years, and 28% (95% CI = 18% to 40%) by age 80 years. Eighteen probands had three or more first-degree relatives with melanoma, but only one was a carrier of a CDKN2A mutation. Conclusions: CDKN2A mutation carriers in the general population have a much lower risk of melanoma than that suggested by estimates obtained from multiple-case families. The preponderance of familial clustering of melanoma occurs in families without identifiable mutations in CDKN2A. [ABSTRACT FROM AUTHOR]

Gene–disease association studies based on case–control designs may often be used to identify candidate polymorphisms (markers) conferring disease risk. If a large number of markers are studied, genotyping all markers on all samples is inefficient in resource utilization. Here, we propose an alternative two-stage method to identify disease-susceptibility markers. In the first stage all markers are evaluated on a fraction of the available subjects. The most promising markers are then evaluated on the remaining individuals in Stage 2. This approach can be cost effective since markers unlikely to be associated with the disease can be eliminated in the first stage. Using simulations we show that, when the markers are independent and when they are correlated, the two-stage approach provides a substantial reduction in the total number of marker evaluations for a minimal loss of power. The power of the two-stage approach is evaluated when a single marker is associated with the disease, and in the presence of multiple disease-susceptibility markers. As a general guideline, the simulations over a wide range of parametric configurations indicate that evaluating all the markers on 50% of the individuals in Stage 1 and evaluating the most promising 10% of the markers on the remaining individuals in Stage 2 provides near-optimal power while resulting in a 45% decrease in the total number of marker evaluations. [ABSTRACT FROM AUTHOR]

Background: Patients diagnosed with superficial bladder cancer who have not undergone total cystectomy are at high risk for recurrence, and bladder surveillance with cystoscopy is recommended for such patients every 3-6 months. We examined the degree to which bladder cancer patients undergo the recommended surveillance procedures and identified patient and primary care provider characteristics associated with nonadherence to these recommendations. Methods: We used information obtained from the Surveillance, Epidemiology, and End Results (SEER) ProgramMedicare-linked database to identify 6717 patients aged 65 years or older who were diagnosed with superficial bladder cancer from 1992 through 1996 and who survived for at least 3 years after diagnosis but did not have a total cystectomy. We used information obtained from Medicare claims forms to examine the frequency with which these patients had a surveillance examination of the bladder during each of five contiguous 6-month intervals from month 7 to month 36 following diagnosis. We examined characteristics of patients and their physicians that were associated with low-intensity surveillance (defined as having an examination during fewer than two of the five possible follow-up intervals). Logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs). All statistical tests were twosided. Results: Only 40% of the entire cohort had an examination during all five intervals; 1216 patients (18.1%) had low-intensity surveillance. Patient characteristics that were independently associated with low-intensity surveillance were being age 75 years or older (adjusted OR = 1.54, 95% CI = 1.35 to 1.74), nonwhite (adjusted OR = 1.94, 95% CI = 1.57 to 2.40), and having favorable tumor histology (adjusted OR = 0.59, 95% CI = 0.48 to 0.72 for poorly differentiated versus referent well-differentiated tumor grade) and high comorbidity (adjusted OR = 1.72, 95% CI = 1.30 to 2.27). Residence in an urban... [ABSTRACT FROM AUTHOR]

Background: Although there is no proven benefit associated with screening for lung cancer, screening programs are attracting many individuals who perceive themselves to be at high risk due to smoking. We sought to determine whether the risk of lung cancer varies predictably among smokers. Methods: We used data on 18172 subjects enrolled in the Carotene and Retinol Efficacy Trial (CARET)—a large, randomized trial of lung cancer prevention—to derive a lung cancer risk prediction model. Model inputs included the subject's age, sex, asbestos exposure history, and smoking history. We assessed the model's calibration by comparing predicted and observed rates of lung cancer across risk deciles and validated it by assessing the extent to which a model estimated on data from five CARET study sites could predict events in the sixth study site. We then applied the model to evaluate the risk of lung cancer among smokers enrolled in a study of lung cancer screening with computed tomography (CT). Results: The model was internally valid and well calibrated. Ten-year lung cancer risk varied greatly among participants in the CT study, from 15% for a 68-year-old man who has smoked two packs per day for 50 years and continues to smoke, to 0.8% for a 51-year-old woman who smoked one pack per day for 28 years before quitting 9 years earlier. Even among the subset of CT study participants who would be eligible for a clinical trial of cancer prevention, risk varied greatly. Conclusions: The risk of lung cancer varies widely among smokers. Accurate risk prediction may help individuals who are contemplating voluntary screening to balance the potential benefits and risks. Risk prediction may also be useful for researchers designing clinical trials of lung cancer prevention. [ABSTRACT FROM AUTHOR]

Background: Estimating the lifetime risk associated with (i.e., the penetrance of) genetic abnormalities that predispose individuals to cancer is important for genetic counseling. (Penetrance may be estimated from the degree of familial aggregation of cancer, that is, the extent to which cancers cluster in families.) Early penetrance studies of BRCA1 and BRCA2 mutations used high-risk families with multiple cases of breast cancer, a study design that led to very high penetrance estimates. However, such studies were subject to potential ascertainment biases. To offset such biases, recent studies have used data from family members of probands ascertained from population-based incident cases of cancer. The use of case probands is, however, also subject to bias because all risk factors are over-represented in case patients. To draw attention to this problem, literature on the penetrance of breast cancer in BRCA1 and BRCA2 carriers is reviewed.Methods: A theory is presented to show that the use of case probands is itself biased, leading to inflated penetrance estimates. The strategy is unbiased only if all carriers share an identical risk. Any unexplained heterogeneity of risk caused by unknown genetic or shared environmental factors within families leads to an inflated estimate of penetrance.Results: Eight published studies using population-based methods are reviewed. All but one of the family-based studies used case probands.Conclusions: Penetrance estimates from case proband studies must be inflated if other factors influence breast cancer risk in addition to the specific genetic abnormality. Thus, women with such genetic abnormalities and a strong family history of breast cancer are likely to possess a much higher risk for breast cancer than women with such abnormalities but without a strong family history. Methodologic techniques to improve the prediction of cancer risk are needed. [ABSTRACT FROM AUTHOR]

Background Evidence is emerging that melanoma has distinct etiologic pathways and subtypes, characterized by factors like anatomic site. For example, older men have more head and neck melanomas, and younger women more leg melanomas. Family history is a strong risk factor and familial risk genes have been identified. We therefore aimed to investigate familial aggregation of melanoma from an etiologic heterogeneity perspective, to determine whether melanoma subtypes aggregate within families. Methods Using population-level linked health data, we examined the extent to which melanomas in first-degree relatives (FDRs) of cases shared the same body site of occurrence. FDR-pairs diagnosed with melanoma were identified using the Western Australian Cancer Registry and genealogical Family Connections System. Site was categorized as head/neck, trunk/arms, or legs. We identified 1,006 pairs of tumours from 677 family pairs and used Chi-Squared tests to evaluate familial aggregation by site. Degrees of etiologic heterogeneity of individual site-pairs were characterized by site concordance odds ratios. Results Familial aggregation by site was statistically significant (P = 0.01). However, only the site pairings of head/neck versus trunk/arms showed strong evidence of familial concordance (OR = 1.7, 95% CI 1.1-1.7). Trends were broadly similar in same-sex pairs. Conclusions Results show modest evidence of familial aggregation of melanoma by site, with overall evidence of aggregation but inconsistent patterns between sites. Key messages Strong etiologic differences in incidence between anatomic sites for age and sex may be more strongly influenced by non-genetic factors, such as familial patterns of sun exposure. [ABSTRACT FROM AUTHOR]

A distribution-free permutation test procedure is proposed for comparing receiver operating characteristic curves based on continuous data from a paired design. The method tests the hypothesis that the two curves are identical for all operating points, unlike previously proposed methods which test the equivalence of the areas under the curves. The new test is shown by simulation to have very similar operating characteristics to the standard method based on comparisons of the areas when the curves are parallel, but markedly superior power when the curves cross, that is when the curves are different but have similar areas. The prospects of generalising the approach to unpaired experiments and to comparisons of ordinal rating data are discussed. [ABSTRACT FROM AUTHOR]

Gives background information on Marianne Berwick's and other scientists research on the detection of skin cancer via self-examination. Research methodology; Who are at risk; Perception on the progression of melanoma; How data was collected; Analysis of data; Results; Self-examination's impact on early detection.

Background: We conducted this combined analysis of available data from studies with information on this issue to clarify the association between Trichomonas vaginalis infection and cervical neoplasia.Methods: We performed MEDLINE searches (1966-1993) using the key words and phrases 'trichomonas vaginitis' and 'neoplasms, cervix' for articles published in English, and searched citations of the articles obtained from MEDLINE: A total of 24 articles (two cohort studies and 22 case-control) were included in this data analysis. In the analysis, the studies were evaluated for heterogeneity using Breslow-Day tests for homogeneity of the odds ratios and of rate ratios. If the odds ratios from studies are heterogeneous, it is not appropriate to combine them using the Mantel-Haenszel method. Also, publication bias was evaluated by assessing the association between the observed effect size and the variance of the effect size using a rank correlation test.Results: The combined summary relative risk for the two cohort studies was 1.93 (95% confidence interval: 1.22-2.65) indicating an approximate doubling of the risk of cervical neoplasia in the presence of T. vaginalis infection. The attributable risks among exposed subjects and among the source population were 47.4% and 2.1% respectively. Results of the 22 retrospective studies were much less consistent. However, most of them demonstrated a significant positive association.Conclusions: This combined analysis suggests that there is an association between T. vaginalis and the risk of cervical neoplasia, but that such infections account for only 2% of cervical neoplasia. [ABSTRACT FROM AUTHOR]

Publication bias is a widely recognized phenomenon that occurs because of the influence of study results on the chances of publication. Usually, studies with positive results are more likely to be published than studies with negative results, which leads to a preponderance of false-positive results in the literature. Empiric studies have demonstrated that the induced bias is large and can have a serious impact on meta-analyses, in which data from several studies are aggregated, as well as on informal reviews. The problem is deeply embedded in current research practice, which encourages demonstration of statistical significance to “prove” theories, and one of its causes is the pressure to publish extensively that is an integral part of the competition for academic promotion. Serious efforts to reduce this problem will involve restructuring the process by which study results are disseminated, changing editorial policies, and altering the style and methods of statistical analysis. [ABSTRACT FROM PUBLISHER]

Presents a reflection on the alpha-tocopherol Beta-carotene trial for cancer prevention in the U.S. Reason behind the cancellation of the trial; Ethical considerations for large anti-cancer trials; Assessment on the effects of Beta-carotene on overall mortality.

Summary: If a cancer patient develops multiple tumors, it is sometimes impossible to determine whether these tumors are independent or clonal based solely on pathological characteristics. Investigators have studied how to improve this diagnostic challenge by comparing the presence of loss of heterozygosity (LOH) at selected genetic locations of tumor samples, or by comparing genomewide copy number array profiles. We have previously developed statistical methodology to compare such genomic profiles for an evidence of clonality. We assembled the software for these tests in a new R package called ‘Clonality’. For LOH profiles, the package contains significance tests. The analysis of copy number profiles includes a likelihood ratio statistic and reference distribution, as well as an option to produce various plots that summarize the results.Availability: Bioconductor (http://bioconductor.org/packages/release/bioc/html/Clonality.html) and http://www.mskcc.org/mskcc/html/13287.cfm.Contact: ostrovni@mskcc.org [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Case-Control and Case-Only Designs With Genotype and Family History Data: Estimating Relative-Risk, Residual Familial Aggregation and Cumulative Risk," by N. Chatterjee, Z. Kalayliouglu, J. Shih and M. Gail in a 2006 issue.

Determines the incidence and mortality rates of cancer in the U.S. Causes of death; Growth in the use of cancer-directed surgery; Classification of cancer mortality.