[Show abstract][Hide abstract] ABSTRACT: Importance
Estimates of familial cancer risk from population-based studies are essential components of cancer risk prediction.Objective
To estimate familial risk and heritability of cancer types in a large twin cohort.Design, Setting, and Participants
Prospective study of 80 309 monozygotic and 123 382 same-sex dizygotic twin individuals (N = 203 691) within the population-based registers of Denmark, Finland, Norway, and Sweden. Twins were followed up a median of 32 years between 1943 and 2010. There were 50 990 individuals who died of any cause, and 3804 who emigrated and were lost to follow-up.Exposures
Shared environmental and heritable risk factors among pairs of twins.Main Outcomes and Measures
The main outcome was incident cancer. Time-to-event analyses were used to estimate familial risk (risk of cancer in an individual given a twin’s development of cancer) and heritability (proportion of variance in cancer risk due to interindividual genetic differences) with follow-up via cancer registries. Statistical models adjusted for age and follow-up time, and accounted for censoring and competing risk of death.Results
A total of 27 156 incident cancers were diagnosed in 23 980 individuals, translating to a cumulative incidence of 32%. Cancer was diagnosed in both twins among 1383 monozygotic (2766 individuals) and 1933 dizygotic (2866 individuals) pairs. Of these, 38% of monozygotic and 26% of dizygotic pairs were diagnosed with the same cancer type. There was an excess cancer risk in twins whose co-twin was diagnosed with cancer, with estimated cumulative risks that were an absolute 5% (95% CI, 4%-6%) higher in dizygotic (37%; 95% CI, 36%-38%) and an absolute 14% (95% CI, 12%-16%) higher in monozygotic twins (46%; 95% CI, 44%-48%) whose twin also developed cancer compared with the cumulative risk in the overall cohort (32%). For most cancer types, there were significant familial risks and the cumulative risks were higher in monozygotic than dizygotic twins. Heritability of cancer overall was 33% (95% CI, 30%-37%). Significant heritability was observed for the cancer types of skin melanoma (58%; 95% CI, 43%-73%), prostate (57%; 95% CI, 51%-63%), nonmelanoma skin (43%; 95% CI, 26%-59%), ovary (39%; 95% CI, 23%-55%), kidney (38%; 95% CI, 21%-55%), breast (31%; 95% CI, 11%-51%), and corpus uteri (27%; 95% CI, 11%-43%).Conclusions and Relevance
In this long-term follow-up study among Nordic twins, there was significant excess familial risk for cancer overall and for specific types of cancer, including prostate, melanoma, breast, ovary, and uterus. This information about hereditary risks of cancers may be helpful in patient education and cancer risk counseling.
Full-text · Article · Jan 2016 · JAMA The Journal of the American Medical Association
[Show abstract][Hide abstract] ABSTRACT: Background: Family history is an established risk factor for breast cancer. Although some important genetic factors have been identified, the extent to which familial risk can be attributed to genetic factors versus common environment remains unclear. Methods: We estimated the familial concordance and heritability of breast cancer among 21,054 monozygotic and 30,939 dizygotic female twin pairs from the Nordic Twin Study of Cancer, the largest twin study of cancer in the world. We accounted for left-censoring, right-censoring, as well as the competing risk of death. Results: From 1943 through 2010, 3,933 twins were diagnosed with breast cancer. The cumulative lifetime incidence of breast cancer taking competing risk of death into account was 8.1% for both zygosities, although the cumulative risk for twins whose co-twins had breast cancer was 28% among monozygotic and 20% among dizygotic twins. The heritability of liability to breast cancer was 31% [95% confidence interval (CI), 10%-51%] and the common environmental component was 16% (95% CI, 10%-32%). For premenopausal breast cancer these estimates were 27% and 12%, respectively, and for postmenopausal breast cancer 22% and 16%, respectively. The relative contributions of genetic and environmental factors were constant between ages 50 and 96. Our results are compatible with the Peto-Mack hypothesis. Conclusion: Our findings indicate that familial factors explain almost half of the variation in liability to develop breast cancer, and results were similar for pre- and postmenopausal breast cancer Impact: We estimate heritability of breast cancer, taking until now ignored sources of bias into account.
No preview · Article · Nov 2015 · Cancer Epidemiology Biomarkers & Prevention
[Show abstract][Hide abstract] ABSTRACT: Missing covariate values is a common problem in survival analysis. In this paper we propose a novel method for the Cox regression model that is close to maximum likelihood but avoids the use of the EM-algorithm. It exploits that the observed hazard function is multiplicative in the baseline hazard function with the idea being to profile out this function before carrying out the estimation of the parameter of interest. In this step one uses a Breslow type estimator to estimate the cumulative baseline hazard function. We focus on the situation where the observed covariates are categorical which allows us to calculate estimators without having to assume anything about the distribution of the covariates. We show that the proposed estimator is consistent and asymptotically normal, and derive a consistent estimator of the variance-covariance matrix that does not involve any choice of a perturbation parameter. Moderate sample size performance of the estimators is investigated via simulation and by application to a real data example.
No preview · Article · Oct 2015 · Lifetime Data Analysis
[Show abstract][Hide abstract] ABSTRACT: Context:
Testosterone levels (T) have been associated with mortality, but controversy exists.
To investigate associations between serum levels of total testosterone, SHBG, free testosterone, estradiol, LH and FSH, and subsequent mortality with up to 30 years of follow-up.
A prospective cohort study consisting of men participating in four independent population-based surveys (MONICA I-III and Inter99) from 1982 to 2001 and followed until December 2012 with complete registry follow-up.
Setting and participants:
5,350 randomly selected men from the general population aged 30, 40, 50, 60 or 70 years at baseline.
Main outcome measures:
All-cause mortality, cardiovascular disease (CVD) mortality and cancer mortality.
1,533 men died during the follow-up period; 428 from CVD and 480 from cancer. Cox proportional hazard models revealed that men in highest LH quartile had an increased all-cause mortality compared to lowest quartile (HR=1.32, 95%CI: 1.14 to 1.53). Likewise, increased quartiles of LH/T and estradiol increased the risk of all-cause mortality (HR=1.23, 95%CI: 1.06 to 1.43, HR=1.23, 95%CI: 1.06 to 1.43). No association to testosterone levels was found. Higher LH levels were associated with increased cancer mortality (HR=1.42, 95%CI: 1.10 to 1.84) independently of smoking status. Lower CVD mortality was seen for men with testosterone in the highest quartile compared to lowest (HR=0.72, 95%CI: 0.53 to 0.98). Furthermore, negative trends were seen for SHBG and free testosterone in relation to CVD mortality, however insignificant.
The observed positive association of LH and LH/T, but not testosterone, with all-cause mortality suggests that a compensated impaired Leydig cell function may be a risk factor for death by all causes in men. Our findings underpin the clinical importance of including LH measurement in the diagnostic work-up of male patients seeking help for possible androgen insufficiency.
No preview · Article · Oct 2015 · The Journal of Clinical Endocrinology and Metabolism
[Show abstract][Hide abstract] ABSTRACT: Twin and family data provide a key source for evaluating inheritance of specific diseases. A standard analysis of such data typically involves the computation of prevalences and different concordance measures such as the casewise concordance, that is the probability that one twin has the disease given that the co-twin has the disease. Most diseases have a varying age-of-onset that will lead to age-specific prevalence. Typically, this aspect is not considered, and this may lead to severe bias as well as make it very unclear exactly what population quantities that we are estimating. In addition, one will typically need to deal with censoring in the data, that is the fact that we for some subjects only know that they are alive at a specific age without having the disease. These subjects needs to be considered age specifically, and clearly if they are young there is still a risk that they will develop the disease. The aim of this contribution is to show that the standard casewise concordance and standard prevalence estimators do not work in general for age-of-onset data. We show how one can in fact do something easy and simple even with censored data. The key is to take age into account when analysing such data.
No preview · Article · Jul 2015 · Behavior Genetics
[Show abstract][Hide abstract] ABSTRACT: With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate-dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate-dependent censoring. We consider a covariate-adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate-adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate-adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.
No preview · Article · Jun 2015 · Scandinavian Journal of Statistics
[Show abstract][Hide abstract] ABSTRACT: A mean residual life function (MRLF) is the remaining life expectancy of a subject who has survived to a certain time point. In the presence of covariates, regression models are needed to study the association between the MRLFs and covariates. If the survival time tends to be too long or the tail is not observed, the restricted mean residual life must be considered. In this paper, we propose the proportional restricted mean residual life model for fitting survival data under right censoring. For inference on the model parameters, martingale estimating equations are developed, and the asymptotic properties of the proposed estimators are established. In addition, a class of goodness-of-fit test is presented to assess the adequacy of the model. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and the approach is applied to a set of real life data collected from a randomized clinical trial.
No preview · Article · May 2015 · Journal of Applied Statistics
[Show abstract][Hide abstract] ABSTRACT: Left-truncation occurs frequently in survival studies, and it is well known how to deal with this for univariate survival times. However, there are few results on how to estimate dependence parameters and regression effects in semiparametric models for clustered survival data with delayed entry. Surprisingly, existing methods only deal with special cases. In this paper, we clarify different kinds of left-truncation and suggest estimators for semiparametric survival models under specific truncation schemes. The large-sample properties of the estimators are established. Small-sample properties are investigated via simulation studies, and the suggested estimators are used in a study of prostate cancer based on the Finnish twin cohort where a twin pair is included only if both twins were alive in 1974.
No preview · Article · Apr 2015 · Scandinavian Journal of Statistics
[Show abstract][Hide abstract] ABSTRACT: Recently, Fine and Gray (J Am Stat Assoc 94:496-509, 1999) proposed a semi-parametric proportional regression model for the subdistribution hazard function which has been used extensively for analyzing competing risks data. However, failure of model adequacy could lead to severe bias in parameter estimation, and only a limited contribution has been made to check the model assumptions. In this paper, we present a class of analytical methods and graphical approaches for checking the assumptions of Fine and Gray's model. The proposed goodness-of-fit test procedures are based on the cumulative sums of residuals, which validate the model in three aspects: (1) proportionality of hazard ratio, (2) the linear functional form and (3) the link function. For each assumption testing, we provide a [Formula: see text]-values and a visualized plot against the null hypothesis using a simulation-based approach. We also consider an omnibus test for overall evaluation against any model misspecification. The proposed tests perform well in simulation studies and are illustrated with two real data examples.
No preview · Article · Nov 2014 · Lifetime Data Analysis
[Show abstract][Hide abstract] ABSTRACT: We consider data from the Danish twin registry and aim to study in detail how lifetimes for twin-pairs are correlated. We consider models where we specify the marginals using a regression structure, here Cox's regression model or the additive hazards model. The best known such model is the Clayton-Oakes model. This model can be extended in several directions. One extension is to allow the dependence parameter to depend on covariates. Another extension is to model dependence via piecewise constant cross-hazard ratio models. We show how both these models can be implemented for large sample data, and suggest a computational solution for obtaining standard errors for such models for large registry data. In addition we consider alternative models that have some computational advantages and with different dependence parameters based on odds ratios of the survival function using the Plackett distribution. We also suggest a way of assessing how and if the dependence is changing over time, by considering either truncated or right-censored versions of the data to measure late or early dependence. This can be used for formally testing if the dependence is constant, or decreasing/increasing. The proposed procedures are applied to Danish twin data to describe dependence in the lifetimes of the twins. Here we show that the early deaths are more correlated than the later deaths, and by comparing MZ and DZ associations we suggest that early deaths might be more driven by genetic factors. This conclusion requires models that are able to look at more local dependence measures. We further show that the dependence differs for MZ and DZ twins and appears to be the same for males and females, and that there are indications that the dependence increases over calendar time.
No preview · Article · Sep 2014 · Lifetime Data Analysis
[Show abstract][Hide abstract] ABSTRACT: Context: Human exposure to polychlorinated biphenyls (PCBs) has been associated to type 2 diabetes in adults. Objectives: To determine whether concurrent serum PCB concentration was associated with markers of glucose metabolism in healthy children. Design: Cross-sectional study. Settings and participants: A total of 771 healthy Danish third grade school children aged 8-10 years in the municipality of Odense were recruited in 1997 through a two-stage cluster sampling from 25 different schools stratified according to location and socioeconomic character; 509 (9.7±0.8 years, 53% girls) had adequate amounts available for PCB and analyses. Main outcome measures: Fasting plasma glucose and serum insulin were measured and a homeostasis assessment model of insulin resistance (HOMA-IR) and β-cell function (HOMA-B) calculated. Serum PCB congeners and other persistent compounds were measured and ΣPCB calculated. Results: PCBs were present in serum at low concentrations, median 0.19μ g/g lipid (interquartile range, IQR: 0.12-0.31). After adjustment for putative confounding factors, the second, third, fourth and fifth quintiles of total PCB were significantly inversely associated with serum insulin (-14.6%, -21.7%, -18.9%, -23.1%, p-trend<0.01), compared to the first quintile, but not with plasma glucose (p=0.45). HOMA-IR and HOMA-B were affected in the same direction due to the declining insulin levels with increasing PCB exposure. Similar results were found for individual PCB congeners, for βHCB and pp-DDE. Conclusion: A strong inverse association between serum insulin and PCB exposure was found while fasting plasma glucose remained within the expected narrow range. Our findings suggest that PCB may not exert effect through decreased peripheral insulin sensitivity, as seen in obese and low fit children, but rather through a toxicity to β-cells. It remains to be shown if lower HOMA-B is caused by destruction of β-cell reducing peripheral insulin resistance and thereby increase fasting plasma glucose as previously found.
No preview · Article · Aug 2014 · Journal of Clinical Endocrinology & Metabolism
[Show abstract][Hide abstract] ABSTRACT: Family studies provide an important tool for understanding etiology of
diseases, with the key aim of discovering evidence of family aggregation and to
determine if such aggregation can be attributed to genetic components.
Heritability and concordance estimates are routinely calculated in twin studies
of diseases, as a way of quantifying such genetic contribution. The endpoint in
these studies are typically defined as occurrence of a disease versus death
without the disease. However, a large fraction of the subjects may still be
alive at the time of follow-up without having experienced the disease thus
still being at risk. Ignoring this right-censoring can lead to severely biased
estimates. We propose to extend the classical liability threshold model with
inverse probability of censoring weighting of complete observations. This leads
to a flexible way of modeling twin concordance and obtaining consistent
estimates of heritability. We apply the method in simulations and to data from
the population based Danish twin cohort where we describe the dependence in
prostate cancer occurrence in twins.
[Show abstract][Hide abstract] ABSTRACT: Background: Prostate cancer is thought to be the most heritable cancer, although little is known about how this genetic contribution varies across age. Methods: To address this question, we undertook the world's largest prospective study in the Nordic Twin Study of Cancer cohort, including 18,680 monozygotic and 30,054 dizygotic same sex male twin pairs. We incorporated time-to-event analyses to estimate the risk concordance and heritability while accounting for censoring and competing risks of death, essential sources of biases that have not been accounted for in previous twin studies modeling cancer risk and liability. Results: The cumulative risk of prostate cancer was similar to that of the background population. The cumulative risk for twins whose co-twin was diagnosed with prostate cancer was greater for MZ than for DZ twins across all ages. Among concordantly affected pairs, the time between diagnoses was significantly shorter for MZ than DZ pairs (median 3.8 versus 6.5 years, respectively). Genetic differences contributed substantially to variation in both the risk and the liability (heritability=58% (95% CI 52%-63%) of developing prostate cancer. The relative contribution of genetic factors was constant across age through late life with substantial genetic heterogeneity even when diagnosis and screening procedures vary. Conclusions: Results from the population based twin cohort, indicate a greater genetic contribution to the risk of developing prostate cancer when addressing sources of bias. The role of genetic factors is consistently high across age Impact: Findings impact the search for genetic and epigenetic markers and frame prevention efforts.
No preview · Article · May 2014 · Cancer Epidemiology Biomarkers & Prevention
[Show abstract][Hide abstract] ABSTRACT: Objective:
Our objective was to explore whether childhood exposure to perfluorinated and polyfluorinated compounds (PFCs), widely used stain- and grease-repellent chemicals, is associated with adiposity and markers of glycemic control.
Materials and methods:
Body mass index, skinfold thickness, waist circumference, leptin, adiponectin, insulin, glucose, and triglyceride concentrations were assessed in 8- to 10-year-old children in 1997 in a subset of the European Youth Heart Study, Danish component. Plasma PFC concentrations were available from 499 children. Linear regression models were performed to determine the association between PFC exposure and indicators of adiposity and markers of glycemic control.
There was no association between PFC exposures and adiposity or markers of glycemic control in normal-weight children. Among overweight children, an increase of 10 ng perfluorooctane sulfonic acid/mL plasma was associated with 16.2% (95% confidence interval [CI], 5.2%-28.3%) higher insulin concentration, 12.0% (95% CI, 2.4%-22.4%) higher β-cell activity, 17.6% (95% CI, 5.8%-30.8%) higher insulin resistance, and 8.6% (95% CI, 1.2%-16.5%) higher triglyceride concentrations, and an increase of 10 ng perfluorooctanoic acid/mL plasma was associated with 71.6% (95% CI, 2.4%-187.5%) higher insulin concentration, 67.5% (95% CI, 5.5%-166.0%) higher β-cell function, 73.9% (95% CI, 0.2%-202.0%) higher insulin resistance, and 76.2% (95% CI, 22.8%-153.0%) higher triglyceride concentrations.
Increased PFC exposure in overweight 8- to 10-year-old children was associated with higher insulin and triglyceride concentrations. Chance findings may explain some of our results, and due to the cross-sectional design, reverse causation cannot be excluded. The findings therefore need to be confirmed in longitudinal studies.
Full-text · Article · Feb 2014 · The Journal of Clinical Endocrinology and Metabolism