We derived estimates of overdiagnosis by polygenic risk groups and examined whether polygenic risk-stratified screening for prostate cancer reduces overdiagnosis.
We calculated the polygenic risk score based on genotypes of 66 known prostate cancer loci for 4967 men from the Finnish section of the European Randomised Study of Screening for Prostate Cancer. We stratified the 72?072 men in the trial into those with polygenic risk below and above the median. Using a maximum likelihood method based on interval cancers, we estimated the mean sojourn time (MST) and episode sensitivity. For each polygenic risk group, we estimated the proportion of screen-detected cancers that are likely to be overdiagnosed from the difference between the observed and expected number of screen-detected cancers.
Of the prostate cancers, 74% occurred among men with polygenic risk above population median. The sensitivity was 0.55 (95% confidence interval (CI) 0.45-0.65) and MST 6.3 (95% CI 4.2-8.3) years. The overall overdiagnosis was 42% (95% CI 37-52) of the screen-detected cancers, with 58% (95% CI 54-65) in men with the lower and 37% (95% CI 31-47) in those with higher polygenic risk.
Targeting screening to men at higher polygenic risk could reduce the proportion of cancers overdiagnosed.
Cites: J Natl Cancer Inst. 2002 Jul 3;94(13):981-9012096083
Cites: Nat Genet. 2002 May;31(1):33-611984562
Cites: Biometrics. 1984 Mar;40(1):1-146733223
Cites: Am J Epidemiol. 1983 Dec;118(6):865-866650488
Cites: BJU Int. 2003 Dec;92 Suppl 2:22-614983949
Cites: Acta Oncol. 1994;33(4):365-98018367
Cites: J Med Screen. 2007;14(4):174-718078561
Cites: Biometrics. 2008 Mar;64(1):10-917501937
Cites: N Engl J Med. 2008 Jun 26;358(26):2796-80318579814
Cites: J Natl Cancer Inst. 2009 Mar 18;101(6):374-8319276453
Cites: BMC Genomics. 2009;10:56119943955
Cites: Br J Cancer. 2011 May 10;104(10):1656-6321468051
Previous studies have established a relationship between socioeconomic status (SES) and survival in coronary heart disease. Acute cardiac care in Sweden is considered to be excellent and independent of SES. We studied the influence of area-level socioeconomic status on mortality after hospitalization for acute myocardial infarction (AMI) between 1995 and 2013 in the Gothenburg metropolitan area, which has little over 800,000 inhabitants and includes three city hospitals.
Data were obtained from the SWEDEHEART registry (Swedish Websystem for Enhancement of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies) and the Swedish Central Bureau of Statistics for patients hospitalized for ST-elevation myocardial infarction (STEMI) and non-STEMI in the city of Gothenburg in Western Sweden. The groups were compared using Cox proportional hazards regression and logistic regression.
10,895 (36% female) patients were hospitalized due to AMI during the study period. Patients residing in areas with lower SES had higher rates of smoking and diabetes (P
Measurement error occurs when we observe error-prone surrogates, rather than true values. It is common in observational studies and especially so in epidemiology, in nutritional epidemiology in particular. Correcting for measurement error has become common, and regression calibration is the most popular way to account for measurement error in continuous covariates. We consider its use in the context where there are validation data, which are used to calibrate the true values given the observed covariates. We allow for the case that the true value itself may not be observed in the validation data, but instead, a so-called reference measure is observed. The regression calibration method relies on certain assumptions.This paper examines possible biases in regression calibration estimators when some of these assumptions are violated. More specifically, we allow for the fact that (i) the reference measure may not necessarily be an 'alloyed gold standard' (i.e., unbiased) for the true value; (ii) there may be correlated random subject effects contributing to the surrogate and reference measures in the validation data; and (iii) the calibration model itself may not be the same in the validation study as in the main study; that is, it is not transportable. We expand on previous work to provide a general result, which characterizes potential bias in the regression calibration estimators as a result of any combination of the violations aforementioned. We then illustrate some of the general results with data from the Norwegian Women and Cancer Study.
BACKGROUND: Incidence and lifetime risk of diabetes are important public health measures. Traditionally, nonparametric estimates are obtained from survey data by means of a Nelson-Aalen estimator which requires data information on both incident events and risk sets from the entire cohort. Such data information is rarely available in real studies. METHODS: We compare two different approaches for obtaining nonparametric estimates of age-specific incidence and lifetime risk with emphasis on required assumptions. The first and novel approach only considers incident cases occurring within a fixed time window-we have termed this cohort-of-cases data-which is linked explicitly to the birth process in the past. The second approach is the usual Nelson-Aalen estimate which requires knowledge on observed time at risk for the entire cohort and their incident events. Both approaches are used on data on anti-diabetic medications obtained from Odense Pharmacoepidemiological Database, which covers a population of approximately 470,000 over the period 1993-2003. For both methods we investigate if and how incidence rates can be projected. RESULTS: Both the new and standard method yield similar sigmoidal shaped estimates of the cumulative distribution function of age-specific incidence. The Nelson-Aalen estimator gives somewhat higher estimates of lifetime risk (15.65% (15.14%; 16.16%) for females, and 17.91% (17.38%; 18.44%) for males) than the estimate based on cohort-of-cases data (13.77% (13.74%; 13.81%) for females, 15.61% (15.58%; 15.65%) for males). Accordingly the projected incidence rates are higher based on the Nelson-Aalen estimate-also too high when compared to observed rates. In contrast, the cohort-of-cases approach gives projections that fit observed rates better. CONCLUSION: The developed methodology for analysis of cohort-of-cases data has potential to become a cost-effective alternative to a traditional survey based study of incidence. To allow more general use of the methodology, more research is needed on how to relax stationarity assumptions.
Recent studies have shown that SNPs in the FTO gene predispose to childhood and adult obesity. In this study, we examined the association between variants in FTO and KIAA1005, a gene that maps closely to FTO, and obesity, as well as obesity related traits among 450 well characterised severely obese children and 512 normal weight controls. FTO showed significant association with several obesity related traits while SNPs in KIAA1005 did not. When stratified by gender, the FTO variant rs9939609 showed association with obesity and BMI among girls (P=0.006 and 0.004, respectively) but not among boys. Gender differences were also found in the associations of the FTO rs9939609 with obesity related traits such as insulin sensitivity and plasma glucose. This study suggests that FTO may have an important role for gender specific development of severe obesity and insulin resistance in children.
A survey for the presence of ochratoxin A (OTA) was undertaken from 2001 to 2005 in 188 samples of sweet wines produced in Spain and in 102 samples originating from other countries: France (n = 49), Austria (9), Chile (9), Portugal (9), Greece (6), Italy (5), Germany (3), Hungary (2), Slovenia (2), Switzerland (2), Canada (1), Japan (1), New Zealand (1), Ukraine (1), South Africa (1) and the USA (1). The analytical method was based on immunoaffinity chromatography clean-up and high-performance liquid chromatography (HPLC) with fluorescence detection. The limit of detection (defined as a signal-noise ratio = 3) was estimated to be 0.01 microg l(-1). The limit of quantification (0.02 microg l(-1)) was checked as being the lowest measurable concentration. OTA was detected in 281 out of 290 samples analysed (96.9% positive) at concentrations ranging from 0.01 to 4.63 microg l(-1). The overall mean and median levels were estimated to be 0.50 and 0.14 microg l(-1), respectively. In Spanish sweet wines OTA was found in 99% of the samples, with mean and median values of 0.65 and 0.19 microg l(-1), respectively. The mean value obtained in this study for OTA in the Spanish sweet wines would result in an intake of about 37.5 and 3.2 ng day(-1) of OTA for regular consumers and for the overall population, respectively. These figures represent a minor contribution to the provisional tolerable weekly intake (PTWI) or TWI established by the Joint Expert Committee on Food Additives (JECFA) and the European Food Safety Authority: 3.8 and 3.1% for regular consumers; and 0.4 and 0.3% for the whole adult population, respectively.
BACKGROUND: Guidelines for prevention of cardiovascular disease (CVD) include calculation of total risk. A new risk model based on updated Norwegian data is needed, as the European SCORE function overestimates the risk of fatal CVD in Norway. NORRISK for 10-year CVD mortality is presented. It includes gender, age and smoking and levels of systolic blood pressure and serumtotal cholesterol. MATERIAL AND METHODS: NORRISK is based on national age- and sex specific mortality rates from Statistics Norway (1999-2003), mean levels of risk factors from Norwegian Health Surveys (2000-03) and relative risks from mortality follow-up of Norwegian Cardiovascular Screenings (1985-2002). The model is adjusted to the mortality level in the period 1999-2003 and is compared with the SCORE model. RESULTS: 10-year risk estimates calculated from NORRISK fall between SCORE high- and low-risk estimates and increase strongly with age. Very few persons below 50 years of age have a 10-year risk above 5% (European limit for high risk). More than half of men aged 60 years have estimated risks above this limit, while only 7% of 60-year-old women exceed the limit. Even if the risk limit is reduced to 1% for younger age groups, very few women below 50 years of age have risks above the limit. INTERPRETATION: NORRISK is more adapted to the current situation in Norway than the SCORE model and may be a useful and relevant tool in Norwegian clinical practice.
BACKGROUND: Birth weight and length have seasonal fluctuations. Previous analyses of birth weight by latitude effects identified seemingly contradictory results, showing both 6 and 12 monthly periodicities in weight. The aims of this paper are twofold: (a) to explore seasonal patterns in a large, Danish Medical Birth Register, and (b) to explore models based on seasonal exposures and a non-linear exposure-risk relationship. METHODS: Birth weight and birth lengths on over 1.5 million Danish singleton, live births were examined for seasonality. We modelled seasonal patterns based on linear, U- and J-shaped exposure-risk relationships. We then added an extra layer of complexity by modelling weighted population-based exposure patterns. RESULTS: The Danish data showed clear seasonal fluctuations for both birth weight and birth length. A bimodal model best fits the data, however the amplitude of the 6 and 12 month peaks changed over time. In the modelling exercises, U- and J-shaped exposure-risk relationships generate time series with both 6 and 12 month periodicities. Changing the weightings of the population exposure risks result in unexpected properties. A J-shaped exposure-risk relationship with a diminishing population exposure over time fitted the observed seasonal pattern in the Danish birth weight data. CONCLUSION: In keeping with many other studies, Danish birth anthropometric data show complex and shifting seasonal patterns. We speculate that annual periodicities with non-linear exposure-risk models may underlie these findings. Understanding the nature of seasonal fluctuations can help generate candidate exposures.
The long-term prognosis of patients with ST-elevation myocardial infarction (STEMI) aged 45 years or younger and differences according to gender have not been well characterized.
We included 16,685 consecutive STEMI patients from 2003 to 2012 (67,992 patient-years follow-up) from the Eastern Danish Heart Registry and the Swedish Coronary Angiography and Angioplasty Registry who were treated with primary percutaneous coronary intervention (PCI).
We identified 1026 (6.2%) patients up to 45 years of age (mean age: 40.7 vs. 66.3 years, P
Comment In: Int J Cardiol. 2016 Jan 1;202:95326549565
Comment In: Int J Cardiol. 2016 May 1;210:54-526925922