A pleiotropy scan to discover new susceptibility loci for pancreatic ductal adenocarcinoma

Pleiotropic variants (i.e., genetic polymorphisms influencing more than one phenotype) are often associated with cancer risk. A scan of pleiotropic variants was successfully conducted ten years ago in relation to pancreatic ductal adenocarcinoma susceptibility. However, in the last decade, genetic association studies performed on several human traits have greatly increased the number of known pleiotropic variants. Based on the hypothesis that variants already associated with a least one trait have a higher probability of association with other traits, 61,052 variants reported to be associated by at least one genome wide association study (GWAS) with at least one human trait were tested in the present study consisting of two phases (discovery and validation), comprising a total of 16,055 pancreatic ductal adenocarcinoma (PDAC) cases and 212,149 controls. The meta-analysis of the two phases showed two loci (10q21.1-rs4948550 (P=6.52×10-5) and 7q36.3-rs288762 (P=3.03×10-5) potentially associated with PDAC risk. 10q21.1-rs4948550 shows a high degree of pleiotropy and it is also associated with colorectal cancer risk while 7q36.3-rs288762 is situated 28,558 base pairs upstream of the Sonic Hedgehog (SHH) gene, which is involved in the cell differentiation process and PDAC etiopathogenesis. In conclusion, none of the single nucleotide polymorphisms (SNPs) showed a formally statistically significant association after correction for multiple testing. However, given their pleiotropic nature and association with various human traits including colorectal cancer, the two SNPs showing the best associations with PDAC risk merit further investigation through fine mapping and ad hoc functional studies.

Post-operative C-reactive protein as a strong independent predictor of long-term colorectal cancer outcomes: consistent findings from two large patient cohorts

BACKGROUND

Post-surgery blood-based biomarkers may be useful for guiding treatment and surveillance decisions among colorectal cancer (CRC) patients. However, most candidate biomarkers provide little if any predictive value beyond stage at diagnosis. We aimed to investigate the independent prognostic value of post-operative serum C-reactive protein (CRP), a highly sensitive biomarker of inflammation, for long-term CRC outcomes in two large patient cohorts.

MATERIALS AND METHODS

CRP levels were measured from serum samples of CRC patients collected ≥1 month post-surgery in the German DACHS (n = 1416) and the UK Biobank (n = 1149) cohorts. Associations of post-operative CRP with overall survival (OS) and CRC-specific survival (CSS) were assessed using Cox regression and presented as hazard ratios (HRs) with 95% confidence intervals (CIs), adjusted for key sociodemographic and clinical covariates.

RESULTS

In both cohorts, consistent strong dose-response relationships between post-operative CRP and both OS and CSS were observed. Adjusted HRs (95% CI) for CRP >10 versus <3 mg/l were 1.93 (1.58-2.35) and 2.70 (2.03-3.59) in the DACHS cohort, and 2.70 (1.96-3.71) and 2.61 (1.83-3.72) in the UK Biobank cohort, respectively. Associations between post-operative CRP and OS were particularly strong among younger patients (<65 years at diagnosis; P value for interaction by age <0.01).

CONCLUSIONS

Serum CRP determined a month or more after surgery may be useful as a strong independent prognostic biomarker for guiding therapeutic decisions and for surveillance of the course of disease of CRC patients, particularly those <65 years of age at diagnosis.

Genome-wide association studies and Mendelian randomization analyses provide insights into the causes of early-onset colorectal cancer

BACKGROUND

The incidence of early-onset colorectal cancer (EOCRC; diagnosed <50 years of age) is rising globally; however, the causes underlying this trend are largely unknown. CRC has strong genetic and environmental determinants, yet common genetic variants and causal modifiable risk factors underlying EOCRC are unknown. We conducted the first EOCRC-specific genome-wide association study (GWAS) and Mendelian randomization (MR) analyses to explore germline genetic and causal modifiable risk factors associated with EOCRC.

PATIENTS AND METHODS

We conducted a GWAS meta-analysis of 6176 EOCRC cases and 65 829 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), the Colorectal Transdisciplinary Study (CORECT), the Colon Cancer Family Registry (CCFR), and the UK Biobank. We then used the EOCRC GWAS to investigate 28 modifiable risk factors using two-sample MR.

RESULTS

We found two novel risk loci for EOCRC at 1p34.1 and 4p15.33, which were not previously associated with CRC risk. We identified a deleterious coding variant (rs36053993, G396D) at polyposis-associated DNA repair gene MUTYH (odds ratio 1.80, 95% confidence interval 1.47-2.22) but show that most of the common genetic susceptibility was from noncoding signals enriched in epigenetic markers present in gastrointestinal tract cells. We identified new EOCRC-susceptibility genes, and in addition to pathways such as transforming growth factor (TGF) β, suppressor of Mothers Against Decapentaplegic (SMAD), bone morphogenetic protein (BMP) and phosphatidylinositol kinase (PI3K) signaling, our study highlights a role for insulin signaling and immune/infection-related pathways in EOCRC. In our MR analyses, we found novel evidence of probable causal associations for higher levels of body size and metabolic factors-such as body fat percentage, waist circumference, waist-to-hip ratio, basal metabolic rate, and fasting insulin-higher alcohol drinking, and lower education attainment with increased EOCRC risk.

CONCLUSIONS

Our novel findings indicate inherited susceptibility to EOCRC and suggest modifiable lifestyle and metabolic targets that could also be used to risk-stratify individuals for personalized screening strategies or other interventions.

Life expectancy associated with different ages at diagnosis of type 2 diabetes in high-income countries: 23 million person-years of observation

BACKGROUND

The prevalence of type 2 diabetes is increasing rapidly, particularly among younger age groups. Estimates suggest that people with diabetes die, on average, 6 years earlier than people without diabetes. We aimed to provide reliable estimates of the associations between age at diagnosis of diabetes and all-cause mortality, cause-specific mortality, and reductions in life expectancy.

METHODS

For this observational study, we conducted a combined analysis of individual-participant data from 19 high-income countries using two large-scale data sources: the Emerging Risk Factors Collaboration (96 cohorts, median baseline years 1961-2007, median latest follow-up years 1980-2013) and the UK Biobank (median baseline year 2006, median latest follow-up year 2020). We calculated age-adjusted and sex-adjusted hazard ratios (HRs) for all-cause mortality according to age at diagnosis of diabetes using data from 1 515 718 participants, in whom deaths were recorded during 23·1 million person-years of follow-up. We estimated cumulative survival by applying age-specific HRs to age-specific death rates from 2015 for the USA and the EU.

FINDINGS

For participants with diabetes, we observed a linear dose-response association between earlier age at diagnosis and higher risk of all-cause mortality compared with participants without diabetes. HRs were 2·69 (95% CI 2·43-2·97) when diagnosed at 30-39 years, 2·26 (2·08-2·45) at 40-49 years, 1·84 (1·72-1·97) at 50-59 years, 1·57 (1·47-1·67) at 60-69 years, and 1·39 (1·29-1·51) at 70 years and older. HRs per decade of earlier diagnosis were similar for men and women. Using death rates from the USA, a 50-year-old individual with diabetes died on average 14 years earlier when diagnosed aged 30 years, 10 years earlier when diagnosed aged 40 years, or 6 years earlier when diagnosed aged 50 years than an individual without diabetes. Using EU death rates, the corresponding estimates were 13, 9, or 5 years earlier.

INTERPRETATION

Every decade of earlier diagnosis of diabetes was associated with about 3-4 years of lower life expectancy, highlighting the need to develop and implement interventions that prevent or delay the onset of diabetes and to intensify the treatment of risk factors among young adults diagnosed with diabetes.

FUNDING

British Heart Foundation, Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.

Biomarker-based prediction of fatal and non-fatal cardiovascular outcomes in individuals of the general population with and without diabetes mellitus

Introduction

Cardiovascular biomarkers may reflect different aspects of cardiovascular disease, including myocardial tissue damage (high-sensitive cardiac troponin [hs-cTn]), hemodynamic stress (N-terminal prohormone of brain natriuretic peptide [NT-proBNP)), or inflammation (high-sensitivity C-reactive protein [hs-CRP]).

Purpose

To determine the risk for fatal and non-fatal cardiovascular events in patients with diabetes mellitus (DM), a high-risk group for cardiovascular complications, after accounting for these biomarkers and to determine the risk associated with these biomarkers.

Methods

Harmonized data of population-based studies from the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomaCaRE) and MOnica Risk, Genetics, Archiving and Monograph (MORGAM) consortia were used to calculate hazard ratios (HRs, 95% confidence intervals [CI] per standard deviation) for these biomarkers adjusted for diabetes, patient characteristics and biomarkers for their association with the primary endpoint of fatal and non-fatal cardiovascular events during a median follow-up of 9.6 years (maximum 28 years). Additionally, a years-of-life-lost analysis was conducted stratified by prevalent diabetes and specific biomarker cut-offs known to be associated with increased risk for events (hs-cTnI &gt;5 ng/L, NTproBNP &gt;125 ng/L, hs-CRP &gt;5mg/L).

Results

We included 95,302 individuals, of whom 6,501 had DM (6.8%). Cox-regression analysis revealed DM to be independently associated with the primary endpoint (2.1 [95% CI 1.9, 2.3], p&lt;0.001) despite adjustment for clinical characteristics and biomarkers. Also, all three biomarkers were independent predictors themselves: log-transformed NT-proBNP 1.3 [95% CI 1.3, 1.4] p&lt;0.001; log-transformed hs-CRP 1.2 [95% CI 1.1, 1.2] p&lt;0.001; third-root-transformed hs-cTnI 1.1 [95% CI 1.0, 1.1] p=0.0038). The sex-, age- and cohort-adjusted HR for the primary endpoint according to absolute biomarker concentrations derived by cox-regression models using cubic splines is provided for the three biomarkers in Figure 1. Upon dichotomization of biomarkers, individuals with diabetes and at least one elevated biomarker lost a median of 15.5 healthy years because of the primary endpoint (Kaplan-Meier plot in Figure 2, with age on the x-axis).

Conclusion

Our findings confirm that diabetes confers a residual cardiovascular risk beyond adjustment for clinical characteristics and cardiovascular biomarker. Furthermore, biomarkers may aid in the identification of patients at highest risk, which should be considered in future models of risk prediction.

Funding Acknowledgement

Type of funding sources: None.

Artificial intelligence for detection of microsatellite instability in colorectal cancer-a multicentric analysis of a pre-screening tool for clinical application

BACKGROUND

Microsatellite instability (MSI)/mismatch repair deficiency (dMMR) is a key genetic feature which should be tested in every patient with colorectal cancer (CRC) according to medical guidelines. Artificial intelligence (AI) methods can detect MSI/dMMR directly in routine pathology slides, but the test performance has not been systematically investigated with predefined test thresholds.

METHOD

We trained and validated AI-based MSI/dMMR detectors and evaluated predefined performance metrics using nine patient cohorts of 8343 patients across different countries and ethnicities.

RESULTS

Classifiers achieved clinical-grade performance, yielding an area under the receiver operating curve (AUROC) of up to 0.96 without using any manual annotations. Subsequently, we show that the AI system can be applied as a rule-out test: by using cohort-specific thresholds, on average 52.73% of tumors in each surgical cohort [total number of MSI/dMMR = 1020, microsatellite stable (MSS)/ proficient mismatch repair (pMMR) = 7323 patients] could be identified as MSS/pMMR with a fixed sensitivity at 95%. In an additional cohort of N = 1530 (MSI/dMMR = 211, MSS/pMMR = 1319) endoscopy biopsy samples, the system achieved an AUROC of 0.89, and the cohort-specific threshold ruled out 44.12% of tumors with a fixed sensitivity at 95%. As a more robust alternative to cohort-specific thresholds, we showed that with a fixed threshold of 0.25 for all the cohorts, we can rule-out 25.51% in surgical specimens and 6.10% in biopsies.

INTERPRETATION

When applied in a clinical setting, this means that the AI system can rule out MSI/dMMR in a quarter (with global thresholds) or half of all CRC patients (with local fine-tuning), thereby reducing cost and turnaround time for molecular profiling.

Association of glycated haemoglobin A1c levels with cardiovascular outcomes in the general population: results from the BiomarCaRE consortium

Background

Glycated haemoglobin A1c (HbA1c) is used to monitor the quality of diabetes treatment; however, its role in predicting cardiovascular outcomes in the general population remains uncertain.

Purpose

The additional use of glycated haemoglobin A1c (HbA1c) as a biomarker might highlight subjects of the general population with an increased risk for cardiovascular outcomes with cardiovascular disease, cardiovascular mortality or overall-mortality.

Methods

Data from six prospective population-based cohort studies across Europe comprising 36,180 participants were analysed. HbA1c was evaluated in conjunction with classical cardiovascular risk factors (CVRFs) for association with cardiovascular mortality, cardiovascular diseases (CVD), and overall mortality in the study population, in non-diabetic (N=32,477), and diabetic participants (N=3,703).

Results

Kaplan-Meier curves showed higher event rates with increasing continuous log-transformed HbA1c levels. Cox regression analysis revealed significant associations between HbA1c (in mmol/mol) log-transformed divided by interquartile range and the examined outcomes, with a hazard ratio (HR) of 1.12 (95% confidence interval (CI): 1.04–1.20, p=0.0019) for cardiovascular mortality, 1.10 (95% CI: 1.04–1.16, p&lt;0.001) for CVD, and 1.09 (95% CI: 1.05–1.14, p&lt;0.001) for overall mortality per one unit increase.

An increased risk of CVD was observed in subjects without diabetes with increased HbA1c levels (HR 1.09; 95% CI: 1.01–1.16, p=0.021). An HbA1c cut-off value of 39.89 mmol/mol (5.8%), 36.62 mmol/mol (5.5%), and 38.80 mmol/mol (5.7%) for cardiovascular mortality, CVD, and overall mortality, respectively, was determined for selecting individuals at an increased risk.

Conclusion

HbA1c was demonstrated to be an independent prognostic biomarker for all investigated outcomes in the general European population. An approximately linear relationship was observed between an increase of HbA1c levels and the outcomes. Elevated HbA1c levels were also associated with the outcomes in participants without diabetes (i.e. HbA1c levels &lt;6.5% (&lt;48mmol/mol) which underlines the importance of HbA1c levels in the overall population.

Funding Acknowledgement

Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union Seventh Framework ProgrammeEuropean Union FP 7 project CHANCES Kaplan-Meier curves for the outcomesPenalised cubic splines HbA1c/time event

Prediction of clinical diagnosis of Alzheimer's disease, vascular, mixed, and all-cause dementia by a polygenic risk score and APOE status in a community-based cohort prospectively followed over 17 years

The strongest genetic risk factor for Alzheimer's disease (AD) is the ε4 allele of Apolipoprotein E (APOE) and recent genome-wide association meta-analyses have confirmed additional associated genetic loci with smaller effects. The aim of this study was to investigate the ability of an AD polygenic risk score (PRS) and APOE status to predict clinical diagnosis of AD, vascular (VD), mixed (MD), and all-cause dementia in a community-based cohort prospectively followed over 17 years and secondarily across age, sex, and education strata. A PRS encompassing genetic variants reaching genome-wide significant associations to AD (excluding APOE) from the most recent genome-wide association meta-analysis data was calculated and APOE status was determined in 5203 participants. During follow-up, 103, 111, 58, and 359 participants were diagnosed with AD, VD, MD, and all-cause dementia, respectively. Prediction ability of AD, VD, MD, and all-cause dementia by the PRS and APOE was assessed by multiple logistic regression and receiver operating characteristic curve analyses. The PRS per standard deviation increase in score and APOE4 positivity (≥1 ε4 allele) were significantly associated with greater odds of AD (OR, 95% CI: PRS: 1.70, 1.45-1.99; APOE4: 3.34, 2.24-4.99) and AD prediction accuracy was significantly improved when adding the PRS to a base model of age, sex, and education (ASE) (c-statistics: ASE, 0.772; ASE + PRS, 0.810). The PRS enriched the ability of APOE to discern AD with stronger associations than to VD, MD, or all-cause dementia in a prospective community-based cohort.

Lifestyle factors and risk of sporadic colorectal cancer by microsatellite instability status: a systematic review and meta-analyses

Introduction

The association of lifestyle factors with molecular pathological subtypes of colorectal cancer (CRC), such as microsatellite instability (MSI), could provide further knowledge about the colorectal carcinogenic process. The aim of this review was to evaluate possible associations between lifestyle factors and risk of sporadic CRC by MSI status.

Methods

PubMed and Web of Science were searched for studies investigating the association between alcohol, body mass index, dietary fiber, hormone replacement therapy (HRT), non-steroidal anti-inflammatory drugs, physical activity, red meat, smoking, or statin use, with MSI-high (MSI-H) and microsatellite stable (MSS) CRC. Meta-analyses were carried out to calculate summary relative risks (sRR).

Results

Overall, 31 studies reporting on the association between lifestyle factors and CRC according to MSI status were included in this review. Ever smoking was associated with MSI-H (sRR = 1.62; 95% CI: 1.40-1.88) and MSS/MSI-low CRC (sRR = 1.10; 95% CI: 1.01-1.20), but the association was significantly stronger for MSI-H CRC. The use of HRT was associated with a 20% decrease (sRR = 0.80; 95% CI: 0.73-0.89) in the risk of MSS CRC, but was not associated with MSI-H CRC. An increase in body mass index per 5 kg/m2 was equally associated with MSS and MSI-H CRC (sRR = 1.22, in both cases), but was statistically significant for MSS CRC only (95% CI: 1.11-1.34 and 0.94-1.58, respectively). Limited evidence for associations between other lifestyle factors and CRC by MSI status exists.

Conclusions

Lifestyle factors, such as HRT and smoking are differentially associated with the risk of MSI-H and MSS CRC. Further research on associations of lifestyle factors and CRC subtypes is necessary to provide a better understanding of the CRC disease pathway.

Screening for gastric cancer using exhaled breath samples

BACKGROUND

The aim was to derive a breath-based classifier for gastric cancer using a nanomaterial-based sensor array, and to validate it in a large screening population.

METHODS

A new training algorithm for the diagnosis of gastric cancer was derived from previous breath samples from patients with gastric cancer and healthy controls in a clinical setting, and validated in a blinded manner in a screening population.

RESULTS

The training algorithm was derived using breath samples from 99 patients with gastric cancer and 342 healthy controls, and validated in a population of 726 people. The calculated training set algorithm had 82 per cent sensitivity, 78 per cent specificity and 79 per cent accuracy. The algorithm correctly classified all three patients with gastric cancer and 570 of the 723 cancer-free controls in the screening population, yielding 100 per cent sensitivity, 79 per cent specificity and 79 per cent accuracy. Further analyses of lifestyle and confounding factors were not associated with the classifier.

CONCLUSION

This first validation of a nanomaterial sensor array-based algorithm for gastric cancer detection from breath samples in a large screening population supports the potential of this technology for the early detection of gastric cancer.

Incident depression and mortality among people with different types of dementia: results from a longitudinal cohort study

PURPOSE

The aim of this study was to investigate the independent and combined association of incident depression and dementia with mortality and to explore whether the magnitude of the association varies according to different types of dementia, including Alzheimer's disease and vascular dementia.

METHODS AND DESIGN

The study was based on a population-based longitudinal cohort consisting of 9940 participants at baseline and followed for over 14 years. The sample used for the analyses included 6114 participants with available information on diagnosis of incident dementia and depression. For survival analyses, Cox regression models with incident dementia (n = 293; 5%) and incident depression (n = 746; 12%) as time-dependent variables were used.

RESULTS

Cox models adjusted for relevant confounders indicated that comorbidity of incident vascular dementia and incident depression was associated with a much higher mortality risk (HR 6.99; 95% CI 3.84-12.75) than vascular dementia in the absence of depression (HR 2.80; 95% CI 1.92-4.08). In contrast, estimates for comorbidity of Alzheimer's disease and depression were slightly lower than those for Alzheimer in absence of depression (HR 3.56; 95% CI 1.83-6.92 and HR 4.19; 95% CI 2.97-5.90, respectively). Incident depression in the absence of incident dementia was only weakly associated with mortality.

CONCLUSIONS

These findings indicate that depression and vascular dementia might have synergistic effects on mortality. The results have relevant public health implications for prevention, routine screening for and early treatment of depression among older people, especially those at risk of vascular dementia.

Meeting report from the joint IARC-NCI international cancer seminar series: a focus on colorectal cancer

Despite significant progress in our understanding of the etiology, biology and genetics of colorectal cancer, as well as important clinical advances, it remains the third most frequently diagnosed cancer worldwide and is the second leading cause of cancer death. Based on demographic projections, the global burden of colorectal cancer would be expected to rise by 72% from 1.8 million new cases in 2018 to over 3 million in 2040 with substantial increases anticipated in low- and middle-income countries. In this meeting report, we summarize the content of a joint workshop led by the National Cancer Institute and the International Agency for Research on Cancer, which was held to summarize the important achievements that have been made in our understanding of colorectal cancer etiology, genetics, early detection and treatment and to identify key research questions that remain to be addressed.

Association of generalized anxiety symptoms and panic with health care costs in older age-Results from the ESTHER cohort study

BACKGROUND

Little is known specifically about the association between generalized anxiety symptoms or panic and health care costs in older age. The aim of this study was to examine the association between generalized anxiety symptoms, panic and health care costs in people aged 65 and over.

METHODS

Cross-sectional data from the 8-year follow-up of a large, prospective cohort study, the ESTHER study, was used. Individuals aged 65 and over, who participated in the study's home assessment, were included in this analysis (n = 2348). Total and sectoral costs were analyzed as a function of either anxiety symptoms, probable panic disorder, or a panic attack, while controlling for selected covariates, using Two Part and Generalized Linear Models. Covariates were chosen based on Andersen's Behavioral Model of Health Care Use.

RESULTS

There was no significant association between either of the anxiety or panic measures and total health care costs. Stratified by health care sectors, only the occurrence of a panic attack was significantly associated with incurring costs for outpatient non-physician services (OR: 1.99; 95% CI: 1.15-3.45) and inpatient services (OR: 2.14; 95% CI: 1.07-4.28). Other illness-related factors, such as comorbidities and depressive symptoms, were associated with health care costs in several models.

LIMITATIONS

This was a cross-sectional study relying on self-reported data.

CONCLUSION

This study points to an association between a panic attack and sector-specific health care costs in people aged 65 and over. Further research, especially using longitudinal data, is needed.

Topography of cancer-associated immune cells in human solid tumors

Lymphoid and myeloid cells are abundant in the tumor microenvironment, can be quantified by immunohistochemistry and shape the disease course of human solid tumors. Yet, there is no comprehensive understanding of spatial immune infiltration patterns (‘topography’) across cancer entities and across various immune cell types. In this study, we systematically measure the topography of multiple immune cell types in 965 histological tissue slides from N = 177 patients in a pan-cancer cohort. We provide a definition of inflamed (‘hot’), non-inflamed (‘cold’) and immune excluded patterns and investigate how these patterns differ between immune cell types and between cancer types. In an independent cohort of N = 287 colorectal cancer patients, we show that hot, cold and excluded topographies for effector lymphocytes (CD8) and tumor-associated macrophages (CD163) alone are not prognostic, but that a bivariate classification system can stratify patients. Our study adds evidence to consider immune topographies as biomarkers for patients with solid tumors.

Unterschiede in der Morbidität nach Krankenversichertenstatus im Alter

Ziel der Studie: Es fehlen bislang Studien, die Morbiditätsunterschiede zwischen GKV und PKV in der älteren Bevölkerung untersuchen. Ziel dieser Studie ist es daher, Unterschiede in der Morbidität zwischen den Versicherten der GKV und PKV im Alter aufzudecken.

Methodik: Es wurden Daten von 2 Follow-Up-Wellen mit einem Abstand von 3 Jahren herangezogen. Diese basieren auf einer bevölkerungsbezogenen Kohortenstudie (ESTHER Studie) im Saarland. Die Morbidität wurde durch Hausarztangaben mit einem generischen Instrument (Cumulative Illness Rating Scale for Geriatrics) erfasst. Zur Schätzung wurde der Between-Schätzer herangezogen, der ausschließlich die Variation zwischen den Individuen quantifiziert. Dabei wurde im Basismodell neben dem Versichertenstatus für das Geschlecht und das Alter kontrolliert. In weiteren Modellen wurde sukzessive ebenfalls für Schulbildung, den Familienstand und das Einkommen kontrolliert.

Ergebnisse: Während in den Spezifikationen ohne Berücksichtigung des Einkommens beträchtliche Unterschiede in der Morbidität zwischen PKV- und GKV-Versicherten erkennbar waren, mindert sich dieser Effekt unter Kontrolle des Einkommens stark und war bei Männern nicht mehr signifikant.

Schlussfolgerung: Zu einem bedeutenden Teil können existierende Morbiditätsunterschiede zwischen Versicherten der GKV und PKV durch Einkommensunterschiede zwischen den beiden Gruppen erklärt werden. Dies zeigt die große Bedeutung der Ausgestaltung des Modells bei der Untersuchung von Morbiditätsunterschieden zwischen GKV und PKV auf.

Osteoarthritis-patterns, cardio-metabolic risk factors and risk of all-cause mortality: 20 years follow-up in patients after hip or knee replacement

Osteoarthritis (OA) is a common musculoskeletal disorder and occur in different patterns. However, its impact on long-term all-cause-mortality is inconclusive. Study aims: Investigate 20-year all-cause-mortality in patients with hip/knee arthroplasty (recruited 1995/1996, N = 809) from the Ulm Osteoarthritis Study-cohort, in comparison to general population. Furthermore, to enlighten the triangle between baseline life-style and cardio-metabolic risk factors, phenotypic OA-patterns (laterality, generalization, cause) and all-cause-mortality. Mortality was assessed during 20 years follow-up. Standardized mortality ratios (SMR), adjusted odds ratios and hazard ratios (aHR) were calculated. After five years cohort-mortality was reduced compared to the general population, however 20 years later assimilated (SMR = 1.11; 95%-CI 0.73-1.49). OA-patterns were associated with age, cholesterol, and overweight/obesity. In comparison to primary OA decreased mortality was observed for patients with secondary OA (aHR = 0.76; 95%-CI 0.61-0.95) adjusted for age, smoking, overweight/obesity, diabetes, hypertension, cardiac insufficiency, uric acid, and lower cholesterol. There was no increased mortality in patients after 20 years follow-up compared to general population. Significantly decreased mortality in secondary compared to primary OA suggests a subtype-specific involvement of systemic co-factors in determination of all-cause-mortality. Because cardio-metabolic risk factors were associated with increased risk of bilateral OA and lower long-term survival, those risk factors should be consequently targeted in OA-patients.

Application of Capture-Recapture Methods for Disease Monitoring: Potential Effects of Imperfect Record Linkage

Capture-recapture methods are increasingly employed to correct for underascertainment of cases in disease monitoring. Routine systems of disease monitoring, such as morbidity registries, are often prone to specific threats of validity, such as in imperfect diagnoses or imperfect record linkage. A quantitative assessment is given of the performance of the two-source capture-recapture method for disease monitoring in the presence of imperfect record linkage. The capture-recapture approach can eliminate underestimation of the number of eligible cases, which is typical for most disease monitoring systems, under certain conditions, including independence of sources of case ascertainment and perfect record linkage. Correction for underestimation remains less than perfect, however, in the case of false-positive matches, whereas application of capture-recapture methods leads to overestimation of case numbers in the presence of false-negative matches. A simple correction procedure to overcome potential overestimation by false-negative matches is outlined.

How to Correct for Chance Agreement in the Estimation of Sensitivity and Specificity of Diagnostic Tests

The traditional concept of describing the validity of a diagnostic test neglects the presence of chance agreement between test result and true (disease) status. Sensitivity and specificity, as the fundamental measures of validity, can thus only be considered in conjunction with each other to provide an appropriate basis for the evaluation of the capacity of the test to discriminate truly diseased from truly undiseased subjects. In this paper, chance-corrected analogues of sensitivity and specificity are presented as supplemental measures of validity, which pay attention to the problem of chance agreement and offer the opportunity to be interpreted separately. While recent proposals of chance-correction techniques, suggested by several authors in this context, lead to measures which are dependent on disease prevalence, our method does not share this major disadvantage. We discuss the extension of the conventional ROC-curve approach to chance-corrected measures of sensitivity and specificity. Furthermore, point and asymptotic interval estimates of the parameters of interest are derived under different sampling frameworks for validation studies. The small sample behavior of the estimates is investigated in a simulation study, leading to a logarithmic modification of the interval estimate in order to hold the nominal confidence level for small samples.

More Up-To-Date Monitoring of Long-Term Survival Rates by Cancer Registries: An Empirical Example

A few years ago, a new method of survival analysis, denoted period analysis, has been developed to derive more up-to-date estimates of long-term survival rates of cancer patients, but this method has rarely been applied so far. Using empirical examples from the Saarland Cancer Registry, we illustrate how seriously traditional long-term survival estimates may lag behind survival expectations of newly diagnosed cancer patients in the case of recent improvement in prognosis, and to what extent this problem may be reduced by period analysis of survival. We conclude that period analysis should be more widely used for deriving more up-to-date long-term survival estimates.

Effects of Record Linkage Errors on Disease Registration

Reliable record linkage is a prerequisite for high-quality population-based disease registration. Rapid developments in computer processing have made record linkage both more efficient and more reliable in recent years. At the same time, concerns about confidentiality increasingly hinder record linkage in many disease registries. This paper provides basic algebraic models describing the effects of record linkage errors on monitoring disease incidence. Homonym errors, that is, erroneous linkage of records that pertain to distinct individuals, lead to underestimation of incidence in the registry population. The degree of underestimation strongly depends on the discriminating power of personal identifiers and the record linkage procedure on the one hand, and the number of registered cases on the other hand. Synonym errors, that is, failure to link notifications on the same individual, lead to overestimation of incidence in the population base. The combined effects of record linkage errors are illustrated with empirical examples. We conclude that it is the largest and most informative disease registries that are potentially affected most by impediments of record linkage procedures due to unduly restrictive confidentiality rules.

A Computer Program to Estimate Power and Relative Efficiency of Flexibly Matched Case-control Studies

Objectives: We recently introduced the concept of flexible matching strategies with varying proportions of a dichotomous matching factor among controls to increase power and efficiency of case-control studies. We now present a method and a computer program to calculate power and relative efficiency compared to an unmatched design varying the proportion of the matching factor in controls over all possible values from 0 to 100 percent.

Methods: For all these values, the program calculates the expected variance of the combined Mantel-Haenszel odds ratio and determines the power using the standard error of the expected combined Mantel-Haenszel odds ratio under the null hypothesis as derived from the Mantel-Haenszel test statistic without continuity correction.

Results: Thereby, the program allows estimating the optimal prevalence of the matching factor in selected controls for a given scenario which often differs from the prevalence in cases. It furthermore allows to estimate loss in power and efficiency compared to optimal matching by suboptimal matching.

Conclusions: Estimations like these are helpful with respect to the decision when to stop efforts to optimize the degree of matching during the recruitment of controls. Our program will strongly facilitate assessing the benefits of flexible matching strategies.

Impact of prediagnostic smoking and smoking cessation on colorectal cancer prognosis: a meta-analysis of individual patient data from cohorts within the CHANCES consortium

Background

Smoking has been associated with colorectal cancer (CRC) incidence and mortality in previous studies and might also be associated with prognosis after CRC diagnosis. However, current evidence on smoking in association with CRC prognosis is limited.

Patients and methods

For this individual patient data meta-analysis, sociodemographic and smoking behavior information of 12 414 incident CRC patients (median age at diagnosis: 64.3 years), recruited within 14 prospective cohort studies among previously cancer-free adults, was collected at baseline and harmonized across studies. Vital status and causes of death were collected for a mean follow-up time of 5.1 years following cancer diagnosis. Associations of smoking behavior with overall and CRC-specific survival were evaluated using Cox regression and standard meta-analysis methodology.

Results

A total of 5229 participants died, 3194 from CRC. Cox regression revealed significant associations between former [hazard ratio (HR) = 1.12; 95 % confidence interval (CI) = 1.04-1.20] and current smoking (HR = 1.29; 95% CI = 1.04-1.60) and poorer overall survival compared with never smoking. Compared with current smoking, smoking cessation was associated with improved overall (HR<10 years = 0.78; 95% CI = 0.69-0.88; HR≥10 years = 0.78; 95% CI = 0.63-0.97) and CRC-specific survival (HR≥10 years = 0.76; 95% CI = 0.67-0.85).

Conclusion

In this large meta-analysis including primary data of incident CRC patients from 14 prospective cohort studies on the association between smoking and CRC prognosis, former and current smoking were associated with poorer CRC prognosis compared with never smoking. Smoking cessation was associated with improved survival when compared with current smokers. Future studies should further quantify the benefits of nonsmoking, both for cancer prevention and for improving survival among CRC patients, in particular also in terms of treatment response.

periodR – an R Package to Calculate Long-term Cancer Survival Estimates Using Period Analysis

Objective: In this paper, a software package for the R language and system for statistical computing is presented for computation of long-term cancer survival estimates based on the period analysis approach. The period analysis approach provides up-to-date long-term survival estimates of concurrently diagnosed patients, enables early detection of recent changes in long-term prognosis of cancer patients and provides better survival predictions for recently and currently diagnosed patients than traditional cohort-based approaches.

Methods: Computation of absolute and relative survival estimates (both conditional follow-up year-specific and cumulative survival estimates) and their standard errors is based on standard actuarial methodology. For relative survival estimation the “Ederer II” and “Hakulinen” method were implemented.

Results: The package may be used for period analysis as well as traditional cohort-based survival estimation. The package further provides functions for the export of survival estimates for use with spreadsheet programs and for plotting survival curves. The application of period analysis is illustrated using stomach cancer data included in the package.

Conclusion: Application of period analysis has gradually increased in recent years but continues to be limited by availability of affordable and easy-to-use software tools. The presented R package aims at closing this gap and will further facilitate the use of period analysis for the research community working with population-based cancer registry data. The software is freely available for download on the website of the Saarland Cancer Registry at http://www.krebsregister.saarland.de improve/periodR_en.html.

New approach shows no association between maternal milk fatty acid composition and childhood wheeze or asthma

BACKGROUND

Previous observational studies have implied breastmilk fatty acid composition may play a role in the development of atopic eczema or atopic sensitization in breastfed infants and toddlers. However, studies investigating associations with wheeze and asthma in later childhood are scarce and did not account for inherent correlation of compositional data. Our aim was to explore the association of maternal milk fatty acid composition with childhood wheezing phenotypes and asthma up to age 13 years using a new statistical approach.

METHODS

Breastmilk was collected 6 weeks and 6 months postdelivery in the Ulm Birth Cohort Study (n=720 and n=454, respectively). Concentrations of 28 fatty acids were measured by high-resolution capillary gas-liquid chromatography. To control for constant-sum constraint, concentration data were transformed using the centered log ratio method. Compositional biplots and correlation matrices were used to group centered log ratio transformed fatty acids. Adjusted risk ratios with parent-reported wheezing phenotypes and doctor-diagnosed asthma were computed using a modified Poisson regression.

RESULTS

We observed no straightforward evidence of associations between overall breastmilk fatty acid composition and specific wheeze phenotypes or doctor-diagnosed asthma.

CONCLUSION

Using appropriate statistical methodology, we report null associations. These findings may partly be attributable to several cohort-specific factors associated with breastfeeding and breastmilk collection. Further studies could improve on ours by analyzing samples of breastmilk and formula and by including all children for whom these are exclusively or together the major source of fatty acids in the first months of life.

Relations between lipoprotein(a) concentrations, LPA genetic variants, and the risk of mortality in patients with established coronary heart disease: a molecular and genetic association study

BACKGROUND

Lipoprotein(a) concentrations in plasma are associated with cardiovascular risk in the general population. Whether lipoprotein(a) concentrations or LPA genetic variants predict long-term mortality in patients with established coronary heart disease remains less clear.

METHODS

We obtained data from 3313 patients with established coronary heart disease in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. We tested associations of tertiles of lipoprotein(a) concentration in plasma and two LPA single-nucleotide polymorphisms ([SNPs] rs10455872 and rs3798220) with all-cause mortality and cardiovascular mortality by Cox regression analysis and with severity of disease by generalised linear modelling, with and without adjustment for age, sex, diabetes diagnosis, systolic blood pressure, BMI, smoking status, estimated glomerular filtration rate, LDL-cholesterol concentration, and use of lipid-lowering therapy. Results for plasma lipoprotein(a) concentrations were validated in five independent studies involving 10 195 patients with established coronary heart disease. Results for genetic associations were replicated through large-scale collaborative analysis in the GENIUS-CHD consortium, comprising 106 353 patients with established coronary heart disease and 19 332 deaths in 22 studies or cohorts.

FINDINGS

The median follow-up was 9·9 years. Increased severity of coronary heart disease was associated with lipoprotein(a) concentrations in plasma in the highest tertile (adjusted hazard radio [HR] 1·44, 95% CI 1·14-1·83) and the presence of either LPA SNP (1·88, 1·40-2·53). No associations were found in LURIC with all-cause mortality (highest tertile of lipoprotein(a) concentration in plasma 0·95, 0·81-1·11 and either LPA SNP 1·10, 0·92-1·31) or cardiovascular mortality (0·99, 0·81-1·2 and 1·13, 0·90-1·40, respectively) or in the validation studies.

INTERPRETATION

In patients with prevalent coronary heart disease, lipoprotein(a) concentrations and genetic variants showed no associations with mortality. We conclude that these variables are not useful risk factors to measure to predict progression to death after coronary heart disease is established.

FUNDING

Seventh Framework Programme for Research and Technical Development (AtheroRemo and RiskyCAD), INTERREG IV Oberrhein Programme, Deutsche Nierenstiftung, Else-Kroener Fresenius Foundation, Deutsche Stiftung für Herzforschung, Deutsche Forschungsgemeinschaft, Saarland University, German Federal Ministry of Education and Research, Willy Robert Pitzer Foundation, and Waldburg-Zeil Clinics Isny.

Excess mortality after hip fracture in elderly persons from Europe and the USA: the CHANCES project

BACKGROUND

Hip fractures are associated with diminished quality of life and survival especially amongst the elderly.

OBJECTIVE

All-cause mortality after hip fracture was investigated to assess its magnitude.

METHODS

A total of 122 808 participants from eight cohorts in Europe and the USA were followed up for a mean of 12.6 years, accumulating 4273 incident hip fractures and 27 999 deaths. Incident hip fractures were assessed through telephone interviews/questionnaires or national inpatient/fracture registries, and causes of death were verified with death certificates. Cox proportional hazards models and the time-dependent variable methodology were used to assess the association between hip fracture and mortality and its magnitude at different time intervals after the injury in each cohort. We obtained the effect estimates through a random-effects meta-analysis.

RESULTS

Hip fracture was positively associated with increased all-cause mortality; the hazard ratio (HR) in the fully adjusted model was 2.12, 95% confidence interval (CI) 1.76-2.57, after adjusting for potential confounders. This association was stronger amongst men [HR: 2.39, 95% CI: 1.72-3.31] than amongst women [HR: 1.92, 95% CI: 1.54-2.39], although this difference was not significant. Mortality was higher during the first year after the hip fracture [HR: 2.78, 95% CI: 2.12-3.64], but it remained elevated without major fluctuations after longer time since hip fracture [HR (95% CI): 1.89 (1.50-2.37) after 1-4 years; 2.15 (1.81-2.55) after 4-8 years; 1.79 (1.57-2.05) after 8 or more years].

CONCLUSION

In this large population-based sample of older persons across eight cohorts, hip fracture was associated with excess short- and long-term all-cause mortality in both sexes.