Validation of the Telephone Interview of Cognitive Status and Telephone Montreal Cognitive Assessment Against Detailed Cognitive Testing and Clinical Diagnosis of Mild Cognitive Impairment After Stroke.

BACKGROUND AND PURPOSE: Assessment of cognitive status poststroke is recommended by guidelines but follow-up can often not be done in person. The Telephone Interview of Cognitive Status (TICS) and the Telephone Montreal Cognitive Assessment (T-MoCA) are considered useful screening instruments. Yet, evidence to define optimal cut-offs for mild cognitive impairment (MCI) after stroke is limited. METHODS: We studied 105 patients enrolled in the prospective DEDEMAS study (Determinants of Dementia After Stroke; NCT01334749). Follow-up visits at 6, 12, 36, and 60 months included comprehensive neuropsychological testing and the Clinical Dementia Rating scale, both of which served as reference standards. The original TICS and T-MoCA were obtained in 2 separate telephone interviews each separated from the personal visits by 1 week (1 before and 1 after the visit) with the order of interviews (TICS versus T-MoCA) alternating between subjects. Area under the receiver-operating characteristic curves was determined. RESULTS: Ninety-six patients completed both the face-to-face visits and the 2 interviews. Area under the receiver-operating characteristic curves ranged between 0.76 and 0.83 for TICS and between 0.73 and 0.94 for T-MoCA depending on MCI definition. For multidomain MCI defined by multiple-tests definition derived from comprehensive neuropsychological testing optimal sensitivities and specificities were achieved at cut-offs <36 (TICS) and <18 (T-MoCA). Validity was lower using single-test definition, and cut-offs were higher compared with multiple-test definitions. Using Clinical Dementia Rating as the reference, optimal cut-offs for MCI were <36 (TICS) and approximately 19 (T-MoCA). CONCLUSIONS: Both the TICS and T-MoCA are valid screening tools poststroke, particularly for multidomain MCI using multiple-test definition.

Prevalence of Amyloid Positron Emission Tomographic Positivity in Poststroke Mild Cognitive Impairment.

BACKGROUND AND PURPOSE: Mild cognitive impairment (MCI) is common after stroke and associated with poor outcome. However, the mechanisms underlying poststroke MCI (PS-MCI) are insufficiently understood. We performed amyloid-ß positron emission tomography (PET) in a prospective cohort of stroke survivors to determine the role of amyloid pathology in PS-MCI. METHODS: We studied 178 consecutive patients enrolled into the prospective DEDEMAS study (Determinants of Dementia After Stroke). Follow-up visits 6 months post stroke included detailed cognitive testing, standardized magnetic resonance imaging, and amyloid-ß imaging using flutemetamol ((18)F) PET. MCI was defined by the modified Petersen criteria. Amyloid-positivity was assessed visually and quantitatively. Fifty-six (31%) patients agreed to undergo PET imaging. RESULTS: Thirty-eight (68%) patients who consented to PET imaging had PS-MCI. Visual assessment revealed amyloid PET positivity in 2 (5%) of the 38 PS-MCI patients and in 2 (11%) of the 18 cognitively healthy stroke survivors. There was no correlation between flutemetamol ((18)F) standardized uptake value ratios and cognitive scores in the 56 patients. PS-MCI patients had significant cognitive impairments on executive function (P<0.01) and memory tests (P<0.01) when compared with cognitively healthy stroke survivors (P<0.01). CONCLUSIONS: The prevalence of amyloid-pathology in patients with PS-MCI is not increased when compared with cognitively healthy stroke survivors and to recent estimates for cognitively healthy elderly subjects. Factors other than amyloid-pathology likely contribute to the development of PS-MCI. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01334749.

Impact of DMARD treatment and systemic inflammation on all-cause mortality in patients with rheumatoid arthritis and interstitial lung disease: a cohort study from the German RABBIT register.

OBJECTIVES: To investigate the impact of disease activity and treatment with disease-modifying antirheumatic drugs (DMARDs) on all-cause mortality in patients with rheumatoid arthritis and prevalent interstitial lung disease (RA-ILD). METHODS: Patients with RA-ILD were selected from the biologics register Rheumatoid Arthritis: Observation of Biologic Therapy (RABBIT). Using time-varying Cox regression, the association between clinical measures and mortality was investigated. The impact of DMARDs was analysed by (1) Cox regression considering cumulative exposure (ie, treatment months divided by total months) and (2) time-varying Cox regression as main approach (treatment exposures at monthly level). RESULTS: Out of 15 566 participants, 381 were identified as RA-ILD cases with 1258 person-years of observation and 2.6 years median length of follow-up. Ninety-seven patients (25.5%) died and 34 (35.1%) of these were not receiving DMARD therapy at the time of death. Higher inflammatory biomarkers but not swollen and tender joint count were significantly associated with mortality. Compared with tumour necrosis factor inhibitors (TNFi), non-TNFi biologic DMARDs (bDMARDs) exhibited adjusted HRs (aHRs) for mortality below 1, lacking statistical significance. This finding was stable in various sensitivity analyses. Joint aHR for non-TNFi biologics and JAKi versus TNFi was 0.56 (95% CI 0.33 to 0.97). Receiving no DMARD treatment was associated with a twofold higher mortality risk compared with receiving any DMARD treatment, aHR 2.03 (95% CI 1.23 to 3.35). CONCLUSIONS: Inflammatory biomarkers and absence of DMARD treatment were associated with increased risk of mortality in patients with RA-ILD. Non-TNFi bDMARDs may confer enhanced therapeutic benefits in patients with RA-ILD.

Subclinical hyperthyroidism is a risk factor for poor functional outcome after ischemic stroke.

BACKGROUND AND PURPOSE: Subclinical hyperthyroidism is associated with adverse cardiovascular events, including stroke and atrial fibrillation. However, its impact on functional outcome after stroke remains unexplored. METHODS: A total of 165 consecutively recruited patients admitted for ischemic stroke were included in this observational prospective study. Blood samples were taken in the morning within 3 days after symptom onset, and patients were divided into the following 3 groups: subclinical hyperthyroidism (0.1< thyroid-stimulating hormone ≤ 0.44 µU/mL), subclinical hypothyroidism (2.5 ≤ thyroid-stimulating hormone <20 µU/mL), and euthyroid state (0.44< thyroid-stimulating hormone <2.5 µU/mL). Patients with overt thyroid dysfunction were excluded. Follow-up took place 3 months after stroke. Primary outcome was functional disability (modified Rankin Scale), and secondary outcome was level of dependency (Barthel Index). Ordinal logistic regression analysis was used to adjust for possible confounders. Variables previously reported to be affected by thyroid function, such as atrial fibrillation, total cholesterol, or body mass index, were included in an additional model. RESULTS: Nineteen patients (11.5%) had subclinical hyperthyroidism, and 23 patients (13.9%) had subclinical hypothyroidism. Patients with subclinical hyperthyroidism had a substantially increased risk of functional disability 3 months after stroke compared with subjects with euthyroid state (odds ratio, 2.63; 95% confidence interval, 1.02-6.82, adjusted for age, sex, smoking status, and time of blood sampling). The association remained significant, when including the baseline NIHSS, TIA, serum CRP, atrial fibrillation, body mass index, and total cholesterol as additional variables (odds ratio, 3.95; 95% confidence interval, 1.25-12.47), and was confirmed by the secondary outcome (Barthel Index: odds ratio, 9.12; 95% confidence interval, 2.08-39.89). CONCLUSIONS: Subclinical hyperthyroidism is a risk factor for poor outcome 3 months after ischemic stroke.

Erythrocyte membrane phospholipid polyunsaturated fatty acids are related to plasma C-reactive protein and adiponectin in middle-aged German women and men.

PURPOSE: Modulation of circulating inflammatory markers and adiponectin may link PUFA to risk of diabetes and cardiovascular diseases. We investigated erythrocyte n-6 and n-3 PUFA in relation to plasma C-reactive protein (CRP) and adiponectin, and whether the Pro12Ala polymorphism in the PPARγ2 gene (PPARG2) modified these associations. METHODS: We conducted a cross-sectional analysis among 1,222 women and 758 men participating in the EPIC-Potsdam study. RESULTS: Most notably, in both sexes, higher linoleic acid (LA) was related to lower CRP (geometric mean outcome [mg/L], quintile 1, quintile 5, p for trend ≤ 0.01 unless otherwise stated: 0.95, 0.61 [women], 0.67, 0.51 [men]) and higher adiponectin (7.9, 9.1 [women], 5.3, 6.1 [men]), whereas higher γ-linolenic acid (GLA) and dihomo-γ-linolenic acid (DGLA) were related to higher CRP (GLA: 0.63, 0.92 [women], 0.55, 0.70, p = 0.08 [men], DGLA: 0.55, 1.07 [women], 0.52, 0.76 [men]) and lower adiponectin (GLA: 8.6, 8.0 [women], 5.8, 5.4, p = 0.08 [men], DGLA: 9.2, 7.9 [women], 5.9, 5.4, p = 0.08 [men]) adjusting for age and lifestyle. The associations mostly did neither strongly nor significantly vary by PPARG2 genotype. In women, Pro12Ala appeared to interact with arachidonic acid on CRP (p = 0.04), as well as with docosatetraenoic acid on CRP (p = 0.08) and adiponectin (p = 0.02). CONCLUSIONS: Our findings suggest that erythrocyte PUFA, particularly LA and n-6 higher unsaturated fatty acids, are related to circulating CRP and adiponectin. They do not indicate that PUFA strongly interact with the PPARG2 Pro12Ala variant on these risk markers.

Genetic variation of the FADS1 FADS2 gene cluster and n-6 PUFA composition in erythrocyte membranes in the European Prospective Investigation into Cancer and Nutrition-Potsdam study.

Delta-5 (D5D) and delta-6 (D6D) desaturases are key enzymes in PUFA metabolism. Several factors (e.g. hyperglycaemia, hypertension, blood lipids, statins and fatty acids in diet and biological tissues) may influence desaturase activity. The goals were to evaluate the associations between variation in genes encoding these desaturases (FADS1 and FADS2) and blood concentrations of n-6 PUFA and estimated D5D and D6D activities (evaluated as product/precursor ratio), and to investigate whether other factors influencing the activity of desaturases modify these associations. A random sample of 2066 participants from the European Prospective Investigation into Cancer and Nutrition-Potsdam study (n 27 548) was utilised in the analyses. Crude and adjusted associations between rs174546 genotypes (reflecting genetic variation in the FADS1 FADS2 gene cluster), n-6 PUFA in erythrocytes and estimated desaturase activities were evaluated using multiple linear regression. Potential effect modification was determined by performing stratified analyses and evaluating interaction terms. We found rs174546 genotypes to be related to linoleic (r² 0·060), γ-linolenic (r² 0·041), eicosadienoic (r² 0·034), arachidonic (r² 0·026), docosatetraenoic acids (r² 0·028), estimated D6D activity (r² 0·052) and particularly strongly to dihomo-γ-linolenic acid (DGLA, r² 0·182) and D5D activity (r² 0·231). We did not observe effect modifications with regard to the estimated D5D activity, DGLA and arachidonic acid (AA) for most of the factors evaluated; however, the genetic effect on D5D activity and DGLA may be modified by the dietary n-6:n-3-ratio (P-values for interaction: 0·008 and 0·002), and the genetic effect on DGLA and AA may be modified by lipid-lowering medication (P-values for interaction: 0·0004 and 0·006). In conclusion, genetic variation in the FADS1 FADS2 gene cluster affects n-6 PUFA profiles in erythrocytes reflecting altered D5D activity.

Do genetic factors protect for early onset lung cancer? A case control study before the age of 50 years.

BACKGROUND: Early onset lung cancer shows some familial aggregation, pointing to a genetic predisposition. This study was set up to investigate the role of candidate genes in the susceptibility to lung cancer patients younger than 51 years at diagnosis. METHODS: 246 patients with a primary, histologically or cytologically confirmed neoplasm, recruited from 2000 to 2003 in major lung clinics across Germany, were matched to 223 unrelated healthy controls. 11 single nucleotide polymorphisms of genes with reported associations to lung cancer have been genotyped. RESULTS: Genetic associations or gene-smoking interactions was found for GPX1(Pro200Leu) and EPHX1(His113Tyr). Carriers of the Leu-allele of GPX1(Pro200Leu) showed a significant risk reduction of OR = 0.6 (95% CI: 0.4-0.8, p = 0.002) in general and of OR = 0.3 (95% CI:0.1-0.8, p = 0.012) within heavy smokers. We could also find a risk decreasing genetic effect for His-carriers of EPHX1(His113Tyr) for moderate smokers (OR = 0.2, 95% CI:0.1-0.7, p = 0.012). Considered both variants together, a monotone decrease of the OR was found for smokers (OR of 0.20; 95% CI: 0.07-0.60) for each protective allele. CONCLUSION: Smoking is the most important risk factor for young lung cancer patients. However, this study provides some support for the T-Allel of GPX1(Pro200Leu) and the C-Allele of EPHX1(His113Tyr) to play a protective role in early onset lung cancer susceptibility.

Early MoCA predicts long-term cognitive and functional outcome and mortality after stroke.

OBJECTIVE: To examine whether the Montreal Cognitive Assessment (MoCA) administered within 7 days after stroke predicts long-term cognitive impairment, functional impairment, and mortality. METHODS: MoCA was administered to 274 patients from 2 prospective hospital-based cohort studies in Germany (n = 125) and France (n = 149). Cognitive and functional outcomes were assessed at 6, 12, and 36 months after stroke by comprehensive neuropsychological testing, the Clinical Dementia Rating (CDR) scale, the modified Rankin Scale (mRS), and Instrumental Activities of Daily Living (IADL) and analyzed with generalized estimating equations. All-cause mortality was investigated by Cox proportional hazard models. Analyses were adjusted for demographic variables, education, vascular risk factors, premorbid cognitive status, and NIH Stroke Scale scores. The additive predictive value of MoCA was examined with receiver operating characteristic curves. RESULTS: In pooled analyses, a baseline MoCA score <26 was associated with cognitive impairment, defined by neuropsychological testing (odds ratio [OR] 5.30, 95% confidence interval [CI] 2.75-10.22) and by CDR score ≥0.5 (OR 2.53, 95% CI 1.53-4.18); functional impairment, defined by mRS score >2 (OR 5.03, 95% CI 2.20-11.51) and by IADL score <8 (OR 2.48, 95% CI 1.40-4.38); and mortality (hazard ratio 7.24, 95% CI 1.99-26.35) across the 3-year follow-up. Patients with MoCA score <26 performed worse across all prespecified cognitive domains (executive function/attention, memory, language, visuospatial ability). MoCA increased the area under the curve for predicting cognitive impairment (neuropsychological testing 0.81 vs 0.72, p = 0.01) and functional impairment (mRS score >2, 0.88 vs 0.84, p = 0.047). CONCLUSION: Early cognitive testing by MoCA predicts long-term cognitive outcome, functional outcome, and mortality after stroke. Our results support routine use of the MoCA in stroke patients.

STROKOG (stroke and cognition consortium): An international consortium to examine the epidemiology, diagnosis, and treatment of neurocognitive disorders in relation to cerebrovascular disease.

INTRODUCTION: The Stroke and Cognition consortium (STROKOG) aims to facilitate a better understanding of the determinants of vascular contributions to cognitive disorders and help improve the diagnosis and treatment of vascular cognitive disorders (VCD). METHODS: Longitudinal studies with ≥75 participants who had suffered or were at risk of stroke or TIA and which evaluated cognitive function were invited to join STROKOG. The consortium will facilitate projects investigating rates and patterns of cognitive decline, risk factors for VCD, and biomarkers of vascular dementia. RESULTS: Currently, STROKOG includes 25 (21 published) studies, with 12,092 participants from five continents. The duration of follow-up ranges from 3 months to 21 years. DISCUSSION: Although data harmonization will be a key challenge, STROKOG is in a unique position to reuse and combine international cohort data and fully explore patient level characteristics and outcomes. STROKOG could potentially transform our understanding of VCD and have a worldwide impact on promoting better vascular cognitive outcomes.

Peripheral glucose levels and cognitive outcome after ischemic stroke-Results from the Munich Stroke Cohort.

INTRODUCTION: The relationship between glucose metabolism and stroke outcome is likely to be complex. We examined whether there is a linear or non-linear relationship between glucose measures in the acute phase of stroke and post-stroke cognition, and whether altered glucose metabolism at different time intervals (long- and short-term before stroke, acute phase) is associated with cognitive outcome. PATIENTS AND METHODS: In all, 664 consecutively recruited patients with acute ischemic stroke and without pre-stroke dementia were included in this prospective observational study. Blood samples were taken at admission and fasting on the first morning after stroke. Duration of diabetes was assessed by interview. Cognitive outcome was assessed by the Telephone Interview for Cognitive Status 3 months post-stroke. Dose-response analyses were used to investigate non-linearity. Regression analyses were stratified by diabetes status and adjusted for relevant confounders. RESULTS: Cognitive status was testable in 422 patients (81 with diabetes). There was a non-linear relationship between both admission and fasting glucose levels and cognitive outcome. Lower glucose values were significantly associated with lower Telephone Interview for Cognitive Status scores 3 months post-stroke in patients without diabetes with a similar trend in diabetic patients. There was an inverse association between duration of diabetes and Telephone Interview for Cognitive Status scores (linear regression: -0.10 (95% confidence interval: -0.17 to -0.02) per year increase of diabetes duration), whereas HbA1c was not related to cognitive outcome. Results were supported by sensitivity analyses accounting for attrition. CONCLUSION: Lower glucose levels in the acute phase of stroke are associated with worse cognitive outcome but the relationship is non-linear. Long-term abnormalities in glucose metabolism are also related to poor outcome but this is not the case for shorter term abnormalities. Altered glucose levels at different stages of stroke may affect stroke outcome through different pathways.

Acute infarcts cause focal thinning in remote cortex via degeneration of connecting fiber tracts.

OBJECTIVE: To study remote effects distant from acute ischemic infarcts by measuring longitudinal changes of cortical thickness in connected brain regions as well as changes in microstructural integrity in connecting fiber tracts. METHODS: Thirty-two patients (mean age 71 years) underwent a standardized protocol including multimodal MRI and clinical assessment both at stroke onset and 6 months after the event. Cortex connected to acute infarcts was identified by probabilistic diffusion tensor tractography starting from the acute lesion. Changes of cortical thickness were measured using the longitudinal stream of FreeSurfer. Microstructural damage in white matter tracts was assessed by changes of mean diffusivity. RESULTS: We found focal cortical thinning specifically in areas connected to acute infarcts (p < 0.001). Thinning was more pronounced in regions showing a high probability of connectivity to infarcts. Microstructural damage in white matter tracts connecting acute infarcts with distant cortex significantly correlated with thickness changes in that region (ρ = -0.39, p = 0.028). There was no indication of an influence of cavitation status or infarct etiology on the observed changes in cortex and white matter. CONCLUSIONS: These findings identify secondary degeneration of connected white matter tracts and remote cortex as key features of acute ischemic infarcts. Our observations may have implications for the understanding of structural and functional reorganization after stroke.

The Determinants of Dementia After Stroke (DEDEMAS) Study: protocol and pilot data.

RATIONALE: About 20% of stroke patients develop dementia within a few months after their event, but the determinants and mechanisms of poststroke dementia are insufficiently understood. AIMS: To identify and characterize the determinants of cognitive impairment poststroke. DESIGN: Observational prospective study in patients with acute stroke and no prior dementia. Six hundred subjects will be characterized by detailed interview, standardized clinical examinations, biometric measures (intima-media thickness, waist-hip ratio, and ankle-brachial index), multimodal imaging (magnetic resonance imaging, fluorodeoxyglucose-positron emission tomography (FDG-PET), amyloid-positron emission tomography (amyloid-PET), and retinal imaging), analysis of biomarkers derived from blood and cerebrospinal fluid, and detailed cognitive testing at repeat time points. Patients will be followed for five-years with a total of five personal visits and three telephone interviews. STUDY OUTCOMES: Primary end-point is the occurrence of poststroke dementia. Secondary end-points include poststroke cognitive impairment-no dementia, stroke recurrence, and death. Predictive factors for poststroke dementia will be identified by multiple Cox proportional-hazards model. RESULTS: Baseline characteristics of the first 71 patients (study inclusion between May 2011 and August 2012) are as follows: median age, 70 years (interquartile range, 65-75); female gender, 25 (35%); median National Institutes of Health Stroke Scale at admission, 2 (1-4); and etiological stroke subtypes according to TOAST classification, 15% large artery disease, 18% small vessel disease, 35% cardioembolic, and 32% undetermined or multiple competing etiologies. DISCUSSION: This study will provide insights into the mechanisms of poststroke dementia and hold the potential to identify novel diagnostic markers and targets for preventive therapies. The study is registered at http://www.clinicaltrials.gov (NCT01334749) and will be extended as a multicenter study starting 2013.

Prediction of vascular risk after stroke - protocol and pilot data of the Prospective Cohort with Incident Stroke (PROSCIS).

RATIONALE: Long-term risk of vascular disease is substantially increased after stroke with several models proposed to predict subsequent stroke and other vascular events after an index event. However, recent validation studies demonstrate limited predictive properties of available prognostic models. AIMS: We aim to determine prediction models of different complexity for the combined vascular end-point of stroke, myocardial infarction, and vascular death at three-years after first-ever stroke. An independent external validation of the developed models will be performed. DESIGN: Prospective observational hospital-based cohort study of patients after first-ever stroke. METHODS: The new predictive models will be developed using the following steps: (1) Development of a basic score based on clinical history data (e.g. hypertension, myocardial infarction, and atrial fibrillation); (2) Development of an advanced score including additional factors such as blood-based biomarkers and results of vascular imaging; (3) Comparing the models fit using different methods (discrimination, calibration); (4) Assessment of clinical utility of an advanced score using methods based on reclassification tables (e.g. net reclassification improvement, integrated discrimination improvement, decision curve analysis); and (5) Investigation of external validity. OUTCOMES: Primary outcome is a combined vascular end-point composed of stroke, myocardial infarction, and vascular death at three-years after stroke. Furthermore, each component of the composite end-point will be investigated individually and the patterns and time points of risk transitions between vascular end-points and stroke sub-types will be determined.

Post-study therapy as a source of confounding in survival analysis of first-line studies in patients with advanced non-small-cell lung cancer.

Clinical trials exploring the long-term effects of first-line therapy in patients with advanced non-small-cell lung cancer generally disregard subsequent treatment although most patients receive second and third-line therapies. The choice of further therapy depends on critical intermediate events such as disease progression and it is usually left at the physician's discretion. Time-dependent confounding may then arise with standard survival analyses producing biased effect estimates, even in randomized trials. Herein we describe the concept of time-dependent confounding in detail and discuss whether the response to first-line treatment may be a potential time-dependent confounding factor for survival in the context of subsequent therapy. A prospective observational study of 406 patients with advanced non-small-cell lung cancer served as an example base. There is evidence that time-dependent confounding may occur in multivariate survival analysis after first-line therapy when disregarding subsequent treatment. In the light of this important but underestimated aspect some of the large and meaningful recent clinical first-line lung cancer studies are discussed, focussing on subsequent treatment and its potential impact on the survival of the study patients. No recently performed lung cancer trial applied adequate statistical analyses despite the frequent use of subsequent therapies. In conclusion, effect estimates from standard survival analysis may be biased even in randomized controlled trials because of time-dependent confounding. To adequately assess treatment effects on long-term outcomes appropriate statistical analyses need to take subsequent treatment into account.

Erythrocyte membrane phospholipid fatty acids, desaturase activity, and dietary fatty acids in relation to risk of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study.

BACKGROUND: The long-term role of fatty acids (FAs) in the cause of diabetes remains largely unclear. OBJECTIVE: We aimed to investigate erythrocyte membrane FAs, desaturase activity, and dietary FAs in relation to the incidence of type 2 diabetes. DESIGN: We applied a nested case-cohort design (n = 2724, including 673 incident diabetes cases) within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study, which involves 27,548 middle-aged subjects. Thirty erythrocyte membrane FAs (percentage of total FAs) and FA intake (percentage of total fat) were measured at baseline, and physician-confirmed incident diabetes was assessed during a mean follow-up of 7.0 y. We evaluated Δ5 desaturase (D5D) and Δ6 desaturase (D6D) activity by using FA product-to-precursor ratios (traditional approach) and by investigating variants in FADS1 and FADS2 genes that encode these desaturases (Mendelian randomization approach). RESULTS: As a main finding, erythrocyte 16:1n-7 and 18:3n-6 and FA ratios, which reflect stearoyl coenzyme A desaturase (SCD) and D6D activity, were directly related to diabetes risk in multivariable-adjusted models [relative risks (95% CIs) comparing extreme quintiles: 16:1n-7, 2.11 (1.46, 3.05); 18:3n-6, 2.00 (1.38, 2.88); SCD, 2.61 (1.75, 3.89); and D6D, 2.46 (1.67, 3.63)], whereas the FA ratio that reflects D5D activity was inversely associated with risk [0.46 (0.31, 0.70)]. The Mendelian randomization approach corroborated the direct relation for D6D activity and tended to support the inverse relation for D5D activity. Proportions of dietary FAs showed only modest to low correlations with erythrocyte FAs and were not significantly associated with risk. CONCLUSION: The FA profile of erythrocyte membrane phospholipids and activity of desaturase enzymes are strongly linked to the incidence of type 2 diabetes.

Pharmacogenomics Bias - Systematic distortion of study results by genetic heterogeneity.

BACKGROUND: Decision analyses of drug treatments in chronic diseases require modeling the progression of disease and treatment response beyond the time horizon of clinical or epidemiological studies. In many such models, progression and drug effect have been applied uniformly to all patients; heterogeneity in progression, including pharmacogenomic effects, has been ignored. OBJECTIVE: We sought to systematically evaluate the existence, direction and relative magnitude of a pharmacogenomics bias (PGX-Bias) resulting from failure to adjust for genetic heterogeneity in both treatment response (HT) and heterogeneity in progression of disease (HP) in decision-analytic studies based on clinical study data. METHODS: We performed a systematic literature search in electronic databases for studies regarding the effect of genetic heterogeneity on the validity of study results. Included studies have been summarized in evidence tables. In the case of lacking evidence from published studies we sought to perform our own simulation considering both HT and HP. We constructed two simple Markov models with three basic health states (early-stage disease, late-stage disease, dead), one adjusting and the other not adjusting for genetic heterogeneity. Adjustment was done by creating different disease states for presence (G+) and absence (G-) of a dichotomous genetic factor. We compared the life expectancy gains attributable to treatment resulting from both models and defined pharmacogenomics bias as percent deviation of treatment-related life expectancy gains in the unadjusted model from those in the adjusted model. We calculated the bias as a function of underlying model parameters to create generic results. We then applied our model to lipid-lowering therapy with pravastatin in patients with coronary atherosclerosis, incorporating the influence of two TaqIB polymorphism variants (B1 and B2) on progression and drug efficacy as reported in the DNA substudy of the REGRESS trial. RESULTS: We found four studies that systematically evaluated heterogeneity bias. All of them indicated that there is a potential of heterogeneity bias. However, none of these studies explicitly investigated the effect of genetic heterogeneity. Therefore, we performed our own simulation study. Our generic simulation showed that a purely HT-related bias is negative (conservative) and a purely HP-related bias is positive (liberal). For many typical scenarios, the absolute bias is smaller than 10%. In case of joint HP and HT, the overall bias is likely triggered by the HP component and reaches positive values >100% if fractions of "fast progressors" and "strong treatment responders" are low. In the clinical example with pravastatin therapy, the unadjusted model overestimated the true life-years gained (LYG) by 5.5% (1.07 LYG vs. 0.99 LYG for 56-year-old men). CONCLUSIONS: We have been able to predict the pharmacogenomics bias jointly caused by heterogeneity in progression of disease and heterogeneity in treatment response as a function of characteristics of patients, chronic disease, and treatment. In the case of joint presence of both types of heterogeneity, models ignoring this heterogeneity may generate results that overestimate the treatment benefit.

Progression-free survival as a surrogate endpoint in advanced breast cancer.

OBJECTIVES: Progression-free survival (PFS) has not been validated as a surrogate endpoint for overall survival (OS) for anthracycline (A) and taxane-based (T) chemotherapy in advanced breast cancer (ABC). Using trial-level, meta-analytic approaches, we evaluated PFS as a surrogate endpoint. METHODS: A literature review identified randomized, controlled A and T trials for ABC. Progression-based endpoints were classified by prospective definitions. Treatment effects were derived as hazard ratios for PFS (HRPFS) and OS (HROS). Kappa statistic assessed overall agreement. A fixed-effects regression model was used to predict HROS from observed HRPFS. Cross-validation was performed. Sensitivity and subgroup analyses were performed for PFS definition, year of last patient recruitment, line of treatment, and constant rate assumption. RESULTS: Sixteen A and fifteen T trials met inclusion criteria, producing seventeen A (n = 4,323) and seventeen T (n = 5,893) trial-arm pairs. Agreement (kappa statistic) between the direction of HROS and HRPFS was 0.71 for A (p = .0029) and 0.75 for T (p = .0028). While HRPFS was a statistically significant predictor of HROS for both A (p = .0019) and T (p = .012), the explained variances were 0.49 (A) and 0.35 (T). In cross-validation, 97 percent of the 95 percent prediction intervals crossed the equivalence line, and the direction of predicted HROS agreed with observed HROS in 82 percent (A) and 76 percent (T). Results were robust in sensitivity and subgroup analyses. CONCLUSIONS: This meta-analysis suggests that the trial-level treatment effect on PFS is significantly associated with the trial-level treatment effect on OS. However, prediction of OS based on PFS is surrounded with uncertainty.