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738 results on '"White IR"'

1. Allergic contact dermatitis: epidemiology, molecular mechanisms, in vitro methods and regulatory aspects

Author

Peiser, M, Tralau, T, Heidler, J, Api, AM, Arts, JHE, Basketter, DA, English, J, Diepgen, TL, Fuhlbrigge, RC, Gaspari, AA, Johansen, JD, Karlberg, AT, Kimber, I, Lepoittevin, JP, Liebsch, M, Maibach, HI, Martin, SF, Merk, HF, Platzek, T, Rustemeyer, T, Schnuch, A, Vandebriel, RJ, White, IR, and Luch, A

Subjects
Medical Biochemistry and Metabolomics, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Food Allergies, Prevention, Aetiology, 2.2 Factors relating to the physical environment, Inflammatory and immune system, Allergens, Congresses as Topic, Dermatitis, Allergic Contact, Humans, Immunity, Innate, Keratinocytes, Local Lymph Node Assay, Natural Killer T-Cells, Risk Factors, Contact allergy, Dermatitis, Epidemiology, Molecular mechanisms, Regulatory aspects, Biochemistry and Cell Biology, Physiology, Clinical Sciences, Biochemistry & Molecular Biology, Biochemistry and cell biology, Medical biochemistry and metabolomics, Oncology and carcinogenesis
Abstract

Contact allergies are complex diseases, and one of the important challenges for public health and immunology. The German 'Federal Institute for Risk Assessment' hosted an 'International Workshop on Contact Dermatitis'. The scope of the workshop was to discuss new discoveries and developments in the field of contact dermatitis. This included the epidemiology and molecular biology of contact allergy, as well as the development of new in vitro methods. Furthermore, it considered regulatory aspects aiming to reduce exposure to contact sensitisers. An estimated 15-20% of the general population suffers from contact allergy. Workplace exposure, age, sex, use of consumer products and genetic predispositions were identified as the most important risk factors. Research highlights included: advances in understanding of immune responses to contact sensitisers, the importance of autoxidation or enzyme-mediated oxidation for the activation of chemicals, the mechanisms through which hapten-protein conjugates are formed and the development of novel in vitro strategies for the identification of skin-sensitising chemicals. Dendritic cell cultures and structure-activity relationships are being developed to identify potential contact allergens. However, the local lymph node assay (LLNA) presently remains the validated method of choice for hazard identification and characterisation. At the workshop the use of the LLNA for regulatory purposes and for quantitative risk assessment was also discussed.

Published
2012

2. The Personalised Randomised Controlled Trial (PRACTical): evaluation of a new trial design

Author

Lee, KM, Turner, RM, Thwaites, GE, Walker, AS, and White, IR

Abstract

In some clinical scenarios, for example, severe sepsis caused by extensively drug resistant bacteria, there is uncertainty between many common treatments, but a conventional multiarm randomized trial is not possible because individual participants may not be eligible to receive certain treatments. The Personalised Randomized Controlled Trial design allows each participant to be randomized between a “personalised randomization list” of treatments that are suitable for them. The primary aim is to produce treatment rankings that can guide choice of treatment, rather than focusing on the estimates of relative treatment effects. Here we use simulation to assess several novel analysis approaches for this innovative trial design. One of the approaches is like a network meta-analysis, where participants with the same personalised randomization list are like a trial, and both direct and indirect evidence are used. We evaluate this proposed analysis and compare it with analyses making less use of indirect evidence. We also propose new performance measures including the expected improvement in outcome if the trial's rankings are used to inform future treatment rather than random choice. We conclude that analysis of a personalized randomized controlled trial can be performed by pooling data from different types of participants and is robust to moderate subgroup-by-intervention interactions based on the parameters of our simulation. The proposed approach performs well with respect to estimation bias and coverage. It provides an overall treatment ranking list with reasonable precision, and is likely to improve outcome on average if used to determine intervention policies and guide individual clinical decisions.

Published
2023

3. Evaluating the clarity of the questions being addressed in randomised trials: a systematic review of estimands

Author

Cro, S, Kahan, BC, Rehal, S, Chis Ster, A, Carpenter, JR, White, IR, Cornelius, VR, and National Institute for Health Research

Subjects
General & Internal Medicine, 1103 Clinical Sciences, 1117 Public Health and Health Services
Abstract

Objective: To evaluate how often the precise question being addressed about an intervention (the estimand) is stated or can be worked out from reported methods, and to identify what types of questions are addressed in phase II-IV randomised trials. Design: A systematic review of the clarity of research questions addressed in randomised trials in 2020 in six leading general medical journals. Eligibility criteria: Phase II-IV randomised trials, with no restrictions on medical conditions or interventions. Cluster randomised, cross-over, non-inferiority, and equivalence trials were excluded. Data source: A search of PubMed was performed in February 2021. Main outcome measures: The number of trials which stated the precise primary question being addressed about an intervention (the primary estimand) or for which this could be unambiguously worked out from the reported methods using statistical knowledge. The strategies being used to handle post-randomisation events that affect the interpretation or existence of patient outcomes, such as intervention discontinuations or uses of additional medications (termed intercurrent events), and the corresponding types of questions being addressed. Results: A total of 255 eligible randomised trials were identified. No trials clearly stated all the attributes of the estimand. In 117/255 (46%) trials the primary question addressed could be worked out from the reported methods. Intercurrent events occurred in 95% of trials; but the handling of these could only be determined in 125/255 (49%) trials. Most trials which provided this information considered the occurrence of intercurrent events as irrelevant in the calculation of the treatment effect and addressed the effect of the intervention regardless (96/125, 76%) i.e. as if introduced into routine practice (treatment policy strategy). 4/99 (4%) trials with treatment non-adherence due to adverse events estimated the treatment effect in a hypothetical setting (the effect as if participants continued treatment despite adverse events) and 19/24 (79%) trials where some patients died estimated the treatment effect in a hypothetical setting (the effect as if participants did not die). Conclusions: It is unclear in most trials what precise research question is being addressed. The main driver for this is lack of clarity on the approach to handling intercurrent events. Clear reporting of estimands is necessary in trial reports so all stakeholders, including clinicians, patients and policy makers, can make fully informed decisions about medical interventions.

Published
2022

4. Mindfulness-based programmes for mental health promotion in adults in non-clinical settings: protocol of an individual participant data meta-analysis of randomised controlled trials

Author

Galante, J, Friedrich, C, Dalgleish, T, White, IR, Jones, PB, Galante, J, Friedrich, C, Dalgleish, T, White, IR, and Jones, PB

Abstract

INTRODUCTION: With mental ill health listed as a top cause of global disease burden, there is an urgent need to prioritise mental health promotion programmes. Mindfulness-based programmes (MBPs) are being widely implemented to reduce stress in non-clinical settings. In a recent aggregate-level meta-analysis we found that, compared with no intervention, these MBPs reduce average psychological distress. However, heterogeneity between studies impedes generalisation of effects across every setting. Study-level effect modifiers were insufficient to reduce heterogeneity; studying individual-level effect modifiers is warranted. This requires individual participant data (IPD) and larger samples than those found in existing individual trials. METHODS AND ANALYSIS: We propose an IPD meta-analysis. Our primary aim is to see if, and how, baseline psychological distress, gender, age, education and dispositional mindfulness moderate the effect of MBPs on distress. We will search 13 databases for good-quality randomised controlled trials comparing in-person, expert-defined MBPs in non-clinical settings with passive controls. Two researchers will independently select, extract and appraise trials using the revised Cochrane risk-of-bias tool. Anonymised IPD of eligible trials will be sought from authors, who will be invited to collaborate.The primary outcome will be psychological distress measured using psychometrically validated questionnaires at 1-6 months after programme completion. Pairwise random-effects two-stage IPD meta-analyses will be conducted. Moderator analyses will follow a 'deft' approach. We will estimate subgroup-specific intervention effects. Secondary outcomes and sensitivity analyses are prespecified. Multiple imputation strategies will be applied to missing data. ETHICS AND DISSEMINATION: The findings will refine our knowledge on the effectiveness of MBPs and help improve the targeting of MBPs in non-clinical settings. They will be shared in accessible formats wi

Published
2022

6. Mindfulness-based programmes for mental health promotion in adults in non-clinical settings: protocol of an individual participant data meta-analysis of randomised controlled trials

Author

Jones Pb, Tim Dalgleish, White Ir, Galante J, and C Friedrich

Subjects
Protocol (science), Promotion (rank), Mindfulness, Non clinical, media_common.quotation_subject, Individual participant data, Meta-analysis, Psychology, Mental health, media_common, Clinical psychology
Abstract

Introduction With mental ill health listed as a top cause of global disease burden, there is an urgent need to prioritise mental health promotion programmes. Mindfulness–based programmes (MBPs) are being widely implemented to reduce stress in non-clinical settings. In a recent aggregate-level meta-analysis we found that, compared with no intervention, these MBPs reduce average psychological distress. However, heterogeneity between studies impedes generalisation of effects across every setting. Study-level moderators were insufficient to reduce heterogeneity; studying individual–level moderators is warranted. This requires individual participant data (IPD) and larger samples than those found in existing individual trials. Methods and analysis We propose an IPD meta–analysis. Our primary aim is to see if, and how, baseline psychological distress, gender, age, education, and dispositional mindfulness moderate the effect of MBPs on distress. We will search 13 databases for good-quality randomised controlled trials (RCTs) comparing in–person, expert–defined MBPs in non-clinical settings with passive controls. Two researchers will independently select, extract, and appraise trials using the revised Cochrane Risk–of–Bias Tool (RoB2). Anonymised IPD of eligible trials will be sought from authors, who will be invited to collaborate. The primary outcome will be psychological distress measured using psychometrically-validated questionnaires at 1 to 6 months after programme completion. Pairwise random-effects two-stage IPD meta-analyses will be conducted. Moderator analyses will follow a “deft” approach. We will estimate subgroup-specific intervention effects. Secondary outcomes and sensitivity analyses are pre-specified. Multiple imputation strategies will be applied to missing data. Ethics and dissemination The findings will refine our knowledge on the effectiveness of MBPs and help improve the targeting of MBPs in non-clinical settings. They will be shared in accessible formats with a range of stakeholders. Public and professional stakeholders are being involved in the planning, conduct and dissemination of this project. PROSPERO registration number CRD42020200117

Published
2021

7. Mindfulness-based programmes for mental health promotion in adults in nonclinical settings: A systematic review and meta-analysis of randomised controlled trials

Author

Patel, V, Galante, J, Friedrich, C, Dawson, AF, Modrego-Alarcon, M, Gebbing, P, Delgado-Suarez, I, Gupta, R, Dean, L, Dalgleish, T, White, IR, Jones, PB, Patel, V, Galante, J, Friedrich, C, Dawson, AF, Modrego-Alarcon, M, Gebbing, P, Delgado-Suarez, I, Gupta, R, Dean, L, Dalgleish, T, White, IR, and Jones, PB

Abstract

BACKGROUND: There is an urgent need for mental health promotion in nonclinical settings. Mindfulness-based programmes (MBPs) are being widely implemented to reduce stress, but a comprehensive evidence synthesis is lacking. We reviewed trials to assess whether MBPs promote mental health relative to no intervention or comparator interventions. METHODS AND FINDINGS: Following a detailed preregistered protocol (PROSPERO CRD42018105213) developed with public and professional stakeholders, 13 databases were searched to August 2020 for randomised controlled trials (RCTs) examining in-person, expert-defined MBPs in nonclinical settings. Two researchers independently selected, extracted, and appraised trials using the Cochrane Risk-of-Bias Tool 2.0. Primary outcomes were psychometrically validated anxiety, depression, psychological distress, and mental well-being questionnaires at 1 to 6 months after programme completion. Multiple testing was performed using p < 0.0125 (Bonferroni) for statistical significance. Secondary outcomes, meta-regression and sensitivity analyses were prespecified. Pairwise random-effects multivariate meta-analyses and prediction intervals (PIs) were calculated. A total of 11,605 participants in 136 trials were included (29 countries, 77% women, age range 18 to 73 years). Compared with no intervention, in most but not all scenarios MBPs improved average anxiety (8 trials; standardised mean difference (SMD) = -0.56; 95% confidence interval (CI) -0.80 to -0.33; p-value < 0.001; 95% PI -1.19 to 0.06), depression (14 trials; SMD = -0.53; 95% CI -0.72 to -0.34; p-value < 0.001; 95% PI -1.14 to 0.07), distress (27 trials; SMD = -0.45; 95% CI -0.58 to -0.31; p-value < 0.001; 95% PI -1.04 to 0.14), and well-being (9 trials; SMD = 0.33; 95% CI 0.11 to 0.54; p-value = 0.003; 95% PI -0.29 to 0.94). Compared with nonspecific active control conditions, in most but not all scenarios MBPs improved average depression (6 trials; SMD = -0.46; 95% CI -0.81 to -0.10; p

Published
2021

8. Performance status and trial site-level factors are associated with missing data in palliative care trials: An individual participant-level data analysis of 10 phase 3 trials.

Author

Hussain, JA, White, IR, Johnson, MJ, Bland, M, Currow, DC, Hussain, JA, White, IR, Johnson, MJ, Bland, M, and Currow, DC

Abstract

BACKGROUND: Missing data compromise the internal and external validity of trial findings, however there is limited evidence on how best to reduce missing data in palliative care trials. AIM: To assess the association between participant and site level factors and missing data in palliative care trials. DESIGN AND SETTING: Individual participant-level data analysis of 10 phase 3 palliative care trials using multi-level cross-classified models. RESULTS: Participants with missing data at the previous time-point and poorer performance status were more likely to have missing data for the primary outcome and quality of life outcomes, at the primary follow-up point and end of follow-up. At the end of follow-up, the number of site randomisations and number of study site personnel were significantly associated with missing data. Trial duration and the number of research personnel explained most of the variance at the trial and site-level respectively, except for the primary outcome where the amount of data requested was most important at the trial-level. Variance at the trial level was more substantial than at the site level across models and considerable variance remained unexplained for all models except quality of life at the end of follow-up. CONCLUSION: Participants with a poorer performance status are at higher risk of missing data in palliative care trials and require additional support to provide complete data. Performance status is a potential auxiliary variable for missing data imputation models. Reducing trial variability should be prioritised and further factors need to be identified and explored to explain the residual variance.

Published
2021

9. The cost-effectiveness of universal late-pregnancy screening for macrosomia in nulliparous women: a decision analysis

Author

Wastlund, D, Moraitis, AA, Thornton, JG, Sanders, J, White, IR, Brocklehurst, P, Smith, Gcs, Wilson, Ecf, Wastlund, D [0000-0002-5074-4740], Moraitis, AA [0000-0003-4634-1129], Thornton, JG [0000-0001-9764-6876], Sanders, J [0000-0001-5712-9989], White, IR [0000-0002-6718-7661], Brocklehurst, P [0000-0002-9950-6751], Smith, Gcs [0000-0003-2124-0997], Wilson, Ecf [0000-0002-8369-1577], and Apollo - University of Cambridge Repository

Subjects
Adult, ultrasound, screening, Cost-Benefit Analysis, Patient Selection, Pregnancy Trimester, Third, third-trimester, Prenatal Care, Ultrasonography, Prenatal, Decision Support Techniques, Fetal Macrosomia, Parity, England, Pregnancy, health economics, Humans, Female, Economic modelling, macrosomia, Health Services Research, health care economics and organizations
Abstract

OBJECTIVE: To identify the most cost-effective policy for detection and management of fetal macrosomia in late-stage pregnancy. DESIGN: Health economic simulation model. SETTING: All English NHS antenatal services. POPULATION: Nulliparous women in the third trimester treated within the UK NHS. METHODS: A health economic simulation model was used to compare long-term maternal-fetal health and cost outcomes for two detection strategies (universal ultrasound scanning at approximately 36 weeks of gestation versus selective ultrasound scanning), combined with three management strategies (planned caesarean section versus induction of labour versus expectant management) of suspected fetal macrosomia. Probabilities, costs and health outcomes were taken from literature. MAIN OUTCOME MEASURES: Expected costs to the NHS and quality-adjusted life-years (QALYs) gained from each strategy, calculation of net benefit and hence identification of most cost-effective strategy. RESULTS: Compared with selective ultrasound, universal ultrasound increased QALYs by 0.0038 (95% CI 0.0012-0.0076), but also costs by £123.50 (95% CI 99.6-149.9). Overall, the health gains were too small to justify the cost increase given current UK thresholds cost-effective policy was selective ultrasound coupled with induction of labour where macrosomia was suspected. CONCLUSIONS: The most cost-effective policy for detection and management of fetal macrosomia is selective ultrasound scanning coupled with induction of labour for all suspected cases of macrosomia. Universal ultrasound scanning for macrosomia in late-stage pregnancy is not cost-effective. TWEETABLE ABSTRACT: Universal late-pregnancy ultrasound screening for fetal macrosomia is not warranted.

Published
2019

12. A comparison of arm-based and contrast-based models for network meta-analysis

Author

White, IR, Turner, RM, Karahalios, A, Salanti, G, White, IR, Turner, RM, Karahalios, A, and Salanti, G

Abstract

Differences between arm-based (AB) and contrast-based (CB) models for network meta-analysis (NMA) are controversial. We compare the CB model of Lu and Ades (2006), the AB model of Hong et al(2016), and two intermediate models, using hypothetical data and a selected real data set. Differences between models arise primarily from study intercepts being fixed effects in the Lu-Ades model but random effects in the Hong model, and we identify four key difference. (1) If study intercepts are fixed effects then only within-study information is used, but if they are random effects then between-study information is also used and can cause important bias. (2) Models with random study intercepts are suitable for deriving a wider range of estimands, eg, the marginal risk difference, when underlying risk is derived from the NMA data; but underlying risk is usually best derived from external data, and then models with fixed intercepts are equally good. (3) The Hong model allows treatment effects to be related to study intercepts, but the Lu-Ades model does not. (4) The Hong model is valid under a more relaxed missing data assumption, that arms (rather than contrasts) are missing at random, but this does not appear to reduce bias. We also describe an AB model with fixed study intercepts and a CB model with random study intercepts. We conclude that both AB and CB models are suitable for the analysis of NMA data, but using random study intercepts requires a strong rationale such as relating treatment effects to study intercepts.

Published
2019

14. Major lipids, apolipoproteins, and risk of vascular disease

Author

Emerging Risk Factors Collaboration, Di Angelantonio E, Sarwar N, Perry P, Kaptoge S, Ray KK, Thompson A, Wood AM, Lewington S, Sattar N, Packard CJ, Collins R, Thompson SG, Tipping RW, Ford CE, Pressel SL, Walldius G, Jungner I, Folsom AR, Chambless LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Goldbourt U, Benderly M, Tanne D, Whincup PH, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Santer P, Mayr A, Wald N, Ebrahim S, Lawlor DA, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Psaty BM, Tracy RP, Tybjaerg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Smith FB, Taylor J, Guralnik JM, Phillips CL, Wallace R, Guralnik J, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Rodriguez B, Dekker JM, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Deeg DJ, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engstrom G, Verschuren WM, Blokstra A, Döring A, Koenig W, Meisinger C, Mraz W, Verschure WM, Bas Bueno de Mesquita H, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson J, Knottenbelt C, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Ford I, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe GD, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Lind L, Giedraitis V, Lannfelt L, Gaziano JM, Stampfer M, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Marmot M, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Cobbe SM, Robertson M, He Y, Marin Ibañez A, Feskens EJ, Kromhout D, Walker M, Watson S, Erqou S, Orfei L, Pennells L, Perry PL, Alexander M, Wensley F, White IR, Danesh J., PANICO, SALVATORE, Developmental Genetics, EMGO+ - Lifestyle, Overweight and Diabetes, Epidemiology and Data Science, General practice, Psychiatry, EMGO - Lifestyle, overweight and diabetes, Emerging Risk Factors, Collaboration, Di Angelantonio, E, Sarwar, N, Perry, P, Kaptoge, S, Ray, Kk, Thompson, A, Wood, Am, Lewington, S, Sattar, N, Packard, Cj, Collins, R, Thompson, Sg, Tipping, Rw, Ford, Ce, Pressel, Sl, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Goldbourt, U, Benderly, M, Tanne, D, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, R, Guralnik, J, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Rodriguez, B, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engstrom, G, Verschuren, Wm, Blokstra, A, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Verschure, Wm, Bas Bueno de Mesquita, H, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, Knottenbelt, C, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Ford, I, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Lind, L, Giedraitis, V, Lannfelt, L, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Marmot, M, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Robertson, M, He, Y, Marin Ibañez, A, Feskens, Ej, Kromhout, D, Walker, M, Watson, S, Erqou, S, Orfei, L, Pennells, L, Perry, Pl, Alexander, M, Wensley, F, White, Ir, and Danesh, J.

Subjects
medicine.medical_specialty, Apolipoprotein B, biology, Triglyceride, business.industry, Vascular disease, Cholesterol, Proportional hazards model, Hazard ratio, Context (language use), General Medicine, 11 Medical And Health Sciences, medicine.disease, Gastroenterology, Article, chemistry.chemical_compound, Endocrinology, chemistry, Internal medicine, General & Internal Medicine, biology.protein, Medicine, lipids (amino acids, peptides, and proteins), Myocardial infarction, business
Abstract

Udgivelsesdato: 2009-Nov-11 CONTEXT: Associations of major lipids and apolipoproteins with the risk of vascular disease have not been reliably quantified. OBJECTIVE: To assess major lipids and apolipoproteins in vascular risk. DESIGN, SETTING, AND PARTICIPANTS: Individual records were supplied on 302,430 people without initial vascular disease from 68 long-term prospective studies, mostly in Europe and North America. During 2.79 million person-years of follow-up, there were 8857 nonfatal myocardial infarctions, 3928 coronary heart disease [CHD] deaths, 2534 ischemic strokes, 513 hemorrhagic strokes, and 2536 unclassified strokes. MAIN OUTCOME MEASURES: Hazard ratios (HRs), adjusted for several conventional factors, were calculated for 1-SD higher values: 0.52 log(e) triglyceride, 15 mg/dL high-density lipoprotein cholesterol (HDL-C), 43 mg/dL non-HDL-C, 29 mg/dL apolipoprotein AI, 29 mg/dL apolipoprotein B, and 33 mg/dL directly measured low-density lipoprotein cholesterol (LDL-C). Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. RESULTS: The rates of CHD per 1000 person-years in the bottom and top thirds of baseline lipid distributions, respectively, were 2.6 and 6.2 with triglyceride, 6.4 and 2.4 with HDL-C, and 2.3 and 6.7 with non-HDL-C. Adjusted HRs for CHD were 0.99 (95% CI, 0.94-1.05) with triglyceride, 0.78 (95% CI, 0.74-0.82) with HDL-C, and 1.50 (95% CI, 1.39-1.61) with non-HDL-C. Hazard ratios were at least as strong in participants who did not fast as in those who did. The HR for CHD was 0.35 (95% CI, 0.30-0.42) with a combination of 80 mg/dL lower non-HDL-C and 15 mg/dL higher HDL-C. For the subset with apolipoproteins or directly measured LDL-C, HRs were 1.50 (95% CI, 1.38-1.62) with the ratio non-HDL-C/HDL-C, 1.49 (95% CI, 1.39-1.60) with the ratio apo B/apo AI, 1.42 (95% CI, 1.06-1.91) with non-HDL-C, and 1.38 (95% CI, 1.09-1.73) with directly measured LDL-C. Hazard ratios for ischemic stroke were 1.02 (95% CI, 0.94-1.11) with triglyceride, 0.93 (95% CI, 0.84-1.02) with HDL-C, and 1.12 (95% CI, 1.04-1.20) with non-HDL-C. CONCLUSION: Lipid assessment in vascular disease can be simplified by measurement of either total and HDL cholesterol levels or apolipoproteins without the need to fast and without regard to triglyceride.

Published
2016

15. On the use of the not-at-random fully conditional specification (NARFCS) procedure in practice

Author

Tompsett, DM, Leacy, F, Moreno-Betancur, M, Heron, J, White, IR, Tompsett, DM, Leacy, F, Moreno-Betancur, M, Heron, J, and White, IR

Abstract

The not-at-random fully conditional specification (NARFCS) procedure provides a flexible means for the imputation of multivariable missing data under missing-not-at-random conditions. Recent work has outlined difficulties with eliciting the sensitivity parameters of the procedure from expert opinion due to their conditional nature. Failure to adequately account for this conditioning will generate imputations that are inconsistent with the assumptions of the user. In this paper, we clarify the importance of correct conditioning of NARFCS sensitivity parameters and develop procedures to calibrate these sensitivity parameters by relating them to more easily elicited quantities, in particular, the sensitivity parameters from simpler pattern mixture models. Additionally, we consider how to include the missingness indicators as part of the imputation models of NARFCS, recommending including all of them in each model as default practice. Algorithms are developed to perform the calibration procedure and demonstrated on data from the Avon Longitudinal Study of Parents and Children, as well as with simulation studies.

Published
2018

16. Canonical Causal Diagrams to Guide the Treatment of Missing Data in Epidemiologic Studies

Author

Moreno-Betancur, M, Lee, KJ, Leacy, FP, White, IR, Simpson, JA, Carlin, JB, Moreno-Betancur, M, Lee, KJ, Leacy, FP, White, IR, Simpson, JA, and Carlin, JB

Abstract

With incomplete data, the "missing at random" (MAR) assumption is widely understood to enable unbiased estimation with appropriate methods. While the need to assess the plausibility of MAR and to perform sensitivity analyses considering "missing not at random" (MNAR) scenarios has been emphasized, the practical difficulty of these tasks is rarely acknowledged. With multivariable missingness, what MAR means is difficult to grasp, and in many MNAR scenarios unbiased estimation is possible using methods commonly associated with MAR. Directed acyclic graphs (DAGs) have been proposed as an alternative framework for specifying practically accessible assumptions beyond the MAR-MNAR dichotomy. However, there is currently no general algorithm for deciding how to handle the missing data given a specific DAG. Here we construct "canonical" DAGs capturing typical missingness mechanisms in epidemiologic studies with incomplete data on exposure, outcome, and confounding factors. For each DAG, we determine whether common target parameters are "recoverable," meaning that they can be expressed as functions of the available data distribution and thus estimated consistently, or whether sensitivity analyses are necessary. We investigate the performance of available-case and multiple-imputation procedures. Using data from waves 1-3 of the Longitudinal Study of Australian Children (2004-2008), we illustrate how our findings can guide the treatment of missing data in point-exposure studies.

Published
2018

17. Should multiple imputation be the method of choice for handling missing data in randomized trials?

Author

Sullivan, TR, White, IR, Salter, AB, Ryan, P, Lee, KJ, Sullivan, TR, White, IR, Salter, AB, Ryan, P, and Lee, KJ

Abstract

The use of multiple imputation has increased markedly in recent years, and journal reviewers may expect to see multiple imputation used to handle missing data. However in randomized trials, where treatment group is always observed and independent of baseline covariates, other approaches may be preferable. Using data simulation we evaluated multiple imputation, performed both overall and separately by randomized group, across a range of commonly encountered scenarios. We considered both missing outcome and missing baseline data, with missing outcome data induced under missing at random mechanisms. Provided the analysis model was correctly specified, multiple imputation produced unbiased treatment effect estimates, but alternative unbiased approaches were often more efficient. When the analysis model overlooked an interaction effect involving randomized group, multiple imputation produced biased estimates of the average treatment effect when applied to missing outcome data, unless imputation was performed separately by randomized group. Based on these results, we conclude that multiple imputation should not be seen as the only acceptable way to handle missing data in randomized trials. In settings where multiple imputation is adopted, we recommend that imputation is carried out separately by randomized group.

Published
2018

19. An investigation of the impact of using different methods for network meta-analysis: a protocol for an empirical evaluation.

Author

Karahalios, AE, Salanti, G, Turner, SL, Herbison, GP, White, IR, Veroniki, AA, Nikolakopoulou, A, Mckenzie, JE, Karahalios, AE, Salanti, G, Turner, SL, Herbison, GP, White, IR, Veroniki, AA, Nikolakopoulou, A, and Mckenzie, JE

Abstract

BACKGROUND: Network meta-analysis, a method to synthesise evidence from multiple treatments, has increased in popularity in the past decade. Two broad approaches are available to synthesise data across networks, namely, arm- and contrast-synthesis models, with a range of models that can be fitted within each. There has been recent debate about the validity of the arm-synthesis models, but to date, there has been limited empirical evaluation comparing results using the methods applied to a large number of networks. We aim to address this gap through the re-analysis of a large cohort of published networks of interventions using a range of network meta-analysis methods. METHODS: We will include a subset of networks from a database of network meta-analyses of randomised trials that have been identified and curated from the published literature. The subset of networks will include those where the primary outcome is binary, the number of events and participants are reported for each direct comparison, and there is no evidence of inconsistency in the network. We will re-analyse the networks using three contrast-synthesis methods and two arm-synthesis methods. We will compare the estimated treatment effects, their standard errors, treatment hierarchy based on the surface under the cumulative ranking (SUCRA) curve, the SUCRA value, and the between-trial heterogeneity variance across the network meta-analysis methods. We will investigate whether differences in the results are affected by network characteristics and baseline risk. DISCUSSION: The results of this study will inform whether, in practice, the choice of network meta-analysis method matters, and if it does, in what situations differences in the results between methods might arise. The results from this research might also inform future simulation studies.

Published
2017

20. Quality of missing data reporting and handling in palliative care trials demonstrates that further development of the CONSORT statement is required: a systematic review

Author

Hussain, JA, Bland, M, Langan, D, Johnson, MJ, Currow, DC, White, IR, Hussain, JA, Bland, M, Langan, D, Johnson, MJ, Currow, DC, and White, IR

Abstract

© 2017 The Authors Objectives Assess (i) the quality of reporting and handling of missing data (MD) in palliative care trials, (ii) whether there are differences in the reporting of criteria specified by the Consolidated Standards of Reporting Trials (CONSORT) 2010 statement compared with those not specified, and (iii) the association of the reporting of MD with journal impact factor and CONSORT endorsement status. Study Design and Setting Systematic review of palliative care randomized controlled trials. CENTRAL, MEDLINE, and EMBASE (2009–2014) were searched. Results One hundred and eight trials (15,560 participants) were included. MD was incompletely reported and not handled in accordance with current guidance. Reporting criteria specified by the CONSORT statement were better reported than those not specified (participant flow, 69%; number of participants not included in the primary outcome analysis, 94%; and the reason for MD, 71%). However, MD in items contributing to scale summaries (10%) and secondary outcomes (9%) were poorly reported, so the proportion of MD stated is likely to be an underestimate. The reason for MD provided was unclear for 54% of participants and only 16% of trials with MD reported a MD sensitivity analysis. The odds of reporting most of the MD and other risk of bias reporting criteria were increased as the journal impact factor increased and in journals that endorsed the CONSORT statement. Conclusion Further development of the CONSORT MD reporting guidance is likely to improve the quality of reporting. Reporting recommendations are provided.

Published
2017

21. Allowing for non-adherence to treatment in a randomized controlled trial of two antidepressants (citalopram versus reboxetine): an example from the GENPOD trial

Author

Wiles, NJ, Fischer, K, Cowen, P, Nutt, D, Peters, TJ, Lewis, G, and White, IR

Subjects
mental disorders
Abstract

BACKGROUND: Meta-analyses suggest that reboxetine may be less effective than other antidepressants. Such comparisons may be biased by lower adherence to reboxetine and subsequent handling of missing outcome data. This study illustrates how to adjust for differential non-adherence and hence derive an unbiased estimate of the efficacy of reboxetine compared with citalopram in primary care patients with depression. METHOD: A structural mean modelling (SMM) approach was used to generate adherence-adjusted estimates of the efficacy of reboxetine compared with citalopram using GENetic and clinical Predictors Of treatment response in Depression (GENPOD) trial data. Intention-to-treat (ITT) analyses were performed to compare estimates of effectiveness with results from previous meta-analyses. RESULTS: At 6 weeks, 92% of those randomized to citalopram were still taking their medication, compared with 72% of those randomized to reboxetine. In ITT analysis, there was only weak evidence that those on reboxetine had a slightly worse outcome than those on citalopram [adjusted difference in mean Beck Depression Inventory (BDI) scores: 1.19, 95% confidence interval (CI) -0.52 to 2.90, p = 0.17]. There was no evidence of a difference in efficacy when differential non-adherence was accounted for using the SMM approach for mean BDI (-0.29, 95% CI -3.04 to 2.46, p = 0.84) or the other mental health outcomes. CONCLUSIONS: There was no evidence of a difference in the efficacy of reboxetine and citalopram when these drugs are taken and tolerated by depressed patients. The SMM approach can be implemented in standard statistical software to adjust for differential non-adherence and generate unbiased estimates of treatment efficacy for comparisons of two (or more) active interventions.

Published
2016

22. Missing data in randomized controlled trials testing palliative interventions pose a significant risk of bias and loss of power: A systematic review and meta-analyses

Author

Hussain, JA, White, IR, Langan, D, Johnson, MJ, Currow, DC, Torgerson, DJ, and Bland, M

Subjects
Risk, Bias, Epidemiology, Data Interpretation, Statistical, Palliative Care, Humans, Reproducibility of Results, Data Accuracy, Randomized Controlled Trials as Topic
Abstract

© 2016 The Authors. Published by Elsevier Inc. Objectives To assess the risk posed by missing data (MD) to the power and validity of trials evaluating palliative interventions. Study Design and Setting A systematic review of MD in published randomized controlled trials (RCTs) of palliative interventions in participants with life-limiting illnesses was conducted, and random-effects meta-analyses and metaregression were performed. CENTRAL, MEDLINE, and EMBASE (2009-2014) were searched with no language restrictions. Results One hundred and eight RCTs representing 15,560 patients were included. The weighted estimate for MD at the primary endpoint was 23.1% (95% confidence interval [CI] 19.3, 27.4). Larger MD proportions were associated with increasing numbers of questions/tests requested (odds ratio [OR], 1.19; 95% CI 1.05, 1.35) and with longer study duration (OR, 1.09; 95% CI 1.02, 1.17). Meta-analysis found evidence of differential rates of MD between trial arms, which varied in direction (OR, 1.04; 95% CI 0.90, 1.20; I2 35.9, P = 0.001). Despite randomization, MD in the intervention arms (vs. control) were more likely to be attributed to disease progression unrelated to the intervention (OR, 1.31; 95% CI 1.02, 1.69). This was not the case for MD due to death (OR, 0.92; 95% CI 0.78, 1.08). Conclusion The overall proportion and differential rates and reasons for MD reduce the power and potentially introduce bias to palliative care trials.

Published
2015

23. Causal inference for long-term survival in randomised trials with treatment switching: Should re-censoring be applied when estimating counterfactual survival times?

Author

Latimer, NR, White, IR, Abrams, KR, Siebert, U, Latimer, N R, White, I R, and Abrams, K R

Subjects
*CENSORING (Statistics), *SURVIVAL analysis (Biometry), *STRUCTURAL failures, *TECHNOLOGY assessment, *MEDICAL technology, *TUMOR treatment, *EXPERIMENTAL design, *COMPUTER simulation, *RESEARCH, *CLINICAL trials, *RESEARCH methodology, *EVALUATION research, *MEDICAL cooperation, *COMPARATIVE studies, *QUALITY assurance, *RESEARCH funding, *STATISTICAL models
Abstract

Treatment switching often has a crucial impact on estimates of effectiveness and cost-effectiveness of new oncology treatments. Rank preserving structural failure time models (RPSFTM) and two-stage estimation (TSE) methods estimate 'counterfactual' (i.e. had there been no switching) survival times and incorporate re-censoring to guard against informative censoring in the counterfactual dataset. However, re-censoring causes a loss of longer term survival information which is problematic when estimates of long-term survival effects are required, as is often the case for health technology assessment decision making. We present a simulation study designed to investigate applications of the RPSFTM and TSE with and without re-censoring, to determine whether re-censoring should always be recommended within adjustment analyses. We investigate a context where switching is from the control group onto the experimental treatment in scenarios with varying switch proportions, treatment effect sizes, treatment effect changes over time, survival function shapes, disease severity and switcher prognosis. Methods were assessed according to their estimation of control group restricted mean survival that would be observed in the absence of switching, up to the end of trial follow-up. We found that analyses which re-censored usually produced negative bias (i.e. underestimating control group restricted mean survival and overestimating the treatment effect), whereas analyses that did not re-censor consistently produced positive bias which was often smaller in magnitude than the bias associated with re-censored analyses, particularly when the treatment effect was high and the switching proportion was low. The RPSFTM with re-censoring generally resulted in increased bias compared to the other methods. We believe that analyses should be conducted with and without re-censoring, as this may provide decision-makers with useful information on where the true treatment effect is likely to lie. Incorporating re-censoring should not always represent the default approach when the objective is to estimate long-term survival times and treatment effects. [ABSTRACT FROM AUTHOR]

Published
2019
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25. Missing data in randomized controlled trials testing palliative interventions pose a significant risk of bias and loss of power: A systematic review and meta-analyses

Author

Hussain, JA, White, IR, Langan, D, Johnson, MJ, Currow, DC, Torgerson, DJ, Bland, M, Hussain, JA, White, IR, Langan, D, Johnson, MJ, Currow, DC, Torgerson, DJ, and Bland, M

Abstract

© 2016 The Authors. Published by Elsevier Inc. Objectives To assess the risk posed by missing data (MD) to the power and validity of trials evaluating palliative interventions. Study Design and Setting A systematic review of MD in published randomized controlled trials (RCTs) of palliative interventions in participants with life-limiting illnesses was conducted, and random-effects meta-analyses and metaregression were performed. CENTRAL, MEDLINE, and EMBASE (2009-2014) were searched with no language restrictions. Results One hundred and eight RCTs representing 15,560 patients were included. The weighted estimate for MD at the primary endpoint was 23.1% (95% confidence interval [CI] 19.3, 27.4). Larger MD proportions were associated with increasing numbers of questions/tests requested (odds ratio [OR], 1.19; 95% CI 1.05, 1.35) and with longer study duration (OR, 1.09; 95% CI 1.02, 1.17). Meta-analysis found evidence of differential rates of MD between trial arms, which varied in direction (OR, 1.04; 95% CI 0.90, 1.20; I2 35.9, P = 0.001). Despite randomization, MD in the intervention arms (vs. control) were more likely to be attributed to disease progression unrelated to the intervention (OR, 1.31; 95% CI 1.02, 1.69). This was not the case for MD due to death (OR, 0.92; 95% CI 0.78, 1.08). Conclusion The overall proportion and differential rates and reasons for MD reduce the power and potentially introduce bias to palliative care trials.

Published
2016

26. C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis

Author

Emerging Risk Factors Collaboration, Kaptoge S, Di Angelantonio E, Lowe G, Pepys MB, Thompson SG, Collins R, Danesh JTipping RW, Ford CE, Pressel SL, Walldius G, Jungner I, Folsom AR, Chambless L, Ballantyne CM, Panagiotakos D, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman MW, Goldbourt U, Benderly M, Tanne D, Whincup P, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Mayr A, Schett G, Wald N, Ebrahim S, Lawlor D, Yarnell J, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Psaty BM, Tracy R, Tybjaerg Hansen A, Nordestgaard BG, Zacho J, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, de la Cámara AG, Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee A, Taylor J, Guralnik JM, Phillips CL, Wallace RB, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Benjamin EJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Kiyohara Y, Arima H, Doi Y, Ninomiya T, Rodriguez B, Dekker J, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Laukkanen JA, Deeg DJ, Bremmer MA, Meade TW, Cooper JA, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Shea S, Döring A, Koenig W, Meisinger C, Bueno de Mesquita HB, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum RF, Mussolino M, Hankinson S, Manson JE, Knottenbelt C, Bauer KA, Davidson K, Kirkland S, Shaffer J, Korin MR, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Luc G, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Packard CJ, Sattar N, Westendorp RG, Buckley BM, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt RR, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler MM, Hofman A, Tunstall Pedoe H, Tavendale R, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Basu S, Cederholm T, Byberg L, Gaziano JM, Stampfer M, Ridker PM, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Wassertheil Smoller S, Marmot IM, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Shepherd J, Cobbe S, Ford I, Robertson M, He Y, Ibañez AM, Feskens EJ, Walker M, Watson S, Erqou S, Lewington S, Pennells L, Perry PL, Ray KK, Sarwar N, Alexander M, Thompson A, White IR, Wood AM, Danesh J., PANICO, SALVATORE, Interne Geneeskunde, MUMC+: MA Interne Geneeskunde (3), RS: CARIM School for Cardiovascular Diseases, General practice, EMGO - Lifestyle, overweight and diabetes, Psychiatry, EMGO - Mental health, Emerging Risk Factors, Collaboration, Kaptoge, S, Di Angelantonio, E, Lowe, G, Pepys, Mb, Thompson, Sg, Collins, R, Danesh JTipping, Rw, Ford, Ce, Pressel, Sl, Walldius, G, Jungner, I, Folsom, Ar, Chambless, L, Ballantyne, Cm, Panagiotakos, D, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, Mw, Goldbourt, U, Benderly, M, Tanne, D, Whincup, P, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Mayr, A, Schett, G, Wald, N, Ebrahim, S, Lawlor, D, Yarnell, J, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, R, Tybjaerg Hansen, A, Nordestgaard, Bg, Zacho, J, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, de la Cámara, Ag, Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, A, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, Rb, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Benjamin, Ej, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, J, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Laukkanen, Ja, Deeg, Dj, Bremmer, Ma, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Shea, S, Döring, A, Koenig, W, Meisinger, C, Bueno de Mesquita, Hb, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, Rf, Mussolino, M, Hankinson, S, Manson, Je, Knottenbelt, C, Bauer, Ka, Davidson, K, Kirkland, S, Shaffer, J, Korin, Mr, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Luc, G, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Packard, Cj, Sattar, N, Westendorp, Rg, Buckley, Bm, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, Rr, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, Mm, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Basu, S, Cederholm, T, Byberg, L, Gaziano, Jm, Stampfer, M, Ridker, Pm, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Wassertheil Smoller, S, Marmot, Im, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Shepherd, J, Cobbe, S, Ford, I, Robertson, M, He, Y, Ibañez, Am, Feskens, Ej, Walker, M, Watson, S, Erqou, S, Lewington, S, Pennells, L, Perry, Pl, Ray, Kk, Sarwar, N, Alexander, M, Thompson, A, White, Ir, Wood, Am, and Danesh, J.

Subjects
Lung Diseases, Male, Databases, Factual, Plasma-fibrinogen, Blood Pressure, Coronary Disease, 030204 cardiovascular system & hematology, Associations, Body Mass Index, Low-density-lipoprotein, Leukocyte Count, 0302 clinical medicine, Risk Factors, Neoplasms, 030212 general & internal medicine, Stroke, Framingham Risk Score, biology, Smoking, 11 Medical And Health Sciences, General Medicine, Articles, Middle Aged, 3. Good health, C-Reactive Protein, Cholesterol, Regression Analysis, low-density lipoprotein cardiovascular-disease nonvascular mortality regression dilution plasma-fibrinogen mendelian randomization independent predictor prospective cohorts vascular-disease inflammation, Female, Risk assessment, medicine.medical_specialty, Alcohol Drinking, Regression dilution, Motor Activity, Risk Assessment, 03 medical and health sciences, Sex Factors, Cardiovascular-disease, General & Internal Medicine, Internal medicine, Diabetes Mellitus, medicine, Humans, Women, Risk factor, Serum Albumin, Triglycerides, Inflammation, Markers, Independent predictor, Interleukin-6, business.industry, Vascular disease, C-reactive protein, Fibrinogen, medicine.disease, Surgery, Relative risk, biology.protein, Nonvascular mortality, business, Biomarkers
Abstract

Udgivelsesdato: 2010-Jan-9 BACKGROUND: Associations of C-reactive protein (CRP) concentration with risk of major diseases can best be assessed by long-term prospective follow-up of large numbers of people. We assessed the associations of CRP concentration with risk of vascular and non-vascular outcomes under different circumstances. METHODS: We meta-analysed individual records of 160 309 people without a history of vascular disease (ie, 1.31 million person-years at risk, 27 769 fatal or non-fatal disease outcomes) from 54 long-term prospective studies. Within-study regression analyses were adjusted for within-person variation in risk factor levels. RESULTS: Log(e) CRP concentration was linearly associated with several conventional risk factors and inflammatory markers, and nearly log-linearly with the risk of ischaemic vascular disease and non-vascular mortality. Risk ratios (RRs) for coronary heart disease per 1-SD higher log(e) CRP concentration (three-fold higher) were 1.63 (95% CI 1.51-1.76) when initially adjusted for age and sex only, and 1.37 (1.27-1.48) when adjusted further for conventional risk factors; 1.44 (1.32-1.57) and 1.27 (1.15-1.40) for ischaemic stroke; 1.71 (1.53-1.91) and 1.55 (1.37-1.76) for vascular mortality; and 1.55 (1.41-1.69) and 1.54 (1.40-1.68) for non-vascular mortality. RRs were largely unchanged after exclusion of smokers or initial follow-up. After further adjustment for fibrinogen, the corresponding RRs were 1.23 (1.07-1.42) for coronary heart disease; 1.32 (1.18-1.49) for ischaemic stroke; 1.34 (1.18-1.52) for vascular mortality; and 1.34 (1.20-1.50) for non-vascular mortality. INTERPRETATION: CRP concentration has continuous associations with the risk of coronary heart disease, ischaemic stroke, vascular mortality, and death from several cancers and lung disease that are each of broadly similar size. The relevance of CRP to such a range of disorders is unclear. Associations with ischaemic vascular disease depend considerably on conventional risk factors and other markers of inflammation. FUNDING: British Heart Foundation, UK Medical Research Council, BUPA Foundation, and GlaxoSmithKline.

Published
2010

27. Emerging Risk Factors Collaboration. Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies

Author

hompson S, Kaptoge S, White I, Wood A, Thompson SG, White IR, Wood AM, Perry PL, Danesh J, Tipping RW, Ford CE, Simpson LM, Walldius G, Jungner I, Chambless LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Goldbourt U, Benderly M, Tanne D, Whincup PH, Wannamethee SG, Morris RW, Willeit J, Kiechl S, Santer P, Mayr A, Lawlor DA, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Tracy RP, Tybjærg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Taylor J, Guralnik JM, Wallace R, Guralnik J, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Lappas G, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Kiyohara Y, Arima H, Doi Y, Ninomiya T, Rodriguez B, Dekker JM, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Tuomainen TP, Deeg DJ, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engstrom G, Verschuren WM, Blokstra A, Shea S, Döring A, Koenig W, Meisinger C, Mraz W, Bas Bueno de Mesquita H, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson JE, Knottenbelt C, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Crespo CJ, Garcia MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Packard CJ, Sattar N, Ford I, Cantin B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe GD, Ben Shlomo Y, Davey Smith G, Howard BV, Zhang Y, Umans J, Onat A, Wilsgaard T, Ingelsson E, Lind L, Giedraitis V, Lannfelt L, Gaziano JM, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Wassertheil Smoller S, Marmot M, Clarke R, Collins R, Brunner E, Shipley M, Buring J, Cobbe SM, Robertson M, He Y, Marín Ibañez A, Feskens EJ, Kromhout D, Di Angelantonio E, Erqou S, Lewington S, Orfei L, Pennells L, Ray KK, Sarwar N, Alexander M, Thompson A, Walker M, Watson S, Wensley F, Perry P, Danesh J., PANICO, SALVATORE, Hompson, S, Kaptoge, S, White, I, Wood, A, Thompson, Sg, White, Ir, Wood, Am, Perry, Pl, Danesh, J, Tipping, Rw, Ford, Ce, Simpson, Lm, Walldius, G, Jungner, I, Chambless, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Goldbourt, U, Benderly, M, Tanne, D, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Tracy, Rp, Tybjærg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Taylor, J, Guralnik, Jm, Wallace, R, Guralnik, J, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Lappas, G, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engstrom, G, Verschuren, Wm, Blokstra, A, Shea, S, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bas Bueno de Mesquita, H, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, Je, Knottenbelt, C, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Crespo, Cj, Garcia, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, Cj, Sattar, N, Ford, I, Cantin, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Ben Shlomo, Y, Davey Smith, G, Howard, Bv, Zhang, Y, Umans, J, Onat, A, Wilsgaard, T, Ingelsson, E, Lind, L, Giedraitis, V, Lannfelt, L, Gaziano, Jm, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Wassertheil Smoller, S, Marmot, M, Clarke, R, Collins, R, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Robertson, M, He, Y, Marín Ibañez, A, Feskens, Ej, Kromhout, D, Di Angelantonio, E, Erqou, S, Lewington, S, Orfei, L, Pennells, L, Ray, Kk, Sarwar, N, Alexander, M, Thompson, A, Walker, M, Watson, S, Wensley, F, Perry, P, and Danesh, J.

Published
2010

28. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality

Author

Emerging Risk Factors Collaboration, Erqou S, Kaptoge S, Perry PL, Di Angelantonio E, Thompson A, White IR, Marcovina SM, Collins R, Thompson SG, Tipping RW, Ford CE, Simpson LM, Walldius G, Jungner I, Folsom AR, Chambless L, Panagiotakos D, Pitsavos C, Chrysohoou C, Stefanadis C, Goldbourt U, Benderly M, Tanne D, Whincup P, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Santer P, Mayr A, Wald N, Ebrahim S, Lawlor D, Yarnell J, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Cushman M, Psaty BM, Tracy R, Tybjaerg Hansen A, Nordestgaard BG, Frikke Schmidt R, Kamstrup PR, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee A, Smith FB, Taylor J, Guralnik JM, Phillips CL, Wallace RB, Blazer DG, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Rodriguez B, Dekker J, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Deeg DJ, Poppelaars JL, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Döring A, Koenig W, Meisinger C, Mraz W, Bueno de Mesquita HB, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum RF, Mussolino M, Hankinson S, Manson JE, Cooper JA, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Luc G, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Packard CJ, Sattar N, Ford I, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Daniels LB, Laughlin GA, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler MM, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe G, Ben Shlomo Y, Davey Smith G, Howard BV, Zhang Y, Best L, Umans J, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Sundström J, Lind L, Lannfelt L, Gaziano JM, Stampfer M, Ridker PM, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Marmot M, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Cobbe S, Robertson M, He Y, Marin Ibanñez A, Feskens E, Kromhout D, Walker M, Watson S, Lewington S, Orfei L, Pennells L, Ray KK, Sarwar N, Alexander M, Wensley F, Wood AM, Danesh J., PANICO, SALVATORE, Developmental Genetics, EMGO+ - Lifestyle, Overweight and Diabetes, Emerging Risk Factors, Collaboration, Erqou, S, Kaptoge, S, Perry, Pl, Di Angelantonio, E, Thompson, A, White, Ir, Marcovina, Sm, Collins, R, Thompson, Sg, Tipping, Rw, Ford, Ce, Simpson, Lm, Walldius, G, Jungner, I, Folsom, Ar, Chambless, L, Panagiotakos, D, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Goldbourt, U, Benderly, M, Tanne, D, Whincup, P, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, D, Yarnell, J, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Cushman, M, Psaty, Bm, Tracy, R, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Kamstrup, Pr, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, A, Smith, Fb, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, Rb, Blazer, Dg, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Rodriguez, B, Dekker, J, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bueno de Mesquita, Hb, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, Rf, Mussolino, M, Hankinson, S, Manson, Je, Cooper, Ja, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Luc, G, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, Cj, Sattar, N, Ford, I, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Daniels, Lb, Laughlin, Ga, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, Mm, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, G, Ben Shlomo, Y, Davey Smith, G, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Sundström, J, Lind, L, Lannfelt, L, Gaziano, Jm, Stampfer, M, Ridker, Pm, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Marmot, M, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Cobbe, S, Robertson, M, He, Y, Marin Ibanñez, A, Feskens, E, Kromhout, D, Walker, M, Watson, S, Lewington, S, Orfei, L, Pennells, L, Ray, Kk, Sarwar, N, Alexander, M, Wensley, F, Wood, Am, and Danesh, J.

Subjects
medicine.medical_specialty, Context (language use), Coronary Disease, Article, Risk Factors, General & Internal Medicine, Internal medicine, Cause of Death, medicine, Humans, Myocardial infarction, Prospective cohort study, Stroke, biology, business.industry, 11 Medical And Health Sciences, General Medicine, Lipoprotein(a), medicine.disease, Surgery, Relative risk, Nested case-control study, biology.protein, business, Cohort study
Abstract

Udgivelsesdato: 2009-Jul-22 CONTEXT: Circulating concentration of lipoprotein(a) (Lp[a]), a large glycoprotein attached to a low-density lipoprotein-like particle, may be associated with risk of coronary heart disease (CHD) and stroke. OBJECTIVE: To assess the relationship of Lp(a) concentration with risk of major vascular and nonvascular outcomes. STUDY SELECTION: Long-term prospective studies that recorded Lp(a) concentration and subsequent major vascular morbidity and/or cause-specific mortality published between January 1970 and March 2009 were identified through electronic searches of MEDLINE and other databases, manual searches of reference lists, and discussion with collaborators. DATA EXTRACTION: Individual records were provided for each of 126,634 participants in 36 prospective studies. During 1.3 million person-years of follow-up, 22,076 first-ever fatal or nonfatal vascular disease outcomes or nonvascular deaths were recorded, including 9336 CHD outcomes, 1903 ischemic strokes, 338 hemorrhagic strokes, 751 unclassified strokes, 1091 other vascular deaths, 8114 nonvascular deaths, and 242 deaths of unknown cause. Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. Analyses excluded participants with known preexisting CHD or stroke at baseline. DATA SYNTHESIS: Lipoprotein(a) concentration was weakly correlated with several conventional vascular risk factors and it was highly consistent within individuals over several years. Associations of Lp(a) with CHD risk were broadly continuous in shape. In the 24 cohort studies, the rates of CHD in the top and bottom thirds of baseline Lp(a) distributions, respectively, were 5.6 (95% confidence interval [CI], 5.4-5.9) per 1000 person-years and 4.4 (95% CI, 4.2-4.6) per 1000 person-years. The risk ratio for CHD, adjusted for age and sex only, was 1.16 (95% CI, 1.11-1.22) per 3.5-fold higher usual Lp(a) concentration (ie, per 1 SD), and it was 1.13 (95% CI, 1.09-1.18) following further adjustment for lipids and other conventional risk factors. The corresponding adjusted risk ratios were 1.10 (95% CI, 1.02-1.18) for ischemic stroke, 1.01 (95% CI, 0.98-1.05) for the aggregate of nonvascular mortality, 1.00 (95% CI, 0.97-1.04) for cancer deaths, and 1.00 (95% CI, 0.95-1.06) for nonvascular deaths other than cancer. CONCLUSION: Under a wide range of circumstances, there are continuous, independent, and modest associations of Lp(a) concentration with risk of CHD and stroke that appear exclusive to vascular outcomes.

Published
2009

29. The Emerging Risk Factors Collaboration: analysis of individual data on lipid, inflammatory and other markers in over 1.1 million participants in 104 prospective studies of cardiovascular diseases

Author

Danesh, J, Erqou, S, Walker, M, Thompson, Sg, Tipping, R, Ford, C, Pressel, S, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, Edoardo, Tikhonoff, Valerie, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, S, Vanuzzo, D, Pilotto, L, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, J, Phillips, C, Wallace, R, Blazer, D, Khaw, Kt, Jansson, Jh, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, Rs, Pencina, Mj, Bladbjerg, Em, Jorgensen, T, Moller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Bjorkelund, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, T, Rodriguez, B, Bouter, Lm, Heine, Rj, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, J, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, D, Poppelaars, Jl, Meade, T, Cooper, J, Hedblad, B, Berglund, G, Engstrom, G, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Kuller, L, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, De Stavola, B, Knottenbelt, C, Cooper, Ja, Bauer, Ka, Rosenberg, Rd, Naito, Y, Holme, I, Nakagawa, H, Miura, H, Ducimetiere, P, Jouven, X, Crespo, C, Garcia Palmieri, M, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, C, Sattar, N, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, D, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Ben Shlomo, Y, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Meade, Tw, Njolstad, I, Mathiesen, E, Lochen, Ml, Wilsgaard, T, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Rodeghiero, F, Tosetto, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Ford, I, Robertson, M, He, Y, Ibanez, Am, Feskens, Ej, Kromhout, D, Collins, R, Di Angelantonio, E, Kaptoge, S, Lewington, S, Orfei, L, Pennells, L, Perry, P, Ray, K, Sarwar, N, Scherman, M, Thompson, A, Watson, S, Wensley, F, White, Ir, Wood, Am, Emerging Risk Factors Collaboration, Interne Geneeskunde, RS: NUTRIM School of Nutrition and Translational Research in Metabolism, RS: CARIM School for Cardiovascular Diseases, Movement Behavior, Executive board Vrije Universiteit, Clinical Child and Family Studies, Sociology and Social Gerontology, Earth and Climate, Environmental Policy Analysis, Developmental Genetics, Danesh, J, Erqou, S, Walker, M, Thompson, Sg, Tipping, R, Ford, C, Pressel, S, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, J, Phillips, C, Wallace, R, Blazer, D, Khaw, Kt, Jansson, Jh, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jorgensen, T, Moller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Bjorkelund, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, T, Rodriguez, B, Bouter, Lm, Heine, Rj, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, J, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, D, Poppelaars, Jl, Meade, T, Cooper, J, Hedblad, B, Berglund, G, Engstrom, G, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Kuller, L, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, De Stavola, B, Knottenbelt, C, Cooper, Ja, Bauer, Ka, Rosenberg, Rd, Naito, Y, Holme, I, Nakagawa, H, Miura, H, Ducimetiere, P, Jouven, X, Crespo, C, Garcia Palmieri, M, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, C, Sattar, N, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, D, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Ben Shlomo, Y, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Meade, Tw, Njolstad, I, Mathiesen, E, Lochen, Ml, Wilsgaard, T, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Rodeghiero, F, Tosetto, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Ford, I, Robertson, M, He, Y, Ibanez, Am, Feskens, Ej, Kromhout, D, Collins, R, Di Angelantonio, E, Kaptoge, S, Lewington, S, Orfei, L, Pennells, L, Perry, P, Ray, K, Sarwar, N, Scherman, M, Thompson, A, Watson, S, Wensley, F, White, Ir, and Wood, A. M.

Subjects
Databases, Factual, Nutrition and Disease, Epidemiology, Inflammatory markers, middle-aged men, Disease, Leukocyte Count, c-reactive protein, Risk Factors, Voeding en Ziekte, adult-treatment-panel, Prospective Studies, Myocardial infarction, Prospective cohort study, education.field_of_study, biology, plasma-fibrinogen, Asia, Eastern, Confounding, density-lipoprotein cholesterol, Cardiovascular disease, Lipids, myocardial-infarction, Coronary heart disease, Cardiovascular Diseases, Meta-analysis, Lipoproteins, HDL, high blood cholesterol, medicine.medical_specialty, low-dose aspirin, Population, 10-year follow-up, SDG 3 - Good Health and Well-being, Albumins, medicine, Humans, education, Triglycerides, VLAG, Inflammation, Estimation, business.industry, C-reactive protein, medicine.disease, Surgery, Emergency medicine, biology.protein, business, coronary-heart-disease, Biomarkers
Abstract

Many long-term prospective studies have reported on associations of cardiovascular diseases with circulating lipid markers and/or inflammatory markers. Studies have not, however, generally been designed to provide reliable estimates under different circumstances and to correct for within-person variability. The Emerging Risk Factors Collaboration has established a central database on over 1.1 million participants from 104 prospective population-based studies, in which subsets have information on lipid and inflammatory markers, other characteristics, as well as major cardiovascular morbidity and cause-specific mortality. Information on repeat measurements on relevant characteristics has been collected in approximately 340,000 participants to enable estimation of and correction for within-person variability. Re-analysis of individual data will yield up to approximately 69,000 incident fatal or nonfatal first ever major cardiovascular outcomes recorded during about 11.7 million person years at risk. The primary analyses will involve age-specific regression models in people without known baseline cardiovascular disease in relation to fatal or nonfatal first ever coronary heart disease outcomes. This initiative will characterize more precisely and in greater detail than has previously been possible the shape and strength of the age-and sex-specific associations of several lipid and inflammatory markers with incident coronary heart disease outcomes (and, secondarily,with other incident cardiovascular outcomes) under a wide range of circumstances. It will, therefore, help to determine to what extent such associations are independent from possible confounding factors and to what extent such markers (separately and in combination) provide incremental predictive value.

Published
2007

31. Evaluation of a weighting approach for performing sensitivity analysis after multiple imputation

Author

Rezvan, PH, White, IR, Lee, KJ, Carlin, JB, Simpson, JA, Rezvan, PH, White, IR, Lee, KJ, Carlin, JB, and Simpson, JA

Abstract

BACKGROUND: Multiple imputation (MI) is a well-recognised statistical technique for handling missing data. As usually implemented in standard statistical software, MI assumes that data are 'Missing at random' (MAR); an assumption that in many settings is implausible. It is not possible to distinguish whether data are MAR or 'Missing not at random' (MNAR) using the observed data, so it is desirable to discover the impact of departures from the MAR assumption on the MI results by conducting sensitivity analyses. A weighting approach based on a selection model has been proposed for performing MNAR analyses to assess the robustness of results obtained under standard MI to departures from MAR. METHODS: In this article, we use simulation to evaluate the weighting approach as a method for exploring possible departures from MAR, with missingness in a single variable, where the parameters of interest are the marginal mean (and probability) of a partially observed outcome variable and a measure of association between the outcome and a fully observed exposure. The simulation studies compare the weighting-based MNAR estimates for various numbers of imputations in small and large samples, for moderate to large magnitudes of departure from MAR, where the degree of departure from MAR was assumed known. Further, we evaluated a proposed graphical method, which uses the dataset with missing data, for obtaining a plausible range of values for the parameter that quantifies the magnitude of departure from MAR. RESULTS: Our simulation studies confirm that the weighting approach outperformed the MAR approach, but it still suffered from bias. In particular, our findings demonstrate that the weighting approach provides biased parameter estimates, even when a large number of imputations is performed. In the examples presented, the graphical approach for selecting a range of values for the possible departures from MAR did not capture the true parameter value of departure used in generating th

Published
2015

32. Covariate-adjusted measures of discrimination for survival data

Author

White, IR, Rapsomaniki, E, White, IR, and Rapsomaniki, E

Abstract

MotivationDiscrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination statistics in censored survival data. ObjectiveTo develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s). MethodWe define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration. ResultsThe proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were substantially smaller than unadjusted values. The study-specific standard deviation of baseline age was strongly associated with the unadjusted C-index and D-index but not significantly associated with the age-adjusted indices. ConclusionsThe proposed estimators improve meta-analysis comparisons, are easy to implement and give a more meaningful clinical interpretation.

Published
2015
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33. Second cite

Author

White Ir

Subjects
medicine.medical_specialty, business.industry, Contact allergy, Hair dyes, Medicine, Dermatology, business
Published
2006

35. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies

Author

Sarwar, N., Gao, P., Seshasai, Srk, Gobin, R., Kaptoge, S., Di Angelantonio, E., Ingelsson, E., Lawlor, Da, Selvin, E., Stampfer, M., Stehouwer, Cda, Lewington, S., Pennells, L., Thompson, A., Sattar, N., White, Ir, Ray, Kk, Danesh, J., and Emerging Risk Factors Collabora

Abstract

BACKGROUND: Uncertainties persist about the magnitude of associations of diabetes mellitus and fasting glucose concentration with risk of coronary heart disease and major stroke subtypes. We aimed to quantify these associations for a wide range of circumstances. METHODS: We undertook a meta-analysis of individual records of diabetes, fasting blood glucose concentration, and other risk factors in people without initial vascular disease from studies in the Emerging Risk Factors Collaboration. We combined within-study regressions that were adjusted for age, sex, smoking, systolic blood pressure, and body-mass index to calculate hazard ratios (HRs) for vascular disease. FINDINGS: Analyses included data for 698 782 people (52 765 non-fatal or fatal vascular outcomes; 8.49 million person-years at risk) from 102 prospective studies. Adjusted HRs with diabetes were: 2.00 (95% CI 1.83-2.19) for coronary heart disease; 2.27 (1.95-2.65) for ischaemic stroke; 1.56 (1.19-2.05) for haemorrhagic stroke; 1.84 (1.59-2.13) for unclassified stroke; and 1.73 (1.51-1.98) for the aggregate of other vascular deaths. HRs did not change appreciably after further adjustment for lipid, inflammatory, or renal markers. HRs for coronary heart disease were higher in women than in men, at 40-59 years than at 70 years and older, and with fatal than with non-fatal disease. At an adult population-wide prevalence of 10%, diabetes was estimated to account for 11% (10-12%) of vascular deaths. Fasting blood glucose concentration was non-linearly related to vascular risk, with no significant associations between 3.90 mmol/L and 5.59 mmol/L. Compared with fasting blood glucose concentrations of 3.90-5.59 mmol/L, HRs for coronary heart disease were: 1.07 (0.97-1.18) for lower than 3.90 mmol/L; 1.11 (1.04-1.18) for 5.60-6.09 mmol/L; and 1.17 (1.08-1.26) for 6.10-6.99 mmol/L. In people without a history of diabetes, information about fasting blood glucose concentration or impaired fasting glucose status did not significantly improve metrics of vascular disease prediction when added to information about several conventional risk factors. INTERPRETATION: Diabetes confers about a two-fold excess risk for a wide range of vascular diseases, independently from other conventional risk factors. In people without diabetes, fasting blood glucose concentration is modestly and non-linearly associated with risk of vascular disease. FUNDING: British Heart Foundation, UK Medical Research Council, and Pfizer.

Published
2010

36. Variance reduction in randomised trials by inverse probability weighting using the propensity score

Author

Williamson, EJ, Forbes, A, White, IR, Williamson, EJ, Forbes, A, and White, IR

Abstract

In individually randomised controlled trials, adjustment for baseline characteristics is often undertaken to increase precision of the treatment effect estimate. This is usually performed using covariate adjustment in outcome regression models. An alternative method of adjustment is to use inverse probability-of-treatment weighting (IPTW), on the basis of estimated propensity scores. We calculate the large-sample marginal variance of IPTW estimators of the mean difference for continuous outcomes, and risk difference, risk ratio or odds ratio for binary outcomes. We show that IPTW adjustment always increases the precision of the treatment effect estimate. For continuous outcomes, we demonstrate that the IPTW estimator has the same large-sample marginal variance as the standard analysis of covariance estimator. However, ignoring the estimation of the propensity score in the calculation of the variance leads to the erroneous conclusion that the IPTW treatment effect estimator has the same variance as an unadjusted estimator; thus, it is important to use a variance estimator that correctly takes into account the estimation of the propensity score. The IPTW approach has particular advantages when estimating risk differences or risk ratios. In this case, non-convergence of covariate-adjusted outcome regression models frequently occurs. Such problems can be circumvented by using the IPTW adjustment approach.

Published
2014

37. Systematically missing confounders in individual participant data meta-analysis of observational cohort studies

Author

Fibrinogen Studies Collaboration, Jackson, D, White, I, Kostis, JB, Wilson, AC, Folsom, AR, Wu, K, Chambless, L, Benderly, M, Goldbourt, U, Willeit, J, Kiechl, S, Yarnell, JW, Sweetnam, PM, Elwood, PC, Cushman, M, Psaty, BM, Tracy, RP, Tybjaerg-Hansen, A, Haverkate, F, de Maat, MP, Thompson, SG, Fowkes, FG, Lee, AJ, Smith, FB, Salomaa, V, Harald, K, Rasi, V, Vahtera, E, Jousilahti, P, D'Agostino, R, Kannel, WB, Wilson, PW, Tofler, G, Levy, D, Marchioli, R, Valagussa, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Cremer, P, Nagel, D, Curb, JD, Rodriguez, B, Yano, K, Salonen, J, Nyyssönen, K, Tuomainen, TP, Hedblad, B, Engström, G, Berglund, G, Loewel, H, Koenig, W, Hense, HW, Meade, TW, Cooper, JA, De Stavola, B, Knottenbelt, C, Miller, GJ, Bauer, KA, Rosenberg, RD, Sato, S, Kitamura, A, Naito, Y, Iso, H, Palosuo, T, Ducimetiere, P, Amouyel, P, Arveiler, D, Evans, AE, Ferrieres, J, Juhan-Vague, I, Bingham, A, Schulte, H, Assmann, G, Cantin, B, Lamarche, B, Despres, JP, Dagenais, GR, Tunstall-Pedoe, H, Lowe, GD, Woodward, M, Ben-Shlomo, Y, Davey Smith, G, Palmieri, V, Yeh, JL, Rudnicka, A, Brennan, P, Ridker, P, Rodeghiero, F, Tosetto, A, Shepherd, J, Ford, I, Robertson, M, Brunner, E, Shipley, M, Feskens, EJ, Di Angelantonio, E, Kaptoge, S, Lewington, S, Sarwar, N, Walker, M, Watson, S, White, IR, Wood, AM, and Danesh, J

Abstract

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohorts

Published
2009

38. Systematically missing confounders in individual participant data meta-analysis of observational cohort studies

Author

Jackson, D, White, I, Kostis, JB, Wilson, AC, Folsom, AR, Wu, K, Chambless, L, Benderly, M, Goldbourt, U, Willeit, J, Kiechl, S, Yarnell, JW, Sweetnam, PM, Elwood, PC, Cushman, M, Psaty, BM, Tracy, RP, Tybjaerg-Hansen, A, Haverkate, F, de Maat, MP, Thompson, SG, Fowkes, FG, Lee, AJ, Smith, FB, Salomaa, V, Harald, K, Rasi, V, Vahtera, E, Jousilahti, P, D'Agostino, R, Kannel, WB, Wilson, PW, Tofler, G, Levy, D, Marchioli, R, Valagussa, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Cremer, P, Nagel, D, Curb, JD, Rodriguez, B, Yano, K, Salonen, J, Nyyssönen, K, Tuomainen, TP, Hedblad, B, Engström, G, Berglund, G, Loewel, H, Koenig, W, Hense, HW, Meade, TW, Cooper, JA, De Stavola, B, Knottenbelt, C, Miller, GJ, Bauer, KA, Rosenberg, RD, Sato, S, Kitamura, A, Naito, Y, Iso, H, Palosuo, T, Ducimetiere, P, Amouyel, P, Arveiler, D, Evans, AE, Ferrieres, J, Juhan-Vague, I, Bingham, A, Schulte, H, Assmann, G, Cantin, B, Lamarche, B, Despres, JP, Dagenais, GR, Tunstall-Pedoe, H, Lowe, GD, Woodward, M, Ben-Shlomo, Y, Davey Smith, G, Palmieri, V, Yeh, JL, Rudnicka, A, Brennan, P, Ridker, P, Rodeghiero, F, Tosetto, A, Shepherd, J, Ford, I, Robertson, M, Brunner, E, Shipley, M, Feskens, EJ, Di Angelantonio, E, Kaptoge, S, Lewington, S, Sarwar, N, Walker, M, Watson, S, White, IR, Wood, AM, and Danesh, J

Subjects
Statistics and Probability, Male, Nutrition and Disease, Epidemiology, Coronary Disease, Bivariate analysis, Logistic regression, 01 natural sciences, survival analysis, Cohort Studies, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Meta-Analysis as Topic, Voeding en Ziekte, Statistics, Medicine, Humans, Computer Simulation, 030212 general & internal medicine, 0101 mathematics, observational studies, patient data, Survival analysis, time, VLAG, Models, Statistical, aggregate data, model, business.industry, Incidence (epidemiology), Confounding, Fibrinogen, confounders, event outcomes, meta-analysis, Meta-analysis, Data Interpretation, Statistical, missing covariates, logistic-regression analysis, Observational study, Female, heterogeneity, business, Demography, Cohort study, Research Article
Abstract

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154 012 participants in 31 cohorts.† Copyright © 2009 John Wiley & Sons, Ltd.

Published
2009

39. Mercaptobenzothiazole or the mercapto-mix: which should be in the standard series?

Author

Diepgen, T, Bruynzeel, DP, Andersen, KE, Brandão, FM, Bruze, M, Gonçalo, Margarida, Goossens, A, Lathi, A, Mahler, V, Menné, T, White, IR, Wilkinson, JD, and European Environmental Contact Dermatitis Research Group (EECDRG)

Subjects
animal structures, embryonic structures, Dermatite de Contacto, Testes Cutâneos
Abstract

Mercaptobenzothiazole (MBT) compounds are well known contact allergens. To detect rubber allergic patients we use both MBT (2% in petrolatum) and a mercapto-mix with 4 constituents of 0.5% each in our standard series. In this article the EECDRG presents data of in total 32,475 consecutive tested patients attending the respective contact dermatitis clinics from 11 centres in Europe to determine if the mix and MBT detected the same allergic patients. We found 327 patients positive to the mix or MBT, or to both. 261 were positive to the mix and 254 to MBT. MBT was negative in 73 patients who were positive to the mix. If the mix had not been in the standard series, on average 22% of patients allergic to a mercapto-compound would have been missed, for MBT this would have been on average 20%. All clinics would have missed a significant number of positive reactions if both compounds had not been tested. We conclude, that both the mercapto mix and MBT are required in the standard series.

Published
2006

42. Allergic contact dermatitis: epidemiology, molecular mechanisms, in vitro methods and regulatory aspects. Current knowledge assembled at an international workshop at BfR, Germany.

Author

Peiser, M, Peiser, M, Tralau, T, Heidler, J, Api, AM, Arts, JHE, Basketter, DA, English, J, Diepgen, TL, Fuhlbrigge, RC, Gaspari, AA, Johansen, JD, Karlberg, AT, Kimber, I, Lepoittevin, JP, Liebsch, M, Maibach, HI, Martin, SF, Merk, HF, Platzek, T, Rustemeyer, T, Schnuch, A, Vandebriel, RJ, White, IR, Luch, A, Peiser, M, Peiser, M, Tralau, T, Heidler, J, Api, AM, Arts, JHE, Basketter, DA, English, J, Diepgen, TL, Fuhlbrigge, RC, Gaspari, AA, Johansen, JD, Karlberg, AT, Kimber, I, Lepoittevin, JP, Liebsch, M, Maibach, HI, Martin, SF, Merk, HF, Platzek, T, Rustemeyer, T, Schnuch, A, Vandebriel, RJ, White, IR, and Luch, A

Abstract

Contact allergies are complex diseases, and one of the important challenges for public health and immunology. The German 'Federal Institute for Risk Assessment' hosted an 'International Workshop on Contact Dermatitis'. The scope of the workshop was to discuss new discoveries and developments in the field of contact dermatitis. This included the epidemiology and molecular biology of contact allergy, as well as the development of new in vitro methods. Furthermore, it considered regulatory aspects aiming to reduce exposure to contact sensitisers. An estimated 15-20% of the general population suffers from contact allergy. Workplace exposure, age, sex, use of consumer products and genetic predispositions were identified as the most important risk factors. Research highlights included: advances in understanding of immune responses to contact sensitisers, the importance of autoxidation or enzyme-mediated oxidation for the activation of chemicals, the mechanisms through which hapten-protein conjugates are formed and the development of novel in vitro strategies for the identification of skin-sensitising chemicals. Dendritic cell cultures and structure-activity relationships are being developed to identify potential contact allergens. However, the local lymph node assay (LLNA) presently remains the validated method of choice for hazard identification and characterisation. At the workshop the use of the LLNA for regulatory purposes and for quantitative risk assessment was also discussed.

Published
2012

50. Contact Sensitization To 5-chloro-2-methyl-4-isothiazolin-3-one and 2-methyl-4-isothiazolin-3-one (mci/mi) - a European Multicenter Study

Author

UCL, Menne, T., Frosch, PJ., Veien, NK., Hannuksela, M., Bjorkner, B., Lachapelle, Jean-Marie, White, IR., Vejlsgaard, G., Schubert, HJ., Andersen, KE., Doomsgoossens, A., Shaw, S., Wilkinson, JD., Camarasa, JG., Wahlberg, JE., Brandrup, F., Brandao, FM., Vanderwalle, HB., Angelini, G., Thestruppedersen, K., Burrows, D., Ducombs, G., Tosti, A., UCL, Menne, T., Frosch, PJ., Veien, NK., Hannuksela, M., Bjorkner, B., Lachapelle, Jean-Marie, White, IR., Vejlsgaard, G., Schubert, HJ., Andersen, KE., Doomsgoossens, A., Shaw, S., Wilkinson, JD., Camarasa, JG., Wahlberg, JE., Brandrup, F., Brandao, FM., Vanderwalle, HB., Angelini, G., Thestruppedersen, K., Burrows, D., Ducombs, G., and Tosti, A.

Abstract

The frequency of positive reactions to 5-chloro-2-methyl-4-isothiazolin-3-one and 2-methyl-4-isothiazolin-3-one (MCI/MI) were studied at 22 European contact dermatitis clinics over a period of 1 year. A total of 4713 patients participated. All the patients were patch tested with nickel sulphate, formaldehyde, paraben-mix, and MCI/MI. 19.4% of the patients had positive patch tests to nickel, making this the most common allergen. 3% of the patients reacted to 100 ppm MCI/MI, while 2.6% reacted to formaldehyde and 1.1% to parabens. There was great variation in the frequency of MCI/MI sensitivity among the 22 centres. MCI/MI contact allergy was most common among women and in patients with facial dermatitis, while it was rarely seen in patients with dermatitis on the lower legs. There were no fluctuations in the number of positive patch tests to MCI/MI on a monthly basis when the results from all centres were combined. 117 of the 141 MCI/MI sensitized patients included in the study were retested. 88% had positive patch tests when retested. 101 of the MCI/MI-sensitive patients participated in a double-blind, placebo-controlled product use test. This test showed that 31% of the MCI/MI-sensitive patients had a positive reaction to a MCI/MI-preserved product. Only a few patients reacted to a control product. It is concluded that the preservative MCI/MI is an important new contact allergen.

Published
1991

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