Search

Your search keyword '"Lambert, Paul C"' showing total 731 results
Start Over Author "Lambert, Paul C"
731 results on '"Lambert, Paul C"'

5. Health outcomes after myocardial infarction: A population study of 56 million people in England

Author

Hall, Marlous, Smith, Lesley, Wu, Jianhua, Hayward, Chris, Batty, Jonathan A., Lambert, Paul C., Hemingway, Harry, and Gale, Chris P.

Subjects
Dementia -- Statistics -- Health aspects, Medical research -- Health aspects -- Statistics, Medicine, Experimental -- Health aspects -- Statistics, Heart attack -- Statistics -- Health aspects, Diabetes -- Health aspects -- Statistics, Atrial fibrillation -- Health aspects -- Statistics, Heart -- Health aspects -- Statistics, Cardiac patients -- Statistics -- Health aspects, Heart failure -- Health aspects -- Statistics, Biological sciences
Abstract

Background The occurrence of a range of health outcomes following myocardial infarction (MI) is unknown. Therefore, this study aimed to determine the long-term risk of major health outcomes following MI and generate sociodemographic stratified risk charts in order to inform care recommendations in the post-MI period and underpin shared decision making. Methods and findings This nationwide cohort study includes all individuals aged [greater than or equal to]18 years admitted to one of 229 National Health Service (NHS) Trusts in England between 1 January 2008 and 31 January 2017 (final follow-up 27 March 2017). We analysed 11 non-fatal health outcomes (subsequent MI and first hospitalisation for heart failure, atrial fibrillation, cerebrovascular disease, peripheral arterial disease, severe bleeding, renal failure, diabetes mellitus, dementia, depression, and cancer) and all-cause mortality. Of the 55,619,430 population of England, 34,116,257 individuals contributing to 145,912,852 hospitalisations were included (mean age 41.7 years (standard deviation [SD 26.1]); n = 14,747,198 (44.2%) male). There were 433,361 individuals with MI (mean age 67.4 years [SD 14.4)]; n = 283,742 (65.5%) male). Following MI, all-cause mortality was the most frequent event (adjusted cumulative incidence at 9 years 37.8% (95% confidence interval [CI] [37.6,37.9]), followed by heart failure (29.6%; 95% CI [29.4,29.7]), renal failure (27.2%; 95% CI [27.0,27.4]), atrial fibrillation (22.3%; 95% CI [22.2,22.5]), severe bleeding (19.0%; 95% CI [18.8,19.1]), diabetes (17.0%; 95% CI [16.9,17.1]), cancer (13.5%; 95% CI [13.3,13.6]), cerebrovascular disease (12.5%; 95% CI [12.4,12.7]), depression (8.9%; 95% CI [8.7,9.0]), dementia (7.8%; 95% CI [7.7,7.9]), subsequent MI (7.1%; 95% CI [7.0,7.2]), and peripheral arterial disease (6.5%; 95% CI [6.4,6.6]). Compared with a risk-set matched population of 2,001,310 individuals, first hospitalisation of all non-fatal health outcomes were increased after MI, except for dementia (adjusted hazard ratio [aHR] 1.01; 95% CI [0.99,1.02];p = 0.468) and cancer (aHR 0.56; 95% CI [0.56,0.57];p < 0.001). The study includes data from secondary care only-as such diagnoses made outside of secondary care may have been missed leading to the potential underestimation of the total burden of disease following MI. Conclusions In this study, up to a third of patients with MI developed heart failure or renal failure, 7% had another MI, and 38% died within 9 years (compared with 35% deaths among matched individuals). The incidence of all health outcomes, except dementia and cancer, was higher than expected during the normal life course without MI following adjustment for age, sex, year, and socioeconomic deprivation. Efforts targeted to prevent or limit the accrual of chronic, multisystem disease states following MI are needed and should be guided by the demographic-specific risk charts derived in this study., Author(s): Marlous Hall 1,2,*, Lesley Smith 3, Jianhua Wu 2,4, Chris Hayward 1,2, Jonathan A. Batty 1,2, Paul C. Lambert 5,6, Harry Hemingway 7,8,9,10, Chris P. Gale 1,2,11 Introduction Information [...]

Published
2024
Full Text
View/download PDF

8. Estimating causal effects in the presence of competing events using regression standardisation with the Stata command standsurv

Author

Syriopoulou, Elisavet, Mozumder, Sarwar I, Rutherford, Mark J, and Lambert, Paul C

Subjects
Statistics - Methodology
Abstract

When interested in a time-to-event outcome, competing events that prevent the occurrence of the event of interest may be present. In the presence of competing events, various statistical estimands have been suggested for defining the causal effect of treatment on the event of interest. Depending on the estimand, the competing events are either accommodated or eliminated, resulting in causal effects with different interpretation. The former approach captures the total effect of treatment on the event of interest while the latter approach captures the direct effect of treatment on the event of interest that is not mediated by the competing event. Separable effects have also been defined for settings where the treatment effect can be partitioned into its effect on the event of interest and its effect on the competing event through different causal pathways. We outline various causal effects that may be of interest in the presence of competing events, including total, direct and separable effects, and describe how to obtain estimates using regression standardisation with the Stata command standsurv. Regression standardisation is applied by obtaining the average of individual estimates across all individuals in a study population after fitting a survival model. With standsurv several contrasts of interest can be calculated including differences, ratios and other user-defined functions. Confidence intervals can also be obtained using the delta method. Throughout we use an example analysing a publicly available dataset on prostate cancer to allow the reader to replicate the analysis and further explore the different effects of interest.

Published
2021

11. A multi-state model incorporating estimation of excess hazards and multiple time scales

Author

Weibull, Caroline E., Lambert, Paul C., Eloranta, Sandra, Andersson, Therese M. L., Dickman, Paul W., and Crowther, Michael J.

Subjects
Statistics - Methodology, Statistics - Applications
Abstract

As cancer patient survival improves, late effects from treatment are becoming the next clinical challenge. Chemotherapy and radiotherapy, for example, potentially increase the risk of both morbidity and mortality from second malignancies and cardiovascular disease. To provide clinically relevant population-level measures of late effects, it is of importance to (1) simultaneously estimate the risks of both morbidity and mortality, (2) partition these risks into the component expected in the absence of cancer and the component due to the cancer and its treatment, and (3) incorporate the multiple time scales of attained age, calendar time, and time since diagnosis. Multi-state models provide a framework for simultaneously studying morbidity and mortality, but do not solve the problem of partitioning the risks. However, this partitioning can be achieved by applying a relative survival framework, by allowing is to directly quantify the excess risk. This paper proposes a combination of these two frameworks, providing one approach to address (1)-(3). Using recently developed methods in multi-state modeling, we incorporate estimation of excess hazards into a multi-state model. Both intermediate and absorbing state risks can be partitioned and different transitions are allowed to have different and/or multiple time scales. We illustrate our approach using data on Hodgkin lymphoma patients and excess risk of diseases of the circulatory system, and provide user-friendly Stata software with accompanying example code.

Published
2020

17. Have the recent advancements in cancer therapy and survival benefitted patients of all age groups across the Nordic countries? NORDCAN survival analyses 2002-2021

Author

Johansson, Anna L.V., primary, Kønig, Simon M., additional, Larønningen, Siri, additional, Engholm, Gerda, additional, Kroman, Niels, additional, Seppä, Karri, additional, Malila, Nea, additional, Steig, Bjarni Á., additional, Gudmundsdóttir, Eva Maria, additional, Ólafsdóttir, Elínborg J., additional, Lundberg, Frida E., additional, Andersson, Therese M.-L., additional, Lambert, Paul C., additional, Lambe, Mats, additional, Pettersson, David, additional, Aagnes, Bjarte, additional, Friis, Søren, additional, and Storm, Hans, additional

Published
2024
Full Text
View/download PDF

25. The impact of excluding or including Death Certificate Initiated (DCI) cases on estimated cancer survival: A simulation study

Author

Andersson, Therese M.-L., Myklebust, Tor Åge, Rutherford, Mark J., Møller, Bjørn, Soerjomataram, Isabelle, Arnold, Melina, Bray, Freddie, Parkin, D. Max, Sasieni, Peter, Bucher, Oliver, De, Prithwish, Engholm, Gerda, Gavin, Anna, Little, Alana, Porter, Geoff, Ramanakumar, Agnihotram V., Saint-Jacques, Nathalie, Walsh, Paul M., Woods, Ryan R., and Lambert, Paul C.

Published
2021
Full Text
View/download PDF

26. Exploring the impact of cancer registry completeness on international cancer survival differences: a simulation study

Author

Andersson, Therese M.-L., Rutherford, Mark J., Myklebust, Tor Åge, Møller, Bjørn, Soerjomataram, Isabelle, Arnold, Melina, Bray, Freddie, Parkin, D. Max, Sasieni, Peter, Bucher, Oliver, De, Prithwish, Engholm, Gerda, Gavin, Anna, Little, Alana, Porter, Geoff, Ramanakumar, Agnihotram V., Saint-Jacques, Nathalie, Walsh, Paul M., Woods, Ryan R., and Lambert, Paul C.

Published
2021
Full Text
View/download PDF

30. Potential bias introduced by not including multiple time-scales in survival analysis: a simulation study.

Author

Batyrbekova, Nurgul, Bower, Hannah, Dickman, Paul W., Szulkin, Robert, Lambert, Paul C., and Andersson, Therese M.-L.

Subjects
SURVIVAL analysis (Biometry), RATIO & proportion, PARAMETRIC modeling
Abstract

When analyzing cohort data, we rarely consider potential simultaneous effects of multiple time-scales on estimated survival proportions and hazard ratios. Instead, often, only one time-scale, such as time-on-study or attained age, is taken as the main time-scale and the other time-scale(s) included in the model as time-fixed covariate(s). In this simulation study, we investigate the potential bias in estimated survival proportions and hazard ratios by not modeling multiple time-scales. We simulate data with two time-scales, under various scenarios, and a binary covariate as the exposure of interest. Flexible parametric models with one time-scale were fitted to the simulated data, including the exposure variable of interest and the other time-scale as a fixed covariate. For many of our simulated scenarios, the models with one time-scale showed small bias for the survival proportions. Bias in the log hazard ratios (for the covariate of interest) was observed when there were non-proportional hazards on the second time-scale. If one is modeling only one time-scale it is advisable to include non-proportional hazards and interactions with the time-scale. Exploration of approaches to modeling multiple time-scales is outside the scope of this study. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

37. Progress in cancer survival, mortality, and incidence in seven high-income countries 1995–2014 (ICBP SURVMARK-2): a population-based study

Author

Arnold, Melina, Rutherford, Mark J, Bardot, Aude, Ferlay, Jacques, Andersson, Therese M-L, Myklebust, Tor Åge, Tervonen, Hanna, Thursfield, Vicky, Ransom, David, Shack, Lorraine, Woods, Ryan R, Turner, Donna, Leonfellner, Suzanne, Ryan, Susan, Saint-Jacques, Nathalie, De, Prithwish, McClure, Carol, Ramanakumar, Agnihotram V, Stuart-Panko, Heather, Engholm, Gerda, Walsh, Paul M, Jackson, Christopher, Vernon, Sally, Morgan, Eileen, Gavin, Anna, Morrison, David S, Huws, Dyfed W, Porter, Geoff, Butler, John, Bryant, Heather, Currow, David C, Hiom, Sara, Parkin, D Max, Sasieni, Peter, Lambert, Paul C, Møller, Bjørn, Soerjomataram, Isabelle, and Bray, Freddie

Published
2019
Full Text
View/download PDF

45. Acute heart failure presentation, management and outcomes in cancer patients: a national longitudinal study

Author

Coles, Briana, primary, Welch, Catherine A, additional, Motiwale, Rishabh S, additional, Teece, Lucy, additional, Oliver-Williams, Clare, additional, Weston, Clive, additional, de Belder, Mark A, additional, Lambert, Paul C, additional, Rutherford, Mark J, additional, Paley, Lizz, additional, Kadam, Umesh T, additional, Lawson, Claire A, additional, Deanfield, John, additional, Peake, Michael D, additional, McDonagh, Theresa, additional, Sweeting, Michael J, additional, and Adlam, David, additional

Published
2023
Full Text
View/download PDF

48. Age-specific survival trends and life-years lost in women with breast cancer 1990–2016: the NORDCAN survival studies

Author

Lundberg, Frida E., primary, Kroman, Niels, additional, Lambe, Mats, additional, Andersson, Therese M.-L., additional, Engholm, Gerda, additional, Johannesen, Tom Børge, additional, Virtanen, Anni, additional, Pettersson, David, additional, Ólafsdóttir, Elínborg J., additional, Birgisson, Helgi, additional, Lambert, Paul C., additional, Mørch, Lina Steinrud, additional, and Johansson, Anna L. V., additional

Published
2022
Full Text
View/download PDF

49. sj-docx-1-mdm-10.1177_0272989X231184247 – Supplemental material for Survival Extrapolation Incorporating General Population Mortality Using Excess Hazard and Cure Models: A Tutorial

Author

Sweeting, Michael J., Rutherford, Mark J., Jackson, Dan, Lee, Sangyu, Latimer, Nicholas R., Hettle, Robert, and Lambert, Paul C.

Subjects
Public Health and Health Services not elsewhere classified, Health and Community Services, Sociological Methodology and Research Methods
Abstract

Supplemental material, sj-docx-1-mdm-10.1177_0272989X231184247 for Survival Extrapolation Incorporating General Population Mortality Using Excess Hazard and Cure Models: A Tutorial by Michael J. Sweeting, Mark J. Rutherford, Dan Jackson, Sangyu Lee, Nicholas R. Latimer, Robert Hettle and Paul C. Lambert in Medical Decision Making

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results