Paul C Lambert

Summary

Affiliation: University of Leicester
Country: UK

Publications

  1. ncbi request reprint Estimating and modeling the cure fraction in population-based cancer survival analysis
    Paul C Lambert
    Department of Health Sciences, Centre for Biostatistics and Genetic Epidemiology, University of Leicester, 22 28 Princess Road West, Leicester LE1 6TP, UK
    Biostatistics 8:576-94. 2007
  2. ncbi request reprint How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS
    Paul C Lambert
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, UK
    Stat Med 24:2401-28. 2005
  3. ncbi request reprint Additive and multiplicative covariate regression models for relative survival incorporating fractional polynomials for time-dependent effects
    Paul C Lambert
    Department of Health Sciences, Centre for Biostatistics and Genetic Epidemiology, University of Leicester, 22 28 Princess Road West, Leicester, LE1 6TP, UK
    Stat Med 24:3871-85. 2005
  4. pmc Bivariate random-effects meta-analysis and the estimation of between-study correlation
    Richard D Riley
    Centre for Medical Statistics and Health Evaluation, School of Health Sciences, University of Liverpool, Shelley s Cottage, Brownlow Street, Liverpool, L69 3GS, UK
    BMC Med Res Methodol 7:3. 2007
  5. ncbi request reprint Evidence-based sample size calculations based upon updated meta-analysis
    Alexander J Sutton
    Department of Health Sciences, University of Leicester, Leicester, UK
    Stat Med 26:2479-500. 2007
  6. pmc Different strategies for screening and prevention of type 2 diabetes in adults: cost effectiveness analysis
    Clare L Gillies
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Leicester LE1 7RH
    BMJ 336:1180-5. 2008
  7. pmc Individual patient data meta-analysis of survival data using Poisson regression models
    Michael J Crowther
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Adrian Building, University Road, Leicester LE1 7RH, UK
    BMC Med Res Methodol 12:34. 2012
  8. pmc Flexible parametric modelling of cause-specific hazards to estimate cumulative incidence functions
    Sally R Hinchliffe
    Department of Health Sciences, Centre for Biostatistics and Genetic Epidemiology, University of Leicester, Leicester, UK
    BMC Med Res Methodol 13:13. 2013
  9. ncbi request reprint Flexible parametric models for relative survival, with application in coronary heart disease
    Christopher P Nelson
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Leicester, U K
    Stat Med 26:5486-98. 2007
  10. ncbi request reprint Sensitivity analyses allowed more appropriate and reliable meta-analysis conclusions for multiple outcomes when missing data was present
    Richard D Riley
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Princess Road West, Leicester LE1 6TP, United Kingdom
    J Clin Epidemiol 57:911-24. 2004

Detail Information

Publications28

  1. ncbi request reprint Estimating and modeling the cure fraction in population-based cancer survival analysis
    Paul C Lambert
    Department of Health Sciences, Centre for Biostatistics and Genetic Epidemiology, University of Leicester, 22 28 Princess Road West, Leicester LE1 6TP, UK
    Biostatistics 8:576-94. 2007
    ..We compare the estimates of relative survival and the cure fraction between the 2 types of model and also investigate the importance of modeling the ancillary parameters in the selected parametric distribution for both types of model...
  2. ncbi request reprint How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS
    Paul C Lambert
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, UK
    Stat Med 24:2401-28. 2005
    ..The choice of 'vague' prior distribution can lead to a marked variation in results, particularly in small studies. Sensitivity to the choice of prior distribution should always be assessed...
  3. ncbi request reprint Additive and multiplicative covariate regression models for relative survival incorporating fractional polynomials for time-dependent effects
    Paul C Lambert
    Department of Health Sciences, Centre for Biostatistics and Genetic Epidemiology, University of Leicester, 22 28 Princess Road West, Leicester, LE1 6TP, UK
    Stat Med 24:3871-85. 2005
    ..All models presented in this paper can be estimated within a generalized linear models framework and thus can be implemented using standard software...
  4. pmc Bivariate random-effects meta-analysis and the estimation of between-study correlation
    Richard D Riley
    Centre for Medical Statistics and Health Evaluation, School of Health Sciences, University of Liverpool, Shelley s Cottage, Brownlow Street, Liverpool, L69 3GS, UK
    BMC Med Res Methodol 7:3. 2007
    ..A multivariate random-effects meta-analysis must incorporate and estimate the between-study correlation (rhoB)...
  5. ncbi request reprint Evidence-based sample size calculations based upon updated meta-analysis
    Alexander J Sutton
    Department of Health Sciences, University of Leicester, Leicester, UK
    Stat Med 26:2479-500. 2007
    ..This raises issues regarding the appropriateness of the use of random effect models when designing and drawing inferences across a series of studies...
  6. pmc Different strategies for screening and prevention of type 2 diabetes in adults: cost effectiveness analysis
    Clare L Gillies
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Leicester LE1 7RH
    BMJ 336:1180-5. 2008
    ....
  7. pmc Individual patient data meta-analysis of survival data using Poisson regression models
    Michael J Crowther
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Adrian Building, University Road, Leicester LE1 7RH, UK
    BMC Med Res Methodol 12:34. 2012
    ..We describe an alternative approach using Poisson based Generalised Linear Models (GLMs)...
  8. pmc Flexible parametric modelling of cause-specific hazards to estimate cumulative incidence functions
    Sally R Hinchliffe
    Department of Health Sciences, Centre for Biostatistics and Genetic Epidemiology, University of Leicester, Leicester, UK
    BMC Med Res Methodol 13:13. 2013
    ..They arise when a patient is at risk of more than one mutually exclusive event, such as death from different causes, and the occurrence of one of these may prevent any other event from ever happening...
  9. ncbi request reprint Flexible parametric models for relative survival, with application in coronary heart disease
    Christopher P Nelson
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Leicester, U K
    Stat Med 26:5486-98. 2007
    ....
  10. ncbi request reprint Sensitivity analyses allowed more appropriate and reliable meta-analysis conclusions for multiple outcomes when missing data was present
    Richard D Riley
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Princess Road West, Leicester LE1 6TP, United Kingdom
    J Clin Epidemiol 57:911-24. 2004
    ..Dissemination bias, in how and what outcomes are reported or published, may be causing this incompleteness. This article illustrates these problems and presents possible sensitivity analyses to allow the most reliable conclusions...
  11. doi request reprint The impact of under and over-recording of cancer on death certificates in a competing risks analysis: a simulation study
    Sally R Hinchliffe
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, 2nd Floor Adrian Building, University Road, University of Leicester, Leicester LE1 7RH, UK
    Cancer Epidemiol 37:11-9. 2013
    ..However, it is well documented that cause of death information taken from death certificates is often lacking in accuracy and completeness...
  12. ncbi request reprint Predicting costs over time using Bayesian Markov chain Monte Carlo methods: an application to early inflammatory polyarthritis
    Nicola J Cooper
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, UK
    Health Econ 16:37-56. 2007
    ..To obtain predicted costs on the original cost scale (rather than the log-cost scale) two different retransformation factors were applied. All analyses were carried out using Bayesian Markov chain Monte Carlo (MCMC) simulation methods...
  13. pmc Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis
    Clare L Gillies
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Leicester LE1 7RH
    BMJ 334:299. 2007
    ..To quantify the effectiveness of pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance...
  14. doi request reprint Flexible parametric joint modelling of longitudinal and survival data
    Michael J Crowther
    Department of Health Sciences, University of Leicester, Adrian Building, University Road, Leicester, LE1 7RH, UK
    Stat Med 31:4456-71. 2012
    ..We provide user-friendly Stata software...
  15. doi request reprint Projecting cancer incidence using age-period-cohort models incorporating restricted cubic splines
    Mark J Rutherford
    University of Leicester, UK
    Int J Biostat 8:33. 2012
    ..Secondly, the new method uses more recent trends to dictate the future projections than previously proposed methods...
  16. doi request reprint Comparison of methods for calculating relative survival in population-based studies
    Mark J Rutherford
    Department of Health Sciences, 2nd Floor, Adrian Building, University of Leicester, LE1 7RH, UK
    Cancer Epidemiol 36:16-21. 2012
    ..This can be obtained by pooling all ages or, more commonly, by using age-standardisation. The various methods for providing a single figure estimate of relative survival can give very different estimates...
  17. ncbi request reprint Meta-analysis of heterogeneously reported trials assessing change from baseline
    Keith R Abrams
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, UK
    Stat Med 24:3823-44. 2005
    ....
  18. ncbi request reprint Providing more up-to-date estimates of patient survival: a comparison of standard survival analysis with period analysis using life-table methods and proportional hazards models
    Lucy K Smith
    Department of Health Sciences, University of Leicester, 22 28 Princess Road West, Leicester, LE1 6TP, UK
    J Clin Epidemiol 57:14-20. 2004
    ..We use statistical models to further develop the method of period analysis, providing more up-to-date estimates of survival and the ability to explore differences in survival by covariates and adjust for case mix...
  19. ncbi request reprint The analysis of peak expiratory flow data using a three-level hierarchical model
    Paul C Lambert
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, 22 28 Princess Road West, Leicester LE1 6TP, UK
    Stat Med 23:3821-39. 2004
    ..In addition, the Bayesian models provide an intuitive and simple way to investigate the within-subject variance components...
  20. ncbi request reprint Estimating the cost-effectiveness of an intervention in a clinical trial when partial cost information is available: a Bayesian approach
    Paul C Lambert
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Leicester, UK
    Health Econ 17:67-81. 2008
    ..The models estimate the interrelationships between the four cost components and survival, and thus enable a predictive distribution for each missing cost item to be obtained...
  21. doi request reprint Adjusting for the proportion of cancer deaths in the general population when using relative survival: a sensitivity analysis
    Sally R Hinchliffe
    Department of Health Sciences, Centre for Biostatistics and Genetic Epidemiology, University of Leicester, UK
    Cancer Epidemiol 36:148-52. 2012
    ..One potential bias when using relative survival that is most often overlooked occurs when there are a high proportion of deaths due to a specific cancer in the external group...
  22. ncbi request reprint Temporal trends in the proportion cured for cancer of the colon and rectum: a population-based study using data from the Finnish Cancer Registry
    Paul C Lambert
    Department of Health Sciences, Centre for Biostatistics and Genetic Epidemiology, University of Leicester, Leicester, United Kingdom, and Department of Oncology, Helsinki University Central Hospital, Finland
    Int J Cancer 121:2052-9. 2007
    ..The reasons for these impressive increases in patient survival are complex, but are highly likely to be strongly related to many improvements in cancer care over this same time period...
  23. doi request reprint Quantifying differences in breast cancer survival between England and Norway
    Paul C Lambert
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, 2nd Floor Adrian Building, University of Leicester, University Road, Leicester LE1 7RH, UK
    Cancer Epidemiol 35:526-33. 2011
    ..Survival from breast cancer is lower in the UK than in some other European countries. We compared survival in England and Norway by age and time from diagnosis...
  24. doi request reprint Relative survival: what can cardiovascular disease learn from cancer?
    Christopher P Nelson
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, 2nd Floor, Adrian Building, University Road, Leicester LE1 7RH, UK
    Eur Heart J 29:941-7. 2008
    ..Relative survival, the ratio of the observed and the expected survival rates, is applied routinely in cancer studies and may improve on current methods for assessment of survival in CHD...
  25. ncbi request reprint A Bayesian approach to evaluating net clinical benefit allowed for parameter uncertainty
    Alexander J Sutton
    Department of Health Sciences, University of Leicester, 22 28 Princess Road West, Leicester LE1 6TP, United Kingdom
    J Clin Epidemiol 58:26-40. 2005
    ..The potential benefits and harms of a treatment policy may differ between individuals. If these benefits and harms are not evaluated distinctly, and in a quantitative framework, transparency can be lost in the decision-making process...
  26. ncbi request reprint Bayesian implementation of a genetic model-free approach to the meta-analysis of genetic association studies
    Cosetta Minelli
    Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Leicester, UK
    Stat Med 24:3845-61. 2005
    ..However, under some circumstances the prospective likelihood has been shown to produce identical results and it is usually preferred for its simplicity. In our meta-analyses the two likelihoods give very similar results...
  27. ncbi request reprint A systematic review of molecular and biological tumor markers in neuroblastoma
    Richard D Riley
    Departments of Health Sciences, Medical Education, University of Leicester, Leicester
    Clin Cancer Res 10:4-12. 2004
    ..Experimental Design: A well-defined, reproducible search strategy was used to identify the relevant literature from 1966 to February 2000...
  28. doi request reprint Modelling time to death or discharge in neonatal care: an application of competing risks
    Sally R Hinchliffe
    Department of Health Sciences, University of Leicester, Leicester, UK
    Paediatr Perinat Epidemiol 27:426-33. 2013
    ..We present an analysis using competing risks methodology which allows the simultaneous modelling of babies who die in neonatal care and those who survive to discharge...