Nell'era della medicina basata sulle evidenze, i professionisti della salute devono essere in grado di comprendere a pieno il progetto, l'analisi e l'interpretazione dei risultati della ricerca. Dovrebbero inoltre possedere gli strumenti per valutare i bisogni delle loro comunità e fornire risposte adeguate. Per raggiungere questi obiettivi, i medici hanno la necessità di familiarizzare con i concetti base dell'epidemiologia e della biostatistica.
Ma l'epidemiologia è più dello "studio di". L'applicazione pratica è determinante per affrontare i temi di salute pubblica. Perciò questo libro non affronta solo la teoria, ma guida il lettore ad applicarla nella pratica clinica. Infatti ogni capitolo presenta uno o più esempi specifici su come realizzare un’analisi epidemiologica o statistica e fornisce al lettore la possibilità di riprodurre l’analisi descritta utilizzando i software e i database scaricabili. L’obiettivo finale consiste nell’illustrare i metodi epidemiologici e biostatistici applicati nella ricerca clinica e nello sviluppare la capacità di realizzare analisi di dati clinici utilizzando software informatici.
In the era of Evidence Based Medicine, health professionals are required to fully understand design, analysis and interpretation of the results of research. Furthermore, they should be able to assess the needs of their communities and respond accordingly. To achieve these goals, clinicians need to be familiar with the basic concepts of epidemiology and biostatistics.
But epidemiology is more than “the study of.” Its application and practice are essential to address public health issues. That is why this book provides not only the theory, but also the opportunity of applying it in practice. In fact, each chapter presents one or more specific examples on how to perform an epidemiological or statistical data analysis and includes download access to the software and databases, giving the reader the possibility of replicating the analyses described.
The final purpose is, therefore, to introduce epidemiologic and biostatistical methods as applied to clinical research, and to develop proficiency with computer software for performing the analysis of clinical datasets.
Maggiori Informazioni
Autore
La Torre Giuseppe
Editore
Seed
Anno
2010
Tipologia
Libro
Lingua
Inglese
Indice
1. Measures of Occurrence...................................................................................................... 11 1.1. Introduction ........................................................................................................................ 11 1.2. Prevalence........................................................................................................................... 12 1.3. Incidence.............................................................................................................................. 13 1.4. Practical issues................................................................................................................... 16 1.5. Practical examples............................................................................................................ 16 References ................................................................................................................................... 22 2. Measures of Association...................................................................................................... 23 2.1. Relative risk......................................................................................................................... 23 2.2. Risk difference.................................................................................................................... 25 2.3. Other measures of attributable risk.......................................................................... 26 2.4. Practical examples............................................................................................................ 28 References.................................................................................................................................... 35 3. Controlling for Confounding............................................................................................. 37 3.1. What is confounding in epidemiology?.................................................................... 37 3.2. Controlling for confounding factors.......................................................................... 38 3.3. How to control for confounding factors................................................................... 39 3.4. Practical examples............................................................................................................ 42 References.................................................................................................................................... 52 4. Cross-Sectional Studies........................................................................................................ 53 4.1. Introduction........................................................................................................................ 53 4.2. Performing a cross-sectional study........................................................................... 55 4.3. A practical example.......................................................................................................... 56 References.................................................................................................................................... 66 5. Cohort Studies.......................................................................................................................... 67 5.1. What is a cohort study?................................................................................................... 67 5.2. Why do we need a cohort study?................................................................................ 68 5.3. The eligibility criteria...................................................................................................... 68 5.4. The structure of a cohort study................................................................................... 69 5.5. Censoring............................................................................................................................. 70 5.6. The statistical analysis in a cohort study................................................................ 70 5.7. Practical examples ........................................................................................................... 71 References.................................................................................................................................... 84 6. Experimental Studies............................................................................................................ 87 6.1. What is a sample experimental study?..................................................................... 87 6.2. Why do we need an experimental study?............................................................... 88 6.3. The eligibility criteria...................................................................................................... 88 6.4. The randomisation process........................................................................................... 89 6.5. The blinding........................................................................................................................ 90 6.6. The structure of an experimental study.................................................................. 90 6.7. The statistical analysis in an experimental study................................................ 94 6.8. Practical examples ........................................................................................................... 95 References..................................................................................................................................100 7. Temporal Trend Analysis..................................................................................................101 7.1. Introduction......................................................................................................................101 7.2. Basic principles of temporal trend analysis.........................................................105 7.3. Practical examples .........................................................................................................112 References..................................................................................................................................116 8. The Surveillance of Sexually Transmitted Infections: the Theory and the Practice....119 8.1. Introduction......................................................................................................................119 8.2. Surveillance of sexually transmitted infections in the third millennium................120 8.3. Attributes of a STI surveillance system..................................................................122 8.4. Universal versus sentinel surveillance systems.................................................127 8.5. How to perform STI surveillance..............................................................................128 8.6. Data management and analysis ................................................................................134 8.7. Practical exercises for analysing a dataset of STIs............................................135 References .................................................................................................................................156 9. Systematic Reviews and Meta-Analysis of Clinical Trials...............................159 9.1. What is a systematic review? What is a meta-analysis?.................................159 9.2. Why do we need systematic reviews and meta-analyses?............................160 9.3. Practical steps of a meta-analysis.............................................................................165 9.4. A practical example of a meta-analysis of RCTs.................................................174 References..................................................................................................................................202 10. Meta-Analysis of Observational Studies...................................................................207 10.1. Introduction...................................................................................................................207 10.2. Practical example..........................................................................................................209 10.3. Worked examples.........................................................................................................211 References..................................................................................................................................230 11. Genetic Epidemiology.........................................................................................................231 11.1. Key concepts of genetic epidemiology.................................................................231 11.2. A practical example: the “candidate gene approach”....................................234 References..................................................................................................................................246 12. Analysis of Cost Data Using Bootstrap Technique..............................................249 12.1. Introduction...................................................................................................................249 12.2. Basic principles of the bootstrap method..........................................................250 12.3. Bootstrap standard normal confidence interval.............................................251 12.4. Percentile method confidence interval...............................................................251 12.5. Bias corrected and accelerated (BCa) confidence interval.........................252 12.6. Application to example...............................................................................................252 References..................................................................................................................................259 13. Sensitivity, Specificity, and ROC Curves....................................................................261 13.1. Study introduction.......................................................................................................261 13.2. Sensitivity, specificity, and predictive value......................................................262 13.3. Basic principles of ROC curves................................................................................264 13.4. Use of ROC analysis for comparison.....................................................................273 References..................................................................................................................................277 14. Measures of Central Tendency and Dispersion....................................................279 14.1. Introduction...................................................................................................................279 14.2. Measures of central tendency..................................................................................279 14.3. Measures of dispersion..............................................................................................282 14.4. Practical exercise .........................................................................................................286 References..................................................................................................................................288 15. Sample Size Calculations...................................................................................................289 15.1. What is a sample size and why do we need a sample?.................................289 15.2. Steps of a sample size calculation..........................................................................290 References..................................................................................................................................302 16. Representation of Data......................................................................................................303 16.1. Introduction...................................................................................................................303 16.2. Representation of qualitative variables..............................................................304 16.3. Representation of quantitative variables...........................................................314 References..................................................................................................................................324 17. Running Multiple Regression With Quantitative and Qualitative Variables With R.....325 17.1. Introduction...................................................................................................................325 17.2. The regression model with quantitative and qualitative variables.........326 17.3. Practical example: multiple regression with 2 qualitative variables.....331 References..................................................................................................................................347 18. Methods for Assessing Normality of Quantitative Variables........................349 18.1. Introduction...................................................................................................................349 18.2. Definition of normality...............................................................................................349 18.3. Parametric and nonparametric statistics...........................................................351 18.4. How to verify normality of data.............................................................................351 18.5. Practical examples........................................................................................................353 References..................................................................................................................................359 19. Quality of Life Evaluation.................................................................................................361 19.1. Quality of life in the general population.............................................................361 19.2. Quality of life in the clinical setting.......................................................................372 References..................................................................................................................................380 Appendix. Algorithm to create the SF-36 scales.........................................................382 20. Disability Adjusted Life Years (DALY) Summary Measure of Population Health....389 20.1. Introduction...................................................................................................................389 20.2. Disability adjusted life year (DALY): the concept and its uses..................390 20.3. Method for DALY estimation used in the serbian burden of disease study.............................................................................................................................................390 20.4. Practical example: calculation of DALY for colorectal cancer, Serbia, 2000..............................................................................................................................................395 Acknowledgments..................................................................................................................397 References..................................................................................................................................398
