Advances in Statistical Methods for the Health Sciences

, by Auget, Jean-louis; Balakrishnan, N.; Mesbah, Mounir; Molenberghs, Geert

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ISBN: 9780817643683 | 0817643680
Cover: Hardcover
Copyright: 12/30/2006

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Statistical methods have become increasingly important and now form integral part of research in the health sciences. Many sophisticated methodologies have been developed for specific applications and problems. This self-contained volume, an outgrowth of an "International Conference on Statistical Methods in Health Sciences," covers a wide range of topics pertaining to new statistical methods and novel applications in the health sciences. The chapters, written by leading experts in their respective fields, are thematically divided into the following areas:* Prognostic studies and general epidemiology* Pharmacovigilance* Quality of life* Survival analysis* Clustering* Safety and efficacy assessment* Clinical design* Models for the environment* Genomic analysis* Animal health This comprehensive volume will be highly useful an of great interest to the health science community as well as practitioners, researchers, and graduate students in applied probability, statistics, and biostatistics.

Preface

xix

Contributors

xxi

List of Tables

xxix

List of Figures

xxxv

PART I: PROGNOSTIC STUDIES AND GENERAL EPIDEMIOLOGY

Systematic Review of Multiple Studies of Prognosis: The Feasibility of Obtaining Individual Patient Data

(16)

D. G. Altman

M. Trivella

F. Pezzella

A. L. Harris

U. Pastorino

Introduction

(2)

Systematic Review Based on Individual Patient Data

(1)

A Case Study: Microvessel Density in Non-Small Cell Lung Cancer

(6)

Identifying studies (data sets) and obtaining the data

(2)

Checking the data

(2)

MVD measurements

(1)

Meta-analysis

(1)

Discussion

(7)

Systematic review of prognostic studies using individual patient data

(1)

The need for higher-quality prognostic studies

(2)

References

(3)

On Statistical Approaches for the Multivariable Analysis of Prognostic Marker Studies

(20)

N. Hollander

W. Sauerbrei

Introduction

(1)

Examples: Two Prognostic Studies in Breast Cancer

(1)

Statistical Methods

(2)

Regression models

(1)

Classification and regression trees (CART)

(1)

Formation of risk groups

(1)

Results in the GBSG-2 Study

(7)

Regression models -- standard applications

(2)

Regression models -- the MFP-approach

(1)

Summary assessment -- implication of the modelling strategy

(3)

Application of classification and regression trees

(2)

Formation and Validation of Risk Groups

(2)

Discussion

(7)

References

(4)

Where Next for Evidence Synthesis of Prognostic Marker Studies? Improving the Quality and Reporting of Primary Studies to Facilitate Clinically Relevant Evidence-Based Results

(22)

R. D. Riley

K. R. Abrams

P. C. Lambert

A. J. Sutton

D. G. Altman

Introduction and Aims

(2)

Prognostic Markers and prognostic marker studies

(1)

The need for formal evidence syntheses of prognostic marker studies

(1)

Aims of this chapter

(1)

Difficulties of an Evidence Synthesis of Prognostic Marker Studies

(7)

Poor and heterogeneous reporting

(2)

Poor study design and problems clarifying study purpose

(1)

Little indication of how to implement markers in clinical practice

(1)

Small sample sizes

(1)

Publication bias, selective within-study reporting, and selective analyses

(2)

Lack of appreciation or validation of previous findings

(1)

What Improvements Are Needed in Primary Prognostic Marker Studies?

(2)

Evidence Synthesis Using Individual Patient Data Rather than Summary Statistics

(3)

Discussion

(7)

References

(6)

PART II: PHARMACOVIGILANCE

Sentinel Event Methods for Monitoring Unanticipated Adverse Events

(14)

P. A. Lachenbruch

J. Wittes

Introduction

(2)

Examples

(1)

Usual Approaches to Monitoring Safety

(2)

Methods for Sentinel Events

(5)

Constant follow-up time

(2)

Censoring at a fixed calendar time

(3)

Methods for Sentinel Event Rates

(1)

Bayesian Models

(1)

Summary

(2)

References

(1)

Spontaneous Reporting System Modelling for the Evaluation of Automatic Signal Generation Methods in Pharmacovigilance

(20)

E. Roux

F. Thiessard

A. Fourrier

B. Begaud

P. Tubert-Bitter

Introduction

(2)

Methods

(6)

Spontaneous reporting system modelling

(1)

Exposure to the drug (Ti)

(1)

Events' relative risk (RRij)

(1)

Reporting probability (pij)

(4)

Data generation process

(1)

Application

(2)

Values of the model parameters

(2)

Application of the empirical Bayes method

(1)

Results

(2)

Discussion

(1)

Conclusion

(6)

References

(5)

PART III: QUALITY OF LIFE

Latent Covariates in Generalized Linear Models: A Rasch Model Approach

(14)

K. B. Christensen

Introduction

(1)

Generalized Linear Mixed Models

(2)

Latent regression models

(1)

Interpretation of Parameters

(1)

Generalized Linear Models with a Latent Covariate

(3)

Model

(1)

Interpretation of parameters

(1)

Parameter estimation

100

(1)

Example

101

(3)

Latent covariate

102

(1)

Job group level effect of the latent covariate

103

(1)

Discussion

104

(5)

References

105

(4)

Sequential Analysis of Quality of Life Measurements with the Mixed Partial Credit Model

109

(18)

V. Sebille

T. Challa

M. Mesbah

Introduction

110

(1)

Methods

111

(5)

The partial credit model

111

(1)

Estimation of the parameters

112

(1)

Sequential analysis

112

(1)

The Z and V statistics

112

(1)

Traditional sequential analysis

113

(1)

Sequential analysis based on partial credit measurements

113

(2)

The sequential probability ratio test and the triangular test

115

(1)

Simulation design

115

(1)

Results

116

(5)

Discussion

121

(1)

Conclusion

122

(5)

Appendix

122

(1)

References

123

(4)

A Parametric Degradation Model Used in Reliability, Survival Analysis, and Quality of Life

127

(12)

M. Nikulin

L. Gerville-Reache

S. Orazio

Introduction

127

(2)

Degradation Process

129

(1)

Estimation Problem

130

(1)

Linear MVUE for a

131

(1)

Solution of the Optimizatio Problem

132

(1)

Estimation of σ2 and θ0

132

(7)

References

134

(5)

Agreement Between Two Ratings with Different Ordinal Scales

139

(12)

S. Natarajan

M. B. McHenry

S. Lipsitz

N. Klar

S. Lipshultz

Introduction

139

(3)

Notation and Model

142

(2)

Examples and Interpretation

144

(3)

Discussion

147

(4)

References

147

(4)

PART IV: SURVIVAL ANALYSIS

The Role of Correlated Frailty Models in Studies of Human Health, Ageing, and Longevity

151

(16)

A. Wienke

P. Lichtenstein

K. Czene

A. I. Yashin

Introduction

151

(2)

Shared Frailty Model

153

(2)

Correlated Frailty Model

155

(1)

Correlated Gamma Frailty Model

156

(7)

Swedish breast cancer twin data

157

(1)

Parametric and semiparametric models

158

(1)

Correlated gamma frailty model with covariates

159

(1)

Cure-mixture models

160

(3)

Discussion

163

(4)

References

164

(3)

Prognostic Factors and Prediction of Residual Survival for Hospitalized Elderly Patients

167

(12)

M. L. Calle

P. Roura

A. Arnau

A. Yanez

A. Leiva

Introduction

167

(1)

Cohort Description and Follow-Up

168

(3)

Multistate Survival Model

171

(5)

Predictive process

173

(3)

Discussion

176

(3)

References

177

(2)

New Models and Methods for Survival Analysis of Experimental Data

179

(16)

G. V. Semenchenko

A. I. Yashin

T. E. Johnson

J. W. Cypser

Introduction

179

(1)

Semiparametric Model of Mortality in Heterogeneous Populations Influenced by Exogenous Interventions

180

(7)

The heterogeneous mortality model

180

(1)

Changes in the baseline hazard and frailty distribution

181

(2)

Semiparametric representation of the model

183

(1)

Interpretation of parameters

184

(3)

One Example of the Model Application to the Analysis of Poststress Survival Data

187

(3)

Heat shock of different duration applied to populations of nematodes Caenorhabditis elegans

187

(1)

Technical details

188

(1)

Results of fitting the model to the data

188

(2)

Discussion

190

(5)

References

191

(4)

Uniform Consistency for Conditional Lifetime Distribution Estimators Under Random Right-Censorship

195

(16)

P. Deheuvels

G. Derzko

Introduction and Results

195

(8)

Notation and statement of the problem

195

(3)

Definition of the estimators and uniform consistency

198

(5)

Proofs

203

(8)

Construction of the estimators

203

(3)

A useful auxiliary result

206

(2)

Concluding comments

208

(1)

References

208

(3)

Sequential Estimation for the Semiparametric Additive Hazard Model

211

(14)

L. Bordes

C. Breuils

Introduction

211

(2)

Example and Numerical Study

213

(2)

Assumptions and Theoretical Results

215

(5)

Technical Tools

220

(5)

Complete convergence, Anscombe condition, and exponential inequality

220

(1)

Technical results

221

(1)

References

222

(3)

Variance Estimation of a Survival Function with Doubly Censored Failure Time Data

225

(14)

C. Zhu

J. Sun

Introduction

225

(2)

Preliminaries

227

(1)

Variance Estimation

228

(3)

Simple bootstrap method

228

(1)

Generalized Greenwood formula

229

(1)

Imputation methods I and II

230

(1)

Numerical Results

231

(2)

Concluding Remarks

233

(6)

References

234

(5)

PART V: CLUSTERING

Statistical Models and Artificial Neural Networks: Supervised Classification and Prediction Via Soft Trees

239

(24)

A. Ciampi

Y. Lechevallier

Introduction

240

(1)

The Prediction Problem: Statistical Models and ANNs

241

(7)

Generalized linear models as ANNs

243

(2)

Generalized additive models as ANNs

245

(1)

Classification and regression trees as ANNs

246

(2)

Combining Prediction Models: Hierarchy of Experts

248

(2)

The Soft Tree

250

(7)

General concepts in tree construction

251

(1)

Constructing a soft tree from data

252

(1)

An example of data analysis

253

(3)

An evaluation study

256

(1)

Extending the Soft Tree

257

(2)

Conclusions

259

(4)

References

260

(3)

Multilevel Clustering for Large Databases

263

(12)

Y. Lechevallier

A. Ciampi

Introduction

263

(2)

Data Reduction by Kohonen SOMs

265

(4)

Kohonen SOMs and PCA initialization

266

(1)

Binning of the original data matrix using a Kohonen map

266

(2)

Dissimilarity for microregimens

268

(1)

Clustering Multilevel Systems

269

(2)

A two-level statistical model

270

(1)

Estimating parameters by the EM algorithm

270

(1)

Extracting Dietary Patterns from the Nutritional Data

271

(4)

References

273

(2)

Neural Networks: An Application for Predicting Smear Negative Pulmonary Tuberculosis

275

(14)

A. M. Santos

B. B. Pereira

J. M. Seixas

F. C. Q. Mello

A. L. Kritski

Introduction

276

(1)

Materials and Methods

277

(6)

Data set

277

(1)

Neural network design

278

(1)

Data selection for network design

279

(4)

Relevance of Explanatory Variables

283

(1)

Results

283

(1)

Conclusions

284

(5)

References

285

(4)

Assessing Drug Resistance in HIV Infection Using Viral Load Using Segmented Regression

289

(16)

H. Liang

W.-Y. Tan

X. Xiong

Introduction

289

(3)

The Model

292

(5)

The likelihood function

294

(1)

The prior distribution

294

(1)

The posterior distributions

295

(2)

The Gibbs Sampling Procedure

297

(1)

Analysis of the ACTG 315 Data

298

(3)

Conclusion and Dicussion

301

(4)

References

303

(2)

Assessment of Treatment Effects on HIV Pathogenesis Under Treatment By State Space Models

305

(18)

W.-Y. Tan

P. Zhang

X. Xiong

P. Flynn

Introduction

305

(1)

A Stochastic Model for HIV Pathogenesis Under Treatment

306

(3)

Stochastic differential equations of state variables

307

(1)

The probability distribution of state variables

308

(1)

A State Space Model for HIV Pathogenesis Under Antiretroviral Drugs

309

(1)

Estimation of Unknown Parameters and State Variables

310

(1)

An Illustrative Example

311

(3)

Conclusions and Discussion

314

(9)

References

317

(6)

PART VI: SAFETY AND EFFICACY ASSESSMENT

Safety Assessment Versus Efficacy Assessment

323

(12)

M. A. Foulkes

Introduction

323

(1)

Design Issues

324

(2)

Outcomes

324

(1)

Power

325

(1)

Population

326

(1)

Comparison

326

(1)

Analytic Issues

326

(3)

Compliance

326

(1)

Missing data

327

(1)

Confounding

327

(1)

Bias

328

(1)

Misclassification

328

(1)

Multiplicity

328

(1)

Analytic Approaches

329

(1)

Inferences

330

(1)

Conclusions

330

(5)

References

332

(3)

Cancer Clinical Trials with Efficacy and Toxicity Endpoints: A Simulation Study to Compare Two Nonparametric Methods

335

(14)

A. Letierce

P. Tubert-Bitter

Introduction

336

(1)

Setting

337

(3)

Method for the Simulation Study

340

(2)

Results

342

(4)

Conclusion

346

(3)

References

347

(2)

Safety Assessment in Pilot Studies When Zero Events Are Observed

349

(12)

R. E. Carter

R. F. Woolson

Introduction

349

(1)

Clinical Setting

350

(1)

Notation

351

(1)

Binomial Setting

351

(1)

Geometric Setting

352

(2)

Bayesian Credible Interval

354

(2)

Clinical Setting: Revisited

356

(1)

Summary

357

(4)

References

357

(4)

PART VII: CLINICAL DESIGNS

An Assessment of Up-and-Down Designs and Associated Estimators in Phase I Trials

361

(26)

H. K. T. Ng

S. G. Mohanty

N. Balakrishnan

Introduction

361

(1)

Notation and Designs

362

(3)

The biased coin design (BCD)

363

(1)

The k-in-a-row rule (KROW)

364

(1)

The Narayana rule (NAR)

364

(1)

Continual reassessment method (CRM)

364

(1)

Estimation of Maximum Tolerated Dose

365

(2)

Simulation Setting

367

(1)

Comparison of Estimators

368

(1)

Comparison of Designs

369

(18)

References

385

(2)

Design of Multicentre Clinical Trials with Random Enrolment

387

(14)

V. V. Anisimov

V. V. Fedorov

Introduction

387

(2)

Recruitment Time Analysis

389

(4)

Analysis of Variance of the Estimated ECRT

393

(2)

Inflation of the Variance Due to Random Enrolment

395

(1)

Solution of the Optimization Problem

396

(2)

Conclusions

398

(3)

Appendix

398

(2)

References

400

(1)

Statistical Methods for Combining Clinical Trial Phases II and III

401

(18)

N. Stallard

S. Todd

Introduction

401

(1)

Background

402

(5)

The clinical evaluation programme for new drugs

402

(1)

Combining clinical trial phases II and III

403

(1)

Background to sequential clinical trials

404

(3)

Methods for Combining Phases II and III

407

(6)

Two-stage methods

408

(1)

A multistage group-sequential method

408

(1)

A multistage adaptive design method

409

(1)

Example---a multistage trial comparing three doses of a new drug for the treatment of Alzheimer's disease

410

(3)

Discussion and Future Directions

413

(6)

References

415

(4)

SCPRT: A Sequential Procedure That Gives Another Reason to Stop Clinical Trials Early

419

(18)

X. Xiong

M. Tan

J. Boyett

Introduction

420

(1)

The SCPRT Procedure

421

(3)

Controlling the boundary

423

(1)

Boundaries in terms of P-values

423

(1)

An Example

424

(2)

SCPRT with Unknown Variance

426

(2)

Clinical Trials with Survival Data

428

(4)

Conclusion

432

(5)

References

432

(5)

PART VIII: MODELS FOR THE ENVIRONMENT

Seasonality Assessment for Biosurveillance Systems

437

(14)

E. N. Naumova

I. B. MacNeill

Introduction

438

(2)

Conceptual framework for seasonality assessment

438

(2)

δ-Method in Application to a Seasonality Model

440

(6)

Single-variable case

440

(1)

Two-variables case

441

(1)

Application to a seasonality model

442

(1)

Potential model extension

443

(1)

Additional considerations

444

(2)

Application to Temperature and Infection Incidence Analysis

446

(3)

Conclusion

449

(2)

References

450

(1)

Comparison of Three Convolution Prior Spatial Models for Cancer Incidence

451

(16)

E.-A. Sauleau

M. Musio

A. Etienne

A. Buemi

Introduction

451

(2)

Materials and Methods

453

(3)

ICAR model

455

(1)

Distance model based on the exponential function

455

(1)

Two-dimensional P-splines model

456

(1)

Implementation of the models

456

(1)

Results

456

(3)

Discussion

459

(8)

References

463

(4)

Longitudinal Analysis of Short-Term Bronchiolitis Air Pollution Association Using Semiparametric Models

467

(24)

S. Willems

C. Segala

M. Maidenberg

M. Mesbah

Introduction

467

(2)

Data

469

(1)

Sanitary data

469

(1)

Environmental data

469

(1)

Methods

470

(5)

Generalized additive models

470

(1)

Air pollution time series studies strategy

471

(3)

Criticism about the use of standard statistical software to fit GAM to epidemiological time series data

474

(1)

Results

475

(9)

Series of number of hospital consultations: Results with S-Plus

475

(7)

Series of number of hospital consultations: Results with R

482

(1)

SAS results

483

(1)

Discussion

484

(7)

References

486

(5)

PART IX: GENOMIC ANALYSIS

Are There Correlated Genomic Substitutions?

491

(28)

M. Karnoub

P. K. Sen

F. Seillier-Moiseiwitsch

Introduction

491

(1)

The Probabilistic Model

492

(4)

Parameter Estimation

496

(1)

New Test Statistic

497

(3)

Power Studies

500

(1)

Numerical Studies

501

(3)

Data Analysis

504

(3)

Discussion

507

(12)

Appendix 31.1

509

(1)

Appendix 31.2

510

(3)

References

513

(6)

PART X: ANIMAL HEALTH

Swiss Federal Veterinary Office Risk Assessments: Advantages and Limitations of the Qualitative Method

519

(8)

R. Hauser

E. Breidenbach

K. D. C. Stark

Introduction

520

(1)

Health Risks from Consumption of Milk and Dairy Products: An Example of a Qualitative Risk Assessment

521

(4)

Risk profile

521

(1)

Hazard identification

521

(1)

Risk network

522

(1)

Risk estimation

523

(1)

Recommendations for random sample planning and risk managers

524

(1)

Advantages and Disadvantages of Qualitative Risk Assessment

525

(1)

Statistics' Part in Qualitative Risk Assessment

526

(1)

References

526

(1)

Qualitative Risk Analysis in Animal Health: A Methodological Example

527

(12)

B. Dufour

F. Moutou

Introduction

528

(1)

Global Presentation of the Method

528

(2)

Qualitative Appreciation of the Probability of Each Event

530

(1)

Qualitative Risk Appreciation

531

(1)

Qualitative Appreciation Examples

532

(2)

Discussion

534

(5)

References

536

(3)

Index

539

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Advances in Statistical Methods for the Health Sciences

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