Measurement in clinical trials: A neglected issue for statisticians?

Biostatisticians have frequently uncritically accepted the measurements provided by their medical colleagues engaged in clinical research. Such measures often involve considerable loss of information. Particularly, unfortunate is the widespread use of the so-called 'responder analysis', which may involve not only a loss of information through dichotomization, but also extravagant and unjustified causal inference regarding individual treatment effects at the patient level, and, increasingly, the use of the so-called number needed to treat scale of measurement. Other problems involve inefficient use of baseline measurements, the use of covariates measured after the start of treatment, the interpretation of titrations and composite response measures. Many of these bad practices are becoming enshrined in the regulatory guidance to the pharmaceutical industry. We consider the losses involved in inappropriate measures and suggest that statisticians should pay more attention to this aspect of their work.

[1]  Carl-Fredrik Burman,et al.  On Sequential Treatment Allocations in Clinical Trials , 1996 .

[2]  Stephen Senn,et al.  Author’s Reply to Walter and Guyatt , 2003 .

[3]  P. Ind,et al.  Dose equivalence and bronchoprotective effects of salmeterol and salbutamol in asthma. , 1997, Thorax.

[4]  K. Kuramoto Double‐Blind Studies of Calcium Antagonists in the Treatment of Hypertension in Japan , 1989, Journal of cardiovascular pharmacology.

[5]  Borje Darpo,et al.  ICH E14: A New Regulatory Guidance on the Clinical Evaluation of QT/QTc Internal Prolongation and Proarrhythmic Potential for Non-antiarrhythmic Drugs , 2005 .

[6]  A. Atkinson,et al.  Optimum biased-coin designs for sequential treatment allocation with covariate information. , 1999, Statistics in medicine.

[7]  T. Arnett,et al.  Differences in proximal femur bone density over two centuries , 1993, The Lancet.

[8]  Douglas G Altman,et al.  Dichotomizing continuous predictors in multiple regression: a bad idea , 2006, Statistics in medicine.

[9]  S. Julious,et al.  The ABC of pharmaceutical trial design: some basic principles , 2002 .

[10]  J. Whitehead Sample size calculations for ordered categorical data. , 1993, Statistics in medicine.

[11]  David R. Cox,et al.  Quality‐Of‐Life Assessment: Can We Keep it Simple? , 1992 .

[12]  Frank E. Harrell,et al.  Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2001 .

[13]  Sj Senn,et al.  Odds ratios revisited , 1998 .

[14]  G. Bray,et al.  Effects on blood pressure of reduced dietary sodium and the Dietary Approaches to Stop Hypertension (DASH) diet , 2001 .

[15]  L. Smeeth,et al.  Numbers needed to treat derived from meta-analyses—sometimes informative, usually misleading , 1999, BMJ.

[16]  S. Julious,et al.  WHY ARE PHARMACOKINETIC DATA SUMMARIZED BY ARITHMETIC MEANS? , 2000, Journal of biopharmaceutical statistics.

[17]  Nan M. Laird,et al.  Further Comparative Analyses of Pretest-Posttest Research Designs , 1983 .

[18]  R. Kay Some Fundamental Statistical Concepts in Clinical Trials and their Application in Herpes Zoster , 1995 .

[19]  D L Sackett,et al.  An assessment of clinically useful measures of the consequences of treatment. , 1988, The New England journal of medicine.

[20]  R. Kronmal Spurious Correlation and the Fallacy of the Ratio Standard Revisited , 1993 .

[21]  S. Senn Individual Therapy: New Dawn or False Dawn? , 2001 .

[22]  S. Julious Sample sizes for clinical trials with Normal data , 2004, Statistics in medicine.

[23]  S. Senn Applying results of randomised trials to patients , 1998, BMJ.

[24]  R. Shah CPMP note for guidance: clinical trials on the medicinal products in the treatment of cardiac failure. , 1996, Methods and findings in experimental and clinical pharmacology.

[25]  R. Stephens,et al.  Sample sizes for randomized trials measuring quality of life in cancer patients , 1997, Quality of Life Research.

[26]  D. DeMets,et al.  Effect of carvedilol on survival in severe chronic heart failure. , 2001, The New England journal of medicine.

[27]  Deborah Ashby,et al.  Harmonizing multiple choice question marks with essay marks , 1986, Medical education.

[28]  Andrew P. Grieve,et al.  The number needed to treat: a useful clinical measure or a case of the Emperor's new clothes? , 2003 .

[29]  Hiroshi Nishiyama,et al.  Points to consider on switching between superiority and non-inferiority. , 2006, British journal of clinical pharmacology.

[30]  S. Senn,et al.  Repeated measures in clinical trials: analysis using mean summary statistics and its implications for design. , 1994, Statistics in medicine.

[31]  P. Royston,et al.  Regression using fractional polynomials of continuous covariates: parsimonious parametric modelling. , 1994 .

[32]  G. Bray,et al.  Effects on blood pressure of reduced dietary sodium and the Dietary Approaches to Stop Hypertension (DASH) diet. DASH-Sodium Collaborative Research Group. , 2001, The New England journal of medicine.

[33]  G Molenberghs,et al.  Estimating the causal effect of compliance on binary outcome in randomized controlled trials. , 1998, Statistics in medicine.

[34]  S. Julious Inference and estimation in a changepoint regression problem , 2001 .

[35]  F. Harrell,et al.  Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors , 2005 .

[36]  Eric R. Ziegel,et al.  Statistical Issues in Drug Development , 1997 .

[37]  H. Bazett,et al.  AN ANALYSIS OF THE TIME‐RELATIONS OF ELECTROCARDIOGRAMS. , 1997 .

[38]  D G Altman,et al.  Estimating sample sizes for binary, ordered categorical, and continuous outcomes in two group comparisons , 1995, BMJ.

[39]  John A. Lewis In defence of the dichotomy , 2004 .

[40]  T. Friede,et al.  Power and sample size determination when assessing the clinical relevance of trial results by ‘responder analyses’ , 2004, Statistics in medicine.

[41]  G. Guyatt,et al.  Interpreting treatment effects in randomised trials , 1998, BMJ.

[42]  S. Julious Issues with number needed to treat , 2005, Statistics in medicine.

[43]  Marek Malik,et al.  The Imprecision in Heart Rate Correction May Lead to Artificial Observations of Drug Induced QT Interval Changes , 2002, Pacing and clinical electrophysiology : PACE.

[44]  J. Mato,et al.  CPMP note for guidance: clinical investigation of anti-anginal drugs in stable angina pectoris. , 1996 .

[45]  Lise,et al.  Comparison of upper gastrointestinal toxicity of rofecoxib and naproxen in patients with rheumatoid arthritis. VIGOR Study Group. , 2000, The New England journal of medicine.

[46]  D. Handt,et al.  Statistics and the Theory of Measurement , 2010 .

[47]  D. Sackett,et al.  The number needed to treat: a clinically useful measure of treatment effect , 1995, BMJ.

[48]  Hiroshi Nishiyama,et al.  Introduction of "Points to Consider on Switching between Superiority and Non-inferiority" and "Guideline on the Choice of the Non-inferiority Margin" , 2006 .

[49]  S. Senn,et al.  The use of baselines in clinical trials of bronchodilators. , 1989, Statistics in medicine.

[50]  D G Altman,et al.  Modeling the effects of continuous risk factors. , 2000, Journal of clinical epidemiology.

[51]  J. de Haes,et al.  Measuring psychological and physical distress in cancer patients: structure and application of the Rotterdam Symptom Checklist. , 1990, British Journal of Cancer.

[52]  Les M Irwig,et al.  An evidence based approach to individualising treatment , 1995, BMJ.

[53]  Barry Kurt Moser,et al.  Odds ratios for a continuous outcome variable without dichotomizing , 2004, Statistics in medicine.

[54]  P. McCullagh Regression Models for Ordinal Data , 1980 .

[55]  L. S. Fridericia Die Systolendauer im Elektrokardiogramm bei normalen Menschen und bei Herzkranken , 2009 .

[56]  J D Habbema,et al.  The marriage of clinical trials and clinical decision science. , 1990, Statistics in medicine.

[57]  E. Steyerberg,et al.  [Regression modeling strategies]. , 2011, Revista espanola de cardiologia.

[58]  S. Senn Statistical Issues in Short-Term Trials in Asthma , 1993 .

[59]  M. Campbell,et al.  Sample sizes for studies using the short form 36 (SF-36) , 1995, Journal of epidemiology and community health.

[60]  S. Senn Individual response to treatment: is it a valid assumption? , 2004, BMJ : British Medical Journal.

[61]  W. G. Cochran,et al.  Some Classification Problems with Multivariate Qualitative Data , 1961 .

[62]  R. Snaith,et al.  The hospital anxiety and depression scale. , 2013, Acta psychiatrica Scandinavica.

[63]  Michael G. Kenward,et al.  A Method for Comparing Profiles of Repeated Measurements , 1987 .

[64]  J. Hutton,et al.  Number needed to treat: properties and problems , 2000 .

[65]  W. Sauerbrei,et al.  Dangers of using "optimal" cutpoints in the evaluation of prognostic factors. , 1994, Journal of the National Cancer Institute.

[66]  COMMITTEE FOR PROPRIETARY MEDICINAL PRODUCTS ( CPMP ) NOTE FOR GUIDANCE ON CLINICAL INVESTIGATION OF DRUGS USED IN WEIGHT CONTROL , 1997 .

[67]  M. Hills,et al.  The two-period cross-over clinical trial. , 1979, British journal of clinical pharmacology.

[68]  H. Dargie,et al.  Effect of carvedilol on outcome after myocardial infarction in patients with left-ventricular dysfunction: the CAPRICORN randomised trial , 2001, The Lancet.