Advanced Issues in CR

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Advanced Issues in Clinical Research

How many patients?

Jones SR, Carley S and Harrison M (2003) An introduction to power and sample size estimation. Emergency medicine journal: EMJ 20(5): 453–458.

Cook JA, Julious SA, Sones W, et al. (2018) DELTA2 guidance on choosing the target difference and undertaking and reporting the sample size calculation for a randomised controlled trial. BMJ 363: k3750.

Cook JA, Julious SA, Sones W, et al. (2017) Choosing the target difference (’effect size') for a randomised controlled trial - DELTA2 guidance protocol. Trials 18(1): 271.

Small trials: Althouse AD, Yabes JG and Abebe KZ (2021) Issues in designing and interpreting small clinical trials. The Canadian journal of cardiology. Elsevier BV. DOI: 10.1016/j.cjca.2021.03.013.


Flanagin A, Frey T, Christiansen SL, et al. (2021) The Reporting of Race and Ethnicity in Medical and Science Journals: Comments Invited. JAMA: the journal of the American Medical Association 325(11): 1049–1052.

The analysis of the data from clinical trials

  • The essential: Exploratory Data analysis. Check for the "Mastering your data" course from the Doctoral School RSU and r4ds

  • Bayesian analysis of clinical trials

  • Frequentist analysis of clinical trials

  • R package for the statistical report of clinical trials: hreport, gtsummary

Repeated measures

Guo Y, Logan HL, Glueck DH, et al. (2013) Selecting a sample size for studies with repeated measures. BMC medical research methodology 13(1): 100.

Dealing with missing data

Donders ART, van der Heijden GJMG, Stijnen T, et al. (2006) Review: a gentle introduction to imputation of missing values. Journal of clinical epidemiology 59(10): 1087–1091.

Little RJ, D’Agostino R, Cohen ML, et al. (2012) The Prevention and Treatment of Missing Data in Clinical Trials. The New England journal of medicine 367(14): 1355–1360.

Groenwold RHH, Donders ART, Roes KCB, et al. (2012) Dealing with missing outcome data in randomized trials and observational studies. American journal of epidemiology 175(3): 210–217.

Survival analysis

Bewick V, Cheek L and Ball J (2004) Statistics review 12: survival analysis. Critical care / the Society of Critical Care Medicine 8(5): 389–394.

Personalized Medicine and Adaptative Clinical trials

Pallmann P, Bedding AW, Choodari-Oskooei B, et al. (2018) Adaptive designs in clinical trials: why use them, and how to run and report them. BMC medicine 16(1): 29.

Garralda E, Dienstmann R, Piris-Giménez A, et al. (2019) New clinical trial designs in the era of precision medicine. Molecular oncology 13(3): 549–557.

Razzouk S and Termechi O (2013) Host genome, epigenome, and oral microbiome interactions: toward personalized periodontal therapy. Journal of periodontology 84(9): 1266–1271.

Kent DM, Steyerberg E and van Klaveren D (2018) Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects. BMJ 363: k4245.

Predictive and Prognostic modelling

Prediction Research Janssens

Hemingway H, Croft P, Perel P, et al. (2013) Prognosis research strategy (PROGRESS) 1: a framework for researching clinical outcomes. BMJ 346: e5595.

Riley RD, Hayden JA, Steyerberg EW, et al. (2013) Prognosis Research Strategy (PROGRESS) 2: prognostic factor research. PLoS medicine 10(2): e1001380.

Steyerberg EW, Moons KGM, van der Windt DA, et al. (2013) Prognosis Research Strategy (PROGRESS) 3: prognostic model research. PLoS medicine 10(2): e1001381.

Hingorani AD, Windt DA van der, Riley RD, et al. (2013) Prognosis research strategy (PROGRESS) 4: stratified medicine research. BMJ 346: e5793.

Rules for interim analysis

Schulz KF and Grimes DA (2005) 20 Multiplicity in randomised trials II: subgroup and interim analyses. The Lancet 365(9471): 1657–1661.

Pilot and feasibility trials

Lancaster GA and Thabane L (2019) Guidelines for reporting non-randomised pilot and feasibility studies. Pilot and feasibility studies 5: 114.

Lancaster GA, Dodd S and Williamson PR (2004) Design and analysis of pilot studies: recommendations for good practice. Journal of evaluation in clinical practice 10(2): 307–312.

Moore CG, Carter RE, Nietert PJ, et al. (2011) Recommendations for planning pilot studies in clinical and translational research. Clinical and translational science 4(5): 332–337.


Phillips R, Cro S, Wheeler G, Bond S, Morris TP, Creanor S, et al. Visualising harms in publications of randomised controlled trials: consensus and recommendations. BMJ. 2022;377:e068983.

Other issues

Institute of Medicine (US) Roundtable on Value & Science-Driven Health Care (2011) Redesigning the Clinical Effectiveness Research Paradigm: Innovation and Practice-Based Approaches: Workshop Summary (L Olsen and JM McGinniseds ). Washington (DC): National Academies Press (US).

Del Paggio JC, Berry JS, Hopman WM, et al. (2021) Evolution of the Randomized Clinical Trial in the Era of Precision Oncology. JAMA Oncology. DOI: 10.1001/jamaoncol.2021.0379.

Clinical National Trials, see

Stats & Design issues

Stats issues

Causal Directed Acyclic Graphs

Heterogeneity of Treatment Effect: Estimating How the Effects of Interventions Vary Across Individuals

Use of Confidence Intervals in Interpreting Nonstatistically Significant Results

Interim Analyses During Group Sequential Clinical Trials

Estimands, Estimators, and Estimates

Interpreting the Results of Intention-to-Treat, Per-Protocol, and As-Treated Analyses of Clinical Trials

Adjusting for Nonadherence or Stopping Treatments in Randomized Clinical Trials

Immortal Time Bias in Observational Studies

Estimating Risk Ratios and Risk Differences: Alternatives to Odds Ratios

Use of Run-in Periods in Randomized Trials

Nonparametric Statistical Analysis

Practical Guide to Assessment of Patient-Reported Outcomes

When Can Intermediate Outcomes Be Used as Surrogate Outcomes?

Using Instrumental Variables to Address Bias From Unobserved Confounders

Number Needed to Treat: Conveying the Likelihood of a Therapeutic Effect

Odds Ratios—Current Best Practice and Use

The Stepped-Wedge Clinical Trial: Evaluation by Rolling Deployment

The “Utility” in Composite Outcome Measures: Measuring What Is Important to Patients

Logistic Regression Diagnostics: Understanding How Well a Model Predicts Outcomes

Equipoise in Research: Integrating Ethics and Science in Human Research

Pragmatic Trials: Practical Answers to “Real World” Questions

Logistic Regression: Relating Patient Characteristics to Outcomes

Time-to-Event Analysis

Analyzing Repeated Measurements Using Mixed Models

The Propensity Score

Noninferiority Trials: Is a New Treatment Almost as Effective as Another?

Cluster Randomized Trials: Evaluating Treatments Applied to Groups

Minimal Clinically Important Difference: Defining What Really Matters to Patients

The Intention-to-Treat Principle: How to Assess the True Effect of Choosing a Medical Treatment