How to Write a Manuscript and Get It Published in European Urology

1. How to Write a Manuscript and Get It Published in European Urology The Importance of Statistical Design and Analysis Richard Sylvester, ScD EORTC Headquarters Brussels, Belgium

2. Interpreting Published Results Urologists need precise information to be able to judge whether the conclusions of a publication are relevant to their practice. The confidence that a reader has in the conclusions is influenced by the way results are reported.

3. Report Results in Accordance With Published Guidelines Randomized Clinical Trials (RCTs) CONSORT is an evidence-based, minimum set of recommendations for reporting RCTs CONSORT Statement: 2010 25 item checklist focuses on reporting how the trial was designed, analyzed, and interpreted. http://www.consort-statement.org/

4. Statistical Design: item 3: trial design item 6: definition of outcomes item 7: sample size items 8 – 11: randomization and blinding CONSORTStatement

5. Statistical Analysis: item 12: statistical methods item 14: recruitment item 15: baseline data item 16: numbers analyzed item 17: outcomes and estimation item 18: ancillary analyses item 20: limitations CONSORTStatement

6. Statistical Design (1) Objectives and Hypotheses Type of study (epidemiological, clinical trial,…) Trial design Case control Non randomized phase 2 study Randomized phase 3 trial… Objectives Superiority, Non Inferiority, or…..?

7. Statistical Design (2) Outcome Measures (Endpoints) Provide a clear definition of endpoints Primary endpoint Secondary endpoint(s) How and when were they measured? Are the endpoints appropriate for the study? Short-term (surrogate) versus long-term endpoints

8. Statistical Design (3) Sample Size Based on primary endpoint Provide assumptions Event rate in the control group Size of difference to be detected Type 1 error rate (alpha) and power Interim analyses Duration of follow up Specify number of patients and events required

9. Statistical Design (4) Randomization Method used Allocation concealment (central randomization?) Blinding Possible biases related to the randomization procedure can invalidate the study results Note: a poorly designed study might not allow any conclusions to be drawn!!

10. Statistical Methods (1) Describe the statistical methodology used to estimate and compare treatment groups for the endpoints Response rate Time to event: progression, death Competing risks Describe any multivariate (adjustment) techniques that will be used

11. Statistical Methods (2) Define the primary analysis population(intent to treat: all randomized) Indicate if interim analyses early stopping rules subgroup analyses multiple comparisons were foreseen and carried out

12. Statistical Analysis (1) Provide by treatment group Number of patients randomized included in the efficacy and safety analyses: All randomized (ITT: intent to treat) All eligible (exams prior to randomization) Per protocol (may be biased!)

13. Statistical Analysis (2) Provide by treatment group Distribution of baseline patient characteristics Number and percent of patients Are there any imbalances in important prognostic factors? Note: do not compare patient characteristics using p values

14. Statistical Analysis (3) Outcomes Duration of follow up (median, maximum) Summary of results for each treatment group Number and percent of patients with the event Kaplan-Meier time to event curves Treatment comparison Estimate of size of treatment effect or difference Scale: absolute or relative difference (OR, HR)? Confidence interval for difference Two sided p values (not simply non significant (NS))

15. Statistical Analysis (4) Ancillary Analyses Adjustment for prognostic factors Pre-specified in protocol Because of imbalances in prognostic factors Subgroup analyses A priori specified in protocol Exploratory: data dredging and fishing expeditions Multiple comparisons and interim analyses Effect on error levels

16. Statistical Analysis (5) Adverse Events (by treatment group) Include all patients who started protocol treatment Toxicity grading scale used Amount of treatment received Stop treatment due to toxicity Toxic deaths Medical significance is more important than statistical significance!

17. Discussion Interpretation Evidence for hypotheses studied? Absence of evidence ≠ evidence of absence Non significant does not imply equivalent! Statistical significance does not imply medical significance! Limitations and sources of potential bias Dangers associated with Small sample sizes Multiplicity of analyses Generalizability of results

18. Summary of Statistical Issues Provide details concerning Trial design: endpoints, sample size and method of randomization Statistical analysismethods used Analysis population Report outcomes in accordance with CONSORT Check consistency of results in Abstract, Results, Discussion, Tables and Figures Are the conclusions supported by the data?

19. Take Home Message The correct statistical design and analysis of a clinical research project is a prerequisite for ensuring the statistical validity of the conclusions. A statistician should be involved in the project upfront at the design stage do the statistical analysis take part in the writing of the manuscript

20. Suggested Reading: Reporting Results European Urology: http://www.europeanurology.com/about-the-journal/for-authors International Committee of Medical Journal Editors: http://www.icmje.org/ Equator Network: http://www.equator-network.org/; http://www.equator-network.org/about-equator/equator-publications0/equator-network-publications-2010/ I. Simera, D. Moher, J. Hoey et al. A catalogue of reporting guidelines for health research. Eur J Clin Invest, 40, 35–53, 2010.

21. Suggested Reading: Reporting Results Randomized Clinical Trials: CONSORT Statement. http://www.consort-statement.org/consort-statement/ Non Randomized Studies: TREND Statement. http://www.cdc.gov/trendstatement/ Meta-analyses: PRISMA Statement. http://www.prisma-statement.org/ Diagnostic Accuracy Studies: STARD Statement. http://www.stard-statement.org/ Epidemiology Studies: STROBE Statement. http://www.strobe-statement.org/ Molecular Studies: see European Urology guidelines

22. Suggested Reading: Reporting Results Tumor Marker Prognostic Studies: REMARK: L.M. McShane, D.G. Altman, W. Sauerbrei et al. Reporting recommendations for tumor marker prognostic studies. Journal of Clinical Oncology, 23, No. 36, 9067 – 72, December 20, 2005. C.D. Scales, R.D. Norris, S.A. Keitz et al. A critical assessment of the quality of reporting of randomized, controlled trials in the urology literature. J Urol, 177, 1090 – 95, March 2007. V.M. Montori, R. Jaeschke, H.J. Schunemann et al. User’s guide to detecting misleading claims in clinical research reports. BMJ, 329, 1093 – 96, November 6, 2004.

23. Suggested Reading: Statistical Guidelines British Medical Journal: Statistical Noteshttp://www-users.york.ac.uk/~mb55/pubs/pbstnote.htm Greenhalgh T. How to read a paper: Statistics for the non-statistician. I: Different types of data need different statistical tests. BMJ, 315, 364-366,1997http://www.bmj.com/content/315/7104/364.full Greenhalgh T. How to read a paper: Statistics for the non-statistician. II: Significant relations and their pitfalls. BMJ, 315, 422-425,1997http://www.bmj.com/content/315/7105/422.full

24. Suggested Reading: Statistical Guidelines Journal of Clinical Oncology. http://jco.ascopubs.org/site/ifc/stats.xhtml Halabi S. Statistical considerations for the design and analysis of phase III clinical trials in prostate cancer. Urol Oncol: Sem and Orig Investig, 26, 300-307, 2008