297 vickers
- 1. Clinical trials, data sharing and supplemental materials Andrew J. Vickers Department of Epidemiology and Biostatistics Memorial Sloan-Kettering Cancer Center 1.30 – 2pm. SSP meeting
- 2. Should authors of clinical trials be able to be submit supplemental materials?
- 3. It should be compulsory
- 5. Read first para of NYT article
- 6. Overview of talk • Experiences trying to obtain raw data • Advantages of making raw data available • Arguments against data sharing • A code of conduct for use of raw data • A final thought: will journals step up to the plate?
- 7. Typical experiences trying to obtain data from medical trials • Needed data from the control arm of a trial to help design a study • NIH researcher, NIH funded trial • “I am not prepared to release the data at this point”
- 8. Anecdote 2 • Conducting a meta-analysis • Needed proportions from a published trial that reported means and SDs • “I would love to provide you with these data but my biostatistician won’t allow it”
- 9. Anecdote 3 • Wanted data from a large cancer trial to illustrate a novel statistical technique n n 1 ∆NB = ∑x i − pt − ∑x i , k =1 − pt ∑xk i =1 i =1 k =0 • Investigators were suspicious
- 10. I implore you, oh great king, pity me, poor, little worm that I am • We promised: – The data would only be used for a statistical methodology study – We would expressly state in the paper that no clinical conclusions should be drawn – We would slightly corrupt the data – We would send a draft to the investigators and they would have veto power
- 11. Too bad …
- 12. How I have done it …. • Show biomed paper • Link to excel file • Etc.
- 18. Notice that …. • File is not large (21 Kb) • File needs no editing
- 19. Why share data? • Analyses can be reproduced and checked by others • Acts as an additional incentive for checking that a data set is clean and accurate • May help prevent fraud and selective reporting • Allows testing of secondary hypotheses • Aids design of future trials • Simplifies data acquisition for meta-analysis • Teaching • Aids development and evaluation of novel statistical methods
- 20. Why share data? • Analyses can be reproduced and checked by others • Acts as an additional incentive for checking that a data set is clean and accurate • May help prevent fraud and selective reporting • Allows testing of secondary hypotheses • Aids design of future trials • Simplifies data acquisition for meta-analysis • Teaching • Aids development and evaluation of novel statistical methods
- 22. Reported results • Sensitivity of 100% • Specificity of 95%
- 25. Conclusions • We compared SELDI proteomic spectra … from three experiments … on … ovarian cancer. • These spectra are available on the web at http://clinicalproteomics.steem.com • The results were not reproducible across experiments.
- 27. Key point • Publication of raw data is routine for: – Protein chemistry – Genomic research – Astronomy • But not clinical trials
- 28. Why share data? • Analyses can be reproduced and checked by others • Acts as an additional incentive for checking that a data set is clean and accurate • May help prevent fraud and selective reporting • Allows testing of secondary hypotheses • Aids design of future trials • Simplifies data acquisition for meta-analysis • Teaching • Aids development and evaluation of novel statistical methods
- 29. Acts as an additional incentive for checking that a data set is clean and accurate • My house is neater when I know someone is coming to visit • Biomarker study: – Gross errors found in clinical trial data set
- 30. May help prevent fraud and selective reporting
- 31. Allows testing of secondary hypotheses • CARET study: do vitamins help prevent lung cancer? • Peter Bach at MSKCC: what is the association between amount of cigarette smoking and lung cancer? – Predictive model – Used to evaluate CT screening for lung cancer
- 32. Aids design of future trials • Numerous decisions on trial design should be based on data – How many patients do we need? – When should we measure patients? – What is the best way to measure outcome?
- 33. Simplifies data acquisition for meta-analysis • A single study rarely tells you much • Combine data from several studies to get the big picture: “meta-analysis” • Can be difficult to combine data if results are presented in different ways
- 34. Teaching • Best way to teach swimming is to put your children in the water • Best way to teach statistics is to have students analyze real data sets
- 35. Development of novel statistical methods n n 1 ∆ NB = ∑ x i − pt − ∑ x i ,k =1 − pt ∑ xk i =1 i =1 k =0
- 36. Arguments against data sharing • Cost and trouble of putting data set together • Doesn’t this have to be done anyway?
- 37. Arguments against data sharing 2 • It might violate patient privacy • Changing names to codes and dates to lengths of time is hardly rocket science
- 38. Arguments against data sharing 3 • Other researchers might conduct invalid analyses • A decision for the scientific community as a whole
- 39. Arguments against data sharing 4 • Researchers have a right to exploit data that they may have spent years collecting
- 40. A code of conduct for sharing data from clinical trials 1. Independent investigators planning to publish a new analysis should contact the trialists before undertaking any analyses 2. One or more trialists should be offered a co- authorship or opportunity to write a commentary published alongside the new analysis 3. Journals should not publish new analyses of previously published data unless a trialist is co- author or writes separate commentary 4. Published new analyses should cite the original trial
- 41. Code of conduct for trialists 1. Data set must be clean, well annotated, de-identified 2. Publish immediately data for the main analyses 3. No need to share data for planned 2ry analyses 4. All raw data made available no longer than five years after first publication of trial results 5. There is no need to update data 6. Trialists must share data if analyses are not to be published
- 42. To the Editor: “Cancer Data? Sorry, Can’t Have It” (Essay, Jan. 22): Andrew Vickers hints at a truth known to most physicians with any connection to medical research; the pursuit of academic and scientific prestige is often as important as the potential benefit to patients. There’s a simple fix. If the top dozen or so medical journals refused to consider publication of any research results without a pledge from the authors to make the raw data available for follow-up analysis, the problem would disappear. David R. Bacon, M.D.
- 43. Will journals step up to the plate? • Should the results of human experimentation become personal property of the researchers? • Publication: – Ethical approval – Disclosure of conflict of interest – Data made publicly available