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Clinical Grant Writing: Pearls and Pitfalls

Clinical Grant Writing: Pearls and Pitfalls. James D. Lewis, MD, MSCE University of Pennsylvania. Is the Clinician Researcher a Dying Breed?. Approx 25% of all grants to MD or MD/PhD. Kotchen et al. JAMA 2004;291:836-43. Human Studies Received Lower Priority Scores.

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Clinical Grant Writing: Pearls and Pitfalls

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  1. Clinical Grant Writing:Pearls and Pitfalls James D. Lewis, MD, MSCE University of Pennsylvania

  2. Is the Clinician Researcher a Dying Breed? Approx 25% of all grants to MD or MD/PhD Kotchen et al. JAMA 2004;291:836-43

  3. Human Studies Received Lower Priority Scores Percentage of Clinical and Nonclinical R01 Applications, by Priority Score Kotchen, T. A. et al. JAMA 2004;291:836-843.

  4. Review Panel Experience – Little Evidence of Bias Median Score % Grants Reviewed That Are Clinical Kotchen, T. A. et al. JAMA 2004;291:836-843.

  5. Where Do Clinical Applications Go Wrong? • Aims • Background • Preliminary studies • Methods • Limitations section

  6. Abstract & Specific Aims • Only sections that most panel members will read (if they even read these) • Sell the whole story in a few paragraphs • State your hypothesis, aims, and design

  7. Specific Aims Need To Be Specific • Identify risk factors for exacerbation of Crohn’s disease • Vague • To determine whether consumption of non-aspirin NSAIDs is associated with exacerbation of Crohn’s disease • Specific

  8. What Does This Have To Do With Grant Writing?

  9. A Hypothesis Is Essential • P01, R01, K08, K23, K01 • Hypothesis testing is essential • R03 • Hypothesis testing preferred • Also fundable • Proof of principle • Feasibility • Hypothesis generation?

  10. Aims Must Be Achievable

  11. Background Section

  12. Background Section • Tell a story - Not a review article • Refer to your prior work if appropriate • Selected references • Demonstrate your knowledge of the field • Reviewers’ articles? • Conclusion of background section – Need for your proposed study is obvious!!!

  13. Preliminary Studies • Support for your hypothesis • Present your background research that led to current hypothesis • Feasibility • Required data available • Study population available • Measurement tools accurate / responsive • You and your team’s qualifications

  14. Sell Yourself • Dr. Smith is an Assistant Professor of Medicine at XYZ University. She has a master’s degree in Clinical Epidemiology from ABC Univ. She has more than X years experience in caring for patients with IBD and conducting research in the field. Her previous research experience includes … (refs). Of particular relevance to this application, she …

  15. Methods Section Form = Function

  16. Methods Section • Details essential • Address each aim • Inclusion / Exclusion criteria • Data collection • Analyses • Potential limitations

  17. Inclusion / Exclusion Criteria • Appropriate to achieve aim • Will answer question • Obtainable • “Reagent grade patients” • Stephen Targan circa 2000 • Internal validity usually more important than generalizability

  18. Data Collection • How will every item be measured? • Primary data collection • Instruments • Assays (biochemical, endoscopy, etc) • Secondary data analysis • Limited by quality of existing data • Must justify accuracy of data

  19. Statistical Issues • Every aim needs a separate analysis plan • Define outcome and exposure variables • How will the variable be categorized? (continuous, dichotomous, quintiles, etc.) • Rationale for statistical plan • Get biostatistical help!!!!

  20. Sample Size – Don’t Make a Rookie Mistake

  21. Sample Size • Easy target for the reviewer • Always based on assumptions • Provide data or references to justify your assumptions

  22. Logistics: Who, When, & How • Sample/CRF transportation • Data entry • Monitoring • Data cleaning and analysis • Timeline

  23. Human Subjects Concerns • Is your study ethical? • Appropriate safety measures? • Women, children and minorities? • Funding R01 human subject proposals • No human subject concerns – 24.9% • Human subject concerns – 12.5% Kotchen, T. A. et al. JAMA 2004;291:836-843.

  24. No Clinical Study Is Perfect

  25. Limitations • Identify your limitations • The reviewers will see them anyway • Explain why they will not compromise your results and interpretation • Not a real problem • Your design will prevent the problem • If you don’t explain it, the reviewer won’t see why it is not a problem

  26. Example • The CDAI is an imperfect measure of disease activity, albeit with sensitivity and specificity for active CD both greater than 90%. Any misclassification resulting from use of the CDAI should be nondifferential. As such, any bias should be toward the null hypothesis. Because of the small degree of misclassification with the CDAI, the small amount of bias resulting from use of the CDAI would not be expected to obscure a clinically important affect of NSAIDs on disease activity. In addition, we have increased our sample size by 15% to account for the possibility of non-differential misclassificaiton bias resulting from use of the CDAI.

  27. Details • Every sentence counts • Defend every statement • Empiric data - best • References – good alternative • Rationale – better than nothing

  28. Non-Science Mistakes • Formatting rules • Budget rules • Time frame • Spelling and grammar mistakes • Table and figure numbers • Missing expertise - biostatistician • Letters of support

  29. Non-Science Mistakes • Run out of energy for final aim Cohort C-C RCT ITT SS

  30. Plan Ahead • 6 to 12 months to prepare a submission • Get feedback from investigators at your institution • Minimum of 2 weeks before deadline • Assume the deadline is 48 hours early • Last day for final proof reading and collating

  31. If At First You Don’t Succeed… • Find out why • Reviewers critiques are the roadmap to revising your proposal • Need to address every critique in a resubmission • Make it easy for the reviewers to see how you responded

  32. If At First You Don’t Succeed… • Try, try again • Anticipate at least one resubmission to achieve a fundable score • 1998 – 1999 Only 37% of those eligible to submit revised applications did so • While historically 30% of grants are funded in a given cycle, more than 40 to 45% of grants are ultimately funded Kotchen, T. A. et al. JAMA 2004;291:836-843.

  33. Good Grants Produce Good Science

  34. Resources on the Web • http://grants1.nih.gov/grants/new_investigators/index.htm • http://grants1.nih.gov/training/careerdevelopmentawards.htm • http://grants1.nih.gov/grants/forms.htm

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