Clinical Writing for Interventional Cardiologists

1. Clinical Writing for Interventional Cardiologists

2. What you will learn • Introduction • General principles for clinical writing • Specific techniques • Practical session: critical review of a published article • Writing the Title and the Abstract • Bibliographic search and writing the Introduction • Principles of statistics and writing the Methods • Practical session: writing the Abstract • Writing the Results • Writing the Discussion • Writing Tables and preparing Figures • Principles of peer-review • Principles of grant writing/regulatory submission • Clinical writing at a glance • Conclusions and take home messages

3. Materials and methods How was the problem studied? The answer is in the Methods

4. Materials and methods The Methods section is often the less read section, but it is the most important because allow us to understand how the study was conducted, thus giving us an idea of the value of its results

5. Expanded IMRAD algorithm IntroductionBackground Limitations of current evidence Study hypothesis MethodsDesign Patients Procedures Follow-up End-points Additional analyses Statistical analysis Results Baseline and procedural data Early outcomes Mid-to-long term outcomes Additional analyses DiscussionSummary of study findings Current research context Implications of the present study Avenues for further research Limitations of the present study Conclusions

6. Materials and methods • Describe with full details what was done to answer the research question • In the beginning include a clear statement of study design: • “The study was a double-blind, randomized, parallel design … designed to compare the efficacy and safety of …” • Include also a sentence about IRB approval, informed consent, or compliance with animal welfare regulations: • “The protocol was approved by the institutional review board, and all patients gave informed consent …”

7. Materials and methods RRISC JACC 2006

8. Materials and methods • State the protocol/procedures. Repeat the question and the aims: • “We tested the efficacy of drug XX administered orally in a dose of XX mg, given XX times daily for up to XX months.” • “There were 2 primary endpoints. The first was event-free survival at XX days, with an event defined as…” • Describe materials/methods or subjects adequately • Write in a logical order (usually chronological) • Describe analytical methods

9. Materials and methods • Use subheadings (design, patients, procedures, follow-up, endpoints….) • Do not include results in Methods • Include appropriate figures and tables if useful to graphically explain concepts • Write in past tense • Use active voice whenever possible • Cite references for published methods • Describe new methods fully

10. Materials and methods • Briefly address questions you can anticipate from the reader, e.g. justify/clarify the design of your study: • “Intra-luminal recanalization of long coronary artery occlusions cannot be obtained in all patients. …. We thus tested the feasibility and safety of subintimal angioplasty in patients in whom standard intra-luminal approaches had failed and who were not candidate to bypass surgery because of severe comorbidities…”

11. Materials and methods If you prevent major limitations in your study, treat them in a matter-of-fact way: "This study was performed as part of a routine clinical assessment, so that no attempt was made to ensure either fasting of the patient or performance of the test at a particular time of day."

12. What you will learn • Principles of statistics and writing the Methods • study designs • intention-to-treat vs per-protocol analysis • type I and type II errors • p values and confidence intervals

13. Design subsection • State clearly the design of the study • Was it retrospective or prospective? • Was it a registry or controlled study? • Did you randomly allocated patients? • Did you follow a protocol(may add figure)? • You can also include here details of IRB approval

14. Prospective non-RCT study RESOLUTE EuroIntervention 2007

15. Prospective non-RCT study Cavallini et al. EHJ 2005

16. Retrospective non-RCT study Biondi-Zoccai et al. EHJ 2006

17. Prospective RCT study Tapas NEJM 2008

18. TAPAS 1 year Lancet 2008

19. Prospective RCT study • State clearly: • If the trial was double-blind / single-blind / open-label • If blinded, how blinding was granted • how randomization was performed ENDEAVOR II Circulation 2006

20. Prospective RCT study RRISC JACC 2006

21. Patient subsection • State clearly how you selected patients • Specific inclusion criteria? • Specific exclusion criteria? • You can include here details of written informed consent Tapas NEJM 2008

22. Patient subsection

23. Procedure subsection • State clearly how you performed the procedure • Any novel approaches or devices? • Complete with details on concomitant or post-intervention medications • If evaluating bio-markers, state clearly which ones, which essay is used and how it works • You can include here pictures detailing what you did/use

24. Procedure subsection TAPAS NEJM 2008

25. Procedure subsection Lefevre et al. CCI 2000

26. Procedure subsection Lefevre et al. CCI 2000

27. Outcome subsection • State clearly outcomes and whoadjudicated them (independent CEC?) • Define each outcome thoroughly (death, MI, RR, TVF, TVR, TLR, ST, bleedings…) • Define the timing of follow-up and specify info on follow-up means (how patients were contacted?) • Make sure you use validated or consensus definitions / classifications (if available, otherwise you are in trouble!)

28. Outcome subsection ENDEAVOR II Circulation 2006

29. Outcome subsection Spaulding et al. NEJM 2007

30. Additional analysis subsection • Focus on additional analyses that may be pertinent to the study • QCA: late loss, binary restenosis… • TIMI score, Myocardial Blush Grade • IVUS: neointimal hyperplasia volume, minimal lumen area… • CT: coronary stenosis > 50%... • MRI: myocardial infarction mass… • Echocardiography: LV ejection fraction… • Quote thoroughly for established methods • Define explicitly terms and ways to compute secondary variables

31. Additional analysis subsection TAPAS NEJM 2008

32. What you will learn • Principles of statistics and writing the Methods • study designs • intention-to-treat vs per-protocol analysis • type I and type II errors • p values and confidence intervals

33. Statistics subsection • Explain how you handled and reported categorical and continuous variables • Explain how you tested for significance at both univariate and multivariate analysis • Define tails and threshold p value • State width of confidence intervals • Provide sample size computation • Spell out which software package was used • Quote extensively and be ready to defend • yourself if you use sophisticated analytic tools

34. Types of variables Variables CATEGORY QUANTITY nominal ordinal discrete continuous Death: yes/no TLR: yes/no measuring counting ordered categories ranks BMI Blood pressure QCA data (MLD, late loss) Stent diameter Stent length TIMI flow Radial/brachial/femoral

35. Categorical variables • Categorical variables are probably the most important ones provided by a clinical study, as hard clinical end-points are always expressed so • Specifically, focus on: • Choose few statistics, and use them consistently • Provide confidence intervals (usually 95%) • May also provide number needed to treat/harm

36. Compare event rates No TVF TVF a b Driver Endeavor c d Absolute Risk = [ d / ( c + d ) ] Absolute Risk Reduction = [ d / ( c + d ) ] - [ b / ( a + b ) ] Relative Risk = [ d / ( c + d ) ] / [ a / ( a + b ) ] Relative Risk Reduction = 1 - RR Odds Ratio = (d/c)/(b/a) = ( a * d ) / ( b * c )

37. Absolute Risk (AR) 7.9% (47/592) &15.1% (89/591) Absolute Risk Reduction (ARR)7.9% (47/592) – 15.1% (89/591) = -7.2% Relative Risk (RR)7.9% (47/592) / 15.1% (89/591) = 0.52(given an equivalence value of 1) Relative Risk Reduction (RRR)1 – 0.52 = 0.48 or 48% Odds Ratio (OR) 8.6% (47/545) / 17.7% (89/502) = 0.49(given an equivalence value of 1) Odds Ratio Reduction (ORR)1 – 0.49 = 0.51 or 51% Compare event rates

38. Continuous variables • Continuous variables are important for the appraisal of baseline/procedural characteristics (eg stent length per lesion), or additional analyses (eg QCA) • Focus on these points: • Provide mean and standard deviation • Or median (interquartile range) if non-Gaussian • May check for normality assumptions

39. Mean (arithmetic) • Characteristics: • -summarises information well • -discards a lot of information(dispersion??) • Assumptions: • -data are not skewed • distorts the mean • outliers make the mean very different • -Measured on measurement scale • cannot find mean of a categorical measure • ‘average’ stent diameter may be meaningless

40. Median • What is it? • The one in the middle • Place values in order • Median is central • Definition: • Equally distant from all other values • Used for: • Ordinal data • Skewed data / outliers

41. Comparing Measures of central tendency • Mean is usually best • If it works • Useful properties (with standard deviation [SD]) • But… Driver Endeavor 17 21 19 21 Lesion length 19 21 17 21 18 6 Mean 18 18 Median 18 21

42. Comparing Measures of central tendency It also depends on the underlying distribution… Symmetric? mean = median = mode Frequency Value

43. Comparing Measures of central tendency It also depends on the underlying distribution… Asymmetric? mean ≠ median ≠ mode 30 Mode Median 25 Mean 20 Frequency 15 10 5 0 0 1 2 3 4 5 6 7 8 9 Number of Endeavor implanted per patient

44. Measures of dispersion: examples Frequency 0 0.30 0.60 0.90 1.20 1.50 Late loss Endeavor Driver

45. Measures of dispersion: examples Frequency 0 0.30 0.60 0.90 1.20 1.50 Late loss Endeavor Driver

46. Measures of dispersion: examples Frequency 0 0.30 0.60 0.90 1.20 1.50 Late loss Endeavor Driver

47. Measures of dispersion: types • Standard deviation (SD) • Used with mean • Parametric tests • Interquartile range • Used with median • 25% (1/4) to 75% (3/4) percentile • Non-parametric tests • Range • First to last value • Not commonly used

48. - 2 ( x x ) S = SD - N 1 Standard deviation • Standard deviation (SD): • approximates population σ • as N increases • Advantages: • with mean enables powerful synthesis • mean±1*SD 68% of data • mean±2*SD 95% of data (1.96) • mean±3*SD 99% of data (2.86) • Disadvantages: • is based on normal assumptions

49. Testing normality assumptions • Rules of thumb • Refer to previous data or analyses (eg landmark articles, large databases) • Inspect tables and graphs (eg outliers, histograms) • Check rough equality of mean, median, mode • Perform ad hoc statistical tests • Levene’s test for equality of means • Kolmogodorov-Smirnov tests • …

50. Inferential statistics P values tell you whether there is a DIFFERENCE and its DIRECTION Confidence intervals tell you what is the MAGNITUDE (or SIZE) of such difference