Research protocol design and collecting the data

1. Research protocol design and collecting the data The Union, Paris, France MSF, Brussels, Belgium

2. BASIC STRUCTURE • Background and rationale to study • Aim and objectives (the research question) • Methods (includes ethics submission) • Budget and time lines • Justification

3. Background and Rationale • Country / context in which study is to be done • The problem and what is known about it • Are there knowledge gaps? • Will this study fill those knowledge gaps?

4. Aim and Objectives • Aim is broad • Objectives are more specific

5. Example:Management and outcomes of TB patients who fail treatment in Malawi

6. Background (1) • Every year 1% of new smear-positive PTB patients FAIL treatment (i.e., are sputum smear positive 5 months or more after starting treatment) • Patients who fail on 2RHZE/4RH have high risk of having MDR-TB • Patients who fail on 2RHZE/6HE have lower risk of having MDR-TB

7. Background (2) • Malawi’s first line TB treatment in 2000 was 2RHZE/6HE • Some concern that those who fail might have MDR-TB and therefore should not be taking the retreatment regimen in 2000 of 3SRHZE / 5R3H3Z3E3

8. Background (3) • What happens to new smear-positive PTB patients who fail treatment • We do not know as failure patients were registered under “Previously Treated Other” and their outcomes were not reported on

9. Aim of Study To document the management and outcome of TB patients who fail first line treatment in Malawi

10. Objectives To determine:- 1. The number of new smear-positive PTB patients who failed treatment 2. The management of patients who failed 3. Their treatment outcomes on Re-Rx regimen 4. The culture and drug sensitivity results of those who failed

11. METHODS • Study design • Setting – general and study site • Participants (time period) • Data variables to be collected: • exposure and outcome variables • data collection instrument • data validation • Sources of data • Analysis and statistics (sample size calculation) • Ethics approval

12. Design • This is a cross-sectional study involving a review of registers and treatment cards. But it also includes district TB officers chasing up failure patients lost to follow up

13. The setting: general and specific • Malawi and National TB Programme • NTP Guidelines about how to diagnose and treat patients with TB failure • The process by which sputum specimens are collected at peripheral sites and sent for culture and drug sensitivity testing • The hospitals which register TB patients

14. Patients– identified from registers • New smear-positive PTB patients in all 43 non-private hospitals that register TB patients in Malawi • Patients registered between 1 July 1999 and 30 June 2000 • Patients who are smear-positive at 5 months or at 8 months of treatment = Failures

15. Data variables: • Of those diagnosed as failures: TB registration number, name, age, sex, month of treatment failure, date of treatment failure • Management of those diagnosed as failures: Did they appear again in TB Register? New TB registration number; name, age, sex, classification; treatment regimen; outcomes • Linking failures and sputum for DST: Inspection of Central Laboratory Register for the patients who had failed: compare TB Registration numbers with those in CLR; date of arrival of specimens; results of culture and DST

16. Data Collection Instrument: (page 1)

17. Data Collection Instrument (page 2)

18. Data Validation • This is a register-based study and therefore not possible Although one can cross check obvious errors against clinic-based patient card

19. Sources of data • TB Registers • TB Patient Treatment Cards • CRL (Central Reference Laboratory) Register • Interviews with District TB Officers to trace missing patients

20. Analysis and Statistics • Arch back file for data collection forms • Data entry to EPI-INFO • Double entry if possible! • Analysis (present study) = descriptive and no need for comparisons

21. Sample size • Not necessary in this study (already knew or checked that numbers were small) • This study involved ALL patients with new smear-positive PTB who had been registered in ALL TB Registration centres over a one year period

22. Sample size calculation • Necessary if we wish to compare groups • No groups in this study • Use EPI-INFO or EPI-DATA to calculate for you – relates to power of the study and the significance at which one accepts a difference – usually one chooses 80% power and differences at the 5% level

23. Ethics approval • Programmatic data • In Malawi, NHSRC granted approval for such work – regarded as “audit of the programme”

24. Doing the research and collecting the data

25. The study team and the plan • Decide who is principal investigator - PI • Who will be in the study team • Decide on the time frame

26. Data collection • Who is going to collect these data? • How will they be collected (eg. proforma)? • How can the data be verified?

27. Data Collecting Tool • Ensure all relevant information is included • Avoid collecting data you will not need • Pre-test the proforma? • Make enough copies plus some extra

28. The Money (1) • Where will you get it? • You will need a budget • Don’t under-budget or over-budget

29. The Money (2) – what to ask for • Personnel time (research allowances, per diems, accommodation) • Equipment (computer, printer, materials) • Transport, fuel, car maintenance • Stationery for data collection tools • Report dissemination (room hire for meetings?, postage?) • Money for publication (open access cost)

30. The Money (3) – What not to ask for • Computer (if you already have one) • 50% of your time (if you are salaried) • A brand new office • A brand new vehicle

31. Permissions and letting everyone know • Make sure all necessary permissions are obtained (useful to have formal letter from programme director with you) • If you have an informed consent procedure, ensure this is applied • Ensure everyone involved knows about the study (those conducting it and those in facilities or communities where it is being conducted • If you forget someone, apologize!

32. Doing the study and collecting the data • Make formal introductions at each site you visit (medical officer, matron, etc) • Be honest with the data - if information is not there then say “No information” • Keep completed proforma well organised and safe

33. Data management (Module 2) • Set up an organised data file • Enter data into EpiData or Epi Info • Make back-up copies as you go along • Enter data soon after study is complete or as you go along • Ensure methods for checking data quality • Don’t analyse data until you are sure there are no data entry mistakes

34. Results of the TB Failure Study

35. Results (1): • 90 patients failed treatment – 60 at 5 months and 30 at end of treatment • 64 (71%) failure patients were re-registered and started on TB treatment • 26 (29%) were never re-registered:- • 4 refused further treatment • 8 died • 14 outcome unknown

36. Results (2): • Of those 64 patients re-registered:- • 61 (95%) registered in same hospital • 57 (89%) were given a different registration number • 43 (67%) were correctly registered as failures (the others as relapses or new patients • 39 (61%) were treated within one month of failing • 63 (98%) given a re-treatment regimen

37. Results (3) • Of 64 patients treated with re-treatment regimen (3SRHZE / 5RHZE), 48 (75%) were cured • 31 (34%) of 90 patients submitted sputum for culture and DST • Only 11 patients had M.TB cultures, of whom 8 were fully sensitive to all retreatment drugs and 3 were mono-resistant to isoniazid

38. Conclusion • Large number of programme deficiencies: • one third of patients not treated • 40% treated after one month • Most patients had no culture and DST results • However, 75% were cured and therefore Malawi’s policy of using Re-Rx regimen was appropriate and where culture and DST was done, no MDR-TB identified