Clinical Research in Surgery and Trauma

1. Clinical Research in Surgery and Trauma Mazen S. Zenati, M.D., MPH, Ph.D.

2. Clinical Research Research: is a systemic investigation, including research development, testing and evaluation, designed to develop or contribute to generalizable knowledge. Clinical Research covers all studies of diseases and trials of treatments that take place in human subjects

3. Why research? Research is essential to the successful promotion and protection of health and well-being and to modern and effective health and social care. It also contributes to the efficiency and effectiveness of the content, planning, delivery and monitoring of health and social care.

4. Why do clinical research • Create new medical information • Investigators • Advancement in the field • Recognition and publications • Promotion • Drug companies (sponsors) • Data needed for new drug application (NDA) • New indications for marketed drugs (sNDA) • Dissemination of knowledge • Safety and efficacy in diverse populations

5. How the public perceive the value of clinical research?

6. Would the public like to participate in clinical research?

7. Would the public like to provide more support and money?

8. The Study Process

9. Discovery processes • Coming up with an idea. • What factors are important to success? • Testing that idea. • Major Issues / Questions: • Safety. • Efficacy. • Feasibility. • Can (will) it be done? • Cost ($ and labor). • Processes: • Clinical Research • Basic Research • Bench Bedside. • Bedside Bench Bedside.

10. Observe problem Make educated guess Review available information Test hypothesis Make conclusions from results Research process (Significance) (Background) (Aims) (Design & methods) (data analysis and interpretation)

11. Study phases Phase II (n=100–300) 2–80 Sites PreclinicalTesting Approval Phase III (n=1,000–5,000) 10–100 or More Sites Phase IV Outcomes Research (n=variable) Variable # of Sites Phase I (n=50–100) Usually Single Site Discovery 2–10 4 1 2 3 1.5 Varies First in Human Time (Years) Source: PhRMA. Tufts Center for the Study of Drug Development

12. Clinical research as an activity • Fundamental to translation of basic research to medically useful interventions • Big business: est. $95 B spent annually in U.S. in biomedical research/drug and device testing • Academic centers lag behind commercial clinical trials organizations in skills related to efficient and high quality clinical research. • Academic centers market share of clinical trials now est. at 20%, was 80+% in 1990 • Generally inferior performance with respect to error rates, missing data, timeliness of submission

13. Independent medical study vs. company-sponsored clinical trial

14. The Study Design

15. First step in designing a study • Stating the objective • Framing research question • Formulating a hypothesis • Null Hypothesis • Alternative hypothesis • Defining the study population • Direction of differences or effect: • Indicated One sided • Not indicated Two sided

16. Research designs • Descriptive • No hypothesis tested • Exploratory • (case reports, case series) • Analytic: designed to test hypotheses • Experimental: investigator assigns exposure. • Observational: investigator does not assign exposure.

17. Analytic designs • The design should be selected based on many factors including: • Hypothesis • Comparison • Population • Outcome related matters • Potential bias • Sample size • Budget • Other factors. The best suitable design of a study depends largely on the nature of the hypothesis being tested

18. Observational studies Can be any of the following: • Case control (start with disease look back to the risk factors) • Cross-sectional (at one point of time/prevalence) • Cohort (start with risk factors and followed overtime for disease/incidence) • Nested …. (a case control study nested in a cohort study) • Case report • Case series

19. Clinical intervention studies • Known as clinical trials “RTC” • Randomized control trial • Non-randomized comparative trial • Also can be: • Factorial • Cross-over • Withdrawal • Group allocation • Hybrid (compared to historical control)

20. Other type of designs • Repeated measures • Before and after • Experimental study .. provide the strongest empirical evidence • Review .. systematic • Historical manuscript • Meta analyses

21. Superiority Trial

22. Non-Inferiority Trial

23. Type of study variables • Variables: Characteristics of subjects to be measured during the study • Dependent variables: • Outcome, endpoint, response, effect • Dependent: variable affected by intervention • Independent variables • Treatment, classification, risk factors, causal • May be manipulated during the study • Extraneous variables • Confounding, covariates, bias the estimate of the relationship

24. Nature of variables • Continuous variables: measurable • BP, HR, age • Discrete variables: countable • Number of lesions, number of events • Continuous variables can discretized • Shock= SBP<90 mm Hg, Normal= SBP >90 mm Hg • Discrete variables can be made continuous • Log of certain scores processed in a defined equation

25. Outcome measures and end point • Should be selected very carefully • Should be limited to one with possible a secondary outcome • Impacts the sample size • Determine the strategy for the statistical analysis • Accuracy: Is the variable actually represent what is supposed to measure? .. validity vs. bias • Precision: The reliability of repeated measurement

26. Randomized clinical trials of surgery are harder than drug trials • “Rubicon Effect” (point of no return ): after surgery, you can’t go back, like stopping a drug • Operations aren’t cookie cutter identical, like manufactured pills: individual skill more important • If comparing surgical and nonsurgical treatment, blinding is impossible • Surgeon and patient reluctance to toss a coin for surgical vs. nonsurgical treatment • RCT’s comparing alternative surgical techniques is feasible, underused – eg open vs. endoscopic carpal tunnel surgery • Carefully designed observational studies can be valuable: cohort studies where there is variability in practice

27. Sample size determination, power analysis • Depends on the following factors: • The nature of the outcome variable • Significance level, differences • Desired statistical power • Type I error ą Usually 0.05 • Type II error β Usually 0.1- 0.2 • Desired or expected effect size • Based on previous data or a pilot study • Subject variability in response (SD) • Type of the statistical test for the analysis

28. Sampling and Randomization • Sampling: selection of subjects to represent the total population • Randomization: the assignment of subjects to two or more interventions by chance alone • Should be indicated how randomization is to be accomplished • Fixed Allocation: Simple, Blocked, Stratified • Adaptive: Baseline, Response • A balance between treatment groups should be checked on the analysis • Analytic plan should be in place in case of imbalance

29. Data Analysis and Results Interpretation

30. Analytic methods for discrete dichotomousoutcome variables • Dichotomous Group/Predictor Variables: • chi-square, Fisher’s exact test, McNemar’s test • Multi-categorical Group/Predictor Variables: • chi-square • Continuous Group/Predictor Variables: • chi-square on continuous variables recoded as discrete variables • survival analysis

31. The brilliant 2X2 table • Take full advantage of the many usage of 2x2 table: • Stratification, • Adjustment for • Pearson’s Chi square • Fisher’s exact • False negative • False positive • Sensitivity • Specificity • Predictive value • Likely hood ratio • Relative risk and OR • Diagnostic tests • Agreement tests • ROC curve applications • In many nonparametric tests • Dis-concordance pair in the analysis of case-control studies • Analysis of cohort studies • Analysis of factorial design • Test for trend

32. Analytic methods for continuous ordiscrete/multicategorial outcome variables • Dichotomous Group/Predictor Variables: • between groups: two-sample t test (normal) or Mann-Whitney-Wilcoxon rank sum test (non-normal) • within groups: paired t-test (normal) or Wilcoxon signed rank test (non-normal) • Multi-categorical Group/Predictor Variables: • ANOVA: analysis of variance • Continuous Group/Predictor Variables: • correlation, regression (linear, Poisson, Mixed)

33. Choosing a statistical test Increased attention to statistical aspects by journals & the medical community

34. Choosing a statistical test

35. The red flags in research design • Chance • Outcome by chance only, no association • Bias • Having prejudice or a preference to one particular point of view or a choice • Many types; almost for everything!!! • Selection: non-response, exclusion, sampling • Information: recall, reporting • Investigator bias • Confounding: • “Is an extraneous variable in a statistical or research model that affects the dependent variables in question but has either not been considered or has not been controlled for”. • Many factors: depends on the research question and study design

36. Potential confounding factors • Age • Gender • Education • Social economic status • Race/ origin • BMI • Previous illnesses and surgeries • Current comorbidity • Smoking • Alcohol consumption • Work status/employment • Disability compensation • Hired an attorney!! • Expectations (quality, treatment) • Depression scale • Baseline values of primary outcome • Institution • Surgeon

37. Study Implementation

38. Research Team • Strong Research Team: Committed to applying the principles of Good Clinical Practice (GCP) in clinical research that may have an impact on the safety and well-being of human subjects • GCP is an international and scientific quality standard for designing, conducting, recording and reporting trials that involve the participation of human subjects • Compliance with GCP provides public assurance that the rights, safety and well-being of trial subjects are protected and that the clinical trial data & reported results are accurate and credible

39. Good Clinical Practice • Based on declaration of Helsinki and Belmont report • Federal regulation of FDA and DHHS • Foundations: law, guidance, report and policies • Issues: • Forms, protocol, and qualifications • Test article, data collection, documentation, and record keeping • Informed consent, safety, quality assurance, and compliance • Is a set of widely accepted standard that address ethical and scientific aspects of all research studies that involve human subjects • Protect the right, welfare, and safety of subjects • Set scientific standard for quality and integrity of data • Outline roles and responsibilities • Set a uniform standard for the conduct of research worldwide

40. Good Clinical Practice

41. Key Players • Sponsor • Develop protocol and provide inv. article • Monitor • Orienting inv. Team, review records & liaison • Contract research organization • P.I. • Responsible for the conduct of a trial • Associate Investigators • Epidemiologist/Biostatistician • Data Manager • IRB • Review protocol, review AEs, review compliance & reduce risk • Research coordinator • Daily follow up, study initiation & start up, screening, recruitment, informed consents, closeout and audit

42. Principal Investigator • Also known as the “PI” • An individual who actually conducts the clinical trial • Is the leader of the research team at the site • Is responsible for the conduct of the study • Qualification as MD, Ph.D., Pharm D, or a nurse • Familiar with the background of the study and the requirements of the study • Has high ethical standards and professional integrity • Obtain IRB approval of the protocol and informed consent prior to initiation of study • Enroll eligible patients

43. Principal Investigator ….. Cont. • Observe, measure and document all effects of study (response, AEs, etc) • Record all data pertinent to study • Evaluate, manage (treat) all toxicities • Report toxicities as specified in protocol • Submit protocol changes or “amendments” to the IRB for approval • Notify IRB of any issues that pose a threat to the welfare of the patients on the study • Maintain study documentation and make this available for data verification • Comply with all procedures specified in protocol in accordance with GCP.

44. A sponsor and investigator matchmaking • First contact .. Screening • Experience, CV • Interest – share basic protocol description • Access to sufficient number of eligible patients • Paper screening check list • Have a potential “match” • Submitted to HQ for further action • Confidentiality agreement signed and study synopsis given • Protocol sent to potential investigator • Still interested? • Institutional IRB approval • Agreement on legal issues and budget • Sign the contract • Start-up

45. What criteria used in selecting a clinical trial site? • Track records and good management of the team • Academic and scientific reputation of principal investigator: qualifications by training and experience • Understanding of regulatory requirements, OSPs, GCP, • Enrollment experience • Size of the institution and nature of practice • Research infrastructure. • Patients’ population • Enough research staff with appropriate training; capable and accomplished coordinators • Agreement on legal and financial issues • IRB turn around time

46. IRB • Exempt • Data in existence • No identifiable information • No consent • HIPPA can be waived • Expedited • Minimal risk • Data through intervention or interaction with individual, or identifiable info. • HIPPA regulation apply • Full board submission • Intervention • Research protocol • Full informed consent • HIPPA authorization

47. Scientific Hypotheses Specific Data Elements Required to Test Hypotheses Data Acquisition Instruments (forms) Computer Data Model and Tool Selection to Support Model and output to Analytical Software People and Process Development (Who does What, When and Where) Documentation: Standard Operating Policies & Procedures “Classical” data management flow for clinical research

48. Study documentation • Case history reports • Source document • Case report forms • Informed consent document • Regulatory documents • Regulatory files binder: protocol, consent .. • Record of receipt and disposition • Shipping, logs, electronic records, records retention • Other tools • Study feasibility ques., budget prep, screening ques., checklists, contacts, site visit flow chart, etc

49. Standard Operating Procedure • Define internal practice: to show how we really do research related work • Knowledge of practice and regulation • Reliable and accountable • It covers administrative work • Regulatory, staffing, training, satellites, communication and responsibilities • It covers clinical work • Protocol, consent, visit, reporting, record access, and confidentiality • It cover laboratory work • Specimen origin, logging, tracking, processing, storage, and shipment • It cover quality management

50. Quality Assurance • Planned and systematic actions that are established to ensure: • Trial is performed in compliance with Good Clinical Practice (GCP) • Data are generated, documented and reported in compliance with GCP • All members of the Research Team have QA responsibilities (Sponsor, PI, Data Managers, etc.)