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Introduction to the Statistical Analysis of the Clinical Trials

Explore the fundamentals of clinical trials, including types, phases, and design. Learn about the statistical methods crucial for interpreting trial data accurately. Discover major software solutions like SPSS and STATISTICA. Gain insights into the basics of STATISTICA and its data analysis capabilities.

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Introduction to the Statistical Analysis of the Clinical Trials

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  1. Introduction to theStatistical Analysisof the Clinical Trials

  2. Main Questions • The Clinical Trials Basics • Importance of the Statistical Methods • Major software solutions • STATISTICA Basics

  3. The Clinical Trials Basics What Are Clinical Trials? • Research studies involving people • Try to answer scientific questions and find better ways to prevent, diagnose, or treat disease

  4. Why Are Clinical Trials Important? • Clinical trials translate results of basic scientific research into better ways to prevent, diagnose, or treat disease • The more people take part, the faster we can: - Answer critical research questions - Find better treatments and ways to prevent disease

  5. What Are the Different Types of Clinical Trials? • Treatment • Prevention • Early detection/screening • Diagnostic • Quality of life/supportive care

  6. Treatment Trials • What new treatments can help people with a particular disease? • What is the most effective treatment for people with that disease?

  7. Clinical Trial Phases • Phase 1: 15-30 people • What dosage is safe? • How should treatment be given? • How does treatment affect the body? • Phase 2: Less than 100 people • Does treatment do what it is supposed to? • How does treatment affect the body?

  8. Clinical Trial Phases • Phase 3: From 100 to thousands of people • Compare new treatment with current standard • Phase 4: From hundreds to thousands of people • Usually takes place after drug is approved • Used to further evaluate long-term safety and effectiveness of new treatment

  9. Clinical Trial Design • Eligibility criteria: Can range from general (age, gender, weight) to specific (prior treatment, tumor characteristics, blood cell counts, organ function); eligibility criteria also vary with trial phase • Varies with protocol and phases • Endpoint: Measurable outcome that indicates an intervention’s effectiveness

  10. Clinical Trial Design • Randomization: A method used to prevent bias in research; a computer or a table of random numbers generates treatment assignments, and participants have an equal chance to be assigned to one of two or more groups (e.g., the control group or the investigational group)

  11. Clinical Trial Design • Stratification: Categorizing subjects into subgroups by specific characteristics • Enables researchers to look into separate subgroups to see whether differences exist

  12. Clinical Trial Protocol • A recipe or blueprint • Strict scientific guidelines: --Purpose of study --How many people will participate --Who is eligible to participate --How the study will be carried out --What information will be gathered about participants --Endpoints

  13. 2. Importance of the Statistical Methods • Appropriate statistical methods for analysing trial data are critical for the correct interpretation of the results. • Item 12 of the CONSORT (Consolidated Standards Of Reporting Trials) statement relates to the statistical methods used in the reporting of trials, together with scientific and statistical principles concerning analyses of subgroups, endpoints and appropriate statistical tests: • http://www.consort-statement.org/

  14. 2. Statistical Analysis plan Specifying how the outcome will be measured. Common measures are: • Binary - event present or not. • Count - the frequency of an event in a set time period. • Measurement on a continuous scale.. • Other measurements include ordinal scales (eg, quality-of-life ratings, 5-point trauma scales) and non-ordered scales (eg, patient preferences between oral, intravenous or combination treatment delivery).

  15. 2. Statistical Analysis plan • Any transformations on the data likely to be required before analysis. This includes possible groupings or classifications of data (eg, into good, acceptable and poor quality of life), as well as mathematical transformations (logarithms, square root, etc) needed to "normalise" the outcome variables.

  16. 2. Statistical Analysis plan • Appropriate statistical tests which will be used to analyse the data. While the underlying assumptions of common statistical tests vary, underpinning all these tests is the assumption that either the outcome or other calculated measures (such as correlation coefficients, hazard or odds ratios) will be "normally" distributed.

  17. 3. Major software solutions • Microsoft Excel / OpenOffice KSpread • SPSS • STATISTICA • Maple • MatLab and other more than 100 solutions listed there: • http://en.wikipedia.org/wiki/List_of_statistical_packages

  18. 4. STATISTICA Basics • STATISTICA is a comprehensive, integrated data analysis, graphics, database management, and custom application development system featuring a wide selection of basic and advanced analytic procedures for business, data mining, science, and engineering applications.

  19. 4. STATISTICA Basics

  20. 4. STATISTICA Basics • The Statistics menu provides access to all available analysis types within STATISTICA. • The Graphs menu provides direct access to a variety of commonly used graph types

  21. 4. STATISTICA Basics STATISTICA uses five principal document types: • Workbooks • Spreadsheets (multimedia tables) • Reports • Graphs • Macros (STATISTICA Visual Basic)

  22. 4. STATISTICA Basics • Spreadsheets are based on StatSoft's proprietary multimedia table technology and are used to manage both input data and the numeric or text output. • The basic form of the spreadsheet is a simple two-dimensional table that can handle a practically unlimited number of cases (rows) and variables (columns), and each cell can contain a virtually unlimited number of characters. • Sound, video, graphs, animations, reports with embedded objects, or any ActiveX compatible documents can also be attached.

  23. 4. STATISTICA Basics

  24. 4. STATISTICA Basics • The spreadsheet window comprises several basic components.

  25. 4. STATISTICA Basics • Workbooks are the default way of  managing output. They store each output document (e.g., a STATISTICASpreadsheet or Graph, as well as an Microsoft Word or Excel document) as a tab.

  26. Adapted from a slide presentation developed by the National Cancer Institute, for its Cancer Clinical Trials Education Series.

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