临床试验写作 Clinical Trial Writing（PPT讲稿）Sample Size Calculation and Randomization

Clinical Trial Writing Sample size calculation and Randomization lying XU (Tel: 22528716 CCTER CUHK 31Juy2002

Clinical Trial Writing II Sample Size Calculation and Randomization Liying XU (Tel: 22528716) CCTER CUHK 31st July 2002

Sample Size Planning

1 Sample Size Planning

1.1 Introduction ■ Fundamental points Clinical trials should have sufficient statistical power to detect difference between groups considered to be of clinical interest. Therefore calculation of sample size with provision for adequate levels of significance and power is a essential part of planning

1.1 Introduction ◼ Fundamental Points ◼ Clinical trials should have sufficient statistical power to detect difference between groups considered to be of clinical interest. Therefore calculation of sample size with provision for adequate levels of significance and power is a essential part of planning

Five Key Questions Regarding the sample Size a What is the main purpose of the trial? What is the principal measure of patients outcome? How will the data be analyzed to detect a treatment difference?(The test statistic: t-test X2orC工 a What type of results does one anticipate with standard treatment? h and h how small a treatment difference is it important to detect and with what degree of certainty?(8, a and B) How to deal with treatment withdraws and protocol violations. (Data set used

Five Key Questions Regarding the Sample Size ◼ What is the main purpose of the trial? ◼ What is the principal measure of patients outcome? ◼ How will the data be analyzed to detect a treatment difference? (The test statistic: t-test , X2 or CI.) ◼ What type of results does one anticipate with standard treatment? ◼ Ho and HA, How small a treatment difference is it important to detect and with what degree of certainty? ( ,  and .) ◼ How to deal with treatment withdraws and protocol violations. (Data set used.)

SSC: Only an Estimate Parameters used in calculation are estimates with uncertainty and often base on very small prior studies a Population may be different Publication bias--overly optimistic a Different inclusion and exclusion criteria a Mathematical models approximation

SSC: Only an Estimate ◼ Parameters used in calculation are estimates with uncertainty and often base on very small prior studies ◼ Population may be different ◼ Publication bias--overly optimistic ◼ Different inclusion and exclusion criteria ◼ Mathematical models approximation

What should be in the protocol? Sample size justification Methods of calculation a Quantities used in calculation: ● Variances ● mean values e response rates difference to be detected

What should be in the protocol? ◼ Sample size justification ◼ Methods of calculation ◼ Quantities used in calculation: • Variances • mean values • response rates • difference to be detected

Realistic and conservative ■ Overestimated size: ■ unfeasible a early termination ■ Underestimated size justify an increase extension in follow-up a incorrect conclusion WORSE)

Realistic and Conservative ◼ Overestimated size: ◼ unfeasible ◼ early termination ◼ Underestimated size ◼ justify an increase ◼ extension in follow-up ◼ incorrect conclusion (WORSE)

What is a(type i error? The probability of erroneously rejecting the null hypothesis a ( Put an useless medicine into the market!)

What is  (Type I error)? ◼ The probability of erroneously rejecting the null hypothesis ◼ (Put an useless medicine into the market!)

What is B(type Ii error)? a The probability of erroneously failing to reject the null hypothesis a(keep a good medicine away from patients!)

What is  (Type II error)? ◼ The probability of erroneously failing to reject the null hypothesis. ◼ (keep a good medicine away from patients!)

What is power a Power quantifies the ability of the study to find true differences of various values ofδ ■ Power=1-β= P(accept H1|H1 1s true) ----the chance of correctly identify h1 (correctly identify a better medicine

What is Power ? ◼ Power quantifies the ability of the study to find true differences of various values of . ◼ Power = 1- =P (accept H1|H1 is true) ◼ ----the chance of correctly identify H1 (correctly identify a better medicine)