Interim Analysis of Clinical Trial Liying XU CCTER, CUHK MSc Sept. 2001 CCTER CUHK

Clinical Trial Protocol Data safety and monitoring Safety Analysis Monitoring of the trial Data and Safety Monitoring Committee External Advisory Committee

Data and Safety Monitoring Committee (DSMC) independent with the investigators, participants or sponsors. Including experts: clinicians, epidemiologist, and bio-statisticians (and lay representatives). To review accumulating data related to treatment effects, adverse events and trial performance. To protect the integrity of the clinical trial from adverse impact resulting from access to trial information with pre-defined SOPs. DSMC is a separate entity from an IRB or IEC.

The Evaluation of Subcutaneous Proleukin(interleukin-2) in a Randomized International Trial (ESPRIT) Patients with HIV diseases,CD4>=300cells/mm3 Primary objective: to determine whether the addition of IL-2 to combination antiretroviral therapy improves morbidity and mortality Sample size:4000 Follow-up: 5 years 27 sites and 23 countries

Statistical considerations Time to event methods including stratified proportional hazard models, log-rank tests, and Kaplan-Meier cumulative event curves will use used to summarize the major outcomes of HIV-disease progression including death and survival. These analysis will be stratified by centre.

Data monitoring The independent DSMC will meet twice each year to review interim analyses. O’Brien-Fleming boundaries and the Lan-DeMets spending function will be used as monitoring guidelines for for the primary endpoint comparisons.

Other reason for early termination The DSMB will also consider results from other studies and recommend early termination or modification of ESPRIT only when there is clear and substantial evidence of benefit or harm.

Other reason for early termination The EC or DSMB may consider early termination of trial for reasons of poor accrual, less than anticipated CD4 cell count differences between treatment groups, or excessive loss to follow-up.

Data monitoring? Asking the same question several times, with the only difference being the amount of data available to answer it.

The Prehospital Treatment of Status Epilepticus (PHTSE) study: 1) to determine whether administration of bezodiazepines by paramedics is an effective and safe means of treating status epilepticus in the prehospital setting and whether this therapy influences longer-term patient outcome 2) to determine whether lorazepam is superior to diazepam for the treatment of status

Safety analysis Interim safety analysis are performed after the enrollment of 25, 50,100 and 150 unique subjects.

Interim analysis Detect: Done by independent person. early dramatic benefits potential harmful effects. Done by independent person. Statistic technique(s) is not the sole basis for the decision to stop or continue the trial.

Rational for interim analysis Ethical Scientific Economic

Decision making process Statistical results of interim analysis. The merits of the treatment. The availability and usefulness of alternative treatments. The seriousness of the conditions being treated. The acceptability of the treatment to patients, Other findings

Decision to extend a trial To maintain the power To increase the sample size. To extend the length of follow-up.

Frequency of interim analysis Long term clinical trials, 4 to 6 month intervals. The time lag between entry and response evaluation. Special meeting for unexpected toxicity of one intervention. Rate of patients accrual. 10%, 25% 75% and 100% of the primary outcomes have been observed.

Examples One full interim analysis will be undertaken when half the participants have followed for 3 years Three planned analysis when the subjects are 18 months, 3 years and 5 years of age

Statistical stopping rules A simple rule to ensure that the overall probability of type I error is controlled. In one anticipates no more than 10 interim analyses and there is one main response variable, one can adopt P<0.01 as the criterion for stopping the trial, since the overall type I error will not exceed 0.05.

Group sequential methods (Pocock 1977) What is the maximum number of interim analyses (or groups)? How many patients should be evaluated between successive analysis, i.e. what should be the size of each group?

Risk of false positive If one carries out 10 interim analyses the chance of at least one analysis showing a treatment difference significant at the 5% level increases to 0.19 even if the treatments are truly equally effective.

Repeated significance tests on accumulating data No. of repeated tests at the 5% level Overall significant level 1 2 3 4 5 10 20 50 100 1000 0.05 0.08 0.11 0.13 0.14 0.19 0.25 0.32 0.37 0.53 1.0 For two treatments, a normal response with known variance and equally spaced analyses Though broadly similar results for other type of data

Nominal significance levels A more stringent nominal significant level for each repeated test, to keep overall significant level at some reasonable value, 0.05 or 0.01.

Nominal significance level required for repeated two-sided significance testing with overall significance level (0.01 or 0.05) and various N N (Max. tests)  = 0.05  = 0.01 2 3 4 5 10 15 20 0.029 0.022 0.028 0.016 0.0106 0.0086 0.0075 0.0056 0.0041 0.0033 0.0028 0.0018 0.0015 0.0013

Fig. 1 Three group sequential stopping boundaries for the standard normal statistic (Zi) for up to five sequential groups with two sided significance level of 0.05

Table 1. Nominal P values for overall type I error of (=0.05) k Pocock O’Brien—Fleming 1 2 3 4 5 0.0294 0.0221 0.0182 0.0158 0.0051 0.0415 0.001 0.0151 0.0471 0.0039 0.0184 0.0412 0.0013 0.0085 0.0228 0.0417

Group sequential tests boundaries (see Fig.1) Pocock (1977) Divides equally the overall significance levels Peto (1976) Interim tests are run with a very low level of significance (0.001), which has little impact on the level of significance of the final test. O’Brien and Fleming (1979) It is a intermediate between the previous two methods, have slightly increase in the significance level on each following test.

Pocock’s method A trial in non-Hodgkins lymphoma compared two drug combinations CP (cytoxan-prednisone) and CVP (cytoxan-vincristine-prednisone) Outcome measure: tumor shrinkage. Patient accrual lasted over two years 120-130 patients were entered. Five interim analysis were planned: one after about every 25 patients were entered.

Interim analyses for a trial in non-Hodgkins lymphoma Response Rate CP CVP X2 (without continuity correction ) Analysis 1 Analysis 2 Analysis 3 Analysis 4 Analysis 5 3/14 11/27 18/40 18/54 23/67 5/11 13/24 17/36 24/48 31/59 1.63 0.92 0.04 3.25 4.15 0.05<P<0.1 0.016<P<0.05

Conclusion The superiority of CVP is interesting but inconclusive. However, further data on response duration and survival eventually clarified that CVP did appear to be a better therapy.

How many interim analysis The theoretical results indicate that there is little statistical advantage in having a large number of repeated significant tests. As a general rule, it would seem sensible to plan on a maximum of five interim analysis.

How many interim analysis It is sensible to consider just two analyses for the trial currently undertaken without interim analysis. One half way through and the other at the end. There can still be a major reduction in the number of patients exposed to an inferior treatment since for such a trial with sufficient overall power there is a reasonable chance of being able to stop halfway though.

Alpha-spending functions (Lan and DeMets) Flexible group sequential procedures (1983) The limitation of group sequential methods. To specified the number K of planned interim analyses in advance. The requirement for equal numbers of either participants or events between each analysis. The exact time of the interim analysis is specified.

Alpha-spending function To allow investigators to determine how they want to “spend” the type-I error or alpha during the course of the trial. The alpha spending function guarantees that at the end of the trial, the overall type I error will be the pre-specified value of . This approach is a generalization of the previous group sequential methods so that Pocock and O’brien Fleming monitoring procedures become special cases.

Calendar time and information fraction At any particular calendar time t in the study, a certain fraction t* of the total information is observed such as:

Calendar time and information fraction For regression slops: the information fraction is more generally defined in terms of the ratio of the inverse of the variance of the test statistic at the particular interim analysis and the final analysis. The alpha spending function (t*), determines how the pre-specified  is allocated at each interim analysis as a function of the information fraction.

Advantages Neither the number nor the time of the interim analyses need to be specified in advance. Once the spending function is selected, the information fractions t*1, t*2…. Determine the critical or boundary values exactly. The frequency of the interim analyses can be changed during the trial and still preserve the pre-specified  level.

A Example of group sequential methods in the Beta-Blocker Heart Attack Trial Specifications of the group sequential boundary: The O’ Brien-Fleming group sequential procedure. Seven meetings scheduled to review interim data. The trial was designed for a two-sided 5% significant level.

Fig.1 Six interim log rank statistics plotted for the time of data monitoring committee meeting with a two –sided O’Brien-Fleming significance level boundary in the Beta-Blocker Heart Attack Trial. Dashed line represents Z=1.96.

Interim log rank tests in the Beta-Blocker Heart Attack Trial From the second analysis on, the conventional significant value of 1.96 was exceeded.  the trial was continued. at the six meeting, the O’Brien-Fleming boundary was crossed a decision was made to terminate the trial Crossing the O’Brien-Fleming boundary was only one of the factors in this decision!

Figure 2 Cumulative mortality curves comparing propranolol and placebo in the Beta-Blocker Heart Attack Trial.

What should be in a interim report Patients recruitment progress Data quality Baseline characteristics Patients compliance Primary and secondary outcomes Adverse events Other safety measures

Who should have access to the report? DSMB members only Confidential!!

Practical Issues of Interim Results Consequences Continuation Termination Modification Unblinding of the code (unmasking) Modification of Patient Information Sheet Notification of ethics committees (and /or FDA, Human Rights Committee) Re-estimating sample size Timing and extent of unblinding of interim results

A software: EaSt 2000 Interactive Software and Consulting Services for the Design and Interim Monitoring of Group-Sequential Clinical Trials CYTEL Software Corporation E-mail:sales@cytel.com

A book Group Sequential Methods with Applications to Clinical Trials By Christopher Jennison and Bruce W. Turnbull. 2000 CHAPMAN & HALL/CRC