THE RAPID ENROLLMENT DESIGN FOR PHASE I CLINICIAL TRIALS

Transcription

1 THE RAPID ENROLLMENT DESIGN FOR PHASE I CLINICIAL TRIALS Anastasia Ivanova 1,2 and Yunfei Wang 1, 1 University of North Carolina Chapel Hill and 2 Lineberger Comprehensive Cancer Center (LCCC) aivanova@bios.unc.edu

2 Translation of innovative designs into Phase I trials Rogatko et al. (JCO, 2007) Looked at journal articles from 1991 to 2006 Searched TS((((phase I)OR(phase 1)OR(phase one))same(study or studies OR trial*)) AND cancer AND (patients OR subjects))) Of 1,235 articles published in 116 journals the following designs were cited 3+3 or variation 1,215 (98.4%) CRM 17 (1.4%) EWOC 3 (0.2%) 2

3 Phase I designs 3+3 Up-and-down methods including Group up-and-down designs Dose-finding design based on t-statistic (Ivanova and Kim, 2009) mtpi (Ji et al., 2010) Continual Reassessment Method (CRM) (O Quigley et al., 1990) 3

4 Dose response Probability of DLT dose/toxicity assumed to be monotonic increasing P(DLT)=0.25 MTD Dose (mg/m 2 ) 4

5 Traditional or 3+3 design If 0/3 DLTs, assign 3 new patients to the next higher dose If 1/3 DLTs, assign 3 new patients at this dose if 1/6 DLTs, assign 3 new patients to the next higher dose if 2/6 DLTs, STOP If 2/3 DLTs, STOP and assign 3 new patients to the preceding dose level unless there are already 6 patients at that level 5

6 Traditional or 3+3 design: operating characteristics The frequency of stopping escalation at a certain dose level in the 3+3 design depends on toxicity rate at that dose as well as rates at all the lower dose levels. On average, the dose chosen by the 3+3 design as the MTD has the probability of toxicity of about 0.2 or 0.25 Target toxicity rate 6

7 Motivating example Phase I trial in patients less than 60 years-old with relapsed/refractory Acute Myeloid Leukemia (AML) The goal was to identify the MTD defined as the dose with DLT rate of DLT was defined as any of the following: - grade 3 non-infection, non-hematologic toxicity lasting 14 days or longer, - any duration of grade 4 non-infection, nonhematologic toxicity, - any grade 3-4 hematologic toxicity lasting beyond day 42 in the absence of residual leukemia. 7

8 Why not the design? In trials of acute leukemia patients, it is difficult to distinguish undue hematologic drug toxicity from the bone marrow effects of the disease itself. Often this requires follow-up for toxicity from an individual cycle of therapy that lasts 4-6 weeks rather than what is typical in solid tumors (3-4 weeks). AML trials should ideally offer continuous enrollment, since the pace of these leukemias is so rapid that waiting for a new cohort to open on a Phase I trial may take so long that the patient may succumb to the disease while waiting. 8

9 Design for the Phase I AML trial Dose escalation cannot occur unless at least three patients have been fully followed for toxicity at the current dose. While patients at the highest-enrolling dose level are being followed, additional patients are allowed to be enrolled at a previous, lower dose level. 9

10 Design for the Phase I AML trial Dose level 3 Dose level 2 Dose level 1 10

11 Current dose in up-and-down methods Up-and-down methods use a notion of the current dose Group up-and-down designs Dose-finding design based on t-statistic mtpi The next assignment (increase, repeat or decrease the dose) depends on the data at the current dose only

12 Design for the Phase I AML trial Dose level 3 Dose level 2 Dose level 1 With assignments to several doses at the same time, there is no current dose 12

13 Design for the Phase I AML trial The CRM does not use the idea of the current dose, but the assignments are made to the best dose so far not to the dose with enough safety data Need a dose assignment strategy where each patient is assigned to the best dose with enough safety information The proposed design does not use the notion of the current dose 13

14 Rapid Enrollment Design (RED) Step 1. Estimate the DLT rates at all doses using isotonic regression (PAVA algorithm) monotonicity violation pooling violators Step 2. Find the two candidate doses: one right below the target DLT rate, Γ = 0.26, and one right above 0 3 = 0 Γ < =

15 Rapid Enrollment Design Step 3. Select one of the two candidate doses according to the probability that the dose is the MTD Prior for the DLT probability at dose j, q j Beta(α = 0.3, β = 0.01) Posterior distribution Beta(α + m j, β + n j - m j ), where m j is the number of DLT at dose j n j is the number of patients at dose j n j -m j is the number of patients without a DLT 15

16 density.default(x = aa1) Density Probability to be in ( , ) 0/3 Æ Pr = /4 * Æ Pr = 0.15 * Since data were pooled from two doses, we use 1.5/4 instead of 3/ Target DLT rate 16

17 Rapid Enrollment Design Step 4. Do not assign to a dose if the probability that the DLT rate at the dose is higher than Γ exceeds /4 Pr{DLT rate is higher than 0.26} =

18 Dose allocation decision based on the posterior probability at two candidate doses. Target probability is Γ = Observed data at d j Observed data at d j + 1 Decision 1/5:12, 2/9:12 1/2, 2/4, 3/6, 5/11 Lower Dose 1/5:9, 2/9:12 1/3, 2/5, 3/7, 5/12 Lower Dose 1/5:7, 2/9:12 3/8 Lower Dose 2/9:12 2/6, 2/7, 3/9, 4/11 Lower Dose 2/9:11 4/12 Lower Dose 1/5:8, 2/9:12 4/10 Lower Dose 0/1:2, 1/5:12,2/9:12 4/8 Lower Dose 1/5:10, 2/9:12 4/9 Lower Dose 0/1:3, 1/5:12, 2/9:12 5/10 Lower Dose 0/1:6, 1/5:12, 2/9:12 6/11 Lower Dose 0/1:4, 1/5:12, 2/9:12 6/12 Lower Dose 0/1:12 1/2, 2/4, 3/6, 5/11 18 Higher Dose

19 Comparison with mtpi and the t-statistic design in the case of no delay in outcome Used all 10 scenarios from Ji et al. (2010) Total sample size is 30 Patients are assigned 3 at a time There is almost no difference among the 3 designs 19

20 Comparison with mtpi and the t-statistic design in the case of no delay in outcome mtpi RED t-stat Scenario Scenario Scenario Scenario Scenario Scenario

21 Delayed outcome Often it takes a long time to observe toxicity. What to do if we need to enroll a patient while some patients are still in follow-up? Example. 1/3 = 1 out of 3 patients had a DLT Can we assign, say, 6 more patients to that dose at once or is it too risky?? 21

22 Delayed outcome Many methods have been developed for dosefinding with delayed outcome Cheung and Chappell (2000) and Ivanova et al. (2005) A patient with a partial follow-up contributes approximately as a fraction of a patient WITHOUT a DLT Bekele et al. (2008) Prescribed when to wait and when a patient can be enrolled 22

23 Mitigating uncertainty from patients still in follow-up T is the length of follow-up for DLT u is a follow up time of a patient Patient has completed a fraction u/t of the total follow-up without a DLT 1-u/T of the follow-up is still remaining Conservative approach: the patient is counted as a patient with 1-u/T of a DLT Example. u/t = 0.3 no DLT Patient s contribution 0.7/1 (proposed) 0/0.3 (TITE-CRM) 23

24 Mitigating uncertainty from patients still in follow-up Ex. 1. Γ = 0.25 In the case of full follow-up 1/3 Pr(DLT rate > 0.25) = 0.67, therefore can enroll a patient at the same dose 1/3 + 1/1 Pr(DLT rate > 0.25) = 0.87, Data already observed Temporary fake DLT from a patient just enrolled therefore can enroll one more patient at the same dose 24

25 Mitigating uncertainty from patients still in follow-up 1/3 + 1/1 + 1/1 Pr(DLT rate > 0.25) = 0.96, therefore cannot enroll at this dose If the first two patients completed 1/3 of their follow-up: 1/ /1+0.66/1 Pr(DLT rate > 0.25) = 0.87, therefore can enroll a patient Conclusion If we observed 1/3, we can enroll 2 more patients right away If we observed 1/3 and have two other patients who completed 1/3 of their follow-up, we can enroll one more patient 25

26 Mitigating uncertainty from patients still in follow-up Ex. 2. Γ = 0.20 Have 5 patients at a dose no DLT no DLT DLT no DLT so far no DLT so far 1/ / /1 = 2/5, Pr( current DLT rate > 0.20 ) = 0.87, therefore at least one patient can be enrolled at this dose 26

27 Motivating example Phase I trial in patients less than 60 years-old with relapsed/refractory Acute Myeloid Leukemia (Foster et al., 2012) The trial used the time-to-event CCD method from Ivanova et al. (2007) with an ad-hoc modification that allowed rapid enrollment with immediate assignment. Next page shows the progression of the trial with dark arrows denoting DLTs 27

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29 Dose assignments for the first 9 patients. The target DLT rate is Pt Day of enrollment Data from pts with full follow-up at the time of enrollment Additional temporary DLTs for patients still in follow-up at the time of enrollment Estimated DLT rate Posterior probability that DLT rate is in (0.21, 0.31) d 1 d 2 d 1 d 2 d 1 d 2 d 1 d / / / / / / /3 0/0 0/0 0.37/ /3 1/2 0/0 0/ /3 1/2 0/0 1/ /3 1/2 0.4/1 0.4/ /4 1/3 0.4/1 0/ /5 2/4 0/0 0/ Dose Assign -ment

30 Comparison TITE-CRM when outcome is delayed Length of follow-up is 7 weeks Scenario TITE-CRM, 1 patient per week RED, 1 patient per week Scenario TITE-CRM, 1 patient per week RED, 1 patient per week

31 References Bekele, B. N., Ji, Y., Shen, Y., and Thall, P. F. (2008). Monitering late-onset toxicities in phase I trials using predited risks. Biostatistics 9(3), Cheung, Y.K. and Chappell, R. (2000). Sequential designs for phase I clinical trials with late-onset toxicities. Biometrics 56, Foster, M. C., Amin, C., Voorhees, P. M., van Deventer, H. W., Richards, K. L., Ivanova, A., Whitman, J., Chiu, W. M., Barr, N. D., and Shea, T. (2012). A phase I dose escalation study of clofarabine in combination with fractionated gemtuzumab ozogamicin in patients with refractory or relapsed acute myeloid leukemia. Leukemia and Lymphoma 53(7), Ji, Y., Liu, P., Li, Y., and Bekele, B. N. (2010). A modified toxicity probability interval method for dose-finding trials. Clinical trials 7, Ji, Y. and Wang, S. (2013). Modified toxicity probability interval design: a safer and more reliable method than the 3+3 design for pratical phase I trials 31, Ivanova, A., Flournoy, N., Chung, Y. (2007). Cumulative cohort design for dosefinding. Journal of Statistical Planning and Inference 137, Ivanova, A., Kim, S. (2009). Dose-finding for binary ordinal and continuous outcomes with monotone objective function: a unified approach. Biometrics 65, O'Quigley J, Pepe M, Fisher L. (1990). Continual reassessment method: A practical design for phase I clinical trials in cancer. Biometrics 46,