Motivating Trial Vidaza ® in AML patients undergoing allotx Activates genes for apoptosis ...

Motivating TrialVidaza® in AML patients undergoing allotx

Activates genes for apoptosis Modifies phenotype of leukemic cells to

potentiate a GVL effectDose-toxicity profile of Vidaza® is unknownThe cumulative risk of toxicity from repeated

administrations is unknown

Goal: Jointly optimize (Dose, Schedule)

Optimizing Dose and Schedule(Braun, Thall, Nguyen, deLima, 2007)

“Schedule” is a predetermined number of courses and days of administration within each course“Dose” = dose per administration

- Example, starting at time 0 : s(1) = (0, 1, 2, 7, 8, 9) s(2) = ( s(1) , s(1) + 14 days ) = (0, 1, 2, 7, 8, 9, 14, 15, 16, 21, 22, 23), etc.

-The agent may be administered as frequently as desired to each patient, provided the (dose,schedule) pair is sufficiently SAFE

- A patient’s actual administration times in the trial may deviate from the scheduled times

One cycle of an agent is administered at a fixedsequence of successive times s1 < s2 < . . . < sk ,the patient rests, & this is repeated one or more

times.

How many cycles can be given “safely?”

_______________________________________________

0 s1 s2 s3 s4 s5 s6 s7 s8rest

Hazard of toxicity from one administration :

A simple 3-parameter piecewise linear model

Each dose has its own 3-parameter triangle for the one-administration hazard

t = time in days

h(t)

Cumulative hazard of toxicity from

multiple administrations at a given dose

t = time in days

H(t)

Cumulative hazard of toxicity at day 10

t = time in days

H(t)

Cumulative Hazard of Toxicity by t* e = time of study entrysj = time of jth administration after e

(t* | dose, schedule)} =

∫ [0, t*] j h{u - (e + sj) | dose} du

Pr(Toxicity by time t* | dose, schedule) = F(t* | d,s,) = 1 – e-(t* | dose, schedule)

replaces the usual Pr(toxicity | dose) used for binary outcomes, ignoring schedule

Dose P erAdministrationmg m2

Day

of A

dmin

istr

atio

n (

Sch

edul

e )

8 16 24

028

5684

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Dose per Administration (mg/m2)

Treat 1st patient at the lowest (dose, schedule) pair

Based on current Time-to-Toxicity data, treat each patient at the best (dose, schedule) pair

Do not “skip” untried (dose, schedule) pairs

If no (dose, schedule) pair is acceptable

Stop the trial

Trial Conduct

Dose P erAdministrationmg m2

Day

of A

dmin

istr

atio

n (

Sch

edul

e )

8 16 24

028

5684

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Dose per Administration (mg/m2)

What Actually Happened in

The Vidaza® Trial

Since only 1 toxicity occurred in the first 27 patients, Dr. de Lima decided to add 4 higher

dose levels of Vidaza:

32, 40, 48, 56 mg/m2

After receiving IRB approval, the trial was re-started with 4x7 = 28 (dose,schedule)

combinations

16 new (dose, schedule)

pairs

Final Optimal CombinationFinal Optimal Combination

(40 mg/m(40 mg/m22 per administration, 3 cycles) per administration, 3 cycles)

A case where all (dose,schedule) combinations

are unacceptably toxic

After pat. #2 began treatment at (8 mg/m2, 2 cycles),

pat. # 1 treated at (8 mg/m2, 1 cycle) experienced toxicity

All (dose,schedule) pairs are too toxic The Trial is Stopped

EarlyT

Dose-schedule toxicity cop

Hazard of toxicity from one administration

b

a = area

c

Final Data Analysis

Posterior mean and standard deviation (SD) of

per-administration hazard parameters in the Bayesian model for Pr(toxicity| PAD, number of cycles).

Areaa

Days to Peak of Hazard

b

Days from Peak of Hazard to

Endc

Duration (Days)b + c

PAD Mean (SD) Mean (SD) Mean (SD) Mean (SD)

8 0.0058 (0.0034)

14.5 (24.1) 8.7 (12.8) 23.2 (27.8)

16 0.0095 (0.0041)

14.9 (22.9) 14.4 (21.6) 29.4 (31.5)

24 0.0138 (0.0049)

11.7 (25.7) 20.3 (38.9) 32.0 (47.3)

32 0.0163 (0.0054)

15.9 (12.4) 31.3 (29.4) 47.3 (26.6)

40 0.0295 (0.0160)

14.0 (11.9) 32.0 (29.0) 46.0 (26.5)

Final Data Analysis

Posterior mean ptox = probability of toxicity by day 116

Per Administration Dose of Vidaza (mg/m2)

Number of Cycles 8 16 24 32 40 48 56

4 0.105 0.164 0.225 0.260 0.407 0.475 0.531

3 0.082 0.129 0.180 0.211 0.339 0.394 0.445

2 0.056 0.089 0.125 0.148 0.246 0.289 0.331

1 0.029 0.046 0.065 0.077 0.134 0.160 0.186

For ptox = Pr(toxicity within 116 days), each entry is the

posterior value of Prob( ptox > 0.30 ). For each combination of

(Number of Cycles, Per-Administration Dose),

A = acceptable toxicity, T = unacceptable toxicity.

Final Data Analysis

Per Administration Dose of Vidaza (mg/m2)

Number of Cycles

8 16 24 32 40 48 56

40.006

A0.034

A0.148

A0.269

A0.783

A0.920

T0.970

T

30.001

A0.005

A0.030

A0.083

A0.558

A0.755

A0.883

T

20.000

A0.000

A0.001

A0.004

A0.220

A0.371

A0.541

A

10.000

A0.000

A0.000

A0.000

A0.025

A0.045

A0.076

A

Take-Away Messages

1) The optimal combination

(3 cycles, 32 mg/m2 per day)

would not have been found using ANY other phase I methods.

2) Current work is to incorporate progression-free survival time, to be used along with time-to-toxicity, into the method.

Conclusions

The Dose-Schedule AlgorithmDose-Schedule Algorithm reliably

1) Finds (Dose,Schedule) pairs having specified Pr(Toxicity by day t)

2) Stops if no (Dose,Schedule) is acceptable

Implementation is Hard Work, but a free computer program “Dose Schedule Finder” is available from

http://biostatistics.mdanderson.org/SoftwareDownload

Motivating Trial Vidaza ® in AML patients undergoing allotx Activates genes for apoptosis ...

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