Transcript Phase I Trial Designs

Phase I Trial Designs
Jud Blatchford, PhD
BIOM 6649 – Clinical Trials
April 9th, 2015
Table of Contents
1.
2.
3.
4.
Orientation
Introduction
Components of a Phase I Trial
Phase I Trial Designs
A. Rule-Based Designs
B. Statistical Designs
5. References
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ORIENTATION
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Orientation
• Features of a Clinical Trial (CT)
◦ Study of human beings
◦ Prospective
◦ Uses an intervention (i.e. changes some aspect of the
subjects)
◦ Protects the safety of the subjects
◦ Follows an approved protocol
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Orientation
• Phases of Clinical Trials
◦ Phase I – First time an experimental drug or treatment is
tested in humans to examine how well the drug is tolerated
◦ Phase II – Trials designed to examine if the drug or
treatment has a biological treatment effect
◦ Phase III – Trials designed to assess the treatment effect on
a clinically meaningful endpoint
◦ Phase IV – Post-marketing studies to gain additional
information regarding the safety of the drug or treatment
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Orientation
• Components of Study Design
◦ Rationale – Establishing a legitimate reason for the study
◦ Design – Detailed description of what treatments will be
administered, how they are administered, including a
timeline of administration
◦ Subjects – Determining the group to be studied and how
they will be assigned to treatment groups
◦ Data – Endpoint(s), obtaining data, and QA
◦ Sample Size Justification – Ensuring the study will be able
to answer the scientific question with adequate power
◦ Study Closure – Archiving study data, analysis files
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INTRODUCTION
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Introduction
• Phase I Clinical Trials
◦ An experimental drug, treatment, chemotherapeutic agent,
cytotoxic agent, is studied—hereafter referred to as “drug”
◦ Primary Goal: Safety
 Investigate whether the new drug or combination of
drugs can be administered safely to subjects
 Investigate optimal dosing and administration of drug
◦ Secondary Goal: Efficacy
 Offer a treatment option to subjects who have failed
other treatment regimens
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Introduction
• Underlying Assumptions
◦ The drug kills both cancer cells and other cells
◦ The effect is dose-dependent, therefore:
1. The efficacy of the drug increases with the dose
2. The toxicity of the drug increases with the dose
◦ Logically, it would be optimal to give the subjects the
highest dose of a drug that can be administered without
unacceptable toxicity
◦ Fundamental Question: What is this dose?
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Maximum Tolerated Dose (MTD)
• Definition of MTD:
◦ The highest dose without observing an unacceptable rate
of toxicity
• Aliases:
◦ Recommended Phase 2 Dose (RP2D)
◦ Phase 2 Recommended Dose (P2RD)
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COMPONENTS OF A PHASE I TRIAL
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Components of a Phase I Trial
• Definition of a Dose-Limiting Toxicity (DLT)
◦ Clarify time-frame for experiencing a DLT
• Dose Levels
◦ How many dose levels will be tested?
◦ What will the smallest dose be?
◦ What will the starting dose be?
• Subjects
◦ How many subjects will be tested?
◦ Will single subjects or cohorts be tested at each dose?
• What dose-escalation scheme will be employed?
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Definition of a DLT
• DLTs are typically defined
using the National Cancer
Institute’s (NCI) Common
Terminology Criteria for
Adverse Events (CTCAE).
• DLTs are often grade ≥ 3
non-hematological and grade
≥ 4 hematological toxicities,
which are definitely,
probably, or possibly related
to the drug.
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• CTCAE Grades
◦
◦
◦
◦
◦
◦
0 – No AE
1 – Mild
2 – Moderate
3 – Severe
4 – Life threatening
5 – Death
• Degrees of Related
Phase I Trial Designs
◦
◦
◦
◦
◦
Unrelated
Unlikely
Possibly
Probably
Definitely
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Definition of a DLT
• The length of observation within which a DLT
occurrence is “counted” should be explicitly stated
in the protocol
• Typical lengths used are the first cycle of
chemotherapy (often 3 weeks)
• Weight the trade-off between observation time
for a DLT and efficiency in enrolling subjects
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Choosing the Starting Dose
• Goals:
◦ Dose high enough to have chance of efficacy
◦ Dose low enough to avoid a DLT
• Use data from animal pre-clinical studies
• Scale dose by body surface area (mg/m2)
• Studies that aren’t “first-in-human” studies may
be informed from previous studies using the same
drug
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Choosing the Starting Dose
• Choices Used:
◦ First find dose that is lethal in 10% of mice (LD10)
 Standard starting dose was 10% of this dose (MELD10),
if no grade 4+ AEs observed in other species (rats, dogs,
etc.)
◦ Find the highest dose for which the most sensitive animals
investigated had no AEs
 Starting dose is 1/3 of this level (scaled)
◦ Find the minimal dose for which any toxicity is seen (TDL)
 Starting dose is 1/3 of the TDL
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Choosing the Number of Dose Levels
• Testing more dose levels to accurately estimate
the MTD creates a more cumbersome trial, and
may require more subjects
• Common number of levels is 4 to 7
• Observed number has ranged from 3 to 14
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Choosing the Dose Levels
• Desire to progress through possible doses in a
quick (e.g. exponential) manner
• Ethical considerations should guide the dose
escalation scheme used
• Linear sequence of numbers may be inefficient
◦ 20, 40, 60, 80, 100, 120, 140, …
• Famous sequence of increasing numbers:
◦ 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, …
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The Fibonacci Sequence
Term (n)
Value (fn)
Ratio (fn / fn-1)
1
1
-
2
1
1.000
3
2
2.000
4
3
1.500
5
5
1.667
6
8
1.600
7
13
1.625
8
21
1.615
9
34
1.619
10
55
1.618
11
89
1.618
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The Golden Ratio
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The Golden Ratio
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Fibonacci Sequence in Nature
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Spirals in a Pine Cone
Clockwise from Center
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Counter-clockwise from Center
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Modified Fibonacci Dose Escalation (MFDE)
Ratio (fn / f1)
Fib. Seq.
1
-
1.00
1
2
2.00
2.00
1
3
1.67
3.33
2
4
1.50
5.00
3
5
1.40
7.00
5
6
1.33
9.33
8
7
1.33
12.44
13
8
1.33
16.59
21
9
1.33
22.12
34
10
1.33
29.50
55
11
1.33
39.33
89
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Comparison
Conservative
Ratio (fn / fn-1)
Similar
Term (n)
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Ethical Considerations
• Approach the MTD from below (under-estimates
MTD)
◦ Bracketing the MTD is unbiased and more efficient
• Expected efficacy is minimal
◦ Historical response rate is 11%; temp. stable rate is 34%
◦ 40% expect a cure
• Subjects suffer significant toxicity
◦ Rate of grade 4 toxicity is 14%; death rate is 0.5%
• What subjects are told is very important
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PHASE I TRIAL DESIGNS
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Rule-Based Designs
1.
2.
3.
4.
5.
Traditional Escalation Rule
Variations of the Traditional Escalation Rule
Best of 5 Rule
Up-and-Down Designs
2-Stage Designs
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Traditional Escalation Rule (TER)
3 subjects receive
dose di
0 DLTs
1 DLT
2 or 3 DLTs
Escalate - 3 subjects
receive dose di+1
3 more subjects at
dose di
Stop escalation
De-escalate to di-1
0 DLTs
(1/6 with DLT)
1—3 DLTs
(≥ 2/6 with DLT)
Escalate - 3 subjects
receive dose di+1
Stop escalation
De-escalate to di-1
De-escalate until a level is reached where at least 6 subjects are treated and at most 1 DLT occurs.
MTD is the highest dose where at least 6 subjects were treated with at most 1 DLT.
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Evaluating the TER
Benefits
Criticisms
• Conservative escalation
• Ease of implementation
• Many subjects treated at
low, ineffective doses
• At least 2 subjects treated
at level above MTD
• The true MTD is
underestimated
◦ Rules regarding dose assignment
are clear
◦ Statistical models not fit after
each subject
• Design is robust
• Will arrive at reasonable
estimate of MTD
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Variations to TER
• After escalation stops, fill out all lower levels until
at least 6 subjects are treated at each level
• Treat subjects at a dose level between the level
where escalation stopped and the next lower level
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Best of 5 Rule
3 subjects receive
dose di
0 DLTs
1 or 2 DLTs
3 DLTs
Escalate to dose di+1
1 more at dose di
Stop escalation
1/4 with DLT
2/4 with DLTs
3/4 with DLTs
Escalate to dose di+1
1 more at dose di
Stop escalation
2/5 with DLTs
3/5 with DLTs
Escalate to dose di+1
Stop escalation
MTD is the dose prior to the dose on which escalation stopped.
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Up-and-Down Design (UaD)
1 subject receives
dose di
0 DLT
1 DLT
Escalate to dose di+1
De-escalate to di-1
Perform UaD for a pre-specified number of subjects (j).
MTD is the dose that would be assigned to the j+1st subject.
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Storer’s C Design (UaD-C)
1 subject receives
dose di
0 DLT
1 DLT
If 2 consecutive
subjects with 0 DLT,
escalate to dose di+1;
else give dose di
De-escalate to di-1
Perform UaD for a pre-specified number of subjects (j).
MTD is the dose that would be assigned to the j+1st subject.
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Stage 1
Storer’s Two-Stage BC Design (UaD-BC)
1 subject receives
dose di
0 DLT
1 DLT
Escalate to dose di+1
De-escalate to di-1
Stage 2
1 subject receives
dose di-1
0 DLT
1 DLT
If 2 consecutive
subjects with 0 DLT,
escalate to dose di;
else give dose di-1
De-escalate to di-2
Perform UaD for a pre-specified number of subjects (j).
MTD is the dose that would be assigned to the j+1st subject.
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Accelerated Titration Designs
Extension by Simon of Storer’s work
Design 1: TER
Designs 2—4
Stage 1: Single subjects until first DLT or second grade 2 AE
Stage 2: TER
Design 2: Toxicities observed in first cycle only
Design 3: Toxicities may be observed in any cycle
Design 4: Same as 3 except escalation factor is 2.0
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Statistical Designs
Dose escalation guided by a statistical model of the
relationship between dose and toxic response
1. Continual Reassessment Method
2. Modifications to the CRM
3. 2-Stage CRM Designs
4. TITE-CRM
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Continual Reassessment Method (CRM)
• First proposed by O’Quigley in 1990
• Subjects are enrolled individually
• A dose-toxicity function is assumed
◦ f(d | α) = Pr{DLT | α}
• After each patient completes observation, the
estimate of α is updated
• Strategy is to assign the dose closest to the
estimated MTD to each subject
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Considerations for the CRM
• Number of dose levels
• Initial estimates of toxicity rates at each dose level
• Target rate of DLT (θ)
• Dose-toxicity function
• Escalation restrictions
• Number of subjects to be treated
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Considerations
Number of Dose Levels
Initial Estimates of Toxicity
• Typically between 3 and 8
• In general, as the number of
dose levels in the trial
increases, the number of
subjects needed to
accurately estimate the MTD
will increase
• The estimates should bound
the target rate (θ)
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◦ The CRM is not robust when
doses tested do not induce
toxicity
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Choosing a Dose-Response Function
Logistic Function
Logistic Regression
Let p = Pr{DLT}
𝑝
ln
= 𝛽0 + 𝛽1(𝐷𝑜𝑠𝑒)
1−𝑝
Solving for p we have:
𝑝 =
𝑒 𝛽0+𝛽1(𝐷𝑜𝑠𝑒)
1+𝑒 𝛽0+𝛽1(𝐷𝑜𝑠𝑒)
One-parameter model:
𝑒 3+α(𝐷𝑜𝑠𝑒)
𝑝=
1 + 𝑒 3+α(𝐷𝑜𝑠𝑒)
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Choosing a Dose-Response Function
Hyperbolic Tangent Function
𝑇𝑎𝑛ℎ =
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𝑒 𝑥 −𝑒 −𝑥
𝑒 𝑥 +𝑒 −𝑥
=
𝑒 2𝑥 −1
𝑒 2𝑥 +1
Scaled Tanh Function
Pr{DLT}=
Phase I Trial Designs
𝑒 2(𝐷𝑜𝑠𝑒) −1
1
+
2𝑒 2(𝐷𝑜𝑠𝑒) +2
2
−α
41
Choosing a Dose-Response Function
CDF of Normal Distribution
2
P{DLT}=
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𝐷𝑜𝑠𝑒 −(𝑥−𝜇)
1
𝑑𝑥
2𝜎2
𝑒
2𝜋𝜎 −∞
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The Method of CRM
• Dose-toxicity function and θ are chosen a-priori
• Function is re-fit (i.e. new estimate of α is
obtained) after each subject’s observed toxicity
◦ New function is determined from the a-priori function and
the vector of observed toxicities
◦ Curve shifts to the right without toxicity; left with toxicity
• Next subject is treated at the dose level whose
Pr{DLT} is closest to θ
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Distributions of DLT Occurrence By Dose
Priors for Subject 1
Priors for Subject 26
• High degree of overlap of
probabilities between doses
• Separation between dose
levels becoming clearer
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Evaluating the CRM
Benefits
Criticisms
• Few subjects are treated at
low, ineffective doses
• Subjects are treated at doses
believed at the time to be
the most efficacious, yet safe
• Starting dose is too high
• Dose escalation is too
aggressive
• Trial length is too long
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Modified CRM
• Start at the lowest dose level under consideration
• Enroll two or three subjects at each cohort
• Constrain dose escalation to increase by at most
one dose level
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“Practical” CRM
• Proposed by Piantadosi
• Based on pre-clinical toxicity data:
◦ Choose dose that would produce low (10%) rate of DLT
◦ Choose dose that would produce high (90%) rate of DLT
◦ Estimate dose/toxicity curve that fits these 2 points
• Use the dose/toxicity curve to find dose for θ
• Treat three subjects at this level, then re-estimate
the dose-toxicity curve, dose for θ, and tx 3 more
• Repeat until target dose changes by < 10%
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2-Stage CRM Designs
• Stage 1: TER
◦ “2 + 2” is a more common first stage than “3 + 3”
◦ Continue until first toxicity is observed
• Stage 2: CRM
◦ After first toxicity, fit the dose-response curve using the
toxicity data accrued thus far
◦ Choose dose for next cohort of 2 as dose with estimated
rate of DLT closest to θ
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Time-to-Event CRM (TITE-CRM)
• Builds on the CRM described thus far
• Uses information from subjects accrued, even if
they haven’t finished observation period
◦ Subjects with DLT are given full weight
◦ Subjects without DLT are given weight t/T.
• Allows subjects to be enrolled without waiting for
prior cohorts to finish
◦ Benefits studies with delayed toxicity (e.g. radiation
studies)
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Example of a TITE-CRM Trial
• Subject accrual is instantaneous
• The majority of doses administered are near MTD
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Additional TITE-CRM Considerations
• Choice of weight function
◦ Uniform toxicities may use a linear function
◦ Expecting late toxicities may use a convex function
◦ Expecting early toxicities may use a concave function
• Setting a Margin (i.e. upper limit) on toxicity
◦ If θ = 0.20 and Margin = 0.05, dose for next subject will be
dose closest to 0.20 and not greater than 0.25
• Determine cumulative time exposure (B) before
allowing escalation (e.g. B = 2)
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Design Comparisons
• Fitting a model to the data will improve the
accuracy of the MTD found by rule-based designs
• Model-guided designs only perform well if
assumptions are met (θ in range of doses tested)
• Conflicting results when designs compared
• Few comparisons made on “level playing field”
• Both rule-based and model-guided designs are in
common use, for good reason
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Important Future Work
• “Individualized” Designs
◦ Development of designs allowing for within-subject dose
escalation
◦ Development of designs for targeted agents
• Designs for trials expecting minimal toxicity
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Pharmacokinetic Profiles
• Often of interest in a phase 1 study
• Studies how the body processes the drug
• Parameters of interest are typically:
◦
◦
◦
◦
◦
Cmax – Maximum concentration of drug
Tmax – Time until the maximum concentration of drug
λ – Elimination constant – describes rate of loss from body
T1/2 – Half-life of the drug
AUC – Area under the concentration curve
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Calculation of PK Parameters
• Cmax & Tmax – Directly from table of results
• λ = Taken from regression of ln(C) on time
• T1/2
◦ Create exponential decay equation from above regression
◦ Solve for T when the concentration is half of reference amt
• AUC = AUC0-t + AUCt-∞
◦ AUC0-t – Use trapezoidal rule
◦ AUCt-∞ = Ct / λ
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Example Calculations
• From regression of ln(C) on time we get:
◦
◦
◦
◦
◦
◦
◦
ln (C) = 2.25 – 0.58 T, so λ = 0.58 (not -0.58)
C = exp(2.25) * exp(-0.58)T
C = 9.5(-.56)T
4.75 = 9.5(-0.56)T
to solve for T1/2
½ = -0.56T
ln(1/2) = T*ln(-0.56)
T = 1.19 so T1/2 = 1.19 hours
• AUC = 12.03 + 0.06/0.58 = 12.18
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PK Design Considerations
• Sampling Times
◦ Important to have accurate estimates of Cmax
◦ Cluster several times around expected Tmax
• Sampling Period
◦ Important to have accurate estimate of λ
◦ US FDA requires times to capture at least 3 half-lives after
Tmax
• Bioequivalence Trials
◦ Create 90% CIs for ln[µ(A)] - ln[µ(B)], µ = PK parameter
◦ Check if all CIs are within 0.80 to 1.25 range
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REFERENCES
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References
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References (Continued)
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