The time to progression ratio for phase II trials of personalized medicine Marc Buyse, ScD IDDI, Louvain-la-Neuve, and I-BioStat, Hasselt University, Belgium

Definition of TTPR TTPR in gastro-intestinal stromal tumors TTPR to design a trial in advanced colorectal cancer TTPR for trials of personalized medicine Tentative conclusions Outline

The TTP ratio (TTPR) TTP 1 First progression Second progression Death Start of Rx for advanced disease TTP 2 TTPR = TTP 2 / TTP 1 Rx 1 Rx 2 Rx 3 … TTP 3

Use of TTPR Cytostatics are not expected to induce tumor shrinkage, but it is hoped that they can stabilize the tumor (delay progression). For second-line therapies, the « time to progression ratio » (or « growth modulation index »), is defined as TTPR = TTP 2 / TTP 1 Given the natural history of most tumors, TTPR generally does not exceed 1 (i.e. TTP2 tends to be shorter than TTP1). Von Hoff suggested that TTPR > 1.33 reflects activity of the second-line therapy. Ref: Mick et al. Controlled Clinical Trials 21:343-59, 2000.

TTPR-based designs : second-line treatment only TTP 1 First progression, entry on trial Second progression Start of Rx for advanced disease TTP 2 Rx 1 Rx 2

TTP 1 First progression Second progression Start of Rx for advanced disease, entry on trial TTP 2 Rx 1 Rx 2 TTPR-based designs : two lines of treatment

Proportion of patients with TTPR > 1.33 after cross-over from 400 mg to 800 mg of imatinib daily, broken down by response to 400mg Partial response2/3 (67%) Stable disease13/36 (36%) Progressive disease12/72 (17%) All patients27/110 (25%) Ref: Zalcberg et al, Eur J Cancer 41:1751-7, TTPR when doubling dose of imatinib for progressing gastro-intestinal stromal tumors

Ref: Debiec-Rychter et al, Eur J Cancer 42: , R 196 *181 * 800 mg imatinib daily400 mg imatinib daily * Nr of patients with adequate DNA for KIT genotype analysis Trial comparing two imatinib doses in patients with gastro-intestinal stromal tumors

Ref: Debiec-Rychter et al, Eur J Cancer 42: , Cumulative incidence of response by KIT mutation

Proportion of patients with TTPR > 1.25 after cross-over from 400 mg to 800 mg Exon 11 mutation (N=248) 83% Exon 9 mutation (N=58)57% Wild type (N=52)7% Ref: Debiec-Rychter et al, Eur J Cancer 42: , P= P= TTPR after cross-over by KIT mutation

Ref: Tournigand et al, J Clin Oncol 22:229-37, R FOLFOX – FOLFIRIFOLFIRI – FOLFOX Trial comparing two chemotherapy sequences in patients with advanced colorectal tumors Primary endpoint = Time to second progression (TTP1 + TTP2) Secondary endpoints = TTP1, TTP2, survival

Distribution of TTPR in advanced colorectal cancer

50% 0.5 Distribution of TTPR in advanced colorectal cancer   of the patients had a TTPR > 0.5

33% Distribution of TTPR in advanced colorectal cancer   of the patients had a TTPR >

25% 1 Distribution of TTPR in advanced colorectal cancer   of the patients had a TTPR > 1

20% 1.25 Distribution of TTPR in advanced colorectal cancer   of the patients had a TTPR > 1.25

TTPR – test of hypothesis A possible null hypothesis is: H 0 : TTPR = TTP 2 / TTP 1  HR 0 versus the alternative hypothesis: H A : TTPR = TTP 2 / TTP 1 > HR 0

50% 0.75 Test of hypothesis in advanced colorectal cancer H 0 : TTPR ≤ 0.75

A sign test statistic For the i th patient, let r i be equal to +1 if TTP 2 > TTP 1  HR 0 –1 if TTP 2  TTP 1  HR 0 and TTP 2 is uncensored The test statistic (equivalent to a sign test statistic) X² = (  i r i )² /  i r i ² has a  ² distribution with 1 d.f. Ref: Mick et al. Controlled Clinical Trials 21:343-59, 2000.

A sign test statistic Ref: Mick et al. Controlled Clinical Trials 21:343-59, % 85% 90% HR 0 = 0.7  = 0.05 Correlation = 0.7

A sign test statistic Ref: Mick et al. Controlled Clinical Trials 21:343-59, HR 0 = 0.7  = 0.05 Correlation = 0.5

A sign test statistic Ref: Mick et al. Controlled Clinical Trials 21:343-59, HR 0 = 0.7  = 0.05 Correlation = 0.3

TTP 1 vs. TTP 2 in advanced colorectal cancer R² = 0.03

TTP 1 vs. TTP 2 in advanced colorectal cancer

Statistics for correlated survival times In the absence of censoring, TTP1 and TTP2 can be compared using a paired t-test or a non-parametric test for paired observations. If TTP 2 is censored, TTP 1 and TTP 2 are paired survival times. The ordinary rank test statistics (e.g. logrank or Gehan-Wilcoxon) can be used with variance corrected to account for the correlation between TTP 1 and TTP 2. Ref: Jung, Lifetime Data Analysis 5:67-79, 1999.

TTPR – another test of hypothesis Let p be the proportion of patients for whom TTPR > HR 0. A possible null hypothesis is: H 0 : p  p 0 versus the alternative hypothesis: H A : p > p 0 which leads to Flemings’ one-stage or Simon’ two-stage designs.

22% 1.33 Tests of hypothesis in advanced colorectal cancer H 0 : p 0 ≤ 22%

Trial of molecular profiling TTP 1 Last progression, entry on trial Progression on targeted therapy TTP 2 At least two prior therapies for advanced disease, no further therapy available Molecular profiling of tumor biopsy by IHC, FISH or micro-array to identify target Ref: Von Hoff, AACR 100 th Annual Meeting, Denver, CO, April 18-22, 2009.

Trial designed to test p 0 (proportion of patients with TTPR > 1.3): H 0 : p  p 0 = 15% Primary analysis: proportion of patients with TTPR > 1.3: 18 / 66 (27%, 95% C.I. 17% - 38%, P = 0.007) Breast 8 / 18 (44%) Colorectal 4 / 11 (36%) Ovarian 1 / 5 (20%) Others 5 / 32 (16%) Trial of molecular profiling Ref: Von Hoff, AACR 100 th Annual Meeting, Denver, CO, April 18-22, 2009.

Promising results, and amongst the 18 patients with TTPR > 1.3, none would have received same drug through plysician’s choice. However, Is TTPR > 1.3 good enough? Trial was not randomized, therefore no evidence that physician’s choice could have yielded similar results Only 66 patients of 106 could have molecular profiling Trial of molecular profiling

Trial designs using TTPR – pros and cons + Test time to progression rather than response; hence well suited to test cytostatic agents + Patients serve as their own control, a desirable feature to control between-patient variability + Efficient if substantial correlation between TTP 1 and TTP 2 -Choice of appropriate value for HR 0 -TTP 1 difficult to estimate retrospectively, and potentially biased downwards if standard first-line treatment included in design and new agent is promising -Inefficient if poor correlation between TTP 1 and TTP 2