We can/could do so much more with publicly shared data Tito Fojo, - - PowerPoint PPT Presentation

we can could do so much more with publicly shared data
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We can/could do so much more with publicly shared data Tito Fojo, - - PowerPoint PPT Presentation

We can/could do so much more with publicly shared data Tito Fojo, MD, PhD Columbia University Theory for regression and growth f(t) = e (g t) + e (-d t) -1 Where f = tumor measurement in t days d = regression rate constant; g = growth


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We can/could do so much more with publicly shared data

Tito Fojo, MD, PhD Columbia University

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f(t) = e(g · t) + e(-d · t) -1

Where f = tumor measurement in t days d = regression rate constant; g = growth rate constant

Theory for regression and growth

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Exponential regression and growth: 4 equations

f(t) = e(g · t) + e(-d · t) -1 f(t) = e(g · t) f(t) = (1 - Ø) • exp(g • t) + Ø • exp(-d • t) - 1

gd [growth AND regression] gx [only growth] dx [only regression] gdØ [growth, regression + sensitive fraction]

f(t) = e(-d · t)

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14 Models

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Analysis of independently conducted colorectal cancer trials in PDS confirms results from randomized trials and provides robust data sets against which to benchmark smaller subsets

Red = Statistically inferior; all others in black including data from Gregorio Marañon Hospital in Madrid were statistically indistinguishable

Bevacizumab + FOLFOX 1st line FOLFIRI 1st line FOLFIRI 2nd line FOLFOX 1st line Gregorio Marañon

N = 451 g = -6.71

(-7.1, -6.29)

N = 243 g = -6.52

(-7.12, -6.06)

N = 172 g = -6.51

(-7.11, -6.17)

N = 390 g = -6.03

(-6.65, -5.51)

N = 58 g = -6.62

(-7.23, -6.17)

Log g

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Project Data Sphere: Colorectal Cancer

Predicting overall survival with g values estimated using scans Survival in Months 6 18 24 12 Survival Probability 1.0 0.75 0.5 0.25 P < 0.0001

Slowest g values] Intermediate g values] Fastest g values] Number at risk

30 36

414 419 423 412 413 346 337 283 169 147 103 53 6 7 4 1 44 32 13 Slowest Intermediate Fastest

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Colorectal Cancer FOLFIRI + Afilbercept OS: 13.5 vs 12.06 months ∆ = 1.44 months p = 0.0032

p = 0.00000000000591 [Wilcoxon]

Volumetric

p = 0.0000000743 [Wilcoxon]

Unidimensional g

p = 0.000000000282 [Wilcoxon]

Bidimensional g

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Colorectal Cancer FOLFIRI + Afilbercept OS: 13.5 vs 12.06 months ∆ = 1.44 months

Power Simulations Reference = Afilbercept + FOLFIRI Experimental = FOLFIRI 1000 resamples with replacement of Exp

Unidimensional Data N = 40 80% P Volumetric Data N = 27 80% P Bidimensional Data N = 27 80% P

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N g value Docetaxel Sample Size for 80% Power Docetaxel Sample Size for 90% Power n = 1132 0.0032 n = 21 n = 26 n = 100 0.0031 n = 26 n = 36 n = 200 0.0030 n = 18 n = 25 n = 300 0.0030 n = 18 n = 24

Towards a Virtual Control – Data in PDS

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Great for real world data ➜ f(t) = e(g · t) + e(-d · t) -1

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Power Simulations: B = Reference; A = Experimental 1000 resamples with replacement of A Volumetric Data