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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, - - 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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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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