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Fig 1.

CONSORT participant flow diagram of the PERMAD trial.

Abbreviations: components of mFOLFOX6: Fluorouracil, folinic acid, oxaliplatin.

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Fig 2.

Classification workflow.

CAF signatures collected before or during treatment until disease progression were normalized and designated as no event or event, respectively. For classification, we only considered the CAF signatures (n) during treatment until disease progression and performed classification experiments with the classifiers random forest, support vector machine, and k-nearest neighbor. To adjust the meta-parameters of the classifiers, we performed a nested crossvalidation (CV) solely on the training data (see Methods). Afterwards, the obtained parameters and the performance of the classifier were evaluated on the test data (outer CV).

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Table 1.

Baseline characteristics (safety set population).

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Fig 3.

Patient characterization.

Kaplan-Meier curves of progression free survival (PFS) (A) and overall survival (OS) in cohort 1, cohort 2, and both cohorts together.

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Table 2.

Prediction performance.

Performance (in %) results of the 5 × 10 crossvalidation (CV) experiment. The mean performance and the interquartile range of the training and test phases are reported.

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Fig 4.

Performance measures of the classification models.

Data was analyzed in 5 × 10 crossvalidation (CV) experiments. The figure shows the accuracy, sensitivity (progress within 100 days), specificity (no progress within 100 days), and SS2 achieved in the test phases of the 5 × 10 CV for the classifiers random forest (RF, blue), support vector machine (SVM, green), and k-nearest neighbor(k-NN, orange).

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Fig 5.

Importance ranking.

The figure shows the results of the crossvalidation (CV) with the random forest (RF) classifier for the individual features within the 5 × 10 CV. The features with the highest importance can be found at the top of the figure.

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Fig 6.

Evaluation of the top-ten signature with RFs.

Accuracy, sensitivity (progression within 100 days), specificity (no progression within 100 days) and SS2 in the test phases of the 5 × 10 CV on the top-ten signature. Reclassification accuracy, i.e. training and test on the data, resulted in an accuracy of 100% for a minimum of 41 trees.

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Table 3.

Prediction performance based on top-10 signature.

Performance of the top-10 signature (in %) in the 5 × 10 crossvalidation (CV) experiment, the mean performance and interquartile range are given.

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