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While MYCN amplification in general predicts unfavorable outcome, no clinical or genomic factors have been identified that predict outcome within these cohorts of high-risk patients.
Stromal gene signatures have been identified that predict resistance to neoadjuvant chemotherapy for breast cancer [ 70].
Several markers have been identified that predict response to the EGFR-TKIs in NSCLC patients.
Multiple serum biomarkers have been identified that predict vascular disease and several have been incorporated into clinical practice.
MRS detectable biomolecules have been identified that predict survival of paediatric brain tumour patients across a range of tumour types.
In fact, sets of genes, commonly called gene signatures, have been identified that predict patient prognosis, and are already used in various clinical settings [ 2- 8].
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A version of a main-stream cyclone model has been identified that predicts the trend in hydrocyclone performance with liquid viscosity well, both in terms of separation efficiency and pressure drop.
In this study, we sought to determine whether PB gene expression signatures could be identified that predict radiation exposure status within a population that was heterogeneous for genotype, gender and time of sampling.
In addition, molecular signatures were identified that predicted the persistence of malignancy in the axillary lymph nodes after neoadjuvant chemotherapy.
No ICU risk factors were identified that predicted deficits in muscle strength or physical functioning.
Several factors were identified that predicted readmission (i.e., age, co-morbidities, economic disadvantage, number of previous admissions).
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