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Since genetic factors do not change over time, the identification of genetic variants that may predict disease behavior and prognosis are superior to other predictive factors such as serological and clinical parameters.
In fact, it has been suggested that genes expressed in tumor-related stroma may predict disease outcome for breast cancer patients [15].
These results demonstrate pathogenic SIV infection results in a marked cytokine/chemokine inflammatory response during acute infection, which likely promotes ongoing viral replication, and may mediate immunopathology by favoring both direct and bystander immune activation, T cell proliferation, and may predict disease progression.
Furthermore, this analysis may predict disease severity in septic patients.
The presence of tumour cells in the blood circulation may predict disease recurrence and metastasis.
The presence of tumour cells in the circulation may predict disease recurrence and metastasis.
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Changes in F-FDG-PET, however, may predict disease-free and overall survival after induction therapy and resection in patients with esophageal cancer [ 42].
In large cohorts, the pre- and posttreatment absolute value, and doubling time of PSA, may predict disease-free survival (DFS) and long-term response to localised and systemic treatment (Christensen et al, 2008; Wo et al, 2009).
Dietary patterns that represent a combination of foods may better predict disease risk than single foods or nutrients.
Viral load monitoring may help predict disease severity and outcome.
(3) Viral load monitoring may help predict disease severity and patient outcome.
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