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For some types of treatment programs, baseline patient status and staff variables were the only covariates to predict benefits, but for others treatment intensity and length have predictive power as presented in Fig. 2.
In some studies a single CRC disease state was used with an average lifetime treatment cost predicted or estimated thus the results failed to predict benefits of early detection and prevention of CRC [14, 19, 50].
These data suggest that BER expression may predict benefits from endocrine therapy.
According to some reports, the FEV1 baseline value appears to be irrelevant to predict benefits from PR in COPD patients [ 6, 7, 10, 11].
Here, we highlight two factors that predict benefits for compliant gaits: (i) minimizing cost of work associated with bouncing viscera; and (ii) leg control for robust stability in uneven terrain.
Here, we address this apparent paradox, highlighting two factors that predict benefits for compliant gaits: (i) minimizing cost of work associated with bouncing viscera; and (ii) leg control for robust stability in uneven terrain.
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Furthermore, evidence is lacking on the ability of VEGF family members to predict benefit from specific treatments, especially on their predictive value for bevacizumab use.
Thus, it is important to identify factors among the older population that predict benefit from ICU treatment, establish prognostic factors for long-term survival, and elucidate the HRQOL.
EndoPredict did not, however, predict benefit from adding paclitaxel.
Biomarkers are required to predict benefit from the different approaches to individualise treatment.
High heregulin levels predict benefit from patritumab treatment in patients with NSCLC.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com