Sentence examples for multivariate prognostic model from inspiring English sources

Then, a multivariate prognostic model was constructed by incorporating all the five adverse prognostic factors.

Whereas, this may not be sufficiently high to forego adjuvant chemotherapy, these observations pave the way to develop a clinically useful multivariate prognostic model for TNBC.

The development of a multivariate prognostic model is based on principles and methods described by Moons and Altman et al. [ 66- 69].

When both ER and PR protein expression were included in the same multivariate prognostic model, neither ER nor PR made an independent contribution to the prognostic model.

In upcoming studies it is necessary to analyze prospectively a large multicenter cohort of ccRCC to develop a multivariate prognostic model for ccRCC integrating each genomic aberration and well-established prognostic parameters such as T-stages, tumour size, nodal status and histological grade.

We depicted a multivariate prognostic model by combining these four independent prognostic factors according to the following criteria: good-risk group, that is, patients with zero to one negative prognostic factors; intermediate-risk group, that is, patients with two negative prognostic factors; poor-risk group, that is, patients with three to four negative prognostic factors.

This justifies the efforts to build multivariate prognostic models such as AdjuvantOnline (Adjuvant! Inc., San Antonio, TX, USA) and multigene predictors.

A P-value >0.1 was used as a criterion for exclusion, in accordance with the literature on multivariate prognostic modelling (Steyerberg et al., 2000).

To further evaluate the clinical significance of ER and PR expression, we built multivariate prognostic models incorporating ER and PR protein expression and standard clinico-pathologic factors.

Efforts are under way to develop simple multivariate prognostic models that use routine pathological variables (such as ER, histologic grade and HER2 status), and these could eventually rival the performance of the first-generation prognostic gene signatures [ 20, 21].

In line with Harrell's recommendations on multivariate prognostic modelling, 19 20 no more than m/10 parameters were considered, where m is the number of uncensored events, in this case cardiovascular deaths (n = 37).