The main question our study tries to answer is whether the mutations of BRAF and KRAS genes are indicators of different prognosis within otherwise uniform (with respect to the clinical parameters considered) subpopulations of patients with CRC.
A ki67 cutoff at 14% discerns two groups of different prognosis inside the luminal group (extracting HER2+ and PR-); and comparison of ki67 cutoff between 14 and 11% found overlapped CI (median: 6.31 (5.99 to 6.62) vs. 6.49 (6.21 to 6.78)).
Although copy number and expression profiles of SCC lung carcinomas have been extensively described [ 10, 30, 31], assigning these patients into groups of different prognosis is still a challenge [ 13], maybe due to the potential existence of several biological subtypes within the SCC category [ 13, 32].
The heterogeneity of the study population due to inclusion of patients with various types of cancer, different prognoses, comorbidities and the need for rehabilitation and supportive care may have diluted the effects of the intervention in subgroups of patients with specific diagnoses or problems.
Further, the neoadjuvant setting permits an in vivo evaluation of treatment efficacy and allows the identification of subgroups of patients with different prognoses.
At a clinical level, this heterogeneity corresponds to different prognosis, patterns of relapse, response to treatment and clinical behavior for each breast cancer subtype.
The belief that NSLBP consists of a number of subgroups, with different prognoses and different treatment responses, has increased over the last decade, and this has been mirrored in a proliferation of studies reporting research into NSLBP subgroups aimed at identifying homogeneous groups of patients with similar trajectories or who would benefit from a certain intervention [ 6- 10].
We conclude that analysis of serum p53 antibodies may be of value for the identification of patients with different prognoses.
The addition of these two markers with these three current prognostic factors improves the predictive ability and allows identifying new groups of patients with different prognoses both in terms of DFS and OS.
Survival analyses for Cdc20 and securin were performed as Kaplan Meier estimates to demonstrate cumulative percentages of breast cancer-specific mortality, and Cox's proportional hazards models to assess differences between the groups of patients with different prognoses.
