METHODS
A comprehensive literature search for relevant studies published up to January 2021 was performed
using SCOPUS and Pubmed databases. Only articles in which survivin was detected by IHC staining
were included in the study. All analyses were conducted by using Comprehensive Meta-Analysis.
Eight articles and data of 1535 patients were included in the study. The Hazard Ratio was used to
examine the relationship between CRC and survivin protein, for the relative weights of each research
article. HR and 95% confidence interval values and general summary HR were calculated and forest
plot graph was obtained.
RESULTS
Statistical heterogeneity Cochrane"s Q test statistics 24.156; p=0.004 and I2 value was obtained as 62,742.
In line with the assumption that the data consisted of different populations, the HR and 95% CI values
were calculated as 1.446 (1.103-1.897) using the Dersimonian and Laird random effects model. In order
to evaluate the risk of publication bias, funnel plots were obtained, including log HR and standard error
values on the x and y axes, respectively.
CONCLUSION
The analyzes obtained suggest that survivin overexpression in CRC is associated with poor prognosis.
(HR=1.446; 95% CI: 1.103-1.897).
Keywords: BIRC5; colorectal cancer; forest plot; metaanalysis; prognostic; survivin
Survivin/BIRC5 is one of the first inhibitors of
apoptosis protein (IAPs) family to stimulate apoptosis.
The survivin gene, which consists of 3 introns
and 4 exons in humans, is located in the 17q25 region
of the chromosome and is 14.7 kb in length.
It encodes the survivin protein which is 142 amino
acids long and 16.5KD weigh.[
Prognostic biomarkers identify patients who are
probabilistically at either higher risk for adverse disease-
related events or a faster rate of decline in their
health status.[
Total, 53 articles from Pubmed database and nine
articles from Scopus database were obtained. Twentyfive
articles were remained after reduction as can be
shown in Table
BIRC5: Baculoviral Inhibitor of apoptosis Repeat-Containing
5; IHC: Immunohistochemistry; OR: Odds ratio;
HR: Hazard ratio; AUC: Area under the curve.
Selection and Extraction Criteria
The articles indicated the expression of survivin immunohistochemically
and overall survival in CRC
were selected. Articles associated with general staining
were taken without considering the relationship
with cytoplasmic and nuclear staining. After entering
the keywords, the compliance of the articles obtained
with the selection criteria was also confirmed from the
article title and abstract. If there are relevant articles
in the literature discussions of the included articles,
they are also included in the study. From these articles
with patient clinicopathological characteristics
and overall survival data were selected. HR for overall
survival was provided or could be calculated from the
data presented were selected. Articles that provided
sufficient data comparing the expression of survivin
with clinicopathological data and that enabled us to
calculate the HR. The publications in which a different
analysis was made other than the immunohistochemistry
analysis, the publications published in a different
language other than English, and the publications
without survival data were excluded. Articles were examined by two independent investigators; Aktas
SH. and Akin-Bali DF. Extracted data were recorded
by including first author's name, year of publication,
PMID or DOI, region, number of cases, tumor stage,
neoadjuvant therapy, cut off value, HR estimate, HR,
and confidence interval (95% CI).
Statistical Analysis
Statistical data analysis was performed in the comprehensive
meta-analysis (version 3-trial edition) program.
The HR was used to examine the relationship
between CRC and survivin protein, for the relative
weights of each research article. HR and 95% confidence
interval values and general summary HR were
calculated and forest plot graph was obtained. HR>1
indicates that patients with survivin overexpression
show a worse prognosis. Pooled estimates of HR were
estimated by a random-effects model due to high between-
study heterogeneity. Heterogeneity was assessed
using Higgin's I2 statistic and Cochran's Q-test. Tausquared
statistics as a part of the statistical analysis
performed in the study and is the estimated variation
between the effects for test accuracy observed in different
studies. HR and 95% CI values were calculated
by Dersimonian and Laird random-effects model, assuming
that the data consisted of different populations.
In order to evaluate the risk of publication bias, funnel
plots were obtained, including log Hazard ratio and
standard error values on the x and y axes, respectively.
P<0.05 was accepted as the statistical significance level.
Funnel Plots a graphical representation of effect size
and standard error. To determine the publication bias
the bottom left of the funnel is analyzed. Negative or
insignificant studies are listed on the lower left. If the
lower left side is blank (asymmetric plot), it is stated as
publication bias. According to the results of the analysis
in the graph above, there is no publication bias for
the literatures included in our study (Fig.
Essentially, survivin has been subjected to some
meta-analysis studies in terms of CRC prognosis due
to these important features mentioned above. Huang et
al.[
Our current meta-analysis study was performed
for 8 of 25 research articles in which survivin was
stained immunohistochemically in CRC to date. The
study of Kallikmanis et al. was extracted from Huang
et al. metaanalysis and Krieg et al. metaanalysis. Hsiao
et al. and Lin et al. study were extracted from Krieg
et al. metaanalysis. Ponnelle, Qui, Sarela articles were
not included although they were related to the overall
survival in CRC and immunohistochemical staining
of survivin from the Huang et al. meta-analysis study.
[
Eight articles define the criteria for the meta-analysis
we performed; survival data HR, HR estimate, 95% CI
data. Immunohistochemical method was chosen for
meta-analysis. Thus, it was aimed to create relatively less
heterogeneity in the meta-analysis of the articles, which
were basically carried out using a single technique.
Investigating the articles that we have meta-analyzed,
the article of Fang et al.[
The contribution to the meta-analysis of the 2009
article by Fang et al. was determined as 45.84%. After
this study, Goossens Beumer et al. made the highest
contribution in the study they carried out in 2014.
The contribution of the research to the meta-analysis
was 19.05% (HR=1.63 CI % 95 1.440-1.845 p<0.001;
HR=1.40, CI % 95 1.021-1.920 p<0.037).
Peer-review: Externally peer-reviewed.
Conflict of Interest: All authors declared no conflict of interest.
Ethics Committee Approval: Ethical approval is not applicable, because this article does not contain any studies with human or animal subjects. The analyzed data are publicly available.
Financial Support: This study has received no financial support.
Authorship contributions: Concept - S.H.A.; Design - S.H.A., O.Y.; Supervision - S.H.A., D.F.A.B.; Funding - None; Materials - None; Data collection and/or processing - B.E.; Data analysis and/or interpretation - S.H.A., B.E., D.F.A.B.; Literature search - S.H.A., D.F.A.B., O.Y.; Writing - S.H.A., B.E.; Critical review - S.H.A., D.F.A.B., O.Y.