Discussion
In this meta-analysis, the results revealed that MTV and TLG measurement
of tumor tissue showed potential as a biomarker for EFS. The results
about primary tumor SUVmax and nodal
SUVmax were significantly correlated with EFS with
relatively high heterogeneity. Besides, primary tumor
SUVmax could be a biomarker for OS, and nodal
SUVmax was significantly related to OS with relatively
high heterogeneity. Other FDG PET/CT parameters were found to have no
significant association with prognosis.
This meta-analysis focused on the FDG PET/CT parameters as a categorical
variable, but the results of articles interesting in FDG PET/CT
parameters as a continuous variable exhibited extreme discrepancy among
different studies. For example, Carpenter et al. reported that primary
tumor MTV and primary tumor TLG were significantly associated with OS in
the univariate analyses, whereas only primary tumor TLG were
significantly correlated with OS in the multivariate
analyses.26 Calles-Sastre et al. found that
primary-tumor MTV and primary-tumor TLG showed a significant association
with OS and with RFS in the univariate analyses.27Scher et al. detected primary-tumor MTV and primary-tumor TLG were
correlated with OS and DFS in the univariate analyses, whereas
primary-tumor TLG was the only FDG PET parameter significantly
correlated with OS and DFS in the multivariate
analyses.24 In addition, Liu et al. confirmed that
primary-tumor MTV was a significant predictor of OS in the univariate
analyses.28 Chong et al. reported that primary-tumor
SUVmax, primary tumor MTV, and primary tumor TLG were
significant prognostic factors for DFS in univariate analysis, but none
of them was significant in the multivariate analyses (Table
S2) .23
Apart from pretreatment FDG PET/CT parameters, some studies focused on
the prognostic value of during-treatment FDG PET/CT parameters.
Carpenter et al. reported that primary-tumor MTV and primary-tumor TLG
during treatment were significantly associated with OS and
DFS.26 Liu et al. found that primary-tumor MTV during
treatment was significantly associated with OS.28Krhili et al. confirmed that not only primary-tumor MTV and
primary-tumor TLG but also SUVmax during treatment were
significant prognostic factors for OS and DFS (Table
S3) .29 Besides, changes between pre- and
intra-treatment FDG-PET/CT parameters also were confirmed to be
prognostic factors in some studies. Park et al. confirmed that the
percentage changes of SUVmax have a prognostic value for
predicting DFS.30 Oh et al. showed that a decrease of
SUVmax was a statistically significant predictor of
PFS.31 However, Carpenter et al. reported no
correlation among the changes in primary-tumor SUVmax,
SUVmean, MTV, TLG, and survival.26
Except for the pretreatment FDG PET/CT parameter, during-treatment FDG
PET/CT parameter, and changes between pre- and intra-treatment
FDG-PET/CT parameters, the one-two punch, using various types of
prognostic factors to create a prognosis-predicting model, was a new
orientation. For example, Hong et al. suggested a simple prognosis
prediction model, using pretreatment FDG PET/CT and human papillomavirus
(HPV) genotyping in patients with LACC treated with
CCRT.32 Lee et al. constructed a nomogram based on
these six (including age, nodal SUVmax, primary-tumor
SUVmax, size, stage, and SCC) and seven (including age,
nodal SUVmax, primary-tumor SUVmax,
size, stage, SCC, and high-risk HPV status) independent risk factors for
two-year DFS and five-year OS.19 Besides, radiomics is
a new frontier to predict the prognosis of patients with LACC. For
example, Lucia et al. found that in LACC treated with CCRT, radiomics
features such as Grey Level Non-uniformity GLRLM from PET are
independent predictors of recurrence and loco-regional control with
significantly higher prognostic power than usual clinical
parameters.16 The predictive tool-enrolled FDG PET/CT
parameter still needs more study.
Our study has some noteworthy limitations. First, all studies enrolled
in the meta-analysis were retrospective, which might add selective bias.
Second, significant heterogeneity existed in the results of this
meta-analysis, and no subgroup analysis was performed for the limited
studies. The potential resource of the heterogeneity was probably from
four aspects. Patients in each study had different FIGO stages, different
histologic subtypes, different treatment strategies, and different
follow-up endpoints (Table 1-3) . Besides this, the different
PET/CT technique and image analysis were existed in each study, which
might cause the heterogeneity in this analysis (Table S4) .
Third, the cut-off values for FDG PET/CT metabolic parameters were
different in each study. Last, the HR used in this meta-analysis was
directly extracted from a Cox proportional hazards model (multivariate
analysis and univariate analysis) or indirectly estimated from
Kaplan-Meier curves. By ignoring this discrepancy, the potential
heterogeneity was exposed after synthesizing the results of all included
studies. Considering these limitations, future large-scale prospective
studies are needed to confirm the prognostic values of FDG PET metabolic
parameters further. Despite these limitations, our study is the first
meta-analysis to evaluate the prognostic value of FDG PET/CT metabolic
parameters in LACC treated with CCRT and offers some significant findings.