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.