Dataset Information

Effectiveness comparisons of various therapies for FIGO stage IB2/IIA2 cervical cancer: a Bayesian network meta-analysis.

ABSTRACT:

Background

Cervical cancer is a common malignancy of the female genital tract. Treatment options for cervical cancer patients diagnosed at FIGO (2009) stage IB2 and IIA2 remains controversial.

Methods

We perform a Bayesian network meta-analysis to directly or indirectly compare various interventions for FIGO (2009) IB2 and IIA2 disease, in order to improve our understand of the optimal treatment strategy for these women. Three databases were searched for articles published between 1971 and 2020. Data on included study characteristics, outcomes, and risk of bias were abstracted by two reviewers.

Results

Seven thousand four hundred eighty-six articles were identified. Thirteen randomized controlled trials of FIGO (2009) IB2 and IIA2 cervical cancer patients were included in the final analysis. These trials used six different interventions: concomitant chemoradiotherapy (CCRT), radical surgery (RS), radical surgery following chemoradiotherapy (CCRT+RS), neoadjuvant chemotherapy followed by radical surgery (NACT+RS), adjuvant radiotherapy followed by Radical surgery (RT + RS), radiotherapy alone (RT).SUCRA ranking of OS and Relapse identified CCRT+RS and CCRT as the best interventions, respectively. Systematic clustering analysis identified the CCRT group as a unique cluster.

Conclusion

These data suggest that CCRT may be the best approach for improving the clinical outcome of cervical cancer patients diagnosed at FIGO (2009) stage IB2/IIA2. Phase III randomized trials should be performed in order to robustly assess the relative efficacy of available treatment strategies in this disease context.

SUBMITTER: Cheng J

PROVIDER: S-EPMC8493709 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundNomograms are predictive tools widely used for estimating cancer prognosis. We aimed to develop/validate a nomogram to predict the postsurgical 5-year overall survival (OS) and disease-free survival (DFS) probability for patients with stages IB1, IB2, and IIA1 cervical cancer [2018 International Federation of Gynecology and Obstetrics (FIGO 2018)].MethodsWe retrospectively enrolled cervical cancer patients at 47 hospitals with stages IB1, IB2, and IIA1 disease from the Clinical Diagnosis and Treatment for Cervical Cancer in China database. All patients were assigned to either the development or validation cohort (75% of patients used for model construction and 25% used for validation). OS and DFS were defined as the clinical endpoints. Clinicopathological variables were analyzed based on the Cox proportional hazards regression model. A nomogram was established and validated internally (with bootstrapping) and externally, and its performance was assessed according to the concordance index (C-index), receiver-operating characteristic curve, and calibration plot.ResultsIn total, 4,065 patients were enrolled and assigned to the development cohort (n=3,074) or validation cohort (n=991). The OS nomogram was constructed based on age, FIGO stage, stromal invasion, and lymphovascular space invasion (LVSI). The DFS nomogram was constructed based on the FIGO stage, histological type, stromal invasion, and LVSI. Both nomograms showed greater discrimination than the FIGO 2018 staging system in the development cohort [OS nomogram vs. FIGO 2018: C-index =0.69 vs. 0.61, area under the curve (AUC): 69.8 vs. 60.3; DFS nomogram vs. FIGO 2018: C-index =0.64 vs. 0.57, AUC: 62.6 vs. 56.9], and the same results were observed the definition in the validation cohort. Calibration plots demonstrated good agreement between the predicted and actual probabilities of 5-year OS/DFS in the development and validation cohorts. We stratified the patients into 3 subgroups with differences in OS/DFS. Each risk subgroup presented a distinct prognosis.ConclusionsWe successfully developed a robust and powerful model for predicting 5-year OS/DFS in stages IB1, IB2, and IIA1 cervical cancer (FIGO 2018) for the first time. Internal and external validation showed that the model had great prediction performance and was superior to the currently utilized FIGO staging system.

Project description:BackgroundTo compare the oncological outcomes of patients with FIGO 2018 stage IIIC cervical cancer (CC) involving different local tumor factors who underwent abdominal radical hysterectomy (ARH), neoadjuvant chemotherapy and radical surgery (NACT), or radical chemoradiotherapy (R-CT).MethodsBased on tumor staging, patients with stage IIIC were divided into T1, T2a, T2b, and T3 groups. Kaplan-Meier and Cox proportional hazards regression analysis were used to compare their overall survival (OS) and disease-free survival (DFS) of 5 years.ResultsWe included 4,086 patients (1,117, 1,019, 869, and 1,081 in the T1, T2a, T2b, and T3 groups, respectively). In the T1 group, NACT was correlated with a decrease in OS (hazard ratio [HR] = 1.631, 95% confidence interval [CI]: 1.150-2.315, P = 0.006) and DFS (HR = 1.665, 95% CI: 1.255-2.182, P < 0.001) than ARH. ARH and NACT were not correlated with OS (P = 0.226 and P = 0.921) or DFS (P = 0.343 and P = 0.535) than R-CT. In the T2a group, NACT was correlated with a decrease in OS (HR = 1.454, 95% CI: 1.057-2.000, P = 0.021) and DFS (HR = 1.529, 95% CI: 1.185-1.974, P = 0.001) than ARH. ARH and NACT were not correlated with OS (P = 0.736 and P = 0.267) or DFS (P = 0.714 and P = 0.087) than R-CT. In the T2b group, NACT was correlated with a decrease in DFS (HR = 1.847, 95% CI: 1.347-2.532, P < 0.001) than R-CT nevertheless was not correlated with OS (P = 0.146); ARH was not correlated with OS (P = 0.056) and DFS (P = 0.676). In the T3 group, the OS rates of ARH (n = 10), NACT (n = 18), and R-CT (n = 1053) were 67.5%, 53.1%, and 64.7% (P = 0.941), and the DFS rates were 68.6%, 45.5%, and 61.1%, respectively (P = 0.761).ConclusionR-CT oncological outcomes were not entirely superior to those of NACT or ARH under different local tumor factors with stage IIIC. NACT is not suitable for stage T1, T2a, and T2b. Nevertheless ARH is potentially applicable to stage T1, T2a, T2b and T3. The results of stage T3 require confirmation through further research due to disparity in case numbers in each subgroup.