Validation of the 2021 FIGO staging schema for advanced vulvar cancer

ObjectiveThe International Federation of Gynecology and Obstetrics (FIGO) revised the vulvar cancer staging schema in 2021. Previous stage IIIA–B diseases were reclassified based on nodal size (≤5 mm for stage IIIA compared with >5 mm for stage IIIB), and previous stage IVA1 disease based on non-osseous organ extension was reclassified to stage IIIA whereas osseous extension remained as stage IVA. This study sought to validate the 2021 FIGO vulvar cancer staging schema.MethodsThis retrospective cohort study examined 889 women with stage III–IV vulvar cancer from 2010 to 2015 in the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program. Stage shift and overall survival were assessed by comparing the 2021 and 2009 FIGO staging schemas.ResultsStage shift occurred in 229 (25.8%) patients (upstaged 17.7% and downstaged 8.1%). When comparing the new and previous staging schemas, 5 year overall survival rates were 45.6% versus 48.9% for stage IIIA, 47.0% versus 44.2% for stage IIIB, and 13.9% versus 25.1% (interval change −11.2%) for stage IVA diseases. According to the revised staging schema, 5 year overall survival rates were similar for stage IVA and IVB diseases (13.9% vs 14.5%) and for stage IIIA and IIIB disease (45.6% vs 47.0%). For new stage IIIA disease, 5 year overall survival rates differed significantly based on the staging factors (nodal involvement vs non-nodal organ involvement, 48.9% vs 38.7%, difference 10.2%, p=0.038).ConclusionThe 2021 FIGO staging schema results in one in four cases of advanced vulvar cancer being reclassified. Survival rates of patients with new stage IVA disease worsened significantly whereas those of patients with new stage IIIA disease were heterogenous based on the staging factors. The discriminatory ability of the revised 2021 FIGO staging schema for 5 year overall survival rate between patients with stage IIIA and IIIB tumors and those with IVA and IVB tumors is limited in this study population.

Risk Prediction Model of Postoperative Venous Thrombosis of Ovarian Cancer

Objective To investigate the influencing factors of venous thromboembolism (VTE) after ovarian cancer surgery, and construct its prediction model. Methods A total of 67 patients with ovarian cancer who developed VTE after surgery were selected from October 2008 to June 2020 in the Department of Obstetrics and Gynecology, First Hospital of Lanzhou University, and conducted a retrospective study with 100 patients without VTE after the operation who were confirmed by imaging during the same period. The clinical data of two groups of patients were analyzed and compared, and the risk prediction model was established. The ROC curve was drawn to evaluate the prediction effect of the model. Results Univariate analysis showed that there were statistically significant differences in age, menopausal status, hypertension, neoadjuvant chemotherapy, FIGO staging, lymph node metastasis, operation time, preoperative plasma FIB and D-dimer between the thrombosis group and the non-thrombosis group;The results of multivariate analysis showed that old age, neoadjuvant chemotherapy, late FIGO staging, high levels of plasma FIB and D-dimer before surgery are independent risk factors for VTE after ovarian cancer surgery. Construct a prediction model based on the results of multivariate regression analysis: Logit(P) = 0.053 × age + 0.917 × neoadjuvant chemotherapy + 0.956 × tumor FIGO staging + 0.398 × preoperative plasma FIB + 0.531 × preoperative D-dimer -7.679 ( Neoadjuvant chemotherapy, yes=1, no=0; tumor FIGO stage Ⅰ+Ⅱ=1, Ⅲ+Ⅳ=2; age, preoperative plasma FIB and D-dimer are actual values). The ROC curve analysis shows that the AUC value of the model is 0.773, the sensitivity is 74.6%, the specificity is 71.0%, and the total prediction accuracy rate is (78+39)/167=0.701. Conclusions Age, neoadjuvant chemotherapy, tumor FIGO staging, preoperative plasma FIB and D-dimer can be used as reliable indicators to predict the occurrence of postoperative VTE in patients with ovarian cancer. The constructed prediction model has good risk prediction ability, It has certain clinical application value.

Nomogram to predict overall survival based on the log odds of positive lymph nodes for patients with endometrial carcinosarcoma after surgery

Purpose Aims to compare the prognostic performance of the number of positive lymph nodes (PLNN), lymph node ratio (LNR) and log odds of metastatic lymph nodes (LODDS) and establish a prognostic nomogram to predict overall survival (OS) rate for patients with endometrial carcinosarcoma (ECS). Methods Patients were retrospectively obtained from Surveillance, Epidemiology and End Results (SEER) database from 2004 to 2015. The prognostic value of PLNN, LNR and LODDS were assessed. A prediction model for OS was established based on univariate and multivariate analysis of clinical and demographic characteristics of ECS patients. The clinical practical usefulness of the prediction model was valued by decision curve analysis (DCA) through quantifying its net benefits. Results The OS prediction accuracy of LODDS for ECS is better than that of PLNN and LNR. Five factors, age, tumor size, 2009 FIGO, LODDS and peritoneal cytology, were independent prognostic factors of OS. The C-index of the nomogram was 0.743 in the training cohort. The AUCs were 0.740, 0.682 and 0.660 for predicting 1-, 3- and 5-year OS, respectively. The calibration plots and DCA showed good clinical applicability of the nomogram, which is better than 2009 FIGO staging system. These results were verified in the validation cohort. A risk classification system was built that could classify ECS patients into three risk groups. The Kaplan-Meier curves showed that OS in the different groups was accurately differentiated by the risk classification system and performed much better than FIGO 2009. Conclusion Our results indicated that LODDS was an independent prognostic indicator for ECS patients, with better predictive efficiency than PLNN and LNR. A novel prognostic nomogram for predicting the OS rate of ECS patients was established based on the population in the SEER database. Our nomogram based on LODDS has a more accurate and convenient value for predicting the OS of ECS patients than the FIGO staging system alone.

Validation of The 2018 FIGO Staging System for Predicting The Prognosis of Patients With Stage IIIC Cervical Cancer

Purpose We aimed to validate the prognostic performance of the 2018 International Federation of Gynecology and Obstetrics(FIGO) IIIC staging system for patients with cervical cancer. Methods We conducted a retrospective analysis of patients with stage III cervical cancer according to the 2018 FIGO staging system who received standardized treatment from January 2011 to December 2014. Results Multivariable analysis revealed that stage IIIC1 was not significantly associated with increased risk of death compared with stages IIIA (hazard ratio [HR] = 1.432; 95% confidence interval [CI]: 0.867 to 2.366; P = 0.161) and IIIB (HR = 1.261; 95% CI: 0.871 to 1.827; P = 0.219). Stage IIIC2 was an independent indicator of increased risk of mortality compared with stages IIIA (HR = 2.958; 95% CI :1.757 to 4.983; P < 0.001) and IIIB (HR = 2.606; 95% CI: 1.752 to 3.877; P < 0.001). We stratified patients with stage IIIC1 according to T stage and compared survival outcomes. Stage IIIC1 (T1) was associated with longer 5-year overall survival (OS) compared with stages IIIA (P = 0.004) or IIIB (P < 0.001). An optimal cut-off value (= 2) was established for predicting the prognosis of stage IIIC1p(T1/T2a), which was associated with the number of pelvic lymph nodes metastases (PLNMs). Patients with stage IIIC1pN1-2 experienced longer 5-year OS compared those with stages IIIA (P = 0.01) or IIIB (P < 0.001). Conclusion Patients with stage IIIC1 cervical cancer exhibited heterogeneous clinical characteristics reflecting their variable prognoses, depending on T-stage and the extent of PLNMs

Imaging in Carcinoma Cervix and Revised 2018 FIGO Staging System: Implications in Radiology Reporting

The International Federation of Gynecology and Obstetrics (FIGO) staging system of carcinoma cervix saw a radical change in 2018 with the inclusion of cross-sectional imaging tools for the assessment of disease extent and staging. One of the major revisions is the inclusion of lymph node status, detected either on imaging or pathological evaluation, in the staging system. The changes were based on long-term patient follow-up and survival rates reported in literature. Thus, it becomes imperative for a radiologist to be well versed with the recent staging system, its limitations, and implications on the patient management.