Impact of lymph node ratio on survival in stage IIIC endometrioid endometrial cancer: a Turkish Gynecologic Oncology Group study

Prognostic value of lymph node features in patients diagnosed with stage IIIC endometrial adenocancer

AIM

Our study investigated the lymph node (LN) features most affecting survival in endometrial adenocancer (EAC) patients with LN involvement.

MATERIALS AND METHODS

This retrospective study was based on a review of the records of patients diagnosed with EAC, who underwent hysterectomy and systematic retroperitoneal lymphadenectomy at the gynecologic oncology clinics of three centers between January 2009 and January 2019.

RESULTS

A total of 120 stage IIIC endometrioid-type EAC patients were included in the study. The patients were divided into small (<10 mm) and large (≥10 mm) groups according to the size of the largest metastatic LN. Patients were divided into single and multiple metastasis groups according to the number of metastatic LNs. The patients were divided into pelvic and paraaortic groups according to the location of the metastatic LNs. The effects of prognostic factors on disease-free survival (DFS) and overall survival (OS) were evaluated by Cox regression analysis. Large-sized metastatic LNs were an independent prognostic factor for DFS (hazard ratio [HR] = 5.4, 95% confidence interval [CI]: 1.-26.2; P = 0.035) and OS (HR = 9.0, 95% CI: 1.1-68.0; P = 0.033). The number (P = 0.093 for DFS, P = 0.911 for OS) and location (P = 0.217 for DFS, P = 0.124 for OS) of metastatic LNs were not independent prognostic factors for DFS or OS.

CONCLUSIONS

Large-sized metastatic LNs were an independent prognostic factor for survival in patients with stage IIIC EAC. Larger prospective studies including similar patient populations are required to verify these findings.

A population-based risk scoring system to individualize adjuvant treatment for stage IIIC endometrial cancer patients after surgery

BACKGROUND

To develop a risk scoring system to tailor the adjuvant treatment for stage IIIC EC patients after surgery.

METHODS

Data source was from the Surveillance, Epidemiology, and End Results (SEER) registry, where 3251 post-operative stage IIIC EC patients with different adjuvant treatment were included. Cox regression analysis was used to identify risk factors. The exp (β) of each independent risk factors generating from the cox analysis was used to construct the risk scoring system, which was further utilized to divide the patients into different risk subgroups and the efficacy of different adjuvant modalities in each risk subgroups would be compared accordingly.

RESULTS

Six independent risk factors were identified to develop the scoring system, which further divided the patients into three risk subgroups based on the total risk score (Low-risk≤8.46, 8.47 ≤ Middle-risk≤9.94, High-risk≥9.95). This study revealed that CRT was not superior to RT alone (HR:1.208, 95%CI: 0.852-1.741; P = 0.289) or CT alone (HR:1.260, 95%CI: 0.750-2.116; P = 0.382) in Low-risk subgroup. We also observed that CRT had a survival advantage over other treatment modalities in the Middle-risk subgroup (All P < 0.001), but CRT and CT alone to be superimposable in the High-risk subgroup (HR: 1.395, 95%CI: 0.878-2.216; P = 0.159).

CONCLUSION

A risk scoring system has been developed to tailor the adjuvant treatment for stage IIIC EC patients after surgery, where RT or CT alone could be a substitute for CRT in Low-risk patients and CT alone was a potential alternative for High-risk patients while CRT remained to be the optimal choice for the Middle-risk patients.

Construction and validation of a prognostic model for stage IIIC endometrial cancer patients after surgery

BACKGROUND

To explore the most predictive lymph node (LN) scheme for stage IIIC endometrial cancer (EC) patients after hysterectomy and develop a scheme-based nomogram.

METHODS

Data from 2626 stage IIIC EC patients, diagnosed between 2010 and 2014, were extracted from the Surveillance, Epidemiology, and End Results (SEER) registry. The predictive ability of four LN schemes was assessed using C-index and Akaike information criterion (AIC). A nomogram based on the most predictive LN scheme was constructed and validated. The comparison of the predictive ability between nomogram and FIGO stage was conducted using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA).

RESULTS

FIGO stage (stage IIIC1/stage IIIC2) was not an independent risk factor for OS in stage IIIC EC patients (P = 0.672) and log odds of positive lymph nodes (LODDS) had the best predictive ability (C-index: 0.742; AIC: 8228.95). A nomogram based on LODDS was constructed and validated, which had a decent C-index of 0.742 (0.723-0.762). The nomogram showed a better predictive ability than that of the FIGO staging system.

CONCLUSION

FIGO IIIC1/FIGO IIIC2 could not differentiate the prognosis for stage IIIC EC patients. We developed and validated a nomogram based on LODDS to predict OS for post-operative patients with stage IIIC EC.

Characterizing impact of positive lymph node number in endometrial cancer using machine-learning: A better prognostic indicator than FIGO staging?

BACKGROUND

Number of involved lymph nodes (LNs) is a crucial stratification factor in staging of numerous disease sites, but has not been incorporated for endometrial cancer. We evaluated whether number of involved LNs provide improved prognostic value.

PATIENTS AND METHODS

Patients diagnosed with node-positive endometrial adenocarcinoma without distant metastasis were identified in the National Cancer Database. We trained a machine-learning based model of overall survival. Shapley additive explanation values (SHAP) based on the model were used to identify cutoffs of number of LNs involved. Results were validated using a Cox proportional hazards regression model.

RESULTS

We identified 11,381 patients with endometrial cancer meeting the inclusion criteria. Using the SHAP values, we selected the following thresholds: 1-3 LNs, 4-5 LNs, and 6+ LNs. The 3-year OS was 82.0% for 1-3 LNs, 74.3% for 4-5 LNs (hazard ratio [HR] 1.38; p < 0.001), and 59.9% for 6+ LNs (HR 2.23; p < 0.001). On univariate Cox regression, PA nodal involvement was a significant predictor of OS (HR 1.20; p < 0.001) but was not significant on multivariate analysis when number of LNs was included (HR 1.05; p = 0.273). Additionally, we identified an interaction between adjuvant therapy and number of involved LNs. Patients with 1-3 involved LNs had 3-year OS of 85.2%, 78.7% and 74.2% with chemoradiation (CRT), chemotherapy, and radiation, respectively. Patients with 6+ involved LNs had 3-yr OS of 67.8%, 49.6%, and 48.9% with CRT, chemotherapy, and radiation, respectively (p < 0.001).

CONCLUSION

Number of involved LNs is a stronger prognostic and predictive factor compared to PA node involvement.

Impact of lymph node ratio in patients with stage IIIC endometrial carcinoma treated with postoperative radiotherapy

Aim: To evaluate the prognostic value of the lymph node ratio (LNR) and other clinicopathological factors in patients with stage IIIC endometrial cancer. Methods: Factors affecting overall survival (OS) and progression-free survival (PFS) were assessed in 397 patients with stage IIIC endometrial cancer treated with postoperative radiotherapy. Patients undergoing the removal of at least ten lymph nodes were included in the study. Results: The 5-year OS and PFS rates were 58% and 52%, respectively, with a median follow-up time of 35.7 months. The LNR cutoff value was 9.6%. In the multivariate analysis, advanced age (≥60 years), grade III tumor, presence of cervical stromal invasion, higher LNR and lack of adjuvant chemotherapy were independent predictors for worse OS and PFS. Conclusion: The LNR is an independent predictor for OS and PFS in patients with stage IIIC endometrial cancer treated with postoperative radiotherapy.

SuMO-Fil: Supervised multi-omic filtering prior to performing network analysis

Multi-omic analyses that integrate many high-dimensional datasets often present significant deficiencies in statistical power and require time consuming computations to execute the analytical methods. We present SuMO-Fil to remedy against these issues which is a pre-processing method for Supervised Multi-Omic Filtering that removes variables or features considered to be irrelevant noise. SuMO-Fil is intended to be performed prior to downstream analyses that detect supervised gene networks in sparse settings. We accomplish this by implementing variable filters based on low similarity across the datasets in conjunction with low similarity with the outcome. This approach can improve accuracy, as well as reduce run times for a variety of computationally expensive downstream analyses. This method has applications in a setting where the downstream analysis may include sparse canonical correlation analysis. Filtering methods specifically for cluster and network analysis are introduced and compared by simulating modular networks with known statistical properties. The SuMO-Fil method performs favorably by eliminating non-network features while maintaining important biological signal under a variety of different signal settings as compared to popular filtering techniques based on low means or low variances. We show that the speed and accuracy of methods such as supervised sparse canonical correlation are increased after using SuMO-Fil, thus greatly improving the scalability of these approaches.

Comparison of Different Lymph Node Staging Schemes for Predicting Survival Outcomes in Node-Positive Endometrioid Endometrial Cancer Patients

Objective: To compare the prognostic predictive performance of six lymph node (LN) staging schemes: American Joint Committee on Cancer (AJCC) N stage, number of retrieved lymph nodes (NRLN), number of positive lymph nodes (NPLN), number of negative lymph nodes (NNLN), lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) among node-positive endometrioid endometrial cancer (EEC) patients. Methods: A total of 3,533 patients diagnosed with node-positive EEC between 2010 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively analyzed. We applied X-tile software to identify the optimal cutoff value for different staging schemes. Univariate and multivariate Cox regression models were used to assess the relationships between different LN schemes and survival outcomes [disease-specific survival (DSS) and overall survival (OS)]. Moreover, Akaike information criterion (AIC) and Harrell concordance index (C-index) were used to evaluate the predictive performance of each scheme in both continuous and categorical patterns. Results: N stage (N1/N2) was not an independent prognostic factor for node-positive EEC patients based on multivariate analysis (DSS: p = 0.235; OS: p = 0.145). Multivariate model incorporating LNR demonstrated the most superior goodness of fit regardless of continuous or categorical pattern. Regarding discrimination power of the models, LNR outperformed other models in categorical pattern (OS: C-index = 0.735; DSS: C-index = 0.737); however, LODDS obtained the highest C-index in continuous pattern (OS: 0.736; DSS: 0.739). Conclusions: N stage (N1/N2) was unable to differentiate the prognosis for node-positive EEC patients in our study. However, LNR and LODDS schemes seemed to have a better predictive performance for these patients than other number-based LN schemes whether in DSS or OS, which revealed that LNR and LODDS should be more helpful in prognosis assessment for node-positive EEC patients than AJCC N stage.

Is the extent of lymphadenectomy a prognostic factor in International Federation of Gynecology and Obstetrics stage II endometrioid endometrial cancer?

AIM

This study aimed to evaluate the prognostic significance of adequate lymph node dissection (LND) (≥10 pelvic lymph nodes (LNs) and ≥ 5 paraaortic LNs removed) in patients with International Federation of Gynecology and Obstetrics (FIGO) stage II endometrioid endometrial cancer (EEC).

METHODS

A multicenter department database review was performed to identify patients who had been operated and diagnosed with stage II EEC at seven centers in Turkey retrospectively. Demographic, clinicopathological, and survival data were collected and analyzed.

RESULTS

We identified 284 women with stage II EEC. There were 170 (59.9%) patients in the adequate lymph node dissection (LND) group and 114 (40.1%) in the inadequate LND group. The 5-year overall survival (OS) rate of the inadequate LND group was significantly lower than that of the adequate LND group (84.1% vs. 89.1%, respectively; p = 0.028). In multivariate analysis, presence of lymphovascular space invasion (LVSI) (hazard ratio [HR]: 2.39, 95% confidence interval [CI]: 1.23-4.63; p = 0.009), age ≥ 60 (HR: 3.30, 95% CI: 1.65-6.57; p = 0.001], and absence of adjuvant therapy (HR: 2.74, 95% CI: 1.40-5.35; p = 0.003) remained as independent risk factors for decreased 5-year disease-free survival (DFS). Inadequate LND (HR: 2.34, 95% CI: 1.18-4.63; p < 0.001), age ≥ 60 (HR: 2.67, 95% CI: 1.25-5.72; p = 0.011), and absence of adjuvant therapy (HR: 4.95, 95% CI: 2.28-10.73; p < 0.001) were independent prognostic factors for decreased 5-year OS in multivariate analysis.

CONCLUSION

Adequate LND and adjuvant therapy were significant for the improvement of outcomes in FIGO stage II EEC patients. Furthermore, LVSI was associated with worse 5-year DFS rate in stage II EEC.