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

Abstract

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.

A Prognostic Nomogram Based on Log Odds of Positive Lymph Nodes to Predict Overall Survival for Non-Metastatic Bladder Cancer Patients after Radical Cystectomy

“…A retrospective study had shown that LODDS was a superior predictive indicator for disease-free survival compared to pN and LNR in patients with rectal cancer [ 16 ]. Similar results and conclusions can be found in various studies with different cancers including lung squamous cell carcinoma [ 17 ], squamous cell carcinoma of the penis [ 18 ], colon cancer [ 19 ], endometrial carcinosarcoma [ 20 ], etc. For bladder cancer, Jin et al assessed the predictive capacity of pN, LNR, and LODDS in patients with muscle-invasive urothelial carcinoma of bladder cancer [ 12 ].…”

Prognostic nomogram based on the lymph node metastasis indicators for patients with bladder cancer: A SEER population‐based study and external validation

“… 32 Compared with the above, LODDS could reflect both the absolute number of PLNs and negative LNs, indicating that it could stratify patients categorized as N0 classification (no regional LNM) and patients with all examined LNs metastasized. 29 , 33 , 34 …”

“…However, the association between LNR and tumor prognosis remains controversial when all or none examined LNs exhibited metastasis, especially with insufficient regional LNs removed 32 . Compared with the above, LODDS could reflect both the absolute number of PLNs and negative LNs, indicating that it could stratify patients categorized as N0 classification (no regional LNM) and patients with all examined LNs metastasized 29,33,34 …”

Epidemiology and prediction model of patients with carcinosarcoma in the United States

“…The rapid decline in mortality among men may be due in part to reduction in smoking ( 29 ). Thus, while medical advances have slowed the trend of rising mortality, targeted cancer control treatments remain urgent ( 11 , 25 , 27 , 28 , 30 ). Consistent with the overall rising incidence and slowing death trend, the prevalence of carcinosarcoma has increased year-by-year, mainly in women, elderly, blacks, and localized stage.…”

“…The total score was calculated using the quantitative score of each factor, and the 1-, 3-, and 5-year survival rate were scientifically and accurately predicted. Due to the inclusion of the primary tumor site, the predictive model is applicable to a wider population of patients and has a better predictive probability than other single-site predictive models ( 11 , 30 ). In summary, this simple but effective model could be used to individualize prognostic assessment of carcinosarcoma and will facilitate clinical decision-making.…”