Relationship Between Neoadjuvant Chemotherapy and Log Odds of Positive Lymph Nodes and Their Prognostic Role in Advanced Ovarian Cancer Patients With Optimal Cytoreductive Surgery

Impact of Treatment Delay on the Prognosis of Patients with Ovarian Cancer: A Population-based Study Using the Surveillance, Epidemiology, and End Results Database

Purpose: This study aimed to assess the impact of treatment delay on prognosis in patients with ovarian cancer. Methods: A retrospective analysis of patients with ovarian cancer in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 was performed. Chi-square tests were used to assess baseline differences. The Kaplan-Meier method was used to evaluate the effect of different treatment intervals on survival outcomes in patients. Cox regression analyses were used to identify independent factors associated with ovarian cancer prognosis. Results: Of the 21,590 patients included, 15,675 (72.6%), 5,582 (25.9%), and 333 (1.54%) were classified into the immediate-treatment (<1 month after diagnosis), intermediate-delay (1-2 month delayed), and long-delay groups (≥3 months delayed), respectively. The 5-year probability of overall survival (OS) was 61.4% in the immediate-treatment group, decreasing to 36.4% and 34.8% in the intermediate- and long-delay groups, respectively. Similar survival differences were also reflected in cancer-specific survival (CSS), with 5-year CSS probabilities of 66.7%, 42.6%, and 41.8% in the aforementioned groups, respectively. Patients in the intermediate-delay group showed poorer OS (adjusted hazard ratio [HR], 1.06; 95% confidence interval [CI], 1.02-1.11; p=0.006) and CSS (adjusted HR, 1.06; 95% CI, 1.01-1.11; p=0.012) than immediate-treatment group. Conclusions: Patients with delayed treatment had poorer OS and CSS. The patient's waiting time from diagnosis to initial treatment should be within 1 month.

Prognostic Value of Lymph Node Parameters in Elderly Patients With Stage III Serous Ovarian Cancer Based on Competing Risk Model

OBJECTIVES

Competing risk models were used in this study. The purpose of this study was to assess the predictive usefulness of lymph node characteristics in elderly patients with stage III serous ovarian cancer.

METHODS

We conducted a retrospective analysis on 148,598 patients from 2010 to 2016 using the surveillance, epidemiology, and end results database. Lymph node characteristics were collected and examined, including the number of lymph nodes retrieved the number of lymph nodes examined (ELN) and the number of positive lymph nodes (PN). Using competing risk models, we evaluated the connection between these variables and overall survival (OS) and disease-specific survival (DSS).

RESULTS

This study included a total of 3457 ovarian cancer patients. Multivariate analysis using the COX proportional hazards model found that ELN>22 was an independent predictive factor for both OS (hazard ratio [HR] [95% CI]=0.688 [0.553 to 0.856], P <0.05) and DSS (HR [95% CI]=0.65 [0.512 to 0.826], P <0.001), PN>8 was identified as a significant risk factor for both OS (HR [95% CI]=0.908 [0.688 to 1.199], P =0.497) and DSS (HR [95% CI]=0.926 [0.684 to 1.254], P =0.62). Subsequently, using the competing risk model, ELN>22 was found to be an independent protective factor for DSS (HR [95% CI]=0.738 [0.574 to 0.949], P =0.018), while PN>8 was identified as a risk factor for DSS (HR [95% CI]=0.999 [0.731 to 1.366], P =1).

CONCLUSIONS

Our findings demonstrate the robustness of the competing risk model to evaluate the results of the COX proportional hazards model analysis.