Histological Tumor Type is Associated with One-Year Cause-Specific Survival in Women with Stage III-IV Epithelial Ovarian Cancer: A Surveillance, Epidemiology, and End Results (SEER) Database Population Study, 2004-2014

Real-world study of lymphadenectomy in patients with advanced epithelial ovarian cancer

BACKGROUND

The evidence on the role of retroperitoneal lymphadenectomy is limited to less common histology subtypes of epithelial advanced ovarian cancer.

METHODS

This retrospective cohort study utilized data from the Surveillance, Epidemiology, and End Results Program from January 1, 2010, to December 31, 2019. Patients with stage III-IV epithelial ovarian cancer were included and divided into two groups based on whether they received retroperitoneal lymphadenectomy. The primary outcomes are overall survival (OS) and cause-specific survival (CSS).

RESULTS

Among the 10 184 included patients, 5472 patients underwent debulking surgery with retroperitoneal lymphadenectomy, while 4712 patients only underwent debulking surgery. No differences were found in the baseline information between the two groups after propensity score matching. Retroperitoneal lymphadenectomy during debulking surgery was associated with improved 5-year OS (43.41% vs. 37.49%, p < 0.001) and 5-year CSS (46.43% vs. 41.79%, p < 0.001). Subgroup analysis further validate the retroperitoneal lymphadenectomy increased the 5-year OS and CSS in patients with high-grade serous cancer. Although the results were not validated in the less common ovarian cancer (including endometrial cancer, mucinous cancer, low-grade serous cancer, and clear cell cancer), the tendency showed patients with the above four subtypes may benefit from the lymphadenectomy which is restricted for small sample size after propensity score matching.

CONCLUSIONS

This study revealed that retroperitoneal lymphadenectomy could further improve the survival outcome during debulking surgery in patients with advanced epithelial ovarian cancer. The conclusion was affected by the histology subtypes of ovarian cancer and further studies are needed to validate the conclusion in less common ovarian cancer.

Differences of survival benefits brought by various treatments in ovarian cancer patients with different tumor stages

PURPOSE

The current study aimed to explore the prognosis of ovarian cancer patients in different subgroup using three prognostic research indexes. The current study aimed to build a prognostic model for ovarian cancer patients.

METHODS

The study dataset was downloaded from Surveillance Epidemiology and End Results database. Accelerated Failure Time algorithm was used to construct a prognostic model for ovary cancer.

RESULTS

The mortality rate in the model group was 51.6% (9,314/18,056), while the mortality rate in the validation group was 52.1% (6,358/12,199). The current study constructed a prognostic model for ovarian cancer patients. The C indexes were 0.741 (95% confidence interval: 0.731-0.751) in model dataset and 0.738 (95% confidence interval: 0.726-0.750) in validation dataset. Brier score was 0.179 for model dataset and validation dataset. The C indexes were 0.741 (95% confidence interval: 0.733-0.749) in bootstrap internal validation dataset. Brier score was 0.178 for bootstrap internal validation dataset.

CONCLUSION

The current research indicated that there were significant differences in the survival benefits of treatments among ovarian cancer patients with different stages. The current research developed an individual mortality risk predictive system that could provide valuable predictive information for ovarian cancer patients.

Observation of the therapeutic effect of apatinib in advanced platinum-resistant recurrent epithelial ovarian cancer

BACKGROUND

Apatinib is an oral anti-angiogenic drug that mainly targets vascular endothelial growth factor receptor 2 (VEGFR-2) and is widely used in a variety of solid tumours. The purpose of this study is to evaluate the clinical efficacy and safety of apatinib in patients with advanced platinum-resistant relapsed epithelial ovarian cancer (EOC).

METHODS

A retrospective analysis was performed, the clinical data of patients with stage IIIC-IV platinum-resistant relapsed EOC between January 2014 and May 2018 were collected. The objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) were reviewed and evaluated. The propensity score matching (PSM) method was used to determine the final case data included in this study.

RESULTS

According to 1:2 propensity matching, 108 patients were finally taken into account: 36 in the apatinib group and 72 in the control group. The follow-up ended in January 2019, and the median follow-up time was 28 months. In the apatinib group, ORR was 30.56% and DCR was 66.67%, whereas in the control group, ORR was 16.67% and DCR was 44.44%. In the apatinib group, median PFS was 6.0 months (95% CI 3.69-8.31) and median OS was 15.8 months (95% CI 6.99-24.6), while in the control group, median PFS was 3.3 months (95% CI 2.44-4.16) and median OS was 9.2 months (95% CI 6.3-12.06); the difference was statistically significant (P < 0.05). Apatinib was more effective than conventional chemotherapy in reducing the risk of PFS [HR 0.40 (95% CI 0.22-0.76), P = 0.0017] and OS [HR 0.40 (95% CI 0.21-0.73), P = 0.002]. Multivariate Cox analysis showed that the course of treatment and decrease in serum CA125 levels are independent risk factors for PFS in patients, while apatinib, the length of treatment course and the location of the lesion are independent risk factors for recurrence affecting the OS of patients. The main grade 3-4 adverse events in the apatinib group were hypertension, hand-foot syndrome, and oral mucosal ulcers, and all adverse events were controllable.

CONCLUSION

Apatinib was found to be both safe and effective in patients with advanced platinum-resistant relapsed EOC. More in-depth clinical research and applications should be carried out.

Nomogram for predicting postoperative cancer-specific early death in patients with epithelial ovarian cancer based on the SEER database: a large cohort study

Purpose

Ovarian cancer is a common gynecological malignant tumor. Poor prognosis is strongly associated with early death, but there is no effective tool to predict this. This study aimed to construct a nomogram for predicting cancer-specific early death in patients with ovarian cancer.

Methods

We used data from the Surveillance, Epidemiology, and End Results database of patients with ovarian cancer registered from 1988 to 2016. Important independent prognostic factors were determined by univariate and multivariate logistic regression and LASSO Cox regression. Several risk factors were considered in constructing the nomogram. Nomogram discrimination and calibration were evaluated using C-index, internal validation, and receiver operating characteristic (ROC) curves.

Results

A total of 4769 patients were included. Patients were assigned to the training set (n = 3340; 70%) and validation set (n = 1429; 30%). Based on the training set, eight variables were shown to be significant factors for early death and were incorporated in the nomogram: American Joint Committee on Cancer (AJCC) stage, residual lesion size, chemotherapy, serum CA125 level, tumor size, number of lymph nodes examined, surgery of primary site, and age. The concordance indices and ROC curves showed that the nomogram had better predictive ability than the AJCC staging system and good clinical practicability. Internal validation based on validation set showed good consistency between predicted and observed values for early death.

Conclusion

Compared with predictions made based on AJCC stage or residual lesion size, the nomogram could provide more robust predictions for early death in patients with ovarian cancer.

Long-Term Survival Among Histological Subtypes in Advanced Epithelial Ovarian Cancer: Population-Based Study Using the Surveillance, Epidemiology, and End Results Database

BACKGROUND

Actual long-term survival rates for advanced epithelial ovarian cancer (EOC) are rarely reported.

OBJECTIVE

This study aimed to assess the role of histological subtypes in predicting the prognosis among long-term survivors (≥5 years) of advanced EOC.

METHODS

We performed a retrospective analysis of data among patients with stage III-IV EOC diagnosed from 2000 to 2014 using the Surveillance, Epidemiology, and End Results cancer data of the United States. We used the chi-square test, Kaplan-Meier analysis, and multivariate Cox proportional hazards model for the analyses.

RESULTS

We included 8050 patients in this study, including 6929 (86.1%), 743 (9.2%), 237 (2.9%), and 141 (1.8%) patients with serous, endometrioid, clear cell, and mucinous tumors, respectively. With a median follow-up of 91 months, the most common cause of death was primary ovarian cancer (80.3%), followed by other cancers (8.1%), other causes of death (7.3%), cardiac-related death (3.2%), and nonmalignant pulmonary disease (3.2%). Patients with the serous subtype were more likely to die from primary ovarian cancer, and patients with the mucinous subtype were more likely to die from other cancers and cardiac-related disease. Multivariate Cox analysis showed that patients with endometrioid (hazard ratio [HR] 0.534, P<.001), mucinous (HR 0.454, P<.001), and clear cell (HR 0.563, P<.001) subtypes showed better ovarian cancer-specific survival than those with the serous subtype. Similar results were found regarding overall survival. However, ovarian cancer-specific survival and overall survival were comparable among those with endometrioid, clear cell, and mucinous tumors.

CONCLUSIONS

Ovarian cancer remains the primary cause of death in long-term ovarian cancer survivors. Moreover, the probability of death was significantly different among those with different histological subtypes. It is important for clinicians to individualize the surveillance program for long-term ovarian cancer survivors.

Pan-metastatic cancer analysis of prognostic factors and a prognosis-based metastatic cancer classification system

We aimed to perform a pan-metastatic cancer analysis on survival and prognostic factors and to create a prognosis-based classification system. We selected distant metastasis patients from the Surveillance, Epidemiology, and End Results (SEER) database. The associations between the characteristics of the patients at admission and overall survival were determined. A prognosis-based metastatic cancer classification was established based on the identified prognostic factors. The differences in prognosis among these categories were tested. The survival rate and prognostic factors were not consistent across cancers. Three metastatic cancer categories were generated, each with different prognoses. The prognostic differences among the categories were satisfactorily validated. Different metastatic cancer types had homogeneous and heterogeneous survival rates and prognostic factors. A prognosis-based classification system for synchronous distant metastasis cancer patients at admission was created. This classification system reflects the grade of malignancy in metastatic cancers and may guide the prediction of survival and individualized treatment. Moreover, it may have important implications for the management of synchronous metastatic cancers and aid clinicians in properly allocating medical resources to metastatic patients.