Impact of age on clinicopathological features and survival of epithelial ovarian neoplasms in reproductive age

Oncological safety of fertility preservation treatment in ovarian cancer: A Spanish multicenter study

OBJECTIVE

To assess the safety of fertility-sparing treatments for early-stage ovarian cancer in women younger than 40 years old.

METHODS

We performed a retrospective multicenter study including women aged 18-40 years diagnosed with early-stage (FIGO I-II) ovarian cancer in 55 Spanish hospitals, from January 2010 to December 2019. Benign and borderline tumors were excluded, as well as advanced stages (FIGO III-IV). All perioperative characteristics and follow-up data were collected and analyzed. Standard staging surgery (SSS) was compared with fertility-sparing surgery (FSS) in terms of oncological outcomes.

RESULTS

In all, 366 women were included; 327 (89.3%) were stage I. Among all patients, 216 (59%) underwent SSS and 150 (41%) FSS. Up to 208 (56.8%) patients did not have children, but only 12 (3.2%) had oocyte preservation before treatment. Patients in the FSS group compared with the SSS group showed a non-significant difference in recurrences (8% vs. 9.3%, respectively; P < 0.711) and deaths (1.3% vs. 4.8%, respectively; P = 0.211) during the follow-up. No significant differences were found between epithelial and non-epithelial ovarian cancer both in recurrences (7.1% vs. 8.8%, respectively; P = 0.771) and in deaths (1.4% vs. 1.3%, respectively; P = 1) among patients who underwent FSS.

CONCLUSION

FSS seems a safe option for treatment of early-stage ovarian cancer in patients who want to preserve fertility, either for epithelial and non-epithelial histology.

A novel clinical nomogram for predicting cancer-specific survival in patients with non-serous epithelial ovarian cancer: A real-world analysis based on the Surveillance, Epidemiology, and End Results database and external validation in a tertiary center

BACKGROUND

Currently, there is a lack of prognostic evaluation methods for non-serous epithelial ovarian cancer (EOC).

METHOD

We collected patients with non-serous EOC diagnosed between 2010 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database into a training cohort (n = 2078) and an internal validation cohort (n = 891). Meanwhile, patients meeting the criteria were screened from the Fujian Provincial Maternal and Child Health Hospital from 2013 to 2022 as an external validation cohort (n = 56). Univariate and multivariable logistic regression were used to determine the independent prognostic factors of cancer-specific survival (CSS) to construct the nomogram. The nomogram was validated by the concordance index (C-index), receiver operating characteristics (ROC) curve and calibration curves.

RESULT

Age, laterality, preoperative CA125 status, histologic type, tumor grade, AJCC stage, surgery lesion, number of lymph nodes examined, residual lesion size, and bone metastasis were identified as independent prognostic factors to construct the nomogram. The nomogram showed better predictive ability than FIGO stage through internal and external cohorts validation. The C-index of the nomogram in the training cohort, validation cohort, and external validation cohort were 0.831, 0.835 and 0.944 higher than those of the Federation International of Gynecology and Obstetric (FIGO) stage, P<0.05. The Area Under Curve (AUC) values results indicated great clinical usefulness of the nomogram. The calibration curve indicated good agreement between the nomogram prediction and actual survival.

CONCLUSION

We developed a nomogram with high predictive accuracy to predict survival in patients with non-serous EOC.

A Nomogram Based on SEER Database for Predicting Prognosis in Patients with Mucinous Ovarian Cancer: A Real-World Study

Purpose

Mucinous ovarian cancer (MOC) is a rare histological type of EOC. In order to guide the clinical diagnosis and management of MOC patients, we constructed and verified a nomogram for the estimation of overall survival in patients with MOC.

Patients and Methods

We collected 494 patients with MOC diagnosed from 2010 to 2015 in SEER database, and the following main inclusion criteria were used: (1) patients whose MOC was confirmed by pathology; (2) patients without a history of primary other cancer. Subsequently, we performed randomized grouping (6:4) and Cox hazard regression analysis in the training group. Subsequently, the nomogram was established. A variety of indicators were used to validate the prognosis value of nomogram, including the C-index, area under the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA). Moreover, Kaplan–Meier analysis was used to compare the survival results among different risk subgroups.

Results

Cox hazard regression analysis revealed that age, grade, FIGO stage and log odds of positive lymph nodes stage were independent risk factors for patients with MOC. In the training group, the C-index of the nomogram was 0.827 (95% CI: 0.791–0.863) and the areas under the curve (AUC) predicting the 1-, 3- and 5-year survival rate were 0.853 (95% CI: 0.791–0.915), 0.886 (95% CI: 0.852–0.920) and 0.815 (95% CI: 0.766–0.864), respectively. The calibration curve revealed that the nomogram of the 1-, 3- and 5-year survival rate was consistent with the actual fact. Patients with high risk had a poorer prognosis than those with low risk (P < 0.001). DCA revealed that the nomogram had the best clinical value than other classical prognostic markers. Similarly, nomogram had excellent prognostic ability in the testing group.

Conclusion

The nomogram was constructed to predict overall survival in patients with MOC, which had the significance for clinical evaluation.

Develop a nomogram to predict overall survival of patients with borderline ovarian tumors

BACKGROUND

The prognosis of borderline ovarian tumors (BOTs) has been the concern of clinicians and patients. It is urgent to develop a model to predict the survival of patients with BOTs.

AIM

To construct a nomogram to predict the likelihood of overall survival (OS) in patients with BOTs.

METHODS

A total of 192 patients with histologically verified BOTs and 374 patients with epithelial ovarian cancer (EOC) were retrospectively investigated for clinical characteristics and survival outcomes. A 1:1 propensity score matching (PSM) analysis was performed to eliminate selection bias. Survival was analyzed by using the log-rank test and the restricted mean survival time (RMST). Next, univariate and multivariate Cox regression analyses were used to identify meaningful independent prognostic factors. In addition, a nomogram model was developed to predict the 1-, 3-, and 5-year overall survival of patients with BOTs. The predictive performance of the model was assessed by using the concordance index (C-index), calibration curves, and decision curve analysis (DCA).

RESULTS

For clinical data, there was no significant difference in body mass index, preoperative CA199 concentration, or tumor localization between the BOTs group and EOC group. Women with BOTs were significantly younger than those with EOC. There was a significant difference in menopausal status, parity, preoperative serum CA125 concentration, Federation International of gynecology and obstetrics (FIGO) stage, and whether patients accepted postoperative adjuvant therapy between the BOT and EOC group. After PSM, patients with BOTs had better overall survival than patients with EOC (P value = 0.0067); more importantly, the 5-year RMST of BOTs was longer than that of EOC (P value = 0.0002, 95%CI -1.137 to -0.263). Multivariate Cox regression analysis showed that diagnosed age and surgical type were independent risk factors for BOT patient OS (P value < 0.05). A nomogram was developed based on diagnosed age, preoperative serum CA125 and CA199 Levels, surgical type, FIGO stage, and tumor size. Moreover, the c-index (0.959, 95% confidence interval 0.8708–1.0472), calibration plot of 1-, 3-, and 5-year OS, and decision curve analysis indicated the accurate predictive ability of this model.

CONCLUSION

Patients with BOTs had a better prognosis than patients with EOC. The nomogram we constructed might be helpful for clinicians in personalized treatment planning and patient counseling.

Fertility-Sparing Surgery for Ovarian Cancer

(1) Background: although most patients with epithelial ovarian cancer (EOC) undergo radical surgery, patients with early-stage disease, borderline ovarian tumor (BOT) or a non-epithelial tumor could be offered fertility-sparing surgery (FSS) depending on histologic subtypes and prognostic factors. (2) Methods: we conducted a systematic review to assess the safety and fertility outcomes of FSS in the treatment of ovarian cancer. We queried the MEDLINE, PubMed, Cochrane Library, and Cochrane (“Cochrane Reviews”) databases for articles published in English or French between 1985 and 15 January 2021. (3) Results: for patients with BOT, FSS should be offered to young women with a desire to conceive, even if peritoneal implants are discovered at the time of initial surgery. Women with mucinous BOT should undergo initial unilateral salpingo-oophorectomy, whereas cystectomy is an acceptable option for women with serous BOT. Assisted reproductive technology (ART) can be initiated in patients with stage I BOT if infertility persists after surgery. For patients with EOC, FSS should only be considered after staging for women with stage IA grade 1 (and probably 2, or low-grade in the current classification) serous, mucinous or endometrioid tumors. FSS could also be offered to patients with stage IC grade 1 (or low-grade) disease. For women with serous, mucinous or endometrioid high-grade stage IA or low-grade stage IC1 or IC2 EOC, bilateral salpingo-oophorectomy and uterine conservation could be offered to allow pregnancy by egg donation. Finally, FSS has a large role to play in patients with non- epithelial ovarian cancer, and particularly women with malignant ovarian germ cell tumors.

A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer

Background: Ovarian cancer is a common gynecological malignancy, most of which is epithelial ovarian cancer (EOC). Advanced EOC is linked with a higher incidence of premature death. To date, no effective prognostic tools are available to evaluate the possibility of early death in patients with advanced EOC.

Methods: Advanced (FIGO stage III and IV) EOC patients who were enrolled in the Surveillance, Epidemiology, and End Results database between 2004 and 2015 were regarded as subjects and studied. We aimed to construct a nomogram that can deliver early death prognosis in patients with advanced EOC by identifying crucial independent factors using univariate and multivariate logistic regression analyses to help deliver accurate prognoses.

Results: In total, 13,403 patients with advanced EOC were included in this study. Three hundred ninety-seven out of a total of 9,379 FIGO stage III patients died early. There were 4,024 patients with FIGO stage IV, 414 of whom died early. Nomograms based on independent prognostic factors have the satisfactory predictive capability and clinical pragmatism. The internal validation feature of the nomogram demonstrated a high level of accuracy of the predicted death.

Conclusions: By analyzing data from a large cohort, a clinically convenient nomogram was established to predict premature death in advanced EOC. This tool can aid clinicians in screening patients who are at higher risk for tailoring treatment plans.

Fertility considerations prior to conservative management of gynecologic cancers

Fertility-sparing management of early-stage gynecologic cancers is becoming more prevalent as increasing evidence demonstrates acceptable oncologic and reproductive outcomes in appropriately selected patients. However, in the absence of randomized controlled trials, most of the commonly used treatment algorithms are based only on observational studies. As women are increasingly postponing childbearing, the need for evidence-based guidance on the optimal selection of appropriate candidates for fertility-sparing therapies is paramount. It is imperative to seriously consider the fertility potential of a given individual prior to making major oncologic treatment decisions that may deviate from the accepted standard of care. It is a disservice to patients to undergo a fertility-sparing procedure in hopes of ultimately achieving a live birth, only to determine later they have poor baseline fertility potential or other substantial barriers to conception including excess financial toxicity. Many women with oncologic diagnoses are of advanced maternal age and their obstetric and neonatal risks must be considered. In the era of advanced assisted reproductive technologies, patients should be provided realistic expectations regarding success rates while understanding the potential oncologic perils. A multidisciplinary approach to the conservative treatment of early-stage gynecologic cancers with early referral to reproductive specialists as well as maternal-fetal medicine specialists is warranted. In this review, we discuss the recommended fertility evaluation for patients with newly diagnosed, early-stage gynecologic cancers who are considering fertility-sparing management.