Identifying safe diagnostic algorithms for sentinel lymph node mapping in high-risk endometrial cancer: The SENTIREC-endo study.

INTRODUCTION: It is unclear if sentinel node (SLN) mapping can replace pelvic- (PLD) and paraaortic lymphadenectomy (PALD) for high-risk endometrial cancer (EC). A diagnostically safe surgical algorithm, taking failed mapping cases into account, is not defined. We aimed to investigate the diagnostic accuracy of SLN mapping algorithms in women with exclusively high-risk EC. METHODS: We undertook a prospective national diagnostic cohort study of SLN mapping in women with high-risk EC from March 2017 to January 2023. The power calculation was based on the negative predictive value (NPV). Women underwent SLN mapping, PLD and PALD besides removal of suspicious and any FDG/PET-positive lymph nodes. Accuracy analyses were performed for five algorithms. RESULTS: 170/216 included women underwent SLN mapping, PLD and PALD and were included in accuracy analyses. 42/170 (24.7%) had nodal metastasis. The algorithm SLN and PLD in case of failed mapping, demonstrated a sensitivity of 86% (95% CI 74-100) and an NPV of 96% (95% CI 91-100). The sensitivity increased to 93% (95% CI 83-100) and the NPV to 98% (95% CI 94-100) if PLD was combined with removal of any PET-positive lymph nodes. Equivalent results were obtained if PLD and PALD were performed in non-mapping cases; sensitivity 93% (95% CI 83-100) and NPV 98% (95% CI 95-100). CONCLUSION: SLN-mapping is a safe staging procedure in women with high-risk EC if strictly adhering to a surgical algorithm including removal of any PET-positive lymph nodes independent of location and PLD or PLD and PALD in case of failed mapping.

The SENTIREC-endo study - Risks and benefits of a national adoption of sentinel node mapping in low and intermediate risk endometrial cancer.

OBJECTIVE: The SENTIREC-endo study aims to investigate risks and benefits of a national protocolled adoption of sentinel lymph node (SLN) mapping in women with early-stage low-grade endometrial cancer (EC) with low- (LR) and intermediate-risk (IR) of lymph node metastases. METHODS: We performed a national multicenter prospective study of SLN-mapping in women with LR and IR EC from March 2017-February 2022. Postoperative complications were classified according to Clavien-Dindo. Lymphedema was assessed as a change score and as incidence of swelling and heaviness evaluated by validated patient-reported outcome measures at baseline and three months postoperatively. RESULTS: 627 women were included in the analyses; 458 with LR- and 169 with IR EC. The SLN detection rate was 94.3% (591/627). The overall incidence of lymph node metastases was 9.3% (58/627); 4.4% (20/458) in the LR- and 22.5% (38/169) in the IR group. Ultrastaging identified 62% (36/58) of metastases. The incidence of postoperative complications was 8% (50/627) but only 0.3% (2/627) experienced an intraoperative complication associated with the SLN procedure. The lymphedema change score was below the threshold for clinical importance 4.5/100 CI: (2.9-6.0), and the incidence of swelling and heaviness was low; 5.2% and 5.8%, respectively. CONCLUSION: SLN mapping in women with LR and IR EC carries a very low risk of early lymphedema and peri- and postoperative complications. The national change in clinical practice contributed to a more correct treatment allocation for both risk groups and thus supports further international implementation of the SLN technique in early stage, low grade EC.

Specific Regions, Rather than the Entire Peritoneal Carcinosis Index, are Predictive of Complete Resection and Survival in Advanced Epithelial Ovarian Cancer.

BACKGROUND: Advanced epithelial ovarian cancer (EOC) often involves the peritoneum. Because complete resection of tumor and carcinosis is the most important prognostic factor, the peritoneal carcinosis index (PCI) has been evaluated in EOC. We hypothesize that specific PCI regions comprising the small intestine with mesentery (regions 9-12) and the hepatoduodenal ligament (region 2) are more predictive of complete resection (R = 0) and survival than the entire PCI. MATERIALS AND METHODS: We analyzed prospectively collected nationwide data from 507 patients with International Federation of Gynecology and Obstetrics stage IIIB to IVB EOC who underwent primary surgery with complete cytoreductive intent. The PCI as a predictor of incomplete resection (R > 0) was evaluated with logistic regression and receiver operating caracteristic curves. Survival analysis was performed with Kaplan-Meier curves and Cox regression. RESULTS: Median (range) PCI was 10 (0-33) in R = 0 patients and 24 (1-39) in R > 0 patients; P < 0.0001. The PCI of regions 9 to 12 (odds ratio [OR]:1.38 (1.29-1.47; 95% confidence interval [CI]) and 2 + 9 to 12 (OR: 1.31 [1.24-1.38; 95% CI]) were more predictive of residual tumor than the entire PCI (OR: 1.10 [1.08-1.12; 95% CI]). Similarly, in receiver operating characteristic curve analyses of R greater than 0 versus R = 0, the area under the curve was higher in regions 9 to 12 (78%) and regions 2 + 9 to 12 (79%) than for the total PCI (75%).Median overall survival was 56.8 months (48.3-65.4; 95% CI) after R = 0 and 26.7 months (21.4-32.0; 95% CI) after R greater than 0 (P < 0.0001). Overall survival was 53.8 months for patients with PCI less than median (14) versus 25.7 in patients with PCI greater than median.The PCI in regions 9 to 12 (hazard ratio [HR]: 1.10 [1.07-1.13; 95% CI]) and 2 + 9 to 12 (HR: 1.08 [1.06-1.11; 95% CI]) was associated with a poorer prognosis than the entire PCI (HR: 1.03 [1.02-1.04; 95% CI]). CONCLUSIONS: Selected PCI regions corresponding to the small intestine and hepatoduodenal ligament are more predictive of complete resection and survival than the entire PCI. This confirms that in the majority of the cases, an early intraoperative examination of those selected PCI regions - and not the entire PCI - will reveal whether R = 0 is achievable.

Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team.

OBJECTIVE: Proper planning of intervention and care of ovarian cancer surgery is of outmost importance and involves a wide range of personnel at the departments involved. The aim of this study is to evaluate the introduction of an ovarian surgery classification (COVA) system for facilitating multidisciplinary team (MDT) decisions. MATERIALS AND METHODS: Four hundred eighteen women diagnosed with ovarian cancers (n = 351) or borderline tumors (n = 66) were selected for primary debulking surgery from January 2008 to July 2013. At an MDT meeting, women were allocated into 3 groups named "pre-COVA" 1 to 3 classifying the expected extent of the primary surgery and need for postoperative care. On the basis of the operative procedures performed, women were allocated into 1 of the 3 corresponding COVA 1 to 3 groups. The outcome measure was the predictive value of the pre-COVA score compared with the actual COVA performed. RESULTS: The MDT meeting allocated 213 women (51%) to pre-COVA 1, 136 (33%) to pre-COVA 2, and 52 (12%) to pre-COVA 3. At the end of surgery, 168 (40%) were classified as COVA 1, 158 (38%) were classified as COVA 2, and 28 (7%) were classified as COVA 3. Traced individually, 212 (51%) patients were correctly preclassified at the MDT meeting and distributed into 110 (52%) COVA 1, 71 (52%) COVA 2, and 17 (32%) COVA 3. Analyzing the subgroup of patients with cancer, 164 (47%) were correctly preclassified. Regarding the International Federation of Gynecology and Obstetrics (FIGO) stages, the pre-COVA classification predicted the actual COVA group in 79 (49%) FIGO stages I to IIIB and in 85 (45%) FIGO stages IIIC to IV. CONCLUSIONS: The COVA classification system is a simple and useful tool in the MDT setting where specialists make treatment decisions based on advanced technology. The use of pre-COVA classification facilitates well-organized patient care-relevant procedures to be undertaken. Pre-COVA accurately predicts the final COVA in 51% classified women.

Danish Gynecological Cancer Database.

AIM OF DATABASE: The Danish Gynecological Cancer Database (DGCD) is a nationwide clinical cancer database and its aim is to monitor the treatment quality of Danish gynecological cancer patients, and to generate data for scientific purposes. DGCD also records detailed data on the diagnostic measures for gynecological cancer. STUDY POPULATION: DGCD was initiated January 1, 2005, and includes all patients treated at Danish hospitals for cancer of the ovaries, peritoneum, fallopian tubes, cervix, vulva, vagina, and uterus, including rare histological types. MAIN VARIABLES: DGCD data are organized within separate data forms as follows: clinical data, surgery, pathology, pre- and postoperative care, complications, follow-up visits, and final quality check. DGCD is linked with additional data from the Danish "Pathology Registry", the "National Patient Registry", and the "Cause of Death Registry" using the unique Danish personal identification number (CPR number). DESCRIPTIVE DATA: Data from DGCD and registers are available online in the Statistical Analysis Software portal. The DGCD forms cover almost all possible clinical variables used to describe gynecological cancer courses. The only limitation is the registration of oncological treatment data, which is incomplete for a large number of patients. CONCLUSION: The very complete collection of available data from more registries form one of the unique strengths of DGCD compared to many other clinical databases, and provides unique possibilities for validation and completeness of data. The success of the DGCD is illustrated through annual reports, high coverage, and several peer-reviewed DGCD-based publications.