This retrospective analysis aimed to assess the risk factors for recurrence in patients diagnosed with early-stage cervical cancer (≤IB1 or IIA1, FIGO 2009) undergoing robot-assisted radical hysterectomy in Spain and Portugal between 2009 and 2018. A second primary objective was to audit the oncological outcomes according to quality indicators (QI) proposed by the European Society of Gynecology Oncology (ESGO). The study population included 239 women. After a median follow-up of 51 months, recurrence occurred in 26 patients (10.9%). Independent factors for recurrence were clinical tumor size > 20 mm (hazard ratio (HR) 2.37), adenocarcinoma as histological type (HR 2.51), positive pelvic lymph nodes (HR 4.83), tumor grade 2 (HR 4.99), tumor grade 3 (HR 8.06), and having not performed sentinel lymph node biopsy (SLNB) (HR 4.08). All 5 QI selected were surpassed by our results. In patients with early-stage cervical cancer undergoing robotic radical hysterectomy, clinicians should be aware that tumor grade 2 and 3, tumor size > 20 mm, adenocarcinoma, positive pelvic nodes, and lack of performance of SLNB are risk factors for recurrence. Fulfillment of QI targets of the ESGO might be considered as an objective oncological outcome indicator supporting the minimally invasive approach for early-stage cervical cancer treatment.

In advanced ovarian cancer, developments in tumor profiling, surgical techniques, and maintenance therapies have led to increased numbers of “long-term survivors” who remain relapse-free beyond five years. These developments require identifying best practices for disease management and patient care to maximize the chances of long-term survival. To meet this need, we implemented the “Health Evidence Achieving Long Survival” (HEaLS) project, which aimed to develop guidelines for optimal management, follow-up, and patient support in advanced ovarian cancer. Through literature review and collaborative discussions, we formulated guidance for nine topics: clinical, pathological and molecular diagnosis, genetic counseling, surgery, systemic therapeutic management, oncology nursing, psycho-oncology, nutrition, physical exercise, and biopsychosocial needs. Here, we present our recommendations for managing advanced epithelial ovarian cancer focusing on integrated care pathways and multidisciplinary collaboration. These recommendations can be used by healthcare teams looking to implement coordinated strategies for maximizing survival and quality of life in ovarian cancer.

Background/Objectives: Endometrial cancer (EC) is the most common gynecologic malignancy in developed countries, with increasing incidence and limited options in advanced disease. Molecular classification has redefined risk stratification and therapeutic decision-making, particularly with the incorporation of immunotherapy. This review provides a clinically oriented overview of immunotherapy in EC across molecular subgroups and treatment settings. Methods: A narrative review was conducted using PubMed/MEDLINE, Embase, and Web of Science, focusing on clinical trials and studies with direct clinical relevance. Results: Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis have demonstrated significant benefit in EC, particularly in mismatch repair-deficient (dMMR)/microsatellite instability–high (MSI-H) tumors, where durable responses are observed. In contrast, mismatch repair-proficient (pMMR) tumors show limited sensitivity to monotherapy and require combination approaches. Recent phase III trials have established chemoimmunotherapy as a first-line standard, with greater benefit in dMMR tumors and clinically meaningful improvements in pMMR disease. In the second-line setting, PD-1 inhibitor monotherapy is standard for dMMR tumors, while lenvatinib plus pembrolizumab is a key option for pMMR disease. However, responses remain heterogeneous and are not fully explained by MMR status alone. Conclusions: Immunotherapy is a cornerstone in advanced EC management, guided by molecular classification. Key challenges include limited efficacy in pMMR tumors, lack of robust predictive biomarkers, and uncertainty in treatment sequencing. Future strategies should focus on biomarker-driven approaches and rational combinations.