Randomized controlled trials remain fundamental to evidence generation in oncology but are increasingly complex, costly, and often misaligned with real-world practice. Traditional explanatory trials, designed under ideal, controlled conditions, frequently enroll highly selected populations, limiting generalizability and underrepresenting key groups such as older adults, patients with comorbidities, and those from low- and middle-income countries. Pragmatic clinical trials offer an alternative by evaluating interventions under routine care conditions, with broader eligibility, simplified procedures, and patient-centered outcomes. To address these challenges, the Gynecologic Cancer InterGroup convened an international brainstorming meeting in May 2025 with multi-disciplinary experts, patients, and advocates to define priorities and develop a roadmap for pragmatic trials in gynecologic oncology. Key discussions emphasized embedding trial design within routine care, aligning eligibility criteria and procedures with standard practice, minimizing non-essential data collection, and prioritizing outcomes meaningful to patients, including quality of life. Innovative designs such as registry-based randomized trials, trials-within-cohorts, and cluster randomization were highlighted as feasible approaches to improve efficiency while preserving internal validity. Integration of patient-reported outcomes and real-world data was considered achievable when carefully streamlined. Major challenges identified included regulatory heterogeneity, consent complexity, data interoperability, and funding limitations, particularly in multi-national settings. Proposed solutions include simplified consent models, centralized ethics processes, hybrid funding strategies, and the responsible use of artificial intelligence to enhance patient identification, recruitment, and potential development of synthetic control arms. Patient engagement was recognized as essential to ensure relevance, feasibility, and equity. Incorporation of patient-reported outcomes was discussed as key to informing acceptance and tolerability. In summary, pragmatic trials within Gynecologic Cancer InterGroup represent a critical pathway to generate efficient, inclusive, and practice-changing evidence in gynecologic cancers across diverse health care settings.

OBJECTIVE:Previous population-based studies on ovarian cancer survival have evaluated less granular disease staging categories and histologic sub-types than are in current use, and there is a need to assess survival in the context of more contemporary treatment practices and histotype classifications. METHODS:Using flexible parametric models, we assessed the 1-, 3-, 5-, and 10-year net survival and excess mortality hazards of 54,267 incident invasive ovarian cancer cases by stage and histology and 9478 borderline cases diagnosed between January 1, 2010 and December 31, 2021 recorded in Germany. RESULTS:Net survival differed markedly by stage, with consistently favorable long-term survival for early-stage (I to II) and poor outcomes for advanced-stage (III to IV) disease across histotypes. Although most stage I tumors showed high 10-year net survival (≥ 77%), carcinosarcomas represented a notable exception. Net survival declined with advancing stage, with 10-year estimates ranging from 46% to 76% for stage II, 18% to 55% for stage III, and poor 5-year survival for stage IV tumors (15% to 41%). Considering patterns by time since diagnosis, the excess mortality hazard was the highest across all histotype-stage groups during the first 3 years with variability suggestive of histotype-specific treatment resistance and disease recurrence. The influence of stage decreased over the follow-up, with the largest impact mostly observed during the first year after diagnosis. Net survival for borderline tumors was high (10-year survival = 92.9%). CONCLUSIONS:Net survival was favorable for patients with early-stage disease. Variability was observed across histotypes by stage. The early post-diagnosis period is a critical window for excess mortality, and the development of histotype-specific treatments is needed.

Intratumor heterogeneity presents a major challenge in precision oncology for endometrial cancer (EC). Circulating tumor DNA (ctDNA) offers a minimally invasive method to monitor tumor evolution and therapeutic resistance. In this retrospective study, we evaluated a tumor-agnostic NGS panel to detect and track ctDNA in 18 EC patients and directly compared its performance with a tumor-informed ddPCR approach. ctDNA was detected by NGS in over 60% of plasma samples, while ddPCR showed higher positivity rates in paired samples (71.9% vs 62.5%), with overall concordance of 65.7% and fair agreement (Cohen's kappa = 0.23). The cfDNA-NGS panel identified a broad spectrum of alterations, including relapse-specific mutations indicative of clonal evolution, but showed lower sensitivity for low-frequency variants compared with ddPCR. Discordant cases, including false-negative results in both approaches, highlight the impact of assay sensitivity, target selection, and biological factors on ctDNA detection. ctDNA dynamics correlated with disease progression and treatment response, although detection was limited in cases with brain metastases. These findings support the utility of tumor-agnostic ctDNA monitoring in advanced EC and highlight the importance of assay quality and careful interpretation to address limitations such as clonal hematopoiesis and technical sensitivity.

BACKGROUND AND PURPOSE:The introduction of immune checkpoint inhibitors (ICIs) into the treatment of patients with metastatic or recurrent cervical cancer has been shown to significantly prolong survival. In this study, we examined the clinical outcomes and tolerability of treatment with ICIs in patients with metastatic or recurrent cervical cancer in a real-world setting in Norway. Patient/material and methods: This retrospective cohort study included patients treated with an ICI in combination with chemotherapy or as single agent at Oslo University Hospital between 2016 and 2024. The primary oncological endpoint was progression-free survival (PFS). Secondary endpoints include overall survival (OS) as well as tolerability. RESULTS:We included 57 patients with a median age of 53 years and a median follow-up of 15.2 months. Thirty-five patients were treated with an ICI in combination with chemotherapy (cohort 1), and or an ICI alone (n = 22) (cohort 2). Forty-six patients (81%) were treated for recurrent disease. In cohort 1, the median PFS was 12.4 months (95% CI: 9.0-15.7), and the median OS was 27.5 months (95% CI: 18.0-37.1). In cohort 2, the median PFS was 3.7 months (95% CI: 2.4-5.0), and the median OS was 9.3 months (95% CI: 4.3-14.4). Nine patients (16%) discontinued treatment due to toxicity. INTERPRETATION:Our real-world data on the use of ICIs alone or in combination showed antitumour efficacy comparable to that reported in clinical studies in patients with advanced or recurrent cervical cancer. Our discontinuation rate highlights that toxicity management and mitigation are paramount when novel drugs are introduced in clinical algorithms.

OBJECTIVE:Growing evidence suggests potential ethnic and geographical variations in chemotherapy efficacy. The CA125 ELIMination rate constant K score is a pragmatic and reproducible indicator of tumor chemosensitivity in newly diagnosed ovarian cancer. We compared ELIMination rate constant K distributions and prognostic performances between patients enrolled in Japanese and Western trials who had stage III/IV serous ovarian cancer from the Gynecologic Cancer InterGroup individual-patient-data Meta-Analysis in OVarian cancer. METHODS:The ELIMination rate constant K values were previously estimated for 5884 women receiving first-line chemotherapy for ovarian cancer. Data from 246 women enrolled in the Japanese JGOG-3016 trial were compared to 2561 patients from Western trials. ELIMination rate constant K was analyzed as a binary variable (favorable ≥1.0 vs unfavorable <1.0). Prognostic value for progression-free survival and overall survival was assessed using univariable and multi-variable models. A standardization cut-off specific to patients enrolled in the Japanese trial was explored using maximally selected rank statistics. RESULTS:KELIM was significantly higher in patients enrolled in the Japanese trial (median 0.071 day-1 vs 0.056 day-1; p <.0001). Using the standard cut-off, favorable ELIMination rate constant K was independently associated with improved progression-free survival (hazard ratio 0.59, 95% confidence interval 0.43 to 0.83) and overall survival (hazard ratio 0.53, 95% confidence interval 0.36 to 0.79) in patients from the Japanese trial. Applying the exploratory cut-off of 0.07 day-1 strengthened prognostic discrimination (progression-free survival: hazard ratio 0.35, 95% confidence interval 0.25 to 0.49, p <.0001; overall survival: hazard ratio 0.40, 95% confidence interval 0.26 to 0.61, p <.0001). CONCLUSIONS:Potential higher ELIMination rate constant K-assessed chemosensitivity is suggested in patients from Japan with advanced serous ovarian cancer, warranting further prospective validation and investigation into underlying biological and environmental determinants and implications for personalized therapeutic strategies.

Deep learning is expected to aid pathologists in tasks such as tumour segmentation. We developed a general tumour segmentation model for histopathological images and examined its performance in different cancer types. The model was developed using over 20,000 whole-slide images from over 4000 patients with colorectal, endometrial, lung, or prostate carcinoma. Performance was validated in pre-planned analyses on external cohorts with over 3000 patients across six cancer types. Exploratory analyses included over 1500 additional patients from The Cancer Genome Atlas. Average Dice coefficient was over 80% in all validation cohorts with en bloc resection specimens and in The Cancer Genome Atlas cohorts. No performance loss was observed when comparing the general model with single-cancer models specialised in cancer types from the development set. In conclusion, extensive and rigorous evaluations demonstrate that generic tumour segmentation by a single model is possible across cancer types, patient populations, sample preparations and slide scanners.

Mitotic figure counting is an established measure of cell proliferation that is included in grading systems. We developed a deep learning method for mitotic figure counting and evaluated its prognostic impact in multiple external validation datasets. The deep learning method was trained in whole slide images of tissue sections stained with haematoxylin and eosin from a publicly available breast cancer dataset where mitotic figures have been annotated by expert pathologists. The final model was externally validated according to a protocol with predefined analyses of 14 571 patient samples from 13 patient cohorts from seven different cancer types. The predefined primary analysis was univariable Cox survival analysis of the number of mitotic figures detected per mm 2 . Automatic mitotic figure counting correlated well with known proliferation rates, and patients with more mitotic figures per mm 2 had significantly worse patient outcome in all the studied cancer types except colorectal cancer. This study demonstrates the practical potential of automated, deep learning‐based mitotic figure counting, both by automating pathology work and by suggesting expanded use in more cancer types, such as prostate cancer.

OBJECTIVE:Endometrial carcinoma is molecularly classified into sub-types with distinct prognoses. The no specific molecular profile sub-group is prognostically heterogeneous. This study evaluates the prognostic significance of ER (estrogen receptor) and L1CAM (L1 cell adhesion molecule) expression in no specific molecular profile tumors individually, in combination with tumor grade, and as a combined biomarker. METHODS:Immunohistochemistry was used to assess expression of ER and L1CAM in tumors from patients with endometrial carcinoma referred to Oslo University Hospital (2006-2017). ER and L1CAM expression were grouped as negative (<10%) or positive (≥10%). Survival analyses were performed using Cox regression with cancer-specific survival as the end point. RESULTS:In this study of 465 no specific molecular profile patients, ER negativity (78/446, 17.5%) and L1CAM positivity (76/454, 14.5%) were positively correlated with adverse clinicopathologic features, particularly non-endometrioid histology. Both markers, individually and in combination, were associated with shorter cancer-specific survival, especially in FIGO (International Federation of Gynecology and Obstetrics) stage I (2009) patients (n = 360). Combining ER and/or L1CAM with tumor grade (grade 1-2 vs grade 3/non-endometrioid) increased the hazard ratio in multi-variable analyses of cancer-specific survival, with hazard ratios of 10.3 (95% confidence interval [CI] 3.43 to 31.14) for ER-negative and/or high grade, 9.43 (95% CI 3.17 to 28.00) for L1CAM-positive and/or high grade, and 15.08 (95% CI 4.13 to 55.14) for ER-negative and/or L1CAM-positive and/or high grade, compared with their corresponding low-risk groups. Estimated 5-year cancer-specific survival rates among FIGO stage I patients were 98.5% for ER-positive/low grade, 98.6% for L1CAM-negative/low grade, and 99.2% for ER-positive/L1CAM-negative/low grade, and 80.5%, 79.5%, and 82.6% for the corresponding high-risk groups. CONCLUSIONS:ER and L1CAM appear to have comparable prognostic value in no specific molecular profile endometrial cancer, and their combination with tumor grade enhances risk stratification. A combined marker including ER, L1CAM, and grade may improve risk stratification beyond either pair of markers and may be used to tailor treatment.

Background and purpose: Molecular profiling guides cancer treatment, by identifying actionable genomic alterations. The IMPRESS-Norway trial (NCT04817956) is a nation-wide precision medicine trial evaluating the efficacy of approved cancer drugs on a novel indication in patients with advanced cancers harbouring potentially actionable alterations. Trametinib, a selective MEK1/2 inhibitor targeting the Mitogen-Activated Protein Kinase (MAPK) signalling pathway, is approved for BRAF V600 mutant melanoma but may also show activity in tumours with other alterations. This sub-study aimed to assess the efficacy of trametinib monotherapy across tumour types with alterations activating the MAPK signalling pathway. Patient/material and methods: In the IMPRESS-Norway trial patients are screened with the TruSight Oncology 500 panel or circulating tumour DNA profiling. Eligible patients are offered biomarker matched targeted therapies. In this subgroup analysis, we identified patients treated with trametinib monotherapy. Primary endpoints were disease control rate (DCR) after 16 weeks and safety. Secondary endpoints included progression-free survival (PFS) and overall survival (OS). Results: DCR after 16 weeks of treatment was 39% in 52 response evaluable patients, with four patients (8%) experiencing partial response, and 16 (31%) stable disease. Responses were seen in tumours harbouring BRAF fusions, GNA11, GNAQ, KRAS, NF1, and NRAS alterations, most frequently in low-grade serous ovarian cancer, central nervous system tumours, and uveal melanoma. Forty-eight percent of patients experienced treatment-related adverse events, including two treatment related deaths. Median PFS and OS were 4 and 9 months, respectively. Interpretation: Trametinib monotherapy achieved a 39% DCR in patients lacking standard options, supporting further studies to confirm efficacy and identify predictive biomarkers for treatment response.

BACKGROUND:Pelvic exenteration (PE) is a potentially curative but highly morbid treatment for recurrent cervical cancer. Evidence on long-term oncologic outcomes and survivorship experiences remain limited. METHODS:This mixed-methods study included 55 patients treated with PE for recurring cervical cancer at Oslo University Hospital between 1995 and 2020. Oncological outcomes were analyzed retrospectively. A subgroup of ten long-term, recurrence-free survivors underwent clinical examination, completed validated patient-reported outcome measures, and participated in semi-structured qualitative interviews. Reflexive thematic analysis was applied to interview data. RESULTS:Ninety-day major (grade ≥ 3) complications occurred in 53% of patients; 4% died postoperatively. After median follow-up of 14 years, five-year overall and cancer-specific survival were 46% and 52%, respectively. An interval > 12 months between primary chemoradiation and PE was independently associated with improved survival (HR 0.38, 95% CI 0.16-0.87). Among survivors (median 9 years post-PE, range 5-18), quantitative HRQoL showed generally preserved global and functional scores, though social functioning, diarrhea, and financial difficulties reached clinical relevance. Anxiety and depression levels were low overall. In contrast, qualitative findings revealed substantial and persistent physical, practical, and relational challenges. Ostomies imposed significant social and logistical burdens, fatigue and pain constrained daily life, and most participants reported permanent loss of sexual function and altered body image. Despite these sequelae, nearly all participants considered the surgery worthwhile. CONCLUSIONS:PE offers meaningful long-term survival for selected patients, particularly with longer recurrence-free intervals. Although standardized measures suggest acceptable long-term HRQoL, qualitative data demonstrate enduring physical and psychosocial burdens, underscoring the importance of tailored counselling and multidisciplinary long-term follow-up.

( Acta Obstet Gynecol Scand . 2024;103(4):669–683. doi:10.1111/aogs.14677) Pregnancy-related cancer, referred to as PAC, is cancer that is detected either during pregnancy or within 1 year after giving birth, with a frequency of around 1 in 1000 births. Diagnosing and treating cancer while pregnant is difficult because of the dangers it can pose to both the mother and the unborn baby, with limited options based on when the cancer is detected in the pregnancy. Cancers discovered after giving birth are affected by changes in the body from pregnancy. Still, they are easier to treat, and delays in diagnosis during pregnancy might lead to postpartum cases. Therefore, a thorough understanding of PAC necessitates detailed information on pregnant and new mothers.