Ovarian cancer (OC) is a common reason for mortality among women. Deep learning has recently proven better performance in predicting OC stages and subtypes. However, most of the state-of-the-art deep learning models employ single modality data, which may afford low-level performance due to insufficient representation of important OC characteristics. Furthermore, these deep learning models still lack to the optimization of the model construction, which requires high computational cost to train and deploy them. In this work, a hybrid evolutionary deep learning model, using multi-modal data, is proposed. The established multi-modal fusion framework amalgamates gene modality alongside with histopathological image modality. Based on the different states and forms of each modality, we set up deep feature extraction network, respectively. This includes a predictive antlion-optimized long-short-term-memory model to process gene longitudinal data. Another predictive antlion-optimized convolutional neural network model is included to process histopathology images. The topology of each customized feature network is automatically set by the antlion optimization algorithm to make it realize better performance. After that the output from the two improved networks is fused based upon weighted linear aggregation. The deep fused features are finally used to predict OC stage. A number of assessment indicators was used to compare the proposed model to other nine multi-modal fusion models constructed using distinct evolutionary algorithms. This was conducted using a benchmark for OC and two benchmarks for breast and lung cancers. The results reveal that the proposed model is more precise and accurate in diagnosing OC and the other cancers.

Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. National Institute for Health and Care Research.

Ovarian cancer poses a significant and growing burden, particularly in low- and middle-income countries (LMICs) where incidence and mortality are projected to increase by over 50 % by 2050. However, there is a critical lack of qualitative data on the challenges and opportunities for improvement in treatment and care for women with ovarian cancer in these regions. The aim of this research is to investigate clinicians' perspectives on the matter in 24 LMICs. As part of the multi-country observational Every Woman Study™ (EWS), semi-structured interviews were conducted with clinicians between June 2022 and June 2023. The interview guide was developed by the EWS LMIC Oversight Committee, including patients, clinicians and data specialists. Relational content and inductive thematic analyses were employed and categories synthesized using the World Health Organization's six building blocks of the Health Systems Framework. 24 clinicians (54 % female; 79 % gynaecologic oncologists, 8 % gynaecologists, 8 % clinical oncologists not specializing in gynaecological cancers, and 4 % clinical oncologists specializing in gynaecological cancers; 42 % from Africa, 29 % from Asia, 29 % from Latin America) participated. Six dominant themes were identified: "Poor Ovarian Cancer Data'', "Inequity in Access to Treatment", "In-Country Inequities in Access to Care", "Role of Cultural Norms on Women's Health", "Increased Engagement of Men in Ovarian Cancer Control", and "Advocacy and Education for Empowering Women". Content analysis revealed system-level challenges such as delayed drug payments, lack of population-based cancer data, and limited imaging facilities. Patient-level challenges included disparities in access to specialists, limited medication affordability, poor symptom recognition, and reliance on alternative treatments. This study reveals the complexity of ovarian cancer treatment and care in LMICs and the need to mitigate disparities in these regions, underscoring the need for patient-centred, context specific and intersectoral strategies to be considered in cancer planning to improve ovarian cancer care quality and equity in LMICs.

For women achieving clinical remission after the completion of initial treatment for epithelial ovarian cancer, 80% with advanced-stage disease will develop recurrence. However, the standard treatment of women with recurrent platinum-sensitive diseases remains poorly defined. Secondary (SCS), tertiary (TCS) or quaternary (QCS) cytoreduction surgery for recurrence has been suggested to be associated with increased overall survival (OS). We searched five databases for studies reporting death rate, OS, cytoreduction rates, post-operative morbidity/mortality and diagnostic models predicting complete cytoreduction in a platinum-sensitive disease recurrence setting. Death rates calculated from raw data were pooled based on a random-effects model. Meta-regression/linear regression was performed to explore the role of complete or optimal cytoreduction as a moderator. Pooled death rates were 45%, 51%, 66% for SCS, TCS and QCS, respectively. Median OS for optimal cytoreduction ranged from 16–91, 24–99 and 39–135 months for SCS, TCS and QCS, respectively. Every 10% increase in complete cytoreduction rates at SCS corresponds to a 7% increase in median OS. Complete cytoreduction rates ranged from 9–100%, 35–90% and 33–100% for SCS, TCS and QCS, respectively. Major post-operative thirty-day morbidity was reported to range from 0–47%, 13–33% and 15–29% for SCS, TCS and QCS, respectively. Thirty-day post-operative mortality was 0–6%, 0–3% and 0–2% for SCS, TCS and QCS, respectively. There were two externally validated diagnostic models predicting complete cytoreduction at SCS, but none for TCS and QCS. In conclusion, our data confirm that maximal effort higher order cytoreductive surgery resulting in complete cytoreduction can improve survival.

Introduction: Pleomorphic adenoma (PA) is the most common benign salivary gland tumor. When neglected on some occasions, its size and weight can enormously augment. Case presentation: We report a case of a giant submandibular pleomorphic adenoma in a 75 years old female patient which measured 34 × 26 × 20 cm and weighed 8.1 kg. Conclusion: Neglecting such tumors without treatment, can cause severe facial disfigurement and can even hinder the airway. Highlights:

Background: Little is known about characteristics of young patients with gastric carcinoma (GC) in Egypt. Aim: The purpose of this study was to define the clinicopathological features and survival of young GC patients in our population. Materials and Methods: We retrospectively analyzed data of 197 GC patients who were treated at our institution from 2011 to 2016. The clinicopathological characteristics and survival were compared between 61 young (≤45 years) and 136 older (>45 years) GC patients. We also studied variables impacting survival of younger patients. Results: The proportion of females, positive family history, and poorly differentiated tumors were significantly higher in young patients. Younger group showed significantly longer interval between symptoms and diagnosis (all P < 0.05). The mean overall survival (OS) of young patients was lower compared to older patients (10.7 vs. 18.7 months, respectively; P=0.06). Multivariate analyses revealed that distant metastasis and CA19-9 were independent factors for reduced survival in younger patients. Conclusion: We conclude that clinico-pathological characteristics of GC are different between young and old patients. Aggressive tumor biology and a significant diagnostic delay may have contributed to worse survival in younger patients.