Muscle invasive bladder cancer in Upper Egypt: the shift in risk factors and tumor characteristics

<p>Abstract</p> <p>Background</p> <p>In Egypt, where bilharziasis is endemic, bladder cancer is the commonest cancer in males and the 2^ndin females; squamous cell carcinoma (SCC) is the commonest type found, with a peculiar mode of presentation. The aim of this study is to identify and rank the risk factors of muscle invasive bladder cancer (MIBC) in Upper Egypt and describe its specific criteria of presentation and histopathology.</p> <p>Methods</p> <p>This is an analytical, hospital based, case controlled study conducted in south Egypt cancer institute through comparing MIBC cases (n = 130) with age, sex and residence matched controls (n = 260) for the presence of risk factors of MIBC. Data was collected by personal interview using a well designed questionnaire. Patients' records were reviewed for histopathology and Radiologic findings.</p> <p>Results</p> <p>The risk factors of MIBC were positive family history [Adjusted odds ratio (AOR) = 7.7], exposure to pesticides [AOR = 6.2], bladder stones [AOR = 5], consanguinity [AOR = 3.9], recurrent cystitis [AOR = 3.1], bilharziasis [odds ratio (OR) = 5.8] and smoking [OR = 5.3]. SCC represented 67.6% of cases with burning micturition being the presenting symptom in 73.8%.</p> <p>Conclusion</p> <p>MIBC in Upper Egypt is usually of the SCC type (although its percentage is decreasing), occurs at a younger age and presents with burning micturition rather than hematuria. Unlike the common belief, positive family history, parents' consanguinity, exposure to pesticides and chronic cystitis seem to play now more important roles than bilharziasis and smoking in the development of this disease in this area.</p

The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

Enhancing the K-Means Algorithm through a Genetic Algorithm Based on Survey and Social Media Tourism Objectives for Tourism Path Recommendations

Social media platforms play a vital role in determining valuable tourist objectives, which greatly aids in optimizing tourist path planning. As data classification and analysis methods have advanced, machine learning (ML) algorithms such as the k-means algorithm have emerged as powerful tools for sorting through data collected from social media platforms. However, traditional k-means algorithms have drawbacks, including challenges in determining initial seed values. This paper presents a novel approach to enhance the k-means algorithm based on survey and social media tourism data for tourism path recommendations. The main contribution of this paper is enhancing the traditional k-means algorithm by employing the genetic algorithm (GA) to determine the number of clusters (k), select the initial seeds, and recommend the best tourism path based on social media tourism data. The GA enhances the k-means algorithm by using a binary string to represent initial centers and to apply GA operators. To assess its effectiveness, we applied this approach to recommend the optimal tourism path in the Red Sea State, Sudan. The results clearly indicate the superiority of our approach, with an algorithm optimization time of 0.01 s. In contrast, traditional k-means and hierarchical cluster algorithms required 0.27 and 0.7 s, respectively