Introduction: Smoking remains a leading cause of preventable diseases worldwide, including cancer, heart disease, and respiratory disorders. In Saudi Arabia, the prevalence of smoking has been increasing, particularly among men and adolescents. However, limited research has focused on the...

(1) Background: This study aims to identify the sociodemographic, behavioural, and systemic predictors of colorectal cancer (CRC) screening among primary healthcare attendees in Riyadh, Saudi Arabia, to inform targeted interventions and policy strategies. (2) Methods: This cross-sectional study was conducted between March and July 2023 across 48 randomly selected primary healthcare centers in Riyadh, Saudi Arabia. The target population for this study was adults aged 18 and above attending primary healthcare centers in Riyadh. Multi-stage random sampling was used to recruit participants. Multivariate logistic regression was performed to identify independent predictors of CRC screening. (3) Results: CRC screening uptake was found to be only 4.2%. Age was a significant predictor, with individuals aged 50–75 years (adjusted odds ratio [AOR]: 1.90, 95% confidence interval [CI]: 1.50–2.42) and those aged 75 years or older (AOR: 1.37, 95% CI: 1.01–1.87) being more likely to undergo screening compared to younger individuals. Insurance coverage strongly influenced screening behaviour (AOR: 1.64, 95% CI: 1.37–1.96). Smokers were nearly four times more likely to participate in screening than non-smokers (AOR: 3.87, 95% CI: 3.21–4.69), and physical activity was positively associated with screening (AOR: 1.43, 95% CI: 1.11–1.82). (4) Conclusions: CRC screening uptake in Riyadh is critically low, highlighting the need for targeted public health interventions. Key predictors such as age, insurance coverage, smoking, and physical activity underscore the importance of addressing sociodemographic disparities and promoting health awareness. The findings emphasize the need for culturally tailored educational campaigns, improved healthcare access, and enhanced screening programs to increase uptake.

Background/Objectives: Despite a link between self-perception of health and morbidity and mortality, data are scarce on factors that can predict one’s health perception, particularly in nations like Saudi Arabia. We conducted a needs assessment to evaluate health perception and identify sociodemographic, behavioural, and comorbidity-related factors influencing health perception among Saudi individuals. Methods: We conducted a cross-sectional survey utilizing an electronic questionnaire that was distributed to 14,239 people who visited primary healthcare centers in Riyadh, Saudi Arabia. We used multiple logistic regression to identify predictors of good health. Data was analyzed using SPSS software. Results: About one-third of the individuals (33.7%) perceived to have excellent health and 35.6% perceived to have very good health. Only 2.1% of the study participants perceived to have poor health. Compared to participants younger than 50 years, those aged 50–75 years were 10% less likely to perceive their health as good (AOR: 0.89, 95% CI: 0.82, 0.97). Males were 1.09 times more likely to perceive their health as good than females (AOR: 1.09, 95% CI: 1.01, 1.18). Smokers were 74% less likely than non-smokers to perceive their health as good (AOR: 0.26; 95% CI: 0.24, 0.29). Obese individuals were 20% less likely to perceive their health in good condition than non-obese individuals (AOR: 0.80; 95% CI: 0.65, 0.98) Individuals with heart disease were about 50% less likely to perceive their health as good condition than those without heart disease (AOR: 0.52; 95% CI: 0.40, 0.76). Conclusions: Despite the high frequency of risk factors, we discovered that Saudis perceive their health to be good on average. However, an independent association between older age, females, smoking, obesity, and heart disease with poor health calls for future epidemiological studies incorporating qualitative dimensions to explore why these individuals with specific risk profiles perceive their health as worse than others.

Prostate cancer stands as a significant global health concern, representing a leading cause of cancer-related morbidity and mortality among men [1]. In 2020, an estimated 1.4 million new cases and ...

Background: Renal disease represents a significant and growing public health concern globally and within Saudi Arabia. Despite the increasing burden of noncommunicable diseases, population-based data on the prevalence and determinants of renal disease in Saudi Arabia remain limited. Understanding epidemiology, including prevalence and associated risk factors of renal disease in the context of Saudi Arabia, is essential for designing preventive and early detection strategies. Objective: This study aims to estimate the prevalence of renal disease and to identify sociodemographic, behavioral, and clinically associated factors among adults attending primary health care centers (PHCs) in Riyadh, Saudi Arabia. Methods: A cross-sectional, community-based study was conducted between March 2023 and July 2023 across 48 PHCs within Riyadh, using a consecutive sampling strategy. Adults aged 18 years and older were recruited and completed a validated, interviewer-administered electronic questionnaire assessing sociodemographic characteristics, lifestyle behaviors, and medical history, including comorbid conditions and health care access. Multivariable logistic regression was used to determine factors associated with self-reported renal disease, with results expressed as adjusted odds ratios (AORs) and 95% CIs, ensuring model adequacy and precision. Results: A total of 14,239 participants were surveyed (n=7519, 52.8% female; mean age 41.6, SD 13.2 y). The prevalence of self-reported renal disease (including chronic kidney disease and kidney stones) was 3.5% (n=504). Individuals aged younger than 50 years had higher odds of renal disease (AOR 1.22, 95% CI 1.02‐1.47). Female individuals were more likely to report renal disease than males (AOR 1.51, 95% CI 1.24‐1.84). Participants with health insurance had increased odds (AOR1.74; 95% CI 1.44‐2.11). Smoking was strongly associated with renal disease (AOR 3.07, 95% CI 2.38‐3.96). Other important associated factors included comorbidities such as diabetes (AOR 1.51, 95% CI 1.12‐2.04), hypertension (AOR 2.27, 95% CI 1.67‐3.08), obesity (AOR 12.75, 95% CI 9.97‐16.30), hypercholesterolemia (AOR 1.93, 95% CI 1.43‐2.60), and heart disease (AOR 6.84, 95% CI 5.14‐9.10). Conclusions: This large, community-based cross-sectional study identifies a significant burden of renal disease among adults in Riyadh and highlights several modifiable risk factors that could be targeted in preventive health programs. The findings emphasize the importance of integrating renal health screening within PHCs and strengthening public health strategies addressing obesity, hypertension, and smoking. While the study relied on self-reported data without biomarker or clinical confirmation, potentially underestimating true prevalence and introducing misclassification bias, it provides a crucial population-level baseline that can guide resource allocation and inform the development of nationwide surveillance systems for early detection of renal disease.

Background/Objectives: Blast-crisis chronic myeloid leukemia (BC-CML) represents a genomically unstable, therapeutically refractory phase driven by clonal evolution beyond BCR::ABL1 dependence. Clinical outcomes remain poor, with median survival under one year. Mutation-level analyses inadequately resolve biological heterogeneity or inform rational patient-specific therapy. We therefore implemented a mutational process–anchored framework integrating genomics, machine learning (ML), and artificial intelligence (AI)–guided drug prioritization at single-patient resolution. Methods: Whole-exome sequencing, COSMIC mutational signature deconvolution, unsupervised ML clustering, and AI-guided pharmacogenomic prioritization were applied to 224 patients with CML (190 chronic phase, 15 accelerated phase, 19 blast crisis) and 19 healthy controls. Results: Mutation burden increased significantly with disease progression, and blast crisis exhibited complex co-mutation architectures involving TP53, BRCA2, IDH1/2, DNMT3A, JAK2, and CSF3R. While gene-level patterns were heterogeneous, dominant mutational processes converged across cases. COSMIC signature extraction stratified BC-CML into three biologically coherent clusters: homologous recombination deficiency/genomic instability (Signatures 3/5), epigenetic–metabolic dysregulation (Signatures 1/2), and oxidative stress–associated cytokine signaling mutagenesis (Signatures 13/18). These process-defined states mechanistically link DNA repair failure, chromatin remodeling, and inflammatory signaling to blast transformation. Integration with an AI-guided pharmacogenomic framework translated signature biology into rational, cluster-specific therapeutic prioritization, including PARP inhibition, IDH targeting, CDK4/6 blockade, JAK pathway inhibition, and redox-modulating strategies. Dominant signature resolution reduced multidrug ambiguity and supported single-patient therapeutic parsimony. External concordance assessment across independent pharmacogenomic datasets supported predicted vulnerabilities. Conclusions: This study establishes a mechanistically interpretable, process-anchored precision oncology framework for BC-CML linking genomic architecture to actionable therapeutic decision-making warranting clinical validation. The approach can further be implemented for AL-AI-prioritized precision treatment of other relapsed, refractory and metastatic cancers.