Study protocol for a mixed methods approach to optimize colorectal cancer screening in Malaysia: Integrating stakeholders insights and knowledge-to-action framework

INTRODUCTION

Colorectal cancer is a growing global health concern and the number of reported cases has increased over the years. Early detection through screening is critical to improve outcomes for patients with colorectal cancer. In Malaysia, there is an urgent need to optimize the colorectal cancer screening program as uptake is limited by multiple challenges. This study aims to systematically identify and address gaps in screening service delivery to optimize the Malaysian colorectal cancer screening program.

METHODS

This study uses a mixed methods design. It focuses primarily on qualitative data to understand processes and strategies and to identify specific areas that can be improved through stakeholder engagement in the screening program. Quantitative data play a dual role in supporting the selection of participants for the qualitative study based on program monitoring data and assessing inequalities in screening and program implementation in healthcare facilities in Malaysia. Meanwhile, literature review identifies existing strategies to improve colorectal cancer screening. Additionally, the knowledge-to-action framework is integrated to ensure that the research findings lead to practical improvements to the colorectal cancer screening program.

DISCUSSION

Through this complex mix of qualitative and quantitative methods, this study will explore the complex interplay of population- and systems-level factors that influence screening rates. It involves identifying barriers to effective colorectal cancer screening in Malaysia, comparing current strategies with international best practices, and providing evidence-based recommendations to improve the local screening program.

Spatial clustering of colorectal cancer in Malaysia

INTRODUCTION

The rise in colorectal cancer (CRC) incidence becomes a global concern. As geographical variations in the CRC incidence suggests the role of area-level determinants, the current study was designed to identify the spatial distribution pattern of CRC at the neighbourhood level in Malaysia.

METHOD

Newly diagnosed CRC cases between 2010 and 2016 in Malaysia were identified from the National Cancer Registry. Residential addresses were geocoded. Clustering analysis was subsequently performed to examine the spatial dependence between CRC cases. Differences in socio-demographic characteristics of individuals between the clusters were also compared. Identified clusters were categorized into urban and semi-rural areas based on the population background.

RESULT

Most of the 18 405 individuals included in the study were male (56%), aged between 60 and 69 years (30.3%) and only presented for care at stages 3 or 4 of the disease (71.3%). The states shown to have CRC clusters were Kedah, Penang, Perak, Selangor, Kuala Lumpur, Melaka, Johor, Kelantan, and Sarawak. The spatial autocorrelation detected a significant clustering pattern (Moran's Index 0.244, p< 0.01, Z score >2.58). CRC clusters in Penang, Selangor, Kuala Lumpur, Melaka, Johor, and Sarawak were in urbanized areas, while those in Kedah, Perak and Kelantan were in semi-rural areas.

CONCLUSION

The presence of several clusters in urbanized and semi-rural areas implied the role of ecological determinants at the neighbourhood level in Malaysia.  Such findings could be used to guide the policymakers in resource allocation and cancer control.

Projecting Malaria Incidence Based on Climate Change Modeling Approach: A Systematic Review

BACKGROUND: Climate change will affect the transmission of malaria by shifting the geographical space of the vector. AIM: The review aims to examine the climate change modeling approach and climatic variables used for malaria projection. METHODS: Articles were systematically searched from four databases, Scopus, Web of Science, PubMed, and SAGE. The PICO concept was used for formulation search and PRISMA approach to identify the final articles. RESULTS: A total of 27 articles were retrieved and reviewed. There were six climate factors identified in this review: Temperature, rainfall/precipitation, humidity, wind, solar radiation, and climate change scenarios. Modeling approaches used to project future malarial trend includes mathematical and computational approach. CONCLUSION: This review provides robust evidence of an association between the impact of climate change and malaria incidence. Prediction on seasonal patterns would be useful for malaria surveillance in public health prevention and mitigation strategies.

Disparities in Recommendations for Colorectal Cancer Screening Among Average-Risk Individuals: An Ecobiosocial Approach

Regardless of the high global burden of colorectal cancer (CRC), the uptake of CRC screening varies across countries. This systematic review aimed to provide a picture of the disparities in recommendations for CRC screening in average-risk individuals using an ecobiosocial approach. It was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The literature search was conducted through Scopus, Web of Science, PubMed, and EBSCOHost. Full-text guidelines which were published between 2011 and 2021, along with guidelines which provided recommendations on CRC screening in average-risk individuals, were included in the review. However, guidelines focusing only on a single screening modality were excluded. Fourteen guidelines fulfilling the eligibility criteria were retained for the final review and analysis. Quality assessment of each guideline was performed using the AGREE II instrument. Disparities in guidelines identified in this review were classified into ecological (screening modalities and strategies), biological (recommended age, gender and ethnicities), and social (smoking history, socioeconomic status, and behavior) factors. In general, unstandardized practices in CRC screening for average-risk individuals are likely attributable to the inconsistent and non-specific recommendations in the literature. This review calls on stakeholders and policymakers to review the existing colorectal cancer screening practices and pursue standardization.

Meta-Analysis of the Association between Dietary Inflammatory Index (DII) and Colorectal Cancer

The Dietary Inflammatory Index (DII) was extensively used to examine the inflammatory potential of diet related to colorectal cancer (CRC). This meta-analysis aimed to update the evidence of the association between the DII and CRC across various culture-specific dietary patterns. Literature search was performed through online databases (Scopus, Web of Science, PubMed, and EBSCOHost). Observational studies exploring the association between the DII and CRC, published between 2017 and 2021, were included. The risk ratio (RR) and 95% confidence interval (CI) were separately computed for 12 studies comparing the highest and lowest DII scores and for 3 studies that presented continuous DII scores. A high DII score was associated with a higher risk of CRC (RR:1.16; 95% CI, 1.05–1.27). In the subgroup analysis, significant associations were seen in cohort design (RR: 1.24; 95% CI, 1.06–1.44), those lasting for 10 years or longer (RR: 2.95; 95% CI, 2.47–3.52), and in adjustment factor for physical activity (RR: 1.13; 95% CI, 1.07–1.20). An increase of one point in the DII score elevates the risk of CRC by 1.34 (95% CI: 1.15–1.55) times. The findings call for standardized measurement of the inflammatory potential of diet in future studies to enable the establishment of global guidelines for CRC prevention.

Machine Learning Models in Prediabetes Screening: A Systematic Review

Introduction: The increasing prevalence of type 2 Diabetes Mellitus (DM) can be done from identifying those with prediabetes and offer early interventions by utilising prescreening diagnostic tools. Machine learning algorithms and big data mining approaches have been postulated for predictive disease modelling in hospital and clinical settings. Aim: This review was aimed at outlining the relative performance accuracies in predicting prediabetes conditions in different machine learning algorithms. Materials and Methods: A systematic literature search was conducted at Universiti of Kebangsaan Malaysia Kuala Lumpur, based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) review protocol, and the research question was formulated based on the keywords of "Prediabetes" (Population), "Internet of Things" and "prediction model" (Intervention) and "screening" and "risk" (Outcome). International Prospective Register of Systematic Reviews (PROSPERO) registration (CRD42021264947) was done and databases were screened on 10th-24th June 2021 via Web of Science, Scopus, PubMed, Ovid and EBSCOhost. Inclusion criteria was English language prediction studies published between 2011-2021. Review articles, editorials, proceedings, commentary articles and articles not focusing on prediabetes were excluded. The quality of the articles was ranked via the Prediction Model Risk of Bias Assessment Tool (PROBAST). Results: Five articles included were published in 2014-2021. The sample sizes ranged from 570 to 24,331 participants. Three studies (South Korea, United State of America (USA), Japan) suggested the applicability of the screening score prediction models for use in clinical settings related to personalised risk assessment and targeted interventions, with the predictors used being suitable for either the clinic or hospital. The simplicity of gender, age, Body Mass Index (BMI), blood pressure and waist circumference as predictors suggested that they can be utilised by the community. Conclusion: This review highlights the fact that the heterogeneity of the population used and validation issues may affect generalisation. Future studies should address these concerns to guide advocacy among healthcare providers in clinical practice as well as in data and expertise sharing for developing and validating urgently needed prediabetic prediction models.

Rate and associated factors of refusal to perform immunochemical Faecal Occult Blood Test (iFOBT) among semi-urban communities

The uptake of the immunochemical faecal occult blood test (iFOBT) in many countries with an opportunistic colorectal cancer (CRC) screening programme remains suboptimal. This study aimed to determine the rate, associated factors and reasons of refusal to perform the iFOBT test offered under an opportunistic CRC screening programme in semi-urban communities. This cross-sectional study was conducted among the average-risk individuals living in semi-urban areas, who sought care from public primary care centres across Kedah state, Malaysia. The information regarding the sociodemographic and clinical characteristics of individuals who were offered the iFOBT between January and April 2019, along with their willingness to perform the test, was gathered. The factors associated with the refusal were further explored using the logistic regression analysis. The individuals offered the iFOBT (n = 920) were mainly female (52.4%) and had a mean age of 58.7±10.6 years. The refusal rate of the iFOBT was 32.2%. Patients who did not have hypertension (adjusted OR: 3.33; 95% CI: 2.44, 4.54), did not have CRC symptoms (adjusted OR: 3.15; 95% CI:1.26, 7.89), had the test offered by either medical assistants (adjusted OR: 2.44; 95% CI: 1.71, 3.49) or nurses (adjusted OR: 2.41; 95% CI 1.65, 3.51), did not have diabetes (adjusted OR: 1.99; 95% CI: 1.42, 2.77),and were not active smokers (adjusted OR: 1.74; 95% CI: 1.22, 2.47), were more likely to refuse the iFOBT. The common reasons of refusing the test included "feeling not ready for the test" (21.6%) and "feeling healthy" (14.9%). The iFOBT was refused by one-third of the average-risk individuals from semi-urban communities. The associated factors and reasons of refusal found in this study could guide policymakers in developing targeted interventions to boost the uptake of CRC screening in Malaysia.

Management and glycemic control of patients with type 2 diabetes mellitus at primary care level in Kedah, Malaysia: A statewide evaluation

Introduction

While Kedah has recorded the highest prevalence of diabetes among all the states in Malaysia, the information on the practice and effectiveness of disease management in public health institutions remains limited. This study aimed to evaluate the management and glycemic control of patients with type-2 diabetes mellitus (T2DM) at the primary care level in Kedah.

Methods

All T2DM patients, who made at least one visit to any of the 58 public health clinics in Kedah during August 2016 and July 2017, were included in this study. The sample was selected from the National Diabetes Registry using the stratified random sampling method. The information on the demographic and clinical characteristics, laboratory findings and pharmacological treatment was gathered from medical records of patients. The differences in mean HbA1C levels across subgroups of each variable were tested using the general linear model. The evaluation of the appropriateness of treatment was performed based on the recommendations of the latest Clinical Practice Guidelines for T2DM.

Results

The patients (n = 23,557) were mainly female (63.4%), of Malay ethnicity (80.1%) and middle-aged (62.2%), with a mean duration of T2DM of 6.2±7.16 years. Only 15.6% of them had a HbA1C level <6.5%, and 28.6% did not have their HbA1C levels tested over the 12-month period. Yet, the underutilization of combination treatment (≥2 antidiabetic agents) and insulin in the patients with a poor glycemic control was evident. Retinopathy emerged as the most prevalent diabetes-related complication (12.6%). Along with those with a longer duration of T2DM, the patients who were younger, female and of Indian ethnicity were found to generally have a poorer glycemic control.

Conclusion

This study discloses the suboptimal T2DM management at the primary care level in Kedah, which warrants a statewide plan for improvement.