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Fulltext Determinants of glycaemic control among type 2 diabetes mellitus patients in Northern State of Kedah, Malaysia: a cross-sectional analysis of 5 years national diabetes registry 2014-2018

Hassan MR, Jamhari MN, Hayati F, Ahmad N, Zamzuri MIA, Nawi AM, et al.

Pan Afr Med J, 2021;39:206.
PMID: 34603587 DOI: 10.11604/pamj.2021.39.206.30410

Introduction: type 2 diabetes mellitus has become a global public health crisis. The increment in the cases has contributed significantly to the parallel increase in the prevalence of overweight and obesity. This paper aimed to analyse the relationship between lipid profile, waist circumference and body mass index (BMI) with the glycaemic control of the diabetes patients in Kedah.
Methods: a cross-sectional study was conducted, using the Kedah audit samples data extracted from the National Diabetes Registry (NDR) from the year 2014 to 2018. A total of 25,062 registered type 2 diabetes mellitus patients were selected using the inclusion and exclusion criteria from the registry. Only patients with complete data on their HbA1C, lipid profile, waist circumference and BMI were analysed using SPSS version 21.
Results: the means for the age, BMI and waist circumference of the samples were 61.5 (±10.85) years, 27.3 (±5.05) kg/m2 and 89.46 (±13.58) cm, respectively. Poor glycaemic control (HbA1c>6.5%) was observed in 72.7% of the patients, with females having poorer glycaemic control. The BMI and waist circumference were found to be significantly associated with glycaemic control (P<0.001). The total cholesterol, triglycerides and low-density lipoproteins values showed positive correlation with glycaemic control (r = 0.178, 0.157, 0.145, p<0.001), while high-density lipoproteins values are negatively correlated (r = -0.019, p<0.001).
Conclusion: implementing lifestyle changes such as physical activity and dietary modifications are important in the management of BMI, waist circumference and body lipids, which in turn results in improved glycaemic control.
Descriptive assessment on diabetic retinopathy screening in an awareness programme in Malaysia

Ngah NF, Muhamad NA, Asnir ZZ, Abdul Aziz RA, Mhad Kassim Z, Sahar SA, et al.

Int J Ophthalmol, 2020;13(11):1808-1813.
PMID: 33215014 DOI: 10.18240/ijo.2020.11.19

AIM: To determine the prevalence of diabetic retinopathy (DR) among diabetic patients at the primary health clinics in Selangor, Malaysia.
METHODS: All diabetic patients were screened in Retinal Disease Awareness Programme (RDAP) and those who had significant DR changes were referred to the hospital for further management. Descriptive analyses were done to determine the prevalence of DR and sociodemographic characteristics among patients with diabetic. Univariate and multivariable analysis using Logistic regression were performed to find association and predictor factors in this screening.
RESULTS: A total of 3305 patients aged 40y and above were screened for DR. Of the patients screened, 9% patients were found to have DR and other visual complication such as maculopathy (0.9%), cataract (4.8%) and glaucoma (0.4%). The mean age of patients without retinopathy was 57.82±8.470y and the mean age of patients with DR was 63.93±9.857y. About 61.5% of the patients screened were aged below 60y and 38.5% were aged 60y and above. Majority of the patients screened were women 58.5% and Malay in the age group of 50-59y, while 27% were aged 60-69y. Significant association were found between age, sex, race, visual loss and DR.
CONCLUSION: Although the prevalence of DR among patients is not alarming, effective interventions need to be implemented soon to avert a large burden of visual loss from DR.
Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Page DB, Broeckx G, Jahangir CA, Verbandt S, Gupta RR, Thagaard J, et al.

J Pathol, 2023 Aug;260(5):514-532.
PMID: 37608771 DOI: 10.1002/path.6165

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.
Fulltext Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Thagaard J, Broeckx G, Page DB, Jahangir CA, Verbandt S, Kos Z, et al.

J Pathol, 2023 Aug;260(5):498-513.
PMID: 37608772 DOI: 10.1002/path.6155

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Fulltext Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Jahangir CA, Page DB, Broeckx G, Gonzalez CA, Burke C, Murphy C, et al.

J Pathol, 2024 Mar;262(3):271-288.
PMID: 38230434 DOI: 10.1002/path.6238

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.