EPIDEMIOLOGY AND HEALTH DATA INSIGHTS

Keyword: Quality Control

1 result found.

Original Article
Are Quality Control Practices in Molecular Genetics Laboratories Good Enough for Ovarian Cancer Diagnosis in Resource-Limited Settings? A Study from Kazakhstan
Epidemiology and Health Data Insights, 2(4), 2026, ehdi047, https://doi.org/10.63946/ehdi/18922
ABSTRACT: Introduction: Ovarian cancer is a major cause of cancer death in women, mostly due to late detection. Quality control (QC) in molecular genetics laboratories is essential for accurate testing of BRCA1/2 and other mutations. This study evaluated QC practices in molecular genetics laboratories in Kazakhstan conducting ovarian cancer diagnostics in a resource-limited setting and compared them with international standards. Aim: To assess the quality control practices of molecular genetics laboratories involved in ovarian cancer diagnostics in Kazakhstan.
Methods: A descriptive cross-sectional study was conducted among 25 laboratory employees from three molecular genetics laboratories in Almaty, Kazakhstan. The questionnaire assessed internal quality control (IQC), external quality assessment (EQA) participation, SOP compliance, and operational challenges. Data were analysed using SPSS v.28. A systematic literature review based on PRISMA 2020 guidelines was also performed.
Results: Daily use of positive and negative controls was reported by 68% of respondents, while 52% performed daily DNA quality checks and 60% reported full SOP compliance. Equipment calibration was conducted weekly or monthly (44% each) rather than daily. Major challenges included sample contamination (56%), unreliable reagents (48%), and inadequate funding (68%). EQA participation was 76%. Respondents recommended improved training (52%), automation (36%), and better sample handling (32%). The review indicated that daily controls, high-depth NGS, and automation achieved 98–99% accuracy in BRCA1/2 testing.
Discussion: QC practices in Kazakh laboratories are reasonable but reveal gaps in calibration frequency, sample integrity, and resources. Daily calibration, affordable automation, local EQA programs, and staff training could improve diagnostic accuracy in resource-limited settings.