A study of the quality of cardiovascular and diabetes medicines in Malang District, Indonesia, using exposure-based sampling

一项采用基于暴露抽样法的研究,调查了印度尼西亚玛琅地区心血管和糖尿病药物的质量。

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Abstract

BACKGROUND: The WHO has warned that substandard and falsified medicines threaten health, especially in low and middle-income countries (LMICs). However, the magnitude of that threat for many medicines in different regions is not well described, and high-quality studies remain rare. Recent reviews of studies of cardiovascular and diabetes medicine quality recorded that 15.4% of cardiovascular and 6.8% of diabetes samples failed at least one quality test. Review authors warn that study quality was mixed. Because they did not record medicine volume, no study reflected the risk posed to patients. METHODS AND FINDINGS: We investigated the quality of five medicines for cardiovascular disease and diabetes in Malang district, East Java, Indonesia. Our sample frame, based on dispensing volumes by outlet and price category, included sampling from public and private providers and pharmacies and reflected the potential risk posed to patients. The content of active ingredient was determined by high-performance liquid chromatography and compared with the labelled content. Dissolution testing was also performed.We collected a total of 204 samples: amlodipine (88); captopril (22); furosemide (21); glibenclamide (21) and simvastatin (52), comprising 83 different brands/products. All were manufactured in Indonesia, and all samples met specifications for both assay and dissolution. None was suspected of being falsified. CONCLUSIONS: While we cannot conclude that the prevalence of poor-quality medicines in Malang district is zero, our sampling method, which reflects likely exposure to specific brands and outlets, suggests that the risk to patients is very low; certainly nothing like the rates found in recent reviews of surveys in LMICs. Our study demonstrates the feasibility of sampling medicines based on likely exposure to specific products and underlines the dangers of extrapolating results across countries.

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