Achieving sensible targets for a diabetes care cascade in LMICs
Authors: Parinya Chamnan
Journal: The Lancet Global Health (2021)

Increasing evidence suggests that coverage of diagnosis, treatment, and control of diabetes in low-income and middle-income countries (LMICs) is generally low, but variable across global regions.1Flood D Seiglie JA Dunn M et al.The state of diabetes treatment coverage in 55 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 680 102 adults.Lancet Healthy Longev. 2021; 2: e340-e351Summary Full Text Full Text PDF Scopus (7) Google Scholar, 2Manne-Goehler J Geldsetzer P Agoudavi K et al.Health system performance for people with diabetes in 28 low- and middle-income countries: a cross-sectional study of nationally representative surveys.PLoS Med. 2019; 16e1002751Crossref PubMed Scopus (63) Google Scholar Challenges remain for LMICs to identify strategies to achieve each of the components of a so-called diabetes care cascade—ie, diagnosis, treatment, and disease control.3Chamnan P Gaps in achieving coverage of diabetes treatments in low-income and middle-income countries.Lancet Healthy Longev. 2021; 2: e306-e307Summary Full Text Full Text PDF Scopus (1) Google Scholar In their study in The Lancet Global Health, Sanjay Basu and colleagues4Basu S Flood D Geldsetzer P et al.Estimated effect of increased diagnosis, treatment, and control of diabetes and its associated cardiovascular risk factors among low-income and middle-income countries: a microsimulation model.Lancet Glob Health. 2021; (published online Sept 22.)https://doi.org/10.1016/S2214-109X(21)00340-5Summary Full Text Full Text PDF PubMed Scopus (1) Google Scholar show that, by applying targets to a care cascade (as has previously been successfully endorsed by WHO for other health problems, particularly HIV) to diabetes care, health-care systems and stakeholders could better understand the current gaps and potential benefits of augmenting diagnosis through screening, treatment, and control of diabetes and other vascular risk factors in LMICs. Based on microsimulation modelling, the investigators' findings show that scaling-up diagnosis, treatment, and control of diabetes to achieve a hypothetical 60% target or an even more challenging 80% target for each component of the care cascade would be highly cost-effective, with overall incremental cost-effectiveness ratios ranging from $807 to $1406 (ie, 2020 International Dollars) per disability-adjusted life-years averted. This finding would largely arise from a substantial predicted reduction in major cardiovascular events through improved treatment with antihypertensive drugs and statins, and achievement of blood pressure control targets.4Basu S Flood D Geldsetzer P et al.Estimated effect of increased diagnosis, treatment, and control of diabetes and its associated cardiovascular risk factors among low-income and middle-income countries: a microsimulation model.Lancet Glob Health. 2021; (published online Sept 22.)https://doi.org/10.1016/S2214-109X(21)00340-5Summary Full Text Full Text PDF PubMed Scopus (1) Google Scholar In Basu and colleagues' study,4Basu S Flood D Geldsetzer P et al.Estimated effect of increased diagnosis, treatment, and control of diabetes and its associated cardiovascular risk factors among low-income and middle-income countries: a microsimulation model.Lancet Glob Health. 2021; (published online Sept 22.)https://doi.org/10.1016/S2214-109X(21)00340-5Summary Full Text Full Text PDF PubMed Scopus (1) Google Scholar possible uncertainties might exist over the model structure and input parameters, particularly the targets in diabetes care they defined, relative risk reductions, and cost estimates. The investigators modelled several fixed combinations of improved targets on diagnosis, treatment, and control. However, a complex interplay exists between different components of the diabetes care cascade—eg, increasing treatment by 10% might not always lead to a proportional increase in the number of people with good control of their diabetes or hypertension. To model the clinical effects of interventions to improve diabetes management, Basu and colleagues used published relative risk reductions, most of which were derived from studies done in high-income countries. Whether these interventions would be similarly effective in the care settings of LMICs is uncertain. Additionally, they used cost estimates from the WHO OneHealth Tool,5WHOOneHealth Tool. World Health Organization, Geneva2021https://www.who.int/tools/onehealthDate accessed: August 15, 2021Google Scholar which assumes a so-called standard-of-care being provided. This assumption might create a discrepancy from the true baseline costs in LMICs, where different standards of diabetes care are accepted and practically met. Because of a paucity of evidence on the incidence of most clinical outcomes in LMICs, the investigators used estimated risk based on risk equations instead of actual or observed risk. The use of existing risk equations—which are mostly developed from high-income countries to estimate probabilities of vascular complications of diabetes—might lead to overestimation or, in some cases, underestimation of risk6Chamnan P Simmons RK Sharp SJ Griffin SJ Wareham NJ Cardiovascular risk assessment scores for people with diabetes: a systematic review.Diabetologia. 2009; 52: 2001-2014Crossref PubMed Scopus (118) Google Scholar and, hence, might have altered the main results on the cost–utility analyses. Additionally, whether the investigators included the risk of developing vascular complications and mortality in those with undiagnosed diabetes in their models is unclear. Any efforts to increase diabetes diagnosis through screening as hypothesised in this study would increase the number of people with newly diagnosed diabetes, and this group would, of course, have a high incidence of microvascular and macrovascular complications and mortality as well as increased costs of related treatments.7Griffin SJ Rutten G Khunti K et al.Long-term effects of intensive multifactorial therapy in individuals with screen-detected type 2 diabetes in primary care: 10-year follow-up of the ADDITION-Europe cluster-randomised trial.Lancet Diabetes Endocrinol. 2019; 7: 925-937Summary Full Text Full Text PDF PubMed Scopus (13) Google Scholar To model management of blood cholesterol, the investigators used a risk-based approach to inform initiation of statins for prevention of vascular complications in their models, and they did not show any benefits of achieving cholesterol targets. Although this risk-based approach is aligned to international and national guidelines on cardiovascular risk management,8Grundy SM Stone NJ Bailey AL et al.2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the management of blood cholesterol.J Am Coll Cardiol. 2019; 73: e285-e350Crossref PubMed Scopus (834) Google Scholar modelling risks and benefits related to prescription of statins based on multivariate risk assessment might not represent real-world scenarios occurring in many LMICs. There might also be practical implications or restrictions on the validity of using such an approach. Few LMICs have implemented this approach, and different countries show varying progress in adopting the concept of cardiovascular risk assessment and management.9Chamnan C Aekplakorn W Cardiovascular risk assessment in developing world.in: Kumar A Recent trend in cardiovascular disease. Intech, Rijeka2017: 57-70Crossref Google Scholar Computation of cardiovascular risk in routine clinical settings in LMICs might require not only a shift in how physicians practise, but also the substantial development of a service delivery system and infrastructure. In the short-term to medium-term, a simple approach of achieving targets for glycated haemoglobin A1c or blood glucose, blood pressure, and blood cholesterol might represent an obvious and sensible choice for cardiovascular risk management among patients with diabetes in LMICs. The effects of such a target-based approach to diabetes management in LMICs as compared with the risk-based approach would be interesting to observe. Basu and colleagues' study is also a clear disposition of an important issue that has become and will continue to be a global challenge: health inequality. Not only disparities in met-need for diagnosis, treatment, and control of diabetes were observed, but clinical and economic effects of efforts to achieve the common goals of diabetes management also varied greatly across these LMICs. Further exploration into key determinants of the between-country differences in the benefits of improving diagnosis, treatment, and control of diabetes is needed; whether it is the starting attainment of diabetes diagnosis, treatment, and control, or certain patient-level and country-level characteristics, these factors might contribute to between-country differences. A better understanding of these contributing factors might be beneficial in improving morbidity and mortality related to diabetes in each of the LMICs and possibly help to narrow the gaps between these countries in the benefits from improving components of diabetes care cascade. I have received honoraria for lectures from Roche Diagnostics. Estimated effect of increased diagnosis, treatment, and control of diabetes and its associated cardiovascular risk factors among low-income and middle-income countries: a microsimulation modelReducing complications from diabetes in LMICs is likely to require a focus on scaling up blood pressure and statin medication treatment initiation and blood pressure medication titration rather than focusing on increasing screening to increase diabetes diagnosis, or a glycaemic treatment and control among people with diabetes. Full-Text PDF Open Access