Medication profiling in women with type 1 diabetes highlights the importance of adequate, guideline-based treatment in low-risk groups

Abstract

Effective treatment may prevent kidney complications, but women might be underprescribed. Novel, data-driven insights into prescriptions and their relationship with kidney health in women with type 1 diabetes may help to optimize treatment. We identified six medication profiles in 1164 women from the FinnDiane Study with normal albumin excretion rate based on clusters of their baseline prescription data using a self-organizing map. Future rapid kidney function decline was defined as an annual estimated glomerular filtration rate (eGFR) loss > 3 ml/min/1.73 m² after baseline. Two profiles were associated with future decline: Profile ARB with the highest proportion of angiotensin receptor blockers (odds ratio [OR] 2.75, P = 0.02) and highly medicated women in profile HighMed (OR 2.55, P = 0.03). Compared with profile LowMed (low purchases of all), profile HighMed had worse clinical characteristics, whereas in profile ARB only systolic blood pressure was elevated. Importantly, the younger women in profile ARB with fewer kidney protective treatments developed a rapid decline despite otherwise similar baseline characteristics to profile ACE & Lipids (the highest proportions of ACE inhibitors and lipid-modifying agents) without a future rapid decline. In conclusion, medication profiles identified different future eGFR trajectories in women with type 1 diabetes revealing potential treatment gaps for younger women.

Figure 1

(A) Self-organizing maps (SOM) and six selected pharmacological subgroups (based on the 3rd level ATC classification), either known to be protective or harmful for the kidneys and which showed a clear patterns in deviation from the study average in purchases of prescription medications at each selected pharmacological subgroups. These selected subgroups were ACE inhibitors [C09A], angiotensin II receptor blockers, ARBs [C09C], lipid-modifying agents [C10A], anti-inflammatory drugs [M01A], antibacterials [J01D], and antidepressants [N06A]. In the coloring scale red refers higher and blue lower deviation from the whole cohort’s average. The intensity of the color shows how much regional variation deviates from the null model. If the observed pattern is stronger than could be expected by change, colors are bright indicating strong impact, while light colors indicates that there is no clear pattern. Moreover, the numerical values on the six map colorings indicate the local mean value of purchasers for that particular subarea. Based on the map colorings, experts’ knowledge was used in setting and deciding all subgroup boundaries (dashed lines). Six baseline medication profiles were identified: LowMed (region A), Antibacterial (region B), ARB (region C), HighMed (region D), Anti-inflammatory (region E) and ACE & Lipids (region F). Each profile represents specific subsets of women that share the same medication pattern at baseline. (B) Bars show how proportions of the six medication subgroups differed from the study average at each medication profile. The astrisks (*) denotes the statistical significance of P < 0.05, compared with the the study average.

Figure 2

Proportions of women on the renin–angiotensin–aldosterone system (RAAS) inhibitors (A) and lipid-lowering drugs (B) in profiles LowMed, ARB and ACE & Lipids during the 5-year follow-up.