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Article

Effects of Statin Dose, Class, and Use Intensity on All-Cause Mortality in Patients with Type 2 Diabetes Mellitus

by
Jung-Min Yu
1,2,†,
Wan-Ming Chen
3,4,†,
Mingchih Chen
3,4,
Ben-Chang Shia
3,4,*,‡ and
Szu-Yuan Wu
3,4,5,6,7,8,9,10,11,*,‡
1
Department of Cardiovascular Surgery, Taichung Tzu Chi Hospital, Taichung 427213, Taiwan
2
Department of Surgery, School of Medicine, Tzu Chi University, Hualien 97004, Taiwan
3
Graduate Institute of Business Administration, College of Management, Fu Jen Catholic University, Taipei 242062, Taiwan
4
Artificial Intelligence Development Center, Fu Jen Catholic University, Taipei 242062, Taiwan
5
Department of Food Nutrition and Health Biotechnology, College of Medical and Health Science, Asia University, Taichung 41354, Taiwan
6
Division of Radiation Oncology, Lo-Hsu Medical Foundation, Lotung Poh-Ai Hospital, Yilan 265501, Taiwan
7
Big Data Center, Lo-Hsu Medical Foundation, Lotung Poh-Ai Hospital, Yilan 265501, Taiwan
8
Department of Healthcare Administration, College of Medical and Health Science, Asia University, Taichung 41354, Taiwan
9
Cancer Center, Lo-Hsu Medical Foundation, Lotung Poh-Ai Hospital, Yilan 265501, Taiwan
10
Centers for Regional Anesthesia and Pain Medicine, Taipei Municipal Wan Fang Hospital, Taipei Medical University, Taipei 11031, Taiwan
11
Department of Management, College of Management, Fo Guang University, Yilan 26247, Taiwan
 
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Authors to whom correspondence should be addressed.
†
These authors have contributed equally to this study (joint primary authors).
‡
These authors have contributed equally to this study (joint primary Corresponding authors).
Pharmaceuticals 2023, 16(4), 507; https://doi.org/10.3390/ph16040507
Submission received: 1 February 2023 / Revised: 10 March 2023 / Accepted: 24 March 2023 / Published: 29 March 2023
(This article belongs to the Special Issue Drug Candidates for the Prevention and Treatment of Cardiovascular Diseases in Patients with Diabetes Mellitus)
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Abstract

:
Purpose: to examine the impact of statins on reducing all-cause mortality among individuals diagnosed with type 2 diabetes. This investigation explored the potential correlations between dosage, drug classification, and usage intensity with the observed outcomes. Methods: The research sample consisted of individuals aged 40 years or older diagnosed with type 2 diabetes. Statin usage was determined as a frequent usage over a minimum of one month subsequent to type 2 diabetes diagnosis, where the average statin dose was ≥28 cumulative defined daily doses per year (cDDD-year). The analysis employed an inverse probability of treatment-weighted Cox hazard model, utilizing statin usage status as a time-varying variable, to evaluate the impact of statin use on all-cause mortality. Results: The incidence of mortality was comparatively lower among the cohort of statin users (n = 50,804 (12.03%)), in contrast to nonusers (n = 118,765 (27.79%)). After adjustments, the hazard ratio (aHR; 95% confidence interval (CI)) for all-cause mortality was estimated to be 0.32 (0.31–0.33). Compared with nonusers, pitavastatin, rosuvastatin, pravastatin, simvastatin, atorvastatin, fluvastatin, and lovastatin users demonstrated significant reductions in all-cause mortality (aHRs (95% CIs) = 0.06 (0.04–0.09), 0.28 (0.27–0.29), 0.29 (0.28–0.31), 0.31 (0.30–0.32), 0.31 (0.30–0.32), 0.36 (0.35–0.38), and 0.48 (0.47–0.50), respectively). In Q1, Q2, Q3, and Q4 of cDDD-year, our multivariate analysis demonstrated significant reductions in all-cause mortality (aHRs (95% CIs) = 0.51 (0.5–0.52), 0.36 (0.35–0.37), 0.24 (0.23–0.25), and 0.13 (0.13–0.14), respectively; p for trend <0.0001). Because it had the lowest aHR (0.32), 0.86 DDD of statin was considered optimal. Conclusions: In patients diagnosed with type 2 diabetes, consistent utilization of statins (≥28 cumulative defined daily doses per year) was shown to have a beneficial effect on all-cause mortality. Moreover, the risk of all-cause mortality decreased as the cumulative defined daily dose per year of statin increased.

1. Introduction

Diabetes is a prominent contributor to global mortality rates and accounts for a position among the top 10 causes of death worldwide. In excess of 80% of premature deaths due to non-communicable diseases result from diabetes, cardiovascular disease, cancer, and respiratory disease collectively [1]. Type 2 diabetes affects a majority (over 90%) of the total number of individuals with diabetes worldwide and represents a significant health burden [2]. Type 2 diabetes is identified by hyperglycemia, insulin resistance, compromised insulin secretion, and dyslipidemia characterized by elevated triglyceride levels and reduced levels of high-density lipoprotein cholesterol [3,4,5,6]. Type 2 diabetes is associated with an elevated risk of heart disease, stroke, high blood pressure, atherosclerosis (narrowing of blood vessels), and peripheral neuropathy (nerve damage) [7,8]. The condition not only represents a significant risk factor for the aforementioned comorbidities, but it also increases the all-cause mortality risk by 35%, particularly in younger and female individuals [9]. However, there is a lack of research on the association between all-cause mortality, protective medication, and the relatively elderly (≥40 years old) type 2 diabetes population.
In patients with diabetes, the mortality rates are higher than in the general population; their prognosis following any cardiovascular event is generally worse as well [9,10,11]. The development of an effective protective medication against mortality in patients with type 2 diabetes is warranted and would be valuable. Statins, a commonly used medication, are often prescribed for patients with type 2 diabetes to help them manage their condition [12]. This is because type 2 diabetes increases the risk of heart disease, including heart attack and stroke [13]. Statin use does not indicate the failure of management of type 2 diabetes [12]. However, whether statin use in patients with type 2 diabetes reduces cardiovascular event incidence and all-cause mortality remains debatable [14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]. Previous retrospective cohort studies have used vague and heterogeneous definitions of statin use: patients who used statins during hospitalization, had at least two invoices for statins during the enrolment period, or had statins listed on the medication list during the study period were considered statin users [26,27,28,29]. These definitions were not stratified by statin use dosage, statin class, or intensity (continuous or discontinuous use) [26,27,28,29]. Similarly, some randomized controlled trials (RCTs) have reported controversial conclusions [14,15,16,17,18,19,20,21,22,23,24,25] because they used a small sample size with heterogeneous endpoints and an insufficient follow-up duration; moreover, most of these RCTs did not state whether the study patients had type 1 or 2 diabetes [14,15,16,17,18,19,20,21,22,23,24,25].
Therefore, in the current study, we estimated the effects of statin use on the all-cause mortality of patients with type 2 diabetes and the dependency of these effects on the statin dose, class, and use intensity by using data from a real-world database. We also estimated the optimal daily statin dose of statins for patients with type 2 diabetes.

2. Results

Throughout the study period spanning from 2008 to 2020, a total of 849,787 patients were diagnosed with type 2 diabetes. The mean age at diagnosis was 56.85 years for nonusers and 56.92 years for users of statins. Atorvastatin was the most frequently prescribed statin (35.88%), followed by simvastatin (19.89%) and rosuvastatin (19.55%). To account for potential confounding factors, the IPTW Cox hazard model was used, resulting in balanced covariates between the two groups (Table 1).

2.1. Association of All-Cause Mortality with Different Statin Dosages and Classes

A total of 118,765 (27.79%) individuals who did not use statins and 50,804 (12.03%) who did, died during the study period. The adjusted hazard ratio (aHR) for all-cause mortality was 0.32 (95% confidence interval (CI) = 0.31–0.33), indicating that statin users had lower mortality rates than nonusers (Table 2). Among statin users, users of pitavastatin, rosuvastatin, pravastatin, simvastatin, atorvastatin, fluvastatin, and lovastatin demonstrated a significant reduction in all-cause mortality, with aHRs (95% CIs) of 0.06 (0.04–0.09), 0.28 (0.27–0.29), 0.29 (0.28–0.31), 0.31 (0.30–0.32), 0.31 (0.30–0.32), 0.36 (0.35–0.38), and 0.48 (0.47–0.50), respectively (Table 2). In the log-rank test, overall survival was significantly different for different statin classes used (p < 0.0001; Figure 1).
Among statin users, users of Q1, Q2, Q3, and Q4 cDDD-year of statins demonstrated a significant reduction in all-cause mortality, with aHRs (95% CIs) of 0.51 (0.5–0.52), 0.36 (0.35–0.37), 0.24 (0.23–0.25), 0.13 (0.13–0.14), respectively (p for trend < 0.0001; p < 0.0001, log-rank test; Figure 2).

2.2. Statin Use Intensity

The optimal statin dose was 0.86 DDD, with the lowest aHR of 0.32 (Figure 3). The protective effects on mortality and dose–response relationships exhibited U-shaped dose–response relationships [30], which means a higher DDD is not always associated with a lower risk of mortality.

2.3. Sensitivity Analysis

We conducted a sensitivity analysis that involved patients who initiated statins either after or before the diagnosis of type 2 diabetes, and the results indicated that statin use was linked with a reduction in all-cause mortality in both groups (Table 3). We also investigated the influence of statin use intensity and found that mortality decreased in patients who used an average of ≤1 and >1 DDD. Additionally, we examined the effects of statins in patients with different comorbidities (CCI ≤ 1), age groups, sexes, income levels, urbanization levels, numbers of antidiabetic drug types used, antidiabetic drugs used, aDCSI scores, and new or prevalent statin use. The reductions in all-cause mortality observed in the sensitivity analysis were similar to those obtained in the primary analysis (Table 3).

3. Discussion

This study presents novel findings on the dose-dependent effects, specific class, and intensity of statin use on all-cause mortality in patients with type 2 diabetes. This study is the leading study to provide real-world evidence showing that persistent statin use, particularly at higher cumulative doses per year, is associated with reduced all-cause mortality in these patients. The study also identifies the optimal daily dose of statins as 0.86 DDD, which is associated with the lowest mortality. Additionally, the study ranks the priority of protective effects on mortality for different classes of statins, with pitavastatin demonstrating the highest protective effects, followed by rosuvastatin, pravastatin, simvastatin, atorvastatin, fluvastatin, and lovastatin. These novel findings clarify the protective effects of dose-dependence and intensity on statin users and specific classes of statin use on mortality in patients with type 2 diabetes, which has not been previously investigated [14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29].
A recent meta-analysis showed that statin use significantly reduced the risk of CVD events and stroke, but not all-cause mortality, in individuals with diabetes undergoing both primary and secondary prevention [31]. The outcomes seemed different from ours. The potential reasons might be that our study focused on the association between statin use and all-cause mortality specifically in individuals with type 2 diabetes. In contrast, Yang XH et al.’s meta-analysis assessed the effect of statin use on a broader range of outcomes, including heterogeneous endpoints such as CVD events and stroke, which were different primary endpoints. Furthermore, the meta-analysis used a heterogeneous study design, including RCTs, observational cohort studies, and retrospective studies. The meta-analysis also included a population that was not solely comprised of individuals with type 2 diabetes, which limited the extrapolation of results to this specific patient population. In addition, our study used a different methodology, which was very large and adjusted for potential confounding factors using IPTW Cox regression models, whereas the meta-analysis may have used different statistical techniques. The meta-analysis did not provide data on the dose, intensity, or class of statin use, whereas our study presented novel findings on the dose-dependent effects, specific class, and intensity of statin use on all-cause mortality in patients with type 2 diabetes.
Numerous studies, both observational and randomized controlled trials (RCTs), have suggested that there is a correlation between the use of statins and a decrease in all-cause mortality in individuals with diabetes [14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]. The results of these studies are debatable because they did not clarify the statin dosage, intensity, or classes used; moreover, they used a small sample size with heterogeneous endpoints and an insufficient follow-up duration and did not classify patients based on their diabetes type [26,27,28,29]. The present study is the first to verify the preventive properties of various classes and use intensities of statins against all-cause mortality in patients diagnosed with type 2 diabetes. We used an IPTW design to estimate the long-term overall survival of patients using specific statin classes at different dosages (cDDD-year) and intensities (>1 or ≤1 DDD); we also estimated the optimal daily dose (DDD) of statin for type 2 diabetes. Our results demonstrated a significant reduction in all-cause mortality among pitavastatin, rosuvastatin, pravastatin, simvastatin, atorvastatin, fluvastatin, and lovastatin users. Moreover, a significant reduction was noted in all-cause mortality among users of Q1, Q2, Q3, and Q4 cDDD-year of statin. Regardless of age, sex, income level, urbanization level, number of antidiabetic drugs used, type of antidiabetic drug used, aDCSI score, comorbidities, and CCI score, statin use at ≥28 cDDD-year significantly reduced all-cause mortality. Compared with no statin use, pitavastatin had the highest protective effects against mortality, followed by rosuvastatin, pravastatin, simvastatin, atorvastatin, fluvastatin, and finally, lovastatin. Moreover, the optimal statin dose was noted to be 0.86 DDD, which was associated with the lowest mortality.
To date, no study has compared the impact of different statin classes on all-cause mortality in individuals with type 2 diabetes. The current study is the first to demonstrate the order of intensity by which specific statin classes affect mortality in patients with type 2 diabetes: pitavastatin > rosuvastatin > pravastatin > simvastatin > atorvastatin > fluvastatin > lovastatin. The mechanisms underlying this order may be associated with the effects of each statin on high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglycerides [32,33,34]. For instance, rosuvastatin is slightly more potent than atorvastatin [32,33]; it is also significantly more potent than pravastatin, simvastatin, atorvastatin, fluvastatin, and lovastatin [33,34]. At maximal prescribed doses, rosuvastatin provides a greater LDL reduction than other statins [33,34]. Statin therapy alters HDL levels, typically by increasing them. However, these effects may vary by the statin type and dose [35]. For instance, simvastatin and rosuvastatin increase HDL levels with an increase in the dose, whereas an increase in HDL levels is noted at a high dose of atorvastatin [35]. Moreover, in patients with hypercholesterolemia, rosuvastatin is more effective at decreasing triglycerides than are other statins [33]. The magnitude of the triglyceride-decreasing effect of statins may be as high as 40%–44% in patients with hypertriglyceridemia [32,33,34,35]. However, the association of specific statins’ potency and effects on LDL, HDL, and triglycerides with mortality remains unclear. In the current study, this appeared be in proportion with the order of intensity of the statins’ effects in patients with type 2 diabetes (Table 2 and Figure 1). Moreover, certain statins, such as fluvastatin, pitavastatin, and pravastatin, are associated with a lower risk of drug interactions and muscle toxicity compared to other statins. For example, pravastatin, fluvastatin, rosuvastatin, and pitavastatin do not undergo CYP3A4 metabolism; therefore, fewer pharmacokinetic drug interactions are expected with these agents [36,37]. In general, patients with type 2 diabetes tend to use different types of medications (Table 1); therefore, statins, such as pitavastatin, demonstrating few drug–drug interactions, might be preferable [36,37]. Although the underlying mechanisms remain unclear, statins with fewer drug–drug interactions, such as pitavastatin [36,37], or those with stronger LDL and triglyceride-lowering and HDL-increasing effects, such as rosuvastatin [32,33,34], might be ideal for use in patients with type 2 diabetes. However, the sample size of pitavastatin users in our study was small; therefore, the current conclusion might be biased, and further research is warranted.
The intensity and daily dose of statin use is complicated by LDL, HDL, and triglycerides because the protective effects of DDD on LDL, HDL, and triglycerides exhibit U-shaped dose–response relationships (Figure 3) [35,38]. Thus, the U-shaped dose–response relationship has been noted for not only the pharmacological effects but also the toxicologic effects of statins on mortality (Figure 3) [30]; this relationship was also noted in the current study: the higher the daily statin dose, the higher the protective effect [39]. In the current study, the optimal DDD was 0.86 for statin users because it was associated with the lowest all-cause mortality, a result compatible with the U-shaped dose–response relationship noted in previous biological, toxicological, and pharmacological studies [30]. Individual variability in the response to and side effects of statins may be related to differences in drug metabolism rates that stem from genetic variations [40,41,42]. For instance, certain genetic differences such as the absence of CYP2D6, a member of the cytochrome P450 superfamily of drug oxidizing enzymes, in 7% of Caucasian and African–American individuals, can impact drug metabolism rates, whereas CYP2D6 deficiency is rare among Asian individuals. Asian (mostly Chinese, Japanese, and Korean) individuals may have a higher response to low statin doses than do Caucasian individuals [41]. In Asian individuals, the initial daily dose of statins should ideally be lower than that in individuals of other ethnicities [41,43]; this is corroborated by the optimal statin DDD noted in the current study.
We investigated the potential impact of different cumulative doses of continuous, discontinuous, or cDDD-year statin use on LDL, HDL, and triglycerides, as well as their effects on all-cause mortality in patients with type 2 diabetes. The analysis revealed that a higher cDDD-year of statin usage corresponded with a lower all-cause mortality in this patient population. Additionally, we explored the influence of specific levels of statin dosage, namely >1 and ≤1 DDD, and found that both levels of use resulted in a significant reduction in all-cause mortality, with ≤1 DDD demonstrating a higher reduction than >1 DDD. These findings may align with the U-shaped relationship previously established between statin effects and LDL [30,38].
The paper from Scicchitano P et al. (2014) highlights the potential role of nutraceuticals in improving dyslipidemia, a major cardiovascular risk factor for coronary heart disease [44]. The authors suggest that nutraceuticals and functional food ingredients may be useful in reducing overall cardiovascular risk induced by dyslipidemia, acting either parallel to statins or as adjuvants in cases where statins cannot be used or fail. The potential mechanisms by which nutraceuticals may act on lipids include reducing 7α-hydroxylase, increasing the fecal excretion of cholesterol, decreasing 3-hydroxy-3-methylglutaryl-CoA reductase mRNA levels, or reducing the secretion of very low-density lipoprotein. However, the exact mechanisms are not yet fully understood. While nutraceuticals may have potential benefits in improving dyslipidemia, the use of these compounds in type 2 diabetes patients is not paid by the National Health Insurance. Moreover, the effects of nutraceuticals on the primary endpoint of all-cause mortality in type 2 diabetes patients are still controversial, and it is unclear whether nutraceutical use is a confounding factor in determining all-cause mortality in type 2 diabetes patients. Therefore, while the potential role of nutraceuticals in improving dyslipidemia is promising, more research is needed to fully understand their effects on type 2 diabetes patients, particularly in relation to mortality outcomes. In the context of this study, the effects of nutraceuticals on the primary endpoint of all-cause mortality in type 2 diabetes patients were not examined, and their potential influence on the results of the study cannot be fully assessed.
It is important to note that in the real-world database used for this study, all type 2 diabetes patients receive treatments based on the professional physicians who prescribe medications for the patients according to diabetes guidelines and are monitored by peer reviewers in Taiwan. If the prescriptions are found to be against the regulations and coverage of NHI, then physicians face punishment and are not paid. Therefore, it is difficult to analyze all pharmacological compounds in the real-world database as not all drugs are covered by Taiwan NHI. However, all antidiabetic drugs were considered and adjusted in the type 2 diabetes population to achieve balance between the case and control groups. After PSM, only statin use was found to be different between the case and control groups (Table 1). While it would be ideal to include all pharmacological compounds in the analysis, it was not feasible in this study due to the limitations of the real-world database. Nevertheless, the effect of statin use on all-cause mortality in type 2 diabetes patients has been well established in previous studies and was included in the multivariate regression analysis.
The main strength of the current study is the large sample size. We also considered the intensity of statin use (>1 DDD (continuous) or ≤1 DDD (discontinuous)) and analyzed it by using a sensitivity analysis, and it was adjusted using a Cox hazard model. Regardless of statin use intensity, statin users had decreased all-cause mortality compared with nonusers. In contrast to the previous relevant studies [14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29], our study obtained reliable real-world evidence through long-term follow-up, which demonstrated that persistent statin use reduces all-cause mortality in patients with type 2 diabetes (Figure 1, Figure 2 and Figure 4). We also noted that the optimal daily statin dose was 0.86 DDD (Figure 2). Moreover, pitavastatin demonstrated the most protective effect, followed by rosuvastatin, pravastatin, simvastatin, atorvastatin, fluvastatin, and lovastatin (Table 2 and Figure 1).
This study has several limitations. Firstly, the data were obtained from a claims database, which means that we could not collect detailed information such as the blood and lipid profiles of each patient, and thus, we could not evaluate whether changes in lipid profiles after initiating statin treatment were associated with mortality. Secondly, we could not eliminate the possibility of selection bias due to unmeasured confounders, as statin users may differ from nonusers. To address this, we used an IPTW Cox hazard model to balance the differences in the covariates and conducted subgroup analyses. We found that the reductions in mortality with statin use were consistent across various subgroups. Thirdly, we were unable to collect information on the body mass index, dietary information, and other lifestyle factors at the time of type 2 diabetes diagnosis. Fourthly, it is possible that the study’s findings may not be generalizable to frail individuals who may not attend regular health check-ups or who may not be prescribed statins due to their frailty. Fifth, small event numbers in some subgroups that used a single type of statin limited the statistical power of our results. Sixth, we could not analyze the use of self-pay nutraceuticals, which are not covered by the NHI. However, the effects of nutraceuticals on all-cause mortality in type 2 diabetes patients remain controversial, and their use as a confounding factor for all-cause mortality is still unclear. Finally, we relied on a sample population that was 95% Han Chinese, which may not be entirely generalizable to other ethnic groups [45]. It is worth noting that the prevalence of statin use varies by region, with usage rates of approximately 76.5%, 69.9%, and 60.5% in North America, western Europe, and Asia, respectively [46]. As a result, populations of other ethnicities with high rates of statin use may yield slightly different outcomes than our results suggest. Nevertheless, other studies conducted in various ethnic populations have indicated a decrease in the risk of mortality related to statin use [14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29].

4. Methods

4.1. Study Population

A population-based cohort study was carried out utilizing the Taiwan National Health Insurance (NHI) Research Database (NHIRD). All beneficiaries’ medical claims data pertaining to disease diagnoses, procedures, drug prescriptions, demographics, and enrollment profiles are included in the NHIRD [47]. The NHIRD data are linked by encrypted patient identifiers, and it also includes the vital status and cause of death of each patient, extracted from Taiwan’s death registry.
The cohort enrolled in our study consisted solely of patients aged ≥40 years who had been diagnosed with type 2 diabetes between 2008 and 2020. Patients with missing data on the age at diagnosis or date of diagnosis were excluded. Moreover, we excluded patients who used multiple classes of statins during the follow-up period. The index date was the date of statin use (≥28 cDDD-year). The observation period for each patient began from the index date and continued until death, or the end of the study period (31 December 2021). Patients with T2DM who were prescribed ≥28 cDDD-year of statins with a prescription duration of >1 months were included in the case group, and those who were prescribed 0 cDDD of statins during the follow-up period were included in the control group. The Institutional Review Board of Tzu-Chi Medical Foundation reviewed and granted approval of the study protocols (IRB109-015-B).

4.2. Study Covariates

We included other covariates to adjust for potential confounding effects. Patients were divided into the following age groups: 40 to 50, 51 to 60, 61 to 70, and ≥71 years at the index date. To reduce the effects of potential confounders when comparing all-cause mortality between the statin user and nonuser groups, we used the inverse probability of treatment-weighted (IPTW) [48]. We used the date of statin use (≥28 cDDD-year) as the index date and matched statin nonusers by using variables collected at this index date. The factors included age, sex, income level, urbanization level, number of antidiabetic drug types used, antidiabetic drugs used, diabetes severity (based on adapted Diabetes Complications Severity Index score), and comorbidities, which were determined based on International Classification of Diseases codes. Comorbidity onsets over one year before the index date were recorded. Continuous variables are presented as means ± standard deviations or medians (first quartile, third quartile) where appropriate. Charlson’s comorbidity index (CCI) score was also calculated, with repeat comorbidities excluded to avoid repetitive adjustments in multivariate analysis. The flowchart depicting the study selection process is presented as Supplemental Figure S1.

4.3. Outcome Variables

The primary variable of interest in this study was mortality due to any cause, which was identified using information from the death registry after the diagnosis of type 2 diabetes.

4.4. Statin Use

Pharmaceutical claims data on statin prescriptions were retrieved using Anatomical Therapeutic Chemical (ATC) codes from the NHIRD. To examine the major exposures of interest, lipophilic (atorvastatin, fluvastatin, lovastatin, simvastatin, and pitavastatin) and hydrophilic (pravastatin and rosuvastatin) statins were selected based on the ATC classification system [49]. Data on statin use initiated 1 year prior to type 2 diabetes diagnosis were extracted to differentiate prevalent and new users. We also evaluated statin use intensity by estimating the average statin dose as the defined daily dose (DDD) divided by the total prescription days. Statin use intensity was categorized into two groups: average daily doses below or above 1 DDD. Additionally, patients were divided into four subgroups based on quartiles (Qs) of cDDD-year. All analyses were adjusted for covariates, including age group, sex, income level, urbanization level, number of antidiabetic drug types used, antidiabetic drugs used, aDCSI score, comorbidities, and CCI score to reduce potential confounding effects on the outcome variable of all-cause mortality, as determined by the cause of death data in the death registry after type 2 diabetes diagnosis.

4.5. Statistical Analysis

A time-dependent Cox hazard model was utilized to evaluate overall survival in relation to statin use, adjusted for age group, sex, income level, urbanization level, number of antidiabetic drug types used, antidiabetic drugs used, aDCSI score, comorbidities, and CCI score. Statin prescriptions were collected every 3 months as a time-dependent variable to determine a user’s status, with “event-free” person-times of users before their first statin prescription and during the 3-month period without a statin prescription considered unexposed follow-up time points. Overall survival risk was also estimated for individual statins. Subgroup analyses, adjusted for baseline characteristics, were performed using stratification instead of weighting and postdiagnosis statin use, with similar results obtained. All-cause mortality was estimated using the Kaplan–Meier method, and the stratified log-rank test was employed to compare survival curves between statin users and nonusers (Figure 4), and between nonusers and statin users using different statin dosages and classes (Figure 1 and Figure 2). SAS (version 9.4; SAS Institute, Cary, NC, USA) was used for all statistical analyses.

5. Conclusions

In conclusion, our real-world evidence indicated that persistent statin use (≥28 cDDD-year) may reduce all-cause mortality in patients with type 2 diabetes: the higher the cDDD-year of statin use, the lower the all-cause mortality. The optimal daily statin dose, which led to the lowest all-cause mortality, was 0.86 DDD. Moreover, the protective effect against mortality was the highest in with the use of pitavastatin, followed by rosuvastatin, pravastatin, simvastatin, atorvastatin, fluvastatin, and, finally, lovastatin.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ph16040507/s1, Figure S1: Study flow-chart.

Author Contributions

Conception and Design: J.-M.Y., W.-M.C., M.C., B.-C.S. and S.-Y.W.; Collection and Assembly of Data: S.-Y.W.; Data Analysis and Interpretation: W.-M.C., J.-M.Y., B.-C.S. and S.-Y.W.; Administrative Support: S.-Y.W.; Manuscript Writing: S.-Y.W. and J.-M.Y. All authors have read and agreed to the published version of the manuscript.

Funding

Lo-Hsu Medical Foundation, LotungPoh-Ai Hospital, supports Szu-Yuan Wu’s work (Funding Number: 10908, 10909, 11001, 11002, 11003, 11006, and 11013).

Institutional Review Board Statement

The study protocols were reviewed and approved by the Institutional Review Board of Tzu-Chi Medical Foundation (IRB109-015-B).

Informed Consent Statement

Not applicable.

Data Availability Statement

Data analyzed during the study were provided by a third party. Requests for data should be directed to the provider indicated in the Acknowledgments.

Acknowledgments

Lo-Hsu Medical Foundation, LotungPoh-Ai Hospital, supports Szu-Yuan Wu’s work (Funding Number: 110908, 10909, 11001, 11002, 11003, 11006; The data sets supporting the study conclusions are included in the manuscript. We used data from the National Health Insurance Research Database and Taiwan Cancer Registry database. The authors confirm that, for approved reasons, some access restrictions apply to the data underlying the findings. The data used in this study cannot be made available in the manuscript, the supplemental files, or in a public repository due to the Personal Information Protection Act executed by Taiwan’s government, starting in 2012. Requests for data can be sent as a formal proposal to obtain approval from the ethics review committee of the appropriate governmental department in Taiwan. Specifically, links regarding contact info for which data requests may be sent to are as follows: http://nhird.nhri.org.tw/en/Data_Subsets.html#S3 and http://nhis.nhri.org.tw/point.html (accessed on 22 May 2019).

Conflicts of Interest

The authors have no potential conflict of interest to declare. The data sets supporting the study conclusions are included in the manuscript.

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Figure 1. Kaplan–Meier overall survival curves of patients with type 2 diabetes who used different classes of statins.
Figure 1. Kaplan–Meier overall survival curves of patients with type 2 diabetes who used different classes of statins.
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Figure 2. Kaplan–Meier overall survival curves of patients with type 2 diabetes who used different cDDD-year of statins.
Figure 2. Kaplan–Meier overall survival curves of patients with type 2 diabetes who used different cDDD-year of statins.
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Figure 3. DDD of statin use vs. HRs for all-cause mortality.
Figure 3. DDD of statin use vs. HRs for all-cause mortality.
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Figure 4. Kaplan–Meier overall survival curves of patients with type 2 diabetes who used and did not use statins.
Figure 4. Kaplan–Meier overall survival curves of patients with type 2 diabetes who used and did not use statins.
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Table
Table 1. Baseline characteristics of type 2 diabetes cohort: overall and stratified by statin use.
Table 1. Baseline characteristics of type 2 diabetes cohort: overall and stratified by statin use.
NonusersUserspASMD
N = 427,407N = 422,380
Characteristicn%n%
Age, mean ± SD, years56.85 ± 20.9756.92 ± 19.240.8520
Age, median (IQR), years56.00 (46.00, 68.00)56.00 (48.00, 68.00)0.9999
Age group, years 0.08440.0046
≤50143,91133.67%141,19433.43%
51–60112,25126.26%111,04626.29%
61–7086,43020.22%86,05720.37%
≥7184,81519.84%84,08319.91%
Sex 0.69460.0004
Female202,04147.27%199,48547.23%
Male225,36652.73%222,89552.77%
Income levels (NTD) 0.62130.0008
Low income68601.61%67021.59%
Financially dependent135,05731.60%133,54831.62%
≤20,000202,25047.32%200,46247.46%
20,001–30,00038,8339.09%38,0889.02%
30,001–45,00028,0276.56%27,5106.51%
>45,00016,3803.83%16,0703.80%
Urbanization 0.94440.0001
Rural121,99528.54%120,58928.55%
Urban305,41271.46%301,79171.45%
Number of antidiabetic drug types used 0.07010.0009
0156,61136.64%155,80436.89%
1105,74224.74%104,72524.79%
2105,36224.65%103,28024.45%
343,35010.14%42,55110.07%
≥416,3423.82%16,0203.79%
Antidiabetic drugs used
Insulin45,21910.58%44,74310.59%0.94850.0002
Metformin183,18643.86%181,48742.97%0.59200.0007
SU206,95048.42%204,77748.48%0.39720.0006
AGI34790.81%34730.82%0.44620.0001
TZD27,0546.33%26,9506.38%0.66420.0002
DPP4i21,0714.93%20,9034.95%0.79500.0002
SGLT2i4880.11%4640.11%0.94290.0001
Others24,6615.78%24,4125.78%0.96520.0001
aDCSI score
Mean ± SD1.00 ± 1.891.03 ± 1.440.5461
Median (IQR)0.00 (0.00, 2.00)0.00 (0.00, 2.00)0.5659
aDCSI score 0.79670.0059
0219,61851.38%217,41951.47%
189,00920.83%87,66220.75%
265,17315.25%64,27315.22%
≥353,60712.54%53,02612.55%
Retinopathy24,6615.77%24,3955.78%0.89360.0004
Nephropathy50,64711.85%50,11811.87%0.88510.0002
Neuropathy44,45010.40%44,13010.45%0.30640.0008
Cerebrovascular45,51810.65%45,22610.71%0.74080.0002
Cardiovascular113,94626.66%113,55926.89%0.88630.0002
Peripheral vascular disease16,1133.77%15,9143.77%0.99400.0001
Metabolic disorder77381.81%77341.83%0.80460.0001
Comorbidities
Hypertension219,83351.43%217,36051.46%0.80530.0003
Coronary artery disease96,75422.64%95,26122.55%0.35410.0008
Stroke62,38814.60%61,60214.58%0.86970.0001
Depression28,1126.58%28,0356.64%0.26450.0006
Anxiety59,00613.81%58,62413.88%0.32450.0007
Heart failure28,6866.71%28,5086.75%0.48970.0004
Peripheral vascular disease92212.16%90912.15%0.86910.0001
COPD88,20920.64%86,83920.56%0.36980.0008
Atrial fibrillation94952.22%93282.21%0.68410.0001
Traumatic head injury26,0036.08%25,6966.08%0.99550.0000
Hearing loss11,3592.66%11,3652.69%0.34640.0003
Sleep apnea24230.57%23490.56%0.50360.0001
Liver cirrhosis119,97328.07%118,67428.10%0.22040.0023
SLE65921.54%65471.55%0.77490.0001
CCI scores
Mean ± SD1.10 ± 2.101.20 ± 1.580.1397
Median (Q1, Q3)0.00 (0.00, 2.00)1.00 (0.00, 2.00)0.9628
CCI scores 0.07850.0019
0229,90553.79%226,39753.60%
≥1197,50346.21%195,98346.40%
Different classes of statins
Lipophilic statins
Atorvastatin00.00%151,55335.88%
Lovastatin00.00%30,5677.24%
Simvastatin00.00%83,99519.89%
Fluvastatin00.00%39,7119.40%
Pitavastatin00.00%28300.67%
Hydrophilic statins
Rosuvastatin00.00%82,59119.55%
Pravastatin00.00%31,1347.37%
cDDD-year of statins
Q100.00%118,54128.06%
Q200.00%109,87326.01%
Q300.00%101,28223.98%
Q400.00%98,68421.94%
DDD
≤100.00%143,14133.89%
>100.00%279,23966.11%
Stain use
New use (after type 2 diabetes diagnosis)00.00%384,10890.94%
Prevalent use (before type 2 diabetes diagnosis)00.00%38,2729.06%
Time from type 2 diabetes diagnosis to statins exposure
Mean ±SD follow-up 2.42 ± 2.69
Median (IQR) follow-up 1.33 (0.07, 4.19)
Follow-up duration
Mean ± SD follow-up8.04 ± 3.129.48 ± 1.76<0.0001
Median (IQR) follow-up8.97 (5.66, 9.33)9.65 (7.58, 9.76)<0.0001
All-cause mortality <0.0001
No308,64372.21%371,57687.97%
Yes118,76527.79%50,80412.03%
Abbreviations: ASMD, absolute standardized mean difference; SD, standard deviation; IQR, interquartile range; Q, quartile; DDD, defined daily dose; AIDS, acquired immunodeficiency syndrome; CCI, Charlson’s comorbidity index; COPD, chronic obstructive pulmonary disease; SLE, systemic lupus erythematosus; NTD, New Taiwan Dollar; aDCSI, adapted Diabetic Complication Severity Index; SU, sulfonylureas; AGI, alpha-glucosidase inhibitor; TZD, thiazolidinedione; DPP4i, dipeptidyl peptidase 4 inhibitor; SGLT2i, sodium–glucose cotransporter-2 inhibitor.
Table
Table 2. All-cause mortality and aHRs for statin use in patients with type 2 diabetes.
Table 2. All-cause mortality and aHRs for statin use in patients with type 2 diabetes.
VariablesCrude HR (95%CI)paHR (95%CI) *p
Stain user or nonusers
NonusersReference
Users0.37(0.36, 0.37)<0.00010.32(0.31, 0.33)<0.0001
Different classes of statins
NonusersReference
Hydrophilic statins
Rosuvastatin0.32(0.31, 0.34)<0.00010.29(0.28, 0.31)<0.0001
Pravastatin0.31(0.3, 0.32)<0.00010.28(0.27, 0.29)<0.0001
Lipophilic statins
Atorvastatin0.05(0.03, 0.07)<0.00010.06(0.04, 0.09)<0.0001
Lovastatin0.47(0.45, 0.48)<0.00010.36(0.35, 0.38)<0.0001
Simvastatin0.34(0.33, 0.35)<0.00010.31(0.30, 0.32)<0.0001
Fluvastatin0.58(0.56, 0.61)<0.00010.48(0.47, 0.50)<0.0001
Pitavastatin0.36(0.36, 0.37)<0.00010.31(0.31, 0.32)<0.0001
cDDD-year of statins
NonusersReference
Q10.61(0.6, 0.62)<0.00010.51(0.5, 0.52)<0.0001
Q20.41(0.4, 0.42)<0.00010.36(0.35, 0.37)<0.0001
Q30.27(0.26, 0.27)<0.00010.24(0.23, 0.25)<0.0001
Q40.15(0.14, 0.15)<0.00010.13(0.13, 0.14)<0.0001
p for trend <0.0001 <0.0001
Abbreviations: aHR, adjusted hazard ratio; HR, hazard ratio, CI, confidence interval; DDD, defined daily dose; Q, quartile. * aHR was derived from the inverse probability treatment-weighted Cox model considering statin use as a time-dependent covariate and was adjusted for age group, sex, income level, urbanization, antidiabetic drug type, antidiabetic drug use, aDCSI score, comorbidities, and CCI score.
Table
Table 3. Sensitivity analyses for statin use–all-cause mortality association in patients with type 2 diabetes.
Table 3. Sensitivity analyses for statin use–all-cause mortality association in patients with type 2 diabetes.
Subpopulation or ExposureNo. of Patients All-Cause Mortality
No. of DeathsaHR *95% CIp
Age group, years
≤50285,105 23,316 0.29(0.28–0.30)<0.0001
51–60223,297 27,319 0.31(0.30–0.32)<0.0001
61–70172,487 37,672 0.33(0.32–0.34)<0.0001
≥71168,898 81,260 0.32(0.32–0.33)<0.0001
Sex
Female401,526 68,131 0.3(0.30–0.31)<0.0001
Male448,261 101,438 0.33(0.33–0.34)<0.0001
Income levels (NTD)
Low income13,562 4936 0.35(0.32–0.38)<0.0001
Financially dependent268,604 62,198 0.33(0.32–0.33)<0.0001
≤20,000402,713 90,946 0.31(0.31–0.32)<0.0001
20,001–30,00076,921 5847 0.34(0.31–0.36)<0.0001
30,001–45,00055,537 3713 0.32(0.29–0.35)<0.0001
>45,00032,450 1928 0.41(0.36–0.47)<0.0001
Urbanization
Rural242,584 58,568 0.31(0.30–0.32)<0.0001
Urban607,203 111,001 0.33(0.32–0.33)<0.0001
Number of antidiabetic drug types used
0312,415 50,615 0.33(0.32–0.34)<0.0001
1210,467 43,730 0.30(0.29–0.31)<0.0001
2208,642 40,260 0.33(0.32–0.34)<0.0001
385,901 24,499 0.31(0.30–0.32)<0.0001
≥432,362 10,464 0.33(0.31–0.35)<0.0001
aDCSI score
0437,037 53,522 0.31(0.31–0.32)<0.0001
1176,671 27,167 0.36(0.34–0.37)<0.0001
2129,446 39,528 0.29(0.28–0.30)<0.0001
≥3106,633 49,352 0.33(0.32–0.34)<0.0001
CCI scores
0437,037 53,522 0.31(0.31–0.32)<0.0001
≥1393,486 105,134 0.30(0.29–0.30)<0.0001
Coexisting comorbidities
Hypertension437,193 112,774 0.33(0.32–0.34)<0.0001
Coronary artery disease192,015 50,785 0.30(0.29–0.31)<0.0001
Stroke123,990 58,964 0.34(0.33–0.34)<0.0001
Depression56,147 13,352 0.32(0.30–0.34)<0.0001
Anxiety117,630 24,118 0.33(0.31–0.34)<0.0001
Heart failure57,194 27,547 0.32(0.31–0.34)<0.0001
Peripheral vascular disease18,312 6472 0.34(0.31–0.36)<0.0001
COPD175,048 56,398 0.31(0.30–0.32)<0.0001
Atrial fibrillation18,823 10,415 0.35(0.33–0.37)<0.0001
Traumatic head injury51,699 15,134 0.29(0.27–0.30)<0.0001
Hearing loss22,724 6519 0.32(0.30–0.35)<0.0001
Sleep apnea4772 840 0.33(0.27–0.42)<0.0001
Liver cirrhosis237,795 46,407 0.29(0.28–0.30)<0.0001
SLE13,139 2879 0.31(0.27–0.34)<0.0001
DDD
≤1560,998 137,268 0.36(0.35–0.37)<0.0001
>1288,789 32,300 0.50(0.46–0.53)<0.0001
Stain use
New use (after type 2 diabetes diagnosis)803,889 159,321 0.31(0.31–0.32)<0.0001
Prevalent use (before type 2 diabetes diagnosis)45,898 10,247 0.28(0.26–0.29)<0.0001
Metformin use357,572 69,229 0.35(0.34–0.36)<0.0001
Abbreviations: ASMD, absolute standardized mean difference; SD, standard deviation; IQR, interquartile range; Q, quartile; DDD, defined daily dose; AIDS, acquired immunodeficiency syndrome; CCI, Charlson’s comorbidity index; COPD, chronic obstructive pulmonary disease; SLE, systemic lupus erythematosus; NTD, New Taiwan Dollar; aDCSI, adapted Diabetic Complication Severity Index; SU, sulfonylureas; AGI, alpha-glucosidase inhibitor; TZD, thiazolidinedione; DPP4i, dipeptidyl peptidase 4 inhibitor; SGLT2i, sodium–glucose cotransporter-2 inhibitor; aHR, adjusted hazard ratio; HR, hazard ratio; CI, confidence interval. * The aHR was derived from the inverse probability treatment-weighted Cox regression model considering statin use as a time-dependent covariate and was adjusted for age group, sex, income level, urbanization, antidiabetic drug type, antidiabetic drug use, aDCSI score, comorbidity, and CCI score.
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MDPI and ACS Style

Yu, J.-M.; Chen, W.-M.; Chen, M.; Shia, B.-C.; Wu, S.-Y. Effects of Statin Dose, Class, and Use Intensity on All-Cause Mortality in Patients with Type 2 Diabetes Mellitus. Pharmaceuticals 2023, 16, 507. https://doi.org/10.3390/ph16040507

AMA Style

Yu J-M, Chen W-M, Chen M, Shia B-C, Wu S-Y. Effects of Statin Dose, Class, and Use Intensity on All-Cause Mortality in Patients with Type 2 Diabetes Mellitus. Pharmaceuticals. 2023; 16(4):507. https://doi.org/10.3390/ph16040507

Chicago/Turabian Style

Yu, Jung-Min, Wan-Ming Chen, Mingchih Chen, Ben-Chang Shia, and Szu-Yuan Wu. 2023. "Effects of Statin Dose, Class, and Use Intensity on All-Cause Mortality in Patients with Type 2 Diabetes Mellitus" Pharmaceuticals 16, no. 4: 507. https://doi.org/10.3390/ph16040507

APA Style

Yu, J. -M., Chen, W. -M., Chen, M., Shia, B. -C., & Wu, S. -Y. (2023). Effects of Statin Dose, Class, and Use Intensity on All-Cause Mortality in Patients with Type 2 Diabetes Mellitus. Pharmaceuticals, 16(4), 507. https://doi.org/10.3390/ph16040507

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