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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Pharmacol.</journal-id>
<journal-title>Frontiers in Pharmacology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Pharmacol.</abbrev-journal-title>
<issn pub-type="epub">1663-9812</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">786203</article-id>
<article-id pub-id-type="doi">10.3389/fphar.2022.786203</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Pharmacology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Chronic Kidney Disease Progression Risk in Patients With Diabetes Mellitus Using Dihydropyridine Calcium Channel Blockers: A Nationwide, Population-Based, Propensity Score Matching Cohort Study</article-title>
<alt-title alt-title-type="left-running-head">Lin et&#x20;al.</alt-title>
<alt-title alt-title-type="right-running-head">CCBs on CKD Progression</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Lin</surname>
<given-names>Shih-Yi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1274898/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lin</surname>
<given-names>Cheng-Li</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/459023/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lin</surname>
<given-names>Cheng-Chieh</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/932822/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hsu</surname>
<given-names>Wu-Huei</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/693316/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hsu</surname>
<given-names>Chung-Y.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/867325/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Kao</surname>
<given-names>Chia-Hung</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<xref ref-type="aff" rid="aff8">
<sup>8</sup>
</xref>
<xref ref-type="aff" rid="aff9">
<sup>9</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/370980/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Graduate Institute of Biomedical Sciences</institution>, <institution>College of Medicine</institution>, <institution>China Medical University</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Division of Nephrology and Kidney Institute</institution>, <institution>China Medical University Hospital</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Management Office for Health Data</institution>, <institution>China Medical University Hospital</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>College of Medicine</institution>, <institution>China Medical University</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Department of Family Medicine</institution>, <institution>China Medical University Hospital</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>Department of Chest Medicine</institution>, <institution>China Medical University Hospital</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>Department of Nuclear Medicine</institution>, <institution>PET Center</institution>, <institution>China Medical University Hospital</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff8">
<sup>8</sup>
<institution>Department of Bioinformatics and Medical Engineering</institution>, <institution>Asia University</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff9">
<sup>9</sup>
<institution>Center of Augmented Intelligence in Healthcare</institution>, <institution>China Medical University Hospital</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1287331/overview">Carlos Alves</ext-link>, University of Coimbra, Portugal</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/901073/overview">Fu-Shun Yen</ext-link>, Dr. Yen&#x2019;s Clinic, Taiwan</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1350331/overview">Diogo Mendes</ext-link>, AIBILI&#x2014;Association for Innovation and Biomedical Research on Light and Image, Portugal</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Chia-Hung Kao, <email>d10040@mail.cmuh.org.tw</email>
</corresp>
<fn fn-type="other">
<p>This article was submitted to Pharmacoepidemiology, a section of the journal Frontiers in Pharmacology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>09</day>
<month>03</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>13</volume>
<elocation-id>786203</elocation-id>
<history>
<date date-type="received">
<day>29</day>
<month>09</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>22</day>
<month>02</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Lin, Lin, Lin, Hsu, Hsu and Kao.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Lin, Lin, Lin, Hsu, Hsu and Kao</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these&#x20;terms.</p>
</license>
</permissions>
<abstract>
<p>
<bold>Background:</bold> Whether diabetes mellitus (DM) patients with chronic kidney disease (CKD) can glean individual renal benefit from dihydropyridine calcium channel blockers (DCCBs) remains to be determined. We conducted a nationwide, population-based, propensity score matching cohort study to examine the effect of DCCBs on CKD progression in DM patients with&#x20;CKD.</p>
<p>
<bold>Methods:</bold> One million individuals were randomly sampled from Taiwan&#x2019;s National Health Insurance Research Database. The study cohort consisted of DM patients with CKD who used DCCBs. The comparison cohort was propensity-matched for demographic characteristics and comorbidities. The endpoint was advanced CKD or end-stage renal disease (ESRD). The Cox proportional hazards model was used to calculate the&#x20;risks.</p>
<p>
<bold>Results:</bold> In total, 9,761 DCCB users were compared with DCCB nonusers at a ratio of 1:1. DCCB users had lower risk of advanced CKD and ESRD than nonusers&#x2014;with adjusted hazard ratio [aHR; 95% confidence interval (CI)] of 0.64 (0.53&#x2013;0.78) and 0.59 (95% CI, 0.50&#x2013;0.71) for advanced CKD and ESRD, respectively. DCCB users aged &#x2265;65&#xa0;years had the lowest incidence rates of advanced CKD and ESRD&#x2014;with aHR (95% CI) of 0.47 (0.34&#x2013;0.65) and 0.48 (0.35&#x2013;0.65) for advanced CKD and ESRD, respectively. Finally, cumulative DCCB use for &#x3e;1,100&#xa0;days was associated with the lowest advanced CKD and ESRD risks [(aHR, 0.29 (95% CI, 0.19&#x2013;0.44)].</p>
<p>
<bold>Conclusion:</bold> DM patients with CKD who used DCCBs had lower risk of progression to advanced CKD and ESRD than nonusers&#x20;did.</p>
</abstract>
<kwd-group>
<kwd>NHIRD: national health insurance</kwd>
<kwd>diabetes mellitus (DM)</kwd>
<kwd>chronic kidney disease (CKD)</kwd>
<kwd>dihydropyridine calcium channel blockers (DCCBs)</kwd>
<kwd>end-stage renal disease (ESRD)</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>Dihydropyridine calcium channel blockers (DCCBs), which bind to calcium channels located on vascular smooth muscles to interrupt calcium entry, are widely used in clinical practice to reduce blood pressure (<xref ref-type="bibr" rid="B5">Braunwald, 1982</xref>; <xref ref-type="bibr" rid="B15">Eisenberg et&#x20;al., 2004</xref>). In addition, DCCBs can provide many cardiovascular (CV) benefits (<xref ref-type="bibr" rid="B49">Staessen et&#x20;al., 1997</xref>; <xref ref-type="bibr" rid="B37">Nissen et&#x20;al., 2004</xref>; <xref ref-type="bibr" rid="B21">Hasebe and Kikuchi, 2005</xref>; <xref ref-type="bibr" rid="B20">Haller, 2008</xref>). A meta-analysis of 175,634 patients demonstrated that DCCBs could reduce all-cause mortality and stroke risk and prevent heart failure (<xref ref-type="bibr" rid="B12">Costanzo et&#x20;al., 2009</xref>). Systematic reviews have shown that DCCBs could reduce the risk of Parkinson disease (<xref ref-type="bibr" rid="B33">Lang et&#x20;al., 2015</xref>), incidental dementia (<xref ref-type="bibr" rid="B23">Hussain et&#x20;al., 2018</xref>), and sequelae of traumatic brain injury (<xref ref-type="bibr" rid="B19">Gurkoff et&#x20;al., 2017</xref>). However, because of their vasodilatory effect, DCCBs have also been reported in association with increased gastrointestinal tract bleeding (<xref ref-type="bibr" rid="B28">Kaplan et&#x20;al., 2000</xref>) and proischemic complication (<xref ref-type="bibr" rid="B53">Waters, 1991</xref>)&#x20;risks.</p>
<p>Currently, whether DCCBs have individual benefits or harms on kidney function, particularly in diabetes mellitus (DM) patients with chronic kidney disease (CKD), who are at the highest risk for end-stage renal disease (ESRD), remains unclear (<xref ref-type="bibr" rid="B13">de Leeuw et&#x20;al., 2004</xref>). This is partly because CKD and CV events share multiple risk factors and medications (<xref ref-type="bibr" rid="B6">Cai et&#x20;al., 2013</xref>) and the other part due to intrinsic characteristic of DCCBs of vasodilatation of afferent arterioles and increased intraglomerular pressure (<xref ref-type="bibr" rid="B8">Carmines and Navar, 1989</xref>; <xref ref-type="bibr" rid="B29">Kimura et&#x20;al., 1994</xref>). Although numerous randomized controlled trials have investigated the effects of DCCBs on renal function, most have compared angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin II receptor blockers (ARBs) with DCCBs (<xref ref-type="bibr" rid="B10">Chan et&#x20;al., 1992</xref>; <xref ref-type="bibr" rid="B3">Bakris et&#x20;al., 1996</xref>; <xref ref-type="bibr" rid="B51">Velussi et&#x20;al., 1996</xref>; <xref ref-type="bibr" rid="B7">Campo et&#x20;al., 1997</xref>; <xref ref-type="bibr" rid="B16">Estacio et&#x20;al., 1998</xref>; <xref ref-type="bibr" rid="B35">Lewis et&#x20;al., 2001</xref>; <xref ref-type="bibr" rid="B44">Rahman et&#x20;al., 2012</xref>), combined DCCB&#x2013;ACEI/ARB therapy with noncombination therapy (<xref ref-type="bibr" rid="B21">Hasebe and Kikuchi, 2005</xref>), DCCBs with diuretics (<xref ref-type="bibr" rid="B13">de Leeuw et&#x20;al., 2004</xref>), or combined ACEIs/ARB&#x2013;DCCB therapy with combined ACEI/ARB&#x2013;diuretics therapy (<xref ref-type="bibr" rid="B27">Kaneshiro et&#x20;al., 2009</xref>; <xref ref-type="bibr" rid="B30">Kohlmann et&#x20;al., 2009</xref>; <xref ref-type="bibr" rid="B4">Bakris et&#x20;al., 2010</xref>; <xref ref-type="bibr" rid="B14">Doi et&#x20;al., 2010</xref>; <xref ref-type="bibr" rid="B24">Ishimitsu et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B34">Lee et&#x20;al., 2012</xref>; <xref ref-type="bibr" rid="B39">Ogihara et&#x20;al., 2014</xref>; <xref ref-type="bibr" rid="B41">Oshikawa et&#x20;al., 2014</xref>). However, most of the aforementioned studies had a short follow-up duration (<xref ref-type="bibr" rid="B7">Campo et&#x20;al., 1997</xref>; <xref ref-type="bibr" rid="B14">Doi et&#x20;al., 2010</xref>; <xref ref-type="bibr" rid="B24">Ishimitsu et&#x20;al., 2011</xref>; <xref ref-type="bibr" rid="B34">Lee et&#x20;al., 2012</xref>), small sample size (<xref ref-type="bibr" rid="B10">Chan et&#x20;al., 1992</xref>; <xref ref-type="bibr" rid="B3">Bakris et&#x20;al., 1996</xref>; <xref ref-type="bibr" rid="B7">Campo et&#x20;al., 1997</xref>; <xref ref-type="bibr" rid="B14">Doi et&#x20;al., 2010</xref>; <xref ref-type="bibr" rid="B24">Ishimitsu et&#x20;al., 2011</xref>), intrinsic heterogeneous population (CKD, DM, diabetic CKD, or diabetic non-CKD) (<xref ref-type="bibr" rid="B17">Fern&#xe1;ndez et&#x20;al., 2001</xref>; <xref ref-type="bibr" rid="B4">Bakris et&#x20;al., 2010</xref>; <xref ref-type="bibr" rid="B24">Ishimitsu et&#x20;al., 2011</xref>), or did not consider possible effects of hypoglycemic agents on renal function in patients with DM (<xref ref-type="bibr" rid="B10">Chan et&#x20;al., 1992</xref>; <xref ref-type="bibr" rid="B3">Bakris et&#x20;al., 1996</xref>; <xref ref-type="bibr" rid="B51">Velussi et&#x20;al., 1996</xref>; <xref ref-type="bibr" rid="B17">Fern&#xe1;ndez et&#x20;al., 2001</xref>). Whether DCCBs have long-term &#x201c;individual&#x201d; effects on renal function remain to be determined. In their study involving patients with type 2 DM, Bakis et&#x20;al. reported comparable effects of DCCBs and ACEIs in slowing renal disease progression; however, the sample size was only 52 patients (<xref ref-type="bibr" rid="B3">Bakris et&#x20;al., 1996</xref>). We hypothesized that DCCBs have individual effects on delaying CKD progression, particularly in DM patients with CKD. We conducted a nationwide, population-based, propensity score matching study to examine the effects of DCCBs on CKD progression in DM patients with&#x20;CKD.</p>
</sec>
<sec sec-type="methods" id="s2">
<title>Methods</title>
<sec id="s2-1">
<title>Data Source</title>
<p>In 1995, Taiwan launched a single-payer healthcare system from which the National Health Insurance (NHI) Research Database (NHIRD) was established. Data used in the present study were obtained from the Longitudinal Health Insurance Database, which contains information on 1 million individuals randomly sampled from NHIRD. The data were deidentified to protect privacy. The medical claims data contained information on diagnosis, outpatient visits, hospital admissions, drug prescriptions, and surgical procedures. The diagnostic classification was based on the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM). The study was approved by the Research Ethics Committee at China Medical University and Hospital [CMUH104-REC2-115 (AR-4)].</p>
</sec>
<sec id="s2-2">
<title>Study Population</title>
<p>We enrolled DM patients who had subsequent new diagnosis of CKD (ICD-9 codes 585.xx). In this study, those who had the record of DM (ICD-9 codes 250.x0 or 250.x2) more than two times within 1&#xa0;year were defined as DM patients. CKD was defined on the basis of ICD-9 codes 585.xx recorded in NHIRD for more than three times. The date of initial DCCB use was defined as the index date. Patients were followed up until date of first erythropoietin (EPO) prescription, onset of ESRD, withdrawal, death, or December 31, 2013. Diagnosis of ESRD was confirmed by ICD-9-CM codes and inclusion in the Registry for Catastrophic Illness Patient Database, a sub-classification of the NHIRD. Although NHIRD lacks information on CKD staging, the NHI program has stated that patients with estimated glomerular filtration rate (eGFR) &#x3c; 15&#xa0;ml/min/1.73&#xa0;m<sup>2</sup> and hemoglobin level &#x3c;10&#xa0;gm/dL may receive the official EPO prescription benefit package. Thus, in the present study, we defined patients with advanced CKD as those with CKD who started EPO prescriptions.</p>
<p>We excluded patients diagnosed as having advanced CKD or ESRD before the index date. A total of 9,761 DCCB users were compared with DCCB nonusers at a ratio of 1:1 using propensity scores after matching for demographic characteristics and baseline comorbidities. Baseline comorbidities included cancer, hyperlipidemia, stroke, chronic obstructive pulmonary disease, cirrhosis, arrhythmia, congestive heart failure, fibromyalgia, coronary artery disease, alcohol-related diseases, peripheral arterial occlusive disease, renal stone, and peptic ulcer disease (list of codes were presented in <xref ref-type="sec" rid="s11">Supplementary Table S1</xref>). The covariates of baseline medications comprised statins, ACEIs/ARBs, loop diuretics, thiazides, potassium-sparing diuretics, non-DCCBs, alpha-blockers, beta-blockers, insulins, sulfonylureas, biguanides, miglitol, acarbose, thiazolidinedione, dipeptidyl peptidase-4 inhibitors, and other antidiabetics.</p>
</sec>
<sec id="s2-3">
<title>Statistical Analysis</title>
<p>Descriptive analyses of demographics, comorbidities, and medications of the cohorts are presented as frequencies and percentages for the categorical variables and as means and standard deviations for the continuous variables. The 1:N Case-Control Matching Macro (Parsons LS et&#x20;al. SUGI 29) was used to match cases with controls (<xref ref-type="bibr" rid="B43">Parsons, 2012</xref>). DM patients with CKD who used DCCB were matched (1:1 ratio) with those who did not use DCCB according to their propensity score through nearest neighbor matching, initially to the eighth digit and then as required to the first digit. Therefore, matches were first made within a caliper width of 0.0000001, and then the caliper width was increased for unmatched cases to 0.1. We reconsidered the matching criteria and performed a rematch (greedy algorithm). For each DM patient on DCCB use, the corresponding comparisons were selected based on the nearest propensity score. A standardized mean difference of &#x2264;0.1 indicates a negligible difference between the two cohorts. Absolute standardized mean difference per covariate before and after PSM was presented in <xref ref-type="table" rid="T1">Table&#x20;1</xref> and <xref ref-type="sec" rid="s11">Supplementary Table S2</xref>. Cumulative incidence rates of advanced CKD and ESRD were calculated based on the Kaplan-Meier method, and the between-cohort comparisons of the cumulative incidence curves were assessed by log-rank&#x20;tests.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Demographic characteristics and comorbidities in the propensity-score-matched cohorts with and without dihydropyridine Calcium Channel Blocker used among diabetes mellitus patients with chronic kidney disease.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="3" align="left">Variable</th>
<th colspan="2" align="center">Dihydropyridine calcium channel blocker</th>
<th rowspan="3" align="center">Standard mean difference<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</th>
</tr>
<tr>
<th align="center">No<italic>N</italic>&#x20;&#x3d; 9,761</th>
<th align="center">Yes<italic>N</italic>&#x20;&#x3d; 9,761</th>
</tr>
<tr>
<th align="center">
<italic>n</italic> (%)</th>
<th align="center">
<italic>n</italic> (%)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td colspan="4" align="left">Age, year</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2264;49</td>
<td align="center">2,537 (26.0)</td>
<td align="center">2,549 (26.1)</td>
<td align="char" char=".">0.003</td>
</tr>
<tr>
<td align="left">&#x2003;50&#x2013;64</td>
<td align="center">4,020 (41.2)</td>
<td align="center">4,070 (41.7)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#x2003;65&#x2b;</td>
<td align="center">3,204 (32.8)</td>
<td align="center">3,142 (32.2)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#x2003;Mean &#xb1;(SD)<sup>&#x2020;</sup>
</td>
<td align="center">58.5 (13.3)</td>
<td align="center">58.4 (12.6)</td>
<td align="char" char=".">0.006</td>
</tr>
<tr>
<td colspan="4" align="left">Sex</td>
</tr>
<tr>
<td align="left">&#x2003;Female</td>
<td align="center">4,348 (44.5)</td>
<td align="center">4,380 (44.9)</td>
<td align="char" char=".">0.007</td>
</tr>
<tr>
<td align="left">&#x2003;Male</td>
<td align="center">5,413 (55.5)</td>
<td align="center">5,381 (55.1)</td>
<td align="char" char=".">0.007</td>
</tr>
<tr>
<td align="left">&#x2003;Mean aDCSI score (SD)<sup>&#x2020;</sup>
</td>
<td align="center">0.91 (1.48)</td>
<td align="center">0.93 (1.50)</td>
<td align="char" char=".">0.009</td>
</tr>
<tr>
<td colspan="4" align="left">Duration of diabetes</td>
</tr>
<tr>
<td colspan="4" align="left">&#x2003;Comorbidity</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;Cancer</td>
<td align="center">1,485 (15.2)</td>
<td align="center">1,521 (15.6)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;Hyperlipidemia</td>
<td align="center">6,377 (65.3)</td>
<td align="center">6,422 (65.8)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;Stroke</td>
<td align="center">2,179 (22.3)</td>
<td align="center">2,338 (24.0)</td>
<td align="char" char=".">0.004</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;COPD</td>
<td align="center">2,310 (23.7)</td>
<td align="center">2,293 (23.5)</td>
<td align="char" char=".">0.004</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;Cirrhosis</td>
<td align="center">3,677 (37.7)</td>
<td align="center">3,688 (37.8)</td>
<td align="char" char=".">0.002</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;Arrhythmia</td>
<td align="center">1,373 (14.1)</td>
<td align="center">1,382 (14.2)</td>
<td align="char" char=".">0.003</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;Congestive heart failure</td>
<td align="center">1,405 (14.4)</td>
<td align="center">1,453 (14.9)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;Fibromyalgia</td>
<td align="center">2,898 (29.7)</td>
<td align="center">3,045 (31.2)</td>
<td align="char" char=".">0.004</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;Coronary artery disease</td>
<td align="center">3,657 (37.5)</td>
<td align="center">3,777 (38.7)</td>
<td align="char" char=".">0.03</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;Alcohol-related diseases</td>
<td align="center">1,130 (11.6)</td>
<td align="center">1,167 (12.0)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;PAOD</td>
<td align="center">879 (9.01)</td>
<td align="center">879 (9.01)</td>
<td align="char" char=".">0.000</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;Renal stone</td>
<td align="center">1,286 (13.2)</td>
<td align="center">1,252 (12.8)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;PUD</td>
<td align="center">4,440 (45.5)</td>
<td align="center">4,459 (45.7)</td>
<td align="char" char=".">0.004</td>
</tr>
<tr>
<td colspan="4" align="left">Medication</td>
</tr>
<tr>
<td align="left">&#x2003;Statin</td>
<td align="center">5,840 (59.8)</td>
<td align="center">5,988 (61.4)</td>
<td align="char" char=".">0.004</td>
</tr>
<tr>
<td align="left">&#x2003;ACEI or ARB</td>
<td align="center">7,600 (77.9)</td>
<td align="center">8,245 (84.5)</td>
<td align="char" char=".">0.004</td>
</tr>
<tr>
<td align="left">&#x2003;Loop diuretics</td>
<td align="center">5,901 (60.5)</td>
<td align="center">5,935 (60.8)</td>
<td align="char" char=".">0.007</td>
</tr>
<tr>
<td align="left">&#x2003;Thiazides</td>
<td align="center">6,207 (63.6)</td>
<td align="center">6,293 (64.5)</td>
<td align="char" char=".">0.02</td>
</tr>
<tr>
<td align="left">&#x2003;Potassium sparing diuretics</td>
<td align="center">3,098 (31.7)</td>
<td align="center">3,120 (32.0)</td>
<td align="char" char=".">0.005</td>
</tr>
<tr>
<td align="left">&#x2003;Non-Dihydropyridine Calcium Channel Blockers</td>
<td align="center">3,448 (35.3)</td>
<td align="center">3,499 (35.9)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#x2003;Alpha-blockers</td>
<td align="center">3,026 (31.0)</td>
<td align="center">3,032 (31.1)</td>
<td align="char" char=".">0.001</td>
</tr>
<tr>
<td align="left">&#x2003;Beta-blockers</td>
<td align="center">6,847 (70.2)</td>
<td align="center">6,930 (71.0)</td>
<td align="char" char=".">0.02</td>
</tr>
<tr>
<td align="left">&#x2003;Insulins</td>
<td align="center">6,965 (71.4)</td>
<td align="center">6,970 (71.4)</td>
<td align="char" char=".">0.001</td>
</tr>
<tr>
<td align="left">&#x2003;Sulfonylureas</td>
<td align="center">8,707 (89.2)</td>
<td align="center">8,744 (89.6)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#x2003;Biguanides</td>
<td align="center">8,898 (91.2)</td>
<td align="center">8,935 (91.5)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#x2003;Miglitol</td>
<td align="center">220 (2.25)</td>
<td align="center">228 (2.34)</td>
<td align="char" char=".">0.005</td>
</tr>
<tr>
<td align="left">&#x2003;Acarbose</td>
<td align="center">3,562 (36.5)</td>
<td align="center">3,616 (37.1)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#x2003;Thiazolidinedione</td>
<td align="center">3,333 (34.2)</td>
<td align="center">3,406 (34.9)</td>
<td align="char" char=".">0.02</td>
</tr>
<tr>
<td align="left">&#x2003;Dipeptidyl peptidase-4</td>
<td align="center">8,757 (89.7)</td>
<td align="center">8,788 (90.0)</td>
<td align="char" char=".">0.01</td>
</tr>
<tr>
<td align="left">&#x2003;Other antidiabetic</td>
<td align="center">5,024 (51.5)</td>
<td align="center">5,091 (52.2)</td>
<td align="char" char=".">0.01</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="Tfn1">
<label>a</label>
<p>A standardized mean difference of &#x2264;0.1 indicates a negligible difference between the two cohorts. &#x2020;, t test.</p>
</fn>
<fn>
<p>CAD: coronary artery disease.</p>
</fn>
<fn>
<p>COPD: chronic obstructive pulmonary disease.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>To consider the effect of the frequency variation in the use of DCCBs, DCCB use was considered as a time-dependent covariate in the Cox proportional hazards model. Hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) for advanced CKD and ESRD were estimated using the Cox proportional hazards models. A two&#x2010;tailed <italic>p</italic> value &#x3c;0.05 was considered statistically significant. The data analysis was generated using SAS (version 9.4) of the SAS System for [Unix] (SAS Institute Inc., Cary, NC, United&#x20;States), and the figures were created using&#x20;R.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<p>
<xref ref-type="table" rid="T1">Table&#x20;1</xref> lists the demographic characteristics and comorbidities in the propensity score&#x2013;matched cohorts. The average age of DCCB nonusers and DCCB users was 58.5&#x20;&#xb1; 13.3 and 58.4&#x20;&#xb1; 12.6&#xa0;years, respectively; 44.5 and 44.9% of the DCCB nonusers and users were women, respectively. In the profiles of baseline comorbidities and medications, they did not significantly differ between the two cohorts according to standardized mean differences after PS matching in <xref ref-type="table" rid="T1">Table&#x20;1</xref>.</p>
<p>
<xref ref-type="table" rid="T2">Table&#x20;2</xref> presents the incidence values and HRs for advanced CKD or ESRD in the cohorts from Cox proportional hazards models with time-dependent exposure covariates. The incidence rates of advanced CKD and ESRD in DCCB nonusers were 3.27 and 3.64 per 1,000&#x20;person-years, respectively. The incidence rates of advanced CKD and ESRD in DCCB users were 2.28 and 2.59 per 1,000&#x20;person-year, respectively. The DCCB users had lower advanced CKD and ESRD risk than did nonusers [with HR (95% CI) of 0.71 (0.59&#x2013;0.85) for advanced CKD and 0.72 (0.61&#x2013;0.86) for ESRD].</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Incidence and HRs of advanced CKD or ESRD in the dihydropyridine calcium channel blocker (DCCB) cohorts compared with those in the non-DCCB cohorts among diabetes mellitus patients with chronic kidney disease by Cox proportional hazard models with time-dependent exposure covariates.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left"/>
<th colspan="2" align="center">DCCB</th>
</tr>
<tr>
<th align="center">No(<italic>N</italic>&#x20;&#x3d; 9,761)</th>
<th align="center">Yes(<italic>N</italic>&#x20;&#x3d; 9,761)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td colspan="3" align="left">Advanced CKD</td>
</tr>
<tr>
<td align="left">&#x2003;Person-years</td>
<td align="center">82,063</td>
<td align="center">86,035</td>
</tr>
<tr>
<td align="left">&#x2003;Follow-up time (y), Median&#xb1;(IQR)</td>
<td align="center">905 (5.30&#x2013;12.0)</td>
<td align="center">9.31 (5.95&#x2013;12.1)</td>
</tr>
<tr>
<td align="left">&#x2003;Event</td>
<td align="center">268</td>
<td align="center">196</td>
</tr>
<tr>
<td align="left">&#x2003;Rate<sup>&#x23;</sup>
</td>
<td align="center">3.27</td>
<td align="center">2.28</td>
</tr>
<tr>
<td align="left">&#x2003;HR (95% CI)</td>
<td align="center">1 (Reference)</td>
<td align="center">0.71 (0.59, 0.85)&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td colspan="3" align="left">ESRD</td>
</tr>
<tr>
<td align="left">&#x2003;Person-years</td>
<td align="center">82,176</td>
<td align="center">86,121</td>
</tr>
<tr>
<td align="left">&#x2003;Follow-up time (y), Median&#xb1;(IQR)</td>
<td align="center">9.05 (5.30&#x2013;12.0)</td>
<td align="center">9.33 (5.96&#x2013;12.1)</td>
</tr>
<tr>
<td align="left">&#x2003;Event</td>
<td align="center">229</td>
<td align="center">223</td>
</tr>
<tr>
<td align="left">&#x2003;Rate<sup>&#x23;</sup>
</td>
<td align="center">3.64</td>
<td align="center">2.59</td>
</tr>
<tr>
<td align="left">&#x2003;HR (95% CI)</td>
<td align="center">1 (Reference)</td>
<td align="center">0.72 (0.61, 0.86)&#x2a;&#x2a;&#x2a;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Rate&#x23;, incidence rate, per 1,000&#x20;person-years; HR, relative hazard&#x20;ratio.</p>
</fn>
<fn>
<p>&#x2a;<italic>p</italic>&#x20;&#x3c; 0.05; &#x2a;&#x2a;<italic>p</italic>&#x20;&#x3c; 0.01; &#x2a;&#x2a;&#x2a;<italic>p</italic>&#x20;&#x3c;&#x20;.001.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>
<xref ref-type="table" rid="T3">Table&#x20;3</xref> lists the incidence and HRs of advanced CKD or ESRD in the cohorts by age and sex from Cox proportional hazards models with time-dependent exposure covariates. Reduced incidence rates of advanced CKD and ESRD in DCCB users were observed in the &#x2265;65-year age group compared with those in DCCB nonusers [with HR (95% CI) of 0.49 (0.36&#x2013;0.68) in the &#x2265;65-year age group for advanced CKD, respectively, and 0.76 (0.59&#x2013;1.00) and 0.50 (0.38&#x2013;0.67) in the 50&#x2013;64- and &#x2265;65-year age group for ESRD, respectively). Women using DCCBs were at lower advanced CKD and ESRD risks compared with women not using DCCBs [with HR (95% CI) of 0.67 (0.51&#x2013;0.88) and 0.61 (0.47&#x2013;0.78) for advanced CKD and ESRD, respectively].</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Incidence and hazards ratio of advanced CKD or ESRD measured by age, sex, and comorbidity in the dihydropyridine calcium channel blocker (DCCB) cohorts among diabetes mellitus patients with chronic kidney disease compared with those in the non-DCCB cohorts by Cox proportional hazard models with time-dependent exposure covariates.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="3" align="center">Variables</th>
<th colspan="4" align="center">DCCB</th>
<th rowspan="3" align="center">HR (95% CI)</th>
</tr>
<tr>
<th colspan="2" align="center">No (<italic>N</italic>&#x20;&#x3d; 9,761)</th>
<th colspan="2" align="center">Yes (<italic>N</italic>&#x20;&#x3d; 9,761)</th>
</tr>
<tr>
<th align="center">Event</th>
<th align="center">Rate<sup>&#x23;</sup>
</th>
<th align="center">Event</th>
<th align="center">Rate<sup>&#x23;</sup>
</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td colspan="6" align="left">Advanced CKD</td>
</tr>
<tr>
<td colspan="6" align="left">&#x2003;Age, years</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;&#x2264;49</td>
<td align="center">42</td>
<td align="char" char=".">1.83</td>
<td align="center">49</td>
<td align="char" char=".">2.08</td>
<td align="char" char=".">1.14 (0.76, 1.73)</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;50-64</td>
<td align="center">112</td>
<td align="char" char=".">3.16</td>
<td align="center">88</td>
<td align="char" char=".">2.38</td>
<td align="char" char=".">0.76 (0.57, 1.00)</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;65&#x2b;</td>
<td align="center">114</td>
<td align="char" char=".">4.82</td>
<td align="center">59</td>
<td align="char" char=".">2.32</td>
<td align="char" char=".">0.49 (0.36, 0.68)&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td colspan="6" align="left">Sex</td>
</tr>
<tr>
<td align="left">&#x2003;Female</td>
<td align="center">125</td>
<td align="char" char=".">3.26</td>
<td align="center">87</td>
<td align="char" char=".">2.13</td>
<td align="char" char=".">0.67 (0.51, 0.88)&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;Male</td>
<td align="center">143</td>
<td align="char" char=".">3.27</td>
<td align="center">109</td>
<td align="char" char=".">2.41</td>
<td align="char" char=".">0.74 (0.58, 0.95)&#x2a;</td>
</tr>
<tr>
<td colspan="6" align="left">ESRD</td>
</tr>
<tr>
<td colspan="6" align="left">&#x2003;Age, years</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;&#x2264;49</td>
<td align="center">45</td>
<td align="char" char=".">1.96</td>
<td align="center">56</td>
<td align="char" char=".">2.37</td>
<td align="char" char=".">1.22 (0.83, 1.81)</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;50&#x2013;64</td>
<td align="center">125</td>
<td align="char" char=".">3.52</td>
<td align="center">99</td>
<td align="char" char=".">2.67</td>
<td align="char" char=".">0.76 (0.59, 1.00)&#x2a;</td>
</tr>
<tr>
<td align="left">&#xa0;&#xa0;65&#x2b;</td>
<td align="center">129</td>
<td align="char" char=".">5.44</td>
<td align="center">68</td>
<td align="char" char=".">2.67</td>
<td align="char" char=".">0.50 (0.38, 0.67)&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td colspan="6" align="left">Sex</td>
</tr>
<tr>
<td align="left">&#x2003;Female</td>
<td align="center">155</td>
<td align="char" char=".">4.04</td>
<td align="center">98</td>
<td align="char" char=".">2.40</td>
<td align="char" char=".">0.61 (0.47, 0.78)&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;Male</td>
<td align="center">144</td>
<td align="char" char=".">3.29</td>
<td align="center">125</td>
<td align="char" char=".">2.76</td>
<td align="char" char=".">0.85 (0.67, 1.08)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Rate&#x23;, incidence rate, per 1,000&#x20;person-years; HR, relative hazard&#x20;ratio.</p>
</fn>
<fn>
<p>&#x2a;<italic>p</italic>&#x20;&#x3c; 0.05; &#x2a;&#x2a;<italic>p</italic>&#x20;&#x3c; 0.01; &#x2a;&#x2a;&#x2a;<italic>p</italic>&#x20;&#x3c;&#x20;.001.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>
<xref ref-type="table" rid="T4">Table&#x20;4</xref> shows incidence values and HRs for advanced CKD or ESRD stratified by duration of DCCB therapy. Compared with nonuse, cumulative DCCB use for &#x3e;300&#xa0;days reduced CKD risk (with HR [95% CI] of 0.63 [0.46&#x2013;0.87] and 0.32 [0.21&#x2013;0.48] for cumulative DCCB use for 301&#x2013;1,100 and &#x3e;1,100&#xa0;days, respectively). Compared with nonuse, cumulative DCCB use for &#x3e;300&#xa0;days reduced ESRD risk [with aHR (95% CI) of 0.66 (0.49&#x2013;0.89), and 0.28 (0.19&#x2013;0.42) for cumulative DCCB use for 301&#x2013;1,100, and &#x3e;1,100&#xa0;days, respectively].</p>
<table-wrap id="T4" position="float">
<label>TABLE 4</label>
<caption>
<p>Incidence and adjusted hazard ratio of advanced CKD or ESRD stratified by duration of dihydropyridine calcium channel blocker (DCCB) therapy among diabetes mellitus patients with chronic kidney disease.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Medication exposed</th>
<th align="center">
<italic>N</italic>
</th>
<th align="center">Event</th>
<th align="center">Person-year</th>
<th align="center">Rate</th>
<th align="center">HR (95%CI)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td colspan="6" align="left">Advanced CKD</td>
</tr>
<tr>
<td align="left">&#x2003;Non- DCCB</td>
<td align="center">9,761</td>
<td align="center">268</td>
<td align="center">82,062</td>
<td align="char" char=".">3.27</td>
<td align="char" char=".">1.00</td>
</tr>
<tr>
<td colspan="6" align="left">DCCB</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2264;30&#xa0;days</td>
<td align="center">2,555</td>
<td align="center">59</td>
<td align="center">19,439</td>
<td align="char" char=".">3.04</td>
<td align="char" char=".">0.88 (0.66, 1.16)</td>
</tr>
<tr>
<td align="left">&#x2003;31-300&#xa0;days</td>
<td align="center">2,294</td>
<td align="center">69</td>
<td align="center">18,499</td>
<td align="char" char=".">3.73</td>
<td align="char" char=".">1.10 (0.85, 1.44)</td>
</tr>
<tr>
<td align="left">&#x2003;301-1,100&#xa0;days</td>
<td align="center">2,372</td>
<td align="center">43</td>
<td align="center">21,071</td>
<td align="char" char=".">2.04</td>
<td align="char" char=".">0.63 (0.46, 0.87)&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;&#x3e;1,100&#xa0;days</td>
<td align="center">2,540</td>
<td align="center">25</td>
<td align="center">27,025</td>
<td align="char" char=".">0.93</td>
<td align="char" char=".">0.32 (0.21, 0.48)&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td colspan="6" align="left">ESRD</td>
</tr>
<tr>
<td align="left">&#x2003;Non-DCCB</td>
<td align="center">9,761</td>
<td align="center">299</td>
<td align="center">82,175</td>
<td align="char" char=".">3.64</td>
<td align="char" char=".">1.00</td>
</tr>
<tr>
<td colspan="6" align="left">DCCB<xref ref-type="table-fn" rid="Tfn2">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2264;30&#xa0;days</td>
<td align="center">2,555</td>
<td align="center">74</td>
<td align="center">19,455</td>
<td align="char" char=".">3.80</td>
<td align="char" char=".">0.99 (0.77, 1.28)</td>
</tr>
<tr>
<td align="left">&#x2003;31-300&#xa0;days</td>
<td align="center">2,294</td>
<td align="center">74</td>
<td align="center">18,527</td>
<td align="char" char=".">3.99</td>
<td align="char" char=".">1.07 (0.83, 1.37)</td>
</tr>
<tr>
<td align="left">&#x2003;301-1,100&#xa0;days</td>
<td align="center">2,372</td>
<td align="center">50</td>
<td align="center">21,093</td>
<td align="char" char=".">2.37</td>
<td align="char" char=".">0.66 (0.49, 0.89)&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;&#x3e;1,100&#xa0;days</td>
<td align="center">2,540</td>
<td align="center">25</td>
<td align="center">27,045</td>
<td align="char" char=".">0.92</td>
<td align="char" char=".">0.28 (0.19, 0.42)&#x2a;&#x2a;&#x2a;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="Tfn2">
<label>a</label>
<p>The cumulative use day are partitioned in to 4 segments by quartile.</p>
</fn>
<fn>
<p>HR, relative hazard&#x20;ratio.</p>
</fn>
<fn>
<p>&#x2a;&#x2a;<italic>p</italic>&#x20;&#x3c; 0.01, &#x2a;&#x2a;&#x2a;<italic>p</italic>&#x20;&#x3c; 0.001.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>
<xref ref-type="fig" rid="F1">Figure&#x20;1</xref> depicts cumulative incidence curves of advanced CKD or ESRD for DCCB users and DCCB nonusers by propensity score matching. The <italic>p</italic> values from the log-rank tests for both cohorts were &#x3c;0.001, and DCCB users were more likely to have lower advanced CKD and ESRD risks than were DCCB nonusers.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Cumulative incidence of EPO <bold>(A)</bold> or ESRD <bold>(B)</bold> curves for dihydropyridine calcium channel blocker (DCCB) users and dihydropyridine calcium channel blocker (DCCB) non-users by propensity score matched.</p>
</caption>
<graphic xlink:href="fphar-13-786203-g001.tif"/>
</fig>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>DM patients with CKD who used DCCBs had a lower risk of progression to advanced CKD or ESRD compared with those who did not use DCCBs. We suggested several mechanisms of DCCBs that could account for this finding: improved blood pressure reduction, improved maintenance of renal perfusion, and DCCBs&#x2019; antiatherosclerotic properties. Although the optimal blood pressure target for improving renal outcomes in patients with CKD remains unclear, the evidence supports blood pressure control through antihypertensives for patients with systolic blood pressure &#x3c;130&#xa0;mmHg (<xref ref-type="bibr" rid="B11">Chang et&#x20;al., 2019</xref>). The Japanese Trial to Assess Optimal Systolic Blood Pressure in Elderly Hyperintensive Patients and the Action in Diabetes and Vascular Disease: Preterax and Diamicron MR Controlled Evaluation trial revealed that improved blood pressure control could lead to reduction in the risk of doubling of creatinine levels and progression to advanced CKD compared with the absence of blood pressure control (<xref ref-type="bibr" rid="B25">JATOS, 2005</xref>; <xref ref-type="bibr" rid="B22">Heerspink et&#x20;al., 2010</xref>). By contrast, other studies have found that intensive blood pressure control does not improve renal outcomes (<xref ref-type="bibr" rid="B46">Ruggenenti et&#x20;al., 2005</xref>; <xref ref-type="bibr" rid="B1">Appel et&#x20;al., 2010</xref>; <xref ref-type="bibr" rid="B32">Ku et&#x20;al., 2017</xref>). These findings suggest that improved renal outcomes require both improved blood pressure control and improved renal perfusion (<xref ref-type="bibr" rid="B42">Palmer, 2002</xref>; <xref ref-type="bibr" rid="B45">Ravera et&#x20;al., 2006</xref>). DCCBs have been effective in lowering systolic blood pressure to &#x3c;130&#xa0;mmHg in different patient populations in combination with other antihypertensives (<xref ref-type="bibr" rid="B20">Haller, 2008</xref>; <xref ref-type="bibr" rid="B36">Matsui et&#x20;al., 2009</xref>; <xref ref-type="bibr" rid="B2">Association, 2019</xref>). DCCBs have a beneficial effect on central systolic blood pressure and arterial stiffness (<xref ref-type="bibr" rid="B36">Matsui et&#x20;al., 2009</xref>). In the past, a concern was raised regarding the effects of DCCBs on kidney function; DCCBs may cause vasodilatation of afferent renal arterioles, increase intraglomerular pressure, and promote proteinuria (<xref ref-type="bibr" rid="B38">Nosadini and Tonolo, 2002</xref>). In the present study, because individual information on baseline blood pressure, proteinuria, and eGFR were unavailable, the effects of DCCB on optimal blood pressure control, proteinuria, and eGFR were unknown for both cohorts. However, through propensity matching by antihypertensive classes and comorbidities, we demonstrated that compared with nonuse, DCCB use reduced the risk of progression to advanced CKD and ESRD, consistent with previous findings (<xref ref-type="bibr" rid="B3">Bakris et&#x20;al., 1996</xref>; <xref ref-type="bibr" rid="B25">JATOS, 2005</xref>). DCCBs could both improve blood pressure control and preserve renal perfusion through the vasodilatory effect of systemic arterioles and renal arterioles, thus resulting in improved renal outcomes&#x2014;reduced advanced CKD and ESRD risks. Further, Orekhov et&#x20;al. have found DCCB could decrease the incorporation of [3H] thymidine, lower the intracellular cholesterol level, and inhibit proliferative activity of cultured cells, which exhibited antiatherosclerotic and atherogenic ability of DCCB in their <italic>in&#x20;vitro</italic> models (<xref ref-type="bibr" rid="B40">Orekhov et&#x20;al., 1988</xref>). A multicenter study found that DCCBs slow the progression of plaque volume in patients with hypertension (<xref ref-type="bibr" rid="B31">Kojima et&#x20;al., 2011</xref>). Another study revealed that DCCBs could help slow the progression of minimal atherosclerotic lesions of coronary arteries (<xref ref-type="bibr" rid="B52">Waters et&#x20;al., 1990</xref>). Because atherosclerosis and atherogenic factors could lead to early renal injuries and promote CKD progression (<xref ref-type="bibr" rid="B9">Chade et&#x20;al., 2005</xref>; <xref ref-type="bibr" rid="B26">Kalra et&#x20;al., 2005</xref>), DCCBs, with their antiatherosclerotic properties, would help reduce the risk of progression from early CKD to advanced CKD and&#x20;ESRD.</p>
<p>Notably, in the present study, the DCCB users aged &#x2265;65&#xa0;years had the lowest advanced CKD and ESRD risks, suggesting DCCB safety and effectiveness in elderly DM patients with CKD. Elderly patients, particularly those with DM and CKD, may glean more benefits from DCCB use because advanced age is associated with greater arterial stiffness (<xref ref-type="bibr" rid="B48">Scuteri et&#x20;al., 2018</xref>; <xref ref-type="bibr" rid="B18">Galv&#xe3;o et&#x20;al., 2020</xref>). Future studies investigating the renal benefits of DCCBs for elderly patients with DM are warranted. Our study also found a dose&#x2013;response relationship with DCCB use: of all patients, patients with the longest duration of DCCB use (i.e.,&#x20;&#x3e;1,100&#xa0;days) had the lowest advanced CKD and ESRD risks, which further strengthens the evidence of the benefits of DCCBs on renal outcomes.</p>
<p>This study has several limitations. First, participant information on systolic and diastolic blood pressure, pulse pressure, glycated hemoglobin level, glucose level, body mass index, low density lipoprotein level, triglyceride level, family history of kidney disease (including immunoglobulin A nephropathy or autosomal dominant polycystic kidney disease), and exercise habits was unavailable in NHIRD. Second, information on serum creatinine, eGFR, urine albumin-to-creatinine ratio, and urine protein-to-creatinine ratio was also lacking in NHIRD. The NHI program has stated that patients whose eGFR is &#x3c; 15&#xa0;ml/min/1.73&#xa0;m<sup>2</sup> and whose hemoglobin levels is &#x3c; 10&#xa0;gm/dL may receive the official EPO prescription benefit package. Because anemia is common in DM patients with CKD, using EPO prescription as a proxy for advanced CKD was reasonable. Third, medication compliance and blood pressure and glucose control among the patients could not be ensured. Also, those individuals on DCCBs may be inherently different from those not on the prescription hence the observed difference rather than the drug effect as the observed difference would be potential confounding by indication. Fourth, the dosage of the antihypertensives, as well as T-type or L-type DCCBs, was not considered. Fifth, ACEIs or ARBs were not completely matched; thus, their effects might not have been eliminated completely. We have used time-dependent model in this study, thus potential immortal time bias in studies for evaluating the effect of drug would be eliminated. Sixth, residual confounding might exist, and we did not run negative control outcome analysis to assess residual confounding should be announced here. Finally, response to antihypertensive treatment involves gene polymorphisms (<xref ref-type="bibr" rid="B50">Stavroulakis et&#x20;al., 2000</xref>; <xref ref-type="bibr" rid="B47">Schelleman et&#x20;al., 2004</xref>). Therefore, the results of this nationwide, population-based cohort study may not be directly applicable to other racial or ethnic populations.</p>
<p>In conclusion, DM patients with CKD who used DCCBs had lower risk of progression to advanced CKD and ESRD compared with those who did not use DCCBs. This study demonstrated the individual renal benefits of DCCBs in DM patients with CKD. Additional randomized controlled trials to confirm these findings are required.</p>
</sec>
</body>
<back>
<sec id="s5">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s10">Supplementary Material</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s6">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by The NHIRD encrypts personal information of the patients to protect privacy and provides researchers with anonymous identification numbers associated with relevant claims information, including sex, date of birth, medical services received, and prescriptions. Therefore, patient&#x2019;s consent is not required to access the NHIRD. This study was approved to fulfill the condition for exemption by the Institutional Review Board (IRB) of China Medical University (CMUH104-REC2-115-AR4). The IRB also specifically waived the consent requirement. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.</p>
</sec>
<sec id="s7">
<title>Author Contributions</title>
<p>Conception/Design: S-YL and C-HK; Provision of study materials: C-HK; Collection and/or assembly of data: S-YL, C-LL, and C-HK; Data analysis and interpretation: All authors; Manuscript writing: All authors; Final approval of manuscript: All authors.</p>
</sec>
<sec id="s8">
<title>Funding</title>
<p>This study is supported in part by Taiwan Ministry of Health and Welfare Clinical Trial Center (MOHW110-TDU-B-212-124004), China Medical University Hospital (DMR-109-231, DMR-110-089, DMR-111-090, DMR-111-091, DMR-111-105); Ministry of Science and Technology (MOST 110-2321-B-039-003).</p>
</sec>
<sec sec-type="COI-statement" id="s9">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="s10">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s11">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fphar.2022.786203/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fphar.2022.786203/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material>
<label>Supplementary Figure S1</label>
<caption>
<p>Distribution of covariates before propensity-scorematching.</p>
</caption>
</supplementary-material>
<supplementary-material xlink:href="Table1.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table2.docx" id="SM2" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
<sec id="s12">
<title>Abbreviations</title>
<p>aHR, adjusted hazard ratio; CI, confidence interval; ICD-9-CM, International Classification of Diseases, Ninth revision, Clinical Modification; IQRs, interquartile ranges; LHID, Longitudinal Health Insurance Database; NHIRD, National Health Insurance Research Database.</p>
</sec>
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