Relation of renal function to mid-term prognosis of stable angina patients with high- or low-dose pitavastatin treatment: REAL-CAD substudy

Influence of Worsening Renal Function and Baseline Chronic Kidney Disease on Clinical Outcomes in Patients With Chronic Coronary Syndromes: Insights From the REAL-CAD Study

BACKGROUND

The effect of worsening renal function and baseline chronic kidney disease (CKD) on outcomes in patients with chronic coronary syndrome in the setting of optimal medical therapy remains unknown.

METHODS AND RESULTS

The REAL-CAD (Randomized Evaluation of Aggressive or Moderate Lipid Lowering Therapy With Pitavastatin in Coronary Artery Disease) study is a prospective, multicenter, randomized trial of high-dose (pitavastatin 4 mg/day) or low-dose (pitavastatin 1 mg/day) statin therapy in 12 118 patients with chronic coronary syndrome. The primary end point was a composite of cardiovascular death, nonfatal myocardial infarction, stroke, or unstable angina requiring hospitalization (major adverse cardiac and cerebral events [MACCE]). CKD was defined as an estimated glomerular filtration rate [eGFR] <60 mL/min per 1.73 m2. WRF was defined as a decrease in eGFR ≥20% in the initial year; borderline renal function was an annual decrease of 0%

CONCLUSIONS

Baseline CKD was an independent predictor for MACCE in patients with CCS. WRF was a significant predictor for MACCE in patients with CKD. Because borderline renal function was an independent predictor for MACCE even in patients without CKD, mild-to-moderate annual declines of eGFR should be carefully monitored (NCT01042730).

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique Identifier: NCT01042730.

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Key Words

• CCS
• CKD
• MACCE
• PCI
• deterioration

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MESH Headings

• Humans
• Male
• Female
• Renal Insufficiency, Chronic/physiopathology
• Renal Insufficiency, Chronic/complications
• Renal Insufficiency, Chronic/diagnosis
• Renal Insufficiency, Chronic/mortality
• Glomerular Filtration Rate
• Aged
• Middle Aged
• Prospective Studies
• Treatment Outcome
• Hydroxymethylglutaryl-CoA Reductase Inhibitors/administration & dosage
• Hydroxymethylglutaryl-CoA Reductase Inhibitors/therapeutic use
• Kidney/physiopathology
• Quinolines/administration & dosage
• Quinolines/therapeutic use
• Risk Factors
• Disease Progression
• Coronary Artery Disease/drug therapy
• Coronary Artery Disease/mortality
• Time Factors

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Affiliation(s)

Yu Yoshiki Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Yukio Ozaki Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Mitsuru Abe Department of CardiologyNational Hospital Organization Kyoto Medical CenterKyotoJapan
Tevfik F. Ismail King’s College London, LondonUK & Guy’s and St Thomas’ Hospital NHS Foundation TrustLondonUnited Kingdom
Hiroshi Takahashi Division of Medical StatisticsFujita Health University HospitalToyoakeAichiJapan
Masaharu Akao Department of CardiologyNational Hospital Organization Kyoto Medical CenterKyotoJapan
Hideki Kawai Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Takashi Muramatsu Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Masahide Harada Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Masaya Ohta Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Yosuke Hashimoto Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Yuichiro Shiki Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Masayuki Koshikawa Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Keiichi Miyajima Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Hidemaro Takatsu Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Yudai Niwa Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Naoyuki Kawashima Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Reina Ozaki Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan Nagoya University Graduate School of MedicineNagoyaJapan
Naotake Tsuboi Department of NephrologyFujita Health University School of MedicineToyoakeAichiJapan
Satoshi Iimuro Teikyo Academic Research CenterTeikyo UniversityTokyoJapan
Hiroshi Iwata Department of Cardiovascular MedicineJuntendo University Graduate School of MedicineTokyoJapan
Ichiro Sakuma Caress Sapporo Hokko Memorial ClinicSapporoJapan
Yoshihisa Nakagawa Department of Cardiovascular MedicineShiga University of Medical Science HospitalOtsuJapan
Kiyoshi Hibi Division of CardiologyYokohama City University Medical CenterYokohamaJapan
Takafumi Hiro Division of Cardiology, Department of MedicineNihon University School of MedicineTokyoJapan
Yoshihiro Fukumoto Division of Cardiovascular Medicine, Department of Internal MedicineKurume University School of MedicineKurumeJapan
Seiji Hokimoto Department of Cardiovascular MedicineKumamoto University HospitalKumamotoJapan
Katsumi Miyauchi Department of Cardiovascular MedicineJuntendo University Graduate School of MedicineTokyoJapan
Hisao Ogawa Department of Cardiovascular MedicineKumamoto University HospitalKumamotoJapan
Hiroyuki Daida Department of Cardiovascular MedicineJuntendo University Graduate School of MedicineTokyoJapan
Hiroaki Shimokawa Department of Cardiovascular MedicineTohoku University Graduate School of MedicineSendaiJapan
Hideo Izawa Department of CardiologyFujita Health University School of MedicineToyoakeAichiJapan
Takeshi Kimura Department of Cardiovascular MedicineKyoto University Graduate School of MedicineKyotoJapan
Ryozo Nagai Jichi Medical UniversityShimotsukeJapan
REAL‐CAD investigators

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Association between pre-treatment with statin and its inhibitory effect on the onset of coronary artery disease at the time of coronary computed tomography angiography: a new look at an old medication

Coronary artery stenosis is often advanced by the time coronary computed tomography angiography (CCTA). Statins are the most important anti-lipidemic medication for improving the prognosis of coronary artery disease (CAD) patients. Although lipid-lowering therapy using statins appears to have been established as a method for preventing CAD, there remains the problem that CAD cannot be completely suppressed. In this study, we investigated whether pre-treatment with statin could significantly inhibit the onset of CAD when patients received CCTA for screening of CAD. The subjects were 1164 patients who underwent CCTA as screening for CAD. CAD was diagnosed when 50% or more coronary stenosis was present in the coronary arteries. Patient backgrounds were investigated by age, gender, body mass index, coronary risk factors [family history of cardiovascular diseases, smoking history, hypertension (HTN), diabetes mellitus (DM), dyslipidemia, chronic kidney disease (CKD) or metabolic sydrome] and medications. Patients were classified into two groups according to the presence or absence of statin pre-administration during CCTA [statin (-) group (n = 804) and (+) group (n = 360)]. Compared with the statin (-) group, the statin (+) group was significantly older and had higher rates of family history, HTN, and DM. The statin (+) group had a significantly higher % CAD than the statin (-) group. Serum levels of low-density lipoprotein cholesterol (LDL-C) were significantly lower in the statin (+) group than in the statin (-) group. There was no significant difference in either high-density lipoprotein cholesterol levels or triglyceride levels between the two groups. Age, male gender, HTN, DM and pre-treatment with statin were all associated with CAD (+) in all patients. In addition, factors that contributed to CAD (+) in the statin (-) group were age, male gender, and DM, and factors that contributed to CAD (+) in the statin (+) group were age, smoking, HTN and % maximum dose of statin. At the time of CCTA, the statin (+) group had a high rate of CAD and coronary artery stenosis progressed despite a reduction of LDL-C levels. To prevent the onset of CAD, in addition to strict control of other coronary risk factors (HTN etc.), further LDL cholesterol-lowering therapy may be necessary.

Residual Coronary Risk Factors Associated With Long-Term Clinical Outcomes in Patients With Coronary Artery Disease Treated With High- vs. Low-Dose Statin Therapy - REAL-CAD Substudy

BACKGROUND

It remains unclear which comorbidities, other than lipid parameters, or combination of comorbidities, best predicts cardiovascular events in patients with known coronary artery disease (CAD) treated with statins. Therefore, we aimed to identify the nonlipid-related prognostic factors and risk stratification of patients with stable CAD enrolled in the REAL-CAD study.

METHODS AND RESULTS

Blood pressure, glucose level, and renal function were considered as risk factors in the 11,141 enrolled patients. The primary endpoint was a composite of cardiovascular death, nonfatal myocardial infarction, nonfatal ischemic stroke, and unstable angina. The secondary composite endpoint was the primary endpoint and/or coronary revascularization. A significantly worse prognosis at the primary endpoint was observed in the estimated glomerular filtration rate (eGFR) ≤60 group, and the combination of eGFR ≤60 and HbA1c ≥6.0 was the worst (hazard ratio (HR) 1.66; P<0.001). However, even in the eGFR >60 group, systolic blood pressure (SBP) ≥140 mmHg met the secondary endpoint (HR 1.33; P=0.006), and the combination of eGFR ≤60 and HbA1c ≥6.0 was also the worst at the secondary endpoint (HR 1.35; P=0.002).

CONCLUSIONS

Regarding nonlipid prognostic factors contributing to the incidence of cardiovascular events in statin-treated CAD patients, renal dysfunction was the most significant, followed by poor glucose control and high SBP.

Trials using composite outcomes neglect the presence of competing risks: a methodological survey of cardiovascular studies

OBJECTIVE

To determine how frequently competing risks were accounted for in recently published cardiovascular disease (CVD) trials with composite end points.

STUDY DESIGN AND SETTING

We conducted a methodological survey of CVD trials that used composite end points and published from January 1 to September 27, 2021. The following databases were searched: PubMed, Medline, Embase, CINAHL, and Web of Science. Eligible studies were categorized according to whether they mentioned a competing risk analysis plan. If yes, whether a competing risk analysis was proposed as the primary or sensitivity analysis.

RESULTS

Among the 136 included studies, only 14 (10.3%) conducted a competing risk analysis and reported the corresponding results. Seven (50%) of them conducted a competing risk analysis as their primary analysis, whereas the other seven (50%) as a sensitivity analysis to assess the robustness of their findings. The most commonly used competing risk analysis methods were the subdistribution hazard model (nine studies), followed by the cause-specific hazard model (four studies) and restricted mean time lost method (one study). None of the studies accounted for competing risks in their sample size calculations.

CONCLUSION

Our findings underscore the pressing need for and importance of applying appropriate competing risk analysis in this field to disseminate clinically meaningful and unbiased results.

Impact of pitavastatin on new-onset diabetes mellitus compared to atorvastatin and rosuvastatin: a distributed network analysis of 10 real-world databases

BACKGROUND

Statin treatment increases the risk of new-onset diabetes mellitus (NODM); however, data directly comparing the risk of NODM among individual statins is limited. We compared the risk of NODM between patients using pitavastatin and atorvastatin or rosuvastatin using reliable, large-scale data.

METHODS

Data of electronic health records from ten hospitals converted to the Observational Medical Outcomes Partnership Common Data Model (n = 14,605,368 patients) were used to identify new users of pitavastatin, atorvastatin, or rosuvastatin (atorvastatin + rosuvastatin) for ≥ 180 days without a previous history of diabetes or HbA1c level ≥ 5.7%. We conducted a cohort study using Cox regression analysis to examine the hazard ratio (HR) of NODM after propensity score matching (PSM) and then performed an aggregate meta-analysis of the HR.

RESULTS

After 1:2 PSM, 10,238 new pitavastatin users (15,998 person-years of follow-up) and 18,605 atorvastatin + rosuvastatin users (33,477 person-years of follow-up) were pooled from 10 databases. The meta-analysis of the HRs demonstrated that pitavastatin resulted in a significantly reduced risk of NODM than atorvastatin + rosuvastatin (HR 0.72; 95% CI 0.59-0.87). In sub-analysis, pitavastatin was associated with a lower risk of NODM than atorvastatin or rosuvastatin after 1:1 PSM (HR 0.69; CI 0.54-0.88 and HR 0.74; CI 0.55-0.99, respectively). A consistently low risk of NODM in pitavastatin users was observed when compared with low-to-moderate-intensity atorvastatin + rosuvastatin users (HR 0.78; CI 0.62-0.98).

CONCLUSIONS

In this retrospective, multicenter active-comparator, new-user, cohort study, pitavastatin reduced the risk of NODM compared with atorvastatin or rosuvastatin.