Abstract
Purpose of the research
The atherogenic lipoprotein(a) [Lp(a)] is recommended to be measured at least once in each adult person’s lifetime. However, the testing frequency and its impact on lipid-lowering therapy is uncertain.
Methods
This retrospective analysis included patients 40–79 years old with at least two ambulatory clinic visits to a Midwestern healthcare system between 2018–2022. Within those patients, Lp(a) testing dates to 2004. Parameters included age, sex, race, traditional ASCVD risk factors, Lp(a) levels, and lipid-lowering therapy (LLT) prevalence. Lp(a) was considered elevated if Lp(a) ≥50 mg/dL or ≥125 nmol/L, respectively.
Results
Patients (n = 419,812) in the sample had a median (IQ range) age of 61 (52 – 71) years, with 61 % with dyslipidemia and 11 % ASCVD. Over 18 years, only 1.4 % of those without prior ASCVD and 4.9 % of those with ASCVD were tested for Lp(a). Median (IQR) Lp(a) levels in patients with and without ASCVD in mass and particle number were 20 (8, 55) mg/dL and 47 (19, 129) nmol/L, and 27 (10, 76) mg/dL and 59 (20, 174) nmol/L, respectively. Compared to those with normal Lp(a) levels, the prevalence of LLT was higher in patients with elevated Lp(a) across ASCVD risk categories including low risk patients (59 % vs 47 %) and those with established ASCVD (88 % vs 85 %).
Conclusions
Although testing for Lp(a) has improved, there is room for significant improvement, particularly in those with ASCVD. The higher use of LLT in all risk categories indicate that Lp(a) testing may have influenced treatment decisions.
Keywords: ASCVD risk, Lipid lowering therapy, Lipoprotein (a), Lp(a), cardiovascular prevention
1. Introduction
Reliable methods for assessing atherosclerotic cardiovascular disease (ASCVD) risk are essential for guiding preventive measures that reduce ASCVD morbidity and mortality [1]. Unfortunately, currently used risk factors fail to accurately identify a large proportion of those at high risk of ASCVD, and residual ASCVD risk persists, partly due to overlooked risk factors [2,3]. Among those overlooked risk factors is lipoprotein(a) [Lp(a)], a genetically determined atherogenic lipoprotein unaffected by lifestyle behaviors and most traditional lipid-lowering therapy (LLT), which is elevated in about 20 % of individuals, depending on sex and race [4].
Due to the atherogenic causing properties of Lp(a), there is a need to significantly increase the rate of testing for Lp(a) at all levels of the population, as epidemiological [5] and meta-analyses [6], Mendelian randomization studies [7] and genome-wide association studies [8] have shown that Lp(a) mediates myocardial infarction, stroke, and peripheral artery disease.
For this reason, a novel feature of the 2019 guideline was the recommendation to consider risk-enhancing factors, such as Lp(a), to aid in individual statin initiation decision-making [1]. While the guidelines consider Lp(a) a risk enhancer, there is no universal consensus on the recommendations for whom, when, and how often to test for Lp(a) [9]. Most recently, the 2024 updated guidelines by the National Lipid Association recommend that Lp(a) is measured at least once in each adult’s lifetime [10]. Real-world trends in Lp(a) testing have shown that testing frequencies vary depending on the healthcare center and the population served [11,12]. In the general population Lp(a) testing is 0.06 % of patients per year [11], but orders of magnitude greater in those with ischemic heart disease (2.9 %), aortic stenosis (3.1 %), individuals with a family history of CVD (3.3 %), stroke (1.7 %), and coronary artery calcification (6.1 %) [12]. In this study, we aimed to evaluate the patterns of real-world Lp(a) assessment in a large multicenter Midwest cohort, its association with ASCVD risk categories, test-retest variation in Lp(a) in consecutive measures, and the associations of elevated Lp(a) with LLT.
2. Methods
2.1. Study population and eligibility criteria
This retrospective observational study used data extracted from electronic health records (EHR) of patients who attended at least on two occasions an ambulatory primary care (family practice, Internal Medicine, OB/GYN) or cardiology clinic at Allina Health. This large Midwestern healthcare system includes over 90 clinics and ten hospitals across Minnesota and Wisconsin. Information about diagnoses, laboratory tests, and medications was extracted based on the International Classification of Diseases (ICD)-10 and CPT codes. This study used all applicable ethical standards approved by the Allina Health Institutional Review Board, reference number 2074,749–1. The database contained de-identified patient-level information to ensure confidentiality. Informed consent was waived, as this study utilized de-identified retrospective data, although patients had consented to the use of their EHR data.
This study included adults between the ages of ≥40 and ≤79 who had at least two ambulatory clinic visits between January 1, 2018, and December 31, 2022. Within these groups of patients, Lp(a) testing dates back to 2004. We excluded patients who did not consent to have their records used for research or who were pregnant. A diagnosis of myocardial infarction, ischemic stroke, percutaneous coronary intervention, or coronary artery bypass surgery defines the presence of ASCVD. In patients without ASCVD, the 10-year ASCVD risk was stratified using the Pooled Cohort Equation [13] and classified as low (0–5 %), borderline (5–7.5 %), intermediate (7.5–20 %), or high (>20 %). Patients with LDL ≥190 or missing data were excluded from this calculation. Smoking habits and the presence of diabetes, hypertension, and dyslipidemia were extracted from the patient’s list of active medical problems in the most recent appointment. Dyslipidemia was synonymous with hypercholesterolemia, hyperlipidemia, and hyperlipoproteinemia. Lp(a) mass concentration (mg/dL) assessment involved transitioning from Beckman Immage rate nephelometry assays on 5/4/2016 to Siemens BNII immunoturbidimetric assays until 3/16/2021. After this date, Lp(a) levels were quantified in particle number (nmol/L) using LabCorp immunoturbidimetric assays. To ensure consistency, only measurements from the same assay were compared; in cases of multiple comparisons, priority was given to the most recent assessment. A Lp(a) ≥50 mg/dL or ≥125 nmol/L was considered elevated [1,14]. The presence of any statin medication, proprotein convertase subtilisin/kexin type 9 inhibitor (PCSK9i), or ezetimibe on medication records defined LLT prescription. ASCVD risk variables, comorbidities, age, self-reported race, gender, and medication history were reported from the data collected at the latest clinic visit recorded during the study period. ASCVD risk was calculated regardless of LLT use. Medication data reflect prescriptions, not confirmed active use.
2.2. Endpoints
The primary endpoint was the prevalence of Lp(a) testing over 18 years according to ASCVD status. Secondary endpoints included the association of elevated Lp(a) with the prevalence of LLT across ASCVD risk categories and changes in repeated Lp(a) measurement levels.
2.3. Statistical analysis
Patients were classified as primary or secondary prevention based on their ASCVD status. We summarized continuous variables as medians (interquartile ranges, IQR) and categorical variables as counts and percentages ( %). We used the Wilcoxon rank sum test for continuous measures and Pearson’s Chi-squared test for categorical measures to compare demographic, clinical, and outcome variables between the groups.
For patients who underwent Lp(a) testing more than once, we explored longitudinal changes as the percent change between the minimum and maximum values of the same measurement unit. Logistic regression was used to determine the odds ratio (OR) of being tested for Lp(a), adjusted for age, sex, whether the individual was seen at a cardiology clinic or not, BMI, presence of ASCVD, dyslipidemia, hypertension, and current or former smoking status.
All analyses were performed using R version 4.3.0 (R Core Development) in the RStudio 2023 (Posit Software, PBC) environment.
3. Results
Baseline Demographics
A total of 419,812 patients were included in the study, with 48,068 (11.4 %) having clinical ASCVD. In this cohort, patients were primarily white (91.5 %) and more likely to be male (64 %). Comparing patients with ASCVD with those without ASCVD, patients with ASCVD were older with a median, interquartile range (IQR) age of 69.0 (61.0, 75.0) vs. 60 (51–69), had a higher prevalence of comorbidities such as dyslipidemia, 91 % vs. 55 %, diabetes, 38 % vs. 17 %, and hypertension, 87 % vs. 49 % (Table 1).
Table 1.
Demographics variables, selected comorbidities, smoking habits, and number of Lp(a) tests by group.
| Variables | Total | No ASCVD | ASCVD |
|---|---|---|---|
| n | 419,812 | 371,744 | 48,068 |
| Age, years | 61 (52- 70) | 60 (51–69) | 69 (61–75) |
| Males, n ( %) | 218,205 (48) | 201,041 (46) | 17,164 (64) |
| White, n ( %) | 375,884 (90) | 331,853 (89) | 44,031 (92) |
| BMI, kg/m2 | 29 (25, 34) | 29 (25–34) | 30 (26–34) |
| Dyslipidemia, n ( %) | 256,665 (61) | 212, 977 (55) | 43,668 (91) |
| Diabetes, n ( %) | 81,401 (19) | 62,971 (17) | 18,430 (38) |
| Hypertension, n ( %) | 223,228 (53) | 181,501 (49) | 41,727 (87) |
| Tobacco status | |||
| Everyday/somedays, n ( %) | 47,881 (11.4) | 41,165 (11) | 6755 (14) |
| Former smoker, n ( %) | 141,755 (34) | 118,978 (32) | 22,777(47) |
Values are median (IQR). BMI = body mass index. ASCVD = atherosclerotic cardiovascular disease. LLT = lipid-lowering therapy. PCSK9i = Proprotein convertase subtilisin/kexin type 9 inhibitors.
Prevalence of Lp(a) testing
Lp(a) testing was performed in 7618 (1.8 %) patients who had at least two clinic visits during the study period (Table 2). Among individuals tested, elevated lipoprotein(a) [Lp(a)] levels were observed in 1641 participants (30.2 %) when assessed by mass concentration, and in 615 participants (27.9 %) when measured by particle number, data not shown. Out of the 48,068 patients with ASCVD, only 2359 (4.9 %) were tested for Lp(a), and of the 371,744 patients without ASCVD, 5260 (1.4 %) were tested for Lp(a) (Table 2).
Table 2.
Frequency of Lp(a) testing and subsequent use of lipid lowering therapy in patients with and without Atherosclerotic Cardiovascular Disease.
| Variables | Total | No ASCVD | ASCVD |
|---|---|---|---|
| n | 419,812 | 371,744 | 48,068 |
| Tested Lp(a), n ( %) | 7618 (1.8) | 5260 (1.4) | 2359 (4.9) |
| LLT use | |||
| Statins, n ( %) | 161,962 (39.1) | 125,661 (33.8) | 36,301 (75.5) |
| Ezetimibe, n ( %) | 6051 (1.4) | 3332 (0.9) | 2719 (5.7) |
| PCSK9i, n ( %) | 1675 (0.4) | 669 (0.2) | 1006 (2.1) |
ASCVD = atherosclerotic cardiovascular disease. LLT = lipid-lowering therapy. PCSK9i = Proprotein convertase subtilisin/kexin type 9 inhibitors.
A total of 169,688 (40.4 %) were on LLT. Of the 48,068 patients with ASCVD, 83.3 % were on LLT, whereas of the 371,744 patients without ASCVD, 34.9 % were on LLT. For most patients with ASCVD, 75.5 % were prescribed statins, 5.7 % were prescribed ezetimibe, and 2.1 % were prescribed a PCSK9i. In contrast, patients without ASCVD had lower LLT prescription rates, with statins being 33.8 %, 0.9 % on ezetimibe, and 0.2 % on PCSK9i (Table 2).
Elevated Lp(a) was associated with higher LLT prescriptions in all ASCVD risk categories than low Lp(a) levels (Fig. 1). LLT prescription prevalence was 47 % in patients with low ASCVD risk and low Lp(a) versus 59 % in those with an elevated Lp(a) level (p < 0.001). When comparing the prevalence of LLT between low vs high Lp(a) levels, the same pattern was observed in all ASCVD risk categories: borderline ASCVD risk (66 % vs. 75 %; p = 0.04), intermediate ASCVD risk (72 % vs. 82 %; p < 0.001), and high ASCVD risk (75 % vs. 83 %; p < 0.005); and established ASCVD (85 % vs. 88 %; p < 0.032), for low vs high Lp(a) levels, respectively (Fig. 1).
Fig. 1.
Summary of findings.
Patients with dyslipidemia, ASCVD, who were male and seen by a cardiologist had an increased odds ratio for being tested for Lp(a), Table 3. The greatest odds ratio (95 % CI) of being tested for Lp(a) were observed in patients with dyslipidemia [8.90 (8.10, 9.80)] and those who had been diagnosed with ASCVD [2.31 (2.18, 2.44)], as shown in Table 3. Instead, patients with diabetes or current/former smokers were 24 % and 23 % less likely to be tested, respectively, as shown in Table 3. In addition, every year of age older was associated with a decreased odds ratio of 0.008 % of being tested for Lp(a), as shown in Table 3.
Table 3.
Odds ratio of being tested for Lp(a).
| Characteristic | OR (95 % CI) | p-value |
|---|---|---|
| Age | 0.992 (0.990, 0.994) | <0.001 |
| Male | 1.07 (1.02, 1.12) | 0.007 |
| Specialty = Cardiology | 1.81 (1.71, 1.91) | <0.001 |
| BMI | 0.969 (0.965, 0.973) | <0.001 |
| ASCVD | 2.31 (2.18, 2.44) | <0.001 |
| Dyslipidemia | 8.90 (8.10, 9.80) | <0.001 |
| Diabetes | 0.76 (0.72, 0.81) | <0.001 |
| Hypertension | 1.05 (0.99, 1.10) | 0.12 |
| Current/Former Smoking | 0.77 (0.73, 0.81) | <0.001 |
OR = Odds Ratio, CI = Confidence Interval.
Fluctuation in Lp(a) values on repeat testing
Among the 734 patients who underwent multiple Lp(a) mass concentration measurements, 432 patients had repeat measures using the rate nephelometry assay, while 186 patients used the immunoturbidimetry assay, as shown in Table 4. The median (IQ range) time in days between tests was 392.0 (178, 1113.8). This includes 12 patients who had repeated tests on the same day. After excluding the 12 patients, the median (IQ range) was 398 (182, 1119.5) days. The median (IQR) change was 12 mg/dL (4, 27) in the rate nephelometry assay and 7 mg/dL (3, 19) in the immunoturbidimetry assay, equating to 26 % and 18 % median change between the minimum and maximum levels, respectively (Table 4). For 116 patients with consecutive Lp(a) particle number measurements, the median (IQR) change was 20 nmol/L (6, 45), reflecting a 20 % median change between the minimum and maximum levels. A variance exceeding 20 % was observed in 411 patients: 61 % when measured by rate nephelometry assay for mass concentration, 47 % for the immunoturbidimetry assay for mass concentration, and 51 % with the immunoturbidimetry assay measuring particle number. Furthermore, 58 % of patients with LLT prescriptions showed a variance exceeding 20 %, compared to 49 % in those without LLT prescriptions (p = 0.03) (Table 5).
Table 4.
Lp(a) changes between visits by type of lab measurement method and percent change.
| Type of lab measurement |
||||
|---|---|---|---|---|
| Overall | mg/dL1 | mg/dL2 | nmol/L3 | |
| n | 432 | 186 | 116 | |
| Absolute change | 12 (4, 27) | 7 (3, 19) | 20 (6, 45) | |
| Percent change | 26 (13, 44) | 18 (9, 37) | 20 (9, 31) | |
| ≥ 10 % change, n ( %) | 569 (78) | 352 (81) | 133 (72) | 84 (72) |
| ≥ 20 % change, n ( %) | 411 (56) | 265 (61) | 87 (47) | 59 (51) |
Values = Median (IQR). indicates nephelometry assay1, immunoturbidimetry assay2, and quantified particle number method3. Absolute change = value visit 2 – value visit 1.
Table 5.
Percent Lp(a) change between visits in those on lipid-lowering therapy or not.
| Lipid-Lowering Therapy |
||||
|---|---|---|---|---|
| Overall | Yes | No | ||
| Total n | 734 | 554 | 180 | p-value |
| ≥ 10 % change, n ( %) | 569 (78) | 429 (77) | 140 (78) | >0.9 |
| ≥ 20 % change, n ( %) | 411 (56) | 323 (58) | 88 (49) | 0.03 |
Absolute change = value visit 2 – value visit 1.
4. Discussion
This analysis, conducted in a large Midwest healthcare system, revealed that <2 % of adults underwent testing for Lp(a) over an 18-year study period. The prevalence of Lp(a) testing was higher in those with established ASCVD (5 %), but it has remained suboptimal overall. Individuals with elevated Lp(a) were more likely to be on LLT across categories of ASCVD risk, though using LLT in those with ASCVD or high risk for ASCVD remains suboptimal. Further work is needed to optimize awareness of Lp(a) as a risk factor for ASCVD and determine the appropriate use of LLT for those with elevated Lp(a).
These results align with other real-world studies, which have shown that infrequent Lp(a) testing is common [11,12]. The 1.4 % prevalence of testing for Lp(a) falls short of the ACC/AHA guidelines recommendations for the primary prevention of CVD [1]. A retrospective cohort study using data from the Veterans Affairs (VA) EHR to evaluate annual Lp(a) testing rates between 2008 and 2014 showed a testing rate substantially lower than ours. However, similar to our results, the testing rate progressively rose in patients with and without ASCVD over nine years, with no difference by race, ethnicity, or age [15]. The potential reasons for the low levels of testing for Lp(a) are enumerated by Bhatia et al. [12], and include a lack of awareness of lipoprotein(a) as a CVD risk factor and deficient dissemination of the guideline for Lp(a) testing among healthcare providers, and how to assess and manage risk in patients with elevated Lp(a), concerns about insurance coverage, and uncertainty related to the variations in clinically available assays that reported Lp(a) levels.
Our findings build upon prior studies examining Lp(a) testing patterns, including the multisystem analyses by Bhatia et al. and Shah et al. [12,16]. Unlike these studies, which evaluated multiple healthcare systems, our study focuses on a single, integrated health system with uniform EHR data, including analyses of Lp(a) variability on repeat testing over an 18-year period. Additionally, our cohort includes primary and secondary prevention populations, allowing for a more focused assessment of Lp(a) testing in borderline and intermediate-risk groups, where its utility as a risk enhancer is most debated.
The proportion of patients in our cohort with elevated Lp(a) levels was similar to that reported by Varvel et al. in over half a million patients tested from a referral laboratory. They noted that the percentage of individuals with Lp(a) levels >50 mg/dL was 24 % [4]. However, those authors did not differentiate between those with and without ASCVD. We reported that the percentage of patients with elevated Lp(a) levels was greater in those with ASCVD than in those without ASCVD. The use of LLT may have impacted Lp(a) levels in our analysis, but this impact was likely only modest as the rates of PCSK9i use, which lower Lp(a) by approximately 20–30 %, were relatively low. Statins have been shown to potentially produce a modest increase in Lp(a), but other studies have shown a more neutral effect [17]. We also observed that non-statin LLTs were more common in those with elevated Lp(a). However, it is also possible that providers who prescribe more non-statin LLTs are more likely to test for Lp(a). Regardless, more routine Lp(a) testing will identify many patients at elevated ASCVD risk who are candidates for primary and secondary prevention.
Although described as 90 % genetically determined and stable throughout a lifetime [[17], [18], [19]], our cohort showed significant variability in repeat Lp(a) testing. The variability of repeat Lp(a) results in this study was more frequent when tested with the commercial assays using rate nephelometry, which is no longer in use. Generally, the coefficient of variation of Lp(a) testing of different testing methods is ≤ 10 % [20]. The more significant variation in Lp(a) in repeated testing in our cohort could be related to the use of LLT, although multiple other causes, such as certain inflammatory conditions, thyroid disorders, and a post-menopausal state, have been shown to cause variation in Lp(a) that we could not account for in our study [14].
Limitations of this study include its retrospective observational nature, the low diversity of the population, which attenuates the generalizability of the results, and the fact that the assessment of traditional risk factors was extracted from a problem list rather than actual measurements, which raises concerns about reliability. Another limitation of being a retrospective observational study is the inability to assess medication usage and determine medication adherence. However, a publication by our group showed that the use of lipid-lowering therapy varied depending on the presence or absence of ASCVD and the level of ASCVD risk. The data showed that it was greater in those with ASCVD and lowest in those at high risk of ASCVD [21]. However, this study also has significant strengths, including a large sample size and duration, which allowed for repeated testing in a substantial number of patients. Additionally, the primary outcome variable, Lp(a) testing, is an easily obtainable variable from the EHR, contributing to the increased reliability of the results.
5. Conclusion
In a large cohort of patients cared for by a large Midwestern healthcare system, we found the prevalence of Lp(a) testing to be low, regardless of baseline ASCVD risk status. While the use of LLT was higher in patients with elevated Lp(a), overall use of LLT remained suboptimal. Further efforts are needed to increase awareness of Lp(a) and its impact on ASCVD risk. Additionally, the trial results of novel Lp(a) lowering therapies on ASCVD outcomes may drive changes in guidelines for Lp(a) testing and treatment.
Lay summary
We conducted an observational study over 18 years in a large healthcare system to evaluate the prevalence of Lp(a) testing, its association with ASCVD risk categories, and LLT prescription. Additionally, we assessed the variability of Lp(a) consecutive measurements using different assays and its association with LLT prescription.
Key findings, see Fig. 1:
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•
Lp(a) testing prevalence was notably low (1.8 %) in the entire cohort and even in patients with established ASCVD (4.9 %).
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•
Elevated Lp(a) levels were associated with LLT prescription across all ASCVD risk categories. LLT prescription was associated with a high variability of repeat measures.
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•
The proportion of elevated Lp(a) results and variability of consecutive measurements greater than 20 % was more common when using rate nephelometry assay compared to immunoturbidimetry assays.
CRediT authorship contribution statement
Felipe Villa Martignoni: Writing – review & editing, Writing – original draft, Investigation. Ellen Cravero: Writing – review & editing, Formal analysis. Elizabeth Tuohy: Writing – review & editing. Thomas Knickelbine: Writing – review & editing. Otto A. Sánchez: Writing – review & editing, Formal analysis. Michael Miedema: Writing – review & editing, Methodology, Formal analysis, Conceptualization.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributor Information
Felipe Villa Martignoni, Email: felipe.martignoni@ttuhsc.edu.
Ellen Cravero, Email: ellen.cravero@allina.com.
Elizabeth Tuohy, Email: elizabeth.tuohy@allina.com.
Thomas Knickelbine, Email: thomas.knickelbine@allina.com.
Otto A. Sánchez, Email: otto.sanchezolarte@allina.com.
Michael Miedema, Email: michael.miedema@allina.com.
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