Cross-Database Mapping of PCSK9 Inhibitor Research: A Bibliometric Analysis of Scopus and PubMed

2.1. Search Strategy

2.2. Search in PubMed

Search: (evolocumab[Title]) OR (alirocumab[Title]) OR (inclisiran[Title]) OR (tafolecimab[Title]) OR (proprotein convertase subtilisin/kexin type 9 inhibitor[Title]) OR (PCSK9 inhibitor[Title]) OR (proprotein convertase subtilisin/kexin type 9 inhibition[Title]). Filters: Clinical Study, Clinical Trial, Clinical Trial Phase I, Clinical Trial Phase II, Clinical Trial Phase III, Clinical Trial Phase IV, Clinical Trial Protocol, Comparative Study, Controlled Clinical Trial, Meta-Analysis, Observational Study, Randomized Controlled Trial, Review, Veterinary, and 1994-2024.

The Boolean operator “OR” was used between keywords to search for relevant articles on PCSK9.

The search was limited to English-language publications. To improve accuracy, records from both databases were merged, and duplicates were removed. Details of the search strategy and workflow are illustrated in Fig. (1). The records were exported in comma-separated values (CSV), plaintext, and BibTeX formats for bibliographic management and analysis. The workflow included identification, screening, descriptive analysis, visual analysis, conceptual network analysis, and data visualization using Biblioshiny, the web interface of the bibliometrix R package, and VOSviewer for constructing and visualizing bibliometric networks.

2.3. Data Analysis

Descriptive statistics were used to summarize publication output, citations, authorship, sources, institutions, countries, and keywords. Bibliometric analyses were conducted using R software version 4.0.4 (R Foundation for Statistical Computing, Vienna, Austria) and the bibliometrix package [14]. Collaboration patterns among authors, countries, organizations, and keywords were analyzed and visualized. The Hirsch index (h-index) and generalized g-index were used as author- and source-level impact indicators. Spearman correlation coefficients were calculated using GraphPad Prism for Windows version 11.0.0 (GraphPad Software, San Diego, CA, United States).

3.1. Basic Characteristics of Data

A total of 1,390 documents on PCSK9 inhibitors were published between 1994 and 2024. These documents were sourced from 495 journals and other scholarly outlets, reflecting broad dissemination of research on this topic. The documents had a mean age of 5.02 years and a mean citation count of 37.09 citations per document, with 51,555 total citations overall. The dataset included 7,601 authors, 135 single-authored documents, and a mean of 9.91 co-authors per document. The international collaboration index was 1.871. Other characteristics of PCSK9 inhibitor research outputs are summarized in Table 1.

3.2. The Global Overview of Publication Outputs

Publication volume on PCSK9 inhibitors reflects the evolving research trends and growth of the field over time. Fig. (2) illustrates annual publication volume and mean total citations per article from 1994 to 2024. The data show a marked and sustained increase in publication output beginning in 2013, peaking at approximately 200 articles per year by 2024. Despite this growth, mean citations per article showed considerable volatility, with an early peak around 2008 followed by a subsequent decline. No significant correlation was observed between annual publication volume and mean total citations (TC) per article (r = 0.059, P = 0.832).

3.3. Highly Cited Documents on Global PCSK9 Inhibitors

The most-cited PCSK9 inhibitor documents identified in the bibliometric dataset are ranked in Table 2. The FOURIER trial had the highest citation score (TNC = 4,568), followed by the ODYSSEY OUTCOMES trial (TNC = 2,590). Pivotal inclisiran/ORION publications were also highly cited, accumulating 1,045 and 821 citations, respectively, indicating the emerging bibliometric visibility of RNA-based therapeutic approaches. Specialized evolocumab studies addressing familial hypercholesterolemia, including RUTHERFORD-2 and TESLA Part B, secured 672 and 649 citations, respectively, while the FOURIER peripheral artery disease subgroup analysis reached 628 citations. Overall, these findings show the dominance of monoclonal antibody outcome trials, alongside growing citation visibility for RNA-based PCSK9-targeted therapies.

Notably, no Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based gene-editing trials appeared in the top-cited list, suggesting that gene-editing approaches remain less visible in the clinical-trial-dominated PCSK9 inhibitor literature captured in this dataset.

3.4. Authorship Analysis

A total of 7,601 authors contributed to global PCSK9 inhibitor-associated publications. Wasserman S had the highest h-index (34), followed by Pordy R, who had 63 publications and an h-index of 32 (Table 3). Significant correlations were observed between the number of articles published per author and total citations (r = 0.222, P < 0.001), h-index (r = 0.918, P < 0.001), and generalized g-index (r = 0.2202, P < 0.001).

3.5. Document Source and Citation Analysis

Global PCSK9 inhibitor-associated publications appeared in 495 sources. The Journal of Clinical Lipidology led the field, contributing 72 publications that collectively received 1,862 citations (Table 4). Significant correlations were observed between the number of articles and h-index (r = 0.9078, P < 0.001), total citations (r = 0.648, P < 0.001), and generalized g-index (r = 0.961, P < 0.001).

3.6. Analysis of Corresponding Authors' Countries

Based on Scopus and PubMed data, PCSK9 inhibitor research has been conducted in 52 regions globally. The United States led output with 343 published articles, followed by China with 167 and Italy with 88 (Table 5). The United States also dominated citation impact, with 28,793 citations, far exceeding the United Kingdom (3,694) and the Netherlands (2,011). This citation gap reflects differences in research output and underscores the central role of the United States in generating high-impact, clinically transformative studies, including pioneering clinical trials and fundamental mechanistic discoveries that have shaped the global PCSK9 research agenda. The correlation analysis suggests that PCSK9 inhibitor research output was driven mainly by domestic research activity, particularly in highly productive countries, such as the United States, with international collaboration contributing less to overall publication volume.

A near-perfect correlation between the number of articles per country and single-country publications (SCP; r = 1.000, P < 0.001) indicates that research productivity is overwhelmingly driven by national efforts. This suggests that most countries conducting PCSK9 research possess the infrastructure and expertise to advance studies independently without extensive external partnerships. Conversely, the weak and non-significant correlation between articles per country and multiple-country publications (MCP; r = 0.224, P = 0.1103) implies that international collaborations remain limited and niche-driven rather than foundational to productivity. Author-level collaboration networks are presented in Fig. (3A).

3.7. Collaboration Network Analysis

International collaboration networks were analyzed for the top authors, institutions, and countries.

Collaboration network analysis of the top 50 authors revealed four distinct clusters. Fig. (3A) shows specialized yet interconnected groups within the PCSK9 inhibitor research community. Prominent authors, including Landmesser, Raal, Koenig, and Wasserman, were central figures within these collaborative networks. This structure highlights established patterns of partnership and knowledge exchange among leading experts in the field.

Figure 3B presents the collaboration network among the top 50 institutions contributing to global PCSK9 inhibitor research. The network is organized into eight distinct clusters, each representing a collaborative consortium. Cluster 1 includes Academic Medical Center, Clinical Development, Lipid Clinic, Columbia University, and Hospital Universitario Miguel Servet. Cluster 2, the largest and most diverse cluster, includes leading institutions from the United States, the United Kingdom, Australia, and Europe, such as Harvard Medical School, Mayo Clinic, Duke University, Imperial College London, the University of Sydney, the University of Oslo, and the University of Ulm. Cluster 3 includes the University of Cape Town, Baylor College of Medicine, Johns Hopkins University School of Medicine, the University of Western Australia, the University of the Witwatersrand, and the Metabolic and Atherosclerosis Research Center. Cluster 4 includes the University of Iowa and the Jacksonville Center for Clinical Research, Chicoutimi. Cluster 5 includes Oslo University Hospital, the University of Amsterdam, the University of the Witwatersrand, the Icahn School of Medicine at Mount Sinai, and Brigham and Women's Hospital. Cluster 6 includes the University of Toronto, University of Colorado School of Medicine, Leiden University Medical Center, Imperial College, University of Alabama at Birmingham, University of Alberta, State University of New York, Institute Cardiovascular de Rosario, Goethe University, Stanford University, Université de Paris, University of Kansas Medical Center, Netherlands Heart Institute, Auckland City Hospital, and University Medical Center Ljubljana. Cluster 7 includes Bern University Hospital, and Cluster 8 contains the University of Bern. These clusters suggest growing institutional cooperation in PCSK9 inhibitor research. Core institutions, including Harvard Medical School, Imperial College London, and Academic Medical Center, functioned as central hubs and highlight the key academic centers driving collaboration in this field.

Figure 3C shows the international collaboration network among the top 30 countries in PCSK9 inhibitor research. The analysis identified four main clusters. The United States, Italy, and the United Kingdom formed the largest and most connected group, whereas Japan, South Africa, and Brazil formed a separate cluster, indicating regional collaboration patterns. These results suggest that international partnerships remain concentrated within specific geographic and economic regions.

Keyword Plus terms are generated from the titles of cited references. LDL-C, low-density lipoprotein cholesterol; PCSK9, proprotein convertase subtilisin/kexin type 9

3.8. Word Cloud of the Top 100 Authors’ Keywords and Keyword Plus Occurrences

Figure 4A displays a word cloud of the top 100 authors' keywords used in global PCSK9 inhibitor research. The most frequent terms include “evolocumab,” “alirocumab,” “PCSK9,” “PCSK9 inhibitors,” “hypercholesterolemia,” “low-density lipoprotein cholesterol,” “PCSK9 inhibitor,” and “familial hypercholesterolemia.” This visual analysis highlights central clinical and pharmacological themes within the field. Keyword Plus refers to words or phrases generated from the titles of cited references. Fig. (4B) shows the Keyword Plus word cloud, which highlights broader related themes, such as lipid metabolism, cardiovascular risk, cholesterol lowering, clinical trials, and treatment outcomes. Together, Fig. (4A and 4B) indicate that PCSK9 inhibitor research is primarily focused on LDL-C reduction, monoclonal antibody therapies, hypercholesterolemia, and cardiovascular outcomes.

3.9. Thematic Evolution of Keyword Plus Terms, 1994-2024

RStudio (Posit, PBC, Boston, MA, United States) and the bibliometrix package were used to analyze PCSK9 inhibitor publications indexed in Scopus and PubMed. Thematic maps were interpreted according to the standard quadrants shown in Fig. (5A-5D): emerging or declining themes, basic themes, motor themes, and niche themes. Motor themes represent well-developed and central topics in the field, whereas niche themes represent specialized but relatively isolated topics in PCSK9 inhibitor research.

Figure 5A, Thematic Evolution: Time Slice 1 (1994-2018), presents research themes by density and centrality. In this period, clinical trials, the PCSK9 protein, and hypercholesterolemia emerged as established motor themes, representing well-developed and influential research clusters. Broader topics, such as human studies and lipid-lowering therapy, were identified as foundational or emerging themes, highlighting the field's shift toward targeted PCSK9 interventions.

Figure 5B presents “alirocumab,” “PCSK9,” “evolocumab,” “PCSK9 inhibitors,” and “hypercholesterolemia” as basic themes. These topics are central to the field and represent the core terminology of PCSK9 inhibitor research.

Figure 5C presents thematic evolution during Time Slice 3 (2021-2023) and reveals several key developments. The terms “lipid lowering” and “acute coronary syndromes” appear in the emerging themes quadrant, reflecting a shift in research focus toward clinical outcomes and patient groups.

Figure 5D highlights “lipoprotein,” “low-density lipoprotein,” and “pregnancy” as emerging themes in 2024. This pattern reflects a shift toward research on specialized metabolic contexts and specific patient groups. The appearance of “pregnancy” suggests increasing interest in the safety and effectiveness of PCSK9 inhibitors in maternal and gestational cardiovascular health.

3.10. Factorial Analysis Using Conceptual Structure Maps

Figure 6 maps key terms from PCSK9 inhibitor research according to their conceptual structure.

Based on Dimension 1 and Dimension 2, the analysis suggests that the field's themes are broadly interconnected rather than strongly separated when using the R-based science-mapping workflow [14].

The terms “monoclonal antibody” and “safety” had the highest values on Dimension 2, indicating distinct conceptual positioning. In contrast, terms, such as “PCSK9 inhibitor,” “inclisiran,” “cardiovascular disease,” and “acute coronary syndrome,” aligned closely along Dimension 1, reflecting their central and interrelated roles in the research landscape. Terms, such as “cost-effective” and “inflammation” also appeared, highlighting emerging or niche thematic directions Figure 6A.

Figure 6B presents a conceptual structure map generated through multiple correspondence analysis (MCA), organizing Keywords Plus terms into distinct conceptual clusters. The analysis revealed several coherent thematic groupings. The first cluster relates to clinical trial design and includes terms, such as “randomized controlled trial” and “placebo.” A second cluster relates to patient and study demographics, including “middle aged,” “adult,” “male,” and “female.” Another cluster covers lipid metabolism and biomarkers, including “low-density lipoprotein cholesterol,” “cholesterol blood level,” and “triacylglycerol.” Core pharmacological topics form a closely related cluster that includes “PCSK9 protein,” “monoclonal antibody,” “alirocumab,” and “hypercholesterolemia.” Terms, such as “cardiovascular disease” and “cardiovascular risk,” are positioned close to these clusters, indicating their relevance and direct association with the main research themes identified in the analysis.

4.1. From Landmark Trials to Shifting Research Priorities

Our time-series and keyword-trajectory analyses identify a rapid expansion in publications after 2013 that reflects the prominence of highly cited outcome trials, including FOURIER, ODYSSEY OUTCOMES, and phase 3 inclisiran studies (Table 2) [7-9]. These landmark studies demonstrated clinically meaningful LDL-C reduction and cardiovascular risk reduction, triggering a measurable redirection of publications away from mechanistic exploration toward outcomes research, guideline integration, and economic evaluation [4, 16]. Recent outputs accelerated (approximately 200 papers anticipated in 2024, representing approximately 14.4% of the corpus), and citation activity increased steeply in the mid-2010s; these transitions were followed by a clear reorientation of keyword prominence from mechanistic descriptors toward trial/outcome language (top keywords: LDL-C, evolocumab, alirocumab, and treatment outcome) (Figs. 2-5; Table 2). This study describes this pattern as trial-associated and time-linked, because we did not perform interrupted-time-series causal testing in the current analysis. However, this volumetric expansion in output did not translate into higher per-article citation impact: no significant correlation was found between the number of publications and the mean total citations per article (P = 0.832), indicating that a higher volume of output alone did not enhance the average impact of individual articles.

Despite this trial-triggered drive, the international collaboration rate (1.87) remained modest. Trial-sponsoring institutions in high-income countries continued to dominate authorship and citation networks, whereas LMIC contributions were relatively sparse. This pattern is reflected in country-level statistics: the number of articles per country correlated perfectly with single-country publications (r = 1.000, P < 0.001) but showed only a weak, non-significant association with multiple-country publications (r = 0.224, P = 0.1103), consistent with limited multi-country collaboration. Given the high cost and delivery challenges of PCSK9 inhibitors, this imbalance risks producing evidence that is poorly generalizable to regions bearing the greatest cardiovascular burden. Implementation has also been constrained by availability, payer policy, list price, prior authorization, and variable national reimbursement, which have limited PCSK9 inhibitor use to narrow high-risk groups and driven health economics, access-barrier, and implementation research [16-22].

4.2. Emerging RNA Therapeutics and Genome-Editing Approaches

Monoclonal antibody trials remain the dominant, mature evidence base. However, RNA-directed therapies, such as inclisiran, have rapidly gained thematic prominence and robust LDL-C lowering in phase 3 trials (ORION reports TNC = 1,045 and 821) [9], signaling movement from early mechanistic interest toward mid-stage clinical adoption. At the author level, productivity correlated strongly with impact metrics: the number of articles per author correlated significantly with total citations (r = 0.222, P < 0.001), with h-index (r = 0.918, P < 0.001), and with g-index (r = 0.2202, P < 0.001), indicating that more productive authors also have higher citation impact and established reputations. Keyword hotspots, such as inclisiran, indicate growing visibility, although relative citation maturity remains lower for these modalities, consistent with their earlier translational stage [9].

CRISPR/gene-editing approaches were not detected as hotspots in the dataset and do not appear among top-cited clinical publications, suggesting they remain at preclinical or early translational stages and are therefore outside the scope of the clinical-trial-dominated literature captured here.

4.3. Analytical exploration of LMIC underrepresentation

The underrepresentation of LMICs in PCSK9 inhibitor research goes beyond a simple publication gap; it reflects deeper structural inequities. Most studies are led by high-income countries with access to industry-sponsored trials, advanced research infrastructure, and early regulatory approvals. This concentration limits the applicability of evidence and guideline recommendations in regions where cardiovascular disease burden is high but access to PCSK9 inhibitors is restricted by cost and reimbursement barriers. Collaboration between countries remains limited, often leaving LMICs on the periphery rather than fully integrated into the research landscape.

Although integrating Scopus and PubMed improved coverage compared with single-database approaches, some regional indexes and non-indexed journals were not captured, meaning publications from LMICs may still be underrepresented. Reliance on citation-based metrics also tends to favor older, well-established outcome trials and may underrepresent emerging modalities, such as RNA-based therapies. While keyword and thematic analyses describe research visibility and evolution, they do not assess implementation outcomes, such as affordability, health-system feasibility, or treatment utilization in routine clinical care.

Importantly, while the bibliometric methods do not measure patient-level rates directly, publication trends mirror clinical milestones; publication activity rose markedly after 2013, following pivotal outcome trials, such as FOURIER and ODYSSEY OUTCOMES, which confirmed cardiovascular benefit beyond LDL-C reduction [7, 8]. However, real-world utilization has remained modest, largely due to non-clinical barriers including high drug costs, restrictive reimbursement policies, and prior-authorization requirements [17-21]. National and multinational observational reports also show persistent gaps in LDL-C control despite availability of high-intensity statins and add-on therapies [3, 17, 20-22].

Geographic patterns mirror access disparities, with North America and Western Europe leading research output, while Asia, Africa, and Latin America lag despite comparable disease burden. These findings highlight the need for inclusive trial designs, regional registry-based studies, and broader data integration to support equitable translation of PCSK9 inhibitor therapy into global cardiovascular care.