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. 2022 Jul 29:9:936651.
doi: 10.3389/fcvm.2022.936651. eCollection 2022.

Online searches for SGLT-2 inhibitors and GLP-1 receptor agonists correlate with prescription rates in the United States: An infodemiological study

Omar Dzaye  1 , Philipp Berning  1   2 , Alexander C Razavi  1   3 , Rishav Adhikari  1 , Kunal Jha  1 , Khurram Nasir  4 , John W Ayers  5 , Martin Bødtker Mortensen  1   6 , Michael J Blaha  1
Affiliations

Online searches for SGLT-2 inhibitors and GLP-1 receptor agonists correlate with prescription rates in the United States: An infodemiological study

Omar Dzaye et al. Front Cardiovasc Med. .

Abstract

Several clinical trials have demonstrated that many SGLT-2 inhibitors (SGLT2i) and GLP-1 receptor agonists (GLP-1 RA) can reduce the risk of cardiovascular events in patients with Type 2 diabetes and atherosclerotic cardiovascular disease. Recent reports indicate an underutilization of new cardiometabolic drugs, including SGLT2i and GLP-1 RA. We aimed to evaluate the use of online search volumes to reflect United States prescription rates. A repeated cross-sectional analysis of Google search volumes and corresponding data from the IQVIA National Prescription Audit (NPA) of pharmacy dispensing of newly prescribed drugs was performed. Monthly data for online searches and prescription between January 1, 2016 and December 31, 2021 were collected for selected SGLT2i and GLP-1 RA. Prescription data for drugs classes (SGLT2i and GLP-1 RA) and individual drugs were calculated as the total of queried data for branded drug names. Trends were analyzed for visual and quantitative correlation as well as predictive patterns. Overall, online searches increased by 157.6% (95% CI: 142.2-173.1%) and 295.2% (95% CI: 257.7-332.6%) for SGLT2i and GLP-1RA between 2016 and 2021. Prescription rates raised by 114.6% (95% CI: 110.8-118.4%) and 221.0% (95% CI: 212.1-229.9%) for SGLT2i and GLP-1RA for this period. Correlation coefficients (range 0.86-0.99) were strongest for drugs with growing number of prescriptions, for example dapagliflozin, empagliflozin, ertugliflozin, dulaglutide, and semaglutide. Online searches might represent an additional tool to monitor the utilization trends of cardiometabolic drugs. Associations were strongest for drugs with reported cardioprotective effect. Thus, trends in online searches complement conventionally acquired data to reflect and forecast prescription trends of cardiometabolic drugs.

Keywords: GLP-1 receptor agonist; Google trends; SGLT 2 inhibitors; cardiometabolic medicine; national prescription audit.

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Conflict of interest statement

MB reports grants from the National Institutes of Health, US Food and Drug Administration, American Heart Association, Bayer, and Novo Nordisk; Advisory Boards with Amgen, Sanofi, Regeneron, Novartis, Bayer, Novo Nordisk, Roche, Inozye, 89Bio, and Kaleido outside the submitted work. The remaining 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.

Figures

Figure 1
Figure 1
Trends in prescriptions and online searches for SGLT2i and GLP-1 RA brands between 2016 and 2021 for the United States. (A) Online searches and (B) prescriptions from 2016 to 2021 for SGLT2i (red line) and GLP-1 RA (blue line) as monthly query fraction/prescriptions per 10 million searches/prescriptions for summarized brands names are shown. (C) Trends in prescriptions (upper panel) and online searches (lower panel) for 4 selected SGLT2i brand names. (D) Trends in prescriptions (upper panel) and online searches (lower panel) for 5 selected GLP-1 RA brand names. All data are representative for the United Sates.
Figure 2
Figure 2
Trends in prescriptions and online searches for SGLT2i and GLP-1 RA drug names between 2016 and 2021 for the United States. Prescription rates for selected (A) SGLT2i and (B) GLP-1 RA drug names as monthly prescriptions per 10 million prescriptions are shown. Trends in online searches for (C) SGLT2i and (D) GLP-1 RA are depicted as monthly query fraction per 10 million searches. All data are representative for the United Sates between 2016 and 2021.
Figure 3
Figure 3
Correlation analyses between prescriptions and online searches for SGLT2i and GLP-1 RA. Correlation matrices for (A) drugs and corresponding brand names with increasing trends in both prescriptions and online searches (indicated by “searches”). (B) Drugs and corresponding brand names with overall decreasing trends in both prescriptions and online searches (indicated by “searches”). Spearman's correlation coefficients were calculated for the period between 2016 and 2021.
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