Associations of SGLT-2i with Cardiorenal Outcomes Among Diabetics with Prostate Cancer on Hormone Therapy

Associations of SGLT-2i with Cardiorenal Outcomes Among Diabetics with Prostate Cancer on Hormone Therapy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Associations of SGLT-2i with Cardiorenal Outcomes Among Diabetics with Prostate Cancer on Hormone Therapy Efstratios Koutroumpakis, Rushin Patel, Sumanth Khadke, Aram Bedrosian, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4510870/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Nov, 2024 Read the published version in Cardiovascular Drugs and Therapy → Version 1 posted 5 You are reading this latest preprint version Abstract Background Studies have reported associations between prostate cancer, type II diabetes mellitus (T2DM) and cardiovascular disease in the context of treatment with hormone therapy (HT). This study aimed to assess the role of Sodium-Glucose Cotransporter-2 Inhibitors (SGLT2i) in preventing adverse cardiovascular and renal outcomes in diabetics with prostate cancer. Methods Patients ≥ 18 years of age with T2DM and prostate cancer who received HT between August 1, 2013, and August 31, 2021, were identified using the TriNetX research network. Patients were divided into two cohorts based on treatment with SGLT2i or alternative antidiabetic therapies. The primary outcome was the composite of all-cause mortality, new onset heart failure (HF), acute myocardial infarction (MI), and peripheral artery disease over two years from HT initiation. Results After propensity score matching, 2,155 patients remained in each cohort. The primary composite outcome occurred in 218 patients (16.1%) in the SGLT2i cohort versus 355 patients (26.3%) in the non-SGLT2i cohort (HR 0.689, 95% CI 0.582–0.816; p < 0.001). Furthermore, SGLT2i were associated with significantly lower odds of HF, HF exacerbation, peripheral artery disease, atrial fibrillation/flutter, cardiac arrest, need for renal replacement therapy, overall emergency room visits/hospitalizations and all-cause mortality. Conclusions Use of SGLT2i for the treatment of T2DM among patients with prostate cancer on HT is associated with favorable cardiovascular, renal and all-cause mortality outcomes. This observation supports the hypothesis that a therapeutically relevant link exists between HT and cardiovascular disease in the context of prostate cancer. prostate cancer hormone therapy type II diabetes mellitus SGLT2 inhibitors cardiovascular outcomes Figures Figure 1 Figure 2 Introduction Prostate cancer is the most common type of cancer among men, aside from skin cancer, with an estimated number of new cases in the US exceeding 288,000 in 2023 1 . Many patients with prostate cancer live beyond a decade from diagnosis and frequently die from non-prostate cancer related causes 1 , 2 . Cardiovascular risk factors, including type 2 diabetes mellitus (T2DM) and cardiovascular disease are prevalent among patients with prostate cancer and represent a leading cause of mortality in this patient population 2 – 4 . Hormone therapy (HT), which is the backbone of prostate cancer therapy, has also been associated with cardiotoxicity through alterations in body composition, lipid abnormalities and impaired glucose control 5 . Even though the association of prostate cancer and HT with development of T2DM and cardiovascular disease is known for decades, a recent study reported that a significant portion of prostate cancer patients have undiagnosed or poorly controlled T2DM 6 , 7 . This suggests that there is an unmet need for early diagnosis and appropriate treatment of T2DM tailored towards the prevention of cardiovascular disease. Sodium-Glucose Cotransporter-2 Inhibitors (SGLT2i) have been associated with significant cardiovascular and renal benefits including prevention of heart failure (HF), renal failure and cardiovascular mortality, and have been recommended for the treatment of patients with T2DM at risk for or with established cardiovascular disease 8 . Despite the significant potential benefits of SGLT2i in patients with prostate cancer, patients with active cancer were excluded from the clinical trials that established the cardiorenal benefits of SGLT2i 9 – 12 . Therefore, their exact role and size of impact among patients with T2DM and prostate cancer treated with HT has not been established yet. We believe that improved understanding of the interaction of HT and SGLT2i in patients with prostate cancer will lead to a biologically sound strategy to mitigate the risk of cardiovascular disease. The aim of this study was to assess the incidence of adverse cardiovascular and renal outcomes in patients with prostate cancer on HT and T2DM treated with versus without SGLT2i using a large real-world database. Methods Study Oversight Each of the authors contributed to various aspects of the study, including data analysis, manuscript development as well as review. The need for Institutional Review Board (IRB) approval was waived by Lahey Clinic IRB due to the use of deidentified data for the analysis. The study findings are reported per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cohort studies. Data Source and Study Setting This study utilized the TriNetX Analytics Network – Research Network, which is a collaborative health research network that draws upon de-identified electronic health records (EHRs) data from various participating healthcare organizations including academic medical centers, specialty physician practices, and community hospitals. The research network encompasses data from nearly 111 million patients. The data remains anonymized and is presented in aggregated form, however the network's integrated analytics capabilities allow for the generation of patient-level data for tasks such as cohort selection and matching, as well as the analysis of the incidence and prevalence of events within a cohort. It also facilitates comparisons of characteristics and outcomes between matched cohorts. For further details about the database, additional information can be accessed online 13 . Study Population and Design The TriNetX research network was searched, and data curation was performed on August 31, 2023. A comparative retrospective cohort study was conducted, which included patients ≥ 18 years with pre-existing T2DM and a history of prostate cancer who received HT, which included GnRH analogs (leuprolide, triptorelin, goserelin, histrelin, relugolix, degarelix, abarelix) and/or androgen signaling inhibitors (enzalutamide, apalutamide, darolutamide, bicalutamide, flunamide, nilutamide and abiraterone) between August 1st, 2013 and August 31st, 2021. We elected to start our search from 2013 since earlier that year that the first SGLT2i was approved by FDA for the treatment of T2DM (canagliflozin, 3/29/2013) 14 , 15 . We ended our search in 2021 to allow for two years of follow up. A two-year follow-up period was decided based on the follow-up period used in the previously published SGLT2i trials evaluating cardiovascular outcomes 11 , 12 . Patients included in this study were further categorized in two cohorts based on their use of SGLT2i (canagliflozin, dapagliflozin, empagliflozin). Various cardiovascular outcomes were obtained during the two years follow-up following the index event defined as initiation of HT for prostate cancer. Patients with history of T2DM as well as prostate cancer were identified using two definitions based on the International Classification of Diseases, Tenth Revision (ICD-10) code. Identification of patients who were prescribed HT as well as SGLT2i was completed using the National Library of Medicine RxNorm terminology. Cohorts were matched using propensity score matching (PSM) using multiple baseline characteristics as deemed clinically significant. The Supplementary Appendix provides additional information on cohort definition criteria, analysis setup, outcome definitions and PSM. Study Endpoints/variables Main Composite Outcome The main composite outcome was all-cause mortality, HF, acute MI and peripheral artery disease (PAD) over two years from the index event of HT initiation. HF is any new diagnosis of HF and PAD any type of PAD as defined by the ICD codes provided in the supplementary appendix. Secondary Outcomes Secondary outcomes included individual outcomes of all-cause mortality, new onset HF, acute MI, PAD, HF exacerbation, LVEF < 50%, atrial fibrillation/flutter, cardiac arrest, ischemic stroke, need for renal replacement therapy and all-cause ER visits/hospitalizations. The outcomes were defined based on ICD or CPT codes and EHR extracted data. HF exacerbation was defined by the diagnostic codes plus need for IV diuretics. Statistical Analysis Patients with history of T2DM and prostate cancer who received HT were divided into 2 cohorts based on the use of SGLT2i: SGLT2i cohort and non-SGLT2i cohort. These two cohorts were compared using independent sample t-tests for continuous variables, reported as mean (range). Categorical variables are reported as counts (%) and compared using the Chi-square (χ2) test. To control for baseline differences in the patient cohorts, we performed 1:1 Propensity Score matching (PSM) for characteristics of clinical relevance utilizing a built-in algorithm that uses the greedy nearest-neighbor algorithm with a caliper of 0.1 pooled standard mean difference (SMD). Any characteristic with a SMD between the cohorts lower than 0.1 was considered well-matched. After propensity matching, time to event analysis reported as hazard ratios with 95% confidence intervals was performed for the primary outcome and odds ratios with 95% confidence intervals for the secondary outcomes using the χ2 for the measures of association. Absolute risk difference (ARD) was calculated as the subtraction of the absolute risk of the event in the treatment (SGLT2i) cohort and the absolute risk of the event in the control (non-SGLT2i) cohort. Furthermore, a sensitivity analysis was performed to evaluate the potential of significant confounding. For the sensitivity analysis we calculated E-values for the odds ratio as previously described 16 . A large E-value means that significant unmeasured confounding would be needed to explain away an effect estimate while a small E-value means that little unmeasured confounding would be needed to explain away an effect estimate. Statistical analyses were completed using the TriNetX online platform using R for statistical computing. Role of Funding Source: No Funding Source is involved. Results Study Population A total of 26,848 patients were identified with a history of T2DM and prostate cancer who received HT. Of the total patients, 2,741 patients received SGLT2i while 24,107 patients did not receive SGLT2i. After propensity score matching, 2,155 patients remained in each cohort (Table 1 ). Patient Demographics Table 1 outlines the baseline characteristics of each cohort before and after propensity matching. The mean age (± SD) of patients in the SGLT2i cohort was 66.8 ± 12.8 and 57.8% of patients were White adults. Before propensity matching, patients treated with SGLT2i had a higher prevalence of comorbidities, including hypertension, hyperlipidemia, ischemic heart disease, cardiomyopathy, HF, atrial fibrillation/flutter, chronic lower respiratory diseases, and chronic kidney disease. The proportion of metformin, glucagon-like peptide-1 (GLP-1) agonists, as well as insulin use was higher in the SGLT2i cohort. All baseline characteristics between the two cohorts, including healthcare utilization, were propensity matched, with no residual difference (standard mean difference for all included covariates was < 0·1; Table 1 ). Main Composite Outcome: Among patients with a history of T2DM and prostate cancer who received HT, patients who received SGLT2i had a lower risk of developing the composite outcome of all-cause mortality, HF, acute MI and peripheral artery disease over two years since initiation of HT, compared to propensity-matched controls who did not receive SGLT2i (HR 0.689, 95% CI 0.582–0.816; p < 0.001; Table 2 ; Fig. 1 ). The composite outcome occurred in 218 patients (16.1%) in the SGLT2i cohort as compared to 355 patients (26.3%) in the non-SGLT2i cohort (OR 0·54 CI 0·45 − 0·65; p < 0·001). The E value of the Odds ratio for the primary outcome was 2.47 and the E value for the lower confidence interval was 2.88, both of which support stronger association of SGLT2i with the observed differences in outcomes (Table 2 ). Secondary Outcomes: Patients who were on SGLT2i had lower odds of having new onset HF (OR = 0.66, CI 0.51–0.87, p = 0·003); HF exacerbation (OR = 0.82, CI 0.68-0·99, p = 0.037); PAD (OR = 0.64, CI 0.50–0.82, p < 0.001). The SGLT2i cohort also had lowers odds of all-cause mortality (OR = 0.41, CI 0.34-0·50, p < 0.001) as well as lower odds of cardiac arrest (OR = 0.51, CI 0.29–0.90, p = 0.019). There were also lower odds of Atrial Fibrillation/Flutter in the SGLT2i cohort (OR = 0.72, CI 0.54–0.96, p = 0.027). The need for renal replacement therapy (RRT) was significantly lower in the SGLT2i cohort compared to the non-SGLT2i cohort (OR = 0.24, CI 0.12–0.46, p < 0.001). The patients who received SGLT2i had lower odds of healthcare utilization in the form of ER visits/hospitalizations (OR = 0.54, CI 0.49–0.62, p < 0.001; Table 2 ; Fig. 2 ). Sensitivity analysis with E-values suggests stronger association of SGLT2i on observed outcomes and a low likelihood that differences in the outcomes are due to unmeasured confounders (Table 2 ). Discussion To our knowledge, this is the first, large, real-world study evaluating the incidence of adverse cardiovascular and renal outcomes among patients with prostate cancer on HT treated with SGLTi compared to other agents for T2DM. We found that among patients with prostate cancer, SGLT2i treatment was associated with a significantly lower risk of developing the composite outcome of all-cause mortality, new onset HF, acute MI and PAD over two years since initiation of HT. In the analysis of individual outcomes, SGLT2i were associated with lower odds of new onset HF, HF exacerbation, PAD, atrial fibrillation/flutter, cardiac arrest, need for RRT, overall ER visits/hospitalizations and all-cause mortality. Patients with prostate cancer represent a unique patient population with a high burden of comorbid cardiovascular conditions, including T2DM, as well as cardiovascular disease, which is a leading cause of death 2 – 4 . The high prevalence of cardiovascular disease among patients with prostate cancer has been attributed not only to the coexistence of shared risk factors but also the effects of HT. HT is the backbone of prostate cancer therapy and it is used for as many as 50% of patients with prostate cancer at some point in their disease course. In 2006, Keating et al. were one of the first to report an association between GnRH agonists and increased incidence of DM, coronary heart disease, MI, and sudden cardiac death 6 . Since then, several studies and clinical trials have confirmed that GnRH agonists, abiraterone, androgen receptor antagonists, and less so GnRH antagonists, are associated with increased incidence of adverse cardiovascular events. The mechanism of HT related cardiotoxicity includes hypogonadism-mediated alterations in body composition, with increase in adiposity and decrease in lean mass, lipid abnormalities (increase in triglycerides and LDL cholesterol) and impaired glucose control with decreased insulin sensitivity and subsequently elevated fasting serum glucose 5 . These metabolic derangements lead to an increase in circulating proinflammatory adipokines and prothrombotic markers with subsequent vascular endothelial dysfunction, vascular inflammation, and adverse cardiovascular and renal events 5 . Over the last decade, several large clinical trials have shown that treatment with SGLT2 inhibitors is associated with favorable cardiovascular and renal outcomes in patients with T2DM at risk of or with established cardiovascular disease but also in patients with HF and chronic kidney disease (CKD) without T2DM 9 – 12 . Empagliflozin was the first SGLT2i that received FDA approval in December of 2016 for reduction of cardiovascular death in adults with T2DM 17 . Subsequently, in May of 2020 FDA approved dapagliflozin for reducing the risk of cardiovascular death and HF hospitalizations in patients with HF with reduced ejection fraction regardless of diabetes status, 18 and in April of 2021 dapagliflozin was approved to reduce the risk of kidney function decline in adults with CKD 19 . More recently, in February of 2022, FDA approved empagliflozin to reduce the risk of cardiovascular death and hospitalizations in adults with HF regardless of ejection fraction 20 . In addition to the above benefits, recent evidence suggests that SGLT2i may also reduce the incidence of atrial fibrillation/flutter 21 . Our study findings further emphasize the importance of using SGLT2i in patients with T2DM to prevent adverse cardiorenal outcomes. Considering that cardiovascular disease is a major cause of death among a large portion of men with prostate cancer, treatment with SGLT2i might have a great impact in improving mortality and morbidity. Furthermore, SGLT2i might be able to mitigate the risk of cardiotoxicity mediated by HT. Despite the significant potential benefits, patients with prostate cancer were excluded from the above-mentioned clinical trials and the exact role and size of impact of SGLT2i in preventing adverse cardiovascular and renal outcomes among patients with T2DM and prostate cancer treated with HT has not been examined. Our study is the first one to report a significant reduction in the risk of adverse cardiorenal outcomes among patients with prostate cancer on HT and T2DM treated with vs without SGLT2i. We hypothesize that by inducing glucosuria and natriuresis, SGLT2i improve hyperglycemia and hypertension, the two major risk factors contributing to the development of cardiovascular disease among patients with prostate cancer treated with HT 22 , 23 . Furthermore, similar to patients with HF, it is likely that SGLT2i alter adipokine signaling and reduce inflammation, which could prevent HT-related cardiotoxicity 22 , 23 . Based upon clinical observations and convergent data, our group has also postulated that a subset of prostate cancers is part of an “overlap syndrome” of age-related illnesses, including cardiovascular disease, with shared biology 24 . The findings of this study suggest that SGLT2i warrant further investigation in this subset of patients since it has the potential to improve survival. In addition to the favorable cardiorenal benefits of SGLT2i among patients with prostate cancer, preclinical studies have suggested functional expression of SGLT receptors in prostate adenocarcinomas and that treatment with SGLT2i might lead to favorable oncologic outcomes as well 25 . Studies evaluating the role of SGLT2i in prostate cancer-specific outcomes in human subjects are currently underway (NCT04887935). Such trials may also be able to assess the cardiovascular benefits of SGLT2i in patients with prostate cancer irrespective of the presence of T2DM. Study Limitations: Our study has several limitations including those inherent to observational studies such as selection bias. Most importantly, despite our efforts to carefully control for baseline differences in the SGLT2i versus non-SGLT2i cohort using propensity matching, unmeasured confounding may still exist. To eliminate this possibility, we performed a sensitivity analysis of patients with prostate cancer treated with vs without SGLT2i, the results of which indicated that the findings are unlikely to be explained by unmeasured confounders. Patients on SGLT2i may have also have socioeconomic differences related to access to medications, which cannot be assessed in this study. Differences in the type of HT that the two patient groups received, and the stage of their prostate cancer could not be assessed either, due to limitations of the database used. Furthermore, retrospective data curated from electronic medical records may be inaccurate or carry the risk of biases. This risk is somewhat mitigated by the large number of patients included in our study and the large effect size. Finally, this study did not assess side effects related to SGLT2i or prostate cancer specific outcomes. Conclusions This study demonstrated that the use of SGLT2i for the treatment of T2DM was associated with significantly lower risk for developing the composite outcome of all-cause mortality, new onset HF, acute MI and PAD among patients with prostate cancer treated with HT. Clinical trials assessing the impact of SGLT2i in patients without T2DM or HF in reducing CV events associated with HT or prostate cancer outcomes are needed. Declarations Author Declarations: Funding: The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Conflicts of Interest/Competing Interests: EK is supported in part by NIH/NCI 1RO1HL157273 and by CPRIT RP200381. AD is supported in part by the Ting Tsung and Wei Fong Chao Distinguished Chair and is a consultant for Bayer. JB is consultant for Abbott, American Regent, Amgen, Applied Therapeutic, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardiac Dimension, Cardior, CVRx, Cytokinetics, Edwards, Element Science, Innolife, Impulse Dynamics, Imbria, Inventiva, Lexicon, Lilly, LivaNova, Janssen, Medtronics, Merck, Occlutech, Novartis, Novo Nordisk, Pfizer, Pharmacosmos, Pharmain, Roche, Sequana, SQ Innovation, and Vifor. AWH is consultant for Janssen, Intellisphere, Exelixis, has received honoraria from Medscape, Binaytara Foundation, travel support from Dava Oncology and institutional funding from Bayer and Eisai. The remaining authors have nothing to disclose. Availability of data and material: The data are available upon request by email to the corresponding authors. Code availability: Not applicable. Authors’ Contributions: All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Efstratios Koutroumpakis, Rushin Patel, Sumanth Khadke and Sarju Ganatra. The first draft of the manuscript was written by Efstratios Koutroumpakis and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Ethics approval: This is an observational study. The need for Institutional Review Board (IRB) approval was waived by Lahey Clinic IRB due to the use of deidentified data for the analysis. The study findings are reported per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cohort studies. Consent to participate: Not applicable. Consent for publication: Not applicable. References Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73(1):17-48. Shikanov S, Kocherginsky M, Shalhav AL, Eggener SE. Cause-specific mortality following radical prostatectomy. 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Sodium‐Glucose Co‐Transporter Inhibitors and Atrial Fibrillation: A Systematic Review and Meta‐Analysis of Randomized Controlled Trials. Journal of the American Heart Association. 2021;10(17):e022222. Lopaschuk GD, Verma S. Mechanisms of Cardiovascular Benefits of Sodium Glucose Co-Transporter 2 (SGLT2) Inhibitors: A State-of-the-Art Review. JACC Basic Transl Sci. 2020;5(6):632-644. Koutroumpakis E, Jozwik B, Aguilar D, Taegtmeyer H. Strategies of Unloading the Failing Heart from Metabolic Stress. Am J Med. 2020;133(3):290-296. Logothetis CJ, Hahn AW. Challenging the Prevailing Therapeutic Dogma for Prostate Cancer: The Case for an Overlap Syndrome. Eur Urol. 2023. Scafoglio C, Hirayama BA, Kepe V, et al. Functional expression of sodium-glucose transporters in cancer. Proc Natl Acad Sci U S A. 2015;112(30):E4111-4119. Tables Table 1. Baseline demographics and clinical characteristics of patients with prostate cancer on androgen deprivation therapy separated by treatment with or without SGLT2 inhibitors for type II diabetes mellitus, before and after propensity score matching. Before Propensity matching After Propensity Matching Baseline Characteristics SGLT2 inhibitor (n=2,741) No SGLT2 inhibitor (n=24,107) SMD SGLT2 inhibitor (n=2,155) No SGLT2 inhibitor (n=2,155) SMD Demographics Age, years 66.6 +/- 12.7 (Mean ± SD) 67.8 +/- 14.7 (Mean ± SD) 0.085 66.8 +/- 12.8 (Mean ± SD) 66.8 +/- 15.0 (Mean ± SD) 0.001 White 1,564 (57.1%) 14,552 (60.4%) 0.067 1,245 (57.8%) 1,259 (58.4%) 0.013 Non-Hispanic or Latino 1,892 (69.0%) 16,619 (68.9%) 0.002 1,475 (68.4%) 1,461 (67.8%) 0.014 Comorbidities Hypertension 2,211 (80.7%) 14,735 (61.1%) 0.440 1,680 (78.0%) 1,658 (76.9%) 0.024 Hyperlipidemia 2,055 (75.0%) 11,856 (49.2%) 0.551 1,527 (70.9%) 1,509 (70.0%) 0.018 Ischemic heart disease 1,066 (38.9%) 6,008 (24.9%) 0.303 788 (36.6%) 774 (35.9%) 0.014 Cardiomyopathy 304 (11.1%) 1,002 (4.2%) 0.264 206 (9.6%) 199 (9.2%) 0.011 Heart Failure 602 (22.0%) 2,690 (11.2%) 0.294 423 (19.6%) 414 (19.2%) 0.011 Ischemic stroke 402 (14.7%) 2,784 (11.5%) 0.092 311 (14.4%) 324 (15.0%) 0.017 Atrial fibrillation and flutter 456 (16.6%) 2,709 (11.2%) 0.156 325 (15.1%) 326 (15.1%) 0.001 Chronic lower respiratory diseases 745 (27.2%) 4,370 (18.1%) 0.218 538 (25.0%) 535 (24.8%) 0.003 Chronic kidney disease (CKD) 706 (25.8%) 4,094 (17.0%) 0.215 509 (23.6%) 477 (22.1%) 0.035 Metastatic cancer 743 (27.1%) 5,493 (22.8%) 0.100 606 (28.1%) 623 (28.9%) 0.017 Procedures Surgical Procedures on the Male Genital System 959 (35.0%) 5,984 (24.8%) 0.223 685(31.8%) 631(29.3%) 0.054 Radiation Oncology Treatment 744 (27.1%) 1,945 (8.1%) 0.517 469(21.8%) 443(20.6%) 0.030 Medications Statins 2,182 (79.6%) 11,330 (47.0%) 0.719 1,629 (75.6%) 1,640 (76.1%) 0.012 Antiarrhythmics 1,764 (64.4%) 10,092 (41.9%) 0.463 1,296 (60.1%) 1,287 (59.7%) 0.009 ACE inhibitors 1,435 (52.4%) 7,767 (32.2%) 0.416 1,077 (50.0%) 1,062 (49.3%) 0.014 Angiotensin II Inhibitors 1,069 (39.0%) 4,189 (17.4%) 0.494 754 (35.0%) 747 (34.7%) 0.007 Loop diuretics 1,572 (57.4%) 8,782 (36.4%) 0.429 1,175 (54.5%) 1,161 (53.9%) 0.013 Beta Blockers 1,671 (61.0%) 9,443 (39.2%) 0.447 1,247 (57.9%) 1,256 (58.3%) 0.008 Calcium Channel Blockers 1,236 (45.1%) 6,737 (27.9%) 0.362 908 (42.1%) 888 (41.2%) 0.019 Insulin 1,513 (55.2%) 6,742 (28.0%) 0.575 1,095 (50.8%) 1,127 (52.3%) 0.030 Metformin 1,971 (71.9%) 7,100 (29.5%) 0.938 1,439 (66.8%) 1,483 (68.8%) 0.044 Sitagliptin 628 (2.9%) 1,306 (5.4%) 0.518 391 (18.1%) 417 (19.4%) 0.031 Exenatide 114 (4.2%) 168 (0.7%) 0.226 68 (3.2%) 64 (3.0%) 0.011 Dulaglutide 314 (11.5%) 185 (0.8%) 0.458 126 (5.8%) 109 (5.1%) 0.035 Liraglutide 223 (8.1%) 258 (1.1%) 0.342 117 (5.4%) 112 (5.2%) 0.010 Semaglutide 119 (4.3%) 50 (0.2%) 0.280 40 (1.9%) 28 (1.3%) 0.045 Lixisenatide 18 (0.7%) 11 (0.0%) 0.103 10 (0.5%) 10 (0.5%) <0.001 Glipizide 657 (24.0%) 2,103 (8.7%) 0.421 448 (20.8%) 467 (21.7%) 0.022 Aspirin 1,512 (55.2%) 8,525 (35.4%) 0.406 1,134 (52.6%) 1,139 (52.9%) 0.005 Apixaban 294 (10.7%) 750 (3.1%) 0.304 178 (8.3%) 170 (7.9%) 0.014 Warfarin 221 (8.1%) 2,010 (8.3%) 0.010 185 (8.6%) 202 (9.4%) 0.028 Rivaroxaban 162 (5.9%) 606 (2.5%) 0.170 104 (4.8%) 124(5.8%) 0.041 Clopidogrel 441 (16.1%) 2,191 (9.1%) 0.212 327 (15.2%) 348(16.1%) 0.027 Ticagrelor 87 (3.2%) 166 (0.7%) 0.181 45 (2.1%) 42(1.9%) 0.010 Labs Creatinine (mg/dL) 1.1 +/- 2.4 1.3 +/- 2.4 0.050 1.1 +/- 0.5 1.2 +/- 0.9 0.036 Hemoglobin (g/dL) 12.8 +/- 1.9 12.5 +/- 2.2 0.144 12.8 +/- 1.9 12.3 +/- 2.2 0.026 Cholesterol LDL ≥130 mg/dL 590 (21.5%) 3,317 (13.8%) 0.205 441(20.5%) 427 (19.8%) 0.016 BNP ≥150 pg/ml 257 (9.4%) 1,096 (4.5%) 0.191 174 (8.1%) 170 (7.9%) 0.007 NT-pro BNP ≥450 pg/ml 154 (5.6%) 728 (3.0%) 0.128 115 (5.3%) 109 (5.1%) 0.013 Hemoglobin A1c ≥7.0% 1,615 (58.9%) 5,329 (22.1%) 0.809 1,125 (52.2%) 1,111 (51.6%) 0.013 BMI ≥ 30kg/m 2 972 (35.5%) 6,268 (26.0%) 0.206 734 (34.1%) 696 (32.3%) 0.037 Left Ventricular Ejection Fraction (LVEF) <40% 54 (2.0%) 130 (0.5%) 0.129 34 (1.6%) 33 (1.5%) 0.004 Abbreviations: SMD: Standardized Mean difference; SGLT2 – Sodium-glucose cotransporter 2; Table 2. Comparison of primary and secondary outcomes of patients with prostate cancer on androgen deprivation therapy who were treated with or without SGLT2 inhibitors for type II diabetes mellitus. Outcomes SGLT2 inhibitor (n=2,155) No SGLT2 inhibitor (n=2,155) ARD (95% CI) Odd Ratio (95% CI) p-value E-value for OR E-value for lower bound CI of OR Composite of Outcomes (All-cause mortality/ HF/AMI/PAD) 218(16.1%) (n=1,351) 355(26.3%) (n=1,349) -0.102 (-0.132, -0.071) 0.539 (0.446, 0.651) (HR 0.689, 95% CI 0.582-0.816; p<0.001) <0.001 2.47 2.88 All-Cause Mortality 168(7.8%) (n=2,155) 365(16.9%) (n=2,155) -0.091 (-0.111, -0.072) 0.415 (0.342, 0.503) <0.001 4.31 5.33 Heart Failure 95(5.6%) (n=1,710) 141(8.1%) (n=1,734) -0.026 (-0.043, -0.009) 0.665 (0.508, 0.870) 0.003 2.4 3.33 Acute Myocardial Infarction 45(2.3%) (n=1,951) 65(3.3%) (n=1,952) -0.010 (-0.021, 0.000) 0.685 (0.466, 1.008) 0.053 2.3 3.77 Peripheral Artery Disease 115(7.0%) (n=1,636) 171(10.5%) (n=1,633) -0.034 (-0.054, -0.015) 0.646 (0.505, 0.828) <0.001 2.5 3.41 Heart Failure Exacerbation 243(11.3%) (n=2,155) 288(13.4%) (n=2,155) -0.021 (-0.040, -0.001) 0.824 (0.687, 0.989) 0.037 1.74 2.3 Left Ventricular Ejection Fraction <50% 12(0.57%) (n=2,083) 24(1.1%) (n=2,096) -0.006 (-0.011, -0.000) 0.503 (0.252, 1.003) 0.047 3.41 7.46 Atrial Fibrillation/Flutter 83(4.6%) (n=1,819) 113(6.2%) (n=1,816) -0.017 (-0.031, -0.002) 0.721 (0.539, 0.964) 0.027 2,12 3.18 Cardiac Arrest 18(0.83) (n=2,155) 35(1.6%) (n=2,155) -0.008 (-0.014, -0.001) 0.510 (0.288, 0.904) 0.019 3.33 6.6 Ischemic Stroke 40(1.98) (n=2,014) 47(2.3) (n=2,004) -0.004 (-0.013, 0.005) 0.844 (0.551, 1.292) 0.434 1.67 3.04 Renal Replacement Therapy 11(0.5%) (n=2,155) 45(2.1%) (n=2,155) -0.016 (-0.023, -0.009) 0.241 (0.124, 0.466) <0.001 7.8 16.15 ER Visit/Hospitalization 894(41.5%) (n=2,155) 1,216(56.4%) (n=2,155) -0.149 (-0.179, -0.120) 0.547 (0.485, 0.618) <0.001 3.11 3.59 Abbreviations: SGLT2 – Sodium-glucose transport protein 2; ARD – Absolute risk difference; HF – heart failure; AMI – acute myocardial infarction; PAD – peripheral artery disease; ER – emergency room Supplementary Files SupplementalappendixSGLT2iprostatecancer.docx Cite Share Download PDF Status: Published Journal Publication published 11 Nov, 2024 Read the published version in Cardiovascular Drugs and Therapy → Version 1 posted Reviewers agreed at journal 02 Jul, 2024 Reviewers invited by journal 02 Jul, 2024 Editor invited by journal 26 Jun, 2024 Editor assigned by journal 24 Jun, 2024 First submitted to journal 23 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4510870","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":321875485,"identity":"63299bd4-bfbc-4a9c-bc37-88c46034ec4f","order_by":0,"name":"Efstratios Koutroumpakis","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIie3PoQoCMRjA8Y0DLSdXBZF7hQNBDL6JxUOYaf2CytJZBlaD6CtoOREM3xjMcmIVLCbNtrM5RQ3CedoE9w/fxtgPNoRMpl/Mvq8eyiFAgd5ZFssm8CTxleAvCMLh9SiDuFyq0mlZ9+d55YvzuNtw+pokQZRKvHVIinAg/oITkIVoRYcSM8zjXTpx7GoRQPpTaDOJI0X1ZBYO04k7eJDNkYnzSNFJFkFrfidbAlBgHTrNIl6sWrUYSGUxPDSlrYDONBHv/uLyltgGUC/PHVI5JZ0eHW+k2CfBm4e9JG8TPr6v631z2WQymf6kC1g7Zsj9amF8AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-6757-6480","institution":"The University of Texas MD Anderson Cancer Center","correspondingAuthor":true,"prefix":"","firstName":"Efstratios","middleName":"","lastName":"Koutroumpakis","suffix":""},{"id":321875486,"identity":"f8ee2c6d-dd71-40c2-bcac-163c1f2061fa","order_by":1,"name":"Rushin Patel","email":"","orcid":"","institution":"Lahey Hospital and Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Rushin","middleName":"","lastName":"Patel","suffix":""},{"id":321875487,"identity":"8fd9afc0-3578-40c8-8e1c-95f4a667d816","order_by":2,"name":"Sumanth Khadke","email":"","orcid":"","institution":"Lahey Hospital and Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Sumanth","middleName":"","lastName":"Khadke","suffix":""},{"id":321875488,"identity":"5ca1b5f5-cc3e-4792-b5bd-ea36753fdc48","order_by":3,"name":"Aram Bedrosian","email":"","orcid":"","institution":"Lahey Hospital and Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Aram","middleName":"","lastName":"Bedrosian","suffix":""},{"id":321875489,"identity":"51beeefc-124d-4b78-bed3-8bf503bfe121","order_by":4,"name":"Ashish Kumar","email":"","orcid":"","institution":"Cleveland Clinic Akron General","correspondingAuthor":false,"prefix":"","firstName":"Ashish","middleName":"","lastName":"Kumar","suffix":""},{"id":321875490,"identity":"1ab86abc-1073-444b-9b5d-6df652e48601","order_by":5,"name":"Yixin Kong","email":"","orcid":"","institution":"Lahey Hospital and Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Yixin","middleName":"","lastName":"Kong","suffix":""},{"id":321875491,"identity":"fff03b3e-33e6-45e4-b0a8-eb9f2880aff1","order_by":6,"name":"Brendan Connell","email":"","orcid":"","institution":"Lahey Hospital and Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Brendan","middleName":"","lastName":"Connell","suffix":""},{"id":321875492,"identity":"e805a1a5-bcf4-41ac-89a2-bdee0b160421","order_by":7,"name":"Jagriti Upadhyay","email":"","orcid":"","institution":"Lahey Hospital and Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Jagriti","middleName":"","lastName":"Upadhyay","suffix":""},{"id":321875493,"identity":"f2498b74-d599-46cd-9f8e-c3515e03cf69","order_by":8,"name":"Sourbha S. 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Many patients with prostate cancer live beyond a decade from diagnosis and frequently die from non-prostate cancer related causes \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Cardiovascular risk factors, including type 2 diabetes mellitus (T2DM) and cardiovascular disease are prevalent among patients with prostate cancer and represent a leading cause of mortality in this patient population \u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Hormone therapy (HT), which is the backbone of prostate cancer therapy, has also been associated with cardiotoxicity through alterations in body composition, lipid abnormalities and impaired glucose control \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Even though the association of prostate cancer and HT with development of T2DM and cardiovascular disease is known for decades, a recent study reported that a significant portion of prostate cancer patients have undiagnosed or poorly controlled T2DM \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. This suggests that there is an unmet need for early diagnosis and appropriate treatment of T2DM tailored towards the prevention of cardiovascular disease.\u003c/p\u003e \u003cp\u003eSodium-Glucose Cotransporter-2 Inhibitors (SGLT2i) have been associated with significant cardiovascular and renal benefits including prevention of heart failure (HF), renal failure and cardiovascular mortality, and have been recommended for the treatment of patients with T2DM at risk for or with established cardiovascular disease \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Despite the significant potential benefits of SGLT2i in patients with prostate cancer, patients with active cancer were excluded from the clinical trials that established the cardiorenal benefits of SGLT2i \u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Therefore, their exact role and size of impact among patients with T2DM and prostate cancer treated with HT has not been established yet. We believe that improved understanding of the interaction of HT and SGLT2i in patients with prostate cancer will lead to a biologically sound strategy to mitigate the risk of cardiovascular disease. The aim of this study was to assess the incidence of adverse cardiovascular and renal outcomes in patients with prostate cancer on HT and T2DM treated with versus without SGLT2i using a large real-world database.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Oversight\u003c/h2\u003e \u003cp\u003eEach of the authors contributed to various aspects of the study, including data analysis, manuscript development as well as review. The need for Institutional Review Board (IRB) approval was waived by Lahey Clinic IRB due to the use of deidentified data for the analysis. The study findings are reported per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cohort studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData Source and Study Setting\u003c/h2\u003e \u003cp\u003eThis study utilized the TriNetX Analytics Network \u0026ndash; Research Network, which is a collaborative health research network that draws upon de-identified electronic health records (EHRs) data from various participating healthcare organizations including academic medical centers, specialty physician practices, and community hospitals. The research network encompasses data from nearly 111\u0026nbsp;million patients. The data remains anonymized and is presented in aggregated form, however the network's integrated analytics capabilities allow for the generation of patient-level data for tasks such as cohort selection and matching, as well as the analysis of the incidence and prevalence of events within a cohort. It also facilitates comparisons of characteristics and outcomes between matched cohorts. For further details about the database, additional information can be accessed online \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population and Design\u003c/h2\u003e \u003cp\u003eThe TriNetX research network was searched, and data curation was performed on August 31, 2023. A comparative retrospective cohort study was conducted, which included patients\u0026thinsp;\u0026ge;\u0026thinsp;18 years with pre-existing T2DM and a history of prostate cancer who received HT, which included GnRH analogs (leuprolide, triptorelin, goserelin, histrelin, relugolix, degarelix, abarelix) and/or androgen signaling inhibitors (enzalutamide, apalutamide, darolutamide, bicalutamide, flunamide, nilutamide and abiraterone) between August 1st, 2013 and August 31st, 2021. We elected to start our search from 2013 since earlier that year that the first SGLT2i was approved by FDA for the treatment of T2DM (canagliflozin, 3/29/2013) \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. We ended our search in 2021 to allow for two years of follow up. A two-year follow-up period was decided based on the follow-up period used in the previously published SGLT2i trials evaluating cardiovascular outcomes\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Patients included in this study were further categorized in two cohorts based on their use of SGLT2i (canagliflozin, dapagliflozin, empagliflozin). Various cardiovascular outcomes were obtained during the two years follow-up following the index event defined as initiation of HT for prostate cancer.\u003c/p\u003e \u003cp\u003ePatients with history of T2DM as well as prostate cancer were identified using two definitions based on the International Classification of Diseases, Tenth Revision (ICD-10) code. Identification of patients who were prescribed HT as well as SGLT2i was completed using the National Library of Medicine RxNorm terminology. Cohorts were matched using propensity score matching (PSM) using multiple baseline characteristics as deemed clinically significant. The Supplementary Appendix provides additional information on cohort definition criteria, analysis setup, outcome definitions and PSM.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStudy Endpoints/variables\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eMain Composite Outcome\u003c/h2\u003e \u003cp\u003eThe main composite outcome was all-cause mortality, HF, acute MI and peripheral artery disease (PAD) over two years from the index event of HT initiation. HF is any new diagnosis of HF and PAD any type of PAD as defined by the ICD codes provided in the supplementary appendix.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSecondary Outcomes\u003c/h2\u003e \u003cp\u003eSecondary outcomes included individual outcomes of all-cause mortality, new onset HF, acute MI, PAD, HF exacerbation, LVEF\u0026thinsp;\u0026lt;\u0026thinsp;50%, atrial fibrillation/flutter, cardiac arrest, ischemic stroke, need for renal replacement therapy and all-cause ER visits/hospitalizations. The outcomes were defined based on ICD or CPT codes and EHR extracted data. HF exacerbation was defined by the diagnostic codes plus need for IV diuretics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003ePatients with history of T2DM and prostate cancer who received HT were divided into 2 cohorts based on the use of SGLT2i: SGLT2i cohort and non-SGLT2i cohort. These two cohorts were compared using independent sample t-tests for continuous variables, reported as mean (range). Categorical variables are reported as counts (%) and compared using the Chi-square (χ2) test. To control for baseline differences in the patient cohorts, we performed 1:1 Propensity Score matching (PSM) for characteristics of clinical relevance utilizing a built-in algorithm that uses the greedy nearest-neighbor algorithm with a caliper of 0.1 pooled standard mean difference (SMD). Any characteristic with a SMD between the cohorts lower than 0.1 was considered well-matched. After propensity matching, time to event analysis reported as hazard ratios with 95% confidence intervals was performed for the primary outcome and odds ratios with 95% confidence intervals for the secondary outcomes using the χ2 for the measures of association. Absolute risk difference (ARD) was calculated as the subtraction of the absolute risk of the event in the treatment (SGLT2i) cohort and the absolute risk of the event in the control (non-SGLT2i) cohort. Furthermore, a sensitivity analysis was performed to evaluate the potential of significant confounding. For the sensitivity analysis we calculated E-values for the odds ratio as previously described \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. A large E-value means that significant unmeasured confounding would be needed to explain away an effect estimate while a small E-value means that little unmeasured confounding would be needed to explain away an effect estimate. Statistical analyses were completed using the TriNetX online platform using R for statistical computing.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eRole of Funding Source:\u003c/h2\u003e \u003cp\u003eNo Funding Source is involved.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy Population\u003c/h2\u003e\n \u003cp\u003eA total of 26,848 patients were identified with a history of T2DM and prostate cancer who received HT. Of the total patients, 2,741 patients received SGLT2i while 24,107 patients did not receive SGLT2i. After propensity score matching, 2,155 patients remained in each cohort (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003ePatient Demographics\u003c/h2\u003e\n \u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e outlines the baseline characteristics of each cohort before and after propensity matching. The mean age (\u0026plusmn;\u0026thinsp;SD) of patients in the SGLT2i cohort was 66.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.8 and 57.8% of patients were White adults. Before propensity matching, patients treated with SGLT2i had a higher prevalence of comorbidities, including hypertension, hyperlipidemia, ischemic heart disease, cardiomyopathy, HF, atrial fibrillation/flutter, chronic lower respiratory diseases, and chronic kidney disease. The proportion of metformin, glucagon-like peptide-1 (GLP-1) agonists, as well as insulin use was higher in the SGLT2i cohort. All baseline characteristics between the two cohorts, including healthcare utilization, were propensity matched, with no residual difference (standard mean difference for all included covariates was \u0026lt;\u0026thinsp;0\u0026middot;1; Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eMain Composite Outcome:\u003c/h2\u003e\n \u003cp\u003eAmong patients with a history of T2DM and prostate cancer who received HT, patients who received SGLT2i had a lower risk of developing the composite outcome of all-cause mortality, HF, acute MI and peripheral artery disease over two years since initiation of HT, compared to propensity-matched controls who did not receive SGLT2i (HR 0.689, 95% CI 0.582\u0026ndash;0.816; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The composite outcome occurred in 218 patients (16.1%) in the SGLT2i cohort as compared to 355 patients (26.3%) in the non-SGLT2i cohort (OR 0\u0026middot;54 CI 0\u0026middot;45\u0026thinsp;\u0026minus;\u0026thinsp;0\u0026middot;65; p\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;001).\u003c/p\u003e\n \u003cp\u003eThe E value of the Odds ratio for the primary outcome was 2.47 and the E value for the lower confidence interval was 2.88, both of which support stronger association of SGLT2i with the observed differences in outcomes (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eSecondary Outcomes:\u003c/h2\u003e\n \u003cp\u003ePatients who were on SGLT2i had lower odds of having new onset HF (OR\u0026thinsp;=\u0026thinsp;0.66, CI 0.51\u0026ndash;0.87, p\u0026thinsp;=\u0026thinsp;0\u0026middot;003); HF exacerbation (OR\u0026thinsp;=\u0026thinsp;0.82, CI 0.68-0\u0026middot;99, p\u0026thinsp;=\u0026thinsp;0.037); PAD (OR\u0026thinsp;=\u0026thinsp;0.64, CI 0.50\u0026ndash;0.82, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The SGLT2i cohort also had lowers odds of all-cause mortality (OR\u0026thinsp;=\u0026thinsp;0.41, CI 0.34-0\u0026middot;50, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) as well as lower odds of cardiac arrest (OR\u0026thinsp;=\u0026thinsp;0.51, CI 0.29\u0026ndash;0.90, p\u0026thinsp;=\u0026thinsp;0.019). There were also lower odds of Atrial Fibrillation/Flutter in the SGLT2i cohort (OR\u0026thinsp;=\u0026thinsp;0.72, CI 0.54\u0026ndash;0.96, p\u0026thinsp;=\u0026thinsp;0.027). The need for renal replacement therapy (RRT) was significantly lower in the SGLT2i cohort compared to the non-SGLT2i cohort (OR\u0026thinsp;=\u0026thinsp;0.24, CI 0.12\u0026ndash;0.46, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The patients who received SGLT2i had lower odds of healthcare utilization in the form of ER visits/hospitalizations (OR\u0026thinsp;=\u0026thinsp;0.54, CI 0.49\u0026ndash;0.62, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e; Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eSensitivity analysis with E-values suggests stronger association of SGLT2i on observed outcomes and a low likelihood that differences in the outcomes are due to unmeasured confounders (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this is the first, large, real-world study evaluating the incidence of adverse cardiovascular and renal outcomes among patients with prostate cancer on HT treated with SGLTi compared to other agents for T2DM. We found that among patients with prostate cancer, SGLT2i treatment was associated with a significantly lower risk of developing the composite outcome of all-cause mortality, new onset HF, acute MI and PAD over two years since initiation of HT. In the analysis of individual outcomes, SGLT2i were associated with lower odds of new onset HF, HF exacerbation, PAD, atrial fibrillation/flutter, cardiac arrest, need for RRT, overall ER visits/hospitalizations and all-cause mortality.\u003c/p\u003e \u003cp\u003ePatients with prostate cancer represent a unique patient population with a high burden of comorbid cardiovascular conditions, including T2DM, as well as cardiovascular disease, which is a leading cause of death \u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The high prevalence of cardiovascular disease among patients with prostate cancer has been attributed not only to the coexistence of shared risk factors but also the effects of HT. HT is the backbone of prostate cancer therapy and it is used for as many as 50% of patients with prostate cancer at some point in their disease course. In 2006, Keating et al. were one of the first to report an association between GnRH agonists and increased incidence of DM, coronary heart disease, MI, and sudden cardiac death \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Since then, several studies and clinical trials have confirmed that GnRH agonists, abiraterone, androgen receptor antagonists, and less so GnRH antagonists, are associated with increased incidence of adverse cardiovascular events. The mechanism of HT related cardiotoxicity includes hypogonadism-mediated alterations in body composition, with increase in adiposity and decrease in lean mass, lipid abnormalities (increase in triglycerides and LDL cholesterol) and impaired glucose control with decreased insulin sensitivity and subsequently elevated fasting serum glucose \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. These metabolic derangements lead to an increase in circulating proinflammatory adipokines and prothrombotic markers with subsequent vascular endothelial dysfunction, vascular inflammation, and adverse cardiovascular and renal events \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOver the last decade, several large clinical trials have shown that treatment with SGLT2 inhibitors is associated with favorable cardiovascular and renal outcomes in patients with T2DM at risk of or with established cardiovascular disease but also in patients with HF and chronic kidney disease (CKD) without T2DM \u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Empagliflozin was the first SGLT2i that received FDA approval in December of 2016 for reduction of cardiovascular death in adults with T2DM \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Subsequently, in May of 2020 FDA approved dapagliflozin for reducing the risk of cardiovascular death and HF hospitalizations in patients with HF with reduced ejection fraction regardless of diabetes status, \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and in April of 2021 dapagliflozin was approved to reduce the risk of kidney function decline in adults with CKD \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. More recently, in February of 2022, FDA approved empagliflozin to reduce the risk of cardiovascular death and hospitalizations in adults with HF regardless of ejection fraction \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. In addition to the above benefits, recent evidence suggests that SGLT2i may also reduce the incidence of atrial fibrillation/flutter \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Our study findings further emphasize the importance of using SGLT2i in patients with T2DM to prevent adverse cardiorenal outcomes.\u003c/p\u003e \u003cp\u003eConsidering that cardiovascular disease is a major cause of death among a large portion of men with prostate cancer, treatment with SGLT2i might have a great impact in improving mortality and morbidity. Furthermore, SGLT2i might be able to mitigate the risk of cardiotoxicity mediated by HT. Despite the significant potential benefits, patients with prostate cancer were excluded from the above-mentioned clinical trials and the exact role and size of impact of SGLT2i in preventing adverse cardiovascular and renal outcomes among patients with T2DM and prostate cancer treated with HT has not been examined. Our study is the first one to report a significant reduction in the risk of adverse cardiorenal outcomes among patients with prostate cancer on HT and T2DM treated with vs without SGLT2i. We hypothesize that by inducing glucosuria and natriuresis, SGLT2i improve hyperglycemia and hypertension, the two major risk factors contributing to the development of cardiovascular disease among patients with prostate cancer treated with HT \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Furthermore, similar to patients with HF, it is likely that SGLT2i alter adipokine signaling and reduce inflammation, which could prevent HT-related cardiotoxicity \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Based upon clinical observations and convergent data, our group has also postulated that a subset of prostate cancers is part of an \u0026ldquo;overlap syndrome\u0026rdquo; of age-related illnesses, including cardiovascular disease, with shared biology \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The findings of this study suggest that SGLT2i warrant further investigation in this subset of patients since it has the potential to improve survival.\u003c/p\u003e \u003cp\u003eIn addition to the favorable cardiorenal benefits of SGLT2i among patients with prostate cancer, preclinical studies have suggested functional expression of SGLT receptors in prostate adenocarcinomas and that treatment with SGLT2i might lead to favorable oncologic outcomes as well \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Studies evaluating the role of SGLT2i in prostate cancer-specific outcomes in human subjects are currently underway (NCT04887935). Such trials may also be able to assess the cardiovascular benefits of SGLT2i in patients with prostate cancer irrespective of the presence of T2DM.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStudy Limitations:\u003c/h2\u003e \u003cp\u003eOur study has several limitations including those inherent to observational studies such as selection bias. Most importantly, despite our efforts to carefully control for baseline differences in the SGLT2i versus non-SGLT2i cohort using propensity matching, unmeasured confounding may still exist. To eliminate this possibility, we performed a sensitivity analysis of patients with prostate cancer treated with vs without SGLT2i, the results of which indicated that the findings are unlikely to be explained by unmeasured confounders. Patients on SGLT2i may have also have socioeconomic differences related to access to medications, which cannot be assessed in this study. Differences in the type of HT that the two patient groups received, and the stage of their prostate cancer could not be assessed either, due to limitations of the database used. Furthermore, retrospective data curated from electronic medical records may be inaccurate or carry the risk of biases. This risk is somewhat mitigated by the large number of patients included in our study and the large effect size. Finally, this study did not assess side effects related to SGLT2i or prostate cancer specific outcomes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrated that the use of SGLT2i for the treatment of T2DM was associated with significantly lower risk for developing the composite outcome of all-cause mortality, new onset HF, acute MI and PAD among patients with prostate cancer treated with HT. Clinical trials assessing the impact of SGLT2i in patients without T2DM or HF in reducing CV events associated with HT or prostate cancer outcomes are needed.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthor Declarations:\u003c/p\u003e\n\n\u003cp\u003eFunding:\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\n\u003cp\u003eConflicts of Interest/Competing Interests:\u003c/p\u003e\n\u003cp\u003eEK is supported in part by NIH/NCI 1RO1HL157273 and by CPRIT RP200381. AD is supported in part by the Ting Tsung and Wei Fong Chao Distinguished Chair and is a consultant for Bayer. JB is consultant for Abbott, American Regent, Amgen, Applied Therapeutic, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardiac Dimension, Cardior, CVRx, Cytokinetics, Edwards, Element Science, Innolife, Impulse Dynamics, Imbria, Inventiva, Lexicon, Lilly, LivaNova, Janssen, Medtronics, Merck, Occlutech, Novartis, Novo Nordisk, Pfizer, Pharmacosmos, Pharmain, Roche, Sequana, SQ Innovation, and Vifor. AWH is consultant for Janssen, Intellisphere, Exelixis, has received honoraria from Medscape, Binaytara Foundation, travel support from Dava Oncology and institutional funding from Bayer and Eisai. The remaining authors have nothing to disclose.\u003c/p\u003e\n\n\u003cp\u003eAvailability of data and material:\u003c/p\u003e\n\u003cp\u003eThe data are available upon request by email to the corresponding authors.\u003c/p\u003e\n\n\u003cp\u003eCode availability:\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\n\u003cp\u003eAuthors\u0026rsquo; Contributions:\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Efstratios Koutroumpakis, Rushin Patel, Sumanth Khadke and Sarju Ganatra. The first draft of the manuscript was written by Efstratios Koutroumpakis and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\n\u003cp\u003eEthics approval:\u003c/p\u003e\n\u003cp\u003eThis is an observational study. The need for Institutional Review Board (IRB) approval was waived by Lahey Clinic IRB due to the use of deidentified data for the analysis. The study findings are reported per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cohort studies.\u003c/p\u003e\n\n\u003cp\u003eConsent to participate:\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\n\u003cp\u003eConsent for publication:\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003cbr\u003e \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSiegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. \u003cem\u003eCA Cancer J Clin. \u003c/em\u003e2023;73(1):17-48.\u003c/li\u003e\n\u003cli\u003eShikanov S, Kocherginsky M, Shalhav AL, Eggener SE. 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Impact of Hormonal Therapies for Treatment of Hormone-Dependent Cancers (Breast and Prostate) on the Cardiovascular System: Effects and Modifications: A Scientific Statement From the American Heart Association. \u003cem\u003eCirc Genom Precis Med. \u003c/em\u003e2021;14(3):e000082.\u003c/li\u003e\n\u003cli\u003eKeating NL, O\u0026apos;Malley AJ, Smith MR. Diabetes and cardiovascular disease during androgen deprivation therapy for prostate cancer. \u003cem\u003eJ Clin Oncol. \u003c/em\u003e2006;24(27):4448-4456.\u003c/li\u003e\n\u003cli\u003eSun L, Parikh RB, Hubbard RA, et al. Assessment and Management of Cardiovascular Risk Factors Among US Veterans With Prostate Cancer. \u003cem\u003eJAMA Netw Open. \u003c/em\u003e2021;4(2):e210070.\u003c/li\u003e\n\u003cli\u003eElSayed NA, Aleppo G, Aroda VR, et al. 9. Pharmacologic Approaches to Glycemic Treatment: Standards of Care in Diabetes\u0026mdash;2023. \u003cem\u003eDiabetes Care. \u003c/em\u003e2022;46(Supplement_1):S140-S157.\u003c/li\u003e\n\u003cli\u003eNeal B, Perkovic V, Mahaffey KW, et al. Canagliflozin and Cardiovascular and Renal Events in Type 2 Diabetes. \u003cem\u003eNew England Journal of Medicine. \u003c/em\u003e2017;377(7):644-657.\u003c/li\u003e\n\u003cli\u003ePerkovic V, Jardine MJ, Neal B, et al. Canagliflozin and Renal Outcomes in Type 2 Diabetes and Nephropathy. \u003cem\u003eNew England Journal of Medicine. \u003c/em\u003e2019;380(24):2295-2306.\u003c/li\u003e\n\u003cli\u003eWiviott SD, Raz I, Bonaca MP, et al. Dapagliflozin and Cardiovascular Outcomes in Type 2 Diabetes. \u003cem\u003eNew England Journal of Medicine. \u003c/em\u003e2018;380(4):347-357.\u003c/li\u003e\n\u003cli\u003eZinman B, Wanner C, Lachin JM, et al. Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes. \u003cem\u003eN Engl J Med. \u003c/em\u003e2015;373(22):2117-2128.\u003c/li\u003e\n\u003cli\u003ehttps://trinetx.com/. \u003cem\u003eAccessed on 10/1/2023.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eFDA approves invokana to treat type 2 diabetes. http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm345848.htm. Date: March 29, 2013. .\u003c/li\u003e\n\u003cli\u003eDiamant M, Morsink LM. SGLT2 inhibitors for diabetes: turning symptoms into therapy. \u003cem\u003eLancet. \u003c/em\u003e2013;382(9896):917-918.\u003c/li\u003e\n\u003cli\u003eVanderWeele TJ, Ding P. Sensitivity Analysis in Observational Research: Introducing the E-Value. \u003cem\u003eAnn Intern Med. \u003c/em\u003e2017;167(4):268-274.\u003c/li\u003e\n\u003cli\u003ehttps://www.fda.gov/news-events/press-announcements/fda-approves-jardiance-reduce-cardiovascular-death-adults-type-2-diabetes. Accessed on: 10/23/2023.\u003c/li\u003e\n\u003cli\u003ehttps://www.fda.gov/news-events/press-announcements/fda-approves-new-treatment-type-heart-failure. Accessed on 10/23/2023.\u003c/li\u003e\n\u003cli\u003ehttps://www.fda.gov/news-events/press-announcements/fda-approves-treatment-chronic-kidney-disease. Accessed on 10/23/2023.\u003c/li\u003e\n\u003cli\u003ehttps://www.fda.gov/news-events/press-announcements/fda-approves-treatment-wider-range-patients-heart-failure. Accessed on 10/23/2023.\u003c/li\u003e\n\u003cli\u003ePandey AK, Okaj I, Kaur H, et al. Sodium‐Glucose Co‐Transporter Inhibitors and Atrial Fibrillation: A Systematic Review and Meta‐Analysis of Randomized Controlled Trials. \u003cem\u003eJournal of the American Heart Association. \u003c/em\u003e2021;10(17):e022222.\u003c/li\u003e\n\u003cli\u003eLopaschuk GD, Verma S. Mechanisms of Cardiovascular Benefits of Sodium Glucose Co-Transporter 2 (SGLT2) Inhibitors: A State-of-the-Art Review. \u003cem\u003eJACC Basic Transl Sci. \u003c/em\u003e2020;5(6):632-644.\u003c/li\u003e\n\u003cli\u003eKoutroumpakis E, Jozwik B, Aguilar D, Taegtmeyer H. Strategies of Unloading the Failing Heart from Metabolic Stress. \u003cem\u003eAm J Med. \u003c/em\u003e2020;133(3):290-296.\u003c/li\u003e\n\u003cli\u003eLogothetis CJ, Hahn AW. Challenging the Prevailing Therapeutic Dogma for Prostate Cancer: The Case for an Overlap Syndrome. \u003cem\u003eEur Urol. \u003c/em\u003e2023.\u003c/li\u003e\n\u003cli\u003eScafoglio C, Hirayama BA, Kepe V, et al. Functional expression of sodium-glucose transporters in cancer. \u003cem\u003eProc Natl Acad Sci U S A. \u003c/em\u003e2015;112(30):E4111-4119.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Baseline demographics and clinical characteristics of patients with prostate cancer on androgen deprivation therapy separated by treatment with or without SGLT2 inhibitors for type II diabetes mellitus, before and after propensity score matching.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.44859813084112%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eBefore Propensity matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.598130841121495%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter Propensity Matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSGLT2 inhibitor\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=2,741)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo SGLT2 inhibitor\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=24,107)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSGLT2 inhibitor\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=2,155)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo SGLT2 inhibitor\u0026nbsp;(n=2,155)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e66.6 +/- 12.7\u003c/p\u003e\n \u003cp\u003e(Mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e67.8 +/- 14.7\u003c/p\u003e\n \u003cp\u003e(Mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e66.8 +/- 12.8\u003c/p\u003e\n \u003cp\u003e(Mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e66.8 +/- 15.0\u003c/p\u003e\n \u003cp\u003e(Mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,564 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e14,552 (60.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,245 (57.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,259 (58.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eNon-Hispanic or Latino\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,892 (69.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e16,619 (68.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,475 (68.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,461 (67.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e2,211 (80.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e14,735 (61.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,680 (78.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,658 (76.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eHyperlipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e2,055 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e11,856 (49.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,527 (70.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,509 (70.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eIschemic heart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,066 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e6,008 (24.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e788 (36.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e774 (35.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eCardiomyopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e304 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e1,002 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e206 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e199 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eHeart Failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e602 (22.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e2,690 (11.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e423 (19.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e414 (19.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eIschemic stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e402 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e2,784 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e311 (14.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e324 (15.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eAtrial fibrillation and flutter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e456 (16.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e2,709 (11.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e325 (15.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e326 (15.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eChronic lower respiratory diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e745 (27.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e4,370 (18.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e538 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e535 (24.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eChronic kidney disease (CKD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e706 (25.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e4,094 (17.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e509 (23.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e477 (22.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eMetastatic cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e743 (27.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e5,493 (22.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e606 (28.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e623 (28.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eProcedures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eSurgical Procedures on the Male Genital System\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e959 (35.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e5,984 (24.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e685(31.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e631(29.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eRadiation Oncology Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e744 (27.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e1,945 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e469(21.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e443(20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eStatins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e2,182 (79.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e11,330 (47.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,629 (75.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,640 (76.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eAntiarrhythmics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,764 (64.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e10,092 (41.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,296 (60.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,287 (59.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eACE inhibitors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,435 (52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e7,767 (32.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,077 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,062 (49.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eAngiotensin II Inhibitors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,069 (39.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e4,189 (17.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e754 (35.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e747 (34.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eLoop diuretics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,572 (57.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e8,782 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,175 (54.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,161 (53.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eBeta Blockers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,671 (61.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e9,443 (39.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,247 (57.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,256 (58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eCalcium Channel Blockers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,236 (45.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e6,737 (27.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e908 (42.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e888 (41.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eInsulin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,513 (55.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e6,742 (28.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,095 (50.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,127 (52.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eMetformin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,971 (71.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e7,100 (29.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,439 (66.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,483 (68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eSitagliptin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e628 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e1,306 (5.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e391 (18.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e417 (19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eExenatide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e114 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e168 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e68 (3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e64 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eDulaglutide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e314 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e185 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e126 (5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e109 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eLiraglutide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e223 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e258 (1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e117 (5.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e112 (5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eSemaglutide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e119 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e50 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e40 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e28 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eLixisenatide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e18 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e11 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e10 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e10 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eGlipizide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e657 (24.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e2,103 (8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e448 (20.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e467 (21.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eAspirin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,512 (55.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e8,525 (35.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,134 (52.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,139 (52.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eApixaban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e294 (10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e750 (3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e178 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e170 (7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eWarfarin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e221 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e2,010 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e185 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e202 (9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eRivaroxaban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e162 (5.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e606 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e104 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e124(5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eClopidogrel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e441 (16.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e2,191 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e327 (15.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e348(16.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eTicagrelor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e87 (3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e166 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e45 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e42(1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eLabs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eCreatinine (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1.1 +/- 2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e1.3 +/- 2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1.1 +/- 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1.2 +/- 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e12.8 +/- 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e12.5 +/- 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e12.8 +/- 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e12.3 +/- 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eCholesterol \u0026nbsp; \u0026nbsp; \u0026nbsp; LDL \u0026ge;130 mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e590 (21.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e3,317 (13.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e441(20.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e427 (19.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eBNP \u0026ge;150 pg/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e257 (9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e1,096 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e174 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e170 (7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eNT-pro BNP \u0026ge;450 pg/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e154 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e728 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e115 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e109 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eHemoglobin A1c \u0026ge;7.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e1,615 (58.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e5,329 (22.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e1,125 (52.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e1,111 (51.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eBMI \u0026ge; 30kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e972 (35.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e6,268 (26.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e734 (34.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e696 (32.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.953271028037383%\"\u003e\n \u003cp\u003eLeft Ventricular Ejection Fraction (LVEF) \u0026lt;40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.149532710280374%\"\u003e\n \u003cp\u003e54 (2.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.018691588785046%\"\u003e\n \u003cp\u003e130 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.280373831775702%\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\"\u003e\n \u003cp\u003e34 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.429906542056074%\"\u003e\n \u003cp\u003e33 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: SMD: Standardized Mean difference; SGLT2 \u0026ndash; Sodium-glucose cotransporter 2;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Comparison of primary and secondary outcomes of patients with prostate cancer on androgen deprivation therapy who were treated with or without SGLT2 inhibitors for type II diabetes mellitus.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"707\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.035360678925034%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eOutcomes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.164073550212164%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSGLT2 inhibitor (n=2,155)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo SGLT2 inhibitor (n=2,155)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eARD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdd Ratio\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eE-value for OR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.183875530410184%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eE-value for lower bound CI of OR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.035360678925034%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComposite of Outcomes\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(All-cause mortality/ HF/AMI/PAD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.164073550212164%\" valign=\"top\"\u003e\n \u003cp\u003e218(16.1%)\u003c/p\u003e\n \u003cp\u003e(n=1,351)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e355(26.3%)\u003c/p\u003e\n \u003cp\u003e(n=1,349)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e-0.102\u003c/p\u003e\n \u003cp\u003e(-0.132, -0.071)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e0.539\u003c/p\u003e\n \u003cp\u003e(0.446, 0.651) (HR 0.689, 95% CI 0.582-0.816; p\u0026lt;0.001)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.183875530410184%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.035360678925034%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAll-Cause Mortality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.164073550212164%\" valign=\"top\"\u003e\n \u003cp\u003e168(7.8%)\u003c/p\u003e\n \u003cp\u003e(n=2,155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e365(16.9%)\u003c/p\u003e\n \u003cp\u003e(n=2,155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e-0.091\u003c/p\u003e\n \u003cp\u003e(-0.111, -0.072)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e0.415\u003c/p\u003e\n \u003cp\u003e(0.342, 0.503)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.183875530410184%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.035360678925034%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHeart Failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.164073550212164%\" valign=\"top\"\u003e\n \u003cp\u003e95(5.6%)\u003c/p\u003e\n \u003cp\u003e(n=1,710)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e141(8.1%)\u003c/p\u003e\n \u003cp\u003e(n=1,734)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e-0.026\u003c/p\u003e\n \u003cp\u003e(-0.043, -0.009)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e0.665\u003c/p\u003e\n \u003cp\u003e(0.508, 0.870)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.183875530410184%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.035360678925034%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAcute Myocardial Infarction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.164073550212164%\" valign=\"top\"\u003e\n \u003cp\u003e45(2.3%)\u003c/p\u003e\n \u003cp\u003e(n=1,951)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e65(3.3%)\u003c/p\u003e\n \u003cp\u003e(n=1,952)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e-0.010\u003c/p\u003e\n \u003cp\u003e(-0.021, 0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e0.685\u003c/p\u003e\n \u003cp\u003e(0.466, 1.008)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.183875530410184%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.035360678925034%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePeripheral Artery Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.164073550212164%\" valign=\"top\"\u003e\n \u003cp\u003e115(7.0%)\u003c/p\u003e\n \u003cp\u003e(n=1,636)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e171(10.5%)\u003c/p\u003e\n \u003cp\u003e(n=1,633)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e-0.034\u003c/p\u003e\n \u003cp\u003e(-0.054, -0.015)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e0.646\u003c/p\u003e\n \u003cp\u003e(0.505, 0.828)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n 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valign=\"top\"\u003e\n \u003cp\u003e24(1.1%)\u003c/p\u003e\n \u003cp\u003e(n=2,096)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003cp\u003e(-0.011, -0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e0.503\u003c/p\u003e\n \u003cp\u003e(0.252, 1.003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.183875530410184%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.035360678925034%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAtrial Fibrillation/Flutter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.164073550212164%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e83(4.6%)\u003c/p\u003e\n \u003cp\u003e(n=1,819)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e113(6.2%)\u003c/p\u003e\n \u003cp\u003e(n=1,816)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.017\u003c/p\u003e\n \u003cp\u003e(-0.031, -0.002)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003cp\u003e(0.539, 0.964)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.183875530410184%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.035360678925034%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCardiac Arrest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.164073550212164%\" valign=\"top\"\u003e\n \u003cp\u003e18(0.83)\u003c/p\u003e\n \u003cp\u003e(n=2,155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e35(1.6%)\u003c/p\u003e\n \u003cp\u003e(n=2,155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003cp\u003e(-0.014, -0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e0.510\u003c/p\u003e\n \u003cp\u003e(0.288, 0.904)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.183875530410184%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.035360678925034%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIschemic Stroke\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.164073550212164%\" valign=\"top\"\u003e\n \u003cp\u003e40(1.98)\u003c/p\u003e\n \u003cp\u003e(n=2,014)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e47(2.3)\u003c/p\u003e\n \u003cp\u003e(n=2,004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003cp\u003e(-0.013, 0.005)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e0.844\u003c/p\u003e\n \u003cp\u003e(0.551, 1.292)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.183875530410184%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.035360678925034%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRenal Replacement Therapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.164073550212164%\" valign=\"top\"\u003e\n \u003cp\u003e11(0.5%)\u003c/p\u003e\n \u003cp\u003e(n=2,155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e45(2.1%)\u003c/p\u003e\n \u003cp\u003e(n=2,155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e-0.016\u003c/p\u003e\n \u003cp\u003e(-0.023, -0.009)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e0.241\u003c/p\u003e\n \u003cp\u003e(0.124, 0.466)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.183875530410184%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.035360678925034%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eER Visit/Hospitalization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.164073550212164%\" valign=\"top\"\u003e\n \u003cp\u003e894(41.5%)\u003c/p\u003e\n \u003cp\u003e(n=2,155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1,216(56.4%)\u003c/p\u003e\n \u003cp\u003e(n=2,155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.456859971711458%\" valign=\"top\"\u003e\n \u003cp\u003e-0.149 (-0.179, -0.120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.305516265912306%\" valign=\"top\"\u003e\n \u003cp\u003e0.547\u003c/p\u003e\n \u003cp\u003e(0.485, 0.618)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.335219236209335%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.637906647807638%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.183875530410184%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003eAbbreviations:\u0026nbsp;\u003c/strong\u003eSGLT2 \u0026ndash; Sodium-glucose transport protein 2; ARD \u0026ndash; Absolute risk difference; HF \u0026ndash; heart failure; AMI \u0026ndash; acute myocardial infarction; PAD \u0026ndash; peripheral artery disease; ER \u0026ndash; emergency room\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-drugs-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cdty","sideBox":"Learn more about [Cardiovascular Drugs and Therapy](https://www.springer.com/journal/10557)","snPcode":"10557","submissionUrl":"https://submission.nature.com/new-submission/10557/3","title":"Cardiovascular Drugs and Therapy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"prostate cancer, hormone therapy, type II diabetes mellitus, SGLT2 inhibitors, cardiovascular outcomes","lastPublishedDoi":"10.21203/rs.3.rs-4510870/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4510870/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eStudies have reported associations between prostate cancer, type II diabetes mellitus (T2DM) and cardiovascular disease in the context of treatment with hormone therapy (HT). This study aimed to assess the role of Sodium-Glucose Cotransporter-2 Inhibitors (SGLT2i) in preventing adverse cardiovascular and renal outcomes in diabetics with prostate cancer.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePatients\u0026thinsp;\u0026ge;\u0026thinsp;18 years of age with T2DM and prostate cancer who received HT between August 1, 2013, and August 31, 2021, were identified using the TriNetX research network. Patients were divided into two cohorts based on treatment with SGLT2i or alternative antidiabetic therapies. The primary outcome was the composite of all-cause mortality, new onset heart failure (HF), acute myocardial infarction (MI), and peripheral artery disease over two years from HT initiation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAfter propensity score matching, 2,155 patients remained in each cohort. The primary composite outcome occurred in 218 patients (16.1%) in the SGLT2i cohort versus 355 patients (26.3%) in the non-SGLT2i cohort (HR 0.689, 95% CI 0.582\u0026ndash;0.816; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Furthermore, SGLT2i were associated with significantly lower odds of HF, HF exacerbation, peripheral artery disease, atrial fibrillation/flutter, cardiac arrest, need for renal replacement therapy, overall emergency room visits/hospitalizations and all-cause mortality.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eUse of SGLT2i for the treatment of T2DM among patients with prostate cancer on HT is associated with favorable cardiovascular, renal and all-cause mortality outcomes. This observation supports the hypothesis that a therapeutically relevant link exists between HT and cardiovascular disease in the context of prostate cancer.\u003c/p\u003e","manuscriptTitle":"Associations of SGLT-2i with Cardiorenal Outcomes Among Diabetics with Prostate Cancer on Hormone Therapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-26 17:12:23","doi":"10.21203/rs.3.rs-4510870/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-07-03T00:54:03+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-02T18:28:52+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Cardiovascular Drugs and Therapy","date":"2024-06-26T14:15:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-24T04:48:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cardiovascular Drugs and Therapy","date":"2024-06-23T06:47:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-drugs-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cdty","sideBox":"Learn more about [Cardiovascular Drugs and Therapy](https://www.springer.com/journal/10557)","snPcode":"10557","submissionUrl":"https://submission.nature.com/new-submission/10557/3","title":"Cardiovascular Drugs and Therapy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a8cf063d-6817-49d8-aef2-23b89ca69793","owner":[],"postedDate":"July 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-18T19:16:56+00:00","versionOfRecord":{"articleIdentity":"rs-4510870","link":"https://doi.org/10.1007/s10557-024-07646-1","journal":{"identity":"cardiovascular-drugs-and-therapy","isVorOnly":false,"title":"Cardiovascular Drugs and Therapy"},"publishedOn":"2024-11-11 15:57:59","publishedOnDateReadable":"November 11th, 2024"},"versionCreatedAt":"2024-07-26 17:12:23","video":"","vorDoi":"10.1007/s10557-024-07646-1","vorDoiUrl":"https://doi.org/10.1007/s10557-024-07646-1","workflowStages":[]},"version":"v1","identity":"rs-4510870","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4510870","identity":"rs-4510870","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}