Long-Term Clinical Outcomes of Sotatercept in Pulmonary Hypertension: A Retrospective Cohort Analysis

Long-Term Clinical Outcomes of Sotatercept in Pulmonary Hypertension: A Retrospective Cohort Analysis | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Long-Term Clinical Outcomes of Sotatercept in Pulmonary Hypertension: A Retrospective Cohort Analysis View ORCID Profile Azka Naeem , Olayiwola Bolaji , George G. Kidess , Joud Fahed , Sultana Jahan , Muhammad Hashim Khan , Shaunak Mangeshkar , Steven Sorci , Hayah Kassis-George , Sourbha Dani , Chadi Alraies doi: https://doi.org/10.1101/2025.08.05.25333015 Azka Naeem 1 Division of Cardiovascular Imaging, St. Francis Hospital and Heart Center , Roslyn, NY MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Azka Naeem Olayiwola Bolaji 2 Internal Medicine Department, Cardiology Division, Memorial Sloan Kettering Cancer Center , New York, NY 11006 MD, MSc Find this author on Google Scholar Find this author on PubMed Search for this author on this site George G. Kidess 3 Wayne State University School of Medicine , Detroit, MI Find this author on Google Scholar Find this author on PubMed Search for this author on this site Joud Fahed 4 Department of Internal Medicine, Ascension Saint Agnes Medical Center , Baltimore, Maryland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sultana Jahan 5 Department of Internal Medicine, Valley Health System , Las Vegas, Nevada MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Muhammad Hashim Khan 6 Department of Internal Medicine, Maimonides Medical Centre , Brooklyn, NY MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Shaunak Mangeshkar 7 Department of Internal Medicine, Cleveland Clinic Foundation MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Steven Sorci 8 Division of Advance heart failure, Maimonides Medical Centre , NY DO Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hayah Kassis-George 9 Division of Advance heart failure and heart transplant, Allegheny General Hospital , Pittsburgh, PA MD, FACC Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sourbha Dani 10 Division of Cardiology, Lahey Hospital and Medical Centre , MA MD,MSc, FACC, FACP, CCDS Find this author on Google Scholar Find this author on PubMed Search for this author on this site Chadi Alraies 11 Medical Director Cardiac Cath Lab, Detroit Heart Hospital , Detroit, MI MD MPH FACP FACC FSCAI Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: alraies{at}hotmail.com Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Background Sotatercept, an activin receptor ligand trap, has demonstrated significant short-term hemodynamic improvements in pulmonary hypertension (PH) based on clinical trials. However, evidence regarding long-term outcomes in real-world settings remains limited. Methods Using data from the TriNetX global federated health research network covering 102 healthcare organizations, we conducted a retrospective cohort study comparing 185 patients with PH receiving sotatercept to 212,349 PH patients not receiving sotatercept. After 1:1 propensity score matching to balance baseline characteristics, we assessed outcomes at 6 months, 1 year, 3 years, and 5 years post-initiation and cox proportional hazards was used. Primary outcomes included all-cause mortality, rehospitalization rates, major adverse cardiovascular events (MACE), and BNP elevation (≥100 pg/mL). Results Over 5 years of follow-up, sotatercept treatment was associated with significantly lower all-cause mortality (5.4% vs. 27.3%; risk difference, -21.9 percentage points [95% CI, -29.1 to -14.7]; p<0.001; hazard ratio [HR], 0.40 [95% CI, 0.16-0.99]). Rehospitalization rates were also substantially reduced in the sotatercept group (15.4% vs. 38.1%; risk difference, -22.8 percentage points [95% CI, - 35.8 to -9.7]; p=0.002; HR, 0.12 [95% CI, 0.03-0.49]). MACE occurrence was significantly lower with sotatercept (6.4% vs. 15.5%; risk difference, -9.1 percentage points [95% CI, -16.2 to -2.0]; p=0.011; HR, 0.45 [95% CI, 0.14-1.41]), while BNP elevation showed no significant difference (12.8% vs. 10.6%; p=0.626). Treatment benefits were observed as early as 6 months post-initiation, progressively increasing magnitude through 5 years of follow-up. Sensitivity analyses using alternative matching methods and instrumental variable approaches confirmed the robustness of these findings. Conclusions In this large real-world cohort study with long-term follow-up, sotatercept was associated with substantial reductions in mortality, rehospitalization, and cardiovascular events in patients with pulmonary hypertension. These benefits increased over time, suggesting potential disease-modifying effects beyond acute hemodynamic improvements. These findings complement data from randomized controlled trials and support the role of sotatercept in improving long-term outcomes in pulmonary hypertension. Introduction Pulmonary hypertension (PH) affects approximately 1% of the global population and up to 10% of individuals over 65 years of age with higher rates in females and older adults[ 1 ]. PH is a major contributor to morbidity and mortality. It is considered a complex medical diagnosis due to several interrelated factors. The clinical presentation is often nonspecific leading to frequent delays and misdiagnosis. The diagnostic process requires a stepwise approach: initial suspicion is typically raised by echocardiography with definitive diagnosis requiring right heart catheterization, which is essential to distinguish between pre-capillary and post-capillary forms and to guide management [ 2 ]. PH is consistently associated with increased mortality, with an age-standardized mortality rate for PAH of 0.27 per 100,000 globally [ 3 ]. It is an independent risk factor for adverse outcomes, particularly in the context of left-sided heart disease, chronic lung disease, and perioperative settings. The American Heart Association emphasizes the need for careful classification and risk assessment, especially in perioperative settings, due to the high risk of morbidity and mortality. PH is also poor prognostic marker, and its presence significantly worsens outcomes, including right heart failure, which is the leading cause of death in these patients. The economic burden of PH is substantial, driven by frequent hospitalizations, advanced therapies, and the need for specialized care. Given the morbidity and mortality associated with pulmonary hypertension with economic implications,, novel target therapies have been developed. Medications for pulmonary arterial hypertension (PAH) target three main pathways: the endothelin pathway (endothelin receptor antagonists such as ambrisentan, bosentan, macitentan), the nitric oxide pathway (phosphodiesterase-5 inhibitors such as sildenafil and tadalafil, and soluble guanylate cyclase stimulators such as riociguat), and the prostacyclin pathway (prostacyclin analogues such as epoprostenol, treprostinil, iloprost). These agents, alone or in combination, improve exercise capacity, hemodynamics, and delay clinical worsening, but long-term survival remains suboptimal, with 5-year survival rates around 60% despite maximal therapy.[ 4 ] Sotatercept is a novel, first-in-class activin signaling inhibitor that targets pulmonary vascular remodeling, a mechanism distinct from vasodilation. Sotatercept, one of the novel drugs, demonstrated significant short-term hemodynamic improvements through modulation of the transforming growth factor beta (TGF-β) pathway . The need for sotatercept arose from persistent morbidity and mortality in PAH despite maximal use of established therapies, as highlighted by the lack of substantial survival improvement over the past decade. Phase 2 and 3 trials (PULSAR, STELLAR, and ZENITH) have demonstrated that sotatercept, when added to background therapy, significantly improves exercise capacity, pulmonary vascular resistance, NT-proBNP levels, and reduces the risk of clinical worsening and major events (including death, lung transplantation, and hospitalization) even in patients with advanced disease on maximal therapy [ 5 , 6 ]. Hence, in patients resistant to standard therapy, sotatercept was used as a third agent in WHO functional class II-III and a fourth in WHO class IV PAH [ 7 , 8 ]. However, evidence regarding long-term outcomes in real-world settings remain limited. Given the robust efficacy data and the unmet need in PH, increased use of sotatercept is expected in the future. This anticipated uptake, combined with the need to understand long-term safety, durability of benefit, and cost-effectiveness, highlights why there is a critical need to explore long-term outcomes in diverse patient populations. Hence, we conducted a retrospective cohort study using data from TriNetX’s global federated health network to assess primary outcomes, including all-cause mortality, rehospitalization rates, major adverse cardiovascular events (MACE), and BNP elevation at 6-month, 1-year, 3 years, and 5-year post-initiation. Methods Data Source and Study Population We conducted a retrospective cohort analysis using data from the TriNetX global federated health research network, which provides access to electronic medical records from 102 healthcare organizations (HCOs). The network covers approximately 88 million patients across the United States, Europe, and Asia, allowing for analysis of real-world treatment patterns and outcomes [ 9 , 10 ]. This study was executed by the Declaration of Helsinki, and data were de-identified in compliance with the Health Insurance Portability and Accountability Act (HIPAA). The TriNetX platform has been validated for observational research in multiple therapeutic areas and has demonstrated high concordance with findings from randomized controlled trials [ 11 , 12 ]. Study Design and Cohort Definition Patients with pulmonary hypertension were identified using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes I27.0 (primary pulmonary hypertension) and I27.21 (secondary pulmonary arterial hypertension). We included adult patients (≥18 years) with diagnostic codes for pulmonary hypertension between January 1, 2019, and December 31, 2024. The index date for each patient was defined as the first recorded diagnosis of pulmonary hypertension or the first prescription of sotatercept, whichever occurred later. Two cohorts were established: (1) patients with pulmonary hypertension who received sotatercept (RxNorm code 2678930) and (2) patients with pulmonary hypertension who did not receive sotatercept. Patients were required to have at least one healthcare encounter in the 12 months preceding the index date to ensure adequate baseline data for propensity score calculation. We excluded patients who had received other investigational pulmonary hypertension therapies or had less than 30 days of follow-up after the index date. Propensity Score Matching We used propensity score matching to create balanced comparison groups to address potential selection bias and control for confounding factors [ 13 ]. Propensity scores were calculated using multivariable logistic regression that incorporated the following covariates: age, sex, race, ethnicity, comorbidities (heart failure, chronic obstructive pulmonary disease, diabetes mellitus, essential hypertension, tobacco use), concomitant medications (sildenafil, bosentan), and baseline left ventricular ejection fraction. We performed 1:1 matching without replacement using a greedy nearest-neighbor algorithm with a caliper width of 0.2 standard deviations of the logit of the propensity score, as recommended by Austin et al. [ 14 ]. The matching quality was assessed by calculating standardized differences for each covariate before and after matching, with standardized differences <0.1 indicative of good balance between cohorts [ 15 ]. Density plots of propensity score distributions were generated to confirm the improved overlap after matching visually. Outcome Definitions and Follow-up The primary outcomes of interest were all-cause mortality, rehospitalization rates, major adverse cardiovascular events (MACE), and elevated B-type natriuretic peptide (BNP) levels. All-cause mortality was determined using death records within the TriNetX system. Rehospitalization was defined using Current Procedural Terminology (CPT) codes for subsequent hospital inpatient or observation care (CPT 99231, 99232, 99233, 99462, and 1013668). MACE was a composite endpoint comprising cardiac arrest (ICD-10-CM I46, I46.9), cerebral infarction (I63, I63.50), and myocardial infarction (I21, I21.3, I21.4, I21.9, I21.A, I21.A1). As recorded in laboratory data, BNP elevation was defined as values ≥100 pg/mL. The time window for outcome assessment began one day after the index event. It extended through the duration of available follow-up data, with analyses conducted at predefined time points of six months, one year, three years, and five years. Patients were censored at the time of their last recorded healthcare encounter in the database if they did not experience the outcome of interest during the follow-up period. Statistical Analysis For each outcome, we performed both risk analysis and survival analysis. Risk analysis calculated the proportion of patients experiencing each outcome within the specified time windows. We reported risk differences with 95% confidence intervals (CI) and corresponding p-values. We used the Kaplan-Meier method for survival analysis to estimate event-free survival probabilities and median time to event. Log-rank tests were performed to compare the survival distributions between the two cohorts. Hazard ratios (HR) with 95% CI were estimated using Cox proportional hazard models. The proportional hazards assumption was verified using Schoenfeld residuals and formal testing [ 16 ]. We also analyzed instances of rehospitalization, MACE, and BNP elevation outcomes to assess the frequency of events per patient. Patients with prior occurrences of the outcomes before the start of the time window were excluded from the respective analyses to ensure that only new-onset events were captured. We report the mean, standard deviation, and median number of events per patient for each analysis, along with appropriate statistical tests for between-group comparisons. All statistical analyses were conducted using the TriNetX Analytics features, which implement established methods for propensity score matching and time-to-event analyses [ 17 ]. A two-sided p-value <0.05 was considered statistically significant. To address the issue of multiple comparisons across different outcomes and time points, we applied the Benjamini-Hochberg procedure to control the false discovery rate at 0.05 [ 18 ]. Sensitivity Analyses We performed several sensitivity analyses to assess the robustness of our findings. First, we conducted an analysis using different matching algorithms (optimal matching and matching with replacement) to determine if the choice of matching method affected the results. Second, we implemented a high-dimensional propensity score method incorporating additional variables extracted from diagnostic codes, procedures, and medications to address potential unmeasured confounding [ 19 ]. Third, we performed an analysis restricted to patients with primary pulmonary hypertension (ICD-10-CM I27.0) to evaluate treatment effects in a more homogeneous population. Finally, we conducted an instrumental variable analysis using healthcare facility preference for sotatercept as an instrument to address potential unmeasured confounding [ 20 ] further. Results Study Population and Baseline Characteristics After propensity score matching, 185 patients with pulmonary hypertension receiving sotatercept were compared with 185 matched controls not receiving sotatercept. Baseline characteristics were well-balanced between groups after matching (standardized differences <0.15 for all variables), including demographics, comorbidities, and concomitant medications ( Table 1 ). The mean age was 53.1 ± 15.4 years in the sotatercept group and 52.1 ± 20.3 years in the control group (p=0.592). Both groups had a predominance of female patients (77.8% vs. 76.2%, p=0.711) and similar racial distribution (73.0% White in the sotatercept group vs 75.7% in the control group, p=0.552). Heart failure was the most common comorbidity in both groups (80.0% vs 78.9%, p=0.797). View this table: View inline View popup Table 1. Baseline Characteristics Before and After Propensity Score Matching Concomitant pulmonary hypertension therapies were balanced between groups, with 61.6% of sotatercept patients and 62.7% of controls receiving sildenafil (p=0.830) and 6.5% and 5.4% receiving bosentan (p=0.660), respectively. Follow-up and Clinical Outcomes Median follow-up was 145 days (interquartile range [IQR], 146 days) in the sotatercept group and 894 days (IQR, 1583 days) in the control group after matching. The differential follow-up duration necessitated time-to-event analyses to account for varying exposure periods. All-Cause Mortality All-cause mortality was significantly lower in the sotatercept group compared with the control group at 5 years of follow-up (5.4% vs. 27.3%; risk difference, -21.9 percentage points [95% CI, -29.1 to -14.7]; p<0.001) ( Figure 1A ). The 5-year Kaplan-Meier survival estimates were 96.1% in the sotatercept group versus 61.2% in the control group (log-rank p=0.042), with a hazard ratio of 0.40 (95% CI, 0.16 to 0.99) ( Figure 2A ). Download figure Open in new tab Figure 1. Risk Differences for Primary Outcomes at 5 Years Download figure Open in new tab Figure 2. Kaplan-Meier Survival Curves (5-year follow-up) ⍰ Panel A: All-cause mortality ⍰ Panel B: Rehospitalization-free survival ⍰ Panel C: MACE-free survival ⍰ Panel D: BNP-event-free survival At 3 years of follow-up, similar mortality benefits were observed (6.0% vs 21.6%; risk difference, -15.6 percentage points [95% CI, -22.8 to -8.4]; p<0.001), with Kaplan-Meier survival estimates of 97.4% versus 74.9% (log-rank p=0.015) and a hazard ratio of 0.28 (95% CI, 0.09 to 0.84). The mortality benefit was also observed, although with lower statistical significance, at 1-year follow-up (5.4% vs. 10.4%; risk difference, -5.0 percentage points [95% CI, -10.5 to 0.5]; p=0.076). Rehospitalization Patients receiving sotatercept demonstrated significantly lower rehospitalization rates at 5 years compared with the control group (15.4% vs. 38.1%; risk difference, -22.8 percentage points [95% CI, -35.8 to -9.7]; p=0.002) ( Figure 1B ). Kaplan-Meier analysis confirmed a substantial reduction in hospitalization-free survival (log-rank p<0.001) with a hazard ratio of 0.12 (95% CI, 0.03 to 0.49) ( Figure 2B ). The mean number of rehospitalizations per patient was also lower in the sotatercept group compared with the control group (1.5 vs. 14.8 over 5 years). At 3 years, rehospitalizations remained significantly lower in the sotatercept group (16.4% vs. 30.9%; risk difference, -14.5 percentage points [95% CI, -28.3 to -0.7]; p=0.025). The 1-year analysis demonstrated consistent findings (15.4% vs 24.7%; risk difference, -9.4 percentage points [95% CI, -21.6 to 2.9]; p=0.152). Major Adverse Cardiovascular Events MACE occurrence at 5 years was significantly lower in the sotatercept group compared with controls (6.4% vs. 15.5%; risk difference, -9.1 percentage points [95% CI, -16.2 to -2.0]; p=0.011) ( Figure 1C ). Kaplan-Meier analysis showed improved MACE-free survival in the sotatercept group (log-rank p=0.161) with a hazard ratio of 0.45 (95% CI, 0.14 to 1.41). The mean number of MACE events per patient was 2.0 in the sotatercept group versus 3.0 in the control group over 5 years. The 3-year analysis showed consistent MACE reduction (6.9% vs 11.0%; risk difference, -4.1 percentage points [95% CI, -10.8 to 2.6]; p=0.231), as did the 1-year analysis (6.4% vs 7.0%; risk difference, -0.6 percentage points [95% CI, -6.3 to 5.1]; p=0.828). BNP Levels The proportion of patients with elevated BNP (≥100 pg/mL) during follow-up did not differ significantly between the sotatercept and control groups at 5 years (12.8% v.s 10.6%; risk difference, 2.2 percentage points [95% CI, -6.9 to 11.3]; p=0.626) ( Figure 1D ). Kaplan-Meier estimates of BNP-event-free survival were similar between groups (log-rank p=0.673) with a hazard ratio of 0.71 (95% CI, 0.14 to 3.52). This lack of significant difference in BNP events was consistent across all follow-up periods. Outcome Consistency Across Follow-up Periods The benefit associated with sotatercept increased with longer follow-up for mortality, rehospitalization, and MACE outcomes ( Figure 3 ). The most robust and consistent benefit was observed for rehospitalization, which maintained statistical significance across most time points. Risk ratios favoring sotatercept were consistently below 0.5 for all clinical outcomes except BNP at the 5-year follow-up. Download figure Open in new tab Figure 3. Risk Ratios Across Different Follow-up Periods ⍰ Forest plot showing risk ratios with 95% CI for each outcome at: ⍰ 6 months ⍰ 1 year ⍰ 3 years ⍰ 5 years Discussion Pulmonary hypertension (pHTN) is a progressive, life-threatening condition that is characterized by the excessive proliferation of pulmonary arterial tissue [ 21 ]. Treatments for this condition have primarily targeted the pathophysiology of the disease, including vasodilators and antiproliferative therapies aiming to slow the disease progression and manage quality of life [ 22 ]. Sotatercept is a novel, recently approved recombinant fusion protein that acts as an activin signaling inhibitor, reducing vascular proliferation by balancing pro-proliferative growth factor cascades [ 22 , 23 ]. Recent clinical trials, such as the PULSAR and STELLAR, have significantly improved pulmonary vascular resistance and exercise capacity at 24 weeks [ 5 , 6 ]. While these results are promising for short-term outcomes, very few studies have explored the long-term impact of this medication on clinical outcomes for patients with pHTN. Our retrospective cohort analysis examines the impact of sotatercept on clinical outcomes for patients with pHTN for up to 5 years, representing the extended follow-up on this therapy to date. .hOur study also found that sotatercept significantly reduced rates of rehospitalization at 1 year and 5 years compared to the control. Rehospitalization is a significant issue for patients with pHTN, with the REVEAL registry reporting that among patients newly diagnosed with pHTN, 56.8% had at least one hospitalization post-enrollment, with over half being pHTN-related [ 28 ]. The authors found that pHTN hospitalization was associated with higher rehospitalizations and worse survival at 3 years [ 28 ]. Rehospitalization for pHTN patients has also been shown to have a higher length of stay and drive hospitalization costs, emphasizing its impact on the healthcare system in addition to the patients and their families [ 29 ]. An interesting finding in our study was that sotatercept did not significantly reduce the rehospitalization rate at 3 years, despite significant reductions at 1 year and 5 years. This could potentially highlight that the effects of sotatercept on rehospitalizations might be time-dependent, as shown in our study with mortality and MACE. Finally, we found no significant difference between sotatercept and control in BNP elevation throughout our study period. This contrasts with the PULSAR and STELLAR trials, which showed a significant reduction in NT-proBNP at 24 weeks with sotatercept compared to placebo [ 5 , 6 ]. Some potential reasons for this disparity include our study exploring long-term outcomes of sotatercept and our control group being treated with pHTN therapies. In contrast, the PULSAR and STELLAR trials utilized a placebo [ 5 , 6 ]. However, the SOTERIA study, which also included a control group being treated with pHTN therapy, did report that reductions in NT-proBNP levels were maintained for one year [ 24 ]. While the stability in BNP levels shown in our study is promising, this disparity highlights the importance of future studies exploring the long-term impacts of sotatercept to improve our understanding of this therapy, especially as increased NT-proBNP levels have been associated with an increased risk of mortality and lung transplantation in patients with pHTN [ 30 ]. It is important to highlight that our study compared the impact of sotatercept on BNP levels in contrast to previous studies utilizing NT-proBNP levels. Most studies show no significant differences between either as a measure of pHTN. However, some suggest that BNP levels might correlate better with pulmonary hemodynamics, while NT-proBNP levels might correlate better with the prognosis for this disease [ 31 ]. Limitations It is important to acknowledge that our study carries several limitations. Our study’s retrospective, observational nature might limit its power and ability to conclude compared to randomized controlled trials. We also did not explore the long-term impact of sotatercept on functional parameters, such as a six-minute walking distance, which could have added helpful insights into its long-term efficacy. Prior to the FDA approval of sotatercept, between 2018 and 2024, its prescription in the United States was relatively limited. However, due to the nature of TrinetX, we were able to longitudinally track patients who were enrolled in clinical trials and received sotatercept during the investigational period. Additionally, we could not extract parameters such as pulmonary vascular resistance, WHO functional class, or quality of life measures, which the medication could have impacted. Despite these limitations, our study was able to explore the long-term clinical impacts of sotatercept to a follow-up period of 5 years, revealing promising benefits worth exploring in future clinical trials. Conclusions Our study found that sotatercept may provide a progressive reduction in mortality, major adverse cardiovascular events, and rehospitalization for up to five years of follow-up, with no significant differences in BNP levels throughout our study period. This study represents the longest follow-up on sotatercept to date and highlights potential benefits worth exploring in future clinical trials. Data Availability All data produced in the present work are contained in the manuscript Supplementary Appendix Download figure Open in new tab Supplementary Figure S1. Propensity Score Distribution Before and After Matching ⍰ Density plots showing improved overlap after matching View this table: View inline View popup Supplementary Table S1. Number of Events and Instances by Outcome Category ⍰ Detailed breakdown of event counts, mean numbers per patient ⍰ P-values for between-group comparisons Central Illustration. Comprehensive Summary of Sotatercept Benefits in Pulmonary Hypertension ⍰ Visual abstract integrating key findings across all outcomes and follow-up periods ⍰ Potential mechanistic framework for observed clinical benefits Download figure Open in new tab Footnotes Financial Disclosures: None of the authors received any financial support Conflict of Interest: None azkanaeem85{at}gmail.com , Olayiwola.bolaji01{at}gmail.com , george.kidess{at}gmail.com , joudf1997{at}gmail.com , sultana.jahan14{at}gmail.com , muhammadhashim412{at}gmail.com , shaunakmangeshkar{at}gmail.com , SSorci{at}maimo.org , hayahkassis{at}gmail.com , Sourbha.S.Dani{at}lahey.org , alraies{at}hotmail.com References 1. ↵ Huang H , Hu C , Zhang R , Xu H , Cao M , Fu Y . Global Burden of Pulmonary Arterial Hypertension and Associated Heart Failure: Global Burden of Disease 2021 Analysis . JACC Heart Fail . 2025 Mar 5: 102385 . doi: 10.1016/j.jchf.2024.12.005 . OpenUrl CrossRef 2. ↵ Gelfman DM . 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