Pulmonary arterial hypertension (PAH) is a chronic and rapidly progressive disease that is characterized by extensive narrowing of the pulmonary vasculature, leading to increases in pulmonary vascular resistance, subsequent right ventricular dysfunction, and eventual death. There are currently multiple approved drugs—developed as single or combination therapies in the last few years—that have improved outcome and functionality in PAH. However, despite improvement in short-term survival with these new effective therapies, PAH remains an incurable disease with a median survival of 7 years (Figure 1).1 This chronic disease state may be characterized by morbid events such as hospitalizations that herald rapid disease progression and account for a significant disease burden (Figure 2).2,3 Physician ability to predict PAH disease progression is critical for determining optimal care of patients. Accurate risk assessment allows clinicians to determine the patient's prognosis, identify treatment goals, and monitor disease progression and the patient's response to treatment. Risk assessment for PAH patients should include a range of clinical, hemodynamic, and exercise parameters, performed in a serial fashion over the treatment course. Patient risk stratification can also help physicians better allocate treatment resources in settings where they are scarce. If widely adopted, risk prediction can enhance the consistency of treatment approaches across PAH practitioners and improve the timeliness of referral for lung transplantation. Hence, along with advancing PAH treatment options, comprehensive risk prediction is essential to make individualized treatment decisions in the current treatment era.

Several tools are currently available for assessing risk in PAH (Figure 3). These include the 2015 European Society of Cardiology/European Respiratory Society pulmonary hypertension guidelines' risk variables,4 the French registry equation,5 the National Institutes of Health risk equation,6 or a risk score such as the one derived from the Registry to Evaluate Early And Long-term PAH Disease Management.1 These registries and evaluations of clinical trial sets have provided important insights into the importance of both modifiable (eg, 6-minute walk distance, functional class, brain natriuretic peptide, and nonmodifiable (eg, age, gender, PAH etiology) risk factors that predict survival. The following review explores commonly cited risk factors, both modifiable and nonmodifiable, and their implications for patient outcomes.

Figure 1:

7-Year Survival Rate in PAH.

Reprinted from Benza RL, Miller DP, Barst RJ, Badesch DB, McGoon MD. An evaluation of long-term survival from time of diagnosis in pulmonary arterial hypertension from the REVEAL Registry. Chest. 2012;142(2):448–456, with permission from Elsevier.

Figure 1:

7-Year Survival Rate in PAH.

Reprinted from Benza RL, Miller DP, Barst RJ, Badesch DB, McGoon MD. An evaluation of long-term survival from time of diagnosis in pulmonary arterial hypertension from the REVEAL Registry. Chest. 2012;142(2):448–456, with permission from Elsevier.

Close modal
Figure 2:

Subsequent 1-Year Survival in Patients With and Without Prior Clinical Worsening. A, all patients. B, newly diagnosed patients. C, previously diagnosed patients.

Reprinted from Frost AE, Badesch DB, Miller DP, Benza RL, Meltzer LA, McGoon MD. Evaluation of the predictive value of a clinical worsening definition using 2-year outcomes in patients with pulmonary arterial hypertension: a REVEAL Registry analysis. Chest. 2013;144(5):1521–1529, with permission from Elsevier.

Figure 2:

Subsequent 1-Year Survival in Patients With and Without Prior Clinical Worsening. A, all patients. B, newly diagnosed patients. C, previously diagnosed patients.

Reprinted from Frost AE, Badesch DB, Miller DP, Benza RL, Meltzer LA, McGoon MD. Evaluation of the predictive value of a clinical worsening definition using 2-year outcomes in patients with pulmonary arterial hypertension: a REVEAL Registry analysis. Chest. 2013;144(5):1521–1529, with permission from Elsevier.

Close modal
Figure 3:

Risk Assessment Variables and Tools for PAH.

Figure 3:

Risk Assessment Variables and Tools for PAH.

Close modal

Male gender was shown to be an indicator of poor prognosis in the French pulmonary arterial hypertension (PAH) risk registry,5,7 and older male patients (aged >60 years) showed an increased risk of mortality in the REVEAL registry (Registry to Evaluate Early And Long-term PAH Disease Management).8 Based on etiology, patients with PAH associated with systemic sclerosis have a worse prognosis compared with patients with idiopathic PAH9–11 or other forms of PAH-associated connective tissue disease (Table 1).10,12 Similarly, patients with bone morphogenetic protein receptor II (BMPR2) mutations have been shown to have higher mean pulmonary arterial pressure (PAP) and pulmonary vascular resistance (PVR), indicating a more severe disease phenotype and worse prognosis.13 

Table 1.

Five-year survival from time of enrollment in REVEAL for PAH subtypes

Reprinted from Benza RL, Miller DP, Barst RJ, Badesch DB, McGoon MD. An evaluation of long-term survival from time of diagnosis in pulmonary arterial hypertension from the REVEAL Registry. Chest. 2012;142(2):448–456, with permission from Elsevier.

Five-year survival from time of enrollment in REVEAL for PAH subtypes
Five-year survival from time of enrollment in REVEAL for PAH subtypes

Functional classification allows differentiation of patients' status based on their own self-reporting of symptoms by drawing distinctions between symptoms with more than usual activity (functional class [FC] II) to shortness of breath at rest (FC IV). Although FC assessment is largely subjective and is only based on a 4-tier scale, it is remarkably consistent among studies and serves as a simple, yet powerfully effective clinical tool that should continue to be used in clinical trials and clinical practice.14 Functional classification can also be used as the basis for therapy determination or criticism of treatment decision making.15,16 Studies consistently demonstrate that patients assigned to World Health Organization FC I or II have a better prognosis than those assigned to FC III or IV.6,8,17,18 In addition, FC is a key variable in most predictive models of PAH, and regulatory approval and labeling of PAH therapies reflect the importance of FC on treatment strategy.8,18–20 As with most clinical indices used in risk assessment, reassessment of FC along the continuum of disease course is a powerful predictor of outcome. A large study by Barst et al,21 utilizing the power of the REVEAL registry, showed that patients with PAH improving from FC III to FC I/II over the course of a year had a significantly better estimated 3-year survival than patients who remain in FC III or worsen to FC IV.21 Moreover, these data show that FC improvement impacts survival outcomes regardless of cause and/or time of diagnosis. Based on these findings, patients who do not improve FC, despite treatment and in the absence of worsening of other comorbidities, or those who deteriorate to FC III after temporarily improving to FC II, should be reevaluated for further escalation of treatment (Figure 4).21 Syncope, considered a marker of FC IV symptoms, has additional prognostic relevance in PAH and is an indicator of disease severity.

Figure 4:

Functional Class: Baseline and Changes and Their Effects on Mortality.

Reprinted from Frost AE, Badesch DB, Miller DP, Benza RL, Meltzer LA, McGoon MD. Evaluation of the predictive value of a clinical worsening definition using 2-year outcomes in patients with pulmonary arterial hypertension: a REVEAL Registry analysis. Chest. 2013;144(5):1521–1529, with permission from Elsevier.

Figure 4:

Functional Class: Baseline and Changes and Their Effects on Mortality.

Reprinted from Frost AE, Badesch DB, Miller DP, Benza RL, Meltzer LA, McGoon MD. Evaluation of the predictive value of a clinical worsening definition using 2-year outcomes in patients with pulmonary arterial hypertension: a REVEAL Registry analysis. Chest. 2013;144(5):1521–1529, with permission from Elsevier.

Close modal

Most studies of 6-minute walk distance (6MWD) in PAH have found a relationship between baseline 6MWD and mortality/survival;7,8,22–24 other studies have not.25 Some studies have found a specific 6MWD threshold (eg, 380 m or 440 m) to predict survival, but these were not randomized, controlled studies, and the numeric value of the walk was actually the mean walk achieved in the open-label group of patients studied.8,26 However, the threshold of 440 meters is now accepted as a guideline-suggested goal and has been found to be predictive of low risk in 4 contemporary evaluations of the European risk table and updated REVEAL calculator (Figure 5A). Evaluation of percent-predicted 6MWD27 has added no more predictive value than absolute 6MWD.28 Change in 6MWD has not been shown to predict survival,29 largely because individual clinical studies have not been designed to evaluate mortality/survival. Improvement in 6MWD (≥41.8 m) was recently found to correlate with lowered odds of a clinical event at 12 weeks, but this accounted for only 22% of treatment effect, suggesting that change in 6MWD alone is not a valid surrogate endpoint for long-term clinical events.30 Thus, current data suggest that 6MWD has prognostic value at baseline, but the value of this parameter alone as a marker of clinical status beyond baseline seems limited.

Figure 5:

6MWD: Ideal Thresholds and Percent Decrements in 6MWD and Outcome.

5A: Benza RL, Miller DP, Gomberg-Maitland M, et al. Predicting survival in pulmonary arterial hypertension: insights from the Registry to EValuate Early and Long-term pulmonary arterial hypertension disease management (REVEAL). Circulation. 2010;122(2):164–172. https://doi.org/10.1161/CIRCULATIONAHA.109.898122.

5B: Farber HW. Validation of the 6-minute walk in patients with pulmonary arterial hypertension: trying to fit a square PEG into a round hole? Circulation. 2012;126(3):258–260. https://doi.org/10.1161/CIRCULATIONAHA.112.118547.

Figure 5:

6MWD: Ideal Thresholds and Percent Decrements in 6MWD and Outcome.

5A: Benza RL, Miller DP, Gomberg-Maitland M, et al. Predicting survival in pulmonary arterial hypertension: insights from the Registry to EValuate Early and Long-term pulmonary arterial hypertension disease management (REVEAL). Circulation. 2010;122(2):164–172. https://doi.org/10.1161/CIRCULATIONAHA.109.898122.

5B: Farber HW. Validation of the 6-minute walk in patients with pulmonary arterial hypertension: trying to fit a square PEG into a round hole? Circulation. 2012;126(3):258–260. https://doi.org/10.1161/CIRCULATIONAHA.112.118547.

Close modal

Currently available studies that have examined change in 6MWD have focused primarily on mean change and not on absolute increases or decreases in 6MWD: ie, the relative value of improving or worsening. A sentinel finding from the REVEAL registry was that worsening in 6MWD over time negatively affected survival and was significantly associated with poor prognosis. In addition, the effect of improvement was not meaningfully different from that of stabilization of 6MWD. Although change in 6MWD over time affected prognosis, it is important to understand that the effect of improvement in 6MWD on prognosis was much smaller than the effect of worsening of 6MWD (Figure 5B).

Exercise treadmill testing (ETT) approximates the total metabolic equivalents utilized by a patient during testing.31 It is a relatively new biomarker in PAH, but appears equivalent to 6MWD in predicting survival in sick and moderately sick populations and offers an alternative to 6MWD in less sick populations.32–34 Reduced exercise capacity on ETT indicates a worse hemodynamic profile, and importantly, predicts mortality in patients with PAH.35 In an interesting study by Gomberg et al, the predictive power of the REVEAL equation improved when ETT was substituted for 6MWD32 and suggests that ETT, as well as 6MWD, may be used to predict survival in PAH using the REVEAL risk calculator.36 

Plasma brain natriuretic peptide (BNP) is a hormone secreted mainly by the cardiac ventricles, with levels increasing in proportion to the degree of right ventricular dysfunction in patients with pulmonary hypertension.37 Plasma BNP level has been shown to be an independent predictor of mortality in patients with PAH.8,38 A previous analysis from REVEAL indicated that a BNP level >180 pg/mL was predictive of an increased risk of mortality at 1 year post-enrollment. The 180 pg/mL BNP threshold was developed based on an earlier REVEAL data cut (n=2716) to predict 1-year survival and was utilized for calculation of a multivariable prognostic score—the REVEAL PAH risk score.8 Patients with a baseline plasma BNP >180 pg/mL had a significantly lower survival than those with a baseline plasma BNP ≤180 pg/mL (hazard ratio [HR], 3.2; 95% confidence interval [CI] 2.7 to 3.8; P<0.001). A recently published evaluation of BNP by REVEAL investigators demonstrated that an optimal BNP threshold of 340 pg/mL strongly predicts 5-year survival in patients with PAH.39 Patients with a baseline BNP ≤340 pg/mL had a significantly lower mortality risk than those with a baseline BNP >340 pg/mL (HR, 3.6; 95% CI 3.0 to 4.2, P<0.001). Patients who remained in the low BNP group had the lowest mortality risk, and those remaining in the high BNP group had the highest mortality risk. However, BNP reduction within 15 months of enrollment was associated with a 40% decrease in risk of mortality, while a rising BNP was associated with a 3.2-fold increase in risk of mortality. Thus, a single BNP assessment, like other risk variables, may not provide a reliable prediction of overall survival.

Echocardiography and cardiac magnetic resonance imaging (MRI) allow quantitative assessment of measures of right ventricular function, which is central to risk prognostication. A tricuspid annular plane systolic excursion value of <1.8 cm has been associated with reduced 2-year survival in PAH.40 Similarly, patients who present with a right atrial area >18 cm2, either at baseline or follow-up, are at an increased risk of mortality. Pericardial effusion at baseline is a strong predictor of mortality in PAH patients41 and is an indicator of a high-risk patient. Right ventricular fractional area change combined with low oxygen pulse on cardiopulmonary exercise testing has also been associated with clinical worsening in PAH.42 Cardiac MRI is another noninvasive, high-resolution technique allowing for the visualization and direct measurement of anatomical and functional changes in the right heart (ie, enhanced volume and pressure measurements compared with echocardiography)43–46 and is becoming an increasingly used tool in the clinical study of PAH.47 Cardiac MRI-derived parameters, such as right ventricular and left ventricular volumes and ratios, mass, and ejection fraction correlate with traditional measures of functional status, including 6MWD,46,48,49 hemodynamics,50 and survival.50–54 In addition, viewing MRI parameters in the context of other standard risk parameters may allow us a better spatial assessment of risk of the continuum of each individual factor (Figure 6).50 

Figure 6:

Competing Outcomes Plot by Cardiac MRI Determined Right Ventricular/Left Ventricular End Diastolic Volume Ratios and PVR.

Benza R, Raina A, Gupta H, et al. Bosentan-based, treat-to-target therapy in patients with pulmonary arterial hypertension: results from the COMPASS-3 study. Pulm Circ. 2018;8(1):2045893217741480.

Figure 6:

Competing Outcomes Plot by Cardiac MRI Determined Right Ventricular/Left Ventricular End Diastolic Volume Ratios and PVR.

Benza R, Raina A, Gupta H, et al. Bosentan-based, treat-to-target therapy in patients with pulmonary arterial hypertension: results from the COMPASS-3 study. Pulm Circ. 2018;8(1):2045893217741480.

Close modal

Right heart catheterization, although invasive, enables monitoring of right atrial pressure,4,55 PVR, mixed venous oxygen saturation, and cardiac index over a patient's treatment course. Deteriorations in these parameters have been significantly associated with poor outcomes.

Many of the laboratory correlates of survival reflect subclinical damage to the right ventricle, low cardiac output, or estimates of congestion and nutritional status, including total bilirubin, creatinine, albumin, uric acid, troponin, and serum sodium. Five investigations have confirmed and stressed the importance of renal dysfunction and changes in renal function as a marker of mortality risk in PAH patients.8,20,35,56–58 High levels of serum uric acid correlate with patient outcome,59,60 as do changes in serum uric acid with therapy (ie, not simply baseline values) in patients with PAH.61 Changes in albumin and total bilirubin are related to overall survival.58,62,63 Hyponatremia predicts outcome even after adjusting for FC, diuretic use, right atrial pressure, and cardiac index.64 Elevated plasma troponin, at any significantly detectable level, is independently associated with more severe disease and worse outcomes in patients with PAH.65–67 

The risk of future mortal events imparted by recent hospitalizations is now recognized as an important milestone in the progressive nature of PAH. Frost et al observed that clinical worsening (defined as all-cause hospitalization or the introduction of a parenteral prostacyclin analog for any reason) was associated with increased 2-year mortality (Figure 2).3 Burger et al also reported that PAH-related hospitalizations were associated with worse survival at 3 years.68 In a multivariable analysis of the REVEAL data, all-cause hospitalization within the last 6 months was an independent predictor of both death and recurrent hospitalization (HR 1.39, P=0.015). Given the implications of this event, all-cause hospitalization was added as a new variable to the updated REVEAL calculator (REVEAL 2.0).

Risk assessment in PAH aims to educate patients about their disease trajectory, identify treatment goals, stratify patient risk, and inform clinical decision making at both patient and physician levels. It is widely agreed and strongly encouraged that risk assessment in PAH be performed, utilizing the full spectrum of available risk-related markers.55,69 The ideal risk assessment tool, particularly in a progressive and uniformly fatal disease like PAH, must hold to certain tenets. It has to be easy to use; applicable, with good predictive ability at any time in a disease course, whether that patient is newly or previously diagnosed; be equally predictive whether used at baseline or at follow-up; be applicable to all Group 1 PAH etiological subgroups; be informed by the most recent data available even if testing was not contemporaneous; retain utility when some data points or risk parameters are missing; and be dynamic (ie, capable of capturing change over time and changes in overall risk, which are reflective of changes in prognosis). To be statistically sound, the risk assessment tool must have good discrimination and calibration; be derived from sizable well-defined cohorts; be composed of risk parameters (and corresponding cut points) that are evidence-based rather than expert opinion-derived; incorporate “weighting” of the various parameters; and be validated internally and externally.69 

The National Institutes of Health (NIH) registry equation,6 reappraised in later work from the Pulmonary Hypertension Connection (PHC) registry,70 the Scottish Composite Score,28 as well as those from the larger French Pulmonary Arterial Hypertension Network (FPHN ItinérAIR-HTAP) registry71,72 and REVEAL (USA)8,20,70,73 have collectively informed current treatment guidelines by facilitating the creation of the current European Society of Cardiology (ESC)/European Respiratory Society (ERS) risk table as well as the recommendations regarding periodic assessment of patient FC, BNP level, 6MWD, and right heart catheterization to stratify risk.4 Data from these registries were used to derive equations and tools that predict survival for patients with PAH.5,6,8,18,28,70,74 Once a patient has been on treatment for at least 4 to 12 weeks, the impact of the therapy will have been captured by variables that are present in each of these models. The most versatile and validated of these equations is the REVEAL calculator.

For REVEAL, a prognostic algorithm was developed based on data from 2529 newly and previously diagnosed PAH patients and a simplified risk score calculator was later validated in 504 newly diagnosed patients.8,20 The REVEAL risk score calculator (Figure 7) was designed to help stratify patients' mortality risk and allow clinicians to make informed treatment decisions based on the unique risk profile of individual patients. The REVEAL predictive algorithm and simplified risk score calculator were internally validated in the newly diagnosed patients in REVEAL,20 demonstrated utility in serial risk assessments,73 and were externally validated in FPHN ItinérAIR-HTAP,71 UK,74 Spanish (REHAP),75 and Mayo Clinic76 registries, as well as several institutional databases enriched in specific PAH subgroups.77 Furthermore, the REVEAL risk score calculator was inherently designed to accommodate periodic updates based on emerging data from PAH registries and clinical trials.

Figure 7:

Original REVEAL Risk Score Calculator.

APAH-CTD, PAH associated with connective tissue disease; APAH-PoPH, PAH associated with portopulmonary hypertension; BNP, brain natriuretic peptide; BPM, beats per minute; DLCO, diffusing capacity of the lungs for carbon monoxide; eGFR, estimated glomerular filtration rate; FPAH, familial PAH; HR, heart rate; mRAP, mean right atrial pressure; NT-proBNP, N-terminal proBNP; NYHA, New York Heart Association; PAH, pulmonary arterial hypertension; PVR, pulmonary vascular resistance; SBP, systolic blood pressure; WHO, World Health Organization. Reprinted from Benza RL, Gomberg-Maitland M, Miller DP, et al. The REVEAL Registry risk score calculator in patients newly diagnosed with pulmonary arterial hypertension. Chest. 2012;141(2):354–362, with permission from Elsevier.

Figure 7:

Original REVEAL Risk Score Calculator.

APAH-CTD, PAH associated with connective tissue disease; APAH-PoPH, PAH associated with portopulmonary hypertension; BNP, brain natriuretic peptide; BPM, beats per minute; DLCO, diffusing capacity of the lungs for carbon monoxide; eGFR, estimated glomerular filtration rate; FPAH, familial PAH; HR, heart rate; mRAP, mean right atrial pressure; NT-proBNP, N-terminal proBNP; NYHA, New York Heart Association; PAH, pulmonary arterial hypertension; PVR, pulmonary vascular resistance; SBP, systolic blood pressure; WHO, World Health Organization. Reprinted from Benza RL, Gomberg-Maitland M, Miller DP, et al. The REVEAL Registry risk score calculator in patients newly diagnosed with pulmonary arterial hypertension. Chest. 2012;141(2):354–362, with permission from Elsevier.

Close modal

It is important to note that in order for a calculator or equation to be used in the clinical environment, it must be “discriminatory” at the individual level. This level of discrimination is determined by ROC curves or the c-index. The c-index of the original REVEAL risk equation was 0.741, which is superior to those derived from the NIH (c-index 0.588),5 PHC (c-index 0.56),29 and FPHN ItinérAIR-HTAP (c-index 0.57)14 registries. In addition, the updated REVEAL risk score calculator (REVEAL 2.0) has a c-index of 0.761, further confirming the excellent risk discrimination of the new model.78,79 Recognizing the potential for enhanced risk prediction, a new variable (all-cause hospitalization) and a revised variable (renal function measured by estimated glomerular filtration rate) were incorporated in the updated REVEAL risk score calculator. The updated REVEAL calculator, in addition to predicting survival, can also be used to predict clinical worsening.

Recently, and in accordance with the ESC/ERS 2015 guidelines, 3 European PAH registries (SPAHR,80 COMPERA19 [80% German], and French18) have developed algorithms to stratify patients with PAH as low, intermediate, or high risk of death. Unlike the NIH, PHC, UK, FPHN ItinérAIR-HTAP, and REVEAL risk equations, the recent European tools are multivariable models (rather than equations) based on expert opinion. This is an important distinction as it pertains to the tool's ability to discriminate risk for the individual patient as opposed to the cohort level, as noted above. Although—like the REVEAL calculator—these tools are easy to use, the ERS-derived tools did not use weighting of variables; are not yet demonstrated collectively to be useful in previously diagnosed patients, in all forms of PAH; and show poorer discrimination at the intermediate level and within the first year of therapy (Table 2). Importantly, weighting markedly improves the calibration of a tool and determines its discrimination level. Any tool that is being applied to clinical care to inform decision making should: 1) work on all PAH patients; 2) be applicable to the bulk of the population we see in clinic (ie, previously diagnosed); 3) should accurately segregate short-term risk, particularly within the first year of therapy and after decompensation; and 4) should prevent misclassification, particularly toward lower risk to avoid under treatment. Whether this is a calculator or “cube”81 or a combination of both (Figure 8) is the decision of the individual clinician and borne out in future investigations.

Figure 8:

Risk Assessment Tools: Calculator and Cube.

Calculator reprinted from Benza RL, Gomberg-Maitland M, Miller DP, et al. The REVEAL Registry risk score calculator in patients newly diagnosed with pulmonary arterial hypertension. Chest. 2012;141(2):354–362, with permission from Elsevier.

Weatherald J, Sitbon O, Humbert M. Validation of a risk assessment instrument for pulmonary arterial hypertension. Eur Heart J. 2017 Jun 13. doi: 10.1093/eurheartj/ehx301.

Bottom right table from Galiè N, Humbert M, Vachiery JL, et al. 2015 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension: The Joint Task Force for the Diagnosis and Treatment of Pulmonary Hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS): Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT). Eur Heart J. 2016;37(1):67–119, by permission of Oxford University Press.

Figure 8:

Risk Assessment Tools: Calculator and Cube.

Calculator reprinted from Benza RL, Gomberg-Maitland M, Miller DP, et al. The REVEAL Registry risk score calculator in patients newly diagnosed with pulmonary arterial hypertension. Chest. 2012;141(2):354–362, with permission from Elsevier.

Weatherald J, Sitbon O, Humbert M. Validation of a risk assessment instrument for pulmonary arterial hypertension. Eur Heart J. 2017 Jun 13. doi: 10.1093/eurheartj/ehx301.

Bottom right table from Galiè N, Humbert M, Vachiery JL, et al. 2015 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension: The Joint Task Force for the Diagnosis and Treatment of Pulmonary Hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS): Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT). Eur Heart J. 2016;37(1):67–119, by permission of Oxford University Press.

Close modal
Table 2.

Comparison of REVEAL calculator and ERS risk table assessments for PAH

Comparison of REVEAL calculator and ERS risk table assessments for PAH
Comparison of REVEAL calculator and ERS risk table assessments for PAH

Risk assessment should be a multifaceted approach using tools that span the broad range of evaluable factors, regardless of whether they are modifiable or not and be repeated at serial time points along the continuum of the disease. Initial and subsequent treatment escalation should always be a risk-based approach (Figure 9). We would recommend formal assessments using the REVEAL calculator at 3 to 4 months after changes in therapy and semiannually and use the cube approach in interim visits to ensure appropriate patient trajectory.

Figure 9:

Theoretic Risk Decision Tree for PAH Using Multifaceted Tools.

Figure 9:

Theoretic Risk Decision Tree for PAH Using Multifaceted Tools.

Close modal

Risk assessment forms an essential part of disease management in PAH and should be performed on a serial basis using a combination of parameters to follow the disease progression. Data from PAH registries in Europe and the United States have provided evidence for a number of prognostic factors in PAH36–41 and led to the development of independent risk scoring systems. These risk assessment tools have proven to be effective in accurately predicting survival in multiple patient cohorts. However, the PAH risk prediction tools available to us today have unique and common limitations. Importantly, none of the PAH risk prediction tools have been prospectively validated. Collaborative efforts utilizing the collective PAH databases across the globe may result in successful validation of an accurate, clinically meaningful, and impactful prognostic algorithm.

1.
Benza
RL
,
Miller
DP
,
Barst
RJ
,
Badesch
DB
,
McGoon
MD.
An evaluation of long-term survival from time of diagnosis in pulmonary arterial hypertension from the REVEAL Registry
.
Chest
.
2012
;
142
(
2
):
448
456
.
2.
Frantz
RP
,
Schilz
RJ
,
Chakinala
MM
,
et al
.
Hospitalization and survival in patients using epoprostenol for injection in the PROSPECT observational study
.
Chest
.
2015
;
147
(
2
):
484
494
.
3.
Frost
AE
,
Badesch
DB
,
Miller
DP
,
Benza
RL
,
Meltzer
LA
,
McGoon
MD.
Evaluation of the predictive value of a clinical worsening definition using 2-year outcomes in patients with pulmonary arterial hypertension: a REVEAL Registry analysis
.
Chest
.
2013
;
144
(
5
):
1521
1529
.
4.
Galiè
N
,
Humbert
M
,
Vachiery
JL
,
et al
.
2015 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension: The Joint Task Force for the Diagnosis and Treatment of Pulmonary Hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS): Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT)
.
Eur Heart J
.
2016
;
37
(
1
):
67
119
.
5.
Humbert
M
,
Sitbon
O
,
Yaïci
A
,
et al
.
Survival in incident and prevalent cohorts of patients with pulmonary arterial hypertension
.
Eur Respir J
.
2010
;
36
(
3
):
549
555
.
6.
D'Alonzo
GE
,
Barst
RJ
,
Ayres
SM
,
et al
.
Survival in patients with primary pulmonary hypertension. Results from a national prospective registry
.
Ann Intern Med
.
1991
;
115
(
5
):
343
349
.
7.
Humbert
M
,
Sitbon
O
,
Chaouat
A
,
et al
.
Survival in patients with idiopathic, familial, and anorexigen-associated pulmonary arterial hypertension in the modern management era
.
Circulation
.
2010
;
122
(
2
):
156
163
.
8.
Benza
RL
,
Miller
DP
,
Gombert-Maitland
M
,
et al
.
Predicting survival in pulmonary arterial hypertension: insights from the Registry to Evaluate Early and Long-Term Pulmonary Arterial Hypertension Disease Management (REVEAL)
.
Circulation
.
2010
;
122
(
2
):
164
172
.
9.
Launay
D
,
Sitbon
O
,
Le Pavec
J
,
et al
.
Long-term outcome of systemic sclerosis-associated pulmonary arterial hypertension treated with bosentan as first-line monotherapy followed or not by the addition of prostanoids or sildenafil
.
Rheumatology (Oxford)
.
2010
;
49
(
3
):
490
500
.
10.
Mathai
SC
Hassoun
PM.
Pulmonary arterial hypertension in connective tissue diseases
.
Heart Fail Clin
.
2012
;
8
(
3
):
413
425
.
11.
Fisher
MR
,
Mathai
SC
,
Champion
HC
,
et al
.
Clinical differences between idiopathic and scleroderma-related pulmonary hypertension
.
Arthritis Rheum
.
2006
;
54
(
9
):
3043
3050
.
12.
Condliffe
R
,
Kiely
DG
,
Peacock
AJ
,
et al
.
Connective tissue disease–associated pulmonary arterial hypertension in the modern treatment era
.
Am J Respir Crit Care Med
.
2009
;
179
(
2
):
151
157
.
13.
Evans
JD
,
Girerd
B
,
Montani
D
,
et al
.
BMPR2 mutations and survival in pulmonary arterial hypertension: an individual participant data meta-analysis
.
Lancet Respir Med
.
2016
;
4
(
2
):
129
137
.
14.
Taichman
DB
,
McGoon
MD
,
Harhay
MO
,
et al
.
Wide variation in clinicians' assessment of New York Heart Association/World Health Organization functional class in patients with pulmonary arterial hypertension
.
Mayo Clin Proc
.
2009
;
84
(
7
):
586
592
.
15.
Sitbon
O
Galiè
N.
Treat-to-target strategies in pulmonary arterial hypertension: the importance of using multiple goals
.
Eur Respir Rev
.
2010
;
19
(
118
):
272
278
.
16.
Farber
HW
,
Miller
DP
,
Meltzer
LA
,
McGoon
MD.
Treatment of patients with pulmonary arterial hypertension at the time of death or deterioration to functional class IV: insights from the REVEAL Registry
.
J Heart Lung Transplant
.
2013
;
32
(
11
):
1114
1122
.
17.
McLaughlin
VV
,
Presberg
KW
,
Doyle
RL
,
et al; American College of Chest Physicians
.
Prognosis of pulmonary arterial hypertension: ACCP evidence-based clinical practice guidelines
.
Chest
.
2004
;
126
(
1 Suppl
):
78S
92S
.
18.
Boucly
A
,
Weatherald
J
,
Savale
L
,
et al
.
Risk assessment, prognosis and guideline implementation in pulmonary arterial hypertension
.
Eur Respir J
.
2017
;
50
(
2
).
19.
Hoeper
MM
,
Kramer
T
,
Pan
Z
,
et al
.
Mortality in pulmonary arterial hypertension: prediction by the 2015 European pulmonary hypertension guidelines risk stratification model
.
Eur Respir J
.
2017
;
50
(
2
).
20.
Benza
RL
,
Gomberg-Maitland
M
,
Miller
DP
,
et al
.
The REVEAL Registry risk score calculator in patients newly diagnosed with pulmonary arterial hypertension
.
Chest
.
2012
;
141
(
2
):
354
362
.
21.
Barst
RJ
,
Chung
L
,
Zamanian
RT
,
Turner
M
,
McGoon
MD.
Functional class improvement and 3-year survival outcomes in patients with pulmonary arterial hypertension in the REVEAL Registry
.
Chest
.
2013
;
144
(
1
):
160
168
.
22.
Miyamoto
S
,
Nagaya
N
,
Satoh
T
,
et al
.
Clinical correlates and prognostic significance of six-minute walk test in patients with primary pulmonary hypertension. Comparison with cardiopulmonary exercise testing
.
Am J Respir Crit Care Med
.
2000
;
161
(
2 Pt 1
):
487
492
.
23.
Nickel
N
,
Golpon
H
,
Greer
M
,
et al
.
The prognostic impact of follow-up assessments in patients with idiopathic pulmonary arterial hypertension
.
Eur Respir J
.
2012
;
39
(
3
):
589
596
.
24.
Fritz
JS
,
Blair
C
,
Oudiz
RJ
,
et al
.
Baseline and follow-up 6-min walk distance and brain natriuretic peptide predict 2-year mortality in pulmonary arterial hypertension
.
Chest
.
2013
;
143
(
2
):
315
323
.
25.
Macchia
A
,
Marchioli
R
,
Marfisi
R
,
et al
.
A meta-analysis of trials of pulmonary hypertension: a clinical condition looking for drugs and research methodology
.
Am Heart J
.
2007
;
153
(
6
):
1037
1047
.
26.
Sitbon
O
,
Humbert
M
,
Nunes
H
,
et al
.
Long-term intravenous epoprostenol infusion in primary pulmonary hypertension: prognostic factors and survival
.
J Am Coll Cardiol
.
2002
;
40
(
4
):
780
788
.
27.
Enright
PL
Sherrill
DL.
Reference equations for the six-minute walk in healthy adults
.
Am J Respir Crit Care Med
.
1998
;
158
(
5 Pt 1
):
1384
1387
.
28.
Lee
WT
,
Peacock
AJ
,
Johnson
MK.
The role of per cent predicted 6-min walk distance in pulmonary arterial hypertension
.
Eur Respir J
.
2010
;
36
(
6
):
1294
1301
.
29.
Farber
HW.
Validation of the 6-minute walk in patients with pulmonary arterial hypertension: trying to fit a square PEG into a round hole?
Circulation
.
2012
;
126
(
3
):
258
260
.
30.
Gabler
NB
,
French
B
,
Strom
BL
,
et al
.
Validation of 6-minute walk distance as a surrogate end point in pulmonary arterial hypertension trials
.
Circulation
.
2012
;
126
(
3
):
349
356
.
31.
Patterson
JA
,
Naughton
J
,
Pietras
RJ
,
Gunnar
RM.
Treadmill exercise in assessment of the functional capacity of patients with cardiac disease
.
Am J Cardiol
.
1972
;
30
(
7
):
757
762
.
32.
Gomberg-Maitland
M
,
Huo
D
,
Benza
RL
,
McLaughlin
VV
,
Tapson
VF
,
Barst
RJ.
Creation of a model comparing 6-minute walk test to metabolic equivalent in evaluating treatment effects in pulmonary arterial hypertension
.
J Heart Lung Transplant
.
2007
;
26
(
7
):
732
738
.
33.
Gulati
M
,
Black
HR
,
Shaw
LJ
,
et al
.
The prognostic value of a nomogram for exercise capacity in women
.
N Engl J Med
.
2005
;
353
(
5
):
468
475
.
34.
Morris
CK
,
Myers
J
,
Froelicher
VF
,
Kawaguchi
T
,
Ueshima
K
,
Hideg
A.
Nomogram based on metabolic equivalents and age for assessing aerobic exercise capacity in men
.
J Am Coll Cardiol
.
1993
;
22
(
1
):
175
182
.
35.
Shah
SJ
,
Thenappan
T
,
Rich
S
,
Sur
J
,
Archer
SL
,
Gomberg-Maitland
M.
Value of exercise treadmill testing in the risk stratification of patients with pulmonary hypertension
.
Circ Heart Fail
.
2009
;
2
(
4
):
278
286
.
36.
Hsu
CH
,
Glassner
C
,
Foreman
AJ
,
et al
.
Treadmill testing improves survival prediction models in pulmonary arterial hypertension
.
Am Heart J
.
2011
;
162
(
6
):
1011
1017
.
37.
Nagaya
N
,
Nishikimi
T
,
Okano
Y
,
et al
.
Plasma brain natriuretic peptide levels increase in proportion to the extent of right ventricular dysfunction in pulmonary hypertension
.
J Am Coll Cardiol
.
1998
;
31
(
1
):
202
208
.
38.
Nagaya
N
,
Nishikimi
T
,
Uematsu
M
,
et al
.
Haemodynamic and hormonal effects of adrenomedullin in patients with pulmonary hypertension
.
Heart
.
2000
;
84
(
6
)
653
658
.
39.
Frantz
RP
,
Farber
H
,
Badesch
DB
,
Benza
RL.
Brain natriuretic peptide (BNP) level at enrollment predicts 1- and 5-year transplant-free survival in patients with pulmonary arterial hypertension (PAH): data from the REVEAL registry
.
Presented at: European Society of Cardiology (ESC) Congress 2016
;
August 27–31, 2016
;
Rome, Italy
(
#62503
).
40.
Forfia
PR
,
Fisher
MR
,
Mathai
SC
,
et al
.
Tricuspid annular displacement predicts survival in pulmonary hypertension
.
Am J Respir Crit Care Med
.
2006
;
174
(
9
):
1034
1041
.
41.
McLaughlin
VV
,
Gaine
SP
,
Howard
LS
,
et al
.
Treatment goals of pulmonary hypertension
.
J Am Coll Cardiol
.
2013
;
62
(
25 Suppl
):
D73
D81
.
42.
Badagliacca
R
,
Papa
S
,
Valli
G
,
et al
.
Echocardiography Combined With Cardiopulmonary Exercise Testing for the Prediction of Outcome in Idiopathic Pulmonary Arterial Hypertension
.
Chest
.
2016
;
150
(
6
):
1313
1322
.
43.
McLure
LE
Peacock
AJ.
Cardiac magnetic resonance imaging for the assessment of the heart and pulmonary circulation in pulmonary hypertension
.
Eur Respir J
.
2009
;
33
(
6
):
1454
1466
.
44.
Lang
IM
,
Plank
C
,
Sadushi-Kolici
R
,
Jakowitsch
J
,
Klepetko
W
,
Maurer
G.
Imaging in pulmonary hypertension
.
JACC Cardiovasc Imaging
.
2010
;
3
(
12
):
1287
1295
.
45.
Peacock
AJ
Vonk Noordegraaf
A.
Cardiac magnetic resonance imaging in pulmonary arterial hypertension
.
Eur Respir Rev
.
2013
;
22
(
130
):
526
534
.
46.
Roeleveld
RJ
,
Vonk-Noordegraaf
A
,
Marcus
JT
,
et al
.
Effects of epoprostenol on right ventricular hypertrophy and dilatation in pulmonary hypertension
.
Chest
.
2004
;
125
(
2
):
572
579
.
47.
Benza
R
,
Biederman
R
,
Murali
S
,
Gupta
H.
Role of cardiac magnetic resonance imaging in the management of patients with pulmonary arterial hypertension
.
J Am Coll Cardiol
.
2008
;
52
(
21
):
1683
1692
.
48.
Chin
KM
,
Kingman
M
,
de Lemos
JA
,
et al
.
Changes in right ventricular structure and function assessed using cardiac magnetic resonance imaging in bosentan-treated patients with pulmonary arterial hypertension
.
Am J Cardiol
.
2008
;
101
(
11
):
1669
1672
.
49.
Peacock
AJ
,
Crawley
S
,
McLure
L
,
et al
.
Changes in right ventricular function measured by cardiac magnetic resonance imaging in patients receiving pulmonary arterial hypertension-targeted therapy: the EURO-MR study
.
Circ Cardiovasc Imaging
.
2014
;
7
(
1
):
107
114
.
50.
Benza
RL
,
Raina
A
,
Gupta
H
,
et al
.
Bosentan-based, treat-to-target therapy in patients with pulmonary arterial hypertension: results from the COMPASS-3 study
.
Pulm Circ
.
2018
;
8
(
1
):
2045893217741480
.
51.
Baggen
VJ
,
Leiner
T
,
Post
MC
,
et al
.
Cardiac magnetic resonance findings predicting mortality in patients with pulmonary arterial hypertension: a systematic review and meta-analysis
.
Eur Radiol
.
2016
;
26
(
11
):
3771
3780
.
52.
van Wolferen
SA
,
Marcus
JT
,
Boonstra
A
,
et al
.
Prognostic value of right ventricular mass, volume, and function in idiopathic pulmonary arterial hypertension
.
Eur Heart J
.
2007
;
28
(
10
):
1250
1257
.
53.
Gan
CT
,
Lankhaar
JW
,
Westerhof
N
,
et al
.
Noninvasively assessed pulmonary artery stiffness predicts mortality in pulmonary arterial hypertension
.
Chest
.
2007
;
132
(
6
):
1906
1912
.
54.
van de Veerdonk
MC
,
Kind
T
,
Marcus
JT
,
et al
.
Progressive right ventricular dysfunction in patients with pulmonary arterial hypertension responding to therapy
.
J Am Coll Cardiol
.
2011
;
58
(
24
):
2511
2519
.
55.
Galiè
N
,
Humbert
M
,
Vachiery
JL
,
et al
.
2015 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension: The Joint Task Force for the Diagnosis and Treatment of Pulmonary Hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS): Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT)
.
Eur Respir J
.
2015
;
46
(
4
):
903
975
.
56.
Haddad
F
,
Peterson
T
,
Fuh
E
,
et al
.
Characteristics and outcome after hospitalization for acute right heart failure in patients with pulmonary arterial hypertension
.
Circ Heart Fail
.
2011
;
4
(
6
):
692
699
.
57.
Chakinala
MM
,
Coyne
DW
,
Benza
RL
,
et al
.
Predicting Outcomes in Pulmonary Arterial Hypertension Based on Estimated Glomerular Filtration Rate
.
Am J Respir Crit Care Med
.
2016
;
193
:
A6316
.
58.
Benza
RL
,
Gomberg-Maitland
M
,
Naeije
R
,
Arneson
CP
,
Lang
IM.
Prognostic factors associated with increased survival in patients with pulmonary arterial hypertension treated with subcutaneous treprostinil in randomized, placebo-controlled trials
.
J Heart Lung Transplant
.
2011
;
30
(
9
):
982
989
.
59.
Nagaya
N
,
Uematsu
M
,
Satoh
T
,
et al
.
Serum uric acid levels correlate with the severity and the mortality of primary pulmonary hypertension
.
Am J Respir Crit Care Med
.
1999
;
160
(
2
):
487
492
.
60.
Bendayan
D
,
Shitrit
D
,
Ygla
M
,
Huerta
M
,
Fink
G
,
Kramer
MR.
Hyperuricemia as a prognostic factor in pulmonary arterial hypertension
.
Respir Med
.
2003
;
97
(
2
):
130
133
.
61.
Dhaun
N
,
Vachiery
JL
,
Benza
RL
,
et al
.
Endothelin antagonism and uric acid levels in pulmonary arterial hypertension: clinical associations
.
J Heart Lung Transplant
.
2014
;
33
(
5
):
521
527
.
62.
Xu
XQ
,
Lv
ZC
,
Liu
QQ
,
et al
.
Direct bilirubin: A new risk factor of adverse outcome in idiopathic pulmonary arterial hypertension
.
Int J Cardiol
.
2017
;
228
:
895
899
.
63.
Takeda
Y
,
Takeda
Y
,
Tomimoto
S
,
Tani
T
,
Narita
H
,
Kimura
G.
Bilirubin as a prognostic marker in patients with pulmonary arterial hypertension
.
BMC Pulm Med
.
2010
;
10
:
22
.
64.
Forfia
PR
,
Mathai
SC
,
Fisher
MR
,
et al
.
Hyponatremia predicts right heart failure and poor survival in pulmonary arterial hypertension
.
Am J Respir Crit Care Med
.
2008
;
177
(
12
):
1364
1369
.
65.
Schuuring
MJ
,
van Riel
AC
,
Vis
JC
,
et al
.
High-sensitivity troponin T is associated with poor outcome in adults with pulmonary arterial hypertension due to congenital heart disease
.
Congenit Heart Dis
.
2013
;
8
(
6
):
520
526
.
66.
Heresi
GA
,
Tang
WH
,
Aytekin
M
,
Hammel
J
,
Hazen
SL
,
Dweik
RA.
Sensitive cardiac troponin I predicts poor outcomes in pulmonary arterial hypertension
.
Eur Respir J
.
2012
;
39
(
4
):
939
944
.
67.
Torbicki
A
,
Kurzyna
M
,
Kuca
P
,
et al
.
Detectable serum cardiac troponin T as a marker of poor prognosis among patients with chronic precapillary pulmonary hypertension
.
Circulation
.
2003
;
108
(
7
):
844
848
.
68.
Burger
CD
,
Long
PK
,
Shah
MR
,
et al
.
Characterization of first-time hospitalizations in patients with newly diagnosed pulmonary arterial hypertension in the REVEAL registry
.
Chest
.
2014
;
146
(
5
):
1263
1273
.
69.
Benza
RL
,
Farber
HW
,
Selej
M
,
Gomberg-Maitland
M.
Assessing risk in pulmonary arterial hypertension: what we know, what we don't
.
Eur Respir J
.
2017
;
50
(
2
).
70.
Thenappan
T
,
Shah
SJ
,
Rich
S
,
Tian
L
,
Archer
SL
,
Gomberg-Maitland
M.
Survival in pulmonary arterial hypertension: a reappraisal of the NIH risk stratification equation
.
Eur Respir J
.
2010
;
35
(
5
):
1079
1087
.
71.
Sitbon
O
,
Benza
RL
,
Badesch
DB
,
et al
.
Validation of two predictive models for survival in pulmonary arterial hypertension
.
Eur Respir J
.
2015
;
46
(
1
):
152
164
.
72.
Humbert
M
,
Gerry Coghlan
J
,
Khanna
D.
Early detection and management of pulmonary arterial hypertension
.
Eur Respir Rev
.
2012
;
21
(
126
):
306
312
.
73.
Benza
RL
,
Miller
DP
,
Foreman
AJ
,
et al
.
Prognostic implications of serial risk score assessments in patients with pulmonary arterial hypertension: a Registry to Evaluate Early and Long-Term Pulmonary Arterial Hypertension Disease Management (REVEAL) analysis
.
J Heart Lung Transplant
.
2015
;
34
(
3
):
356
361
.
74.
Ling
Y
,
Johnson
MK
,
Kiely
DG
,
et al
.
Changing demographics, epidemiology, and survival of incident pulmonary arterial hypertension: results from the pulmonary hypertension registry of the United Kingdom and Ireland
.
Am J Respir Crit Care Med
.
2012
;
186
(
8
):
790
796
.
75.
Escribano-Subias
P
,
Blanco
I
,
López-Meseguer
M
,
et al; REHAP investigators
.
Survival in pulmonary hypertension in Spain: insights from the Spanish registry
.
Eur Respir J
.
2012
;
40
(
3
):
596
603
.
76.
Kane
GC
,
Maradit-Kremers
H
,
Slusser
JP
,
Scott
CG
,
Frantz
RP
,
McGoon
MD.
Integration of clinical and hemodynamic parameters in the prediction of long-term survival in patients with pulmonary arterial hypertension
.
Chest
.
2011
;
139
(
6
):
1285
1293
.
77.
Mullin
CJ
,
Khair
R
,
Damico
RL
,
et al
.
Validation of the REVEAL Registry Prognostic Equation and Risk Score Calculator in Incident Systemic Sclerosis-Associated Pulmonary Arterial Hypertension
.
Am J Respir Crit Care Med
.
2017
;
195
:
A7033
.
78.
Benza
RL
,
Elliott
CG
,
Farber
HW
,
et al
.
Updated Risk Score Calculator for Pulmonary Arterial Hypertension Patients
.
J Heart Lung Transplant
.
2017
;
36
(
4 Suppl
):
S19
.
79.
Benza
RL
,
Elliott
CG
,
Farber
HW
,
et al
.
Updated Risk Score Calculator for Patients with Pulmonary Arterial Hypertension (PAH) in the Registry to Evaluate Early and Long-Term PAH Disease Management (REVEAL)
.
Am J Respir Crit Care Med
.
2017
;
195
:
A6899
.
80.
Kylhammar
D.
,
Kjellström
B
,
Hjalmarsson
C
,
et al
;
SveFPH and SPAHR. A comprehensive risk stratification at early follow-up determines prognosis in pulmonary arterial hypertension
.
Eur Heart J
.
2017
Jun
1
.
doi: 10.1093/eurheartj/ehx257
.
81.
Weatherald
J
,
Sitbon
O
,
Humbert
M.
Validation of a risk assessment instrument for pulmonary arterial hypertension
.
Eur Heart J
.
2017
Jun
13
.
doi: 10.1093/eurheartj/ehx301
.

Author notes

Disclosure: Dr Benza serves as a consultant, advisory board member, or steering committee member for Medtronic PLC; Gilead Sciences, Inc.; United Therapeutics Corporation; and Actelion Pharmaceuticals US, Inc. He has received institutional grant/research support from Actelion Pharmaceuticals US, Inc.; Bellerophon; and Eiger BioPharmaceuticals. Dr Kanwar serves as a consultant, advisory board member, or steering committee member for Bayer HealthCare LLC. He is a speaker's bureau member for Bayer HealthCare LLC. Lisa Carey Lohmueller and Jidapa Kraisangka have nothing to disclose.