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Meta-Analysis
. 2023 Jul 27;62(1):2300190.
doi: 10.1183/13993003.00190-2023. Print 2023 Jul.

Heterogeneity of treatment effects by risk in pulmonary arterial hypertension

Hao-Min Pan  1 , Robyn L McClelland  2 , Jude Moutchia  3 , Dina H Appleby  3 , Jason S Fritz  1 , John H Holmes  3 , Jasleen Minhas  1 , Harold I Palevsky  1 , Ryan J Urbanowicz  4 , Steven M Kawut  1   3 , Nadine Al-Naamani  5
Affiliations
Meta-Analysis

Heterogeneity of treatment effects by risk in pulmonary arterial hypertension

Hao-Min Pan et al. Eur Respir J. .

Abstract

Background: It is currently unknown if disease severity modifies response to therapy in pulmonary arterial hypertension (PAH). We aimed to explore if disease severity, as defined by established risk-prediction algorithms, modified response to therapy in randomised clinical trials in PAH.

Methods: We performed a meta-analysis using individual participant data from 18 randomised clinical trials of therapy for PAH submitted to the United States Food and Drug Administration to determine if predicted risk of 1-year mortality at randomisation modified the treatment effect on three outcomes: change in 6-min walk distance (6MWD), clinical worsening at 12 weeks and time to clinical worsening.

Results: Of 6561 patients with a baseline US Registry to Evaluate Early and Long-Term PAH Disease Management (REVEAL 2.0) score, we found that individuals with higher baseline risk had higher probabilities of clinical worsening but no difference in change in 6MWD. We detected a significant interaction of REVEAL 2.0 risk and treatment assignment on change in 6MWD. For every 3-point increase in REVEAL 2.0 score, there was a 12.49 m (95% CI 5.86-19.12 m; p=0.001) greater treatment effect in change in 6MWD. We did not detect a significant risk by treatment interaction on clinical worsening with most of the risk-prediction algorithms.

Conclusions: We found that predicted risk of 1-year mortality in PAH modified treatment effect as measured by 6MWD, but not clinical worsening. Our findings highlight the importance of identifying sources of treatment heterogeneity by predicted risk to tailor studies to patients most likely to have the greatest treatment response.

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Conflict of interest statement

Conflict of interest: H-M. Pan has received funding support from the National Institutes of Health (T32HL007891). R.L. McClelland has received full-time-equivalent salary support via a subcontract from the University of Pennsylvania. J.S. Fritz has had grants or contracts from United Therapeutics as monies paid to the institution for the conduct of multicentre pulmonary arterial hypertension drug trials. J.H. Holmes has received funding support from the Cardiovascular Medical Research and Education Fund; has received grants or contracts from the National Institutes of Health, University of Florida Juvenile Diabetes Research Foundation and the University of Pavia; has served as a participant on the Clinical Data to Health External Advisory Board and COACH T2D (Columbia University); and has served unpaid leadership or fiduciary roles for the American College of Medical Informatics, American College of Epidemiology and the Artificial Intelligence Society. J. Minhas has received funding support from the National Institutes of Health (T32HL007891) and the American Thoracic Society Early Career Investigator Award. H.I. Palevsky has participated on a data safety monitoring board for studies for pulmonary arterial hypertension sponsored by United Therapeutics. S.M. Kawut has received funding support from the National Institutes of Health (K24HL103844) and the Cardiovascular Medical Research and Education Fund; received consulting fees from Janssen, Morphic and Regeneron; received payment or honoraria from Janssen; contributed to continuing medical education courses through Accredo, Actelion, Aerovate, Bayer, Inari Medical, Merck, United Therapeutics, Janssen, Liquidia and Pfizer; received support for attending meetings from Aerovate; participated in data safety monitoring boards or advisory boards for United Therapeutics, Acceleron, Vivus and Aerovate; participated in leadership or fiduciary roles for the editorial board of the European Respiratory Journal (ended 2022); received stock or stock options from Verve Therapeutics; and received remote monitory equipment from PhysIQ. N. Al-Naamani has received funding support from the National Institutes of Health (K23HL141584) and from the Cardiovascular Medical Research and Education Fund. The remaining authors disclose no potential conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Patient inclusion flowchart. PAH: pulmonary arterial hypertension; FDA: US Food and Drug Administration; CTEPH: chronic thromboembolic pulmonary hypertension; REVEAL 2.0: US Registry to Evaluate Early and Long-Term PAH Disease Management; REVEAL Lite 2.0: abridged version of REVEAL 2.0; COMPERA: Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension; COMPERA 2.0: modified four-strata model of COMPERA; FPHR: French Pulmonary Hypertension Registry.
FIGURE 2
FIGURE 2
a) Forest plot of association of baseline REVEAL 2.0 risk (on continuous scale, per three-point increment) with change in 6-min walk distance (6MWD) from baseline to end of follow-up. b) Forest plot of the baseline REVEAL 2.0 (on continuous scale, per three-point increment) by treatment interaction terms and change in 6MWD from baseline to end of follow-up. Weights are from random-effects model. REVEAL 2.0: US Registry to Evaluate Early and Long-Term PAH Disease Management; REML: restricted maximum likelihood; HKSJ: Hartung, Knapp, Sidik, Jonkman approach.
FIGURE 3
FIGURE 3
a) Interaction between baseline REVEAL 2.0 risk by treatment on change in 6-min walk distance (6MWD). b) Pre- and post-treatment 6MWD stratified by baseline REVEAL 2.0 risk. REVEAL 2.0: US Registry to Evaluate Early and Long-Term PAH Disease Management.
FIGURE 4
FIGURE 4
a) Forest plot of association of baseline REVEAL 2.0 risk (on continuous scale, per three-point increment) with odds of clinical worsening at 12 weeks. b) Forest plot of the baseline REVEAL 2.0 (on continuous scale, per three-point increment) by treatment interaction terms and odds of clinical worsening at 12 weeks. Weights are from random-effects model. REVEAL 2.0: US Registry to Evaluate Early and Long-Term PAH Disease Management.
FIGURE 5
FIGURE 5
a) Forest plot of association of baseline REVEAL 2.0 risk (on continuous scale, per three-point increment) with time to clinical worsening. b) Forest plot of the baseline REVEAL 2.0 risk (on continuous scale, per three-point increment) by treatment interaction terms and time to clinical worsening. Weights are from random-effects model. REVEAL 2.0: US Registry to Evaluate Early and Long-Term PAH Disease Management.
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