Anchored Indirect Treatment Comparison Finds Comparable Effects of Pegcetacoplan and Iptacopan in Paroxysmal Nocturnal Hemoglobinuria
Authors: Peffault de Latour Régis , Szer Jeffrey , Wilson Koo , Wojciechowski Piotr , Hakimi Zalmai , Nazir Jameel , Czech Barbara , Kulasekararaj Austin G. 
Published: December 2024

Background
Paroxysmal nocturnal hemoglobinuria (PNH) is an ultra-rare, acquired non-malignant hematological disorder characterized by thrombosis risk, high morbidity, and high symptom burden. This anchored indirect treatment comparison (ITC) evaluated the proximal complement inhibitors (Ci), pegcetacoplan (C3i) and iptacopan (factor B inhibitor) in C5i treatment-experienced patients with PNH.
Methods
Data obtained retrospectively from 2 pivotal clinical studies informed the ITC: patient-level data for pegcetacoplan from PEGASUS (NCT03500549) at 16 weeks, and digitalised published trial data for iptacopan from APPLY PNH (NCT04558918) at 24 weeks. The availability of a common reference C5i treatment group in both PEGASUS and APPLY PNH enabled the analyses. However, considering differences in data availability, study design, duration, and statistical methods between PEGASUS and APPLY PNH, a comparison of the primary endpoints measured in each study was not feasible. Hence, the ITC evaluated other select study endpoints including hemoglobin (Hb) levels, absolute reticulocyte count (ARC), lactate dehydrogenase (LDH) levels, and patient reported outcomes measured on Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-Fatigue) scale scores. The anchored ITC (Bucher method) was conducted based on mean changes from baseline (CFB) to randomized controlled period end (end of study, EOS; week 16 for pegcetacoplan and week 24 for iptacopan). Regression-based simulated treatment comparison (STC) assessed the robustness of results, with models selected based on the Bayesian information criterion.
Results
Baseline characteristics of patient populations in PEGASUS and APPLY PNH were broadly similar.
Anchored ITC showed comparable outcomes (mean difference, [95% CI]; mean absolute values (SD) treatment arm vs control arm) in CFB to EOS across endpoints between pegcetacoplan vs C5i, and iptacopan vs C5i, respectively: Hb level-0.49 g/dL [-1.78 ,0.80], 54 (1.96) vs 8.58 (0.96) and 12.48 (1.12) vs 9.12 (1.42);ARC-34.41 109/L [-90.02, 21.21], 14 (26.63) vs 220.78 (88.73) and 70.96 (42.41) vs 176.19 (80.94);LDH level-115.16 U/L [-244.40, 14.07], 11 (78.05) vs 353.19 (477.50) and 270.96 (117.54) vs 275.96 (127.45);FACIT-Fatigue: 57 [-5.60, 12.73], 41.81 (9.61) vs 30.62 (11.76) and 43.08 (7.80) vs 31.04 (12.65).
On safety versus pegcetacoplan, patients treated with iptacopan revealed significantly greater risk of headache, with no significant differences in other safety endpoints. STC analyses confirmed that point estimates and CI across all endpoints were consistent with results of the Bucher analyses.
Conclusions
This anchored ITC of the two proximal complement inhibitors, pegcetacoplan and iptacopan, used the best available trial data for the comparator treatments versus C5i standard of care, respectively. Our anchored ITC findings did not reveal significant differences between pegcetacoplan and iptacopan in clinical endpoints or patient-reported outcomes. Hence consideration of both, clinical and individualized patient-centered factors (including age, comorbidities, lifestyle needs, and administration preferences between pegcetacoplan long-acting subcutaneous or iptacopan short-acting oral), are clearly needed in treatment decision-making.
In the absence of direct, head-to-head clinical trials, ITC provides robust comparative data on which to inform evidence-based medicine. The anchored ITC analytic approach has distinct advantages over unanchored comparisons, hence explaining the difference in findings by another previously presented ITC which did not use an anchored approach. One key strength is that the anchored ITC preserved the randomization feature of both trials while cancelling the impact of unbalanced prognostic factors, of which some are known and others unknown. A potential limitation was digitalisation of graphed data and imputation of standard deviation for mean CFB values, along with an assumption of normal distribution of the data.