Proteasome Inhibitor-Associated PRES in Multiple Myeloma: Pharmacovigilance Evidence of Risk Signals and Concomitant Drug Interactions

Proteasome Inhibitor-Associated PRES in Multiple Myeloma: Pharmacovigilance Evidence of Risk Signals and Concomitant Drug Interactions | 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 Article Proteasome Inhibitor-Associated PRES in Multiple Myeloma: Pharmacovigilance Evidence of Risk Signals and Concomitant Drug Interactions Peipei Gao, Huajun Sun, Hongyan Wei, Boyu Tan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7709378/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Proteasome inhibitors (PIs), essential for multiple myeloma (MM) therapy, are associated with posterior reversible encephalopathy syndrome (PRES), a rare but serious neurotoxic event. Using the FDA Adverse Event Reporting System (2004–2025), we conducted a disproportionality analysis with Bayesian Confidence Propagation Neural Network to assess PI-associated PRES risk and the impact of concomitant medications. Among 315 cases, bortezomib (73.3%) and carfilzomib (24.1%) were predominant, mainly affecting females (72.3%), median age 62, with a median onset of 21 days. Significant risk signals were detected for PIs overall (IC 2.71, 95% CI 2.52–2.84), driven by bortezomib (IC 3.00, 95% CI 2.78–3.16) and carfilzomib (IC 2.96, 95% CI 2.60–3.22). In stratified analyses of concomitant antihypertensives, ACEIs increased risk (IC 2.81, 95% CI 1.94–3.42), while ARBs (IC 1.90, 95% CI 0.34–2.89) and CCBs (IC 2.24, 95% CI 1.47–2.77) suggested risk reduction. Concomitant glucocorticoids significantly lowered risk for bortezomib (IC 0.67, 95% CI 0.41–0.86) and carfilzomib (IC 1.07, 95% CI 0.67–1.36). All PRES cases were serious; carfilzomib had a 53.9% rate of death or life-threatening outcomes. These findings underscore the need for early clinical vigilance during PI therapy and suggest glucocorticoids mitigate PRES risk, warranting further validation. Biological sciences/Drug discovery Health sciences/Medical research Health sciences/Neurology Biological sciences/Neuroscience Proteasome inhibitors reversible posterior leukoencephalopathy syndrome FAERS Pharmacovigilance Glucocorticoid Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Multiple myeloma (MM), a hematologic malignancy characterized by the proliferation of clonal plasma cells and the production of monoclonal immunoglobulins, accounts for approximately 10% of all hematologic cancers[ 1 ]. Although MM remains incurable, significant progress in diagnostic techniques and therapeutic approaches, particularly the introduction of proteasome inhibitors (PIs), has greatly improved its management[ 2 ]. Bortezomib, the first PI, approved in 2003, paved the way for the development of subsequent agents such as carfilzomib and ixazomib. With its optimized structure and mechanism, carfilzomib delivers an improved benefit-risk profile, while ixazomib, the first oral PI, boosts patient adherence[ 3 ]. Today, PI-based regimens stand as a cornerstone of MM therapy, highlighting their essential role in modern treatment approaches[ 1 , 4 ]. Common adverse events (AEs) associated with PIs, such as peripheral neuropathy and infections, are well-documented, whereas complications affecting the central nervous system remain rare[ 5 , 6 ]. Nevertheless, a growing number of reports have linked the PIs bortezomib and carfilzomib to reversible posterior leukoencephalopathy syndrome (PRES)[ 7 – 10 ]. This clinical syndrome is characterized by reversible subcortical vasogenic edema, most observed in the parietal-occipital regions on neuroimaging. PRES typically presents with acute or subacute neurological symptoms, including headache, altered mental status, seizures, and visual disturbances[ 11 ]. Known triggers encompass a wide range of conditions, such as hypertension, renal failure, preeclampsia/eclampsia, organ transplantation, autoimmune diseases, and the use of immunosuppressants or cytotoxic drugs. Although PRES is generally reversible with prompt removal of the triggering factor, delayed or inadequate management can lead to permanent neurological damage or life-threatening complications, including cerebral hemorrhage or ischemic infarction[ 12 ]. PRES is a critical safety concern for PIs, especially in MM patients with comorbidities like hypertension or renal impairment. However, the comparative risk profiles of different PIs and the role of co-administered glucocorticoids, such as dexamethasone, which can both trigger PRES and treat its associated edema, remain poorly understood[ 13 – 15 ]. To bridge this gap, our study harnesses the FDA Adverse Event Reporting System (FAERS), a global database of spontaneous adverse event reports, to explore the link between PIs and PRES. This real-world evidence aims to deepen clinical insight into PI safety. 2. Materials and Methods 2.1 Data Source and Preprocessing This study utilized data from the FAERS database, covering the period from January 2004 to March 2025. Data extracted for this study encompassed demographic characteristics, drug details, AEs, onset dates, and clinical outcomes. Reports were excluded based on FDA guidelines, including those missing year or month data, where event dates preceded drug initiation, or where AEs were reported fewer than three times. Since FAERS data are anonymized and publicly accessible, this study did not require ethical review. 2.2 Outcome and Indication Identification AEs in FAERS are coded using the Medical Dictionary for Regulatory Activities (MedDRA) preferred terms (PTs). To analyze these events by specific medical conditions, Standardized MedDRA Queries (SMQs) are employed, grouping related PTs together. For increased specificity in this study, narrow SMQs, which target the event of interest more precisely, were utilized[ 16 ]. The indication for proteasome inhibitor (PI) exposure was defined using the narrow SMQ for plasmacytoma (SMQ code 10035484), while PRES was identified using the MedDRA PT code 10071066. 2.3 Exposure Definition The PIs analyzed in this study included bortezomib, carfilzomib, and ixazomib. Concomitant medications comprised immunomodulatory agents (thalidomide, lenalidomide, and pomalidomide) and glucocorticoids. Glucocorticoids were classified according to the Anatomical Therapeutic Chemical (ATC) Classification System at Level 4 (H02AB, Glucocorticoids), without specifying individual agents. All the drug names were standardized to generic forms using DrugBank v5.1.9[ 17 ], with fuzzy matching applied to minimize the risk of misclassification[ 18 ]. Each case was independently verified by two clinical pharmacists. Only reports identifying PIs as the primary or secondary suspect drugs were included in the analysis. To validate the risk signals, tacrolimus and clopidogrel were used as positive and negative controls, respectively. 2.4 Statistical Analysis This retrospective pharmacovigilance study investigates the potential association between PIs and PRES in patients with MM. Disproportionality analysis was performed using R (version 4.4.2) with the DiAna package to evaluate safety signals derived from ICSRs[ 19 – 21 ]. Demographic characteristics of ICSRs were summarized using descriptive statistics, with categorical variables reported as counts and percentages, and continuous variables expressed as medians with interquartile ranges (IQRs). The Bayesian Confidence Propagation Neural Network (BCPNN) method was employed to detect safety signals, using the Information Component (IC) as the primary metric. A positive safety signal was defined as a lower bound of the 95% credible interval (IC025) greater than 0, with a minimum of three PRES cases per drug to ensure statistical reliability. The BCPNN method effectively accounts for data sparsity, providing robust estimates suitable for spontaneous reporting systems[ 18 ]. To assess potential confounding biases in the disproportionality analysis, we conducted stratified analyses to evaluate the robustness of the findings. These analyses accounted for key clinical variables, including the presence of comorbid hypertension (PT code: 10020772) and concomitant therapies such as angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), calcium channel blockers (CCBs), glucocorticoids, and immunomodulatory agents (IMiDs). Additional stratifications examined glucocorticoid use in the absence of hypertension and the combined use of immunomodulatory agents and glucocorticoids. This approach was designed to enhance the reliability of disproportionality analysis results by systematically addressing potential confounders and ensuring a comprehensive evaluation of their impact on the observed associations. 3. Results 3.1 Descriptive Analysis From the first quarter of 2004 to the first quarter of 2025, a total of 131,908 adverse event reports related to PIs were identified in the FAERS database. Among these, we identified 339 reports of posterior reversible encephalopathy syndrome (PRES). After applying inclusion criteria, 315 cases were included in the final analysis, in which PIs were designated as the primary and secondary suspect drug (Fig. 1 ) . The specific PIs implicated in these 315 cases were predominantly bortezomib, involved in 231 reports (73.3%), followed by carfilzomib in 84 reports (26.7%) and ixazomib in 11 reports (3.5%). The baseline characteristics of the 315 patients are summarized in Table 1 . PRES was more frequently reported in females (72.26%), with a median age of 62 years (IQR, 53–70). Notably, patients who developed PRES while on ixazomib were older, with a median age of 72 years (IQR, 69–78). The median time to onset of PRES was 21 days (IQR, 10–90). Ixazomib was associated with the longest median time to onset at 63 days (IQR, 9–225). Most reports originated from Europe (53.02%) and North America (39.68%) and were submitted by physicians (40.45%). Table 1 Baseline characteristics of patients with PRES events associated with protease inhibitors Characteristic Overall N = 315 Bortezomib N = 231 Carfilzomib N = 76 Ixazomib N = 8 Age (years) 62 (53.00–70) 60 (53.00–68) 64 (52.50–70) 72 (69.00–78) Unknown 54 37 12 5 Sex Female 198(72.26) 157(78.89) 36(52.94) 5(71.43) Male 76(27.74) 42(21.11) 32(47.06) 2(28.57) Unknown 41 32 8 1 Submission Direct 5(1.59) 3(1.30) 2(2.63) 0(0.00) Expedited 282(89.52) 215(93.07) 59(77.63) 8(100.00) Periodic 28(8.89) 13(5.63) 15(19.74) 0(0.00) Reporter Consumer 31(10.03) 27(11.89) 2(2.70) 2(25.00) Healthcare practitioner 68(22.01) 61(26.87) 7(9.46) 0(0.00) Other 77(24.92) 61(26.87) 15(20.27) 1(12.50) Pharmacist 8(2.59) 1(0.44) 7(9.46) 0(0.00) Physician 125(40.45) 77(33.92) 43(58.11) 5(62.50) Unknown 6 4 2 0 Continent North America 125(39.68) 101(43.72) 21(27.63) 3(37.50) Europe 167(53.02) 118(51.08) 47(61.84) 2(25.00) Asia 16(5.08) 11(4.76) 4(5.26) 1(12.50) South America 2(0.63) 0(0.00) 2(2.63) 0(0.00) Oceania 5(1.59) 1(0.43) 2(2.63) 2(25.00) Africa 0(0.00) 0(0.00) 0(0.00) 0(0.00) Wt (kg) 62 (50.00–77) 52 (34.00–70) 66 (58.00–79) 79 (75.00–89) Unknown 228 178 45 5 Time to onset 21 (10.00–90) 15 (9.00–60) 27 (11.00-176) 63 (9.00-225) Unknown 201 166 33 2 Role code SS 168(53.33) 144(62.34) 23(30.26) 1(12.50) PS 147(46.67) 87(37.66) 53(69.74) 7(87.50) Denote : data are presented as n (%) for categorical variables and median (interquartile range) for continuous variables. 3.2 Disproportionality Analysis The BCPNN analysis revealed significant disproportionality signals for PRES associated with PIs overall (IC 2.71, 95% CI 2.52–2.84). Signals were robust for bortezomib (IC 3.00, 95% CI 2.78–3.16), and carfilzomib (IC 2.96, 95% CI 2.60–3.22). In contrast, no significant signal was detected for ixazomib (IC 0.06, 95% CI -0.97–0.75) (Fig. 2 ). A sensitivity analysis using tacrolimus as positive and clopidogrel as negative controls yielded the expected strong positive and negative signals, respectively, supporting the validity of our analysis results (Table 2 ). Table 2 BCPNN analysis of PRES risk signals associated with PIs Drug D_E D_nE nD_E nD_nE IC (95% CI) PIs 315 97853 8866 18799775 2.71 (2.52–2.84) Bortezomib 231 58130 8950 18839498 3.00 (2.78–3.16) Carfilzomib 84 21166 9097 18876462 2.96 (2.60–3.22) Ixazomib 11 21672 9170 18875956 0.06 (-0.97–0.75) Clopidogrel 0 64043 9181 18833585 -5.99 (-16.31–-4.01) Tacrolimus 1275 108547 7906 18789081 4.56 (4.47–4.63) Denote: D_E , the number of reports containing the drug of interest and the event of interest; D_nE , reports containing the drug of interest but not the event of interest; nD_E , reports for other drugs containing the event of interest; and nD_nE , reports for other drugs not containing the event of interest. CI , confidence interval. 3.3 Stratify Analysis 3.3.1 By indication To mitigate potential confounding, we performed several stratified analyses. When the analysis was restricted to cases with an indication of plasma cell neoplasms (74.91% of PRES cases), the overall risk signal for PIs was slightly attenuated but remained significant (IC 2.21, 95% CI 2.00–2.37). Specifically, bortezomib (IC 2.53, 95% CI 2.28–2.72) and carfilzomib (IC 2.56, 95% CI 2.16–2.85) maintained strong signals, whereas ixazomib did not reach the signal threshold (IC -0.61, 95% CI -1.82– 0.19) (Fig. 3 A, Supplementary Table S1) . 3.3.2 By disease status Stratification by comorbid hypertension showed a persistent signal in both patients with hypertension (IC 2.14, 95% CI, 1.16–2.80) and those without (IC 2.72, 95% CI 2.53–2.86) (Fig. 3 B). A similar pattern was observed when analyses were stratified by the co-occurrence of hypertension-related adverse events (Fig. 3 C, Supplementary Table S2-S3) . 3.3.3 By concomitant medication Compared with non-concomitant users, concomitant ACEIs use was associated with slightly elevated PRES risk signals, mainly for bortezomib (IC 2.5, 95% CI, 1.29–3.31) and carfilzomib (IC 3.12, 95% CI, 1.82–3.98); no signals were observed for ixazomib (Fig. 4 A, Supplementary Table S4) . Conversely, concomitant ARBs or CCBs use showed a trend toward lower risk signals. Due to the small number of cases with concomitant ARBs use, no statistically significant differences were observed. Concomitant CCBs use was associated with reduced IC values for bortezomib (IC 2.21, 95% CI, 1.19–2.91) and carfilzomib (IC 2.73, 95% CI, 1.52–3.53) (Fig. 4 B, 4 C, Supplementary Table S5-S6) . Further analyses explored the impact of concomitant medications. Concomitant use of IMiDs had a minimal effect on the PRES signal associated with PIs (IC 2.67, 95% CI 2.42–2.85) (Fig. 5 B, Supplementary Tables S8 ). Strikingly, concomitant glucocorticoid use was associated with a markedly lower PRES signal (IC 0.52, 95% CI 0.30–0.67) compared to the unstratified analysis (Fig. 5 A). This attenuating effect was consistent across individual PIs, with bortezomib (IC 0.69, 95% CI 0.43–0.88) and carfilzomib (IC 1.07, 95% CI 0.67–1.36) retaining significance, albeit at a reduced level (Supplementary Table S7 ). This pattern also held in multi-stratified analyses, where the signal remained attenuated in patients receiving glucocorticoids alongside IMiDs (IC 1.61, 95% CI 1.29–1.84) or in patients without hypertension (IC 0.50, 95% CI 0.28–0.67) (Fig. 5 C, 5 D, Supplementary Tables S9-S10 ). 3.4 Temporal Trend Analysis The temporal analysis of PRES risk signals from 2004 to 2025 showed an increasing trend in the early years, starting from a null signal in 2004 (IC -0.02, 95% CI -10.34–1.96) and peaking in 2015 (IC 2.94, 95% CI 2.64–3.17). Subsequently, the signal strength stabilized, with IC values fluctuating between 2.3 and 2.78 through the first quarter of 2025 (Fig. 6 ). 3.5 Clinical Outcomes All 315 PIs-associated PRES events were classified as serious. The outcomes including death (23.81%), life-threatening conditions (17.46%), hospitalization (24.13%), disability (2.22%), and other serious AEs (32.38%). In total, 41.27% of cases resulted in death or a life-threatening event. Carfilzomib was associated with the highest proportion of death/life-threatening outcomes (53.95%), followed by bortezomib (37.66%) and ixazomib (25.00%) (Table 3 ). Table 3 Clinical outcomes of PRES events associated with protease inhibitors Outcome Overall N = 315 Bortezomib N = 231 Carfilzomib N = 76 Ixazomib N = 8 Death 75 (23.81) 60 (25.97) 15 (19.74) 0 (0.00) Life threatening 55 (17.46) 27 (11.69) 26 (34.21) 2 (25.00) Disability 7 (2.22) 6 (2.60) 1 (1.32) 0 (0.00) Hospitalization 76 (24.13) 52 (22.51) 20 (26.32) 4 (50.00) Other serious 102 (32.38) 86 (37.23) 14 (18.42) 2 (25.00) 4. Discussion PIs remain a cornerstone of MM therapy across all treatment phases[ 4 ]. While generally well tolerated, their use can be complicated by rare but serious adverse events (AEs) such as PRES. In this large pharmacovigilance analysis, 315 PI-associated PRES cases were identified, predominantly involving bortezomib (73.3%) and carfilzomib (24.1%). These reporting patterns likely reflect approval timelines and usage prevalence, with bortezomib’s broader application across treatment settings accounting for its predominance[ 22 ]. Our demographic findings are consistent with prior reports. The predominance of female patients (72.26%) supports evidence of sex-specific susceptibility to PRES, potentially mediated by hormonal influences or structural differences in neuronal architecture[ 23 ]. The overall median onset of 21 days highlights early treatment as a critical risk window[ 11 , 15 ], while the notably longer onset observed with ixazomib (63 days) represents a novel signal that warrants further study. Disproportionality analysis confirmed significant PRES signals for bortezomib and carfilzomib, but not for ixazomib. This disparity may relate to differences in pharmacological properties. Carfilzomib’s irreversible β5 inhibition, with additional β2 activity at higher concentrations[ 5 , 24 ], likely contributes to endothelial dysfunction by suppressing NF-κB activation and VEGF transcription, thereby destabilizing the blood–brain barrier[ 25 , 26 ]. Bortezomib’s off-target inhibition of neuronal proteases may further predispose to autonomic dysfunction, vasoconstriction, and edema, mechanisms not shared by carfilzomib[ 9 ] , [ 27 ]. The absence of a signal for ixazomib may reflect both its distinct pharmacological profile and the smaller number of reports, limiting statistical power. Hypertension, a classical risk factor for PRES, revealed a paradoxical associated in out dataset: patients with pre-existing hypertension receiving PIs exhibited a lower risk of PRES compared to those without a prior history of hypertension. This result does not imply a protective effect of hypertension per se, but may instead relate to adaptations in cerebral autoregulation. Chronic hypertension induces arteriolar smooth muscle hypertrophy, vascular wall thickening, and remodeling, allowing cerebral vessels to adapt to higher perfusion pressures over time[ 28 – 30 ]. Consequently, such patients may be less prone to surpassing the upper limit of cerebral autoregulation during acute blood pressure fluctuations[ 29 ], conferring greater tolerance to PI-induced endothelial injury and hemodynamic stress. This mechanistic interpretation also helps explain why approximately 50% of hypertensive patients who develop PRES demonstrate mean arterial pressures exceeding the autoregulatory threshold (≥ 140–150 mmHg)[ 11 ]. Moreover, patients with established hypertension are commonly under antihypertensive management prior to PI initiation. This prophylactic intervention may mitigate PI-related hypertensive crises, thereby indirectly reducing PRES risk. Interestingly, even among PRES cases, those with concurrent hypertension-related AEs showed slightly reduced risk, possibly due to earlier recognition and more aggressive management of hypertension compared to PRES itself. In the evaluation of potential confounding by antihypertensive medications, we observed divergent effects across different classes. Specifically, ACEIs, ARBs, and CCBs exhibited distinct risk signals for PRES, with ACEIs showing an opposite trend compared to ARBs and CCBs. While both ACEIs and ARBs target the renin–angiotensin system, underlying mechanistic differences may explain these divergent associations. ACEIs inhibit angiotensin-converting enzyme, thereby reducing angiotensin II formation but also preventing bradykinin degradation, which leads to elevated bradykinin levels. As a potent vasodilator, bradykinin can increase vascular permeability[ 31 ]. Although the pathophysiology of PRES is not fully elucidated, key hypotheses involve reduced transcription of endothelial trophic factors such as vascular endothelial growth factor, culminating in endothelial dysfunction, vasospasm, and blood–brain barrier disruption[ 11 , 32 ]. In the setting of PI-induced endothelial injury, ACEI-mediated bradykinin accumulation may further enhance vascular permeability and promote PRES onset. By contrast, ARBs selectively block the binding of angiotensin II to Ang II type 1 receptors without impacting bradykinin metabolism[ 33 ], providing a potential rationale for the opposing risk trends between ACEIs and ARBs. CCBs, through inhibition of calcium influx into vascular smooth muscle cells, promote vasodilation, alleviate cerebrovascular vasospasm, and stabilize endothelial function[ 34 , 35 ], thereby mitigating several pathological pathways implicated in PI-associated PRES. Aligning with this mechanism, our data indicated that concomitant CCB use was linked to a substantially reduced PRES risk. Nevertheless, these mechanistic interpretations are hypothesis-generating and warrant further validation; thus, the current findings should be interpreted cautiously. Further combination analysis revealed that the concomitant use of glucocorticoids was associated with a markedly attenuated PRES signal (Fig. 4 A). Prior studies have suggested that glucocorticoids may induce or exacerbate hypertension, thereby precipitating PRES, consistent with the hyperperfusion theory[ 13 ]. This theory proposes that acute elevations in blood pressure can exceed cerebral autoregulatory capacity, resulting in hyperperfusion, endothelial damage, blood–brain barrier disruption, and subsequent vasogenic edema with associated clinical features [ 23 ]. However, our results suggest that hypertension and hyperperfusion alone are insufficient to fully explain the observed PRES risk. As a cornerstone of standard therapy for multiple myeloma, glucocorticoids not only exert direct antitumor and immunomodulatory effects but also possess potent anti-inflammatory and endothelium-stabilizing properties[ 36 ]. These protective actions may counterbalance PI-induced vascular injury and vasogenic edema, thereby reducing the overall risk of PRES. This observation was consistently evident in our data, suggesting that PRES pathobiology is unlikely to be attributable solely to hemodynamic mechanisms and more likely arises from the interplay of multiple biological pathways. All PI-associated PRES cases were classified as serious, with 41.27% resulting in death or life-threatening outcomes, likely compounded by the severity of underlying MM. Carfilzomib exhibited the highest rate of these severe outcomes (53.95%), possibly due to its increased potency or patient selection bias. Prompt detection and management, including PI discontinuation or Symptomatic treatment, are crucial, as PRES is generally reversible, although delays can lead to irreversible neurological damage[ 12 ]. 5. Limitations The FAERS database, as a spontaneous reporting system, has inherent limitations that constrain the ability to establish causal relationships. Key challenges include reporting biases, incomplete data, and unmeasured confounding factors, such as genetic predispositions, comorbidities, concomitant medications, and interindividual variability, which may influence the observed associations. Although stratified analyses were undertaken to mitigate confounding from comorbid hypertension and concomitant therapies, including ACEIs, ARBs, CCBs, glucocorticoids, and immunomodulatory agents, residual confounding from unmeasured covariates cannot be excluded. Furthermore, given the limited number of PRES cases, multivariable logistic regression could not be performed to adjust for multiple risk factors simultaneously, warranting cautious interpretation of the findings. Notably, while stratified analyses suggested a potential reduction in PRES risk associated with glucocorticoid use, this statistical association does not establish causality and requires validation through methodologies beyond pharmacovigilance, such as prospective clinical studies. In addition, the spontaneous nature of FAERS data precludes estimation of PRES incidence in the general population, thereby limiting the generalizability of these observations. 6. Conclusion This FAERS-based disproportionality analysis reveals the risk profile of PRES associated with PIs, with bortezomib and carfilzomib showing significant pharmacovigilance signals, particularly among middle-aged and older female patients. Concomitant glucocorticoid use was associated with a significantly attenuated risk of PRES, however further mechanistic and epidemiological validation is required. While PRES is often reversible, the risk of serious adverse events remains non-negligible. Clinicians should remain vigilant for PRES during PI therapy, especially in the early treatment phase, and implement timely preventive and therapeutic measures when indicated. Declarations Funding This study was funded by the Changning District Medical and Health Scientific Research Special Project of Shanghai (Grant ID. CNKW2024Y20) , Hunan Provincial Natural Science Foundation Joint Fund (Grant ID 2022JJ80066), the Young Medical Talents Training Program of the Pudong Health Committee of Shanghai (Grant ID. PWRq2022-28) and the Clinical Pharmacy Key Specialized Subject Construction Project of Pudong Hospital Affiliated to Fudan University (Grant ID. Tszk2020-05). Conflict of interest The authors declare that they have no conflict of interests. Ethics approval The data included in this study were obtained from the FAERS database, which is publicly available and anonymous, and therefore the study was exempt from approval by the institutional ethics committee. Statement of Human and Animal Rights This article does not contain any studies with human or animal subjects performed by any of authors. Consent to participate Not applicable. Consent for publication Not applicable. Data Availability The raw data used and/or analyzed in this study are accessible from the FAERS Quarterly Data Extract Files, available at https://fis.fda.gov/extensions/FPD-QDE-FAERS/FPD-QDE-FAERS.html. Code availability Not applicable. Author contributions P.G. was involved in the concept and design of the study, data collection and analysis, and drafting and critical review of the manuscript. H.S. finalized and provided suggestions to improve the manuscript. 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2","display":"","copyAsset":false,"role":"figure","size":57239,"visible":true,"origin":"","legend":"\u003cp\u003eBCPNN analysis of PRES risk signals associated with PIsand sensitivity analysis with controls\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7709378/v1/bc87a26120ae2678acbc9591.png"},{"id":96970258,"identity":"9ec250e2-04de-41af-b57c-a6ffa5555844","added_by":"auto","created_at":"2025-11-28 07:13:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":44531,"visible":true,"origin":"","legend":"\u003cp\u003eStratified disproportionality analysis of PRES risk signals associated with PIs by indication and hypertension status\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7709378/v1/4b8b2d88a05d2dd89081258b.png"},{"id":97137083,"identity":"6cab2567-e844-4e28-8220-ea8ddf946f3e","added_by":"auto","created_at":"2025-12-01 09:57:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48393,"visible":true,"origin":"","legend":"\u003cp\u003eStratified disproportionality analysis of PRES risk signals associated with PIs by concomitant use of ACEIs, ARBs, and CCBs\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7709378/v1/117eddd3447e8c6c9a223195.png"},{"id":97137975,"identity":"64df0ad2-528e-4e26-8b0b-3f40085fb64a","added_by":"auto","created_at":"2025-12-01 09:58:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":75389,"visible":true,"origin":"","legend":"\u003cp\u003eStratified analysis of PRES risk signals associated with PIs by glucocorticoid use, IMiDs, and hypertension interactions\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7709378/v1/d5d67149491d52aef22fbd79.png"},{"id":97137889,"identity":"beede584-f913-433b-ba4f-17b8332d3bcd","added_by":"auto","created_at":"2025-12-01 09:58:17","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":41372,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal Trends in the IC Values for PRES Risk Associated with PIs, 2004–2025\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7709378/v1/dcae2665f0afb14bb4ff2202.png"},{"id":97673143,"identity":"e109a9a8-0469-4226-a45d-96b181b082f1","added_by":"auto","created_at":"2025-12-08 09:39:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1342975,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7709378/v1/5dfb2425-49a9-4d17-9d58-0a711c05a3a8.pdf"},{"id":97136609,"identity":"2159b9a3-a6c6-42ec-8f35-a73c1d0a6155","added_by":"auto","created_at":"2025-12-01 09:56:49","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":63798,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-7709378/v1/0b417e4934718fb824099220.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Proteasome Inhibitor-Associated PRES in Multiple Myeloma: Pharmacovigilance Evidence of Risk Signals and Concomitant Drug Interactions","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMultiple myeloma (MM), a hematologic malignancy characterized by the proliferation of clonal plasma cells and the production of monoclonal immunoglobulins, accounts for approximately 10% of all hematologic cancers[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although MM remains incurable, significant progress in diagnostic techniques and therapeutic approaches, particularly the introduction of proteasome inhibitors (PIs), has greatly improved its management[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Bortezomib, the first PI, approved in 2003, paved the way for the development of subsequent agents such as carfilzomib and ixazomib. With its optimized structure and mechanism, carfilzomib delivers an improved benefit-risk profile, while ixazomib, the first oral PI, boosts patient adherence[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Today, PI-based regimens stand as a cornerstone of MM therapy, highlighting their essential role in modern treatment approaches[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCommon adverse events (AEs) associated with PIs, such as peripheral neuropathy and infections, are well-documented, whereas complications affecting the central nervous system remain rare[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Nevertheless, a growing number of reports have linked the PIs bortezomib and carfilzomib to reversible posterior leukoencephalopathy syndrome (PRES)[\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This clinical syndrome is characterized by reversible subcortical vasogenic edema, most observed in the parietal-occipital regions on neuroimaging. PRES typically presents with acute or subacute neurological symptoms, including headache, altered mental status, seizures, and visual disturbances[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Known triggers encompass a wide range of conditions, such as hypertension, renal failure, preeclampsia/eclampsia, organ transplantation, autoimmune diseases, and the use of immunosuppressants or cytotoxic drugs. Although PRES is generally reversible with prompt removal of the triggering factor, delayed or inadequate management can lead to permanent neurological damage or life-threatening complications, including cerebral hemorrhage or ischemic infarction[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePRES is a critical safety concern for PIs, especially in MM patients with comorbidities like hypertension or renal impairment. However, the comparative risk profiles of different PIs and the role of co-administered glucocorticoids, such as dexamethasone, which can both trigger PRES and treat its associated edema, remain poorly understood[\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. To bridge this gap, our study harnesses the FDA Adverse Event Reporting System (FAERS), a global database of spontaneous adverse event reports, to explore the link between PIs and PRES. This real-world evidence aims to deepen clinical insight into PI safety.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Data Source and Preprocessing\u003c/h2\u003e\u003cp\u003eThis study utilized data from the FAERS database, covering the period from January 2004 to March 2025. Data extracted for this study encompassed demographic characteristics, drug details, AEs, onset dates, and clinical outcomes. Reports were excluded based on FDA guidelines, including those missing year or month data, where event dates preceded drug initiation, or where AEs were reported fewer than three times. Since FAERS data are anonymized and publicly accessible, this study did not require ethical review.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Outcome and Indication Identification\u003c/h2\u003e\u003cp\u003eAEs in FAERS are coded using the Medical Dictionary for Regulatory Activities (MedDRA) preferred terms (PTs). To analyze these events by specific medical conditions, Standardized MedDRA Queries (SMQs) are employed, grouping related PTs together. For increased specificity in this study, narrow SMQs, which target the event of interest more precisely, were utilized[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The indication for proteasome inhibitor (PI) exposure was defined using the narrow SMQ for plasmacytoma (SMQ code 10035484), while PRES was identified using the MedDRA PT code 10071066.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Exposure Definition\u003c/h2\u003e\u003cp\u003eThe PIs analyzed in this study included bortezomib, carfilzomib, and ixazomib. Concomitant medications comprised immunomodulatory agents (thalidomide, lenalidomide, and pomalidomide) and glucocorticoids. Glucocorticoids were classified according to the Anatomical Therapeutic Chemical (ATC) Classification System at Level 4 (H02AB, Glucocorticoids), without specifying individual agents. All the drug names were standardized to generic forms using DrugBank v5.1.9[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], with fuzzy matching applied to minimize the risk of misclassification[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Each case was independently verified by two clinical pharmacists. Only reports identifying PIs as the primary or secondary suspect drugs were included in the analysis. To validate the risk signals, tacrolimus and clopidogrel were used as positive and negative controls, respectively.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e\u003cp\u003eThis retrospective pharmacovigilance study investigates the potential association between PIs and PRES in patients with MM. Disproportionality analysis was performed using R (version 4.4.2) with the DiAna package to evaluate safety signals derived from ICSRs[\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDemographic characteristics of ICSRs were summarized using descriptive statistics, with categorical variables reported as counts and percentages, and continuous variables expressed as medians with interquartile ranges (IQRs). The Bayesian Confidence Propagation Neural Network (BCPNN) method was employed to detect safety signals, using the Information Component (IC) as the primary metric. A positive safety signal was defined as a lower bound of the 95% credible interval (IC025) greater than 0, with a minimum of three PRES cases per drug to ensure statistical reliability. The BCPNN method effectively accounts for data sparsity, providing robust estimates suitable for spontaneous reporting systems[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo assess potential confounding biases in the disproportionality analysis, we conducted stratified analyses to evaluate the robustness of the findings. These analyses accounted for key clinical variables, including the presence of comorbid hypertension (PT code: 10020772) and concomitant therapies such as angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), calcium channel blockers (CCBs), glucocorticoids, and immunomodulatory agents (IMiDs). Additional stratifications examined glucocorticoid use in the absence of hypertension and the combined use of immunomodulatory agents and glucocorticoids. This approach was designed to enhance the reliability of disproportionality analysis results by systematically addressing potential confounders and ensuring a comprehensive evaluation of their impact on the observed associations.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Descriptive Analysis\u003c/h2\u003e\u003cp\u003eFrom the first quarter of 2004 to the first quarter of 2025, a total of 131,908 adverse event reports related to PIs were identified in the FAERS database. Among these, we identified 339 reports of posterior reversible encephalopathy syndrome (PRES). After applying inclusion criteria, 315 cases were included in the final analysis, in which PIs were designated as the primary and secondary suspect drug (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eThe specific PIs implicated in these 315 cases were predominantly bortezomib, involved in 231 reports (73.3%), followed by carfilzomib in 84 reports (26.7%) and ixazomib in 11 reports (3.5%).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe baseline characteristics of the 315 patients are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. PRES was more frequently reported in females (72.26%), with a median age of 62 years (IQR, 53\u0026ndash;70). Notably, patients who developed PRES while on ixazomib were older, with a median age of 72 years (IQR, 69\u0026ndash;78). The median time to onset of PRES was 21 days (IQR, 10\u0026ndash;90). Ixazomib was associated with the longest median time to onset at 63 days (IQR, 9\u0026ndash;225). Most reports originated from Europe (53.02%) and North America (39.68%) and were submitted by physicians (40.45%).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBaseline characteristics of patients with PRES events associated with protease inhibitors\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;315\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBortezomib \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;231\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCarfilzomib \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;76\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIxazomib \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;8\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" 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colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e198(72.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e157(78.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36(52.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5(71.43)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" 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colname=\"c1\"\u003e\u003cp\u003eExpedited\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e282(89.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e215(93.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59(77.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8(100.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeriodic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28(8.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13(5.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15(19.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0(0.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eReporter\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConsumer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31(10.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27(11.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2(2.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(25.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealthcare practitioner\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68(22.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61(26.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7(9.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0(0.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e77(24.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61(26.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15(20.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1(12.50)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePharmacist\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8(2.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(0.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7(9.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0(0.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysician\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e125(40.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77(33.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43(58.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5(62.50)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eContinent\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNorth America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e125(39.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101(43.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21(27.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3(37.50)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEurope\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e167(53.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e118(51.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47(61.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(25.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16(5.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11(4.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4(5.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1(12.50)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouth America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2(0.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0(0.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2(2.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0(0.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOceania\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5(1.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(0.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2(2.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(25.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAfrica\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0(0.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0(0.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0(0.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0(0.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWt (kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62 (50.00\u0026ndash;77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (34.00\u0026ndash;70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66 (58.00\u0026ndash;79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79 (75.00\u0026ndash;89)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e228\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTime to onset\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21 (10.00\u0026ndash;90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (9.00\u0026ndash;60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (11.00-176)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e63 (9.00-225)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRole code\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e168(53.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e144(62.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23(30.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1(12.50)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147(46.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87(37.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53(69.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7(87.50)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDenote\u003c/b\u003e: data are presented as n (%) for categorical variables and median (interquartile range) for continuous variables.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Disproportionality Analysis\u003c/h2\u003e\u003cp\u003eThe BCPNN analysis revealed significant disproportionality signals for PRES associated with PIs overall (IC 2.71, 95% CI 2.52\u0026ndash;2.84). Signals were robust for bortezomib (IC 3.00, 95% CI 2.78\u0026ndash;3.16), and carfilzomib (IC 2.96, 95% CI 2.60\u0026ndash;3.22). In contrast, no significant signal was detected for ixazomib (IC 0.06, 95% CI -0.97\u0026ndash;0.75) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A sensitivity analysis using tacrolimus as positive and clopidogrel as negative controls yielded the expected strong positive and negative signals, respectively, supporting the validity of our analysis results (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBCPNN analysis of PRES risk signals associated with PIs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrug\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eD_E\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eD_nE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003enD_E\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003enD_nE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIC (95% CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePIs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e97853\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8866\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18799775\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.71 (2.52\u0026ndash;2.84)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBortezomib\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e231\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8950\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18839498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.00 (2.78\u0026ndash;3.16)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarfilzomib\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9097\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18876462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.96 (2.60\u0026ndash;3.22)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIxazomib\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21672\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18875956\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.06 (-0.97\u0026ndash;0.75)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClopidogrel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18833585\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-5.99 (-16.31\u0026ndash;-4.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTacrolimus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1275\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e108547\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7906\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18789081\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.56 (4.47\u0026ndash;4.63)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eDenote: D_E\u003c/b\u003e, the number of reports containing the drug of interest and the event of interest; \u003cb\u003eD_nE\u003c/b\u003e, reports containing the drug of interest but not the event of interest; \u003cb\u003enD_E\u003c/b\u003e, reports for other drugs containing the event of interest; and \u003cb\u003enD_nE\u003c/b\u003e, reports for other drugs not containing the event of interest. \u003cb\u003eCI\u003c/b\u003e, confidence interval.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Stratify Analysis\u003c/h2\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1 By indication\u003c/h2\u003e\u003cp\u003eTo mitigate potential confounding, we performed several stratified analyses. When the analysis was restricted to cases with an indication of plasma cell neoplasms (74.91% of PRES cases), the overall risk signal for PIs was slightly attenuated but remained significant (IC 2.21, 95% CI 2.00\u0026ndash;2.37). Specifically, bortezomib (IC 2.53, 95% CI 2.28\u0026ndash;2.72) and carfilzomib (IC 2.56, 95% CI 2.16\u0026ndash;2.85) maintained strong signals, whereas ixazomib did not reach the signal threshold (IC -0.61, 95% CI -1.82\u0026ndash; 0.19) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, Supplementary \u003cb\u003eTable S1)\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2 By disease status\u003c/h2\u003e\u003cp\u003eStratification by comorbid hypertension showed a persistent signal in both patients with hypertension (IC 2.14, 95% CI, 1.16\u0026ndash;2.80) and those without (IC 2.72, 95% CI 2.53\u0026ndash;2.86) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). A similar pattern was observed when analyses were stratified by the co-occurrence of hypertension-related adverse events (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, Supplementary Table \u003cb\u003eS2-S3)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e3.3.3 By concomitant medication\u003c/h2\u003e\u003cp\u003eCompared with non-concomitant users, concomitant ACEIs use was associated with slightly elevated PRES risk signals, mainly for bortezomib (IC 2.5, 95% CI, 1.29\u0026ndash;3.31) and carfilzomib (IC 3.12, 95% CI, 1.82\u0026ndash;3.98); no signals were observed for ixazomib (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, Supplementary Table \u003cb\u003eS4)\u003c/b\u003e. Conversely, concomitant ARBs or CCBs use showed a trend toward lower risk signals. Due to the small number of cases with concomitant ARBs use, no statistically significant differences were observed. Concomitant CCBs use was associated with reduced IC values for bortezomib (IC 2.21, 95% CI, 1.19\u0026ndash;2.91) and carfilzomib (IC 2.73, 95% CI, 1.52\u0026ndash;3.53) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, Supplementary Table \u003cb\u003eS5-S6)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFurther analyses explored the impact of concomitant medications. Concomitant use of IMiDs had a minimal effect on the PRES signal associated with PIs (IC 2.67, 95% CI 2.42\u0026ndash;2.85) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, Supplementary Tables \u003cb\u003eS8\u003c/b\u003e). Strikingly, concomitant glucocorticoid use was associated with a markedly lower PRES signal (IC 0.52, 95% CI 0.30\u0026ndash;0.67) compared to the unstratified analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). This attenuating effect was consistent across individual PIs, with bortezomib (IC 0.69, 95% CI 0.43\u0026ndash;0.88) and carfilzomib (IC 1.07, 95% CI 0.67\u0026ndash;1.36) retaining significance, albeit at a reduced level (Supplementary Table \u003cb\u003eS7\u003c/b\u003e). This pattern also held in multi-stratified analyses, where the signal remained attenuated in patients receiving glucocorticoids alongside IMiDs (IC 1.61, 95% CI 1.29\u0026ndash;1.84) or in patients without hypertension (IC 0.50, 95% CI 0.28\u0026ndash;0.67) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, Supplementary Tables \u003cb\u003eS9-S10\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Temporal Trend Analysis\u003c/h2\u003e\u003cp\u003eThe temporal analysis of PRES risk signals from 2004 to 2025 showed an increasing trend in the early years, starting from a null signal in 2004 (IC -0.02, 95% CI -10.34\u0026ndash;1.96) and peaking in 2015 (IC 2.94, 95% CI 2.64\u0026ndash;3.17). Subsequently, the signal strength stabilized, with IC values fluctuating between 2.3 and 2.78 through the first quarter of 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Clinical Outcomes\u003c/h2\u003e\u003cp\u003eAll 315 PIs-associated PRES events were classified as serious. The outcomes including death (23.81%), life-threatening conditions (17.46%), hospitalization (24.13%), disability (2.22%), and other serious AEs (32.38%). In total, 41.27% of cases resulted in death or a life-threatening event. Carfilzomib was associated with the highest proportion of death/life-threatening outcomes (53.95%), followed by bortezomib (37.66%) and ixazomib (25.00%) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical outcomes of PRES events associated with protease inhibitors\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;315\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBortezomib \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;231\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCarfilzomib \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;76\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIxazomib \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;8\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeath\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75 (23.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (25.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 (19.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 (0.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLife threatening\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55 (17.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (11.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26 (34.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (25.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDisability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (2.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (2.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 (0.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHospitalization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e76 (24.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (22.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20 (26.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 (50.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther serious\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e102 (32.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86 (37.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (18.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (25.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003ePIs remain a cornerstone of MM therapy across all treatment phases[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. While generally well tolerated, their use can be complicated by rare but serious adverse events (AEs) such as PRES. In this large pharmacovigilance analysis, 315 PI-associated PRES cases were identified, predominantly involving bortezomib (73.3%) and carfilzomib (24.1%). These reporting patterns likely reflect approval timelines and usage prevalence, with bortezomib\u0026rsquo;s broader application across treatment settings accounting for its predominance[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur demographic findings are consistent with prior reports. The predominance of female patients (72.26%) supports evidence of sex-specific susceptibility to PRES, potentially mediated by hormonal influences or structural differences in neuronal architecture[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The overall median onset of 21 days highlights early treatment as a critical risk window[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], while the notably longer onset observed with ixazomib (63 days) represents a novel signal that warrants further study.\u003c/p\u003e\u003cp\u003eDisproportionality analysis confirmed significant PRES signals for bortezomib and carfilzomib, but not for ixazomib. This disparity may relate to differences in pharmacological properties. Carfilzomib\u0026rsquo;s irreversible β5 inhibition, with additional β2 activity at higher concentrations[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], likely contributes to endothelial dysfunction by suppressing NF-κB activation and VEGF transcription, thereby destabilizing the blood\u0026ndash;brain barrier[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Bortezomib\u0026rsquo;s off-target inhibition of neuronal proteases may further predispose to autonomic dysfunction, vasoconstriction, and edema, mechanisms not shared by carfilzomib[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The absence of a signal for ixazomib may reflect both its distinct pharmacological profile and the smaller number of reports, limiting statistical power.\u003c/p\u003e\u003cp\u003eHypertension, a classical risk factor for PRES, revealed a paradoxical associated in out dataset: patients with pre-existing hypertension receiving PIs exhibited a lower risk of PRES compared to those without a prior history of hypertension. This result does not imply a protective effect of hypertension per se, but may instead relate to adaptations in cerebral autoregulation. Chronic hypertension induces arteriolar smooth muscle hypertrophy, vascular wall thickening, and remodeling, allowing cerebral vessels to adapt to higher perfusion pressures over time[\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Consequently, such patients may be less prone to surpassing the upper limit of cerebral autoregulation during acute blood pressure fluctuations[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], conferring greater tolerance to PI-induced endothelial injury and hemodynamic stress. This mechanistic interpretation also helps explain why approximately 50% of hypertensive patients who develop PRES demonstrate mean arterial pressures exceeding the autoregulatory threshold (\u0026ge;\u0026thinsp;140\u0026ndash;150 mmHg)[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Moreover, patients with established hypertension are commonly under antihypertensive management prior to PI initiation. This prophylactic intervention may mitigate PI-related hypertensive crises, thereby indirectly reducing PRES risk. Interestingly, even among PRES cases, those with concurrent hypertension-related AEs showed slightly reduced risk, possibly due to earlier recognition and more aggressive management of hypertension compared to PRES itself.\u003c/p\u003e\u003cp\u003eIn the evaluation of potential confounding by antihypertensive medications, we observed divergent effects across different classes. Specifically, ACEIs, ARBs, and CCBs exhibited distinct risk signals for PRES, with ACEIs showing an opposite trend compared to ARBs and CCBs. While both ACEIs and ARBs target the renin\u0026ndash;angiotensin system, underlying mechanistic differences may explain these divergent associations. ACEIs inhibit angiotensin-converting enzyme, thereby reducing angiotensin II formation but also preventing bradykinin degradation, which leads to elevated bradykinin levels. As a potent vasodilator, bradykinin can increase vascular permeability[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Although the pathophysiology of PRES is not fully elucidated, key hypotheses involve reduced transcription of endothelial trophic factors such as vascular endothelial growth factor, culminating in endothelial dysfunction, vasospasm, and blood\u0026ndash;brain barrier disruption[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In the setting of PI-induced endothelial injury, ACEI-mediated bradykinin accumulation may further enhance vascular permeability and promote PRES onset. By contrast, ARBs selectively block the binding of angiotensin II to Ang II type 1 receptors without impacting bradykinin metabolism[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], providing a potential rationale for the opposing risk trends between ACEIs and ARBs. CCBs, through inhibition of calcium influx into vascular smooth muscle cells, promote vasodilation, alleviate cerebrovascular vasospasm, and stabilize endothelial function[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], thereby mitigating several pathological pathways implicated in PI-associated PRES. Aligning with this mechanism, our data indicated that concomitant CCB use was linked to a substantially reduced PRES risk. Nevertheless, these mechanistic interpretations are hypothesis-generating and warrant further validation; thus, the current findings should be interpreted cautiously.\u003c/p\u003e\u003cp\u003eFurther combination analysis revealed that the concomitant use of glucocorticoids was associated with a markedly attenuated PRES signal (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Prior studies have suggested that glucocorticoids may induce or exacerbate hypertension, thereby precipitating PRES, consistent with the hyperperfusion theory[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This theory proposes that acute elevations in blood pressure can exceed cerebral autoregulatory capacity, resulting in hyperperfusion, endothelial damage, blood\u0026ndash;brain barrier disruption, and subsequent vasogenic edema with associated clinical features [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, our results suggest that hypertension and hyperperfusion alone are insufficient to fully explain the observed PRES risk. As a cornerstone of standard therapy for multiple myeloma, glucocorticoids not only exert direct antitumor and immunomodulatory effects but also possess potent anti-inflammatory and endothelium-stabilizing properties[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. These protective actions may counterbalance PI-induced vascular injury and vasogenic edema, thereby reducing the overall risk of PRES. This observation was consistently evident in our data, suggesting that PRES pathobiology is unlikely to be attributable solely to hemodynamic mechanisms and more likely arises from the interplay of multiple biological pathways.\u003c/p\u003e\u003cp\u003eAll PI-associated PRES cases were classified as serious, with 41.27% resulting in death or life-threatening outcomes, likely compounded by the severity of underlying MM. Carfilzomib exhibited the highest rate of these severe outcomes (53.95%), possibly due to its increased potency or patient selection bias. Prompt detection and management, including PI discontinuation or Symptomatic treatment, are crucial, as PRES is generally reversible, although delays can lead to irreversible neurological damage[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e"},{"header":"5. Limitations","content":"\u003cp\u003eThe FAERS database, as a spontaneous reporting system, has inherent limitations that constrain the ability to establish causal relationships. Key challenges include reporting biases, incomplete data, and unmeasured confounding factors, such as genetic predispositions, comorbidities, concomitant medications, and interindividual variability, which may influence the observed associations. Although stratified analyses were undertaken to mitigate confounding from comorbid hypertension and concomitant therapies, including ACEIs, ARBs, CCBs, glucocorticoids, and immunomodulatory agents, residual confounding from unmeasured covariates cannot be excluded. Furthermore, given the limited number of PRES cases, multivariable logistic regression could not be performed to adjust for multiple risk factors simultaneously, warranting cautious interpretation of the findings. Notably, while stratified analyses suggested a potential reduction in PRES risk associated with glucocorticoid use, this statistical association does not establish causality and requires validation through methodologies beyond pharmacovigilance, such as prospective clinical studies. In addition, the spontaneous nature of FAERS data precludes estimation of PRES incidence in the general population, thereby limiting the generalizability of these observations.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis FAERS-based disproportionality analysis reveals the risk profile of PRES associated with PIs, with bortezomib and carfilzomib showing significant pharmacovigilance signals, particularly among middle-aged and older female patients. Concomitant glucocorticoid use was associated with a significantly attenuated risk of PRES, however further mechanistic and epidemiological validation is required. While PRES is often reversible, the risk of serious adverse events remains non-negligible. Clinicians should remain vigilant for PRES during PI therapy, especially in the early treatment phase, and implement timely preventive and therapeutic measures when indicated.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Changning District Medical and Health Scientific Research Special Project of Shanghai (Grant ID. CNKW2024Y20) , Hunan Provincial Natural Science Foundation Joint Fund (Grant ID 2022JJ80066), the Young Medical Talents Training Program of the Pudong Health Committee of Shanghai (Grant ID. PWRq2022-28) and the Clinical Pharmacy Key Specialized Subject Construction Project of Pudong Hospital Affiliated to Fudan University (Grant ID. Tszk2020-05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data included in this study were obtained from the FAERS database, which is publicly available and anonymous, and therefore the study was exempt from approval by the institutional ethics committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatement of Human and Animal Rights\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article does not contain any studies with human or animal subjects performed by any of authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data used and/or analyzed in this study are accessible from the FAERS Quarterly Data Extract Files, available at https://fis.fda.gov/extensions/FPD-QDE-FAERS/FPD-QDE-FAERS.html.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e Not applicable.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u003cstrong\u003eAuthor contributions\u003cbr\u003e\u0026nbsp;\u003c/strong\u003eP.G. was involved in the concept and design of the study, data collection and analysis, and drafting and critical review of the manuscript. H.S. finalized and provided suggestions to improve the manuscript. B.T. were involved in data collection, data analysis and interpretation, and critical review of the manuscript. H.W. was involved in conceived, and designed the study, critically reviewed the manuscript, and prepared the final version for publication. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRajkumar, S. V. Multiple myeloma: 2024 update on diagnosis, risk-stratification, and management. \u003cem\u003eAm J Hematol\u003c/em\u003e \u003cstrong\u003e99,\u003c/strong\u003e 1802\u0026ndash;1824 (2024).\u003c/li\u003e\n\u003cli\u003eDonk, N. W. C. J. van de, Pawlyn, C. \u0026amp; Yong, K. L. Multiple myeloma. \u003cem\u003eThe Lancet\u003c/em\u003e \u003cstrong\u003e397,\u003c/strong\u003e 410\u0026ndash;427 (2021).\u003c/li\u003e\n\u003cli\u003eJakubowiak, A. J. 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Glucocorticoids in multiple myeloma: past, present, and future. \u003cem\u003eAnn Hematol\u003c/em\u003e \u003cstrong\u003e98,\u003c/strong\u003e 19\u0026ndash;28 (2019).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Proteasome inhibitors, reversible posterior leukoencephalopathy syndrome, FAERS, Pharmacovigilance, Glucocorticoid","lastPublishedDoi":"10.21203/rs.3.rs-7709378/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7709378/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eProteasome inhibitors (PIs), essential for multiple myeloma (MM) therapy, are associated with posterior reversible encephalopathy syndrome (PRES), a rare but serious neurotoxic event. Using the FDA Adverse Event Reporting System (2004–2025), we conducted a disproportionality analysis with Bayesian Confidence Propagation Neural Network to assess PI-associated PRES risk and the impact of concomitant medications. Among 315 cases, bortezomib (73.3%) and carfilzomib (24.1%) were predominant, mainly affecting females (72.3%), median age 62, with a median onset of 21 days. Significant risk signals were detected for PIs overall (IC 2.71, 95% CI 2.52–2.84), driven by bortezomib (IC 3.00, 95% CI 2.78–3.16) and carfilzomib (IC 2.96, 95% CI 2.60–3.22). In stratified analyses of concomitant antihypertensives, ACEIs increased risk (IC 2.81, 95% CI 1.94–3.42), while ARBs (IC 1.90, 95% CI 0.34–2.89) and CCBs (IC 2.24, 95% CI 1.47–2.77) suggested risk reduction. Concomitant glucocorticoids significantly lowered risk for bortezomib (IC 0.67, 95% CI 0.41–0.86) and carfilzomib (IC 1.07, 95% CI 0.67–1.36). All PRES cases were serious; carfilzomib had a 53.9% rate of death or life-threatening outcomes. These findings underscore the need for early clinical vigilance during PI therapy and suggest glucocorticoids mitigate PRES risk, warranting further validation.\u003c/p\u003e","manuscriptTitle":"Proteasome Inhibitor-Associated PRES in Multiple Myeloma: Pharmacovigilance Evidence of Risk Signals and Concomitant Drug Interactions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-28 07:12:55","doi":"10.21203/rs.3.rs-7709378/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"79d17127-2cea-4820-9efc-bea3de57dc6d","owner":[],"postedDate":"November 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58515376,"name":"Biological sciences/Drug discovery"},{"id":58515377,"name":"Health sciences/Medical research"},{"id":58515378,"name":"Health sciences/Neurology"},{"id":58515379,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2025-12-05T18:38:32+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-28 07:12:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7709378","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7709378","identity":"rs-7709378","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}