Analysis Of Clinical Trial Data Research Articles

Immune Checkpoint Inhibitors and the Risk of Cardiovascular Adverse Events: A Pooled Clinical Trial Database Analysis

Introduction Immune checkpoint inhibitors (ICIs) are a highly effective class of cancer immunotherapy, but their use has been limited by immune-related adverse events (irAEs) affecting various organ systems. Recent real-world studies have shown higher incidence rates of cardiovascular (CV) events in patients with cancer who are treated with ICIs compared to those treated with conventional chemotherapy (Laenens et al, J Clin Oncol 2022). Studies suggest that the underlying mechanism involves a pro-inflammatory response causing unintended vascular compromise, but there have been limited data on ICI-related cardiotoxicity across pooled datasets. Given that ICIs have been applied to lung cancer treatment in recent years, we use it as an example indication to study clinical trial (CT) patients with advanced non-small cell lung cancer (aNSCLC) randomized to either a first-line (1L) ICI-containing regimen or to 1L chemotherapy alone (chemo) to evaluate for potential differential rates of CV events. Methods We pooled patient-level, phase 3 CT data on aNSCLC patients treated with ICI or chemo from the Medidata Enterprise Data Store. Treatment assignment was the main variable of interest. The primary outcome was a composite CV event (acute coronary syndrome, heart failure, stroke, transient ischemic attack), occurring between the start of study treatment (index date) and 30 days following the last dose of study treatment. Incidence rates and the relative hazard of a CV event by treatment assignment were estimated. Additionally, the risk of CV event with non-CV death treated as a competing risk was estimated using the Fine-Gray model. In a post-hoc subgroup analysis we explored the impact of treatment assignment on overall survival (OS) among patients with and without baseline vascular disease. OS was defined as the time from the index date until the date of death (all-cause). Patients alive at the end of CT follow-up were censored. Results A total of 1862 patients were included in this analysis, with 1128 (60.6%) randomized to ICI and 734 (39.4%) to chemo. Baseline demographics and comorbidities were balanced across treatment groups. Forty-six (2.5%) patients experienced at least 1 CV event. The incidence rate of CV events was 2.48 times (95% CI: 1.10, 6.57) higher among patients treated with ICI compared to chemo. The unadjusted hazard of composite CV event, estimated using Kaplan-Meier, differed significantly by treatment assignment (p= 0.008) ( Figure 1). After adjusting for baseline demographics and comorbidities, the hazard of a composite CV event remained higher for patients treated with ICI compared to chemo (aHR 2.68, 95% CI: 1.19-6.06) ( Table 1). Baseline vascular disease history (N=359; 19.3%) was also associated with an increased hazard of a CV event (aHR: 2.40; 95% CI: 1.25-4.60). Similar results were found in the competing risk analysis. In the subgroup analysis, patients without baseline vascular disease history had a significant OS benefit from an ICI compared to chemo (aHR 0.84, 95% CI: 0.75-0.95), whereas patients with baseline vascular disease did not (aHR 1.00, 95% CI: 0.78-1.27). Conclusion Though ICIs enhance the body's immune responses against cancer, it is important to study the associated effect of irAEs on off-target tissues. These analyses of historical CT data suggest a positive association between 1L treatment of aNSCLC with ICI and subsequent composite CV events compared with chemo alone. Given the high prevalence of morbidity among patients with lung cancer, the use of concomitant cardioprotective therapies may be an important consideration when treating cancer populations with ICIs. Pooling CT data increases the power to detect clinically important differences in rare toxicities and may inform future research and patient-physician decision-making regarding the suitability of ICI use in aNSCLC treatment. Furthermore, this research highlights the potential clinical utility of drug repurposing: expanding the use of drugs approved to treat CV events and exploring their use in patients with vascular disease who are also being treated with ICIs. As cell-mediated immune responses play a key role in the potential CV effects of ICI treatments, future studies are needed to define the underlying mechanisms of ICI-related dysregulation of the immune system to better monitor patients and improve clinical outcomes in the context of immunotherapy for aNSCLC and other cancer types.

Bayesian second-order sensitivity of longitudinal inferences to non-ignorability: an application to antidepressant clinical trial data.

Incomplete data is a prevalent complication in longitudinal studies due to individuals' drop-out before intended completion time. Currently available methods via commercial software for analyzing incomplete longitudinal data at best rely on the ignorability of the drop-outs. If the underlying missing mechanism was non-ignorable, potential bias arises in the statistical inferences. To remove the bias when the drop-out is non-ignorable, joint complete-data and drop-out models have been proposed which involve computational difficulties and untestable assumptions. Since the critical ignorability assumption is unverifiable based on the observed part of the sample, some local sensitivity indices have been proposed in the literature. Specifically, Eftekhari Mahabadi (Second-order local sensitivity to non-ignorability in Bayesian inferences. Stat Med 2018;59:55-95) proposed a second-order local sensitivity tool for Bayesian analysis of cross-sectional studies and show its better performance for handling bias compared with the first-order ones. In this paper, we aim to extend this index for the Bayesian sensitivity analysis of normal longitudinal studies with drop-outs. The index is driven based on a selection model for the drop-out mechanism and a Bayesian linear mixed-effect complete-data model. The presented formulas are calculated using the posterior estimation and draws from the simpler ignorable model. The method is illustrated via some simulation studies and sensitivity analysis of a real antidepressant clinical trial data. Overall, the numerical analysis showed that when repeated outcomes are subject to missingness, regression coefficient estimates are nearly approximated well by a linear function in the neighbourhood of MAR model, but there are a considerable amount of second-order sensitivity for the error term and random effect variances in Bayesian linear mixed-effect model framework.

Abstract 14354: The Impact of Riociguat in Pulmonary Arterial Hypertension Patients With Comorbidities Included in Interventional Clinical Trials

Background: The number of pulmonary arterial hypertension (PAH) patients with comorbidities is increasing, however, there are few published data from these patients in PAH therapy clinical trials meaning that evidence-based treatment recommendations have not been made. Aim: This post-hoc analysis of pooled riociguat clinical trial data assessed the impact of riociguat in patients with PAH and comorbidities. Methods: All interventional studies of riociguat in patients with PAH (PATENT-1, PATENT PLUS, RESPITE, MOTION, REPLACE, and the Phase II study) were included in the pooled analysis. The safety of riociguat and placebo was assessed in patients with ≥3 comorbidities vs <3 comorbidities. Safety was assessed by adverse events (AEs) and serious AEs (SAEs). Comorbidities included: age ≥65 years, body mass index ≥30 kg/m 2 , history of essential hypertension, diabetes mellitus, history of significant coronary artery disease, and atrial fibrillation. Results: The 609 patients who received riociguat and 132 patients who received placebo in the main phase clinical trials of riociguat were included in the analysis. Of these, 113 patients (19%) in the riociguat group and 21 patients (16%) in the placebo group had ≥3 comorbidities. In both treatment groups, AE rates were higher in patients with ≥3 comorbidities vs <3 comorbidities (riociguat 93% vs 86%; placebo 95% vs 84%); with most AEs being mild or moderate. Study drug-related AE rates were similar in both treatment groups and in patients with ≥3 comorbidities vs <3 comorbidities (riociguat 54% vs 56%; placebo 52% vs 52%). SAE rates were higher in riociguat-treated patients with ≥3 comorbidities vs <3 comorbidities (25% vs 12%); of these, 4% and 3% were study drug-related, respectively. In patients with ≥3 comorbidities, study drug-related SAE rates were higher in those receiving placebo vs riociguat (10% vs 4%). AE rates leading to study drug discontinuation were higher in patients with ≥3 comorbidities vs <3 comorbidities (riociguat 6% vs 4%; placebo 10% vs 6%), whereas AE rates leading to death were similar in both groups (riociguat 2% vs 1%; placebo 0% vs 4%). Conclusion: These data suggest that riociguat had an acceptable tolerability profile in PAH patients with comorbidities with most AEs being mild or moderate.

Graft Failure After Coronary Artery Bypass Grafting and Its Association With Patient Characteristics and Clinical Events: A Pooled Individual Patient Data Analysis of Clinical Trials With Imaging Follow-Up.

Graft patency is the postulated mechanism for the benefits of coronary artery bypass grafting (CABG). However, systematic graft imaging assessment after CABG is rare, and there is a lack of contemporary data on the factors associated with graft failure and on the association between graft failure and clinical events after CABG. We pooled individual patient data from randomized clinical trials with systematic CABG graft imaging to assess the incidence of graft failure and its association with clinical risk factors. The primary outcome was the composite of myocardial infarction or repeat revascularization occurring after CABG and before imaging. A 2-stage meta-analytic approach was used to evaluate the association between graft failure and the primary outcome. We also assessed the association between graft failure and myocardial infarction, repeat revascularization, or all-cause death occurring after imaging. Seven trials were included comprising 4413 patients (mean age, 64.4±9.1 years; 777 [17.6%] women; 3636 [82.4%] men) and 13 163 grafts (8740 saphenous vein grafts and 4423 arterial grafts). The median time to imaging was 1.02 years (Q1;Q3: 1.00;1.03). Graft failure occurred in 1487 (33.7%) patients and in 2190 (16.6%) grafts. Age (adjusted odds ratio [aOR], 1.08 [per 10-year increment] [95% CI, 1.01-1.15]; P=0.03), female sex (aOR, 1.27 [95% CI, 1.08-1.50]; P=0.004), and smoking (aOR, 1.20 [95% CI, 1.04-1.38]; P=0.01) were independently associated with graft failure, whereas statins were associated with a protective effect (aOR, 0.74 [95% CI, 0.63-0.88]; P<0.001). Graft failure was associated with an increased risk of myocardial infarction or repeat revascularization occurring between CABG and imaging assessment (8.0% in patients with graft failure versus 1.7% in patients without graft failure; aOR, 3.98 [95% CI, 3.54-4.47]; P<0.001). Graft failure was also associated with an increased risk of myocardial infarction or repeat revascularization occurring after imaging (7.8% versus 2.0%; aOR, 2.59 [95% CI, 1.86-3.62]; P<0.001). All-cause death after imaging occurred more frequently in patients with graft failure compared with patients without graft failure (11.0% versus 2.1%; aOR, 2.79 [95% CI, 2.01-3.89]; P<0.001). In contemporary practice, graft failure remains common among patients undergoing CABG and is strongly associated with adverse cardiac events.

Chinese Clinical Trial Registry 13-year data collection and analysis: geographic distribution, financial support, research phase, duration, and disease categories.

To evaluate the current status of trial registration on the Chinese Clinical Trial Registry (ChiCTR). In this descriptive study, a multi-dimensional grouping analysis was conducted to estimate trends in the annual trial registration, geographical distribution, sources of funding, targeted diseases, and trial subtypes. We have analyzed all clinical trial records (over 30,000) registered on the Chinese Clinical Trial Registry (ChiCTR) from 2007 to 2020 executed in China. The main outcome was the baseline characteristics of registered trials. These trials were categorized and analyzed based on geographical distribution, year of implementation, disease type, resource and funding type, trial duration, trial phase, and the type of experimental approach. From 2008 to 2017, a consistent upward trend in clinical trial registrations was observed, showing an average annual growth rate of 29.2%. The most significant year-on-year (yoy%) growth in registrations occurred in 2014 (62%) and 2018 (68.5%). Public funding represented the predominant source of funding in the Chinese healthcare system. The top five ChiCTR registration sites for all disease types were highly populated urban regions of China, including Shanghai (5,658 trials, 18%), Beijing (5,127 trials, 16%), Guangdong (3,612 trials, 11%), Sichuan (2,448 trials, 8%), and Jiangsu (2,196 trials, 7%). Trials targeting neoplastic diseases accounted for the largest portion of registrations, followed by cardio/cerebrovascular disease (CCVD) and orthopedic diseases-related trials. The largest proportions of registration trial duration were 1-2 years, less than 1 year, and 2-3 years (at 27.36, 26.71, and 22.46%). In the case of the research phase, the top three types of all the registered trials are exploratory research, post-marketing drugs, and clinical trials of new therapeutic technology. Oncological and cardiovascular diseases receive the highest share of national public funding for medical clinical trial-based research in China. Publicly funded trials represent a major segment of the ChiCTR registry, indicating the dominating role of public governance in this health research sector. Furthermore, the growing number of analyzed records reflect the escalation of clinical research activities in China. The tendency to distribute funding resources toward exceedingly populated areas with the highest incidence of oncological and cardiovascular diseases reveals an aim to reduce the dominating disease burden in the urban conglomerates in China.

Reattribution to Mind-Brain Processes and Recovery From Chronic Back Pain

ImportanceIn primary chronic back pain (CBP), the belief that pain indicates tissue damage is both inaccurate and unhelpful. Reattributing pain to mind or brain processes may support recovery.ObjectivesTo test whether the reattribution of pain to mind or brain processes was associated with pain relief in pain reprocessing therapy (PRT) and to validate natural language–based tools for measuring patients’ symptom attributions.Design, Setting, and ParticipantsThis secondary analysis of clinical trial data analyzed natural language data from patients with primary CBP randomized to PRT, placebo injection control, or usual care control groups and treated in a US university research setting. Eligible participants were adults aged 21 to 70 years with CBP recruited from the community. Enrollment extended from 2017 to 2018, with the current analyses conducted from 2020 to 2022.InterventionsPRT included cognitive, behavioral, and somatic techniques to support reattributing pain to nondangerous, reversible mind or brain causes. Subcutaneous placebo injection and usual care were hypothesized not to affect pain attributions.Main Outcomes and MeasuresAt pretreatment and posttreatment, participants listed their top 3 perceived causes of pain in their own words (eg, football injury, bad posture, stress); pain intensity was measured as last-week average pain (0 to 10 rating, with 0 indicating no pain and 10 indicating greatest pain). The number of attributions categorized by masked coders as reflecting mind or brain processes were summed to yield mind-brain attribution scores (range, 0-3). An automated scoring algorithm was developed and benchmarked against human coder–derived scores. A data-driven natural language processing (NLP) algorithm identified the dimensional structure of pain attributions.ResultsWe enrolled 151 adults (81 female [54%], 134 White [89%], mean [SD] age, 41.1 [15.6] years) reporting moderate severity CBP (mean [SD] intensity, 4.10 [1.26]; mean [SD] duration, 10.0 [8.9] years). At pretreatment, 41 attributions (10%) were categorized as mind- or brain-related across intervention conditions. PRT led to significant increases in mind- or brain-related attributions, with 71 posttreatment attributions (51%) in the PRT condition categorized as mind- or brain-related, as compared with 22 (8%) in control conditions (mind-brain attribution scores: PRT vs placebo, g = 1.95 [95% CI, 1.45-2.47]; PRT vs usual care, g = 2.06 [95% CI, 1.57-2.60]). Consistent with hypothesized PRT mechanisms, increases in mind-brain attribution score were associated with reductions in pain intensity at posttreatment (standardized β = −0.25; t127 = −2.06; P = .04) and mediated the effects of PRT vs control on 1-year follow-up pain intensity (β = −0.35 [95% CI, −0.07 to −0.63]; P = .05). The automated word-counting algorithm and human coder-derived scores achieved moderate and substantial agreement at pretreatment and posttreatment (Cohen κ = 0.42 and 0.68, respectively). The data-driven NLP algorithm identified a principal dimension of mind and brain vs biomechanical attributions, converging with hypothesis-driven analyses.Conclusions and RelevanceIn this secondary analysis of a randomized trial, PRT increased attribution of primary CBP to mind- or brain-related causes. Increased mind-brain attribution was associated with reductions in pain intensity.

Glycated serum proteins and albumin but not glycated albumin show negative correlation with BMI in an overweight/obese, diabetic population from the United States

Background and aimsMultiple previously published studies have shown a weak to medium, negative correlation between BMI and glycated albumin (GA). However, many of these studies were in populations with a narrow range of BMI. It is unknown whether this trend exists if a wider BMI range is used. This is an important question for proper interpretation of GA levels in obese populations.Materials and methods:A retrospective analysis of clinical trial data (NCT02519309) was performed. After appropriate exclusions, 334 subjects remained. These included 73.7% with type 2 diabetes (T2D) diagnosis and 26.3% with prediabetes. BMI ranged from 24.8–86.9 kg/m2. Laboratory data were measured in a CLIA-certified laboratory using commercially available, automated methods.Results:No significant, negative correlation was seen between GA and BMI. However, individual components (glycated serum proteins and albumin) as well as the GA/HbA1c ratio show a weak, negative correlation with BMI for all subjects and those with T2D. The strongest negative correlation was with albumin. Examination by traditional BMI subgroups also showed statistically significant differences for those with T2D, but not for the prediabetic cohort. Correlations between BMI and C-reactive protein were similar in those with diabetes and prediabetes; however, correlation between BMI and insulin was stronger in those with diabetes.Conclusion:Negative correlations between BMI and albumin or BMI and glycated serum proteins persist in diabetic populations that are obese and overweight, even when a statistically significant negative correlation is not observed between BMI and GA. Inflammation or insulin-mediated changes in protein synthesis could be contributors to these negative correlations, but BMI-related changes to the glomerulus could also affect clearance of albumin or glycated proteins and should be examined.

Heterogeneity of treatment responses in rheumatoid arthritis using group based trajectory models: secondary analysis of clinical trial data

BackgroundTraditionally rheumatoid arthritis (RA) trials classify patients as responders and non-responders; they ignore the potential range of treatment responses. Group Based Trajectory Models (GBTMs) provide a more refined approach. They identify patient subgroups with similar outcome trajectories. We used GBTMs to classify patients into subgroups of varying responses and explore factors associated with different responses to intensive treatment in a secondary analysis of intensive treatment in the TITRATE clinical trial.MethodsThe TITRATE trial enrolled 335 patients with RA: 168 patients were randomised to receive intensive management, which comprised monthly assessments including measures of the disease activity score for 28 joints (DAS28), treatment escalation when patients were not responding sufficiently and psychosocial support; 163 of these patients completed the trial. We applied GBTMs to monthly DAS28 scores over one year to these patients who had received intensive management. The control group had standard care and were assessed every 6 months; they had too few DAS28 scores for applying GBTMs.ResultsGBTMs identified three distinct trajectories in the patients receiving intensive management: good (n = 40), moderate (n = 76) and poor (n = 47) responders. Baseline body mass index (BMI), disability, fatigue and depression levels were significantly different between trajectory groups. Few (10%) good responders were obese, compared to 38% of moderate, and 43% of poor responders (P = 0.002). Few (8%) good responders had depression, compared to 14% moderate responders, and 38% poor responders (P < 0.001). The key difference in treatments was using high-cost biologics, used in only 5% of good responders but 30% of moderate and 51% of poor responders (P < 0.001). Most good responders had endpoint remissions and low disability, pain, and fatigue scores; few poor responders achieved any favourable outcomes.ConclusionGBTMs identified three trajectories of disease activity progression in patients receiving intensive management for moderately active RA. Baseline variables like obesity and depression predicted different treatment responses. Few good responders needed biologic drugs; they responded to conventional DMARDs alone. GBTMs have the potential to facilitate precision medicine enabling patient-oriented treatment strategies based on key characteristics.RegistrationTITRATE Trial ISRCTN 70160382.

Pre-vaccination monocyte-to-lymphocyte ratio as a biomarker for the efficacy of malaria candidate vaccines: A subgroup analysis of pooled clinical trial data.

Pre-vaccination monocyte-to-lymphocyte ratio was previously suggested as a marker for malaria vaccine effectiveness. We investigated the potential of this cell ratio as a marker for malaria vaccine efficacy and effectiveness. Effectiveness was investigated by using clinical malaria endpoint, and efficacy was investigated by using surrogate endpoints of Plasmodium falciparum prepatent period, parasite density, and multiplication rates in a controlled human malaria infection trial (CHMI). We evaluated the correlation between monocyte-to-lymphocyte ratio and RTS,S vaccine effectiveness using Cox regression modeling with clinical malaria as the primary endpoint. Of the 1704 participants in the RTS,S field trial, data on monocyte-to-lymphocyte ratio was available for 842 participants, of whom our analyses were restricted. We further used Spearman Correlations and Cox regression modeling to evaluate the correlation between monocyte-to-lymphocyte ratio and Whole Sporozoite malaria vaccine efficacy using the surrogate endpoints. Of the 97 participants in the controlled human malaria infection vaccine trials, hematology and parasitology information were available for 82 participants, of whom our analyses were restricted. The unadjusted efficacy of RTS,S malaria vaccine was 54% (95% CI: 37%-66%, p <0.001). No correlation was observed between monocyte-to-lymphocyte ratio and RTS,S vaccine efficacy (Hazard Rate (HR):0.90, 95%CI:0.45-1.80; p = 0.77). The unadjusted efficacy of Whole Sporozoite malaria vaccine in the appended dataset was 17.6% (95%CI:10%-28.5%, p<0.001). No association between monocyte-to-lymphocyte ratio and the Whole Sporozoite malaria vaccine was found against either the prepatent period (HR = 1.16; 95%CI:0.51-2.62, p = 0.72), parasite density (rho = 0.004, p = 0.97) or multiplication rates (rho = 0.031, p = 0.80). Monocyte-to-lymphocyte ratio alone may not be an adequate marker for malaria vaccine efficacy. Further investigations on immune correlates and underlying mechanisms of immune protection against malaria could provide a clearer explanation of the differences between those protected in comparison with those not protected against malaria by vaccination.

Artificial Intelligence and Machine Learning in Pharmacological Research: Bridging the Gap Between Data and Drug Discovery.

Artificial intelligence (AI) has transformed pharmacological research through machine learning, deep learning, and natural language processing. These advancements have greatly influenced drug discovery, development, and precision medicine. AI algorithms analyze vast biomedical data identifying potential drug targets, predicting efficacy, and optimizing lead compounds. AI has diverse applications in pharmacological research, including target identification, drug repurposing, virtual screening, de novo drug design, toxicity prediction, and personalized medicine. AI improves patient selection, trial design, and real-time data analysis in clinical trials, leading to enhanced safety and efficacy outcomes. Post-marketing surveillance utilizes AI-based systems to monitor adverse events, detect drug interactions, and support pharmacovigilance efforts. Machine learning models extract patterns from complex datasets, enabling accurate predictions and informed decision-making, thus accelerating drug discovery. Deep learning, specifically convolutional neural networks (CNN), excels in image analysis, aiding biomarker identification and optimizing drug formulation. Natural language processing facilitates the mining and analysis of scientific literature, unlocking valuable insights and information. However, the adoption of AI in pharmacological research raises ethical considerations. Ensuring data privacy and security, addressing algorithm bias and transparency, obtaining informed consent, and maintaining human oversight in decision-making are crucial ethical concerns. The responsible deployment of AI necessitates robust frameworks and regulations. The future of AI in pharmacological research is promising, with integration with emerging technologies like genomics, proteomics, and metabolomics offering the potential for personalized medicine and targeted therapies. Collaboration among academia, industry, and regulatory bodies is essential for the ethical implementation of AI in drug discovery and development. Continuous research and development in AI techniques and comprehensive training programs will empower scientists and healthcare professionals to fully exploit AI's potential, leading to improved patient outcomes and innovative pharmacological interventions.

Impact of Concomitant 5-Aminosalicylic Acid Therapy on Vedolizumab Efficacy and Safety in Inflammatory Bowel Disease: Post Hoc Analyses of Clinical Trial Data.

The benefit of continuing 5-aminosalicylic acid [5-ASA] treatment when escalating to advanced therapies in patients with inflammatory bowel disease [IBD] is unclear. Vedolizumab is a gut-selective monoclonal anti-α4β7-integrin antibody used to treat moderate to severe IBD. Clinical trial data were analysed post hoc to assess the impact of 5-ASA co-treatment on vedolizumab efficacy and safety in patients with IBD. Data were analysed from patients aged 18-80 years with moderate to severe ulcerative colitis [UC]/Crohn's disease [CD] receiving intravenous [IV]/subcutaneous [SC] vedolizumab. Efficacy data were from four studies [GEMINI 1 and 2 and VISIBLE 1 and 2]; safety data were from seven studies [GEMINI 1‒3 and long-term, VISIBLE 1, 2, and open-label extension]. The impact of 5-ASA co-treatment on clinical and endoscopic outcomes at Weeks 6 and 52 was assessed using multivariate analysis (adjusted odds ratios [aORs] with 95% confidence intervals [CIs]). There were no significant differences in UC clinical remission [Mayo score ≤2, no subscore >1] rates with vs without 5-ASA at Week 6 [20.7% vs 20.4%, respectively; aOR 0.77, 95% CI 0.43-1.38] or at Week 52 [45.1% vs 40.6%; aOR 1.14, 0.70-1.86], and in CD clinical remission [CD activity index score ≤150] rates at Week 6 [41.4% vs 35.1%; 1.26, 0.86-1.85] or at Week 52 [49.6% vs 37.8%; 1.35, 0.91-1.99]. The incidence of enteric and all infections in vedolizumab IV/SC-treated patients was low with and without 5-ASA. Continuation of concomitant oral 5-ASA after starting vedolizumab had no significant impact on clinical and endoscopic outcomes. GEMINI 1: NCT00783718, EudraCT 2008-002782-32; GEMINI 2: NCT00783692, EudraCT 2008-00278-33; GEMINI 3: NCT01224171, EudraCT 2009-016488-12; GEMINI long-term safety study: NCT00790933, EudraCT 2008-002784-14; VISIBLE 1: NCT02611830, EudraCT 2015-000480-14; VISIBLE 2: NCT02611817, EudraCT 2015-000481-58; VISIBLE open-label extension: NCT02620046, EudraCT 2015-000482-31.

Disease characteristics, pathogenesis, and treatment controversies of axial psoriatic arthritis

Axial psoriatic arthritis (axPsA) has considerable overlap with axial spondyloarthritis (axSpA) but has some unique features that sometimes preclude classification into axSpA. It has some clinical and radiographic differences compared to axSpA. Imaging typically shows asymmetric syndesmophytes, mainly in the cervical spine, with less frequent sacroiliitis. It more commonly presents later in life and is associated with less severe inflammatory back pain than axSpA. The interleukin (IL) IL-23/IL-17 axis is central to the pathogenesis of both diseases. However, the response to therapies targeting these cytokines has been different. IL-23 inhibitors are ineffective in axSpA but may be effective in psoriatic arthritis (PsA). Recent post hoc analyses of clinical trial data with IL-23 inhibitors in PsA have raised the possibility of their efficacy in axPsA and need evaluation in future clinical trials. Moreover, there is a need for classification criteria for axPsA and better tools to assess therapeutic response.

850-P: The Efficacy of Imeglimin in Diabetes Subgroups Stratified by Data-Driven Cluster Analysis—A Post Hoc Analysis of Imeglimin Clinical Trial Data

Objectives: We performed a post-hoc analysis of clinical trial data with the goal of investigating whether diabetic subgroups identified by data-driven clustering respond differently to imeglimin. Methods: Data from randomized, double-blind clinical trials of imeglimin as monotherapy or add-on to insulin therapy were included in the analysis. For monotherapy, 1) duration of type 2 diabetes, 2) baseline BMI, 3) baseline HbA1c, and 4) baseline HOMA-β, and for add-on to insulin therapy, the first three and 4) insulin total daily dose were applied as coordinates to form clusters by the non-hierarchical k-means method. The efficacy of imeglimin were examined for each cluster. Results: We identified four clusters of patients with diabetes, which had significantly different patient characteristics. Cluster 1 was a group with lower values of all four indices compared to the total patient population before cluster segregation, cluster 2 was a group with longer duration of diabetes, cluster 3 was a group with higher baseline BMI and higher HOMA-β (for monotherapy) or higher insulin total daily dose (for add-on to insulin therapy), and cluster 4 was a group with higher baseline HbA1c. The improvement in HbA1c with imeglimin differed significantly among the four clusters. The mean change differences versus placebo for imeglimin in monotherapy ranged from -0.64% to -1.27%, and add-on to insulin therapy ranged from -0.31% to -0.82%. In all clusters except for cluster 3 in the add-on to insulin therapy, imeglimin showed statistically significant HbA1c improvement compared to placebo. Conclusion: Data-driven clustering of patients with type 2 diabetes allowed us to identify subgroups that respond differently to imeglimin in improving HbA1c. This new stratification might help to tailor and target the imeglimin treatment to patients who would benefit most. Disclosure K.Hagi: Employee; Sumitomo Pharma. K.Kochi: Employee; Sumitomo Dainippon Pharma Co., Ltd., Sumitomo Pharma Co., Ltd. H.Watada: Research Support; Boehringer Ingelheim Japan, Inc., Mitsubishi Tanabe Pharma Corporation, LifeScan Diabetes Institute, Eli Lilly Japan K.K., Sun Pharmaceutical Industries Ltd., Teijin Pharma Limited, Taisho Pharmaceutical Holdings Co., Ltd., Ono Pharmaceutical Co., Ltd., Kowa Company, Ltd., Merck Sharp &amp; Dohme Corp., Sanwa Kagaku Kenkyusho, Speaker's Bureau; Mitsubishi Tanabe Pharma Corporation, Taiho Pharmaceutical Co. Ltd., Novo Nordisk, Abbott Japan Co., Ltd., Astellas Pharma Inc., Merck Sharp &amp; Dohme Corp., Kissei Pharmaceutical Co., Ltd., AstraZeneca, Ono Pharmaceutical Co., Ltd., Boehringer Ingelheim Japan, Inc., Sanofi, Sun Pharmaceutical Industries Ltd., Eli Lilly Japan K.K. K.Kaku: Advisory Panel; Novo Nordisk, Consultant; Sanwa Kagaku Kenkyusho, Speaker's Bureau; Astellas Pharma Inc., Daiichi Sankyo, Eli Lilly Japan K.K., Boehringer Ingelheim Japan, Inc., Kowa Company, Ltd., Mitsubishi Tanabe Pharma Corporation, Taiho Pharmaceutical Co. Ltd., Takeda Pharmaceutical Co., Ltd. K.Ueki: Advisory Panel; Abbott Japan Co., Ltd., Research Support; Abbott Japan Co., Ltd., Boehringer Ingelheim Japan, Inc., Eli Lilly Japan K.K., Sumitomo Dainippon Pharma Co., Ltd., Novo Nordisk, Sanofi K.K., MSD Life Science Foundation, Takeda Pharmaceutical Co., Ltd., Speaker's Bureau; Boehringer Ingelheim Japan, Inc., Eli Lilly Japan K.K., Astellas Pharma Inc., AstraZeneca, Sumitomo Dainippon Pharma Co., Ltd., Novo Nordisk, Taiho Pharmaceutical Co. Ltd., Kowa Company, Ltd., Mitsubishi Tanabe Pharma Corporation, Ono Pharmaceutical Co., Ltd.

Use of Quantile Treatment Effects Analysis to Describe Antidepressant Response in Randomized Clinical Trials Submitted to the US Food and Drug Administration

Major depressive disorder (MDD) is a leading cause of global distress and disability. Earlier studies have indicated that antidepressant therapy confers a modest reduction in depressive symptoms on average, but the distribution of this reduction requires more research. To estimate the distribution of antidepressant response by depression severity. In this secondary analysis of pooled trial data, quantile treatment effect (QTE) analysis was conducted from the US Food and Drug Administration (FDA) database of antidepressant monotherapy for patients with MDD, encompassing 232 positive and negative trials submitted to the FDA between 1979 and 2016. Analysis was restricted to participants with severe MDD (17-item Hamilton Rating Scale for Depression [HAMD-17] score ≥20). Data analysis was conducted from August 16, 2022, to April 16, 2023. Antidepressant monotherapy compared with placebo. The distribution of percentage depression response was compared between the pooled treatment arm and pooled placebo arm. Percentage depression response was defined as 1 minus the ratio of final depression severity to baseline depression severity, expressed as a percentage. Depression severity was reported in HAMD-17-equivalent units. A total of 57 313 participants with severe depression were included in the analysis. There was no significant imbalance in baseline depression severity between the pooled treatment arm and pooled placebo arm, with a mean HAMD-17 difference of 0.037 points (P = .11 by Wilcoxon rank sum test). An interaction term test for rank similarity did not reject the rank similarity governing percentage depression response (P > .99). The entire distribution of depression response was more favorable in the pooled treatment arm than in the pooled placebo arm. The maximum separation between treatment and placebo occurred at the 55th quantile and corresponded to an absolute improvement in depression due to active drug of 13.5% (95% CI, 12.4%-14.4%). The separation between treatment and placebo diminished near the tails of the distribution. In this QTE analysis of pooled clinical trial data from the FDA, antidepressants were found to confer a small reduction in depression severity that was broadly distributed across participants with severe depression. Alternatively, if the assumptions behind the QTE analysis are not met, then the data are also compatible with antidepressants eliciting more complete response in a smaller subset of participants than is suggested by this QTE analysis.

Adjuvant chemotherapy does not improve outcome in children with ovarian immature teratoma: A comparative analysis of clinical trial data from the Malignant Germ Cell International Consortium.

Surgery is the mainstay of therapy for children with ovarian immature teratoma (IT), whereas adults receive adjuvant chemotherapy, except those with stage-I, grade-1 disease. In Brazil, children with metastatic ovarian IT received postoperative chemotherapy. This practice variation allowed evaluation of the value of chemotherapy, by comparison of Brazilian patients with those in the United States and United Kingdom. From the Malignant Germ Cell International Consortium data commons, data on ovarian IT patients from two recently added Brazilian trials (TCG-99/TCG-2008) were compared with data from US/UK (INT-0106/GC-2) trials. Primary outcome measure was event-free (EFS) and overall survival (OS). Forty-two Brazilian patients were included (stage I: 27, stage II: 4, stage III: 8, stage IV: 3). Twenty-nine patients had surgery alone, whereas 13 patients received postoperative chemotherapy. The EFS and OS for entire cohort was 0.80 (95% CI: 0.64-0.89) and 0.97 (0.84-0.99). There was no difference in relapse risk based on stage, grade, or receipt of chemotherapy. Comparing the Brazilian cohort with 98 patients in US/UK cohort (stage I: 59, stage II: 12, stage III: 27), there was no difference in EFS and OS across all stages, despite 87% of stage II-IV Brazilian patients receiving postoperative chemotherapy compared with only 13% of US/UK patients. The EFS and OS for Brazilian compared with US/UK cohort was stage I: 88% versus 98% (p=.05), stage II-IV EFS: 67% versus 79% (p=.32), stage II-IV OS: 93% versus 97% (p=.44); amongst grade-3 patients, there was no difference in EFS or OS. Addition of postoperative chemotherapy did not improve outcome in children with ovarian IT, even at higher grade or stage, compared with surgery alone.

Performance of Cox regression models for composite time-to-event endpoints with component-wise censoring in randomized trials.

Composite time-to-event endpoints are beneficial for assessing related outcomes jointly in clinical trials, but components of the endpoint may have different censoring mechanisms. For example, in the PRagmatic EValuation of evENTs And Benefits of Lipid-lowering in oldEr adults (PREVENTABLE) trial, the composite outcome contains one endpoint that is right censored (all-cause mortality) and two endpoints that are interval censored (dementia and persistent disability). Although Cox regression is an established method for time-to-event outcomes, it is unclear how models perform under differing component-wise censoring schemes for large clinical trial data. The goal of this article is to conduct a simulation study to investigate the performance of Cox models under different scenarios for composite endpoints with component-wise censoring. We simulated data by varying the strength and direction of the association between treatment and outcome for the two component types, the proportion of events arising from the components of the outcome (right censored and interval censored), and the method for including the interval-censored component in the Cox model (upper value and midpoint of the interval). Under these scenarios, we compared the treatment effect estimate bias, confidence interval coverage, and power. Based on the simulation study, Cox models generally have adequate power to achieve statistical significance for comparing treatments for composite outcomes with component-wise censoring. In our simulation study, we did not observe substantive bias for scenarios under the null hypothesis or when the treatment has a similar relative effect on each component outcome. Performance was similar regardless of if the upper value or midpoint of the interval-censored part of the composite outcome was used. Cox regression is a suitable method for analysis of clinical trial data with composite time-to-event endpoints subject to different component-wise censoring mechanisms.

Reduction in hospitalisations with dupilumab in Japanese adults with atopic dermatitis in a real‐world setting

AbstractBackgroundIn a recent post hoc analysis of multinational clinical trial data, dupilumab treatment for patients with moderate or severe atopic dermatitis (AD) reduced all‐cause and AD‐related hospitalisations.ObjectivesWe studied the impact of dupilumab on health care resource utilisation (HCRU) and AD medication by comparing use during the 6 months either side of starting dupilumab (index) in a real‐world setting.MethodsThis observational, retrospective, cohort study used Japanese hospital claims data (1 April 2018 to 28 February 2019). A total of 357 patients (mean [range] age 45 [15–92] years; 65.5% male) with ≥1 AD diagnosis and ≥1 dupilumab prescription were included. Outcome variables included AD treatments and HCRU during the 6 months pre‐ and post‐index.ResultsThe number of all‐cause hospitalisations decreased by 43.1% (from 51 in the 6 months before to 29 in the 6 months after dupilumab initiation), with a 96.0% reduction in skin/subcutaneous tissue disease‐related hospitalisations (25 to 1). Use of nonsteroidal systemic immunosuppressants, phototherapy and systemic corticosteroids decreased (by 59.8%, 59.5% and 30.6%, respectively) after dupilumab initiation. At 180 days after dupilumab initiation, 86.8% of patients were still taking dupilumab.ConclusionsOverall, these results suggest that dupilumab can reduce skin/soft tissue‐related hospitalisations and use of various other AD medications in a real‐world setting.

Defining Successful Intubation on the First Attempt Using Both Laryngoscope and Endotracheal Tube Insertions: A Secondary Analysis of Clinical Trial Data

Successful intubation on the first attempt has historically been defined as successful placement of an endotracheal tube (ETT) using a single laryngoscope insertion. More recent studies have defined successful placement of an ETT using a single laryngoscope insertion followed by a single ETT insertion. We sought to estimate the prevalence of first-attempt success using these 2 definitions and estimate their associations with the duration of intubation and serious complications. We performed a secondary analysis of data from 2 multicenter randomized trials of critically ill adults being intubated in the emergency department or ICU. We calculated the percent difference in successful intubations on the first attempt, median difference in the duration of intubation, and percent difference in the development of serious complications by definition. The study population included 1,863 patients. Successful intubation on the first attempt decreased by 4.9% (95% confidence interval 2.5% to 7.3%) when defined as 1 laryngoscope insertion followed by 1 ETT insertion (81.2%) compared with when defined as only 1 laryngoscope insertion (86.0%). When successful intubation with 1 laryngoscope and 1 ETT insertion was compared with 1 laryngoscope and multiple ETT insertions, the median duration of intubation decreased by 35.0 seconds (95% confidence interval 8.9 to 61.1 seconds). Defining successful intubation on the first attempt as placement of an ETT in the trachea using 1 laryngoscope and 1 ETT insertion identifies attempts with the shortest apneic time.

Abstract LB143: Improving treatment outcomes: a digital solution for remote patient monitoring of stomatitis for patients receiving Dato-DXd

Abstract Instances of stomatitis are very painful and compromise nutrition and oral hygiene as well as induce an increased risk for local and systemic infection. Stomatitis is a well-known toxicity of radiotherapy, chemotherapy and other targeted therapies and is associated with dose interruptions, reductions, and treatment discontinuation. For upcoming Dato DXd phase III trials, the mitigation strategies included patient education delivered at the site and supported by printed material to foster continued adherence to an oral care protocol (OCP). The study team thought to leverage digital technology, namely patient-provisioned smartphones to bring the OCP right “to the patients’ fingertips”, while enabling health care providers at the site to monitor onset or worsening of stomatitis for each patient. The digital solution consists of a patient interface for data acquisition and personalized education/behavioral reinforcement, and a clinician interactive data dashboard to access, in real time, patients’ records of stomatitis-related symptoms and their impact on nutrition and hydration, respectively. For a few days post infusion, the solution surfaces personalized illustrated vignettes to provide the participant with simple recommendations for self-care and probe to contact the clinical site team when symptom(s) reach a given morbidity threshold. The clinical team can visualize data on demand or upon being prompted, to quickly assess trends towards stomatitis worsening and decide on the next course of action. This solution for remote patient monitoring of stomatitis risk is deployed in four studies and is planned for an additional three, reaching approximately a total of 7,000 patients across 49 sites in 16 countries. Early feedback from patients confirmed the engaging design, the low burden daily usage, and the perceived utility of the solution. Patients who had experienced stomatitis previously indicated that such a solution would have given them confidence to engage with their site sooner to receive care. Further structured feedback from clinical study teams and analyses of clinical trial data are planned to inform patients’ sustained compliance using the solution and its effectiveness in mitigating high grade of stomatitis and helping patients to better manage their treatment and outcomes. Citation Format: Rebecca H. Wray, Elisabeth Piault, Lucie Miller-Potucka, Jill A. Bell, Rick Fairhurst, Sabrina S. Khan, Micah J. Maxwell, Neelima Denduluri, Leora Horn. Improving treatment outcomes: a digital solution for remote patient monitoring of stomatitis for patients receiving Dato-DXd [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB143.

Abstract 5464: Predictive biomarkers for PD-1 and PD-L1 checkpoint inhibitor response in NSCLC: An analysis of clinical trial and real-world data

Abstract Importance: Largest analysis combining clinical trial and real-world data (RWD) to assess the clinical utility of biomarkers for anti-PD-1/PD-L1 checkpoint inhibitors (CPI) in NSCLC patients. Objective: To assess the association between tumor PD-L1, TMB and blood analytes with clinical outcomes in patients with advanced NSCLC following CPI therapy. Design: Retrospective cohort study with patients stratified into high and low biomarker groups. Correlation with treatment outcome in the different biomarker groups was investigated and compared between patients treated with CPI versus chemotherapy. Setting: Data derived from electronic health records mostly from community oncology settings were combined with clinical trial data. Participants: Starting with 71850 patients with advanced NSCLC who received CPI or chemotherapy, we selected 24152 patients from an electronic health record-derived de-identified NSCLC clinicogenomic database (CGDB) from a real-world cohort and nine Roche atezolizumab trials. Patients were diagnosed between January 2011 and February 2020 (data collection cut-off date). Main Outcomes and Measures: Drug response was assessed by RECIST criteria for clinical trials and real-world response for RWD. Durable response was defined as having CR/PR without progression during the study period of 270 days. Associations of biomarker levels with treatment outcomes were analyzed using Fisher’s exact test. Results: High expression of PD-L1 on tumors (≥50%) were associated with lower risk of resistance to CPI (odds ratio [OR] 0.21; 95% CI = 0.14, 0.32; P&amp;lt; .001). The association was stronger in patients who had prior chemotherapy than first line CPI, with non-squamous than squamous histology, and smokers than non-smokers. Higher TMB (≥9.57 mut/Mb) was also associated with durable response (OR = 0.41; CI = 0.30, 0.55; P&amp;lt; .001). The combination of high TMB and PD-L1 expression was the strongest predictor of durable response (OR = 0.04; CI = 0.00, 0.20; P&amp;lt; .001). There was no evidence of an association between PD-L1/TMB and response to chemotherapy, suggesting a CPI-specific predictive effect. In contrast, blood analytes were prognostic, having correlation with clinical outcome irrespective of treatment type. Conclusion: This study supports the predictive utility of PD-L1 expression and TMB for NSCLC patients receiving CPI therapy and further elucidates their utility in patient sub-populations. Citation Format: WeiQing Venus So, David Dejardin, Eva Rossmann, Jehad Charo. Predictive biomarkers for PD-1 and PD-L1 checkpoint inhibitor response in NSCLC: An analysis of clinical trial and real-world data. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5464.