Analysis of the frequency characteristics and reasons for termination of clinical trials in Systemic Lupus Erythematosus: based on the Clinical Trial. gov database

Analysis of the frequency characteristics and reasons for termination of clinical trials in Systemic Lupus Erythematosus: based on the Clinical Trial. gov database | 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 Analysis of the frequency characteristics and reasons for termination of clinical trials in Systemic Lupus Erythematosus: based on the Clinical Trial. gov database Lina BAI, Yanli YANG, Junkang ZHAO, Qianyu GUO, Li ZHAO, Zhiqiang HE, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6983104/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 Background Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease with limited treatment options. Clinical trials play a crucial role in developing therapies; however, SLE trials often face high termination rates, hindering advancements in patient care. Objective This study aims to analyze the characteristics and reasons for the termination of SLE clinical trials and to provide insights into strategies for improving trial sustainability and success. Methods Using data from ClinicalTrials.gov, 490 SLE clinical trials, including 388 completed and 102 terminated trials, were evaluated. Trial characteristics such as intervention type, trial phase, funding source, and reasons for termination were analyzed using descriptive and multivariate regression analyses. Results Termination rates were significantly associated with trial phase, intervention type, and primary purpose. Phase III trials exhibited the highest termination risk (OR = 1.99, P = 0.037). Drug/biological trials had a higher likelihood of termination compared to non-drug interventions (OR = 0.43, P = 0.031). Recruitment challenges and insufficient accrual rates were leading causes of termination, while adaptive trial designs and innovative recruitment methods showed potential to mitigate these risks. Conclusion SLE clinical trials face unique challenges, with high termination rates driven by operational and design complexities. Strategies such as adaptive designs, decentralized recruitment, and collaborative funding could improve trial sustainability, advancing the development of effective treatments for SLE. Health sciences/Diseases Biological sciences/Immunology Health sciences/Medical research Health sciences/Rheumatology Systemic Lupus Erythematosus clinical trial termination reason Figures Figure 1 1. Introduction Systemic Lupus Erythematosus (SLE) is a chronic autoimmune disease characterized by the immune system's erroneous attack on multiple organs and systems of the body, leading to inflammation and tissue damage 1 . The global incidence of SLE ranges from 20 to 70 cases per 100,000 individuals, with a predilection for women of childbearing age 2 . The clinical manifestations of SLE are diverse and complex, including joint pain, skin rashes, fatigue, and renal impairment, which significantly impair the quality of life of affected individuals 3 . Currently, the management of SLE focuses on symptom relief and reduction of disease activity, as there is no known cure. Treatment options encompass nonsteroidal anti-inflammatory drugs, antimalarials, corticosteroids, and immunosuppressants 4 . However, the efficacy and safety of available treatments are limited, leaving many patients without adequate disease control 5 . Clinical trials are a pivotal component of medical research, essential for the development and validation of new therapeutic approaches. Yet, clinical trials have a high rate of failure, with approximately 85% of drug development trials not meeting their primary endpoints 6 . In the context of SLE, the termination of clinical trials not only diminishes treatment options but also has a profound impact on the quality of life and disease outcomes for patients 7 . Previous studies have identified a multitude of reasons for the discontinuation of clinical trials, including safety concerns, insufficient efficacy, funding issues, and recruitment challenges 8 , 9 . Understanding these reasons is crucial for optimizing clinical trial design, enhancing research efficiency, and minimizing the waste of resources. While general reasons for clinical trial termination have been explored, a specific analysis focused on SLE is lacking. This study aims to analyze the reasons for the termination of SLE clinical trials and to investigate how improvements in study design and execution strategies can increase the success rate of clinical trials. By analyzing data from ClinicalTrials.gov, the U.S. registry of clinical trials, we intend to provide valuable insights for the advancement of SLE treatment research, thereby facilitating the development of more effective and safer therapeutic interventions. 2. Methods This article is designed for retrospective data analysis. As this study does not involve any commercial interests, and the data in the database does not include any private information of the research subjects, it has been granted an exemption from ethical review by the Shanxi Bethune Hospital for Clinical Research Ethics Committee (LYLL-MC-2025-001). Clinical trial number: not applicable. 2.1 Data Filtering This study draws upon data from the ClinicalTrials.gov registry, administered by the National Library of Medicine at the National Institutes of Health in the United States, as its primary source of information. ClinicalTrials.gov, administered by the National Library of Medicine (NLM) within the National Institutes of Health (NIH) in the United States, is recognized as the preeminent global registry, encompassing the most extensive and diverse array of clinical research studies. Search Strategy: In the "Condition or Disease" field, the search terms "Systemic Lupus Erythematosus" "Lupus Nephritis" "Lupus Erythematosus" "Cutaneous Lupus Erythematosus" "Lupus" "Discoid Lupus Erythematosus" and "Disseminated Lupus Erythematosus" were entered. The "Study Start Date" was set to range from the inception of the database to May 31, 2024. The "Study Type" was specified as "Interventional". The "Study Status" was filtered to include only "COMPLETED" and "TERMINATED" studies. Following this screening process, a total of 499 clinical trials met the criteria. 2.2 Data Extraction The clinical trials data obtained from ClinicalTrials.gov was downloaded in a Tab-separated values format and subsequently merged using Microsoft Office Excel 2019. The final data extraction yielded the following information: Registration Number, Trial Title, Trial Status, Study Results, Intervention(s), Outcome Measures, Sponsor, Trial Phase, Study Design, Funding Source, Number of Participants, Participant Gender, Age, Registration Date, and Registration Region. 2.3 Operational Definitions To facilitate analysis, the research team grouped the data extracted from the ClinicalTrials.gov website and established the following definitions: Intervention: Types are categorized as follows: Drug/Biological, Device/Procedure, Other (including Behavioral, Dietary supplement, Genetic, Radiation, Diagnostic tests and others). Primary purpose: Interventions or treatment (including Treatment, prevention), Health services and diagnosis (including Health service research, diagnostic, and screening), other including (basic science, supportive care and others) Study Phases are defined as: Phase I, which includes all studies prior to Phase I; Phase II, encompassing Phase I/II and Phase II studies; and Phase III, including Phase II/III and Phase III studies. Primary Sponsoring Organizations are categorized as: the National Institutes of Health (NIH) or other U.S. federal government agencies, Industry, and Other (including individuals, academic institutions, and social organizations). In study design, the allocation is defined as Randomized (Yes or No); Blinding (Yes or No), which is used to indicate whether the blinding is applied to trial participants, researchers, care providers, and outcome assessors. 2.4 Data Analysis Categorical data are presented as frequencies (%), continuous variables as median (IQR) or mean ± SD. Group comparisons used chi-square/Fisher's exact tests. Predictors of termination were identified by multivariable logistic regression (adjusted ORs with 95% CIs), visualized via forest plot (SPSS 25.0). Model fit was assessed using Hosmer-Lemeshow test (P > 0.05). Significance level was P < 0.05 (two-tailed). 2.5 Categorization of Reasons for Termination The reasons for study termination were obtained from the "Why Study Stopped" column as indicated from the Researcher View column and classified into one of the following categories. The general classification of reasons for trial termination draws upon a prior research study 7 , 10 . Reasons included: (1) Scientific data from the trial; (2) Insufficient accrual rate; (3) Unspecified business decision/strategic reason; (4) Trial administration or conduct (issues with protocol, investigators, site, etc.); (5) External information (results from other trials, competing trials, or changes in standard of care); (6) Funding; (7) Product withdrawal; (8) Lack of drug supply (other than drug withdrawal); (9) Other (e.g., uninformative or non-specific text); (10) Termination Reason Not Provided. 3. Results The study analyzed 490 SLE clinical trials, of which 388 (79.2%) were completed and 102 (20.8%) were terminated. Various primary and secondary trial characteristics, as well as reasons for termination, were evaluated to identify factors associated with trial discontinuation. 3.1 Characteristics of Completed and Terminated Trials Table 1 shows that the termination rate varied based on intervention type, trial phase, and primary purpose, with the following significant findings. In terms of Intervention Type, although not statistically significant (χ²=5.24, P = 0.073), drug/biological trials had a higher proportion of termination (86.27%) compared to other types, such as device/procedure (5.88%) and other interventions (7.84%). And, a significant association was observed between trial phase and termination risk (χ²=18.70, P < 0.001). Phase III trials had the highest termination rate (33.33%), followed by Phase II (29.41%) and Phase I (21.57%). Notably, Phase IV trials were less likely to be terminated (3.92%). Besides, trials with a primary purpose of "interventions or treatment" were more likely to be terminated (97.06%) compared to "health services and diagnosis" (0.98%) and "other" purposes (1.96%), with a statistically significant association (χ²=9.51, P = 0.009). As shown in Table 2 , secondary characteristics, including sex eligibility, age group, and intervention model, were analyzed. Although most trials were open to all sexes (88.78%), this variable was not significantly associated with termination (P = 0.502). And, there was no significant association between age group eligibility and trial termination (χ²=4.00, P = 0.406). Most trials included adults and older adults (74.08%). Trials with a parallel intervention model accounted for the highest proportion of terminated trials (72.55%). However, the difference in intervention model types did not reach statistical significance (P = 0.103). Table 1 Primary characteristics of completed and terminated SLE clinical trials Variables Total (n = 490) Completed (n = 388) Terminated (n = 102) Statistic P Intervention Type χ²=5.24 0.073 Drug/Biological 394 (80.41) 306 (78.87) 88 (86.27) Device/Procedure 23 (4.69) 17 (4.38) 6 (5.88) Other a 73 (14.90) 65 (16.75) 8 (7.84) Phase χ²=18.70 < .001 Phase Ⅰ 101 (20.61) 79 (20.36) 22 (21.57) Phase Ⅱ 166 (33.88) 136 (35.05) 30 (29.41) Phase Ⅲ 84 (17.14) 50 (12.89) 34 (33.33) Phase Ⅳ 37 (7.55) 33 (8.51) 4 (3.92) Not Provided 102 (20.82) 90 (23.20) 12 (11.76) Funder Type χ²=2.04 0.361 NIH/Fed/Other Gov 31 (6.33) 26 (6.70) 5 (4.90) Industry 239 (48.78) 183 (47.16) 56 (54.90) Other 220 (44.90) 179 (46.13) 41 (40.20) Allocation χ²=3.45 0.178 Randomized 338 (68.98) 265 (68.30) 73 (71.57) None Randomized 59 (12.04) 52 (13.40) 7 (6.86) NA 93 (18.98) 71 (18.30) 22 (21.57) Masking χ²=0.01 0.941 Blinded 261 (53.27) 207 (53.35) 54 (52.94) None 229 (46.73) 181 (46.65) 48 (47.06) Primary Purpose χ²=9.51 0.009 Interventions or Treatment 433 (88.37) 334 (86.08) 99 (97.06) Health Services and Diagnosis 25 (5.10) 24 (6.19) 1 (0.98) Other b 32 (6.53) 30 (7.73) 2 (1.96) χ²: Chi-square test; a : Other include Behavioral, Dietary supplement, genetic, radiation, diagnostic tests and others. b : Other included basic science, supportive care and others. Table 2 Secondary characteristics of completed and terminated SLE clinical trials Variables Total (n = 490) Completed (n = 388) Terminated (n = 102) Statistic P Sex Eligibility - 0.502 Male 5 (1.02) 5 (1.29) 0 (0.00) Female 50 (10.20) 42 (10.82) 8 (7.84) ALL 435 (88.78) 341 (87.89) 94 (92.16) Age Group χ²=4.00 0.406 Adult 62 (12.65) 53 (13.66) 9 (8.82) Adult/ Older Adult 363 (74.08) 282 (72.68) 81 (79.41) Child/Adult/Older Adult 33 (6.73) 25 (6.44) 8 (7.84) Child/ Adult 28 (5.71) 25 (6.44) 3 (2.94) Child 4 (0.82) 3 (0.77) 1 (0.98) Intervention Model - 0.103 Single Group 138 (28.16) 111 (28.61) 27 (26.47) Parallel 319 (65.10) 245 (63.14) 74 (72.55) Sequential 12 (2.45) 11 (2.84) 1 (0.98) Crossover 14 (2.86) 14 (3.61) 0 (0.00) Factorial 7 (1.43) 7 (1.80) 0 (0.00) χ²: Chi-square test, -: Fisher exact; 3.2 Categorization of Reasons for Termination Table 3 outlines the reasons for trial termination, with the most common causes being "insufficient accrual rate" (28.4%) and "scientific data from the trial" (28.4%). Other reasons included unspecified business or strategic decisions (8.8%), external information (4.9%), trial administration or conduct issues (4.9%), and COVID-19 (2.9%). Table 3 Categorization of Reasons for Trial Termination Termination Reason Category Number (Percentage of Trials) Total terminated 102 (100) Insufficient accrual rate 29 (28.4) Scientific data from the trial 29 (28.4) Unspecified business decision/strategic reason 9 (8.8) External information 5 (4.9) Trial administration or conduct 5 (4.9) Other (uninformative or non-specific text) 4 (3.9) COVID-19 3 (2.9) Funding 3 (2.9) Lack of drug supply 1 (1.0) Not provided 14 (13.7) 3.3 Factors Associated with Termination Figure 1 displays the results of the multivariate logistic regression analysis, identifying factors significantly associated with trial termination. Trials involving non-drug/biological interventions, including behavioral, dietary supplements, and genetic interventions, had a significantly lower termination risk (OR = 0.43, 95%CI: 0.20–0.93, P = 0.031) compared to drug/biological trials. Phase III trials exhibited a significantly higher risk of termination (OR = 1.99, 95%CI: 1.04–3.82, P = 0.037) compared to Phase I trials. Trials that did not specify their phase also trended towards reduced termination risk (OR = 0.48, 95%CI: 0.22–1.03, P = 0.059). Trials with primary purposes other than "interventions or treatment", specifically those categorized as "health services and diagnosis" and "other", showed reduced termination risks, with odds ratios of 0.14 (95%CI: 0.02–1.05, P = 0.056) and 0.22 (95%CI: 0.05–0.96, P = 0.044), respectively. This analysis suggests that the type of intervention, trial phase, and primary purpose are critical factors in SLE trial termination, with drug/biological interventions, Phase III trials, and trials focused on treatment interventions showing increased risks for discontinuation. 4. Discussion This study analyzed the characteristics and reasons for termination of SLE clinical trials, revealing potential associations between specific trial attributes and termination risk. The findings integrate data from Table 1 and Table 2 on basic trial characteristics, Table 3 on sponsor-reported reasons for termination, and Fig. 1 on multivariate regression analysis, providing multidimensional insights into factors driving SLE trial discontinuation. Trial Phase and Termination Risk Results indicate that Phase III trials have a significantly higher risk of termination compared to Phase I trials (OR = 1.99, 95%CI: 1.04–3.82, P = 0.037). This finding aligns with expectations, as Phase III trials typically involve larger patient cohorts, extended timelines, and higher costs, which increase resource demands and uncertainty. 11 Moreover, the elevated termination rate in Phase III trials may reflect challenges in trial management and operational complexity, consistent with findings in Table 3 , where "insufficient accrual rate" accounted for 28.4% of terminations. On one hand, Phase III trials are often conducted across multiple sites to obtain representative data, which complicates coordination and management. Multi-center designs, while expanding patient recruitment, present challenges related to personnel allocation, data consistency, and ethical oversight. These added layers of trial complexity may hinder trial continuity. 8 On the other hand, the small target population of SLE, coupled with stringent inclusion criteria, complicates recruitment efforts. Phase III trials demand high patient enrollment, which extends recruitment timelines and escalates costs, further raising the likelihood of trial termination. Impact of Intervention Type and Primary Purpose on Termination In terms of intervention type, non-drug/biological trials (including behavioral, dietary supplements, and genetic interventions) showed a significantly lower risk of termination compared to drug/biological trials (OR = 0.43, 95%CI: 0.20–0.93, P = 0.031). This finding suggests that drug/biological trials, which typically face higher standards of safety and efficacy verification, encounter increased termination risks due to the stringent regulatory expectations associated with these interventions. 12 Drug and biological trials require multi-phase clinical assessments, progressively expanding sample sizes to validate efficacy and safety. Such trials are inherently more complex, with higher associated costs and a greater dependency on robust data, particularly in chronic disease research, where adverse events or lack of efficacy can lead to early termination. 13 Non-drug interventions, such as behavioral interventions and dietary supplements, have relatively lower safety risks and greater trial design flexibility compared to drug-based interventions. Behavioral intervention trials are less affected by the complexities of drug metabolism or interactions, allowing for more straightforward assessments of patient outcomes. Detailed Analysis of Termination Reasons Table 3 indicates that "insufficient accrual rate" (28.4%) and "scientific data" (28.4%) were leading causes of termination in SLE trials. Recruitment challenges are particularly common in trials for chronic, 14 low-prevalence conditions such as SLE, where patient populations are small and enrollment criteria stringent. Additionally, the heterogeneous nature of SLE symptoms and fluctuating disease course may further complicate recruitment and retention. At the same time, in trials for diseases with variable disease courses like SLE, efficacy data may fluctuate, making it difficult to achieve consistent statistical outcomes. For early-phase clinical trials, the lack of reliable biomarkers can indeed contribute to lower data quality and may increase the likelihood of trial termination. As the absence of validated biomarkers can hinder efforts to monitor therapeutic effects accurately, leading to challenges in justifying the continuation of the trial if initial results do not meet efficacy or safety benchmarks. 15 In addition, business or strategic decisions accounted for 8.8% of terminations, suggesting that some trials were terminated not for scientific reasons but due to resource allocation or market strategies. Although the multivariate analysis did not find a statistically significant association with funding source (P = 0.364), industry-sponsored trials exhibited a marginally higher termination rate than those funded by government or other sources. This trend may reflect the influence of business priorities or resource constraints on trial sustainability. 16 Influence of Randomization, Blinding, and Trial Design Despite the role of randomization and blinding in reducing bias, this study did not observe a significant effect of these factors on termination risk. The presence or absence of randomization and blinding did not show notable differences between terminated and completed trials. Additionally, while parallel-group design trials accounted for a slightly higher proportion of terminated trials (72.55%), regression analysis found no statistically significant association (P = 0.103), suggesting that in SLE trials, design factors may play a limited role in trial sustainability compared to external management or resource issues. Parallel-group and randomized controlled trials typically require larger patient enrollment, longer observation periods, and stricter trial conditions. Although randomization and blinding enhance data reliability, they also incur high execution and monitoring costs, which may indirectly contribute to trial termination risks. 17 Recently, some trials have adopted adaptive designs or simplified randomization to enhance flexibility. Adaptive designs allow for interim evaluations, enabling researchers to adjust sample sizes or interventions dynamically, thus lowering termination risks. 18 , 19 This approach is especially useful for chronic diseases like SLE that benefit from adaptable study frameworks. Implications of Clinical Trial Termination Rates The high termination rate in SLE trials not only impacts patient treatment expectations but also results in considerable resource wastage. This study suggests that clinical trial design for rare diseases like SLE must strike a balance between scientific rigor and operational feasibility to mitigate termination risks. Flexible patient recruitment strategies, careful selection of trial phases, and clearly defined scientific objectives can contribute to trial completion. Future studies could explore more flexible patient recruitment methods such as decentralized methods, 20 multi-regional screening and remote monitoring, to broaden enrollment scope. Through strategic trial planning, cost reduction, and resource allocation, trials may more effectively reduce termination risks. Furthermore, increased collaboration between funding agencies, research centers, and industry could support trial sustainability. For example, establishing shared research resources and information platforms can help address resource limitations and asymmetries that often lead to termination. Additionally, promoting joint funding from multiple sources could further minimize the commercial impact on trial sustainability. 5. Limitation This study has several limitations. The analysis relied on publicly available data from ClinicalTrials.gov, which may lack detailed information on trial execution and context-specific factors influencing termination. Besides, variability in how sponsors document reasons for trial termination may introduce inconsistencies and affect the accuracy of the classification. Future studies could avoid these factors, making the analysis more comprehensive. 6. Conclusion This study highlights critical factors driving the termination of systemic lupus erythematosus (SLE) clinical trials, providing valuable insights for future research. Phase III trials exhibited a higher risk of termination, driven by their operational complexity, extensive resource demands, and recruitment challenges. Similarly, drug/biological interventions demonstrated increased termination risks, reflecting the stringent efficacy and safety requirements inherent in their development. Addressing these challenges requires implementing innovative strategies. Adaptive trial designs allow for flexibility in trial execution, while decentralized recruitment methods and multi-regional screening can expand patient pools. Collaborative funding mechanisms that integrate public, private, and academic resources could mitigate financial constraints, fostering trial sustainability. Achieving a balance between scientific rigor and practical feasibility is essential for advancing SLE research. Optimizing trial designs, recruitment strategies, and funding structures will enhance trial completion rates, thereby accelerating the development of effective and safe treatments for SLE. Declarations Funding This study was funded by Shanxi Province Clinical Research Center for Dermatologic and Immunologic Diseases（Rheumatic diseases), Research and Innovation Team Project for Scientific Breakthroughs at Shanxi Bethune Hospital（2024AOXIANG02）and Science Fundation of Shanxi Bethune Hospital in China (2022YH10). Declaration of Conflicting Interests The authors declared no potential conflicts of interest concerning this article's research, authorship, and/or publication. Author Contribution Lina BAI was primarily responsible for conceptualizing the study, conducted the initial manuscript, methodology, and analyzing the data. Yanli YANG reviewed and edit the initial manuscript. Qianyu GUO and Li ZHAO contributed to data curation, and Junkang ZHAO contributed to software and methodology. Zhiqiang HE and Liyun ZHANG supervised the overall study design, provided critical guidance throughout the research process, and is the co-corresponding author. All authors reviewed and approved the final manuscript. Data Availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Hochberg MC. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Letter. Arthritis and rheumatism . Sep 1997;40(9):1725-1725. doi:10.1002/art.1780400928 Petri M, Orbai A-M, Alarcon GS, et al. Derivation and validation of the systemic lupus international collaborating clinics classification criteria for systemic lupus erythematosus. Article. Arthritis and rheumatism . 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Clinical Cancer Research . 2010;16(6):1745-1755. doi:10.1158/1078-0432.Ccr-09-2167 Khunger M, Rakshit S, Hernandez AV, et al. Premature Clinical Trial Discontinuation in the Era of Immune Checkpoint Inhibitors. The Oncologist . 2018;23(12):1494-1499. doi:10.1634/theoncologist.2018-0003 Dijkgraaf MGW, Haukoos J, Itani KMF. Practical Guide to Design Choice of Randomized Clinical Trials in Surgery. JAMA Surg . Dec 1 2022;157(12):1154-1155. doi:10.1001/jamasurg.2022.4889 Julie CL, Niteesh KC, Massimiliano R, Robert JG, Steffen V, Lorenzo T. Designing and conducting adaptive trials to evaluate interventions in health services and implementation research: practical considerations. BMJ Medicine . 2022;1(1):e000158. doi:10.1136/bmjmed-2022-000158 Kaizer AM, Belli HM, Ma Z, et al. Recent innovations in adaptive trial designs: A review of design opportunities in translational research. Journal of Clinical and Translational Science . 2023;7(1):e125. e125. doi:10.1017/cts.2023.537 Miyata BL, Tafuto B, Jose N. Methods and perceptions of success for patient recruitment in decentralized clinical studies. J Clin Transl Sci . 2023;7(1):e232. doi:10.1017/cts.2023.643 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6983104","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":481149980,"identity":"95f42073-1781-4178-b866-7c2085b702ec","order_by":0,"name":"Lina BAI","email":"","orcid":"","institution":"Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lina","middleName":"","lastName":"BAI","suffix":""},{"id":481149981,"identity":"bafdbc8c-25bf-404b-ad0a-9c7bec9b838e","order_by":1,"name":"Yanli YANG","email":"","orcid":"","institution":"Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yanli","middleName":"","lastName":"YANG","suffix":""},{"id":481149982,"identity":"4f0e1741-e6d0-49e7-876c-e38a5aaa0365","order_by":2,"name":"Junkang ZHAO","email":"","orcid":"","institution":"Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital","correspondingAuthor":false,"prefix":"","firstName":"Junkang","middleName":"","lastName":"ZHAO","suffix":""},{"id":481149983,"identity":"62a4c281-e4c4-45b1-aee5-fe6cd2a25b75","order_by":3,"name":"Qianyu GUO","email":"","orcid":"","institution":"Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qianyu","middleName":"","lastName":"GUO","suffix":""},{"id":481149984,"identity":"08d02e5d-85db-4523-a081-e77e5a88cdd4","order_by":4,"name":"Li ZHAO","email":"","orcid":"","institution":"Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"ZHAO","suffix":""},{"id":481149985,"identity":"195bea6b-080b-4cbf-b924-01769bf11291","order_by":5,"name":"Zhiqiang HE","email":"","orcid":"","institution":"Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhiqiang","middleName":"","lastName":"HE","suffix":""},{"id":481149986,"identity":"c3da4917-1a55-4b93-8f95-bd4034d2adf5","order_by":6,"name":"Liyun ZHANG","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYDACCRBRACKZDzAwNjAwGBCnxQBEsiWQpAVE8BgQp0V+dvOzh18MLBI33O75/Jl3h7WcOQPzw0c3GOzycGlhnHPM3FjGQCJxw52z2yRnnkk3tmxgMzbOYUguxqWFWSLBTFoCpOVG7jaGj22HEzcc4GGTzmE4kNiAQwubRPo3qJacxx8S2w7XE9TCI5FjJvkBooVBAmhLggEhLRISOWXSwEA2nnkjzQzkF8MNh0F+MUjGqUV+Rvo2yR8VdbJ9N5Ifg0JM3uB488PHORV2OLWAg4CHgcERqoAZjAjGDuMPBgZ7mHb8SkfBKBgFo2BEAgA20la2L4sV8AAAAABJRU5ErkJggg==","orcid":"","institution":"Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital","correspondingAuthor":true,"prefix":"","firstName":"Liyun","middleName":"","lastName":"ZHANG","suffix":""}],"badges":[],"createdAt":"2025-06-26 11:38:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6983104/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6983104/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86218371,"identity":"e352870c-b131-4944-be35-7d2642140d81","added_by":"auto","created_at":"2025-07-08 06:29:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":387918,"visible":true,"origin":"","legend":"\u003cp\u003eMultivariate Logistic Regression Analysis of Factors Associated with Termination\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6983104/v1/6f5f470b94d4185288343e2f.png"},{"id":99315782,"identity":"09ea2280-250d-4579-8d03-892c4a51e16d","added_by":"auto","created_at":"2025-12-31 16:27:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1228061,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6983104/v1/267829ac-0129-4c65-93ba-d1e0e4dad476.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAnalysis of the frequency characteristics and reasons for termination of clinical trials in Systemic Lupus Erythematosus: based on the Clinical Trial. gov database\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSystemic Lupus Erythematosus (SLE) is a chronic autoimmune disease characterized by the immune system's erroneous attack on multiple organs and systems of the body, leading to inflammation and tissue damage\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The global incidence of SLE ranges from 20 to 70 cases per 100,000 individuals, with a predilection for women of childbearing age\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The clinical manifestations of SLE are diverse and complex, including joint pain, skin rashes, fatigue, and renal impairment, which significantly impair the quality of life of affected individuals\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Currently, the management of SLE focuses on symptom relief and reduction of disease activity, as there is no known cure. Treatment options encompass nonsteroidal anti-inflammatory drugs, antimalarials, corticosteroids, and immunosuppressants\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. However, the efficacy and safety of available treatments are limited, leaving many patients without adequate disease control\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eClinical trials are a pivotal component of medical research, essential for the development and validation of new therapeutic approaches. Yet, clinical trials have a high rate of failure, with approximately 85% of drug development trials not meeting their primary endpoints\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. In the context of SLE, the termination of clinical trials not only diminishes treatment options but also has a profound impact on the quality of life and disease outcomes for patients\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Previous studies have identified a multitude of reasons for the discontinuation of clinical trials, including safety concerns, insufficient efficacy, funding issues, and recruitment challenges\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Understanding these reasons is crucial for optimizing clinical trial design, enhancing research efficiency, and minimizing the waste of resources. While general reasons for clinical trial termination have been explored, a specific analysis focused on SLE is lacking. This study aims to analyze the reasons for the termination of SLE clinical trials and to investigate how improvements in study design and execution strategies can increase the success rate of clinical trials. By analyzing data from ClinicalTrials.gov, the U.S. registry of clinical trials, we intend to provide valuable insights for the advancement of SLE treatment research, thereby facilitating the development of more effective and safer therapeutic interventions.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eThis article is designed for retrospective data analysis. As this study does not involve any commercial interests, and the data in the database does not include any private information of the research subjects, it has been granted an exemption from ethical review by the Shanxi Bethune Hospital for Clinical Research Ethics Committee (LYLL-MC-2025-001). Clinical trial number: not applicable.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Data Filtering\u003c/h2\u003e\u003cp\u003eThis study draws upon data from the ClinicalTrials.gov registry, administered by the National Library of Medicine at the National Institutes of Health in the United States, as its primary source of information. ClinicalTrials.gov, administered by the National Library of Medicine (NLM) within the National Institutes of Health (NIH) in the United States, is recognized as the preeminent global registry, encompassing the most extensive and diverse array of clinical research studies. Search Strategy: In the \"Condition or Disease\" field, the search terms \"Systemic Lupus Erythematosus\" \"Lupus Nephritis\" \"Lupus Erythematosus\" \"Cutaneous Lupus Erythematosus\" \"Lupus\" \"Discoid Lupus Erythematosus\" and \"Disseminated Lupus Erythematosus\" were entered. The \"Study Start Date\" was set to range from the inception of the database to May 31, 2024. The \"Study Type\" was specified as \"Interventional\". The \"Study Status\" was filtered to include only \"COMPLETED\" and \"TERMINATED\" studies. Following this screening process, a total of 499 clinical trials met the criteria.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Data Extraction\u003c/h2\u003e\u003cp\u003eThe clinical trials data obtained from ClinicalTrials.gov was downloaded in a Tab-separated values format and subsequently merged using Microsoft Office Excel 2019. The final data extraction yielded the following information: Registration Number, Trial Title, Trial Status, Study Results, Intervention(s), Outcome Measures, Sponsor, Trial Phase, Study Design, Funding Source, Number of Participants, Participant Gender, Age, Registration Date, and Registration Region.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Operational Definitions\u003c/h2\u003e\u003cp\u003eTo facilitate analysis, the research team grouped the data extracted from the ClinicalTrials.gov website and established the following definitions:\u003c/p\u003e\u003cp\u003eIntervention: Types are categorized as follows: Drug/Biological, Device/Procedure, Other (including Behavioral, Dietary supplement, Genetic, Radiation, Diagnostic tests and others).\u003c/p\u003e\u003cp\u003ePrimary purpose: Interventions or treatment (including Treatment, prevention), Health services and diagnosis (including Health service research, diagnostic, and screening), other including (basic science, supportive care and others)\u003c/p\u003e\u003cp\u003eStudy Phases are defined as: Phase I, which includes all studies prior to Phase I; Phase II, encompassing Phase I/II and Phase II studies; and Phase III, including Phase II/III and Phase III studies.\u003c/p\u003e\u003cp\u003ePrimary Sponsoring Organizations are categorized as: the National Institutes of Health (NIH) or other U.S. federal government agencies, Industry, and Other (including individuals, academic institutions, and social organizations).\u003c/p\u003e\u003cp\u003eIn study design, the allocation is defined as Randomized (Yes or No); Blinding (Yes or No), which is used to indicate whether the blinding is applied to trial participants, researchers, care providers, and outcome assessors.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Data Analysis\u003c/h2\u003e\u003cp\u003eCategorical data are presented as frequencies (%), continuous variables as median (IQR) or mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Group comparisons used chi-square/Fisher's exact tests. Predictors of termination were identified by multivariable logistic regression (adjusted ORs with 95% CIs), visualized via forest plot (SPSS 25.0). Model fit was assessed using Hosmer-Lemeshow test (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Significance level was P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (two-tailed).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Categorization of Reasons for Termination\u003c/h2\u003e\u003cp\u003eThe reasons for study termination were obtained from the \"Why Study Stopped\" column as indicated from the Researcher View column and classified into one of the following categories. The general classification of reasons for trial termination draws upon a prior research study\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eReasons included: (1) Scientific data from the trial; (2) Insufficient accrual rate; (3) Unspecified business decision/strategic reason; (4) Trial administration or conduct (issues with protocol, investigators, site, etc.); (5) External information (results from other trials, competing trials, or changes in standard of care); (6) Funding; (7) Product withdrawal; (8) Lack of drug supply (other than drug withdrawal); (9) Other (e.g., uninformative or non-specific text); (10) Termination Reason Not Provided.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe study analyzed 490 SLE clinical trials, of which 388 (79.2%) were completed and 102 (20.8%) were terminated. Various primary and secondary trial characteristics, as well as reasons for termination, were evaluated to identify factors associated with trial discontinuation.\u003c/p\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Characteristics of Completed and Terminated Trials\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that the termination rate varied based on intervention type, trial phase, and primary purpose, with the following significant findings. In terms of Intervention Type, although not statistically significant (χ\u0026sup2;=5.24, P\u0026thinsp;=\u0026thinsp;0.073), drug/biological trials had a higher proportion of termination (86.27%) compared to other types, such as device/procedure (5.88%) and other interventions (7.84%). And, a significant association was observed between trial phase and termination risk (χ\u0026sup2;=18.70, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Phase III trials had the highest termination rate (33.33%), followed by Phase II (29.41%) and Phase I (21.57%). Notably, Phase IV trials were less likely to be terminated (3.92%). Besides, trials with a primary purpose of \"interventions or treatment\" were more likely to be terminated (97.06%) compared to \"health services and diagnosis\" (0.98%) and \"other\" purposes (1.96%), with a statistically significant association (χ\u0026sup2;=9.51, P\u0026thinsp;=\u0026thinsp;0.009).\u003c/p\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, secondary characteristics, including sex eligibility, age group, and intervention model, were analyzed. Although most trials were open to all sexes (88.78%), this variable was not significantly associated with termination (P\u0026thinsp;=\u0026thinsp;0.502). And, there was no significant association between age group eligibility and trial termination (χ\u0026sup2;=4.00, P\u0026thinsp;=\u0026thinsp;0.406). Most trials included adults and older adults (74.08%). Trials with a parallel intervention model accounted for the highest proportion of terminated trials (72.55%). However, the difference in intervention model types did not reach statistical significance (P\u0026thinsp;=\u0026thinsp;0.103).\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\u003ePrimary characteristics of completed and terminated SLE clinical trials\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\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;490)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCompleted\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;388)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTerminated\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;102)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStatistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntervention Type\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\u003cp\u003eχ\u0026sup2;=5.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrug/Biological\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e394 (80.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e306 (78.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e88 (86.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDevice/Procedure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23 (4.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 (4.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (5.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73 (14.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65 (16.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (7.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhase\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\u003cp\u003eχ\u0026sup2;=18.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhase Ⅰ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e101 (20.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79 (20.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (21.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhase Ⅱ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e166 (33.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e136 (35.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (29.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhase Ⅲ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84 (17.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50 (12.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34 (33.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhase Ⅳ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37 (7.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (8.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (3.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot Provided\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e102 (20.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90 (23.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (11.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFunder Type\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\u003cp\u003eχ\u0026sup2;=2.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.361\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNIH/Fed/Other Gov\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31 (6.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (6.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (4.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndustry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e239 (48.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e183 (47.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56 (54.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\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\u003e220 (44.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e179 (46.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41 (40.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAllocation\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\u003cp\u003eχ\u0026sup2;=3.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.178\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRandomized\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e338 (68.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e265 (68.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73 (71.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone Randomized\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59 (12.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (13.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (6.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e93 (18.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e71 (18.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (21.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMasking\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\u003cp\u003eχ\u0026sup2;=0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.941\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlinded\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e261 (53.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e207 (53.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54 (52.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e229 (46.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e181 (46.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48 (47.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary Purpose\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\u003cp\u003eχ\u0026sup2;=9.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInterventions or Treatment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e433 (88.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e334 (86.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99 (97.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth Services and Diagnosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (5.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (6.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32 (6.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (7.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eχ\u0026sup2;: Chi-square test; \u003csup\u003ea\u003c/sup\u003e: Other include Behavioral, Dietary supplement, genetic, radiation, diagnostic tests and others. \u003csup\u003eb\u003c/sup\u003e: Other included basic science, supportive care and others.\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\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\u003e Secondary characteristics of completed and terminated SLE clinical trials\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\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;490)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCompleted\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;388)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTerminated\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;102)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStatistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex Eligibility\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\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.502\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (1.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (1.29)\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\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\u003e50 (10.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42 (10.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (7.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e435 (88.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e341 (87.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94 (92.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge Group\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\u003cp\u003eχ\u0026sup2;=4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.406\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62 (12.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53 (13.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (8.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdult/ Older Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e363 (74.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e282 (72.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e81 (79.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChild/Adult/Older Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33 (6.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (6.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (7.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChild/ Adult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28 (5.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (6.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (2.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChild\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (0.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (0.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntervention Model\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\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.103\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle Group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e138 (28.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e111 (28.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (26.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParallel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e319 (65.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e245 (63.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e74 (72.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSequential\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (2.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (2.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCrossover\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (2.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (3.61)\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFactorial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (1.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (1.80)\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eχ\u0026sup2;: Chi-square test, -: Fisher exact;\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=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Categorization of Reasons for Termination\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e outlines the reasons for trial termination, with the most common causes being \"insufficient accrual rate\" (28.4%) and \"scientific data from the trial\" (28.4%). Other reasons included unspecified business or strategic decisions (8.8%), external information (4.9%), trial administration or conduct issues (4.9%), and COVID-19 (2.9%).\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\u003eCategorization of Reasons for Trial Termination\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTermination Reason Category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber (Percentage of Trials)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal terminated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e102 (100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsufficient accrual rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29 (28.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScientific data from the trial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29 (28.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnspecified business decision/strategic reason\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (8.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExternal information\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (4.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrial administration or conduct\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (4.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther (uninformative or non-specific text)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (3.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCOVID-19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (2.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFunding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (2.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLack of drug supply\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot provided\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (13.7)\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=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Factors Associated with Termination\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays the results of the multivariate logistic regression analysis, identifying factors significantly associated with trial termination. Trials involving non-drug/biological interventions, including behavioral, dietary supplements, and genetic interventions, had a significantly lower termination risk (OR\u0026thinsp;=\u0026thinsp;0.43, 95%CI: 0.20\u0026ndash;0.93, P\u0026thinsp;=\u0026thinsp;0.031) compared to drug/biological trials. Phase III trials exhibited a significantly higher risk of termination (OR\u0026thinsp;=\u0026thinsp;1.99, 95%CI: 1.04\u0026ndash;3.82, P\u0026thinsp;=\u0026thinsp;0.037) compared to Phase I trials. Trials that did not specify their phase also trended towards reduced termination risk (OR\u0026thinsp;=\u0026thinsp;0.48, 95%CI: 0.22\u0026ndash;1.03, P\u0026thinsp;=\u0026thinsp;0.059). Trials with primary purposes other than \"interventions or treatment\", specifically those categorized as \"health services and diagnosis\" and \"other\", showed reduced termination risks, with odds ratios of 0.14 (95%CI: 0.02\u0026ndash;1.05, P\u0026thinsp;=\u0026thinsp;0.056) and 0.22 (95%CI: 0.05\u0026ndash;0.96, P\u0026thinsp;=\u0026thinsp;0.044), respectively.\u003c/p\u003e\u003cp\u003eThis analysis suggests that the type of intervention, trial phase, and primary purpose are critical factors in SLE trial termination, with drug/biological interventions, Phase III trials, and trials focused on treatment interventions showing increased risks for discontinuation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study analyzed the characteristics and reasons for termination of SLE clinical trials, revealing potential associations between specific trial attributes and termination risk. The findings integrate data from Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e on basic trial characteristics, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e on sponsor-reported reasons for termination, and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e on multivariate regression analysis, providing multidimensional insights into factors driving SLE trial discontinuation.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTrial Phase and Termination Risk\u003c/b\u003e\u003c/p\u003e\u003cp\u003eResults indicate that Phase III trials have a significantly higher risk of termination compared to Phase I trials (OR\u0026thinsp;=\u0026thinsp;1.99, 95%CI: 1.04\u0026ndash;3.82, P\u0026thinsp;=\u0026thinsp;0.037). This finding aligns with expectations, as Phase III trials typically involve larger patient cohorts, extended timelines, and higher costs, which increase resource demands and uncertainty.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Moreover, the elevated termination rate in Phase III trials may reflect challenges in trial management and operational complexity, consistent with findings in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, where \"insufficient accrual rate\" accounted for 28.4% of terminations. On one hand, Phase III trials are often conducted across multiple sites to obtain representative data, which complicates coordination and management. Multi-center designs, while expanding patient recruitment, present challenges related to personnel allocation, data consistency, and ethical oversight. These added layers of trial complexity may hinder trial continuity.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e On the other hand, the small target population of SLE, coupled with stringent inclusion criteria, complicates recruitment efforts. Phase III trials demand high patient enrollment, which extends recruitment timelines and escalates costs, further raising the likelihood of trial termination.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImpact of Intervention Type and Primary Purpose on Termination\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn terms of intervention type, non-drug/biological trials (including behavioral, dietary supplements, and genetic interventions) showed a significantly lower risk of termination compared to drug/biological trials (OR\u0026thinsp;=\u0026thinsp;0.43, 95%CI: 0.20\u0026ndash;0.93, P\u0026thinsp;=\u0026thinsp;0.031). This finding suggests that drug/biological trials, which typically face higher standards of safety and efficacy verification, encounter increased termination risks due to the stringent regulatory expectations associated with these interventions.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Drug and biological trials require multi-phase clinical assessments, progressively expanding sample sizes to validate efficacy and safety. Such trials are inherently more complex, with higher associated costs and a greater dependency on robust data, particularly in chronic disease research, where adverse events or lack of efficacy can lead to early termination.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Non-drug interventions, such as behavioral interventions and dietary supplements, have relatively lower safety risks and greater trial design flexibility compared to drug-based interventions. Behavioral intervention trials are less affected by the complexities of drug metabolism or interactions, allowing for more straightforward assessments of patient outcomes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDetailed Analysis of Termination Reasons\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicates that \"insufficient accrual rate\" (28.4%) and \"scientific data\" (28.4%) were leading causes of termination in SLE trials. Recruitment challenges are particularly common in trials for chronic,\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e low-prevalence conditions such as SLE, where patient populations are small and enrollment criteria stringent. Additionally, the heterogeneous nature of SLE symptoms and fluctuating disease course may further complicate recruitment and retention. At the same time, in trials for diseases with variable disease courses like SLE, efficacy data may fluctuate, making it difficult to achieve consistent statistical outcomes. For early-phase clinical trials, the lack of reliable biomarkers can indeed contribute to lower data quality and may increase the likelihood of trial termination. As the absence of validated biomarkers can hinder efforts to monitor therapeutic effects accurately, leading to challenges in justifying the continuation of the trial if initial results do not meet efficacy or safety benchmarks.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e In addition, business or strategic decisions accounted for 8.8% of terminations, suggesting that some trials were terminated not for scientific reasons but due to resource allocation or market strategies. Although the multivariate analysis did not find a statistically significant association with funding source (P\u0026thinsp;=\u0026thinsp;0.364), industry-sponsored trials exhibited a marginally higher termination rate than those funded by government or other sources. This trend may reflect the influence of business priorities or resource constraints on trial sustainability.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eInfluence of Randomization, Blinding, and Trial Design\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDespite the role of randomization and blinding in reducing bias, this study did not observe a significant effect of these factors on termination risk. The presence or absence of randomization and blinding did not show notable differences between terminated and completed trials. Additionally, while parallel-group design trials accounted for a slightly higher proportion of terminated trials (72.55%), regression analysis found no statistically significant association (P\u0026thinsp;=\u0026thinsp;0.103), suggesting that in SLE trials, design factors may play a limited role in trial sustainability compared to external management or resource issues. Parallel-group and randomized controlled trials typically require larger patient enrollment, longer observation periods, and stricter trial conditions. Although randomization and blinding enhance data reliability, they also incur high execution and monitoring costs, which may indirectly contribute to trial termination risks.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Recently, some trials have adopted adaptive designs or simplified randomization to enhance flexibility. Adaptive designs allow for interim evaluations, enabling researchers to adjust sample sizes or interventions dynamically, thus lowering termination risks.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e This approach is especially useful for chronic diseases like SLE that benefit from adaptable study frameworks.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImplications of Clinical Trial Termination Rates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe high termination rate in SLE trials not only impacts patient treatment expectations but also results in considerable resource wastage. This study suggests that clinical trial design for rare diseases like SLE must strike a balance between scientific rigor and operational feasibility to mitigate termination risks. Flexible patient recruitment strategies, careful selection of trial phases, and clearly defined scientific objectives can contribute to trial completion. Future studies could explore more flexible patient recruitment methods such as decentralized methods,\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e multi-regional screening and remote monitoring, to broaden enrollment scope. Through strategic trial planning, cost reduction, and resource allocation, trials may more effectively reduce termination risks. Furthermore, increased collaboration between funding agencies, research centers, and industry could support trial sustainability. For example, establishing shared research resources and information platforms can help address resource limitations and asymmetries that often lead to termination. Additionally, promoting joint funding from multiple sources could further minimize the commercial impact on trial sustainability.\u003c/p\u003e"},{"header":"5. Limitation","content":"\u003cp\u003eThis study has several limitations. The analysis relied on publicly available data from ClinicalTrials.gov, which may lack detailed information on trial execution and context-specific factors influencing termination. Besides, variability in how sponsors document reasons for trial termination may introduce inconsistencies and affect the accuracy of the classification. Future studies could avoid these factors, making the analysis more comprehensive.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis study highlights critical factors driving the termination of systemic lupus erythematosus (SLE) clinical trials, providing valuable insights for future research. Phase III trials exhibited a higher risk of termination, driven by their operational complexity, extensive resource demands, and recruitment challenges. Similarly, drug/biological interventions demonstrated increased termination risks, reflecting the stringent efficacy and safety requirements inherent in their development. Addressing these challenges requires implementing innovative strategies. Adaptive trial designs allow for flexibility in trial execution, while decentralized recruitment methods and multi-regional screening can expand patient pools. Collaborative funding mechanisms that integrate public, private, and academic resources could mitigate financial constraints, fostering trial sustainability. Achieving a balance between scientific rigor and practical feasibility is essential for advancing SLE research. Optimizing trial designs, recruitment strategies, and funding structures will enhance trial completion rates, thereby accelerating the development of effective and safe treatments for SLE.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Shanxi Province Clinical Research Center for Dermatologic and Immunologic Diseases（Rheumatic diseases), Research and Innovation Team Project for Scientific Breakthroughs at Shanxi Bethune Hospital（2024AOXIANG02）and Science Fundation of Shanxi Bethune Hospital in China (2022YH10).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDeclaration of Conflicting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared no potential conflicts of interest concerning this article\u0026apos;s research, authorship, and/or publication.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eLina BAI was primarily responsible for conceptualizing the study, conducted the initial manuscript, methodology, and analyzing the data. Yanli YANG reviewed and edit the initial manuscript. Qianyu GUO and Li ZHAO contributed to data curation, and Junkang ZHAO contributed to software and methodology. Zhiqiang HE and Liyun ZHANG supervised the overall study design, provided critical guidance throughout the research process, and is the co-corresponding author. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHochberg MC. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Letter. \u003cem\u003eArthritis and rheumatism\u003c/em\u003e. Sep 1997;40(9):1725-1725. doi:10.1002/art.1780400928\u003c/li\u003e\n\u003cli\u003ePetri M, Orbai A-M, Alarcon GS, et al. Derivation and validation of the systemic lupus international collaborating clinics classification criteria for systemic lupus erythematosus. Article. \u003cem\u003eArthritis and rheumatism\u003c/em\u003e. Aug 2012;64(8):2677-2686. doi:10.1002/art.34473\u003c/li\u003e\n\u003cli\u003eBertsias GK, Ioannidis JPA, Aringer M, et al. EULAR recommendations for the management of systemic lupus erythematosus with neuropsychiatric manifestations: report of a task force of the EULAR standing committee for clinical affairs. \u003cem\u003eAnnals of the Rheumatic Diseases\u003c/em\u003e. 2010;69(12):2074-2082. doi:10.1136/ard.2010.130476\u003c/li\u003e\n\u003cli\u003eMorand EF, Fernandez-Ruiz R, Blazer A, Niewold TB. Advances in the management of systemic lupus erythematosus. \u003cem\u003eBMJ\u003c/em\u003e. 2023;383:e073980. doi:10.1136/bmj-2022-073980\u003c/li\u003e\n\u003cli\u003eKandane-Rathnayake R, Louthrenoo W, Hoi A, et al. \u0026apos;Not at target\u0026apos;: prevalence and consequences of inadequate disease control in systemic lupus erythematosus-a multinational observational cohort study. \u003cem\u003eArthritis Res Ther\u003c/em\u003e. Mar 14 2022;24(1):70. doi:10.1186/s13075-022-02756-3\u003c/li\u003e\n\u003cli\u003eHay M, Thomas DW, Craighead JL, Economides C, Rosenthal J. Clinical development success rates for investigational drugs. Article. \u003cem\u003eNature Biotechnology\u003c/em\u003e. Jan 2014;32(1):40-51. doi:10.1038/nbt.2786\u003c/li\u003e\n\u003cli\u003eBriel M, Williams RJ, Tse T, DiPiazza K, Zarin DA. Terminated Trials in the ClinicalTrials.gov Results Database: Evaluation of Availability of Primary Outcome Data and Reasons for Termination. \u003cem\u003ePlos One\u003c/em\u003e. 2015;10(5)doi:10.1371/journal.pone.0127242\u003c/li\u003e\n\u003cli\u003eHwang TJ, Carpenter D, Lauffenburger JC, Wang B, Franklin JM, Kesselheim AS. Failure of Investigational Drugs in Late-Stage Clinical Development and Publication of Trial Results. \u003cem\u003eJAMA Intern Med\u003c/em\u003e. Dec 1 2016;176(12):1826-1833. doi:10.1001/jamainternmed.2016.6008\u003c/li\u003e\n\u003cli\u003eHuo BN, Ai ML, Jia YT, et al. General characteristics and reasons for the discontinuation of drug clinical trials in mainland China. \u003cem\u003eBMC Med Res Methodol\u003c/em\u003e. Nov 13 2021;21(1):246. doi:10.1186/s12874-021-01443-2\u003c/li\u003e\n\u003cli\u003ePak TR, Rodriguez MD, Roth FP. Why clinical trials are terminated. \u003cem\u003ebioRxiv\u003c/em\u003e. 2015:021543. doi:10.1101/021543\u003c/li\u003e\n\u003cli\u003eDiMasi JA, Grabowski HG, Hansen RW. Innovation in the pharmaceutical industry: New estimates of R\u0026amp;D costs. \u003cem\u003eJ Health Econ\u003c/em\u003e. May 2016;47:20-33. doi:10.1016/j.jhealeco.2016.01.012\u003c/li\u003e\n\u003cli\u003ePaul SM, Mytelka DS, Dunwiddie CT, et al. How to improve R\u0026amp;D productivity: the pharmaceutical industry\u0026apos;s grand challenge. \u003cem\u003eNat Rev Drug Discov\u003c/em\u003e. Mar 2010;9(3):203-14. doi:10.1038/nrd3078\u003c/li\u003e\n\u003cli\u003eHwang TJ, Carpenter D, Lauffenburger JC, Wang B, Franklin JM, Kesselheim AS. Failure of Investigational Drugs in Late-Stage Clinical Development and Publication of Trial Results. \u003cem\u003eJAMA Internal Medicine\u003c/em\u003e. 2016;176(12):1826-1833. doi:10.1001/jamainternmed.2016.6008\u003c/li\u003e\n\u003cli\u003eWilliams RJ, Tse T, DiPiazza K, Zarin DA. Terminated Trials in the ClinicalTrials.gov Results Database: Evaluation of Availability of Primary Outcome Data and Reasons for Termination. \u003cem\u003ePLOS ONE\u003c/em\u003e. 2015;10(5):e0127242. doi:10.1371/journal.pone.0127242\u003c/li\u003e\n\u003cli\u003eDancey JE, Dobbin KK, Groshen S, et al. Guidelines for the Development and Incorporation of Biomarker Studies in Early Clinical Trials of Novel Agents. \u003cem\u003eClinical Cancer Research\u003c/em\u003e. 2010;16(6):1745-1755. doi:10.1158/1078-0432.Ccr-09-2167\u003c/li\u003e\n\u003cli\u003eKhunger M, Rakshit S, Hernandez AV, et al. Premature Clinical Trial Discontinuation in the Era of Immune Checkpoint Inhibitors. \u003cem\u003eThe Oncologist\u003c/em\u003e. 2018;23(12):1494-1499. doi:10.1634/theoncologist.2018-0003\u003c/li\u003e\n\u003cli\u003eDijkgraaf MGW, Haukoos J, Itani KMF. Practical Guide to Design Choice of Randomized Clinical Trials in Surgery. \u003cem\u003eJAMA Surg\u003c/em\u003e. Dec 1 2022;157(12):1154-1155. doi:10.1001/jamasurg.2022.4889\u003c/li\u003e\n\u003cli\u003eJulie CL, Niteesh KC, Massimiliano R, Robert JG, Steffen V, Lorenzo T. Designing and conducting adaptive trials to evaluate interventions in health services and implementation research: practical considerations. \u003cem\u003eBMJ Medicine\u003c/em\u003e. 2022;1(1):e000158. doi:10.1136/bmjmed-2022-000158\u003c/li\u003e\n\u003cli\u003eKaizer AM, Belli HM, Ma Z, et al. Recent innovations in adaptive trial designs: A review of design opportunities in translational research. \u003cem\u003eJournal of Clinical and Translational Science\u003c/em\u003e. 2023;7(1):e125. e125. doi:10.1017/cts.2023.537\u003c/li\u003e\n\u003cli\u003eMiyata BL, Tafuto B, Jose N. Methods and perceptions of success for patient recruitment in decentralized clinical studies. \u003cem\u003eJ Clin Transl Sci\u003c/em\u003e. 2023;7(1):e232. doi:10.1017/cts.2023.643\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":"Systemic Lupus Erythematosus, clinical trial, termination reason","lastPublishedDoi":"10.21203/rs.3.rs-6983104/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6983104/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eSystemic Lupus Erythematosus (SLE) is a complex autoimmune disease with limited treatment options. Clinical trials play a crucial role in developing therapies; however, SLE trials often face high termination rates, hindering advancements in patient care.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eThis study aims to analyze the characteristics and reasons for the termination of SLE clinical trials and to provide insights into strategies for improving trial sustainability and success.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eUsing data from ClinicalTrials.gov, 490 SLE clinical trials, including 388 completed and 102 terminated trials, were evaluated. Trial characteristics such as intervention type, trial phase, funding source, and reasons for termination were analyzed using descriptive and multivariate regression analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eTermination rates were significantly associated with trial phase, intervention type, and primary purpose. Phase III trials exhibited the highest termination risk (OR\u0026thinsp;=\u0026thinsp;1.99, P\u0026thinsp;=\u0026thinsp;0.037). Drug/biological trials had a higher likelihood of termination compared to non-drug interventions (OR\u0026thinsp;=\u0026thinsp;0.43, P\u0026thinsp;=\u0026thinsp;0.031). Recruitment challenges and insufficient accrual rates were leading causes of termination, while adaptive trial designs and innovative recruitment methods showed potential to mitigate these risks.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eSLE clinical trials face unique challenges, with high termination rates driven by operational and design complexities. Strategies such as adaptive designs, decentralized recruitment, and collaborative funding could improve trial sustainability, advancing the development of effective treatments for SLE.\u003c/p\u003e","manuscriptTitle":"Analysis of the frequency characteristics and reasons for termination of clinical trials in Systemic Lupus Erythematosus: based on the Clinical Trial. gov database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-08 06:21:54","doi":"10.21203/rs.3.rs-6983104/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":"054548e8-6c43-4269-8b94-b5ebd595af54","owner":[],"postedDate":"July 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51167488,"name":"Health sciences/Diseases"},{"id":51167489,"name":"Biological sciences/Immunology"},{"id":51167490,"name":"Health sciences/Medical research"},{"id":51167491,"name":"Health sciences/Rheumatology"}],"tags":[],"updatedAt":"2025-12-29T06:38:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-08 06:21:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6983104","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6983104","identity":"rs-6983104","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}