Assessing the degree to which randomized controlled trials align with the core outcome set for osteoarthritis of knee and hip: A cross-sectional analysis.

OBJECTIVE: To assess the degree of core outcome set alignment and identify issues with alignment to the 2019 COS among clinical trial registrations focused on knee and/or hip osteoarthritis (OA). METHODS: Our search was performed on registered knee and hip OA randomized controlled trials (RCTs) available on ClinicalTrials.gov and WHO International Clinical Trials Registry Platform. The screening process considered trials registered between 8/2014 and 6/2023. We extracted data on general trial characteristics and the five trial endpoints detailed in the COS (pain, physical function, quality of life, patient global assessment, and adverse events), in a masked and duplicate manner. The frequencies of COS alignment were assessed over time prior to and after COS publication. RESULTS: Of the 10,718 RCTs screened, 481 met inclusion criteria. Most were phase 3 (368/481, 76.51%) and heavily university-funded (184/481, 38.25%). Despite the 2019 COS, no marked enhancement in overall alignment was noted. The outcome 'Pain' exhibited the highest degree of COS alignment (455/481, 94.59%), whereas 'adverse events' lagged behind (89/481, 18.50%). Additionally, trial factors such as 'Continent', 'Funding Type', and 'Recruitment Status' displayed no significant influence on COS alignment. CONCLUSIONS: Despite the acknowledged advantages of using COS in RCTs and the availability of an updated COS, the alignment to these outcomes remains notably low. Significant efforts are needed to encourage broader adoption in future studies on knee and hip OA, with the aim of improving research quality and patient care.

Identifying trials run in India that are registered in other clinical trial registries: a cross-sectional study.

BACKGROUND: Clinical trials play a crucial role in biomedical research, and it is important to register them in public registries to ensure transparency and prevent research waste. In this study, we wished to determine what steps need to be taken to identify every clinical trial run in India that has been registered in any of the (non-Indian) World Health Organization-recognised primary registries. Of the 16 registries, we studied all except that of the European Union, which will be studied separately. METHODS: Two methodologies were employed for each registry, except for four that did not facilitate one or the other method. Methodology A involved downloading all the records in a registry and querying them. Methodology B involved conducting a search via the registry website. RESULTS: Only four registries provided consistent results with both methodologies. Seven registries had different results from the two methodologies. Of these, in four cases, in Methodology A one field indicated that the study ran in India, while another indicated otherwise. CONCLUSIONS: The above-mentioned ambiguities should be addressed by the concerned registries. Overall, this study reinforces the need for improved data accuracy and transparency in clinical trial registries and emphasizes the importance of resolving complications faced by users while navigating the registries. Ensuring accurate and comprehensive registration of clinical trials is essential for meta-research and the use of such data by a variety of stakeholders.

Reporting of clinical trial safety results in ClinicalTrials.gov for FDA-approved drugs: A cross-sectional analysis.

BACKGROUND: Adverse events identified during clinical trials can be important early indicators of drug safety, but complete and timely data on safety results have historically been difficult to access. The aim was to compare the availability, completeness, and concordance of safety results reported in ClinicalTrials.gov and peer-reviewed publications. METHODS: We analyzed clinical trials used in the Food and Drug Administration safety assessment of new drugs approved between 1 July 2018 and 30 June 2019. The key safety outcomes examined were all-cause mortality, serious adverse events, adverse events, and withdrawals due to adverse events. Availability of safety results was measured by the presence and timing of a record of trial-level results in ClinicalTrials.gov and a corresponding peer-reviewed publication. For the subset of trials with available results, completeness was defined as the reporting of safety results for all participants and compared between ClinicalTrials.gov and publications. To assess concordance, we compared the numeric results for safety outcomes reported in ClinicalTrials.gov and publications to results in Food and Drug Administration trial reports. RESULTS: Among 156 trials studying 52 drugs, 91 (58.3%) trials reported safety results in ClinicalTrials.gov and 106 (67.9%) in peer-reviewed publications (risk difference = -9.6%, 95% confidence interval = -20.3 to 1.0). All-cause mortality was reported sooner in published articles compared with ClinicalTrials.gov (log-rank test, p = 0.01). There was no difference in time to reporting for serious adverse events (p = 0.05), adverse events (p = 0.09), or withdrawals due to adverse events (p = 0.20). Complete reporting of all-cause mortality was similar in ClinicalTrials.gov and publications (74.7% vs 78.3%, respectively; risk difference = -3.6%, 95% confidence interval = -15.5 to 8.3) and higher in ClinicalTrials.gov for serious adverse events (100% vs 79.2%; risk difference = 20.8%, 95% confidence interval = 13.0 to 28.5) and adverse events (100% vs 86.8%; risk difference = 13.2%, 95% confidence interval = 6.8 to 19.7). Withdrawals due to adverse events were less often completely reported in ClinicalTrials.gov (62.6% vs 92.5%; risk difference = -29.8%, 95% confidence interval = -40.1 to -18.7). No difference was found in concordance of results between ClinicalTrials.gov and publications for all-cause mortality, serious adverse events, or withdrawals due to adverse events. CONCLUSION: Safety results were available in ClinicalTrials.gov at a similar rate as in peer-reviewed publications, with more complete reporting of certain safety outcomes in ClinicalTrials.gov. Future efforts should consider adverse event reporting in ClinicalTrials.gov as an accessible data source for post-marketing surveillance and other evidence synthesis tasks.

Updated analysis of pediatric clinical studies registered in ClinicalTrials.gov, 2008-2019.

BACKGROUND: Since the national clinical trials registry ( ClinicalTrials.gov ) launched in February 2000, more than 360,000 research studies in the United States and over 200 countries have registered. As the characteristics of pediatric clinical studies keep changing over time and the results-reporting mechanism is under evolving, to know about the relevant updates of data elements and the effect of policies on the quality of reporting results is significant. METHODS: In this research, 53,060 clinical studies related to children registered from January 2008 to December 2019 were downloaded from ClinicalTrials.gov on August 1st, 2020. Different types of studies and critical categorical variables were identified, based on which, Cochran-Armitage test was performed to explore temporal trend of study characteristics and common pediatric clinical conditions in four time subsets. Further, to examine heterogeneity among subgroups (funding sources, funding sites, pediatric clinical conditions,etc), chi-squared test was applied. RESULTS: A total of 36,136 clinical trials and 16,692 observational studies were identified during the study period. The pediatric clinical trials increased from 7,029 (January 2008-December 2010) to 11,738 (January 2017-December 2019). The number of missing data has declined, with the maximum extent decline from 3.7 to 0.0% (Z = - 15.90, p <  0.001). Drug trials decreased from 48.8 to 28.9% (Z = - 24.68, p <  0.001). Behavioral trials, on the other hand, increased from 12.6 to 20.4% (Z = 12.28, p <  0.001). Most pediatric clinical trials were small-scale (58.9% enrolling 1-100 participants), single-site (61.4%) and funded neither by industry nor by the NIH (59.2%). The proportion of reporting study results varied by study type (χ2 = 1,256.8, p <  0.001), lead sponsor (χ2 = 4,545.6, p <  0.001), enrollment (χ2 = 29.4, p <  0.001) and trial phase (χ2 = 218.8, p <  0.001). CONCLUSION: Pediatric clinical studies registered in ClinicalTrials.gov were dominated by small-scale interventional trials, containing significant heterogeneity in funding sources, funding sites, pediatric clinical conditions and study characteristics. Although the results database has evolved in the past decade, efforts to strengthen the practice of systematic reporting must be continued.

Infrequent use of clinical trials registries in published systematic reviews in urology.

OBJECTIVE: Validity of systematic reviews may be affected by non-publication of statistically non-significant or unfavorable clinical trial results. One function of clinical trial registries is to make these non-published studies available and thereby reduce potential publication bias. We aim to assess the use of clinical trial registries in published systematic reviews in urology. METHODS: We identified all systematic reviews published in the five highest-impact general urology journals that publish original research between January 1 and December 31, 2017. Full-text analysis was performed to determine if protocols included searching clinical trial registries meeting WHO Registry Network criteria. RESULTS: Of a total of 204 search results, 92 were included in the analysis as systematic reviews. The majority searched the MEDLINE (91, 98%), EMBASE (69, 75%), and Cochrane (49, 53%) databases. Based on published methods, only 16 (17%) systematic reviews searched any clinical trial registries: 14 (15%) ClinicalTrials.gov, 6 (6%) WHO International Clinical Trials Registry Platform, and 2 (2%) ISRCTN registry. Rates of searching clinical trial registries were low regardless of the journal: 8 of 34 (24%) in European Urology; 2 of 10 (20%) in BJU International; 3 of 17 (18%) in Urology; 2 of 18 (11%) in The Journal of Urology; and 1 of 13 (8%) in World Journal of Urology. CONCLUSION: The majority of recently published systematic reviews in urology do not routinely search clinical trial registries. Inclusion of these registries can help identify unpublished trial data, which may improve the quality of systematic reviews by reducing publication bias.

Trials that turn from retrospectively registered to prospectively registered: a cohort study of "retroactively prospective" clinical trial registration using history data.

BACKGROUND: Prospective registration of clinical trials is mandated by various regulations. However, clinical trial registries like ClinicalTrials.gov allow registry entries to be updated at any time, and key study elements, including the start date, may change before the first patient is enrolled. If a trial changes its start date after recruiting began, however, it may indicate a reason for concern. This study aimed to measure the rate of "retroactively prospective" trials. This refers to trials that are originally registered retrospectively, with the start date before the registration date, but that retroactively change their start date to be after the registration date, making them appear as if they were prospectively registered. METHODS: We retrieved clinical trial history data for all clinical trials registered on ClinicalTrials.gov with a first registration date in the year 2015 (N = 11,908). Using automated analyses, we determined the timepoints of registration in relation to the start date of the trial over time. For retroactively prospective trials and a set of control trials, we manually checked the accompanying publications to determine which start date they report and whether they report changes to the start date. RESULTS: We found 235 clinical trials to be retroactively prospective, comprising 2.0% of all clinical trials in our sample of 11,908 trials. Among the 113 retroactively prospective clinical trials with an accompanying publication, 12 (10.6%) explicitly stated in the publication that they had been prospectively registered. CONCLUSIONS: Retroactively prospective trial registration happens in one in 50 trials. While these changes to the start date could be mistakes or legitimate edits based on the most up-to-date information, they could also indicate a retrospectively registered trial that has been made to appear as a prospectively registered trial, which would lead to biases unapparent to reviewers. Our results point to the need for more transparent reporting of changes to a trial's details and have implications for the review and conduct of clinical trials, with our fully automated and freely available tools allowing reviewers or editors to detect these changes. TRIAL REGISTRATION: The preregistered protocol of our study is available via https://osf.io/rvq53 . The most recent version of the protocol lists all deviations from the original study plan, including the rationale behind the changes, and additional analyses that were conducted.

Three levels of discrepancies in the records of trial sites in India, registered with the European Union Clinical Trials Register.

Introduction: Clinical trial registries serve a key role in tracking the trial enterprise. We are interested in the record of trials sites in India. In this study, we focused on the European Union Clinical Trial Registry (EUCTR). This registry is complex because a given study may have records from multiple countries in the EU, and therefore a given study ID may be represented by multiple records. We wished to determine what steps are required to identify the studies that list sites in India that are registered with EUCTR. Methods: We used two methodologies. Methodology A involved downloading the EUCTR database and querying it. Methodology B used the search function on the registry website. Results: Discrepant information, on whether or not a given study listed a site in India, was identified at three levels: (i) the methodology of examining the database; (ii) the multiple records of a given study ID; and (iii) the multiple fields within a given record. In each of these situations, there was no basis to resolve the discrepancy, one way or another. Discussion: This work contributes to methodologies for more accurate searches of trial registries. It also adds to the efforts of those seeking transparency in trial data.

In India, most principal investigators have run very few trials over the years.

Background: In the past, clinical trials run in India have been the subject of criticism. Among other steps to improve the trial ecosystem, for some time the government limited the number of trials that a Principal Investigator (PI) could run to three at a time. We were interested to know how many trials PIs in India tend to run at a time. Methods: We accessed the 52,149 trial records hosted by the Clinical Trials Registry-India in April 2023. Of these, we shortlisted trials that had run in India, were interventional, and involved certain interventions such as drug, biological etc. We used multiple parameters, such as email ID, phone number etc. to determine whether one name always represented the same PI and whether two names corresponded to the same PI. We then determined how many trials each PI had run. Results: We found that 3,916 unique PI names were associated with 6,665 trials. Of these, 2,963 (75.7%) PIs had run a single study. Only 251 (6.4%) had run more than three trials. A mere 14 PIs had run 20 or more trials. The 14 PIs were affiliated with local pharma companies (6), local or global contract research organizations (4), multinational pharma companies (3) and the Central Council for Research in Homeopathy (1). The maximum number of trials run by a single PI was 108. Of these, the largest number run in a single year, 2022, was 53. Conclusion: Each PI name needs to be connected to a unique ID that does not change with time, so that it is easier to track the number of trials that a given PI has run. The number of studies run by a given PI at a given time must not be excessive and needs to be monitored more actively. The government needs to consider whether a cap on the number of trials that a PI runs at a time is required and what infrastructure needs to be in place to facilitate higher numbers of trials. Trial registry records need to be updated more regularly. Other countries may wish to do likewise.

The need for a new keyword - "Trial registry-metaresearch" - to track certain uses of clinical trial registry records.

Public clinical trial registries contain a large amount of information about a large number of trials. Academic researchers have conducted various analyses using such data. However, some of these studies do not concern the medical condition or intervention that is the focus of each trial. We list examples of publications that have performed such analyses. Currently, there is no keyword to track relevant publications. Here, we propose a novel keyword, "Trial registry-metaresearch", that could be used in such publications. This would be a great help to researchers who wish to more systematically search the literature for such metaresearch.

Ethnic representation in interventional clinical trials run in India.

Globally, the need to enhance the diversity of trial participants is receiving increasingly urgent attention. We wanted to know whether trials run in India had adequately sampled the country's enormous ethnic diversity. We accessed the Clinical Trials Registry-India website to determine whether each interventional drug or biologic Phase 2 or 3 study, registered in a recent five-year period had run in each of six geographic zones. As regards Phase 3 trials conducted only in India, 61.4% ran in a single zone and just 6.8% were conducted in all six zones. Multinational Phase 3 trials had a better distribution since 3.6% had run in just one zone and 7.1% in all six. India's diverse ethnic groups are underrepresented in the majority of trials covered in this study. A trial that is conducted on non-representative groups and later discovered to be harmful or ineffective in parts of the population, is unethical. We propose various remedial steps.

The characteristics of oncological clinical trials investigating the synergistic effect of radiotherapy and immune checkpoint inhibitors: a cross-sectional study.

Background: The combined use of radiotherapy (RT) and immune checkpoint inhibitors (ICIs) is a promising strategy in the treatment of cancer patients. We sought to comprehensively summarize the characteristics of oncological trials investigating the synergistic effect of RT and ICIs registered at ClinicalTrials.gov. Methods: In this cross-sectional study, oncological trials investigating the synergistic effect of RT and ICIs registered at ClinicalTrials.gov from database inception to November 30, 2021 were retrieved. The characteristics of the included trials were assessed. Results: Overall, 403 registered trials were identified for analysis. Of these trials, 393 (97.5%) were interventional trials and 10 (2.5%) were observational trials. The top 3 most-studied conditions were gastrointestinal cancer (25.8%), head and neck cancer (18.6%), and non-small cell lung cancer (NSCLC) (17.9%). Approximately, 60.0% of the trials comprised ≤50 participants and 22.6% of the trials comprised >100 participants. More than half of the registered trials were prospective phase 2 trials (54.3%). In relation to trial location, 39.7% of the trials were conducted in the United States, which was the most common registered area, followed by China (33.7%) and Europe (19.4%). In relation to the radiation fractionation, the conventional fractionation size of 1.8-2.0 Gy was comparable to the ultra-hypofractionation size of ≥5 Gy (46.4% vs. 32.8%), and the most commonly used ultra-hypofractionation regimen was 24 Gy/3 Fx (24%), followed by 25 Gy/5 Fx (11%) and 30 Gy/5 Fx (11%). Additionally, the most commonly used ICI in the registered trials was pembrolizumab (20.1%), followed by durvalumab (11.4%) and nivolumab (9.2%). Among all the registered trials, only 4% of the trials had been completed, but 61.5% of the completed trials had reported their results on ClinicalTrials.gov. The conventional fractionation trials were more likely to be phase 3 trials, located in China, and performed in patients with head and neck cancer or gynecological cancer (all P values <0.05), while the ultra-hypofractionation trials were more likely to be phase 1 trials, stopped early, located in the United States, and performed in patients with lung cancer (all P values <0.05). Conclusions: The number of prospective trials investigating the synergistic effect of RT and ICIs registered at ClinicalTrials.gov has increased significantly over the past decade. The ultra-hypofractionation size of the registered trials varies, but the 24 Gy/3 Fx regimen is commonly used. The clinical results of registered trials examining the synergistic effect of RT in combination with ICIs, specifically in terms of ultra-hypofractionation, remain limited.

An observational study on the adherence to study registrations in German interventional and observational studies from various fields.

Background: The registration of studies, especially in the case of clinical trials, is required by the declaration of Helsinki and the policies of various scientific journals. However, numerous analyses have found considerable discrepancies between published articles and accompanying trial registrations. The aim of this study is to assess such discrepancies for a sample of studies with recruiting locations in Germany. Additionally, the association between the adherence to registrations and possible involvement of Coordinating Centers for Clinical Studies (KKS) as well as Universities of Excellence was tested. Methods: For a sample of 376 interventional or observational study registrations, we found 115 published articles. Subsequently, we searched for discrepancies in the study design, the key inclusion criteria, the interventions, the blinding, and a primary and a secondary outcome. Results: We found discrepancies in 26% of all studies, most frequently in the secondary outcomes, where 16.5% of the secondary outcomes per study that were registered in most detail had discrepancies. When running regression models for adherence discrepancies, the only variable that had a statistically significant association with better adherence was registration on ClinicalTrials.gov. The association of potential involvement of a KKS with adherence ratings was positive, too, but statistically insignificant. Conclusions: In summary, the amount of discrepancies between registrations and published articles remains elevated.

Utilization of sentiment analysis to assess and compare negative finding reporting in veterinary and human literature.

Publication bias and the decreased publication of trials with negative or non-significant results is a well-recognized problem in human and veterinary medical publications. These biases may present an incomplete picture of evidence-based clinical care and negatively impact medical practices. The purpose of this study was to utilize a novel sentiment analysis tool as a quantitative measure for assessing clinical trial reporting trends in human and veterinary medical literature. Abstracts from 177,617 clinical trials in human medical journals and 8684 in veterinary medical journals published in the PubMed database from 1995 to 2020. Abstracts were analyzed using the GAN-BioBERT sentiment classifier for both general trends and percentage of neutral/negative publications. Sentiment was defined on a - 1 (highly negative) to 1 (highly positive) scale. Human-based clinical trial publications were less likely to feature positive findings (OR 0.87, P < 0.001) and more likely to include neutral findings (OR 1.18, P < 0.001) relative to veterinary clinical trials. No difference was found in reporting of negative sentiment trials (OR 1.007, P = 0.83). In both groups, the published sentiment of clinical trials increased over time. Using sentiment analysis to evaluate large publication datasets and compare publication trends within and between groups, this study is significant in its detection of significant publication differences between human and veterinary medicine clinical trials and a continued unbalanced positive sentiment in the published literature. The implications of this unbiased reporting have important clinical and research implications that require consideration.

Patient-reported outcomes are under-utilised in evaluating supportive therapies in paediatric oncology - A systematic review of clinical trial registries.

BACKGROUND: Children with cancer suffer from numerous symptoms and side-effects, making supportive interventions indispensable to improve their quality of life. The gold standard for evaluating the latter is patient-reported outcome (PRO) assessment. This systematic review investigates the current practice of clinical outcome assessment (COA) in clinical trials on supportive interventions. METHODS: ClinicalTrials.gov and EudraCT were searched for trials including children and adolescents (≤21 years) with cancer receiving supportive care registered 2007-2020. The use of different types of COAs was analysed, focusing on PRO assessment and the domains measured with PRO measures (PROMs). Associations with trial characteristics were investigated using univariate and multivariable analyses. RESULTS: Of 4789 identified trials, 229 were included. Among them, 44.1 % relied on PROMs, the most commonly used COA. The proportion of trials using PROMs did not significantly differ over time. In the multivariable analysis, intervention type (higher PROM use in behavioural vs. medical interventional trials) and cancer type (higher PROM use in mixed and solid tumour samples vs. haematological samples) were significant predictors of PROM use. The majority of trials using PROMs (59.6 %) measured more than one health domain. 'Physical health' was the most frequently assessed domain (92.6 %). CONCLUSION: Less than half of registered clinical trials investigating supportive interventions for children with cancer used PROMs. This result is striking since supportive care explicitly focuses on patients' quality of life, which is best assessed using PROMs. Our systematic review underlines the need to identify barriers for PROM implementation and to improve PRO research in paediatric oncology.

Evidence synthesis, digital scribes, and translational challenges for artificial intelligence in healthcare.

Healthcare has well-known challenges with safety, quality, and effectiveness, and many see artificial intelligence (AI) as essential to any solution. Emerging applications include the automated synthesis of best-practice research evidence including systematic reviews, which would ultimately see all clinical trial data published in a computational form for immediate synthesis. Digital scribes embed themselves in the process of care to detect, record, and summarize events and conversations for the electronic record. However, three persistent translational challenges must be addressed before AI is widely deployed. First, little effort is spent replicating AI trials, exposing patients to risks of methodological error and biases. Next, there is little reporting of patient harms from trials. Finally, AI built using machine learning may perform less effectively in different clinical settings.

Rare use of patient-reported outcomes in childhood cancer clinical trials - a systematic review of clinical trial registries.

BACKGROUND: Patient-reported outcomes (PROs) are the gold standard to assess the patients' subjective health status. While both the Food and Drug Administration and European Medicines Agency recommend the use of PROs as end-points in paediatric clinical trials to support claims for medical product labelling, it is not known how often PROs are actually used. The aim of this study was to assess the usage of PRO instruments in childhood cancer clinical trials investigating anti-cancer medication. METHODS: In June 2020 ClinicalTrials and EudraCT were systematically searched for all trials including children and adolescents (≤21 years) with cancer registered between 2007 and 2020. The use of PRO measures and trials characteristics were analysed. To investigate which trial characteristics are associated with the use of PROs, a binary logistic regression was calculated. RESULTS: Of 4789 identified trials, 711 were included. The most frequent reason for exclusion was age limitation (age >21 years). Of all included trials, only 8.2% used PROs as end-points; .6% as the primary end-point. The most commonly used questionnaire was the PedsQL™ (32.8%), followed by the Patient-Reported Outcomes Measurement Information System scales (12.1%). No association was observed between the use of PROs and trial region, number of centres, trial phase, time period or intervention type (all p > .05). The use of PROs did not substantially increase over time. Only 20.3% of the closed studies had published their results. CONCLUSION: Despite recommendations of regulatory agencies, PRO assessment is extremely rare in paediatric oncology clinical trials. More efforts should be undertaken to facilitate implementation of PRO in paediatric trials to guarantee patient-centred research and treatments.

Selective reporting bias in randomised controlled trials from two network meta-analyses: comparison of clinical trial registrations and their respective publications.

OBJECTIVE: To determine (i) the difference in the frequency of serious adverse events (SAEs) reported in trial registrations and their respective primary publications and (ii) the effect of adding SAE data from registries to a network meta-analysis (NMA) in changing the surface under the cumulative ranking (SUCRA) curve values of interventions. DESIGN: Secondary analysis of primary publications from two NMAs. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: We included randomised trials published in English after 2005 that were included in two NMAs of pharmacological interventions for Alzheimer's disease and chronic obstructive pulmonary disease. DATA EXTRACTION: Two reviewers independently searched multiple international trial registries for registration status and abstracted data from the included study publications and ClinicalTrials.gov. RESULTS: Of the 203 randomised trials included, 140 (69.0%) were registered with a trial registry and 72 (35.5%) posted results in the registry. The proportion of registered trials increased over time (38.5% in 2005 vs 78.6% in 2014). Of the publications with results posted in a trial registry, 14 (19.4%) had inconsistent reporting of overall SAEs; 7 (10.4%) studies did not report SAEs in the publication but did in the registry. In the 134 randomised trials with a prespecified primary outcome in the registry, 19 studies (9.4%) had a change in the primary outcome in the publication. Adding SAEs reported in registries to the NMAs did not affect the ranking of interventions. CONCLUSION: We identified inconsistent reporting of SAEs in randomised trials that were included in two NMAs. Findings highlight the importance of including trial registries in the grey literature search and verifying safety data before incorporating it into NMAs. STUDY REGISTRATION: osf.io/mk6dr.

A landscape analysis of HIV cure-related clinical trials and observational studies in 2018.

OBJECTIVES: The community-based organisation Treatment Action Group has established an online listing of HIV cure-related trials and observational studies derived from trial registries. Our objective was to use the listing as a basis for a landscape analysis of the current status of HIV cure-related clinical research. METHODS: Trials and observational studies listed as of August 2018 formed the sample set. Survey questions were developed on trial development, trial design, recruitment, enrolment, study completion and dissemination plans. A survey was sent to the contact(s) for each study. Supplemental information was collected from clinicaltrials.gov. The full dataset was then analysed. RESULTS: A total of 99 interventional trials and 29 observational studies were included. Diverse interventions are under evaluation, including combinations of experimental candidates. Current studies plan to enrol over 7000 participants. Projected completion dates for ~90% of the sample fell between the fourth quarter of 2018 and the end of 2020. Potential obstacles to enrolment that were reported included concerns over invasive procedures and lack of potential benefit to participants. Data on the sex and ethnicity of enrollees were limited but sufficient to note a significant under-representation of women. CONCLUSIONS: A considerable amount of HIV cure-related clinical research is under way. The results from these studies, which should help shape the future of the field, will become available over the next 2-4 years. Diversity both geographically and in terms of enrollees remains limited, particularly in terms of the participation of women, a concern that could significantly affect the generalisability of the findings.

The risk of conclusion change in systematic review updates can be estimated by learning from a database of published examples.

OBJECTIVES: To determine which systematic review characteristics are needed to estimate the risk of conclusion change in systematic review updates. STUDY DESIGN AND SETTING: We applied classification trees (a machine learning method) to model the risk of conclusion change in systematic review updates, using pairs of systematic reviews and their updates as samples. The classifiers were constructed using a set of features extracted from systematic reviews and the relevant trials added in published updates. Model performance was measured by recall, precision, and area under the receiver operating characteristic curve (AUC). RESULTS: We identified 63 pairs of systematic reviews and updates, of which 20 (32%) exhibited a change in conclusion in their updates. A classifier using information about new trials exhibited the highest performance (AUC: 0.71; recall: 0.75; precision: 0.43) compared to a classifier that used fewer features (AUC: 0.65; recall: 0.75; precision: 0.39). CONCLUSION: When estimating the risk of conclusion change in systematic review updates, information about the sizes of trials that will be added in an update are most useful. Future tools aimed at signaling conclusion change risks would benefit from complementary tools that automate screening of relevant trials.

Time-to-update of systematic reviews relative to the availability of new evidence.

BACKGROUND: A number of methods for deciding when a systematic review should be updated have been proposed, yet little is known about whether systematic reviews are updated more quickly when new evidence becomes available. Our aim was to examine the timing of systematic review updates relative to the availability of new evidence. METHODS: We performed a retrospective analysis of the update timing of systematic reviews published in the Cochrane Database of Systematic Reviews in 2010 relative to the availability of new trial evidence. We compared the update timing of systematic reviews with and without signals defined by the completion or publication of studies that were included in the updates. RESULTS: We found 43% (293/682) systematic reviews were updated before June 2017, of which 204 included an updated primary outcome meta-analysis (median update time 35.4 months; IQR 25.5-54.0), 38% (77/204) added new trials, and 4% (8/204) reported a change in conclusion. In the 171 systematic reviews with reconcilable trial reporting information, we did not find a clear difference in update timing (p = 0.05) between the 15 systematic reviews with a publication signal (median 25.3 months; IQR 15.3-43.5) and the 156 systematic reviews without a publication signal (median 34.4 months; IQR 25.1-52.2). In the 145 systematic reviews with reconcilable trial completion information, we did not find a difference in update timing (p = 0.33) between the 15 systematic reviews with a trial completion signal (median 26.0 months; IQR 19.3-49.5) and the 130 systematic reviews without a trial completion signal (median 32.4 months; IQR 24.1 to 46.0). CONCLUSION: A minority of 2010 Cochrane reviews were updated before June 2017 to incorporate evidence from new primary studies, and very few updates led to a change in conclusion. We did not find clear evidence that updates were undertaken faster when new evidence was made available. New approaches for finding early signals that a systematic review conclusion is at risk of change may be useful in allocated resources to the updating of systematic reviews.