The State of Infectious Diseases Clinical Trials: A Systematic Review of ClinicalTrials.gov

Background

There is a paucity of clinical trials informing specific questions faced by infectious diseases (ID) specialists. The ClinicalTrials.gov registry offers an opportunity to evaluate the ID clinical trials portfolio.

Methods

We examined 40,970 interventional trials registered with ClinicalTrials.gov from 2007–2010, focusing on study conditions and interventions to identify ID-related trials. Relevance to ID was manually confirmed for each programmatically identified trial, yielding 3570 ID trials and 37,400 non-ID trials for analysis.

Results

The number of ID trials was similar to the number of trials identified as belonging to cardiovascular medicine (n = 3437) or mental health (n = 3695) specialties. Slightly over half of ID trials were treatment-oriented trials (53%, vs. 77% for non-ID trials) followed by prevention (38%, vs. 8% in non-ID trials). ID trials tended to be larger than those of other specialties, with a median enrollment of 125 subjects (interquartile range [IQR], 45–400) vs. 60 (IQR, 30–160) for non-ID trials. Most ID studies are randomized (73%) but nonblinded (56%). Industry was the funding source in 51% of ID trials vs. 10% that were primarily NIH-funded. HIV-AIDS trials constitute the largest subset of ID trials (n = 815 [23%]), followed by influenza vaccine (n = 375 [11%]), and hepatitis C (n = 339 [9%]) trials. Relative to U.S. and global mortality rates, HIV-AIDS and hepatitis C virus trials are over-represented, whereas lower respiratory tract infection trials are under-represented in this large sample of ID clinical trials.

Conclusions

This work is the first to characterize ID clinical trials registered in ClinicalTrials.gov, providing a framework to discuss prioritization, methodology, and policy.     

Trial Publication after Registration in ClinicalTrials.Gov: A Cross-Sectional Analysis

Background

ClinicalTrials.gov is a publicly accessible, Internet-based registry of clinical trials managed by the US National Library of Medicine that has the potential to address selective trial publication. Our objectives were to examine completeness of registration within ClinicalTrials.gov and to determine the extent and correlates of selective publication.

Methods and Findings

We examined reporting of registration information among a cross-section of trials that had been registered at ClinicalTrials.gov after December 31, 1999 and updated as having been completed by June 8, 2007, excluding phase I trials. We then determined publication status among a random 10% subsample by searching MEDLINE using a systematic protocol, after excluding trials completed after December 31, 2005 to allow at least 2 y for publication following completion. Among the full sample of completed trials (n = 7,515), nearly 100% reported all data elements mandated by ClinicalTrials.gov, such as intervention and sponsorship. Optional data element reporting varied, with 53% reporting trial end date, 66% reporting primary outcome, and 87% reporting trial start date. Among the 10% subsample, less than half (311 of 677, 46%) of trials were published, among which 96 (31%) provided a citation within ClinicalTrials.gov of a publication describing trial results. Trials primarily sponsored by industry (40%, 144 of 357) were less likely to be published when compared with nonindustry/nongovernment sponsored trials (56%, 110 of 198; p<0.001), but there was no significant difference when compared with government sponsored trials (47%, 57 of 122; p = 0.22). Among trials that reported an end date, 75 of 123 (61%) completed prior to 2004, 50 of 96 (52%) completed during 2004, and 62 of 149 (42%) completed during 2005 were published (p = 0.006).

Conclusions

Reporting of optional data elements varied and publication rates among completed trials registered within ClinicalTrials.gov were low. Without greater attention to reporting of all data elements, the potential for ClinicalTrials.gov to address selective publication of clinical trials will be limited. Please see later in the article for the Editors'' Summary     

ClinicalTrials.gov as a Data Source for Semi-Automated Point-Of-Care Trial Eligibility Screening

Background

Implementing semi-automated processes to efficiently match patients to clinical trials at the point of care requires both detailed patient data and authoritative information about open studies.

Objective

To evaluate the utility of the ClinicalTrials.gov registry as a data source for semi-automated trial eligibility screening.

Methods

Eligibility criteria and metadata for 437 trials open for recruitment in four different clinical domains were identified in ClinicalTrials.gov. Trials were evaluated for up to date recruitment status and eligibility criteria were evaluated for obstacles to automated interpretation. Finally, phone or email outreach to coordinators at a subset of the trials was made to assess the accuracy of contact details and recruitment status.

Results

24% (104 of 437) of trials declaring on open recruitment status list a study completion date in the past, indicating out of date records. Substantial barriers to automated eligibility interpretation in free form text are present in 81% to up to 94% of all trials. We were unable to contact coordinators at 31% (45 of 146) of the trials in the subset, either by phone or by email. Only 53% (74 of 146) would confirm that they were still recruiting patients.

Conclusion

Because ClinicalTrials.gov has entries on most US and many international trials, the registry could be repurposed as a comprehensive trial matching data source. Semi-automated point of care recruitment would be facilitated by matching the registry''s eligibility criteria against clinical data from electronic health records. But the current entries fall short. Ultimately, improved techniques in natural language processing will facilitate semi-automated complex matching. As immediate next steps, we recommend augmenting ClinicalTrials.gov data entry forms to capture key eligibility criteria in a simple, structured format.     

Impact of Inclusion of Industry Trial Results Registries as an Information Source for Systematic Reviews

Background

Clinical trial results registries may contain relevant unpublished information. Our main aim was to investigate the potential impact of the inclusion of reports from industry results registries on systematic reviews (SRs).

Methods

We identified a sample of 150 eligible SRs in PubMed via backward selection. Eligible SRs investigated randomized controlled trials of drugs and included at least 2 bibliographic databases (original search date: 11/2009). We checked whether results registries of manufacturers and/or industry associations had also been searched. If not, we searched these registries for additional trials not considered in the SRs, as well as for additional data on trials already considered. We reanalysed the primary outcome and harm outcomes reported in the SRs and determined whether results had changed. A “change” was defined as either a new relevant result or a change in the statistical significance of an existing result. We performed a search update in 8/2013 and identified a sample of 20 eligible SRs to determine whether mandatory results registration from 9/2008 onwards in the public trial and results registry ClinicalTrials.gov had led to its inclusion as a standard information source in SRs, and whether the inclusion rate of industry results registries had changed.

Results

133 of the 150 SRs (89%) in the original analysis did not search industry results registries. For 23 (17%) of these SRs we found 25 additional trials and additional data on 31 trials already included in the SRs. This additional information was found for more than twice as many SRs of drugs approved from 2000 as approved beforehand. The inclusion of the additional trials and data yielded changes in existing results or the addition of new results for 6 of the 23 SRs. Of the 20 SRs retrieved in the search update, 8 considered ClinicalTrials.gov or a meta-registry linking to ClinicalTrials.gov, and 1 considered an industry results registry.

Conclusion

The inclusion of industry and public results registries as an information source in SRs is still insufficient and may result in publication and outcome reporting bias. In addition to an essential search in ClinicalTrials.gov, authors of SRs should consider searching industry results registries.     

Differences in Investigator-Initiated Trials between Japan and Other Countries: Analyses of Clinical Trials Sponsored by Academia and Government in the ClinicalTrials.gov Registry and in the Three Japanese Registries

Background

Following the amendment of the Pharmaceutical Affairs Law in Japan in 2003 researchers were permitted to begin investigator-initiated trials (IITs). In subsequent years, however, the number of IITs remained low. In other countries in Asia as well as in Europe, North America, and South Africa, the number of IITs has increased over the past decade. The differences in the characteristics of IITs between Japan and other countries are unknown. Some studies have analyzed the characteristics of all clinical trials according to registry databases, but there has been less research focusing on IITs.

Aims

The purpose of this study is to analyze the characteristics of IITs in the ClinicalTrials.gov registry and in the three Japanese registries, to identify differences in IITs between Japan and other countries.

Methods

Using Thomson Reuters Pharma™, trials sponsored by academia and government as IITs in 2010 and registered in ClinicalTrials.gov were identified. IITs from 2004 to 2012 in Japan were identified in the three Japanese registries: the University Hospital Medical Information Network Clinical Trials Registry, the Japan Pharmaceutical Information Center Clinical Trials Information, and the Japan Medical Association Center for Clinical Trials, Clinical Trials Registry. Characterization was made of the trial purposes, phases, participants, masking, arms, design, controls, and other data.

Results

New and revised IITs registered in ClinicalTrials.gov during 2010 averaged about 40% of all sponsor-identified trials. IITs were nearly all early-phase studies with small numbers of participants. A total of 56 Japanese IITs were found over a period of 8 years, and these were also almost nearly all early-phase studies with small numbers of participants.

Conclusion

There appear to be no great differences between Japan and other countries in terms of characteristics of IITs. These results should prompt a new review of the IIT environment in Japan.     

A human rights approach to low data reporting in clinical trials of psychiatric deep brain stimulation

The reporting of clinical trial data is necessary not only for doctors to determine treatment efficacy, but also to explore new questions without unnecessarily repeating trials, and to protect patients and the public from dangers when data are withheld. This issue is particularly salient in those trials involving invasive neurosurgical interventions, such as deep brain stimulation (DBS), for ‘treatment refractory’ psychiatric disorders. Using the federal database ClinicalTrials.gov, it was discovered that out of the completed or unknown‐status trials related to psychiatric DBS up to November 2018, only two had submitted results to ClinicalTrials.gov. These results suggest that, despite federal requirements to report clinical trial data, reporting on psychiatric DBS trials is problematically minimal. It is argued that a human rights approach to this problem establishes a legal and ethical foundation for the need to report clinical trial results in this area.     

Ten Years after the International Committee of Medical Journal Editors’ Clinical Trial Registration Initiative,One Quarter of Phase 3 Pediatric Epilepsy Clinical Trials Still Remain Unpublished: A Cross Sectional Analysis

Introduction

Although selective reporting of clinical trial results introduces bias into evidence based clinical decision making, publication bias in pediatric epilepsy is unknown today. Since there is a considerable ambiguity in the treatment of an important and common clinical problem, pediatric seizures, we assessed the public availability of results of phase 3 clinical trials that evaluated treatments of seizures in children and adolescents as a surrogate for the extent of publication bias in pediatric epilepsy.

Methods

We determined the proportion of published and unpublished study results of phase 3 clinical trials that were registered as completed on ClinicalTrials.gov. We searched ClinicalTrials.gov, PubMed, and Google Scholar for publications and contacted principal investigators or sponsors. The analysis was performed according to STROBE criteria.

Results

Considering studies that were completed before 2014 (N = 99), 75 (76%) pediatric phase 3 clinical trials were published but 24 (24%) remained unpublished. The unpublished studies concealed evidence from 4,437 patients. Mean time-to-publication was 25 SD ± 15.6 months, more than twice as long as mandated.

Conclusion

Ten years after the ICMJE’s clinical trials registration initiative there is still a considerable amount of selective reporting and delay of publication that potentially distorts the body of evidence in the treatment of pediatric seizures.     

Timing and Completeness of Trial Results Posted at ClinicalTrials.gov and Published in Journals

Background

The US Food and Drug Administration Amendments Act requires results from clinical trials of Food and Drug Administration–approved drugs to be posted at ClinicalTrials.gov within 1 y after trial completion. We compared the timing and completeness of results of drug trials posted at ClinicalTrials.gov and published in journals.

Methods and Findings

We searched ClinicalTrials.gov on March 27, 2012, for randomized controlled trials of drugs with posted results. For a random sample of these trials, we searched PubMed for corresponding publications. Data were extracted independently from ClinicalTrials.gov and from the published articles for trials with results both posted and published. We assessed the time to first public posting or publishing of results and compared the completeness of results posted at ClinicalTrials.gov versus published in journal articles. Completeness was defined as the reporting of all key elements, according to three experts, for the flow of participants, efficacy results, adverse events, and serious adverse events (e.g., for adverse events, reporting of the number of adverse events per arm, without restriction to statistically significant differences between arms for all randomized patients or for those who received at least one treatment dose).From the 600 trials with results posted at ClinicalTrials.gov, we randomly sampled 50% (n = 297) had no corresponding published article. For trials with both posted and published results (n = 202), the median time between primary completion date and first results publicly posted was 19 mo (first quartile = 14, third quartile = 30 mo), and the median time between primary completion date and journal publication was 21 mo (first quartile = 14, third quartile = 28 mo). Reporting was significantly more complete at ClinicalTrials.gov than in the published article for the flow of participants (64% versus 48% of trials, p<0.001), efficacy results (79% versus 69%, p = 0.02), adverse events (73% versus 45%, p<0.001), and serious adverse events (99% versus 63%, p<0.001).The main study limitation was that we considered only the publication describing the results for the primary outcomes.

Conclusions

Our results highlight the need to search ClinicalTrials.gov for both unpublished and published trials. Trial results, especially serious adverse events, are more completely reported at ClinicalTrials.gov than in the published article. Please see later in the article for the Editors'' Summary     

Current clinical trials with non-coding RNA-based therapeutics in malignant diseases: A systematic review

This systematic review aimed to shed light on the trend of current clinical trials of non-coding RNA (ncRNA)-based therapeutics for malignant diseases. We conducted a database search for published literature and ongoing clinical trials using PubMed, clinicaltrials.gov, and University Medical Information Network (UMIN) clinical trial registry. To ensure that our review was based on up-to-date clinical trials, we limited our search to literature published within the last five years (January 2017–September 2022). Furthermore, due to the “clinical” nature of our review, we focused only on studies involving human participants. Among ncRNAs, microRNAs have been extensively explored in observational studies of malignant diseases as potential diagnostic markers and prognostic predictors, as well as for their therapeutic monitoring and profiling capabilities. As therapeutic agents, microRNA or siRNA were estimated in interventional human clinical trials and showed promising outcomes; however, the number of trials was small. Evidence and ongoing clinical trials in which ncRNAs other than microRNA or siRNA have been evaluated for their potential as therapeutic agents are limited. Here, we summarized microRNA as a potential therapeutic agent in malignant diseases, but most of the current evidence suggests that it is useful as a potential biomarker. siRNA is also a promising ncRNA technique in cancer, however more data from clinical trials are warranted for clinical use.     

Completeness and changes in registered data and reporting bias of randomized controlled trials in ICMJE journals after trial registration policy

Objective

We assessed the adequacy of randomized controlled trial (RCT) registration, changes to registration data and reporting completeness for articles in ICMJE journals during 2.5 years after registration requirement policy.

Methods

For a set of 149 reports of 152 RCTs with ClinicalTrials.gov registration number, published from September 2005 to April 2008, we evaluated the completeness of 9 items from WHO 20-item Minimum Data Set relevant for assessing trial quality. We also assessed changes to the registration elements at the Archive site of ClinicalTrials.gov and compared published and registry data.

Results

RCTs were mostly registered before 13 September 2005 deadline (n = 101, 66.4%); 118 (77.6%) started recruitment before and 31 (20.4%) after registration. At the time of registration, 152 RCTs had a total of 224 missing registry fields, most commonly ‘Key secondary outcomes’ (44.1% RCTs) and ‘Primary outcome’ (38.8%). More RCTs with post-registration recruitment had missing Minimum Data Set items than RCTs with pre-registration recruitment: 57/118 (48.3%) vs. 24/31 (77.4%) (χ² ₁ = 7.255, P = 0.007). Major changes in the data entries were found for 31 (25.2%) RCTs. The number of RCTs with differences between registered and published data ranged from 21 (13.8%) for Study type to 118 (77.6%) for Target sample size.

Conclusions

ICMJE journals published RCTs with proper registration but the registration data were often not adequate, underwent substantial changes in the registry over time and differed in registered and published data. Editors need to establish quality control procedures in the journals so that they continue to contribute to the increased transparency of clinical trials.     

Linking ClinicalTrials.gov and PubMed to Track Results of Interventional Human Clinical Trials

Objective

In an effort to understand how results of human clinical trials are made public, we analyze a large set of clinical trials registered at ClinicalTrials.gov, the world’s largest clinical trial registry.

Materials and Methods

We considered two trial result artifacts: (1) existence of a trial result journal article that is formally linked to a registered trial or (2) the deposition of a trial’s basic summary results within the registry.

Results

The study sample consisted of 8907 completed, interventional, phase 2-or-higher clinical trials that were completed in 2006-2009. The majority of trials (72.2%) had no structured trial-article link present. A total of 2367 trials (26.6%) deposited basic summary results within the registry. Of those , 969 trials (10.9%) were classified as trials with extended results and 1398 trials (15.7%) were classified as trials with only required basic results. The majority of the trials (54.8%) had no evidence of results, based on either linked result articles or basic summary results (silent trials), while a minimal number (9.2%) report results through both registry deposition and publication.

Discussion

Our study analyzes the body of linked knowledge around clinical trials (which we refer to as the “trialome”). Our results show that most trials do not report results and, for those that do, there is minimal overlap in the types of reporting. We identify several mechanisms by which the linkages between trials and their published results can be increased.

Conclusion

Our study shows that even when combining publications and registry results, and despite availability of several information channels, trial sponsors do not sufficiently meet the mandate to inform the public either via a linked result publication or basic results submission.     

Evaluating the frequency of English language requirements in clinical trial eligibility criteria: A systematic analysis using ClinicalTrials.gov

BackgroundA number of prior studies have demonstrated that research participants with limited English proficiency in the United States are routinely excluded from clinical trial participation. Systematic exclusion through study eligibility criteria that require trial participants to be able to speak, read, and/or understand English affects access to clinical trials and scientific generalizability. We sought to establish the frequency with which English language proficiency is required and, conversely, when non-English languages are affirmatively accommodated in US interventional clinical trials for adult populations.Methods and findingsWe used the advanced search function on ClinicalTrials.gov specifying interventional studies for adults with at least 1 site in the US. In addition, we used these search criteria to find studies with an available posted protocol. A computer program was written to search for evidence of English or Spanish language requirements, or the posted protocol, when available, was manually read for these language requirements. Of the 14,367 clinical trials registered on ClinicalTrials.gov between 1 January 2019 and 1 December 2020 that met baseline search criteria, 18.98% (95% CI 18.34%–19.62%; n = 2,727) required the ability to read, speak, and/or understand English, and 2.71% (95% CI 2.45%–2.98%; n = 390) specifically mentioned accommodation of translation to another language. The remaining trials in this analysis and the following sub-analyses did not mention English language requirements or accommodation of languages other than English. Of 2,585 federally funded clinical trials, 28.86% (95% CI 27.11%–30.61%; n = 746) required English language proficiency and 4.68% (95% CI 3.87%–5.50%; n = 121) specified accommodation of other languages; of the 5,286 industry-funded trials, 5.30% (95% CI 4.69%–5.90%; n = 280) required English and 0.49% (95% CI 0.30%–0.69%; n = 26) accommodated other languages. Trials related to infectious disease were less likely to specify an English requirement than all registered trials (10.07% versus 18.98%; relative risk [RR] = 0.53; 95% CI 0.44–0.64; p < 0.001). Trials related to COVID-19 were also less likely to specify an English requirement than all registered trials (8.18% versus 18.98%; RR = 0.43; 95% CI 0.33–0.56; p < 0.001). Trials with a posted protocol (n = 366) were more likely than all registered clinical trials to specify an English requirement (36.89% versus 18.98%; RR = 1.94, 95% CI 1.69–2.23; p < 0.001). A separate analysis of studies with posted protocols in 4 therapeutic areas (depression, diabetes, breast cancer, and prostate cancer) demonstrated that clinical trials related to depression were the most likely to require English (52.24%; 95% CI 40.28%–64.20%). One limitation of this study is that the computer program only searched for the terms “English” and “Spanish” and may have missed evidence of other language accommodations. Another limitation is that we did not differentiate between requirements to read English, speak English, understand English, and be a native English speaker; we grouped these requirements together in the category of English language requirements.ConclusionsA meaningful percentage of US interventional clinical trials for adults exclude individuals who cannot read, speak, and/or understand English, or are not native English speakers. To advance more inclusive and generalizable research, funders, sponsors, institutions, investigators, institutional review boards, and others should prioritize translating study materials and eliminate language requirements unless justified either scientifically or ethically.

Akila Muthukumar and coauthors, systematically analyze ClinicalTrials.gov to evaluate the frequency of English language requirements in clinical trial eligibility criteria.     

Poor reporting of scientific leadership information in clinical trial registers

Background

In September 2004, the International Committee of Medical Journal Editors (ICMJE) issued a Statement requiring that all clinical trials be registered at inception in a public register in order to be considered for publication. The World Health Organization (WHO) and ICMJE have identified 20 items that should be provided before a trial is considered registered, including contact information. Identifying those scientifically responsible for trial conduct increases accountability. The objective is to examine the proportion of registered clinical trials providing valid scientific leadership information.

Methodology/Principal Findings

We reviewed clinical trial entries listing Canadian investigators in the two largest international and public trial registers, the International Standard Randomized Controlled Trial Number (ISRCTN) register, and ClinicalTrials.gov. The main outcome measures were the proportion of clinical trials reporting valid contact information for the trials'' Principal Investigator (PI)/Co-ordinating Investigator/Study Chair/Site PI, and trial e-mail contact address, stratified by funding source, recruiting status, and register. A total of 1388 entries (142 from ISRCTN and 1246 from ClinicalTrials.gov) comprised our sample. We found non-compliance with mandatory registration requirements regarding scientific leadership and trial contact information. Non-industry and partial industry funded trials were significantly more likely to identify the individual responsible for scientific leadership (OR = 259, 95% CI: 95–701) and to provide a contact e-mail address (OR = 9.6, 95% CI: 6.6–14) than were solely industry funded trials.

Conclusions/Significance

Despite the requirements set by WHO and ICMJE, data on scientific leadership and contact e-mail addresses are frequently omitted from clinical trials registered in the two leading public clinical trial registers. To promote accountability and transparency in clinical trials research, public clinical trials registers should ensure adequate monitoring of trial registration to ensure completion of mandatory contact information fields identifying scientific leadership     

Glocal Clinical Registries: Pacemaker Registry Design and Implementation for Global and Local Integration – Methodology and Case Study

Background

The ability to apply standard and interoperable solutions for implementing and managing medical registries as well as aggregate, reproduce, and access data sets from legacy formats and platforms to advanced standard formats and operating systems are crucial for both clinical healthcare and biomedical research settings.

Purpose

Our study describes a reproducible, highly scalable, standard framework for a device registry implementation addressing both local data quality components and global linking problems.

Methods and Results

We developed a device registry framework involving the following steps: (1) Data standards definition and representation of the research workflow, (2) Development of electronic case report forms using REDCap (Research Electronic Data Capture), (3) Data collection according to the clinical research workflow and, (4) Data augmentation by enriching the registry database with local electronic health records, governmental database and linked open data collections, (5) Data quality control and (6) Data dissemination through the registry Web site. Our registry adopted all applicable standardized data elements proposed by American College Cardiology / American Heart Association Clinical Data Standards, as well as variables derived from cardiac devices randomized trials and Clinical Data Interchange Standards Consortium. Local interoperability was performed between REDCap and data derived from Electronic Health Record system. The original data set was also augmented by incorporating the reimbursed values paid by the Brazilian government during a hospitalization for pacemaker implantation. By linking our registry to the open data collection repository Linked Clinical Trials (LinkedCT) we found 130 clinical trials which are potentially correlated with our pacemaker registry.

Conclusion

This study demonstrates how standard and reproducible solutions can be applied in the implementation of medical registries to constitute a re-usable framework. Such approach has the potential to facilitate data integration between healthcare and research settings, also being a useful framework to be used in other biomedical registries.     

An application of MeSH enrichment analysis in livestock

An integral part of functional genomics studies is to assess the enrichment of specific biological terms in lists of genes found to be playing an important role in biological phenomena. Contrasting the observed frequency of annotated terms with those of the background is at the core of overrepresentation analysis (ORA). Gene Ontology (GO) is a means to consistently classify and annotate gene products and has become a mainstay in ORA. Alternatively, Medical Subject Headings (MeSH) offers a comprehensive life science vocabulary including additional categories that are not covered by GO. Although MeSH is applied predominantly in human and model organism research, its full potential in livestock genetics is yet to be explored. In this study, MeSH ORA was evaluated to discern biological properties of identified genes and contrast them with the results obtained from GO enrichment analysis. Three published datasets were employed for this purpose, representing a gene expression study in dairy cattle, the use of SNPs for genome‐wide prediction in swine and the identification of genomic regions targeted by selection in horses. We found that several overrepresented MeSH annotations linked to these gene sets share similar concepts with those of GO terms. Moreover, MeSH yielded unique annotations, which are not directly provided by GO terms, suggesting that MeSH has the potential to refine and enrich the representation of biological knowledge. We demonstrated that MeSH can be regarded as another choice of annotation to draw biological inferences from genes identified via experimental analyses. When used in combination with GO terms, our results indicate that MeSH can enhance our functional interpretations for specific biological conditions or the genetic basis of complex traits in livestock species.     

Therapeutic efficacy of alpha-1 antitrypsin augmentation therapy on the loss of lung tissue: an integrated analysis of 2 randomised clinical trials using computed tomography densitometry

Background

Two randomised, double-blind, placebo-controlled trials have investigated the efficacy of IV alpha-1 antitrypsin (AAT) augmentation therapy on emphysema progression using CT densitometry.

Methods

Data from these similar trials, a 2-center Danish-Dutch study (n = 54) and the 3-center EXAcerbations and CT scan as Lung Endpoints (EXACTLE) study (n = 65), were pooled to increase the statistical power. The change in 15^th percentile of lung density (PD15) measured by CT scan was obtained from both trials. All subjects had 1 CT scan at baseline and at least 1 CT scan after treatment. Densitometric data from 119 patients (AAT [Alfalastin^® or Prolastin^®], n = 60; placebo, n = 59) were analysed by a statistical/endpoint analysis method. To adjust for lung volume, volume correction was made by including the change in log-transformed total lung volume as a covariate in the statistical model.

Results

Mean follow-up was approximately 2.5 years. The mean change in lung density from baseline to last CT scan was -4.082 g/L for AAT and -6.379 g/L for placebo with a treatment difference of 2.297 (95% CI, 0.669 to 3.926; p = 0.006). The corresponding annual declines were -1.73 and -2.74 g/L/yr, respectively.

Conclusions

The overall results of the combined analysis of 2 separate trials of comparable design, and the only 2 controlled clinical trials completed to date, has confirmed that IV AAT augmentation therapy significantly reduces the decline in lung density and may therefore reduce the future risk of mortality in patients with AAT deficiency-related emphysema.

Trial registration

The EXACTLE study was registered in ClinicalTrials.gov as ''Antitrypsin (AAT) to Treat Emphysema in AAT-Deficient Patients''; ClinicalTrials.gov Identifier: {"type":"clinical-trial","attrs":{"text":"NCT00263887","term_id":"NCT00263887"}}NCT00263887.     

Measuring readmission rates.

OBJECTIVE--To assess the feasibility of extracting data on readmissions and readmission rates from Körner data for use as health service indicators. DESIGN--Retrospective analysis of inpatient Körner data for January 1988 to April 1989. SETTING--Three districts in North East Thames region. MAIN OUTCOME MEASURES--Number of readmissions after index discharge for all acute specialties combined and by specialty (general medicine, general surgery, gynaecology, trauma and orthopaedics, and geriatrics); readmission rates at 28 days after index discharge; and rates standardised for age group and sex by specialty and by consultant. RESULTS--All specialties showed an early peak in number of admissions, which levelled off by 28 days. Readmission rates at 28 days were appreciably lower in surgical specialties than in medical specialties (for example, general surgery 4.1% v geriatric medicine 15.1%). They were related to age and sex of the patient. Rates standardised for these variables did not significantly differ by district. Likewise, significant differences in standardised rates were not obtained for consultants within a specialty in one district. CONCLUSIONS--Readmission rates may be measured with Körner data. The pattern of readmissions with time means that readmission rates should be measured at not more than 28 days after the index discharge; the rates require standardisation for age and sex. Annual comparisons of standardised rates may be made among districts for combinations of specialties; those among individual consultants or specialties are unlikely to be statistically valid.     

A quantitative ranking of Canada's research output of original human studies for the decade 1989 to 1998

BACKGROUND: Since 1987 research articles have been catalogued with the author''s affiliation address in the 40 databases of the Medical Literature Analysis and Retrieval System (MEDLARS) of the National Library of Medicine, Bethesda, Md. The present study was conducted to examine the Canadian entries in MEDLARS to interpret past and future trends and to combine the MEDLARS demographic data with data from other sources to rank Canadian research output of human studies both nationally and internationally. METHODS: The PubMed Web site of the National Library of Medicine was used to count medical articles archived in MEDLARS and published from Jan. 1, 1989, through Dec. 31, 1998. The articles attributed to Canadian authors were compared by country, province, city, medical school, hospital, article type, journal and medical specialty. RESULTS: During the study period Canadian authors contributed on average 3% (standard deviation [SD] 0.2%) of the worldwide MEDLARS content each year, which translated to a mean of 11,067 (SD 1037) articles per year; 49% were human studies, of which 13% were clinical or controlled trials, and 55% involved people aged 18 years or less. In total, 68% of the articles were by authors affiliated with Canadian medical schools; those affiliated with the University of Toronto accounted for the greatest number (8604), whereas authors affiliated with McGill University had the greatest rate of annual increase in the quantity published (8%). Over one-third (38%) of the articles appeared in Canadian journals. When counted by specialty, 17% of the articles were by authors with clinical specialties, 5% by those with surgical specialties and 3% by those with laboratory specialties. INTERPRETATION: The annual rate of increase in research output for Canada was more than 3 times higher than that seen world wide. Canada is now ranked seventh among countries contributing human studies to MEDLARS. The increase indicates that Canada''s medical schools are productive, competitive in making contributions to medical science and are supporting Canadian journals.     

A Machine Learning Approach to Identify Clinical Trials Involving Nanodrugs and Nanodevices from ClinicalTrials.gov

Background

Clinical Trials (CTs) are essential for bridging the gap between experimental research on new drugs and their clinical application. Just like CTs for traditional drugs and biologics have helped accelerate the translation of biomedical findings into medical practice, CTs for nanodrugs and nanodevices could advance novel nanomaterials as agents for diagnosis and therapy. Although there is publicly available information about nanomedicine-related CTs, the online archiving of this information is carried out without adhering to criteria that discriminate between studies involving nanomaterials or nanotechnology-based processes (nano), and CTs that do not involve nanotechnology (non-nano). Finding out whether nanodrugs and nanodevices were involved in a study from CT summaries alone is a challenging task. At the time of writing, CTs archived in the well-known online registry ClinicalTrials.gov are not easily told apart as to whether they are nano or non-nano CTs—even when performed by domain experts, due to the lack of both a common definition for nanotechnology and of standards for reporting nanomedical experiments and results.

Methods

We propose a supervised learning approach for classifying CT summaries from ClinicalTrials.gov according to whether they fall into the nano or the non-nano categories. Our method involves several stages: i) extraction and manual annotation of CTs as nano vs. non-nano, ii) pre-processing and automatic classification, and iii) performance evaluation using several state-of-the-art classifiers under different transformations of the original dataset.

Results and Conclusions

The performance of the best automated classifier closely matches that of experts (AUC over 0.95), suggesting that it is feasible to automatically detect the presence of nanotechnology products in CT summaries with a high degree of accuracy. This can significantly speed up the process of finding whether reports on ClinicalTrials.gov might be relevant to a particular nanoparticle or nanodevice, which is essential to discover any precedents for nanotoxicity events or advantages for targeted drug therapy.