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A systematic review of the processes used to link clinical trial registrations to their published results

Systematic Reviews20176:123

https://doi.org/10.1186/s13643-017-0518-3

Received: 28 November 2016

Accepted: 9 June 2017

Published: 3 July 2017

Abstract

Background

Studies measuring the completeness and consistency of trial registration and reporting rely on linking registries with bibliographic databases. In this systematic review, we quantified the processes used to identify these links.

Methods

PubMed and Embase databases were searched from inception to May 2016 for studies linking trial registries with bibliographic databases. The processes used to establish these links were categorised as automatic when the registration identifier was available in the bibliographic database or publication, or manual when linkage required inference or contacting of trial investigators. The number of links identified by each process was extracted where available. Linear regression was used to determine whether the proportions of links available via automatic processes had increased over time.

Results

In 43 studies that examined cohorts of registry entries, 24 used automatic and manual processes to find articles; 3 only automatic; and 11 only manual (5 did not specify). Twelve studies reported results for both manual and automatic processes and showed that a median of 23% (range from 13 to 42%) included automatic links to articles, while 17% (range from 5 to 42%) of registry entries required manual processes to find articles. There was no evidence that the proportion of registry entries with automatic links had increased (R 2 = 0.02, p = 0.36). In 39 studies that examined cohorts of articles, 21 used automatic and manual processes; 9 only automatic; and 2 only manual (7 did not specify). Sixteen studies reported numbers for automatic and manual processes and indicated that a median of 49% (range from 8 to 97%) of articles had automatic links to registry entries, and 10% (range from 0 to 28%) required manual processes to find registry entries. There was no evidence that the proportion of articles with automatic links to registry entries had increased (R 2 = 0.01, p = 0.73).

Conclusions

The linkage of trial registries to their corresponding publications continues to require extensive manual processes. We did not find that the use of automatic linkage has increased over time. Further investigation is needed to inform approaches that will ensure publications are properly linked to trial registrations, thus enabling efficient monitoring of trial reporting.

Keywords

Clinical trials as topic Trial registration Publication bias Reporting bias Systematic reviews as topic

Background

Clinical trial registries were established to improve transparency and completeness in the reporting of clinical trials [16]. Since they were established, a number of policies have been implemented to encourage or mandate their use, and this has led to substantial growth in the number of trials that have been registered [711]. For example, since 2005, prospective trial registration has been a condition for publication in member journals of the International Committee of Medical Journal Editors (ICMJE) [1, 12]. The European Union and USA have also passed legislation requiring prospective registration of clinical trials involving drugs or devices [13].

Clinical trial registries provide the ability to measure biases in the reporting of clinical trials that arise due to non-publication, delayed publication, or incomplete publication of results [14]. Studies examining these issues rely on the ability to establish a link between the original trial registration and subsequent published article. These links can be established in an automatic fashion if the publication abstract or metadata includes the registry identifier [15, 16]. However, if this identifier is not included by trial investigators or added by journals, manual processes are needed to create these links, either through searches and inference or through direct contact with investigators. Despite the number of studies that have examined reporting biases by linking trial registry entries and publications, the processes for linking are variable and poorly described.

Clinical trial registries are a critical source of information for systematic reviewers who use these registries to augment bibliographic database searches when compiling relevant evidence from clinical trials [1719]. Systematic reviewers may seek to identify links from published trial reports to their respective registry entries to fill in gaps for information that is missing or incompletely reported. They may also independently search trial registries to identify additional trials [20, 21] and follow links from the registry to reports of the trials.

Our aim was to quantify the processes that have been used to link clinical trial registries with published results and to examine the use and utility of automatic linkage over time. To do this, we conducted a systematic review of all studies examining a cohort of clinical trials to identify links from clinical trial registries to bibliographic databases and from bibliographic databases to clinical trial registries, following a published systematic review protocol [22].

Methods

Inclusion criteria and search strategy

We identified all primary studies that examined links between any of the registries in the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) and published articles in bibliographic databases. Studies were excluded if there was no English-language version, if they did not unambiguously report the total number of clinical trials for which links were identified, if they were reporting on a specific clinical trial, or if the identification of links was not the primary focus of the study. Studies that did not unambiguously report the processes used to identify links were included in the review but excluded from the analyses.

PubMed and Embase were searched from inception to May 27, 2016, [23, 24]. The search strategy was developed with the assistance of a medical research librarian with details described in a previously published protocol [22]. The full version of the search strategy for both databases is provided in additional files (see Additional files 1 and 2). This strategy included searching of all study references to identify any other relevant articles not captured in the original search. Duplicate studies were removed using digital object identifiers and manually comparing titles, authors, publication dates, and article metadata. All identified studies were screened individually by two reviewers for inclusion, and disagreement was resolved through discussion.

Data extraction

Two reviewers evaluated all the included studies to extract relevant information from the studies and resolved ambiguities by discussion. For each study, the following information was extracted: (a) number of reported clinical trials, (b) number of published articles, (c) trial registries used, (d) the study purpose (such as publication bias, outcome reporting bias, or assessing the publication rate of registered trials), (e) application domain (any constraints such as journal lists, conditions, or specialties), (f) processes for identifying links, and (g) proportions of links found using each process.

The processes used to identify links were categorised as one of three types: automatic, inferred, and inquired. Automatic links were defined by any process that used the unique registry identifier to reconcile the link into or from a bibliographic database without the need for a search or inquiry. This included searching PubMed for registry identifiers to find published articles in cohorts of registry entries or using identifiers in the metadata, abstract, or full text of published articles to find registry entries in cohorts of published articles. Inferred links were defined by any manual processes in which investigators searched for matches across databases using characteristics of the trial such as the names of the investigators, titles, and acronyms associated with the trial, location, sample size, or the population, intervention, or measurable outcome information to find a match in a bibliographic database or trial registry. Inquired links were defined by any manual process where the study authors attempted to contact the investigators or authors of a trial to request or confirm the presence or absence of a registry entry or a published article for each included trial.

Data synthesis and analysis

We examined the proportions of links that were identified through each of these three processes. Using the publication year of the studies that used both automatic and manual processes, we applied linear regression to determine whether the utility of the automatic processes—the proportion that were found automatically compared to the proportion that required manual processes—had increased over time. We did not undertake a pooled analysis of the utility of automatic links because many studies did not specify proportions found by each process used and because of the heterogeneity in the study designs. All statistical analyses were conducted using SPSS statistical software version 24.0 (IBM, Armonk, NY).

The protocol for this systematic review was published in 2016 [22] (see Additional file 3). We did not register the systematic review with PROSPERO because it does not directly examine at least one outcome of direct patient or clinical relevance.

Results

The initial search returned 11,986 results (after non-English articles were excluded), which produced 9486 articles after de-duplication (Fig. 1) [25]. A set of 348 studies remained after screening titles and abstracts, and of these, 81 studies were included in the review. One study considered links from both cohorts of registry entries and published articles [15, 26], for a total of 82 analyses. Excluded studies included conference abstracts, studies for which information about the proportions of registry entries or published articles that were identified was ambiguous [2729] and studies that considered reporting biases but could not be included because the linking was atypical or there was no linking performed [3033]. Some studies were excluded because they did not measure links between trial registries and bibliographic databases and, instead, considered links to or from other source of clinical trial information. These included links to or from protocols [3437], conference or meeting abstracts [3842], internal company documents [17], Food and Drug Administration (FDA) documents or new drug approvals [4347], or other databases of published articles [48, 49].
Fig. 1

PRISMA flow diagram of study selection for a search and screening process that resulted in the inclusion of 81 studies

Studies identifying published articles from cohorts of registry entries

We identified 43 studies that examined links to published articles from registries, typically with the aim of examining publication bias or outcome reporting bias (Table 1). The application domains varied by types of studies (e.g., terminated and withdrawn trials [50, 51], trials funded by specific organisations or from certain countries [52, 53]), and by specialty and condition (e.g., paediatric or surgical trials [54, 55]). The most commonly studied registry was ClinicalTrials.gov only (35 studies), followed by some or all the registries of the WHO ICTRP (8 studies). The most commonly examined bibliographic databases were PubMed alone (22 studies), or Embase in combination with PubMed or other bibliographic databases (20 studies). The studies included cohorts of registry entries that ranged in size from 34 to 8907 (median 305) entries. The median proportion of registry entries for which published articles were found was 47%, and these proportions ranged from 4% (2 published articles in a cohort of 46 registry entries) to 76% (47 published articles in a cohort of 62 registry entries).
Table 1

Characteristics of 43 analyses identifying published articles from cohorts of trial registry entries

Study

Registry entry cohort

Published articles found

Trial registries included

Study purpose

Study publication year

Application domain

Proportion of links by process

Hartung [70]

305

110

ClinicalTrials.gov

To determine consistency between registered trials and their publication

2014

Phase III or IV trials

Automatic = 95

Inferred = 15

Ross [51]

677

315

ClinicalTrials.gov

To assess the publication of registered trials in ClinicalTrials.gov

2009

Completed trials of phase II or higher

Automatic = 96

Inferred = 215

Inquired = 4 (contact = 117, responded = 44, published = 4)

Bourgeois [71]

546

362

ClinicalTrials.gov

To determine whether funding source of these trials is associated with favorable published outcomes

2010

Anticholesteremics, antidepressants, antipsychotics, proton-pump inhibitors, and vasodilators

Inferred = unknown

Inquired = unknown

Liu [72]

443

156

ANZCTR, ISRCTN, ChiCTR, IRCT, DRKS, NTR, JPRN, SLCTR, CTRI, PACTR, Clinicaltrials.gov.

Publication rate of Chinese Trials in WHO Registries

2010

Trials sponsored by China

Automatic = 103

Inferred = 40

Inquired = 13 (contact = 54, responded = all, published = 1)

Prenner [73]

64

35

Clinicaltrials.gov

To evaluate the rate of publication of registered clinical trials concerning age-related macular degeneration

2009

Muscular degeneration

Automatic = 8

Inferred = 27

Wildt [74]

105

66

ClinicalTrials.gov

To evaluate the adequacy of reporting of protocols for on diseases of the digestive system

2011

Gastrointestinal diseases

Inferred = 66

Gandhi [75]

37

20

ClinicalTrials.gov

To compare the published orthopaedic trauma trials following registration in ClinicalTrials.gov

2011

Orthopaedic trauma

Automatic and Inferred = unknown

Ross [53]

635

432

ClinicalTrials.gov

To review patterns of publication of clinical trials funded by NIH in peer reviewed biomedical journals

2012

NIH-funded trials in biomedical journals

Automatic and Inferred = unknown

Shamliyan [76]

758

212

ClinicalTrials.gov

To examine registration, completeness and publication of children studies

2012

Children studies funded by NIH

Inferred = 212

Vawdrey [77]

62

47

ClinicalTrials.gov

To measure the rate of non-publication and assess possible publication bias in clinical trials of electronic health records

2012

Electronic health record registered in clinicaltrials.gov

Automatic, inferred, and inquired = unknown

Chapman [55]

314

208

ClinicalTrials.gov

To determine the rate of early discontinuation and non-publication of RCTs

2014

Surgery

Inferred = 192

Inquired = 16 (contact = 101, responded = 25, published = 16)

Liu [52]

505

115

All 14 registries in ICTRP and ClinicalTrials.gov

To estimate bias risk and outcome-reporting bias in RCTs of traditional Chinese medicine

2013

Traditional Chinese medicines

Unknown

van de Wetering [26]

599

312

NTR

To evaluate the reporting of trial registration numbers in biomedical publications

2012

Biomedical publications

Automatic and inferred = unknown

Inquired = 0 (contact = 42, responded = 9, published = 0)

Huser [15]

8907

885

ClinicalTrials.gov

Linking ClinicalTrials.gov with PubMed

2013

Interventional phase II or higher clinical trials

Automatic = 885

Stockmann [78]

108

65

ClinicalTrials.gov

To evaluate the publication patterns of obstetric studies registered in ClinicalTrials.gov

2014

Obstetric studies

Automatic = 45

Inferred = 20

Jones [79]

585

414

ClinicalTrials.gov

To estimate the frequency with which results of large randomized clinical trials registered with ClinicalTrials.gov are not available to the public

2013

Interventional RCTs with more than one arm

Automatic and inferred = unknown

Inquired = 4

Riveros [80]

594

297

ClinicalTrials.gov

To assess timing and completeness of trial results posted at ClinicalTrials.gov and published in journals

2013

Interventional studies of phase III and IV

Unknown

Korevaar [81]

418

224

ClinicalTrials.gov

To assess publication and reporting of test accuracy studies registered in ClinicalTrials.gov

2014

Test accuracy studies

Automatic = 154

Inferred = 64

Inquired = 6 (contact = 175, responded = 119, published = 6)

Munch [82]

391

118

ICTRP, ClinicalTrials.gov

To analyse the perils and pitfalls of constructing a global open-access database of registered analgesic clinical trials

2014

Analgesic clinical trials

Inferred = 118

Hill [54]

90

66

ClinicalTrials.gov

To assess the characteristics of paediatric cardiovascular clinical trials registered on ClinicalTrials.gov

2014

Pediatric cardiovascular clinical trials

Unknown

Khan [83]

143

95

ClinicalTrials.gov

To examine characteristics associated with the publication and timeliness of publication of RCTs of treatment of rheumatoid arthritis

2014

Rheumatoid Arthritis

Automatic and inferred = unknown

Inquired = 1 (contact = 58, responded = 28, published = 1)

Su [84]

239

88

All 14 registries in ICTRP and ClinicalTrials.gov

Outcome reporting bias

2015

Acupuncture

Automatic and inferred = unknown

Hakala [85]

177

102

ClinicalTrials.gov

To quantify the proportion of trials for unsuccessfully licensed drugs that are not published

2015

Stalled drugs

Automatic = unknown

Inferred = unknown

Inquired = 0 (emails or calls = 42, responded = 9, published = 0)

Pranic [50]

81

21

ClinicalTrials.gov

Outcome reporting bias

2016

Completed RCTs

Inferred = 21

Tang [86]

300

222

ClinicalTrials.gov

Outcome reporting bias

2015

Random sample of phase II or IV trials

Automatic and inferred = unknown

Boccia [87]

1109

120

ClinicalTrials.gov

To assess the status of registration of observational studies

2015

Cancer

Inferred = 120

Saito [88]

400

229

ClinicalTrials.gov

To determine publication rates of completed US trials

2014

Interventional studies

Automatic = 126

Inferred = 103

Son [89]

161

62

ClinicalTrials.gov

To assess whether there is publication bias in industry funded clinical trials of degenerative diseases of the spine

2015

Diseases of the spine

Inferred = 62

Baudart [90]

489

189

ClinicalTrials.gov

To evaluate the publication rate of observational studies for intervention

2016

Observational studies with safety outcomes

Automatic = 75

Inferred = 99

Inquired = 15 (contact = 241, responded = 52, published = 15)

Chahal [91]

34

20

ClinicalTrials.gov

To determine publication rates of RCTs in sports medicine

2012

Sports medicine

Automatic and Inferred = unknown

Manzoli [92]

355

176

ClinicalTrials.gov, ICTRP, ANZCTR, ChiCTR, Current Control Trails, Clinical Study Register or Indian

To evaluate the extent of non-publication or delayed publication of registered RCTs on vaccines

2014

Vaccines

Automatic = 132

Inferred = 44

Inquired = 0, (contact = 24, responded = 0, published = unknown)

Lebensburger [93]

147

52

ClinicalTrials.gov

To analyse ClinicalTrials.gov for registered sickle cell trials

2015

Sickle cells

Automatic = 28

Inferred = 24

Smith [94]

101

25

ClinicalTrials.gov

Outcome reporting bias

2012

Arthroplasty

Automatic = 10

Inferred = 15

Guo [95]

35

11

ClinicalTrials.gov

To estimate patterns of publication of clinical trials of endometriosis registered in ClinicalTrials.gov

2013

Endometriosis

Inquired = 8

Inferred = 3

Tsikkinis [96]

333

141

ClinicalTrials.gov

To identify all phase III prostate cancer trials in ClinicalTrials.gov with pending results

2015

Prostate cancer

Inferred = 141

Chen [97]

4347

2458

ClinicalTrials.gov

To assess publication rate and reporting of results for completed trials

2016

Interventional clinical trials

Automatic and inferred = unknown

Ramsey [98]

2028

357

ClinicalTrials.gov

To assess the proportion of registered trials that are published

2008

Oncology

Automatic = 357

Hurley [99]

142

62

ClinicalTrials.gov

To assess the delayed publication of clinical trials

2012

Cystic fibrosis

Inferred = 59

Inquired = 3 (contact = 83, responded = 29, published = 3)

Ioannidis [100]

73

21

Cochrane Controlled Clinical Trial Register, ISRCTN, ClinicalTrials.gov, ICTRP, GSK Clinical Study Register, and Indian, ANZCTR, and Chinese Clinical Trial Registries)

To assess publication delay

2011

Influenza A (H1N1) vaccination

Unknown

Ohnmeiss [101]

72

28

ClinicalTrials.gov

To assess the publication of the studies registered on ClinicalTrials.gov.

2015

Spine studies

Automatic and inferred = unknown

Gopal [102]

6251

818

ClinicalTrials.gov

To evaluated the rate of compliance with the FDA mandatory results reporting in clinicaltrials.gov

2012

Interventional studies

Automatic = 818

Lampert [103]

76

40

ClinicalTrials.gov

To determine selective outcome reporting and delay of publication

2015

Epilepsy

Automatic = 32

Inferred = 7

Inquired = 1

Gandhi [104]

46

2

ISRCTN, ClinicalTrials.gov, ANZCTR

To determine the extent to which ongoing and future RCTs in diabetes will ascertain patient-important outcomes

2008

Diabetes

Unknown

The processes used to identify links between clinical trial registries and published articles varied across the set of studies (Figs. 2 and 3). The most common process was to use a combination of automatic and manual processes (24/43, 56%), followed by manual processes only (11/43, 26%), and automatic processes only (3/43, 7%). There were five studies for which the process for identifying published articles was not clear or not provided.
Fig. 2

The processes used to identify links in 81 included studies, including studies that examined automatic links only (red), both automatic and manual processes (purple), manual processes only (blue), and studies that did not report the processes used (grey)

Fig. 3

The proportions of published articles identified in cohorts of registry entries (top, 43 studies, ranging from 34 to 8907 registry entries) and the proportions of registry entries found in cohorts of published articles (bottom, 39 studies, ranging from 54 to 698 articles), with studies that only considered automatic links (red) and all other studies (blue). The circle areas are proportional to the study size

Of the 24 studies that looked for published articles among a cohort of registry entries and used both manual and automatic processes, 12 studies specified the number of published articles identified via each process (Fig. 4). Among these studies, automatic links were used to identify between 13 and 42% (median 23%) of the published articles, and manual processes were used to find a further 5–42% (median 17%) articles that were not available via automatic links.
Fig. 4

The proportions of published articles found in cohorts of registry entries (12 studies, top) and the proportions of registry entries found in cohorts of published articles (16 studies, bottom), by automatic links (grey) and manual processes (blue)

We found no evidence of a change in the overall proportion of publications that could be found via automatic links. A linear regression over the 12 studies—using the publication year as the independent variable—indicated no significant trend in the proportion of available links that can be identified by automatic processes (R 2 = 0.02, p = 0.36, β = 1.28% increase per year).

Studies identifying registry entries from cohorts of publications

There were 39 studies that considered cohorts of publications and identified associated registry entries in one or more of the WHO ICTRP clinical trial registries (Table 2). These studies included a range of 51–698 (median 181) published articles. These studies also covered a range of application domains, varying by the selection of journal, discipline, or study design [5662]. The most commonly used bibliographic database was PubMed alone (19 studies), followed by PubMed in combination with other bibliographic databases (7 studies). To identify registrations, the studies most commonly searched ClinicalTrials.gov in combination with other registries (25 studies), followed by all trial registries included in the WHO ICTRP (9 studies). The median proportion of registry entries that were identified from cohorts of published articles was 54%, ranging from 10% (8 registrations from a cohort of 83 published articles) to 99% (75 registrations from a cohort of 76 published articles).
Table 2

Characteristics of 39 analyses identifying trial registry entries from cohorts of published articles

Study

Published article cohort

Registry entries found

Trial registries included

Study purpose

Study publication year

Application domain

Proportion of links by process

Mathieu [59]

234

323

ClinicalTrials.gov, ISRCTN, ICTRP, national register based on country of first author

Outcome reporting bias

2009

Cardiology, rheumatology, gastroenterology

Automatic = 205

Inferred = 6

Inquired = 23

Chowers [105]

49

60

Unknown

Outcome reporting bias

2009

Anti-retroviral therapy

Unknown

Rasmussen [60]

54

137

ClinicalTrials.gov, ISRCTN, ICTRP, NCI-PDQ

To determine association of trial registration with the results and conclusions of published trials

2009

Oncology drugs

Inferred = 54

Kunath [58]

63

106

ICTRP

To observe trial registration in urology journals

2011

Urology

Automatic = 48

Inferred = 15

Ewart [56]

135

124

ISRCTN, ClinicalTrials.gov, ANZCTR, EU-CTR, National Research Register

Outcome reporting bias

2009

RCTs in five high-impact factor journals

Unknown

You [106]

215

366

ClinicalTrials.gov, ISRCTN

Outcome reporting bias

2011

Oncology drugs

Unknown

Reveiz [109]

89

526

ICTRP

Outcome reporting bias

2012

RCT from Latin America and Caribbean

Unknown

Nankervis [108]

37

109

ICTRP

Outcome reporting bias

2012

Eczema treatment

Automatic = 20

Inferred = 17

Pinto [107]

67

200

ClinicalTrials.gov, ISRCTN, ANZCTR, national register based on country of first author

Completeness of clinical trial registration and the extent of selective reporting of outcomes in published trials

2013

Physical therapy

Automatic = 48

Inferred = 2

Inquired = 17

van de Wetering [26]

185

302

ClinicalTrials.gov, ISRCTN, ICTRP, national register based on country of first author

To determine reporting of trial registration numbers in biomedical publications

2012

RCT from core clinical journals

Automatic = 166

Inquired = 19 (contact = 136, responded = 51, published = 19)

Hannink [110]

218

327

ClinicalTrials.gov, ISRCTN, ANZCTR and others

Outcome reporting bias

2013

Surgical interventions

Automatic = 218

Huser [16]

661

698

ClinicalTrials.gov.gov, ISRCTN

Evaluating adherence to ICMJE policy of mandatory and timely clinical trial registration

2013

Trials published in five ICMJE journals

Automatic = 661

Rosenthal [111]

51

55

ClinicalTrials.gov, ISRCTN, ANZCTR, ChiCTR, UMIN

Outcome reporting bias

2013

Surgery

Automatic, inferred, and inquired = unknown

Hopewell [112]

30

69

Unknown

To observe reporting characteristics of non-primary publications of results of RCTs

2013

RCTs from National Library of Medicine’s set of 121 core clinical journals

Automatic = 30

Babu [113]

121

417

Unknown

To observe clinical trial registration in physical therapy journals

2014

Physical therapy journals

Automatic = 121

Lee [114]

8

83

Unknown

Assessment of compliance of randomized controlled trials in trauma surgery with the CONSORT statement

2013

Trauma surgery

Automatic = 8

Li [115]

252

305

ClinicalTrials.gov, Current Controlled Trials, NTR, ANZCTR, UMIN CTR

Outcome reporting bias

2013

Gastroenterology and herpetology

Automatic = 212

Inferred = 40

Norris [116]

50

107

ICTRP

To determine selective outcome reporting

2013

Pharmacotherapy

Automatic = 30

Inferred = 20

Hardt [117]

85

103

ICTRP(ClinicalTrials.gov, ISRCTN, EU-CTR, NTR, ANZCTR, DRKS, JPRNUMIN, ChiCTR, CTRI), Belgian register

To determine whether the results of registered surgical RCTs are published in journals requiring registration

2013

Ten highest rank surgery journals

Automatic = 68

Inferred = 17

Anand [118]

133

197

ClinicalTrials.gov, ISRCTN, ANZCTR

To determine the registration and design alterations of clinical trials in clinical care

2014

RCT in clinical care medicine

Automatic = 105

Inferred = 28

Mann [119]

140

220

ICTRP

To assess the registration status of RCTs and analyse the correspondence of registered outcomes with published outcomes

2014

Clinical geriatrics

Unknown

Walker [120]

75

76

ISRCTN, ClinicalTrials.gov, national register based on country of first author

Outcome reporting bias

2014

RCTs published in British Medical Journal and the Journal of American Medical Association

Automatic and inferred = unknown

Dekkers [121]

29

54

ICTRP

To compare non-inferiority margins defined in study protocols and trial registry records with margins reported in subsequent publications

2015

Non-inferiority trials submitted 2001–2005 to ethics committees in Switzerland and Netherlands

Automatic and inferred = unknown

Østervig [122]

85

200

ISRCTN, IRCT, EU-CTR, ChiCTR, CRiS, UMIN CTR, ClinicalTrials.gov

To check registration of randomized clinical trials

2015

Trials in Acta Anaesthesiologica Scandinavica

Automatic = 85

Scott [62]

160

181

ISRCTN, NTR, ANZCTR, ClinicalTrials.gov, national register based on country of first author

Selective outcome reporting

2015

Psychiatry journals

Automatic = 150

Inferred = 6

Inquired = 4

De Oliveira [123]

107

201

ISRCTN, ClinicalTrials.gov, ICTRP

Outcome reporting bias

2015

Anaesthesiology

Automatic, inferred, and inquired = unknown

Rayhill [61]

58

225

ClinicalTrials.gov and others

To assess the registration status of RCTs and analyse the correspondence of registered outcomes with published outcomes

2015

Core headache medicine journals

Automatic = 58

Dal-Ré [124]

175

178

ClinicalTrials.gov, ISRCTN, ANZCTR, NTR, EU-CTR, CTRI, DRKS

To evaluate adherence to ICMJE policy on prospective trial registration

2016

Trials in high-impact journals

Unknown

Reveiz [125]

52

144

Registered in any international clinical trial registry

To evaluate the influence of trial registration on reporting quality of RCTs

2010

Highest rank journals

Unknown

Rongen [126]

90

362

ClinicalTrials.gov, ISRCTN, ANZCTR, NTR and others

Outcome reporting bias

2016

Orthopedic surgical interventions

Automatic = 90

Harriman [57]

105

108

ClinicalTrials.gov, ISRCTN, ANZCTR, UMIN CTR, NTR, ChiCTR, IRCT

To assess trial registration, analysis of prospective versus retrospective registration

2016

Clinical trials published in the BMC series

Automatic = 105

Inquired = 0

Vera-Badillo [129]

30

164

ClinicalTrials.gov

Outcome reporting bias

2013

Breast cancer

Automatic and inferred = unknown

McGee [128]

74

307

ICTRP

To determine whether trial is registered and declared registration in the publication

2016

Kidney transplantation

Automatic = 44

Inferred = 30

Huić [127]

149

152

ClinicalTrials.gov

To determine completeness and outcome reporting bias

2011

RCTs published in ICMJE journals

Automatic = 149

Chan [34]

519

553

Unknown

Outcome reporting bias

2005

RCTs indexed in PubMed

Inferred and inquired = unknown

Korevaar [130]

52

351

ClinicalTrials.gov, ISRCTN, national register based on country of first author

To identify the proportion of articles for which the corresponding study had been registered

2014

Test accuracy studies

Automatic = 27

Inferred = 11

Inquired = 14 (contact = 324, responded = 187, published = 14)

Jones [131]

57

123

ClinicalTrials.gov, ISRCTN, ICTRP, national register based on country of first author

Outcome reporting bias

2012

Emergency

Automatic = 23

Inferred = 34

Smaïl-Faugeron [132]

73

317

ICTRP

To assess the registration rate of RCTs

2015

Oral health

Automatic = 50

Inferred = 23

Riehm [133]

40

76

ISRCTN, ClinicalTrials.gov, ICTRP

Outcome reporting bias

2015

Psychosomatic and behavioral health

Automatic = 33

Inferred = 7

The processes used to identify links between clinical trial registries and published articles varied across the set of studies (Figs. 2 and 3). The most common process was to use a combination of automatic and manual processes (21/39, 54%), followed by automatic processes only (9/39, 23%), and manual processes only (2/39, 5%). There were 7 studies for which the processes used to identify registry entries were not clear or not provided.

Of the 21 studies that looked for registry entries among a cohort of published articles and used both manual and automatic processes, 16 reported the number of registry entries found using each process (Fig. 4). Among these studies, automatic links identified between 8 and 97% (median 49%) of registry entries and the manual processes identified between 0 and 28% (median 10%) additional entries.

We found no evidence of a change in the overall proportion of published articles for which registry entries could be found via automatic links. A linear regression over the 16 studies—using the publication year as the independent variable—indicated no significant trend in the proportion of links that can be identified via automatic processes (R 2 = 0.01, p = 0.73, β = 1.40% increase per year).

Discussion

In this systematic review, we found that investigators use both automatic and manual processes to link registry entries and publications and that automatic links could be used to identify some but not all links between registry entries and published articles. We found no evidence that the utility of automatic processes had increased over time.

To the best of our knowledge, no other systematic review has examined the utility of automatic links between trial registries and bibliographic databases. Previous studies that examined the availability of automatic links provided a broad analysis of automatic links made available through ClinicalTrials.gov and PubMed but did not systematically evaluate the proportion of links that could additionally be resolved using manual processes [15, 16, 63]. Other systematic reviews have examined reporting biases as a topic and included subsets of the studies we included [14, 64], but focused on publication rates and the completeness and consistency of outcome reporting, which we did not evaluate here. Our review adds to this area of research by compiling information about a broader group of studies and synthesising what is known about the utility of automatic links, and the need for supplementing automatic processes with manual processes, in studies that rely on links between trial registries and bibliographic databases.

Implications

Our results indicate that automatic links alone are a useful but not sufficient process for measuring rates of registration and publication or associated biases. Relying on automatic links to draw conclusions about the rate of non-publication will likely over-estimate the rate of non-publication. When aiming to monitor compliance with prospective registration of clinical trials, or monitoring publication practices and patterns, the limits of automatic links should be considered.

In general, the proportion of links identified by automatic processes was lower in studies that started with a cohort of registry entries and aimed to identify published articles, compared to studies that started with a cohort of published articles, and aimed to identify registrations. This may be a consequence of journals that have not yet established standards for registration [65] or have not implemented standards for incorporating registry identifiers in the information they pass to bibliographic databases.

The results also have implications for systematic reviews. Systematic review technologies for automating or supporting reviewers rarely consider information from clinical trial registries to improve the searching or screening processes [66] or the prioritisation or scheduling of systematic review updates. Because systematic reviews are already time-consuming [67, 68], the need for additional manual effort in the linking of trial registry entries with their published results may have hindered the development of tools based on this linkage. Areas for development include processes where systematic reviewers compare published reports with information in a registry or use trial registries to identify trials not found in bibliographic databases. By removing these barriers, machine-readable information linking all published studies with all registry entries may provide the catalyst for the increased use of registries in the searching, screening, and prioritising of systematic reviews.

Recommendations

We recommend continued pressure to ensure that journals and publishers adhere to standards of reporting that require unique trial identifiers to be specified in the abstract of the article and reported as part of the metadata provided to bibliographic databases. Trial investigators should also be encouraged to update registry entries with links to published results when journals do not provide the information to bibliographic databases. As we move into an era where the structured reporting of clinical trial results and individual participant data become the standard for responsible clinical trial reporting [69], the inability to automatically identify all sources of information about a clinical trial hinders our ability to reuse and synthesise results across trials. Given the number of extra links that could be identified by examining the full text of articles, we also recommend that journals ensure that clinical trial identifiers are included in the abstract or metadata provided to bibliographic databases.

We additionally recommend a standardised method for identifying links between registry entries and published articles that, for the time being, includes manual validation and checking and avoids drawing conclusions based only on automatic links. A standardised method should include details about what elements of a registry entry should be used to search for published articles and a standard definition for what constitutes published results. Standard reporting for these studies should include the number of registry entries for which searches were performed, the proportion that were identified by automatic links, by inference or by inquiry, and the full details of the dates of trial completion and the length of follow-up. Presenting studies in terms of the time to publication rather than the presence or absence of publication would make a greater proportion of the studies comparable and amenable to meta-analysis.

Limitations

There are two limitations to this review. First, the exclusion of studies for which there was no English language version available meant that we may have missed some studies examining WHO ICTRP registries from countries where English is not the primary language. Second, we used the publication year of the studies as a proxy for estimating changes in the proportions of links identified by each process without considering the period of study that each of the studies covered. This was necessary because a substantial proportion of studies did not report the range and distribution of publication and registration dates in the cohorts they examined, and this may have influenced our analysis of the trends in the utility of the automatic processes.

Conclusions

In this systematic review, we have quantified the use and utility of the processes that are used to link trial registries to bibliographic databases. The results indicate that manual processes are still used extensively and that the gap between what can be identified via automatic processes and what must be identified via manual processes persists. Future improvements in the quality of automatic linking between clinical trial registries and bibliographic databases should come from continued pressure on journals to enforce policies and practices to consistently include registry identifiers in published reports.

Abbreviations

ICTRP: 

International Clinical Trial Registry Platform

WHO: 

World Health Organization

Declarations

Acknowledgements

Not applicable.

Funding

RB is supported by a Macquarie University Postgraduate Scholarship. AD and FB report funding from the Agency for Healthcare Research and Quality (R03HS024798).

Availability of data and materials

All data generated or analysed during this study are included in this published article and its Additional files 1, 2, and 3.

Authors’ contributions

RB and AD drafted the manuscript, conducted the review, critically revised the manuscript, and approved the final version. FB critically revised the manuscript and approved the final version. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University
(2)
Computational Health Informatics Program, Boston Children’s Hospital
(3)
Departments of Pediatrics and Emergency Medicine, Harvard Medical School

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