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

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. 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. 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.

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 [ 27 – 29 ] and studies that considered reporting biases but could not be included because the linking was atypical or there was no linking performed [ 30 – 33 ]. 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 [ 34 – 37 ], conference or meeting abstracts [ 38 – 42 ], internal company documents [ 17 ], Food and Drug Administration (FDA) documents or new drug approvals [ 43 – 47 ], 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 PRISMA flow diagram of study selection for a search and screening process that resulted in the inclusion of 81 studies 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 Characteristics of 43 analyses identifying published articles from cohorts of trial registry entries 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 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 ) 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 ) 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). 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 [ 56 – 62 ]. 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 Characteristics of 39 analyses identifying trial registry entries from cohorts of published articles 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).

Clinical trial registries were established to improve transparency and completeness in the reporting of clinical trials [ 1 – 6 ]. 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 [ 7 – 11 ]. 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 [ 17 – 19 ]. 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 ].

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. 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. 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. 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.

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.

Additional file 1: Search strategy for PubMed. Search strategy for MEDLINE via PubMed. (PDF 259 kb) Additional file 2: Search strategy for Embase. Search strategy for Embase via Ovid. (PDF 309 kb) Additional file 3: PRISMA checklist. PRISMA Checklists with manuscript page number reference. (PDF 277 kb) Search strategy for PubMed. Search strategy for MEDLINE via PubMed. (PDF 259 kb) Search strategy for Embase. Search strategy for Embase via Ovid. (PDF 309 kb) PRISMA checklist. PRISMA Checklists with manuscript page number reference. (PDF 277 kb)