Data sharing through an NIH central database repository: a cross-sectional survey of BioLINCC users

State of open science in cancer research

PURPOSE

This study has been focused on assessing the Open Science scenario of cancer research during the period 2011-2021, in terms of the derived scientific publications and raw data dissemination.

METHODS

A cancer search equation was executed in the Science Citation Index-Expanded, collecting the papers signed by at least one Spanish institution. The same search strategy was performed in the Data Citation Index to describe dataset diffusion.

RESULTS

50,822 papers were recovered, 71% of which belong to first and second quartile journals. 59% of the articles were published in Open Access (OA) journals. The Open Access model and international collaboration positively conditioned the number of citations received. Among the most productive journals stood out Plos One, Cancers, and Clinical and Translational Oncology. 2693 genomics, proteomics and metabolomics datasets were retrieved, being Gene Expression Omnibus the favoured repository.

CONCLUSIONS

There has been an increase in oncology publications in Open Access. Most were published in first quartile journals and received higher citations than non-Open Access articles, as well as when oncological investigation was performed between international research teams, being relevant in the context of Open Science. Genetic repositories have been the preferred for sharing oncology datasets. Further investigation of research and data sharing in oncology is needed, supported by stronger Open Science policies, to achieve better data sharing practices among three scientific main pillars: researchers, publishers, and scientific organizations.

Improved Prognostic Performance of Cardiac Power Output With Right Atrial Pressure: A Subanalysis of the ESCAPE Trial

BACKGROUND

The initial derivation of cardiac power output (CPO) included the difference between mean arterial pressure (MAP) and right atrial pressure (RAP) in the numerator, before multiplying by cardiac output (CO). We hypothesized that the inclusion of RAP (CPO-RAP) would enhance the prognostic performance of this parameter in those with an elevated RAP.

METHODS AND RESULTS

We obtained patient-level data from the ESCAPE trial via the Biolincc database. Participants with full final hemodynamics were included in the analysis. The CPO-RAP was calculated as [(MAP - RAP) × CO)]/451 Watts (W), and the CPO was calculated as (MAP × CO)/451. The primary outcome was freedom from left ventricular assist device, heart transplant, or death at 6 months. Included participants (n = 157) were a median of 58 years of age (interquartile range [IQR] 49-67 years), 27% were women, and 59% had ischemic cardiomyopathy. The median CPO was 0.70 W (IQR 0.50-0.90 W), and the median CPO-RAP was 0.62 W (IQR 0.47-0.79 W). In univariable logistic regressions, the CPO was not associated with the primary outcome (odds ratio 0.32, 95% confidence interval 0.08-1.29, P = .11), but the CPO-RAP was (odds ratio 0.10, 95% confidence interval 0.02-0.54, P < .01). In Kaplan-Meier analyses, there were no significant difference in outcomes with CPO (76% vs 64%, P = .08), but for CPO-RAP, there were significant differences in outcomes (81% vs 63%, P = .01). When further delineating CPO-RAP by RAP above or below the median, there was no significant difference in the outcome for participants with a RAP 8 or less (94% vs 79%, P = .07), but a significant difference in participants with a RAP of more than 8 mm Hg (66% vs 45%, P < .05).

CONCLUSIONS

The inclusion of RAP resulted in a significant association with the primary outcome; CPO alone was not.

Status, use and impact of sharing individual participant data from clinical trials: a scoping review

OBJECTIVES

To explore the impact of data-sharing initiatives on the intent to share data, on actual data sharing, on the use of shared data and on research output and impact of shared data.

ELIGIBILITY CRITERIA

All studies investigating data-sharing practices for individual participant data (IPD) from clinical trials.

SOURCES OF EVIDENCE

We searched the Medline database, the Cochrane Library, the Science Citation Index Expanded and the Social Sciences Citation Index via Web of Science, and preprints and proceedings of the International Congress on Peer Review and Scientific Publication. In addition, we inspected major clinical trial data-sharing platforms, contacted major journals/publishers, editorial groups and some funders.

CHARTING METHODS

Two reviewers independently extracted information on methods and results from resources identified using a standardised questionnaire. A map of the extracted data was constructed and accompanied by a narrative summary for each outcome domain.

RESULTS

93 studies identified in the literature search (published between 2001 and 2020, median: 2018) and 5 from additional information sources were included in the scoping review. Most studies were descriptive and focused on early phases of the data-sharing process. While the willingness to share IPD from clinical trials is extremely high, actual data-sharing rates are suboptimal. A survey of journal data suggests poor to moderate enforcement of the policies by publishers. Metrics provided by platforms suggest that a large majority of data remains unrequested. When requested, the purpose of the reuse is more often secondary analyses and meta-analyses, rarely re-analyses. Finally, studies focused on the real impact of data-sharing were rare and used surrogates such as citation metrics.

CONCLUSIONS

There is currently a gap in the evidence base for the impact of IPD sharing, which entails uncertainties in the implementation of current data-sharing policies. High level evidence is needed to assess whether the value of medical research increases with data-sharing practices.

A composite metric for predicting benefit from spironolactone in heart failure with preserved ejection fraction

AIMS

The TOPCAT trial showed no benefit for spironolactone in heart failure patients with preserved ejection fraction (HFpEF). Post-hoc, spironolactone helped participants from the Americas, but not Eastern Europe. Determining which patients with HFpEF could respond like TOPCAT's responders should help guide their care. We aimed to develop a TOPCAT Trial Score (TS) as a composite metric to identify such patients.

METHODS AND RESULTS

From the TOPCAT individual-level data, we calculated a TS of age, body mass index, systolic blood pressure, heart rate, creatinine, potassium, glucose, left ventricular ejection fraction, and left atrial volume for each participant as a weighted distance in multidimensional space from the theoretical perfectly average Americas participant. Logistic regression was used to measure TS and spironolactone as predictors of TOPCAT's primary outcome. The relationship between TS and the H₂ FPEF score was also determined in TOPCAT and a registry cohort of real-world patients in the U.S. with HFpEF. A bimodal distribution of TS separated American (n = 1766) and Eastern European (n = 1,677) participants. Those with lower TS showed no significant response to spironolactone. Spironolactone's benefit rose with rising TS [β_interaction  = -0.28 (P < 0.01)]. Significantly more American participants had benefit from spironolactone based on higher TS (> 1.14), in addition to higher likelihood of HFpEF based on higher H₂ FPEF scores (≥3). The cohort of real-world patients with HFpEF had even higher TS than American TOPCAT participants.

CONCLUSIONS

Patients with HFpEF can be quantified by the TS to capture the likelihood of benefit from spironolactone.

Intent to share Annals of Internal Medicine's trial data was not associated with data re-use

OBJECTIVE

To explore the impact of the Annals of Internal Medicine (AIM) data-sharing policy for randomized controlled trials (RCTs) in terms of output from data-sharing (i.e. publications re-using the data).

STUDY DESIGN AND SETTING

Retrospective study. RCTs published in the AIM between 2007 and 2017 were retrieved on PubMed. Publications where the data had been re-used were identified on Web of Science. Searches were performed by two independent reviewers. The primary outcome was any published re-use of the data (re-analysis, secondary analysis, or meta-analysis of individual participant data [MIPD]), where the first, last and corresponding authors were not among the authors of the RCT. Analyses used Cox (primary analysis) models adjusting for RCTs characteristics (registration: https://osf.io/8pj5e/).

RESULTS

185 RCTs were identified. 106 (57%) mentioned willingness to share data and 79 (43%) did not. 208 secondary analyses, 67 MIPD and no re-analyses were identified. No significant association was found between intent to share and re-use where the first, last and corresponding authors were not among the authors of the primary RCT (adjusted hazard ratio = 1.04 [0.47-2.30]).

CONCLUSION

Over ten years, RCTs published in AIM expressing an intention to share data were not associated with more extensive re-use of the data.

Aortic pulsatility index predicts clinical outcomes in heart failure: a sub-analysis of the ESCAPE trial

AIMS

Aortic pulsatility index (API), calculated as (systolic-diastolic blood pressure)/pulmonary capillary wedge pressure (PCWP), is a novel haemodynamic measurement representing both cardiac filling pressures and contractility. We hypothesized that API would better predict clinical outcomes than traditional haemodynamic metrics of cardiac function.

METHODS AND RESULTS

The Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness (ESCAPE) trial individual-level data were used. Routine haemodynamic measurements, including Fick cardiac index (CI), and the advanced haemodynamic metrics of API, cardiac power output (CPO), and pulmonary artery pulsatility index (PAPI) were calculated after final haemodynamic-monitored optimization. The primary outcome was a composite endpoint of death or need for orthotopic heart transplant (OHT) or left ventricular assist device (LVAD) at 6 months. A total of 433 participants were enrolled in the ESCAPE trial of which 145 had final haemodynamic data. Final API measurements predicted the primary outcome, OR 0.47 (95% CI 0.32-0.70, P < 0.001), while CI, CPO, and PAPI did not. Receiver operator characteristic analyses of final advanced haemodynamic measurements indicated API best predicted the primary outcome with a cutoff of 2.9 (sensitivity 76.2%, specificity 55.3%, correctly classified 61.4%, area-under-the-curve 0.71), compared with CPO, CI, and PAPI. Kaplan-Meier analyses indicated API ≥ 2.9 was associated with greater freedom from the primary outcome (83.5%), compared with API < 2.9 (58.4%), P = 0.001. While PAPI was also significantly associated, CI and CPO were not.

CONCLUSIONS

The novel haemodynamic measurement API better predicted clinical outcomes in the ESCAPE trial when compared with traditional invasive haemodynamic metrics of cardiac function.

Brief introduction of medical database and data mining technology in big data era

Data mining technology can search for potentially valuable knowledge from a large amount of data, mainly divided into data preparation and data mining, and expression and analysis of results. It is a mature information processing technology and applies database technology. Database technology is a software science that researches manages, and applies databases. The data in the database are processed and analyzed by studying the underlying theory and implementation methods of the structure, storage, design, management, and application of the database. We have introduced several databases and data mining techniques to help a wide range of clinical researchers better understand and apply database technology.

The National MDS Natural History Study: design of an integrated data and sample biorepository to promote research studies in myelodysplastic syndromes

Myelodysplastic syndromes (MDS), a spectrum of heterogeneous hematopoietic stem cell diseases, vary in clinical severity, response to therapy, and propensity toward progression to acute myeloid leukemia. These are acquired clonal disorders resulting from somatic mutations within the hematopoietic stem or progenitor cell population. Understanding the natural history and the risk of developing leukemia and other adverse outcomes is dependent on access to well-annotated biospecimens linked to robust clinical and molecular data. To facilitate the acquisition and distribution of MDS biospecimens to the wider scientific community and support scientific discovery in this disease, the National MDS Natural History study was initiated by the National Heart, Lung, and Blood Institute (NHLBI) and is being conducted in collaboration with community hospitals and academic medical centers supported by the National Cancer Institute (NCI). The study will recruit up to 2000 MDS patients or overlapping myeloproliferative neoplasms (MDS/MPN) and up to 500 cases of idiopathic cytopenia of undetermined significance (ICUS). The National MDS Natural History Study (NCT02775383) will offer the world's largest disease-focused tissue biobank linked to longitudinal clinical and molecular data in MDS. Here, we report on the study design features and describe the vanguard phase of 200 cases. The study assembles a comprehensive clinical database, quality of life results, laboratory data, histopathology slides and images, genetic information, hematopoietic and germline tissues representing high-quality biospecimens and data from diverse centers across the United States. These resources will be available to the scientific community for investigator-initiated research.

Overview and experience of the YODA Project with clinical trial data sharing after 5 years

The Yale University Open Data Access (YODA) Project has facilitated access to clinical trial data since 2013. The purpose of this article is to provide an overview of the Project, describe key decisions that were made when establishing data sharing policies, and suggest how our experience and the experiences of our first two data generator partners, Medtronic, Inc. and Johnson & Johnson, can be used to enhance other ongoing or future initiatives.

Biomedical journal speed and efficiency: a cross-sectional pilot survey of author experiences

Background

Although the peer review process is believed to ensure scientific rigor, enhance research quality, and improve manuscript clarity, many investigators are concerned that the process is too slow, too expensive, too unreliable, and too static. In this feasibility study, we sought to survey corresponding authors of recently published clinical research studies on the speed and efficiency of the publication process.

Methods

Web-based survey of corresponding authors of a 20% random sample of clinical research studies in MEDLINE-indexed journals with Ovid MEDLINE entry dates between December 1 and 15, 2016. Survey addressed perceived manuscript importance before first submission, approximate first submission and final acceptance dates, and total number of journal submissions, external peer reviews, external peer reviewers, and revisions requested, as well as whether authors would have considered publicly sharing their manuscript on an online platform instead of submitting to a peer-reviewed journal.

Results

Of 1780 surveys distributed, 27 corresponding authors opted out or requested that we stop emailing them and 149 emails failed (e.g., emails that bounced n = 64, returned with an away from office message n = 70, or were changed/incorrect n = 15), leaving 1604 respondents, of which 337 completed the survey (21.0%). Respondents and non-respondents were similar with respect to study type and publication journals’ impact factor, although non-respondent authors had more publications (p = 0.03). Among respondents, the median impact factor of the publications’ journal was 2.7 (interquartile range (IQR), 2.0–3.6) and corresponding authors’ median h-index and number of publications was 9 (IQR, 3–20) and 27 (IQR, 10–77), respectively. The median time from first submission to journal acceptance and publication was 5 months (IQR, 3–8) and 7 months (IQR, 5–12), respectively. Most respondents (62.0%, n = 209) rated the importance of their research as a 4 or 5 (5-point scale) prior to submission. Median number of journal submissions was 1 (IQR, 1–2), external peer reviews was 1 (IQR, 1–2), external peer reviewers was 3 (IQR, 2–4), and revisions requested was 1 (IQR, 1–1). Sharing manuscripts to a public online platform, instead of submitting to a peer-reviewed journal, would have been considered by 55.2% (n = 186) of respondents.

Conclusion

Corresponding authors have high perceptions of their research and reported requiring few manuscript submissions prior to journal acceptance, most commonly by lower impact factor journals.

Electronic supplementary material

The online version of this article (10.1186/s41073-017-0045-8) contains supplementary material, which is available to authorized users.

Data Sharing and Cardiology: Platforms and Possibilities

Sharing deidentified patient-level research data presents immense opportunities to all stakeholders involved in cardiology research and practice. Sharing data encourages the use of existing data for knowledge generation to improve practice, while also allowing for validation of disseminated research. In this review, we discuss key initiatives and platforms that have helped to accelerate progress toward greater sharing of data. These efforts are being prompted by government, universities, philanthropic sponsors of research, major industry players, and collaborations among some of these entities. As data sharing becomes a more common expectation, policy changes will be required to encourage and assist data generators with the process of sharing the data they create. Patients also will need access to their own data and to be empowered to share those data with researchers. Although medicine still lags behind other fields in achieving data sharing's full potential, cardiology research has the potential to lead the way.

Availability and Use of Shared Data From Cardiometabolic Clinical Trials

BACKGROUND

Sharing of patient-level clinical trial data has been widely endorsed. Little is known about how extensively these data have been used for cardiometabolic diseases. We sought to evaluate the availability and use of shared data from cardiometabolic clinical trials.

METHODS

We extracted data from ClinicalStudyDataRequest.com, a large, multisponsor data-sharing platform hosting individual patient-level data from completed studies sponsored by 13 pharmaceutical companies.

RESULTS

From January 2013 to May 2017, the platform had data from 3374 clinical trials, of which 537 (16%) evaluated cardiometabolic therapeutics (phase 1, 36%; phase 2, 17%; phase 2/3, 1%; phase 3, 42%; phase 4, 4%). They covered 74 therapies and 398 925 patients. Diabetes mellitus (60%) and hypertension (15%) were the most common study topics. Median time from study completion to data availability was 79 months. As of May 2017, ClinicalStudyDataRequest.com had received 318 submitted proposals, of which 163 had signed data-sharing agreements. Thirty of these proposals were related to cardiometabolic therapies and requested data from 79 unique studies (15% of all trials, 29% of phase 3/4 trials). Most (96%) data requesters of cardiometabolic clinical trial data were from academic centers in North America and Western Europe, and half the proposals were unfunded. Most proposals were for secondary hypothesis-generating questions, with only 1 proposed reanalysis of the original study primary hypothesis. To date, 3 peer-reviewed articles have been published after a median of 19 months (9-32 months) from the data-sharing agreement.

CONCLUSIONS

Despite availability of data from >500 cardiometabolic trials in a multisponsor data-sharing platform, only 15% of these trials and 29% of phase 3/4 trials have been accessed by investigators thus far, and a negligible minority of analyses have reached publication.

Use of the National Heart, Lung, and Blood Institute Data Repository

BACKGROUND

Research on data sharing from clinical trials has focused on elucidating perceptions, barriers, and attitudes among trialists and study participants with respect to sharing data. However, little information exists regarding utilization or associated publication of articles once clinical trial data have been widely shared.

METHODS

We analyzed administrative records of investigator requests for data access, linked publications, and bibliometrics to describe the use of the National Heart, Lung, and Blood Institute data repository.

RESULTS

From January 2000 through May 2016, a total of 370 investigators requested data from 1 or more clinical trials. Requests for trial data have been increasing, with 195 investigators (53%) initiating requests during the last 4.4 years of the study period. The predominant reason for requesting data was post hoc secondary analysis of new questions (72%), followed by analytic or statistical approaches to clinical trials (9%) and meta-analyses or pooled study research (7%). Of 172 requests with online project descriptions, only 2 requests were initiated for reanalysis of primary-outcome findings. Data from 88 of 100 available clinical trials were requested at least once, and the median time from repository availability to first request was 235 days. A total of 277 articles were published on the basis of data from 47 trials. Citation metrics from 224 articles indicated that half of the publications have cumulative citations that rank in the top 34% normalized for subject category and year of publication.

CONCLUSIONS

Demand for trial data for secondary analysis has been increasing. Requesting data for the a priori purpose of reanalysis or verification of original findings was rare.