SPIRIT Evaluations of IDD clinical Trial Protocols

Description:This dataset supports the study “SPIRIT-Based Prediction of Clinical Trial Completion in Intervertebral Disc Degeneration,” providing comprehensive protocol-level data for interventional clinical trials addressing intervertebral disc degeneration (IDD) between 2013 and 2024.

Contents:

clinical trials.csv: Contains structured metadata on 18 interventional clinical trials for IDD extracted from ClinicalTrials.gov. Fields include NCT registration number, trial title, intervention type, sponsor category, start and end dates, enrolment, trial status (completed/failed), and other core design features.

SPIRIT Evaluations.csv: Provides binary adherence scoring for each protocol using a 64-item reduction of the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) 2013 checklist. Each row corresponds to a trial protocol, each column to a SPIRIT item, with ‘1’ denoting compliance and ‘0’ non-compliance.

creative-commons-attribution-40-international-cc-40.jsonld: Machine-readable license declaration (CC-BY 4.0).

Provenance and Methodology:Data was systematically collected from ClinicalTrials.gov using a PRISMA-compliant strategy. SPIRIT adherence was independently assessed for each trial according to consensus-based criteria (see Chemorion et al., 2024 for methodology). All trials are indexed with their NCT numbers, and adherence scoring follows the ASPIRE framework for protocol quality assessment.

Intended Use:The dataset is designed to support secondary research on clinical trial protocol quality, reproducibility, and predictive analytics for trial success/failure. It is particularly relevant for meta-research, biomedical informatics, and policy initiatives promoting protocol transparency and reporting standards in musculoskeletal and spine research.

Licensing:This dataset is made available under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Users are free to share and adapt the materials with appropriate attribution.