All submissions must include a Data Availability Statement describing where underlying data can be accessed or why access is restricted.

Data sharing must comply with institutional, ethical, and legal requirements to protect patient privacy.

Use repositories that provide persistent identifiers and clear access terms for clinical datasets.

When data cannot be shared, provide aggregated or anonymized summaries to support verification.

Provide repository access dates and contact points for restricted data requests.

Use standardized file formats to improve long-term accessibility.

Document de-identification methods for patient-level data.

Provide repository access dates and contact details for restricted datasets.

Use controlled access for sensitive patient data and document the process.

Include README files, data dictionaries, and variable definitions.

Provide software versions and dependencies for analytic code.

Use persistent identifiers such as DOIs for datasets and code.

Specify embargo periods and rationale for delayed release.

Document de-identification procedures and consent restrictions.

Cite datasets in the references to ensure attribution and tracking.

Ensure repository links are active and accessible at submission.

Use open formats such as CSV or TXT when possible.

Describe any access committees or approvals needed for data requests.

Include dataset version numbers when updates are expected.

Document preprocessing steps to support replication and audit trails.

State whether data are available immediately or after a defined embargo.

Provide clear criteria for approving data access requests.

Describe how patient privacy is protected in shared datasets.

Include code repositories and dependencies where analytic scripts are used.

Cite data and code resources in the references section.

Provide access criteria for controlled datasets and expected timelines.

Use secure repositories that comply with privacy regulations.

Include data dictionaries to clarify variable definitions and coding.

Ensure datasets are aligned with reported results and tables.

Describe any data use agreements or consent restrictions.

Provide persistent identifiers for shared code repositories.

Specify whether datasets will be updated after publication.

Provide a clear data sharing timeline for embargoed datasets.

Include access instructions for controlled repositories.

State whether data are open, restricted, or available upon request.

Provide contact details for data access queries.

Ensure data records align with reported tables and figures.

Describe any data use agreements or licensing restrictions.

Use clear file naming conventions to improve reuse.

Confirm that repository permissions allow reviewer access if needed.

State whether anonymized datasets are available for secondary analyses.

Include analysis scripts for reproducibility when feasible.

Provide a contact email for data access inquiries.

Clarify whether data can be shared with qualified researchers upon request.

Provide data sharing timelines aligned with funder requirements.

Include structured metadata for datasets to support reuse.

Confirm datasets reflect the final analyzed cohort.

Ensure repository records include clear access instructions.

Provide data citations with DOIs when possible.

Document any data use agreements or restrictions.

Provide links to data use agreements when required.

Ensure anonymization steps are described in the data statement.

Document data provenance and collection dates when relevant.

Authors may deposit accepted or published versions in institutional or subject repositories with proper citation.

Data access requests should include contact points and expected response timelines.

Where applicable, include data citation in the references to ensure proper attribution.