Lung Adenocarcinoma Clinical Data with Effectiveness Scores

874 patients with adenocarcinoma of the lung, each with 47 clinical data elements, form the cohort for developing a novel effectiveness metric. The E-score metric, created by author Gregory C. Bloom, incorporates statistical p-values and quality A-scores to assess the utility of biomedical data elements. This dataset from 2020 provides the foundation for testing this metric, which ranks elements like age-at-diagnosis and tobacco-use based on both outcome correlation and data quality.

Use Cases

• Analyze the relationship between an element's p-value for overall survival and its A-score for quality attributes like Completeness and Consistency.
• Rank clinical data elements such as age-at-diagnosis, gender, and tobacco-use by their calculated E-score to prioritize data collection in research.
• Investigate why elements like surgery-site and pathological-TNM stage have lower A-scores and E-scores despite potential statistical significance.
• Validate the E-score metric's ability to down-rank elements with high acquisition costs, as demonstrated for histologic-type.

Strengths

• The cohort consists of 874 patients, providing a substantive sample for analysis.
• Each patient record includes 47 distinct clinical data elements, offering a multi-faceted view of lung adenocarcinoma cases.
• The dataset is the basis for a peer-reviewed, novel methodology (E-score) that combines statistical and data quality metrics.

Limitations

• The dataset is static and was last updated in 2020, potentially limiting its relevance to current clinical practices.
• The cohort is specific to lung adenocarcinoma patients, limiting generalizability to other cancer types or diseases.
• Without access to the raw columnar data or sample records, the exact structure and potential data issues are unknown.

Provenance

Source

Dryad digital repository.

Collection Method

Clinical data from a cohort of lung adenocarcinoma patients, with p-values calculated via Cox proportional hazard univariable regression and A-scores derived from quantifying four quality attributes.

Freshness

Static dataset last updated on 2020-06-24.