Table 1_Muscle matters: automated CT-based body composition analysis predicts survival in

45 HNSCC patients treated with Nivolumab or Pembrolizumab were assessed using automated thoracic CT scans to measure skeletal muscle, bone, and adipose tissue volumes. Frederic Jungbauer published this study on figshare in March 2026 under a CC-BY-4.0 license. The analysis identified the skeletal muscle to bone ratio and serum albumin levels as independent prognostic factors for overall survival.

Use Cases

• Predicting overall survival in head and neck cancer patients based on CT-derived body composition markers like the SM/B ratio.
• Analyzing the relationship between changes in body composition (e.g., ≥8% SM/B decrease) and patient outcomes during immunotherapy.
• Building multivariate survival models incorporating clinical factors (albumin, ECOG status, BMI) with automated imaging biomarkers.
• Investigating sex-based differences in prognostic factors for cancer survival using clinical and imaging data.

Strengths

• Dataset includes 45 patient records with detailed clinical (age, sex, BMI, albumin) and imaging-derived body composition metrics.
• Analysis provides specific hazard ratios (e.g., SM/B ratio HR: 0.25) and survival times (median OS 8.13 months) for key prognostic factors.
• Data is openly shared under a permissive CC-BY-4.0 license, facilitating reuse and validation.

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale model training.
• Column-level documentation is absent; field semantics must be inferred after download.
• The 24.2 KB file size suggests a very limited scope, likely containing summary results rather than raw patient-level data.

Provenance

Source

figshare, author Frederic Jungbauer.

Collection Method

Retrospective assessment of patient CT scans using automated body composition analysis.

Time Range

The study period is not specified in the provided metadata.

Freshness

Last updated 2026-03 13:05:35; freshness should be verified.

Geography

The geographic origin of the patient cohort is not specified.