Bayesian Network Meta-Analysis of Targeted Therapies for Advanced Thyroid Cancer

A 33.0 KB Excel file containing results from a Bayesian network meta-analysis of 9 randomized controlled trials involving 1,760 patients with radioiodine-refractory differentiated thyroid cancer. The analysis, authored by Pin Wang and uploaded to figshare, compares the efficacy and safety of targeted therapies like lenvatinib, anlotinib, apatinib, and cabozantinib, with outcomes including progression-free survival and objective response rate. The dataset was last updated on March 18, 2026.

Use Cases

• Compare the relative efficacy of targeted therapies for radioiodine-refractory thyroid cancer based on hazard ratios for progression-free survival.
• Rank treatments by safety profile based on the analysis of grade ≥3 adverse events.
• Evaluate time-dependent efficacy patterns of tyrosine kinase inhibitors mentioned in the results.
• Assess objective response rates across different drug interventions for metastatic thyroid cancer.

Strengths

• Analysis is based on 9 randomized controlled trials, a standard for clinical evidence.
• Includes data from 1,760 patients, providing a substantive sample for meta-analysis.
• Employs Bayesian network meta-analysis, a sophisticated statistical method for comparing multiple treatments.
• Reports specific statistical results, such as hazard ratios and SUCRA ranking scores for treatments like lenvatinib.

Limitations

• Row count and column-level documentation are absent; field semantics must be inferred after download.
• The dataset is very small (33.0 KB), indicating limited raw data, likely containing only summary results.
• Data may reflect publication or selection bias inherent to the systematic review and meta-analysis methodology.

Provenance

Source

figshare, author Pin Wang.

Collection Method

Systematic search of six electronic databases and subsequent Bayesian network meta-analysis of identified randomized controlled trials.

Freshness

Last updated 2026-03-18 07:35:10; freshness should be verified.