The Current Landscape of Clinical Studies Focusing on Thyroid Cancer: A Comprehensive Analysis of Study Characteristics and Their Publication Status
Bibliographic record
Abstract
Background A better understanding of the current characteristics of clinical trials on thyroid cancer (TC) is important to improve trial designs and identify neglected areas of research. However, there is a lack of a thorough understanding of the clinical studies on TC. Therefore, this study aimed to present a comprehensive overview of clinical trials on TC based on the ClinicalTrials.gov database and evaluate their publication status. Methods We searched for TC-related clinical studies registered in the ClinicalTrials.gov database before December 2018 by using the keyword “thyroid cancer” and assessed the characteristics of the included trials. We searched the publication status of primary completed studies in PubMed and Google Scholar. Results A total of 450 studies were identified for analysis, including 333 (74.0%) interventional studies and 117 (26.0%) observational studies. Interventional studies about TC were commonly non-randomized (67.6%), single-arm (55.6%), single-center (76.3%), and early-phase (60.0%) trials. The major category for which studies were performed was for target drug-related therapy (53.6%). In addition, 57.0% of the primary completed interventional studies were published. The published studies were more commonly primary completed studies after 2010 and used randomization and were less commonly designed as single-arm studies and were conducted in the USA/Canada, compared to non-published studies (P < 0.05 for all). The median time from primary completion to publication was 46.5 months, and the time decreased to 36.5 months after 2010. Studies conducted in the USA/Canada [odds ratio (OR) = 9.43, P = 0.020] and multi-center studies (OR = 6.55, P = 0.021) significantly increased the potential of publication in high-impact journals. Conclusions High-quality, randomized phase 3 trials regarding TC are still insufficient. Therefore, more efforts are needed to improve the treatment of poor prognostic TC and timely publication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.089 | 0.294 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.042 | 0.043 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".