Consensus Statement: Recommendations on Actionable Biomarker Testing for Thyroid Cancer Management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Thyroid cancer management is rapidly changing. The identification of actionable biomarkers through both germline and somatic testing are now an integral part of directing patient management. However, deficiencies and disparities within existing thyroid cancer biomarker test approaches are resulting in inconsistent application for patient care. An expert panel was convened to create consensus biomarker testing algorithms and recommendations on actionable biomarker testing for patients diagnosed with medullary thyroid cancer, non-anaplastic follicular cell-derived thyroid cancer, or anaplastic follicular cell-derived thyroid cancer who may benefit from targeted therapies. A review of international guidelines was performed to determine the current state, and a literature review was carried out to further evaluate the evidence supporting the use of actionable biomarkers in patients diagnosed with thyroid cancer. Thyroid biomarker-related gaps impacting patient care were also discussed, with an emphasis on the importance of a multidisciplinary team approach for optimal patient care. The recommendations are presented with the aim to help physicians navigate the current thyroid cancer biomarker testing landscape with its many challenges, balancing aspirational care with what is practical and feasible in terms of economic realities and jurisdictional constraints. By remaining therapy-agnostic, these algorithms and recommendations are broadly applicable.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it