Management of childhood cancer survivors at risk for thyroid function abnormalities: A Delphi study
Bibliographic record
Abstract
BACKGROUND: Thyroid function abnormalities can occur after treatment for childhood cancer. Evidence for the management of thyroid dysfunction among asymptomatic childhood cancer survivors (CCS) is lacking. We used a Delphi consensus methodology to expand guidelines for screening asymptomatic CCS at risk for thyroid dysfunction and explore recommendations for the clinical management of abnormal results. PROCEDURE: A Delphi panel of 40 expert physicians representing oncology, endocrinology, and primary care participated in three rounds of anonymous, iterative questionnaires formatted as clinical scenarios. Consensus is defined as ≥ 90% of panelists agree with recommendation and disagreement as < 70% agree. RESULTS: Panelists reached consensus that CCS treated with radiation including neck, total body, whole brain, brain including the hypothalamic-pituitary axis (HPA), and therapeutic meta-iodobenzylguanidine (MIBG) should have annual, lifelong screening using serum thyroid-stimulating hormone (TSH) and free T4 starting within one year off-treatment (98%). Panelists disagreed on continuing to screen CCS for thyroid dysfunction after immunotherapy associated with acute thyroid injury (31%-50%). There was also disagreement on indications for brain (17%-43%) or thyroid (50%-65%) imaging, laboratory tests to assess the HPA (29%-75%), and TSH threshold to initiate treatment of subclinical hypothyroidism. Lack of evidence was the most frequent rationale panelists offered for not recommending additional testing or medications. Panelists' recommendations did not vary by geography, specialty, or survivorship clinical experience. CONCLUSIONS: Consensus was reached on most recommendations for screening and management of cancer treatment-related thyroid dysfunction. Screening after completion of thyroid-toxic immunotherapy, indications for imaging, and treatment of subclinical hypothyroidism are areas of disagreement for further investigation.
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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 | 0.050 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".