To Stimulate or Withdraw? A Cost-Utility Analysis of Recombinant Human Thyrotropin<i>Versus</i>Thyroxine Withdrawal for Radioiodine Ablation in Patients with Low-Risk Differentiated Thyroid Cancer in the United States
Bibliographic record
Abstract
CONTEXT: Use of recombinant human TSH (rhTSH) prior to radioactive iodine remnant ablation for patients with differentiated thyroid cancer avoids the hypothyroid state and improves quality of life. European studies have shown that use of rhTSH vs. thyroid hormone withdrawal is a cost-effective method for preparing patients for ablation. OBJECTIVE: The objective of the study was to determine the cost-utility of rhTSH prior to ablation in the United States. DESIGN/SETTING/SUBJECTS: A Markov decision model was developed for a hypothetical group of adult patients with low-risk differentiated thyroid cancer who were prepared for ablation by either rhTSH or thyroid hormone withdrawal. Patients entered the model after initial thyroidectomy; follow-up was in accordance with current American Thyroid Association guidelines. Input data were obtained from the literature, Medicare reimbursement schedule, and U.S. Bureau of Labor Statistics. Sensitivity analyses were performed for all clinically relevant inputs. MAIN OUTCOME MEASURES: Cost-utility, measured in U.S. dollars per quality-adjusted life-year ($/QALY), was measured. RESULTS: Use of rhTSH yielded an incremental cost-utility of $52,554/QALY (95% confidence interval $52,058-53,050/QALY) (incremental societal cost of $1,365/patient; incremental benefit of 0.026 QALY/patient). The majority of cost and benefit occurs during the preablation, ablation, and postablation period; differences in cost are due to cost of rhTSH and differences in productivity loss (days off work). The model was most sensitive to changes in time off work, cost of rhTSH, and differences in utilities of health states. CONCLUSIONS: In the United States, the cost-effectiveness of rhTSH for ablation in patients with low-risk differentiated thyroid cancer is highly dependent on potential variations in cost of rhTSH, rates of remnant ablation, time off work, and quality of life.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".