Second Primary Malignancies in Patients with Differentiated Thyroid Cancer after Radionuclide Therapy: A Retrospective Single-Centre Study
Bibliographic record
Abstract
Second primary malignancies (SPM) are described as any primary, not synchronous, malignancy arising in a different anatomical district, with confirmed histological diagnosis. Age at diagnosis, previous non-thyroidal primary malignancy, and radioactive iodine (RAI) therapy have been proposed as independent risk factors for SPM. RAI therapy is a standard treatment for moderate-high risk differentiated thyroid cancer (DTC), and its effect on the development of SPM has become a critical topic in DTC treatment. The purpose of this retrospective single-center study was to investigate the occurrence and the possible association of non-thyroidal SPM diagnosed after DTC and RAI therapy in a cohort of 1326 consecutive DTC patients referred at our Institution for RAI treatment from 1993 to 2009. Eighty-nine patients with ages ≤ 18 years at the time of DTC diagnosis or with a follow-up of ≤12 months were excluded from the final analysis. All patients underwent a complete clinical and hematological follow-up every 6 months for a minimum of 12 months. During follow-up (mean 89 ± 73 months), 25 patients (2%) had an SPM diagnosis (mean 133 ± 73 months). The most common site of the second malignancy was the breast, accounting for 32% of all SPM, followed by colon-rectal cancer (16%), leukemia, and gynecological and kidney cancer (4%). At Cox univariable regression analysis, age at DTC diagnosis (p < 0.001), age ≥55 years (p < 0.001) and follow-up duration (p < 0.004) were associated with SPM onset, while no significant association was observed with the administered activity of radioiodine. In conclusion, our data suggest that the older a person gets, the more sharply the likelihood of developing additional diseases, such as PMS, increases. Similarly, for follow-up, the more a patient is followed up clinically over time, the higher the risk of new diagnoses increases.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".