MétaCan
Menu
Back to cohort
Record W4387613522 · doi:10.1016/j.heliyon.2023.e20853

Analysis of the clinical factors affecting excellent response of Iodine-131 treatment for pulmonary metastases from differentiated thyroid cancer

2023· article· en· W4387613522 on OpenAlexaff
Xinyu Wu, Bo Li, Jie Zhang, Lili Duan, Bingxin Hu, Yongju Gao

Bibliographic record

VenueHeliyon · 2023
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsNovelis (Canada)
FundersNatural Science Foundation of Henan Province
KeywordsMedicineThyroid cancerThyroglobulinReceiver operating characteristicInternal medicineStage (stratigraphy)Radioiodine therapyLogistic regressionPathologicalThyroidTherapeutic effectProgressive diseaseCancerGastroenterologyDiseaseOncologyRadiology

Abstract

fetched live from OpenAlex

Background Iodiene-131 ( 131 I) treatment is the primary therapeutic approach for imaging 131 I-avid pulmonary metastases. The response to radioiodine (RAI) treatment is an important prognostic factor in patients with pulmonary metastases from differentiated thyroid cancer (DTC). Patients who achieve an excellent response (ER) to 131 I treatment show significantly reduced disease-related mortality. This study aimed to retrospectively analyse the clinical data and therapeutic effects of 131 I treatment in patients with DTC and pulmonary metastases and to screen out the clinical factors affecting ER. Materials and methods The study included a total of 75 patients with exclusively Iodine-131 avid ( 131 I-avid) pulmonary metastases who underwent 131 I treatment. Relevant clinical data for these patients were collected. Following treatment, the status of DTC metastatic lesions was categorized as follows: excellent response (ER), biochemical incomplete response (BIR), structural incomplete response (SIR), or indeterminate response (IDR). Gender, age at diagnosis, pathological type, stages (TNM), stimulated thyroglobulin (sTg) value before initial 131 I treatment, metastatic nodule size, and type of post-treatment whole body scan (Rx-WBS) were recorded. Mono-factor analysis and binary logistic regression analyses were used to identify the factors that might affect the ER in DTC pulmonary metastases. The receiver operating characteristic (ROC) curve of the sTg value was used to predict the ER of 131 I treatment. Results All 75 patients with exclusively 131 I-avid pulmonary metastases received 131 I treatment and underwent follow-up. Out of the 75 patients, 26 achieved ER, resulting in an excellent response rate of 34.7 % (26/75). Among them, 25 (25/26, 96.2 %) achieved an ER after undergoing two rounds of 131 I treatment. Binary logistic regression analysis showed that the factors influencing DTC pulmonary metastases excellent response were lower sTg levels [odds ratio ( OR ) = 0.998, P < 0.001], micronodular metastases ( OR = 0.349, P = 0.001) and focal distribution on Rx-WBS imaging ( OR = 0.113, P = 0.001). The area under the ROC curve for sTg value predicting ER was 0.876, and the cut-off value was 26.84 ng/mL, with a sensitivity and specificity of 87.9 % and 80.3 %, respectively. Conclusions 131 I treatment is effective for 131 I-avid pulmonary metastases of DTC. Some patients who underwent 131 I treatment achieved ER. Most patients with ER were obtained after two rounds of 131 I treatments. Patients with sTg values before initial 131 I treatment lower than 26.84 ng/mL, micronodular metastases, and focal distribution on Rx-WBS imaging were more likely to achieve ER.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.089
GPT teacher head0.381
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHeliyonSame topicThyroid Cancer Diagnosis and TreatmentFrench-language works237,207