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Record W4308135991 · doi:10.1210/jendso/bvac150.1665

PSAT243 Late Versus Early Administration of Radioiodine Therapy for Patients with Differentiated Thyroid Cancer: A Systematic Review and Meta-analysis

2022· review· en· W4308135991 on OpenAlexaboutno aff
Eddy P Lincango Naranjo, Samantha Mora, Dámaris P. Intriago-Baldeón, William Acosta, Ivelin Leal-Medina, Sarahí Dueñas-Andrade, Tannya Ledesma-León, Camila Oliveira do Valle, Carla M Dominguez, Andrés Ayala, Oscar J. Ponce, Juan P. Brito

Bibliographic record

VenueJournal of the Endocrine Society · 2022
Typereview
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineThyroid cancerInternal medicineConfidence intervalMeta-analysisRelative riskRetrospective cohort studyAdjuvant therapyCohort studyThyroid carcinomaThyroidCancer

Abstract

fetched live from OpenAlex

Abstract Background Radioiodine (RAI) therapy is an important adjuvant therapy for differentiated thyroid carcinoma (DTC) patients. Several studies have demonstrated the efficacy of RAI in reducing the risk of thyroid cancer recurrence and mortality; however, the ideal timing to initiate RAI after surgery is debatable. This systematic review and meta-analysis evaluates the risk of achieving excellent response and mortality when comparing late administration versus early administration of RAI in patients with DTC. Methods We searched Medline, Embase, Scopus, and Cochrane Database from inception to April 2021 to identify experimental and observational studies that evaluated the impact of different timings of RAI after surgery (<3 months vs. >3 months, <6 months vs. >6 months, <9 months vs. >9 months) on the risk of excellent response and thyroid-specific mortality in DTC patients with low, intermediate, and high risk of recurrence. We used random-effects model to pool dichotomous variables with odd ratios (OR) and their confidence intervals (95%CI). The risk of bias was evaluated using the Newcastle Ottawa Scale. PROSPERO Protocol ID CRD42021267036. Results We included 12 retrospective cohort studies with 34,833 patients. The majority of participants were female (78.00%) and the mean age ranged from 39.70 (± 3.40) to 51.60 (± 1.70) years. In patients with low-to-intermediate risk of recurrence, there were no differences in excellent response (OR 0.76, 95%CI: 0.34-1.68, I2: 78.00%, n=1099) and mortality risk (OR 1.00, 95%CI: 0.84-1.19, I2: 0.00%, n=21450) in the late group (>3 months) compared to the early group (<3 months). The same outcomes were obtained for DTC patients who underwent RAI at 6 months (excellent response, OR 1.26, 95%CI: 0.94-1.69, I2: 0.00%, n=880) and at 9 months cut-offs (excellent response, OR 0.78, 95%CI: 0.32-1.91, I2: 0.00%, n=597; mortality, OR 1.28, 95%CI: 0.74-2.23, I2: 0.00%, n=327). Regarding DTC patients with high risk of recurrence, there were no differences in excellent response (OR 0.82, 95%CI: 0.61-1.11, I2: 0.00%, n=720) and mortality risk (OR 1.04, 95%CI: 0.74-1.47, I2: 62.50, n=10426) in the late group (>3 months) when compared to the early group (<3 months). Similarly for patients who underwent RAI at 6 months cut-off (excellent response, OR 1.04, 95%CI: 0.64-1.68, I2: 58.90%, n=72). However, mortality risk was higher in the late group (>6 months) when compared to the early group (<6 months) (OR 6.55, 95%CI: 2.92-14.67, I2: 0.00%, n=198). The risk of bias was considered moderate in 7 studies and high in 5. Conclusions Low-to-moderate quality of evidence suggests increased mortality with delayed RAI (>6 months) in DTC patients with high risk of recurrence. The timing of RAI for other risk categories has little or no effect. Further experimental studies are needed to confirm these results and draw robust conclusions. Presentation: Saturday, June 11, 2022 1:00 p.m. - 3:00 p.m.

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: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.351
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.006
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 head0.073
GPT teacher head0.358
Teacher spread0.284 · 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 designMeta-analysis
Domainnot available
GenreReview

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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