Association between sodium iodide symporter and differentiated Thyroid cancer: a meta-analysis of 9 studies.
Bibliographic record
Abstract
CONTEXT: As many studies proved that sodium iodide symporter (NIS) plays a key role in radioactive iodide (RAI) therapy of thyroid cancer, however, a growing number of studies suggests that part of differentiated thyroid carcinomas (DTC) with overexpression of NIS are insensitive to RAI well. OBJECTIVE: The aim of this meta-analysis is to assess the expression of NIS in differentiated thyroid cancer, compared with normal thyroid tissue. DATA SOURCES: PUBMED, Sinomed, CNKI, Wanfang and VIP were searched for relevant case-control studies up to now. STUDY SELECTION: Studies that concerning the qualitative expression NIS in DTC were included. DATA EXTRACTION: Working independently, authors used a standard form to extract data. For quality assessment, Newcastle-Ottawa Scale (NOS) were applied. DATA SYNTHESIS: Totally nine eligible studies included, involving 765 cases and 473 controls. The results revealed that the expression of NIS had a statistically increased in DTC, compared with controls (OddsRadio OR: 1.47, 95% CI: 1.12 to 1.94, Z=2.78, P=0.005). Since the existence of the significant heterogeneity, subgroup analysis and sensitivity analysis were performed and found that the heterogeneity came from the different criteria evaluate positive NIS expression (Liu 2008, Mu 2010) and the small simple size of the control group (Lin. J D2001). The heterogeneity disappeared or dropped to below 50% after remove these studies. CONCLUSION: Our study shows that the expression of NIS is significantly increased in DTC, which could help explain the reason for individual with a poor response to RAI therapy. In other word, the reduced iodide uptake in thyroid cancer may not caused by the decreased expression of NIS, function of NIS protein or its post-transcriptional translocation might be the point.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.047 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".