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Record W1522833368

A Meta-Analysis of the Relationship between Testicular Microlithiasis and Incidence of Testicular Cancer.

2015· review· en· W1522833368 on OpenAlexaboutno aff
Tao Wang, Luhao Liu, Jintai Luo, TaiSheng Liu, Anyang Wei

Bibliographic record

VenuePubMed · 2015
Typereview
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsnot available
FundersNatural Science Foundation of Guangdong ProvinceNational Natural Science Foundation of China
KeywordsMedicineTesticular cancerMeta-analysisRelative riskObservational studyIncidence (geometry)Confidence intervalCochrane LibrarySubgroup analysisGynecologyCancerInternal medicinePublication biasOncology
DOInot available

Abstract

fetched live from OpenAlex

PURPOSE: There are many recent observational studies on testicular microlithiasis (TM) and risk of testicular cancer. Whether TM increases the risk of testicular cancer is still inconclusive. The objective of this updated meta-analysis was to synthesize evidence from clinical observational studies that evaluated the association between TM and testicular cancer. MATERIALS AND METHODS: We identified eligible studies by searching the PubMed, Embase and Cochrane Library before March 2014. Adjusted relative risks (RR) with 95% confidence interval (CI) were calculated using random-or fixed-model. RESULTS: A total of 14 studies involving 35,578 participants were included in the meta-analysis. On the basis of the Newcastle Ottawa Scale systematic review, eleven studies were identified as relatively high-quality. TM was strong association with an increased incidence of testicular cancer (RR = 12.70, 95% CI: 8.18-19.71, P < .001), with significant evidence of heterogeneity among these studies (P for heterogeneity < .001, I2 = 82.1%). The subgroup and sensitivity analysis confirmed the stability of the results and no publication bias was detected. CONCLUSION: The present meta-analysis suggests that TM is significantly associated with risk of testicular cancer. More researches are warranted to clarify an understanding of the association between TM and risk of testicular cancer.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.282
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.002
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 head0.363
GPT teacher head0.392
Teacher spread0.029 · 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
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".

Quick stats

Citations51
Published2015
Admission routes1
Has abstractyes

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