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Record W2929897807 · doi:10.1111/bju.14759

Biparametric vs multiparametric prostate magnetic resonance imaging for the detection of prostate cancer in treatment‐naïve patients: a diagnostic test accuracy systematic review and meta‐analysis

2019· review· en· W2929897807 on OpenAlexafffund
Mostafa Alabousi, Jean‐Paul Salameh, Kaela Gusenbauer, Lucy Samoilov, Ali Jafri, Hang Yu, Abdullah Alabousi

Bibliographic record

VenueBritish Journal of Urology · 2019
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsSt. Joseph’s Healthcare HamiltonWestern UniversityOttawa Public HealthOttawa HospitalUniversity of OttawaMcMaster University
FundersMcMaster University
KeywordsProstate cancerMedicineMeta-analysisConfidence intervalProstateMagnetic resonance imagingNuclear medicineRadiologyCancerInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To perform a diagnostic test accuracy (DTA) systematic review and meta-analysis comparing multiparametric (diffusion-weighted imaging [DWI], T2-weighted imaging [T2WI], and dynamic contrast-enhanced [DCE] imaging) magnetic resonance imaging (mpMRI) and biparametric (DWI and T2WI) MRI (bpMRI) in detecting prostate cancer in treatment-naïve patients. METHODS: The Medical Literature Analysis and Retrieval System Online (MEDLINE) and Excerpta Medica dataBASE (EMBASE) were searched to identify relevant studies published after 1 January 2012. Articles underwent title, abstract, and full-text screening. Inclusion criteria consisted of patients with suspected prostate cancer, bpMRI and/or mpMRI as the index test(s), histopathology as the reference standard, and a DTA outcome measure. Methodological and DTA data were extracted. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool. DTA metrics were pooled using bivariate random-effects meta-analysis. Subgroup analysis was conducted to assess for heterogeneity. RESULTS: From an initial 3502 studies, 31 studies reporting on 9480 patients (4296 with prostate cancer) met the inclusion criteria for the meta-analysis; 25 studies reported on mpMRI (7000 patients, 2954 with prostate cancer) and 12 studies reported on bpMRI DTA (2716 patients, 1477 with prostate cancer). Pooled summary statistics demonstrated no significant difference for sensitivity (mpMRI: 86%, 95% confidence interval [CI] 81-90; bpMRI: 90%, 95% CI 83-94) or specificity (mpMRI: 73%, 95% CI 64-81; bpMRI: 70%, 95% CI 42-83). The summary receiver operating characteristic curves were comparable for mpMRI (0.87) and bpMRI (0.90). CONCLUSIONS: No significant difference in DTA was found between mpMRI and bpMRI in diagnosing prostate cancer in treatment-naïve patients. Study heterogeneity warrants cautious interpretation of the results. With replication of our findings in dedicated validation studies, bpMRI may serve as a faster, cheaper, gadolinium-free alternative to mpMRI.

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)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0010.003
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 head0.032
GPT teacher head0.327
Teacher spread0.295 · 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.

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".

Quick stats

Citations121
Published2019
Admission routes2
Has abstractyes

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