Diagnostic accuracy of transrectal elastosonography (TRES) imaging for the diagnosis of prostate cancer: a systematic review and meta‐analysis
Notice bibliographique
Résumé
What's known on the subject? and What does the study add? Cancer tissue is stiffer than normal tissue, a fact known for many years. This has been measured using ultrasound (US) technology and is termed as elastosonography (ES). There have been reports of this technique being used in the detection of prostate cancer; however, no definite guidelines for its clinical application exist. The present review, for the first time synthesises published data of transrectal ES (TRES) using diagnostic review methodology. TRES increases prostate cancer detection as compared with grey‐scale US. Also, the study highlights limitations and strengths of data in this area and includes recommendations for future research. To assess the diagnostic performance of transrectal elastosonography (TRES) for the detection of prostate cancer. Two reviewers independently extracted the data from each study. Quality was assessed with a validated quality assessment tool for diagnostic accuracy studies. Diagnostic accuracy of TRES in relation to current standard references (transrectal ultrasonography [TRUS] biopsies and histopathology of radical prostatectomy [RP] specimens) was estimated. A bivariate random effects model was used to obtain sensitivity and specificity values. Hierarchical summary receiver operating characteristic (HSROC) were calculated. In all, 16 studies (2278 patients) were included in the review. Using histopathology of the RP specimen as reference standard, the pooled data of four studies showed that the sensitivity of TRES ranged between 0.71 to 0.82 and the specificity ranged between 0.60 to 0.95 (pooled diagnostic odds ratio [DOR] 19.6; 95% confidence interval [CI] 7.7–50.03). The sensitivity varied from 0.26 to 0.87 and specificity varied from 0.17 to 0.76 (pooled DOR 2.141; 95% CI 0.525 to –8.737) using TRUS biopsies (minimum of 10) as a reference standard. The quality of most studies was modest. SROC estimated 0.8653 area under the curve predicting high chances of detecting prostate cancer. There were no health economics or health‐related quality of life of the participants reported in the studies and all the studies used compressional technique with no reported standardisation. The TRES technique appears to improve the detection of prostate cancer compared with systematic biopsy and shows a good accuracy in comparison with histopathology of the RP specimen. However, studies lacked standardisation of the technique, had poor quality of reporting and a large variation in the outcomes based on the reference standards and techniques used.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,008 | 0,005 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».