MP06-06 DOES URINARY CYTOLOGY HAVE A ROLE IN HEMATURIA INVESTIGATIONS? RESULTS OF A PROSPECTIVE OBSERVATIONAL STUDY (DETECT I)
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Résumé
You have accessJournal of UrologyBladder Cancer: Epidemiology & Evaluation I1 Apr 2018MP06-06 DOES URINARY CYTOLOGY HAVE A ROLE IN HEMATURIA INVESTIGATIONS? RESULTS OF A PROSPECTIVE OBSERVATIONAL STUDY (DETECT I) Wei Shen Tan, Andrew Feber, Liqin Dong, Rachael Sarpong, Simon Rodney, Pramit Khetrapal, Patricia de Winter, Rumana Jalil, Norman Williams, Chris Brew-Graves, John Kelly, and DETECT I trial group Wei Shen TanWei Shen Tan More articles by this author , Andrew FeberAndrew Feber More articles by this author , Liqin DongLiqin Dong More articles by this author , Rachael SarpongRachael Sarpong More articles by this author , Simon RodneySimon Rodney More articles by this author , Pramit KhetrapalPramit Khetrapal More articles by this author , Patricia de WinterPatricia de Winter More articles by this author , Rumana JalilRumana Jalil More articles by this author , Norman WilliamsNorman Williams More articles by this author , Chris Brew-GravesChris Brew-Graves More articles by this author , John KellyJohn Kelly More articles by this author , and DETECT I trial groupDETECT I trial group More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.198AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES The role of urinary cytology as part of hematuria investigations is debatable. The Dutch, Canadian and Japanese Urology Associations recommended that urinary cytology should be performed for selected patient groups presenting with gross hematuria (GH). The UK National Institute of Clinical Excellence (NICE) does not comment on the use of urinary cytology and American Urology Association does not recommend the use of urinary cytology for initially hematuria evaluation. We determine the diagnostic accuracy of urinary cytology in a multicentre prospective observational study of 567 patients investigated for hematuria. Primary outcome: the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of urinary cytology to diagnosed bladder cancer and/ or upper tract transitional cell carcinoma (TCC) in patients investigated with hematuria at secondary care. METHODS The DETECT I study (clinicaltrials.gov NCT02676180) recruited patients presenting with hematuria following referral to secondary case at 9 institutions. All patients had a cystoscopy and upper tract imaging (ultrasound and/ or CT intravenous urography) and urinary cytology. Patients with a suspicion of bladder cancer had transurethral resection of bladder cancer or bladder biopsy for histological confirmation of cancer. Urinary cytology results were defined as positive/ atypical or negative. RESULTS 567 patients with a median age of 68 years were recruited over a 14-month period. 37 (6.5%) bladder cancers and 8 upper tract TCC (1.4%) were identified. 13 urinary samples (2.3%) were excluded due to inadequate urinary cellular content for cytology analysis. The accuracy of urinary cytology for the diagnosis of bladder or upper tract TCC was: sensitivity 40%, specificity 95%, PPV 40% and NPV 95%. 20 bladder cancers and 6 upper tract TCC were missed. Bladder cancers missed according to grade and stage were: 4 (20%) G3= pT2, 3 (15%) G3 pT1, 9 (45%) G3/2 pTa, and 4 (20%) G1 pTa. 38% of patients were classified as high risk. When selecting for patients with GH, the diagnostic accuracy of urinary cytology CONCLUSIONS In clinical practice, urine cytology will miss a significant number of muscle invasive TCC and high risk NMIBC. The role of urinary cytology as part of routine hematuria investigations should not be recommended. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e54 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Wei Shen Tan More articles by this author Andrew Feber More articles by this author Liqin Dong More articles by this author Rachael Sarpong More articles by this author Simon Rodney More articles by this author Pramit Khetrapal More articles by this author Patricia de Winter More articles by this author Rumana Jalil More articles by this author Norman Williams More articles by this author Chris Brew-Graves More articles by this author John Kelly More articles by this author DETECT I trial group More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,013 | 0,095 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,024 | 0,004 |
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 source (Gemma direct ou Codex distillé), 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 ».