MP36-13 ASSOCIATION BETWEEN THE SARCOMATOID STATUS AND PERCENTAGE OF SARCOMATOID ON THE CLINICAL OUTCOMES OF LOCALIZED RENAL CELL CARCINOMA POST NEPHRECTOMY
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Résumé
You have accessJournal of UrologyKidney Cancer: Epidemiology & Evaluation/Staging/Surveillance I (MP36)1 May 2024MP36-13 ASSOCIATION BETWEEN THE SARCOMATOID STATUS AND PERCENTAGE OF SARCOMATOID ON THE CLINICAL OUTCOMES OF LOCALIZED RENAL CELL CARCINOMA POST NEPHRECTOMY Mustafa Soytas, Ghady Bou-Nehme Sawaya, Alice Dragomir, Charles Hesswani, Antonio Finelli, Lori Wood, Ricardo Rendon, Anil Kapoor, Aly-Khan Lalani, Daniel Heng, Bimal Bhindi, Naveen Basappa, Lucas Dean, Alan So, Darel Drachtenberg, Georg Bjarnason, Rodney Breau, Luke Lavallee, Jean Baptiste, Frederic Pouliot, and Simon Tanguay Mustafa SoytasMustafa Soytas , Ghady Bou-Nehme SawayaGhady Bou-Nehme Sawaya , Alice DragomirAlice Dragomir , Charles HesswaniCharles Hesswani , Antonio FinelliAntonio Finelli , Lori WoodLori Wood , Ricardo RendonRicardo Rendon , Anil KapoorAnil Kapoor , Aly-Khan LalaniAly-Khan Lalani , Daniel HengDaniel Heng , Bimal BhindiBimal Bhindi , Naveen BasappaNaveen Basappa , Lucas DeanLucas Dean , Alan SoAlan So , Darel DrachtenbergDarel Drachtenberg , Georg BjarnasonGeorg Bjarnason , Rodney BreauRodney Breau , Luke LavalleeLuke Lavallee , Jean BaptisteJean Baptiste , Frederic PouliotFrederic Pouliot , and Simon TanguaySimon Tanguay View All Author Informationhttps://doi.org/10.1097/01.JU.0001008612.93052.9d.13AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Sarcomatoid RCC (sRCC) is present in 5% of all localized RCCs and 20% of metastatic RCCs and can originate in any RCC subtype. The objectives of this study are to evaluate and compare the outcomes of localized RCC patients with and without a sarcomatoid component and its impact on cancer recurrence and survival. METHODS: The Canadian Kidney Cancer information system database was used to identify patients diagnosed with localized RCC between January 2011 and March 2023. Only patients with a pT1-T3 stage and documented sarcomatoid status were included. Patients were first classified in two groups according to the sarcomatoid status defined at the time of nephrectomy. Patients with sRCC were then subclassified according to the percentage of sarcomatoid component. Inverse probability of treatment weighting (IPTW) scores was used to balance the groups (sarcomatoid vs non-sarcomatoid and subgroups of sarcomatoid percentages) for sex, age, Charlson comorbidity score, clear cell carcinoma, pathological stage, grade, and size of the tumor. Cox proportional hazards models were used to assess the impact of sarcomatoid status and sarcomatoid percentage on recurrence-free and overall survival (RFS and OS). RESULTS: A total of 192 sarcomatoid and 6283 non-sarcomatoid localized RCC patients were included in the study cohort. The sarcomatoid percentage was available for 155 patients (57 patients>10% and 98 <10%). The weighted analysis revealed that sarcomatoid status was associated with an increased risk of metastasis and mortality compared to non-sarcomatoid patients ((RFS hazard ratio [HR] 2.42, 95% confidence interval [CI] 1.84-3.18) and (OS HR 2.36, 95%CI 1.68-3.31)). Sarcomatoid involvement of>10% was associated with an increased risk of metastasis and mortality compared to <10% ((RFS HR 1.70, 95%CI 1.08-2.66) and (OS HR 1.93, 95%CI 1.06-3.53)) (Table 1). CONCLUSIONS: Patients with sarcomatoid status and a sarcomatoid percentage>10% have an increased risk of recurrence and mortality. These patients may benefit from a more stringent follow-up post-nephrectomy and the sarcomatoid percentage could represent an important criterion in the risk assessment for adjuvant therapy. Source of Funding: The Canadian Kidney Cancer Information System (CKCis) © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e597 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Mustafa Soytas More articles by this author Ghady Bou-Nehme Sawaya More articles by this author Alice Dragomir More articles by this author Charles Hesswani More articles by this author Antonio Finelli More articles by this author Lori Wood More articles by this author Ricardo Rendon More articles by this author Anil Kapoor More articles by this author Aly-Khan Lalani More articles by this author Daniel Heng More articles by this author Bimal Bhindi More articles by this author Naveen Basappa More articles by this author Lucas Dean More articles by this author Alan So More articles by this author Darel Drachtenberg More articles by this author Georg Bjarnason More articles by this author Rodney Breau More articles by this author Luke Lavallee More articles by this author Jean Baptiste More articles by this author Frederic Pouliot More articles by this author Simon Tanguay More articles by this author Expand All 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 | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| 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 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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 ».