PD35-09 TALL SCORE FOR PREDICTION OF ONCOLOGICAL OUTCOMES AFTER RADICAL NEPHROURETERECTOMY FOR HIGH GRADE UPPER TRACT UROTHELIAL CARCINOMA
Bibliographic record
Abstract
You have accessJournal of UrologyBladder Cancer: Upper Tract Tumors I1 Apr 2014PD35-09 TALL SCORE FOR PREDICTION OF ONCOLOGICAL OUTCOMES AFTER RADICAL NEPHROURETERECTOMY FOR HIGH GRADE UPPER TRACT UROTHELIAL CARCINOMA Ramy Youssef, Laura-Maria Krabbe, Shahrokh F. Shariat, Yair Lotan, Arthur Sagalowsky, Jay D. Raman, Christopher G. Wood, Alon Z. Weizer, Christian Bolenz, Mesut Remzi, Karim Bensalah, Wassim Kassouf, Francesco Montorsi, Vitaly Margulis, and UTUC Collaboration Ramy YoussefRamy Youssef More articles by this author , Laura-Maria KrabbeLaura-Maria Krabbe More articles by this author , Shahrokh F. ShariatShahrokh F. Shariat More articles by this author , Yair LotanYair Lotan More articles by this author , Arthur SagalowskyArthur Sagalowsky More articles by this author , Jay D. RamanJay D. Raman More articles by this author , Christopher G. WoodChristopher G. Wood More articles by this author , Alon Z. WeizerAlon Z. Weizer More articles by this author , Christian BolenzChristian Bolenz More articles by this author , Mesut RemziMesut Remzi More articles by this author , Karim BensalahKarim Bensalah More articles by this author , Wassim KassoufWassim Kassouf More articles by this author , Francesco MontorsiFrancesco Montorsi More articles by this author , Vitaly MargulisVitaly Margulis More articles by this author , and UTUC Collaboration More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.2422AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Grade remains the main factor determining treatment decisions for UTUC. We created a simple prognostic tool for prediction of outcomes after radical nephroureterctomy (RNU) for high grade non-metatstatic upper tract urothelial carcinoma (UTUC). METHODS Data from UTUC collaboration database was utilized to include 586 patients who underwent RNU for non-metastatic, node negative, high grade UTUC. A score was defined based on the sum of the selected independent prognostic variables from univariate and multivariate survival analyses. Survival outcomes were compared according to the score. RESULTS The study included 382 males (65%), 374 kidney tumors (64%) and 212 (34%) ureteric tumors. Pathological tumor stage (T) was T2 or less in 304 (52%) and T3/T4 in 282 (48%) patients. Sessile architecture (A) was found in 204 (35%) and lympho-vascular invasion (LVI) in 152 (26%). Lymphadectomy (L) was performed in 245 (42%). Independent prognostic factors holding significance in multivariate analysis included: T, A, LVI and L. The sum of T (0 < T1, 1= T1, 2= T2, 3= T3 and 4 equal T4), A (papillary = 0 and sessile = 1), LVI (negative = 0 and positive = 1) and L (lymphadenectomy = 0 and no lympadenectomy = 1) was entered into a TALL score (0-7). Disease free survival (DFS) and cancer specific survival (CSS) was stratified into 4 risk categories according to the TALL score: low (n= 172 [29%], TALL 0-2), intermediate (n= 152 [26%], TALL = 3), high (n= 109 [19%], TALL = 4) and very high risk (n= 153 [26%], TALL 5 or more) using Kaplan- Meier survival analyses (figure). 3 and 5 year DFS and CSS were 90, 86, 86, 86 in low, 73, 71, 79, 75 in intermediate, 63,58,55,52 in high and 39, 34, 20, 0 in very high risk categories. CONCLUSIONS We developed a simple prognostic tool for the prediction of oncological outcomes after RNU for high grade UTUC. This postoperative simplified prediction model can be utilized for counseling of patients, selection for adjuvant systemic therapies and design of clinical trials. © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e894 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Ramy Youssef More articles by this author Laura-Maria Krabbe More articles by this author Shahrokh F. Shariat More articles by this author Yair Lotan More articles by this author Arthur Sagalowsky More articles by this author Jay D. Raman More articles by this author Christopher G. Wood More articles by this author Alon Z. Weizer More articles by this author Christian Bolenz More articles by this author Mesut Remzi More articles by this author Karim Bensalah More articles by this author Wassim Kassouf More articles by this author Francesco Montorsi More articles by this author Vitaly Margulis More articles by this author UTUC Collaboration More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".