MP36-13 ASSOCIATION BETWEEN THE SARCOMATOID STATUS AND PERCENTAGE OF SARCOMATOID ON THE CLINICAL OUTCOMES OF LOCALIZED RENAL CELL CARCINOMA POST NEPHRECTOMY
Bibliographic record
Abstract
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 ...
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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 | 0.000 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".