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PD02-07 A NOVEL CLINICAL DECISION AID TO SUPPORT PERSONALIZED TREATMENT SELECTION FOR PATIENTS WITH RENAL CORTICAL MASSES ≤7 CM: RESULTS FROM A MULTI-INSTITUTIONAL COMPETING RISKS ANALYSIS INCLUDING PERFORMANCE STATUS AND COMORBIDITY

2020; Lippincott Williams & Wilkins; Volume: 203; Issue: Supplement 4 Linguagem: Inglês

10.1097/ju.0000000000000822.07

1527-3792

Sarah P. Psutka, Roman Gulati, Michael Jewett, Kamel Fadaak, Antonio Finelli, Laura Legere, Todd M. Morgan, Phillip M. Pierorazio, Mohammad E. Allaf, Jeph Herrin, Christine M. Lohse, R. Houston Thompson, Stephen A. Boorjian, Thomas D. Atwell, Grant D. Schmit, Brian A. Costello, Nilay Shah, Bradley C. Leibovich,

Health Systems, Economic Evaluations, Quality of Life

You have accessJournal of UrologyKidney Cancer: Localized: Surgical Therapy I (PD02)1 Apr 2020PD02-07 A NOVEL CLINICAL DECISION AID TO SUPPORT PERSONALIZED TREATMENT SELECTION FOR PATIENTS WITH RENAL CORTICAL MASSES ≤7 CM: RESULTS FROM A MULTI-INSTITUTIONAL COMPETING RISKS ANALYSIS INCLUDING PERFORMANCE STATUS AND COMORBIDITY Sarah Psutka*, Roman Gulati, Michael Jewett, Kamel Fadaak, Antonio Finelli, Laura Legere, Todd Morgan, Phillip Pierorazio, Mohammad Allaf, Jeph Herrin, Christine Lohse, R. Houston Thompson, Stephen Boorjian, Thomas Atwell, Grant Schmit, Brian Costello, Nilay Shah, and Bradley Leibovich Sarah Psutka*Sarah Psutka* More articles by this author , Roman GulatiRoman Gulati More articles by this author , Michael JewettMichael Jewett More articles by this author , Kamel FadaakKamel Fadaak More articles by this author , Antonio FinelliAntonio Finelli More articles by this author , Laura LegereLaura Legere More articles by this author , Todd MorganTodd Morgan More articles by this author , Phillip PierorazioPhillip Pierorazio More articles by this author , Mohammad AllafMohammad Allaf More articles by this author , Jeph HerrinJeph Herrin More articles by this author , Christine LohseChristine Lohse More articles by this author , R. Houston ThompsonR. Houston Thompson More articles by this author , Stephen BoorjianStephen Boorjian More articles by this author , Thomas AtwellThomas Atwell More articles by this author , Grant SchmitGrant Schmit More articles by this author , Brian CostelloBrian Costello More articles by this author , Nilay ShahNilay Shah More articles by this author , and Bradley LeibovichBradley Leibovich More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000822.07AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Personalized treatment for clinical T1 renal cortical masses (RCMs) should account for competing risks related to tumor and patient characteristics. We developed treatment-specific prediction models for cancer-specific and other-cause mortality, and 90-day complication rates in patients managed with surgery, thermal ablation (TA), and active surveillance (AS) to inform individualized treatment selection. METHODS: Preoperative clinical and radiological features were collected for eligible patients aged 18-91 years treated at four academic centers from 2000-2016. Prediction models used competing risks regressions for cancer-specific (CSM) and other-cause mortality (OCM) and logistic regressions for Clavien ≥3 complications, adjusting for tumor size, patient age, sex, ECOG performance status (PS), and Charlson comorbidity index (CCI). Predictions accounted for missing data using multiple imputation. RESULTS: After excluding 25 patients with no follow-up, the cohort was comprised of 4995 RCM patients treated with radical nephrectomy (RN,1270), partial nephrectomy (PN, 2842), thermal ablation (TA, 479), or active surveillance (AS, 404). Median follow-up was 5.1 years (IQR 2.5-8.5). Predictions from the fitted model are shown in an online calculator (https://rgulati.shinyapps.io/rcc-risk-calculator). To illustrate the use of this calculator for a specific patient, a 70-year-old female with a 5.5 cm RCM, PS of 2, and CCI of 3 has predicted 5-year CSM of 4-7% across treatments, 5-year OCM of 34-49%, and 90-day risk of Clavien ≥3 complications of 4%, 10%, and 6% for RN, PN, and TA respectively (Table). CONCLUSIONS: Personalized treatment selection for cT1 RCM is challenging. We present a competing risk calculator that incorporates pretreatment features to quantify competing causes of mortality and treatment-associated complications. Pending validation, this tool may be used in clinical practice to provide patients with estimated individualized treatment-specific probabilities of competing causes of death and complication risks to facilitate shared decision-making. Source of Funding: Mr. Gulati is funded under NIH grant R50 CA221836 © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e68-e69 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Sarah Psutka* More articles by this author Roman Gulati More articles by this author Michael Jewett More articles by this author Kamel Fadaak More articles by this author Antonio Finelli More articles by this author Laura Legere More articles by this author Todd Morgan More articles by this author Phillip Pierorazio More articles by this author Mohammad Allaf More articles by this author Jeph Herrin More articles by this author Christine Lohse More articles by this author R. Houston Thompson More articles by this author Stephen Boorjian More articles by this author Thomas Atwell More articles by this author Grant Schmit More articles by this author Brian Costello More articles by this author Nilay Shah More articles by this author Bradley Leibovich More articles by this author Expand All Advertisement PDF downloadLoading ...