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Development of a New Comorbidity Assessment Tool for Specific Prediction of Perioperative Mortality in Contemporary Patients Treated with Radical Cystectomy

  • Paolo Dell’OglioEmail author
  • Zhe Tian
  • Sami-Ramzi Leyh-Bannurah
  • Alessandro Larcher
  • Elio Mazzone
  • Marco Moschini
  • Vincent Trudeau
  • Armando Stabile
  • Andrea Gallina
  • Nazareno Suardi
  • Umberto Capitanio
  • Alexandre Mottrie
  • Alberto Briganti
  • Francesco Montorsi
  • Christian M. Rochefort
  • Pierre I. Karakiewicz
Urologic Oncology
  • 36 Downloads

Abstract

Purpose

The Deyo adaptation of the Charlson comorbidity index (DaCCI), which relies on 17 comorbid condition groupings defined with 200 ICD-9-CM diagnostic codes, lacks specificity in the context of radical cystectomy (RC) for bladder cancer (BCa). We attempted to develop a new comorbidity assessment tool based on individual comorbid conditions and/or BCa manifestations for specific prediction of perioperative mortality after RC.

Methods

We relied on 7076 T1–T4 nonmetastatic BCa patients treated with RC between 2000 and 2009 in the SEER-Medicare linked database. Within the development cohort (n = 6076), simulated annealing (SA) was used to identify (1) individual comorbid conditions, (2) individual BCa manifestations, and (3) the combination of both, that satisfy the criteria of maximal accuracy and parsimony for prediction of 90-day mortality after RC, after adjusting for several confounders. The accuracy of the newly identified groups of individual comorbid conditions and/or BCa manifestations and of the original DaCCI was tested in a 1000-patient external validation cohort.

Results

The combination of six individual comorbid conditions and two individual BCa disease manifestations (type II diabetes without complications, anemia, chronic obstructive pulmonary disease, congestive heart failure, aortocoronary bypass, cardiomegaly, urinary tract infection, and hydronephrosis), and seven individual comorbid conditions (type II diabetes without complications, anemia, chronic obstructive pulmonary disease, congestive heart failure, aortocoronary bypass, osteoarthrosis, and cardiomegaly) respectively showed 71.1 and 70.2% accuracy versus 68.0% for the original DaCCI.

Conclusions

These new approaches are specific to contemporary RC patients and represent simpler methods compared with the original DaCCI, without any compromise in accuracy.

Notes

Disclosure

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. The authors declare no conflicts of interest in preparing this article.

Supplementary material

10434_2019_7313_MOESM1_ESM.xlsx (11 kb)
Supplementary File 1 Risk calculator based on the combination of six individual comorbid conditions and two individual bladder cancer manifestations that allow individual estimation of 90-day mortality after radical cystectomy (XLSX 11 kb)
10434_2019_7313_MOESM2_ESM.xlsx (11 kb)
Supplementary File 2 Risk calculator based on seven individual comorbid conditions that allow individual estimation of 90-day mortality after radical cystectomy (XLSX 12 kb)

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Copyright information

© Society of Surgical Oncology 2019

Authors and Affiliations

  • Paolo Dell’Oglio
    • 1
    • 2
    Email author
  • Zhe Tian
    • 1
    • 3
  • Sami-Ramzi Leyh-Bannurah
    • 1
    • 4
  • Alessandro Larcher
    • 2
  • Elio Mazzone
    • 2
  • Marco Moschini
    • 2
  • Vincent Trudeau
    • 1
    • 5
  • Armando Stabile
    • 2
  • Andrea Gallina
    • 2
  • Nazareno Suardi
    • 2
  • Umberto Capitanio
    • 2
  • Alexandre Mottrie
    • 6
    • 7
  • Alberto Briganti
    • 2
  • Francesco Montorsi
    • 2
  • Christian M. Rochefort
    • 3
    • 8
  • Pierre I. Karakiewicz
    • 1
    • 5
  1. 1.Cancer Prognostics and Health Outcomes UnitUniversity of Montreal Health CenterMontrealCanada
  2. 2.Division of Oncology/Unit of UrologyUrological Research Institute, IRCCS Ospedale San RaffaeleMilanItaly
  3. 3.Department of Epidemiology, Biostatistics and Occupational HealthMcGill UniversityMontrealCanada
  4. 4.Martini-Clinic, Prostate Cancer Center Hamburg-EppendorfHamburgGermany
  5. 5.Department of UrologyUniversity of Montreal Health CenterMontrealCanada
  6. 6.ORSI, AcademyMelleBelgium
  7. 7.Department of UrologyOnze Lieve Vrouw HospitalAalstBelgium
  8. 8.Faculté de Médecine, École des Sciences InfirmièresUniversité de SherbrookeSherbrookeCanada

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