Validation of a Questionnaire-Suitable Comorbidity Index in Patients Undergoing Radical Cystectomy

Froehner, Michael; Koch, Rainer; Heberling, Ulrike; Borkowetz, Angelika; Hübler, Matthias; Wirth, Manfred P.; Thomas, Christian

doi:10.1159/000507100

Cited by 10 publications

(7 citation statements)

References 17 publications

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“…Among 891 patients with bladder cancer, the CCI predicted 5-year mortality [189]. In 1,337 patients who had radical cystectomy, the CCI predicted 5-year survival [190].…”

Section: Predictive Validitymentioning

confidence: 99%

Charlson Comorbidity Index: A Critical Review of Clinimetric Properties

Charlson

Carrozzino

Guidi

et al. 2022

Psychother Psychosom

677

317

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The present critical review was conducted to evaluate the clinimetric properties of the Charlson Comorbidity Index (CCI), an assessment tool designed specifically to predict long-term mortality, with regard to its reliability, concurrent validity, sensitivity, incremental and predictive validity. The original version of the CCI has been adapted for use with different sources of data, ICD-9 and ICD-10 codes. The inter-rater reliability of the CCI was found to be excellent, with extremely high agreement between self-report and medical charts. The CCI has also been shown either to have concurrent validity with a number of other prognostic scales or to result in concordant predictions. Importantly, the clinimetric sensitivity of the CCI has been demonstrated in a variety of medical conditions, with stepwise increases in the CCI associated with stepwise increases in mortality. The CCI is also characterized by the clinimetric property of incremental validity, whereby adding the CCI to other measures increases the overall predictive accuracy. It has been shown to predict long-term mortality in different clinical populations, including medical, surgical, intensive care unit (ICU), trauma, and cancer patients. It may also predict in-hospital mortality, although in some instances, such as ICU or trauma patients, the CCI did not perform as well as other instruments designed specifically for that purpose. The CCI thus appears to be clinically useful not only to provide a valid assessment of the patient’s unique clinical situation, but also to demarcate major diagnostic and prognostic differences among subgroups of patients sharing the same medical diagnosis.

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“…Among 891 patients with bladder cancer, the CCI predicted 5-year mortality [189]. In 1,337 patients who had radical cystectomy, the CCI predicted 5-year survival [190].…”

Section: Predictive Validitymentioning

confidence: 99%

Charlson Comorbidity Index: A Critical Review of Clinimetric Properties

Charlson

Carrozzino

Guidi

et al. 2022

Psychother Psychosom

677

317

View full text Add to dashboard Cite

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“…Leucocyte count was usually normal, with a mean of 8.4±4.1 x103 cells/µL. The mean CCI was 4.6±2.6 (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11). The overall length of hospital stay ranged from two to 28 days, with an average of 10 days (excluding the two nosocomial cases).…”

Section: Resultsmentioning

confidence: 99%

“…Froehner et al validated it in patients with post-radical cystectomy who underwent radical cystectomy for muscle-invasive or high-risk non-muscle-invasive urothelial or undifferentiated bladder cancer after a five-year follow-up period. He studied 1,337 patients and compared CCI with a modified self-administrable comorbidity index that was based on standard sets for neoplastic diseases [ 11 ]. CCI was also found to predict outcomes in internal medicine-related complications post-hip arthroplasty after a mean 27-month follow-up period by Schmolders et al [ 12 ].…”

Section: Discussionmentioning

confidence: 99%

Mortality and Morbidity of Human Metapneumovirus Infection in the Pre-COVID-19 Era: The Value of the Charlson Comorbidity Index on Outcome Prediction

Shehu,

Pascual,

Kapinos

et al. 2024

Cureus

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Introduction: Human metapneumovirus (HMPV) is an important cause of seasonal respiratory tract infections, mainly in children and immunocompromised adults. The use of the Charlson Comorbidity Index (CCI) to predict outcomes in hospitalized patients has been validated in several settings. Objective: This study aims to describe the clinical characteristics of adult patients with HMPV infection and evaluate the value of the CCI in predicting outcomes in patients with acute HMPV infections requiring hospitalization. Method: This is a single-center case-series study of hospitalized patients with HMPV infection in 2017. Results: Twenty-two adult patients with a mean age of 65 years were reviewed. The mean CCI was 4.6±2.6. The overall mortality was 22%. An abnormal chest X-ray (CXR) was reported in 15 patients. CCI was not different between survivors and non-survivors. Non-survivors were more likely to have abnormal CXR and a higher fever at the time of diagnosis, required mechanical ventilation, or had other concomitant infections. Conclusion: The average CCI was 4.5, which was not significantly different between survivors and non-survivors. The mortality rate was elevated by 22% and was likely associated with admission to the ICU as well as the presence of another concomitant infection.

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“…A good performance of the CCI and aCCI in mortality prediction is well documented in the current literature. Froehner et al reported an AUROC of 0.74 using the CCI to predict 90-day mortality in a larger cohort [25]. Prayer Galetti et al showed that the aCCI as a significant predictor of mortality in elderly patients undergoing RC [11].…”

Section: Discussionmentioning

confidence: 99%

Comorbidity Scores and Machine Learning Methods Can Improve Risk Assessment in Radical Cystectomy for Bladder Cancer

et al. 2022

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BACKGROUND: Pre-operative risk assessment in radical cystectomy (RC) is an ongoing challenge especially in elderly patients. OBJECTIVE: To evaluate the ability of comorbidity indices and their combination with clinical parameters in machine learning models to predict mortality and morbidity after RC. METHODS: In 392 patients who underwent open RC, complication and mortality rates were reported. The predictive values of the age-adjusted Charlson Comorbidity index (aCCI), the Elixhauser Index (EI), the Physical Status Classification System (ASA) and Gagne’s combined comorbidity Index (GCI) were evaluated using regression analyses. Various machine learning models (Gaussian naïve bayes, logistic regression, neural net, decision tree, random forest) were additionally investigated. RESULTS: The aCCI, ASA and GCI showed significant results for the prediction of complications (χ 2 = 8.8, p < 0.01, χ 2 = 15.7, p < 0.01 and χ 2 = 4.6, p = 0.03) and mortality (χ 2 = 21.1, p < 0.01, χ 2 = 25.8, p < 0.01 and χ 2 = 2.4, p = 0.04) after RC while the EI showed no significant prediction. However, areas under receiver characteristic curves (AUROCs) revealed good performance only for the prediction of mortality by the aCCI and ASA (0.81 and 0.78, CGI 0.63) while the prediction of complications was poor (aCCI 0.6, ASA 0.63, CGI 0.58). The combination of ASA, age, body mass index and sex in machine learning models showed a better prediction. Gaussian naïve bayes (0.79) and logistic regression (0.76) showed the best performance using a hold-out test set. CONCLUSIONS: The ASA and aCCI show good prediction of mortality after RC but fail predicting complications accurately. Here, the combination of comorbidity indices and clinical parameters in machine learning models seems promising.

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Validation of a Questionnaire-Suitable Comorbidity Index in Patients Undergoing Radical Cystectomy

Cited by 10 publications

References 17 publications

Charlson Comorbidity Index: A Critical Review of Clinimetric Properties

Charlson Comorbidity Index: A Critical Review of Clinimetric Properties

Mortality and Morbidity of Human Metapneumovirus Infection in the Pre-COVID-19 Era: The Value of the Charlson Comorbidity Index on Outcome Prediction

Comorbidity Scores and Machine Learning Methods Can Improve Risk Assessment in Radical Cystectomy for Bladder Cancer

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