Effect of comorbidity assessed by the Charlson Comorbidity Index on the length of stay, costs, and mortality among colorectal cancer patients undergoing colorectal surgery

Zhang, Xuexue; Wang, Xujie; Wang, Miaoran; Gu, Jiyu; Guo, Huijun; Yang, Yufei; Liu, Jian; Li, Qiuyan

doi:10.1080/03007995.2022.2139053

Cited by 10 publications

(6 citation statements)

References 47 publications

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“…The greater the CCI score is, the more complications are; therefore, the more serious the patient’s disease, the higher the cost of diagnosis and treatment, and also the longer the hospital stay, thus affecting the total cost of hospitalization. Which is in agreement with the findings of Zhang’s research ( 35 ). CCI score is a notable influencing factor.…”

Section: Discussionsupporting

confidence: 93%

Prediction and the influencing factor study of colorectal cancer hospitalization costs in China based on machine learning-random forest and support vector regression: a retrospective study

Gao,

Liu

2024

Front. Public Health

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AimsAs people’s standard of living improves, the incidence of colorectal cancer is increasing, and colorectal cancer hospitalization costs are relatively high. Therefore, predicting the cost of hospitalization for colorectal cancer patients can provide guidance for controlling healthcare costs and for the development of related policies.MethodsThis study used the first page of medical record data on colorectal cancer inpatient cases of a tertiary first-class hospital in Shenzhen from 2018 to 2022. The impacting factors of hospitalization costs for colorectal cancer were analyzed. Random forest and support vector regression models were used to establish predictive models of the cost of hospitalization for colorectal cancer patients and to compare and evaluate.ResultsIn colorectal cancer inpatients, major procedures, length of stay, level of procedure, Charlson comorbidity index, age, and medical payment method were the important influencing factors. In terms of the test set, the R2 of the Random forest model was 0.833, the R2 of the Support vector regression model was 0.824; the root mean square error (RMSE) of the Random forest model was 0.029, and the RMSE of the Support vector regression model was 0.032. In the Random Forest model, the weight of the major procedure was the highest (0.286).ConclusionMajor procedures and length of stay have the greatest impacts on hospital costs for colorectal cancer patients. The random forest model is a better method to predict the hospitalization costs for colorectal cancer patients than the support vector regression.

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Section: Discussionsupporting

confidence: 93%

Prediction and the influencing factor study of colorectal cancer hospitalization costs in China based on machine learning-random forest and support vector regression: a retrospective study

Gao,

Liu

2024

Front. Public Health

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“…Moreover, when examining our survival data, it was shown that, expectedly, the risk for mortality was highest in patients with a high CCI. While other studies have examined CCI as a predictive factor in CRC patients 28 , 29 and were able to show the value of using CCI in CRC patients, none of them specifically examined the effect of the interactions of CCI and postoperative complications. Our data demonstrates that patients with a high CCI stratified by major and minor complications did not show a difference in overall survival rates, which is a novel report in patients undergoing left-sided oncological colorectal resections.…”

Section: Discussionmentioning

confidence: 99%

The predictive value of comorbidities on postoperative complication rates and overall survival in left-sided oncological colorectal resections: a multicentre cohort study

Schlager,

Monschein,

Schüller

et al. 2023

International Journal of Surgery

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Introduction: Surgical- and non-surgical complications significantly worsen postoperative outcomes, and identification of patients at risk is crucial to improve care. This study investigated whether comorbidities, graded by the Charlson Comorbidity Index (CCI), impact complication rates and impair long-term outcome in a cohort of left-sided colorectal resections. Methods: Retrospective analysis of patients undergoing oncological left-sided colorectal resections due to colorectal cancer between 01/2015 and 12/2020 in two referral centres in Austria using electronic medical records and national statistical bureau survival data. Patients with recurrent disease, peritoneal carcinomatosis, and emergency surgeries were excluded. Comorbidities were assessed using the CCI, and complication severity was defined by the Clavien Dindo classification (CDC). Logistic regression analysis was performed to identify factors influencing the risk for postoperative complications, and overall survival was assessed using data from the national statistics bureau. Results: A total of 471 patients were analysed. Multinominal logistic regression analysis identified a CCI ≥6 (P=0.049; OR 1.59, 95% CI 1.10-2.54) and male sex (P=0.022; OR 1.47 95%, CI 1.21-2.98) as independent risk factors for major complications. While patients with a high CCI had the worst postoperative survival rates, perioperative complications only impacted on overall survival in patients with low CCIs, but not in patients with high CCIs. Conclusion: Although a high CCI is a risk factor for major postoperative complications, the presence of comorbidities should not result in withholding surgery.

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“…It is a proven, simple, and readily applicable method to estimate the risk of death from comorbid disease and has been widely used as a predictor of long-term prognosis and survival [ 50 ]. Many studies [ 51 , 52 ] have analyzed the relationship between CCI and the incidence of postoperative mortality, and found a significant correlation. There is no report on the correlation between CCI and the prognosis of patients with thymic epithelial tumors.…”

Section: Discussionmentioning

confidence: 99%

Postoperative clinical outcomes of patients with thymic epithelial tumors after over-3-year follow-up at a single-center

Jiao

Tian

et al. 2023

J Cardiothorac Surg

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Background To evaluate postoperative clinical outcomes and analyze influencing factors for patients with thymic epithelial tumors over 3 years after operation. Methods Patients with thymic epithelial tumors (TETs) who underwent surgical treatment in the Department of Thoracic Surgery at Beijing Hospital from January 2011 to May 2019 were retrospectively enrolled in the study. Basic patient information, clinical, pathological, and perioperative data were collected. Patients were followed up by telephone interviews and outpatient records. Statistical analyses were performed using SPSS version 26.0. Results A total of 242 patients (129 men, 113 women) with TETs were included in this study, of which 150 patients (62.0%) were combined with myasthenia gravis (MG) and 92 patients (38.0%) were not. 216 patients were successfully followed up and their complete information was available. The median follow-up period was 70.5 months (range, 2–137 months). The 3-year overall survival (OS) rate of the whole group was 93.9%, and the 5-year OS rate was 91.1%. The 3-year relapse-free survival (RFS) rate of the whole group was 92.2%, and the 5-year relapse-free survival rate was 89.8%. Multivariable COX regression analysis indicated that recurrence of thymoma was an independent risk factor for OS. Younger age, Masaoka-Koga stage III + IV, and TNM stage III + IV were independent risk factors for RFS. Multivariable COX regression analysis indicated that Masaoka-Koga staging III + IV, WHO type B + C were independent risk factors for postoperative improvement of MG. For patients with MG, the postoperative complete stable remission (CSR) rate was 30.5%. And the result of multivariable COX regression analysis showed that thymoma patients with MG with Osserman staging IIA + IIB + III + IV were not prone to achieving CSR. Compared with patients without MG, MG was more likely to develop in patients with WHO classification type B, and patients with myasthenia gravis were younger, with longer operative duration, and more likely to develop perioperative complications. Conclusions The 5-year overall survival rate of patients with TETs was 91.1% in this study. Younger age and advanced stage were independent risk factors for RFS of patients with TETs, and recurrence of thymoma were independent risk factors for OS. In patients with MG, WHO classification type B and advanced stage were independent predictors of poor outcomes of MG treatment after thymectomy.

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Effect of comorbidity assessed by the Charlson Comorbidity Index on the length of stay, costs, and mortality among colorectal cancer patients undergoing colorectal surgery

Cited by 10 publications

References 47 publications

Prediction and the influencing factor study of colorectal cancer hospitalization costs in China based on machine learning-random forest and support vector regression: a retrospective study

Prediction and the influencing factor study of colorectal cancer hospitalization costs in China based on machine learning-random forest and support vector regression: a retrospective study

The predictive value of comorbidities on postoperative complication rates and overall survival in left-sided oncological colorectal resections: a multicentre cohort study

Postoperative clinical outcomes of patients with thymic epithelial tumors after over-3-year follow-up at a single-center

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