Age-adjusted Charlson Comorbidity Index as a prognostic factor for radical prostatectomy outcomes of very high-risk prostate cancer patients

Park, Jae Won; Koh, Dong Hoon; Jang, Won Sik; Lee, Joo Yong; Ham, Won Sik; Rha, Koon Ho; Jung, Woo Hee; Hong, Sung Joon; Choi, Young Deuk

doi:10.1371/journal.pone.0199365

Cited by 19 publications

(13 citation statements)

References 29 publications

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“…Like our results there was a high negative predictive value for adverse events (21). Another study in patients undergoing prostatectomy MCI was an effective prognostic factor (22). A study in kidney transplant recipients suggested MCI in clinical practice to stratify the mortality hazard in patients who undergo renal transplantation (23).However another study showed no association between MCI and mortality (24) In decision we demonstrated that MCI combined with procalcitonin and CRP can be used reliably for predicting mortality instead of APACHE II in medical ICU cases.…”

Section: Discussionsupporting

confidence: 83%

Comparison of APACHE II and Modified Charlson Index in Mortality Prediction in Patients at Medical Intensive Care Unit

Bulur¹,

Efe²,

Iynem³

et al. 2021

Osmangazi̇ Journal of Medicine

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Section: Discussionsupporting

confidence: 83%

Comparison of APACHE II and Modified Charlson Index in Mortality Prediction in Patients at Medical Intensive Care Unit

Bulur¹,

Efe²,

Iynem³

et al. 2021

Osmangazi̇ Journal of Medicine

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“…Several studies reported the clinical impact of ACCI on survival in patients with various cancers including those who underwent surgical resection 13–16 . Here, we demonstrated that ACCI was significantly prognostic for OS, but not for PFS in BTC patients receiving palliative chemotherapy.…”

Section: Discussionmentioning

confidence: 58%

“…While comorbidities increase with age, chronological age alone would not reflect overall physical status in those patients because variations among each individual tend to be large in elderly patients. Recently, the age‐adjusted Charlson comorbidity index (ACCI) has been widely used in the field of clinical oncology, 12 demonstrating a prognostic value in several types of cancer 13–16 . Herein, we aimed to clarify the impact of age and comorbidity assessment indicated by ACCI on clinical outcomes in patients with advanced or recurrent BTC undergoing palliative chemotherapy.…”

Section: Introductionmentioning

confidence: 99%

The impact of age and comorbidity in advanced or recurrent biliary tract cancer receiving palliative chemotherapy

Takahara

Nakai

Saito

et al. 2020

J of Gastro and Hepatol

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Background and Aim: Limited data are available on age and comorbidity assessment in patients with biliary tract cancer (BTC). This study aimed to evaluate the association of age and comorbidity burden with clinical outcomes of chemotherapy for BTC. Methods: Consecutive 197 BTC patients undergoing first-line chemotherapy between 2007 and 2017 were retrospectively studied. Patients were classified to three groups according to the age-adjusted Charlson comorbidity index (ACCI) excluding the score about BTC and progression-free survival, overall survival (OS), and safety were compared. Results: Fifty-one patients (26%) were elderly (≥ 75 years), and ACCI was 0-2 in 73 patients (37%), 3-4 in 98 (50%), and ≥ 5 in 26 (13%). ACCI was associated with the administration of first-line combination chemotherapy (89% in 0-2, 80% in 3-4, and 64% in ≥ 5, P < 0.01) and second-line chemotherapy (67% in 0-2, 51% in 3-4, and 35% in ≥ 5, P = 0.01). ACCI was prognostic for OS in addition to performance status, disease status, and CA19-9: The hazard ratios in ACCI of 3-4 and ≥ 5 were 1.39 and 1.79, compared with ACCI of 0-2 (P = 0.04). While overall safety profile did not differ by ACCI, higher ACCI score group developed Grade 3-4 neutropenia more frequently (26% in 0-2, 42% in 3-4, and 46% in ≥ 5, P = 0.04). Conclusion: Age and comorbidity burden did affect OS and safety profile in BTC patients undergoing first-line palliative chemotherapy. ACCI can be a simple and useful tool to evaluate the age and comorbidity burden in these patients.

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“…The CCI has been used to measure comorbidity and adjust for associated risks in survival models based on the various data sources, including clinical trials, prospective and retrospective cohort studies, and claims data [ 26 – 33 ]. Recently, population-based health care claims data have been used more frequently in studies of health-related outcomes, as these data could yield generalizable results.…”

Section: Discussionmentioning

confidence: 99%

Impact of comorbidity assessment methods to predict non-cancer mortality risk in cancer patients: a retrospective observational study using the National Health Insurance Service claims-based data in Korea

Lee

Chang

Cho

2021

BMC Med Res Methodol

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Background Cancer patients’ prognoses are complicated by comorbidities. Prognostic prediction models with inappropriate comorbidity adjustments yield biased survival estimates. However, an appropriate claims-based comorbidity risk assessment method remains unclear. This study aimed to compare methods used to capture comorbidities from claims data and predict non-cancer mortality risks among cancer patients. Methods Data were obtained from the National Health Insurance Service-National Sample Cohort database in Korea; 2979 cancer patients diagnosed in 2006 were considered. Claims-based Charlson Comorbidity Index was evaluated according to the various assessment methods: different periods in washout window, lookback, and claim types. The prevalence of comorbidities and associated non-cancer mortality risks were compared. The Cox proportional hazards models considering left-truncation were used to estimate the non-cancer mortality risks. Results The prevalence of peptic ulcer, the most common comorbidity, ranged from 1.5 to 31.0%, and the proportion of patients with ≥1 comorbidity ranged from 4.5 to 58.4%, depending on the assessment methods. Outpatient claims captured 96.9% of patients with chronic obstructive pulmonary disease; however, they captured only 65.2% of patients with myocardial infarction. The different assessment methods affected non-cancer mortality risks; for example, the hazard ratios for patients with moderate comorbidity (CCI 3–4) varied from 1.0 (95% CI: 0.6–1.6) to 5.0 (95% CI: 2.7–9.3). Inpatient claims resulted in relatively higher estimates reflective of disease severity. Conclusions The prevalence of comorbidities and associated non-cancer mortality risks varied considerably by the assessment methods. Researchers should understand the complexity of comorbidity assessments in claims-based risk assessment and select an optimal approach.

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Age-adjusted Charlson Comorbidity Index as a prognostic factor for radical prostatectomy outcomes of very high-risk prostate cancer patients

Cited by 19 publications

References 29 publications

Comparison of APACHE II and Modified Charlson Index in Mortality Prediction in Patients at Medical Intensive Care Unit

Comparison of APACHE II and Modified Charlson Index in Mortality Prediction in Patients at Medical Intensive Care Unit

The impact of age and comorbidity in advanced or recurrent biliary tract cancer receiving palliative chemotherapy

Impact of comorbidity assessment methods to predict non-cancer mortality risk in cancer patients: a retrospective observational study using the National Health Insurance Service claims-based data in Korea

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