Lifetime direct healthcare costs of treating colorectal cancer: a systematic review

Bhimani, Nazim; Wong, Geoffrey Ym; Molloy, Charles; Dieng, Mbathio; Kelly, Patrick J.; Hugh, Thomas J.

doi:10.1007/s10198-022-01497-z

Cited by 8 publications

(2 citation statements)

References 32 publications

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“…China and the United States will be the countries with the largest number of new CRC cases in the next 20 years ( 3 ). Although CRC has good treatment prospects, CRC still poses a heavy economic burden and a huge healthcare challenge for both developed and developing countries ( 4 - 6 ). Reduced physical activity, excess weight, poor diet, excessive alcohol consumption, and smoking are considered variable risk factors for CRC ( 2 ).…”

Section: Introductionmentioning

confidence: 99%

A prognostic nomogram integrating carcinoembryonic antigen levels for predicting overall survival in elderly patients with stage II–III colorectal cancer

Zhang,

Wang,

et al. 2024

J Gastrointest Oncol

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Background With the aging of the population, colorectal surgeons will have to face more elderly colorectal cancer (CRC) patients in the future. We aim to analyze independent risk factors affecting overall survival in elderly (age ≥65 years) patients with stage II–III CRC and construct a nomogram to predict patient survival. Methods A total of 3,016 elderly CRC patients with stage II–III were obtained from the SEER database. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) regression analyses were used to screen independent prognostic factors, and a survival prediction nomogram was constructed based on the results. The consistency index (C-index), decision curve analysis (DCA), Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to compare the predictive ability between the nomogram and tumor-node-metastasis (TNM) stage system. All patients were classified into high-risk and low-risk groups based on risk scores calculated by nomogram. The Kaplan-Meier method was used to compare the survival differences between two groups. Results The 3- and 5-year area under the curve (AUC) values of the prediction nomogram model were 76.6% and 74.8%, respectively. The AIC, BIC, and C-index values of the nomogram model were 6,032.502, 15,728.72, and 0.707, respectively, which were better than the TNM staging system. Kaplan-Meier survival analysis showed a significant survival difference between high-risk and low-risk groups (P<0.0001). Conclusions We constructed a prediction nomogram for stage II–III elderly CRC patients by combining pre-treatment carcinoembryonic antigen (CEA) levels, which can accurately predict patient survival. This facilitates clinicians to accurately assess patient prognosis and identify high-risk patients to adopt more aggressive and effective treatment strategies.

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Section: Introductionmentioning

confidence: 99%

A prognostic nomogram integrating carcinoembryonic antigen levels for predicting overall survival in elderly patients with stage II–III colorectal cancer

Zhang,

Wang,

et al. 2024

J Gastrointest Oncol

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“…12 The costs of providing healthcare for children and AYA with cancer are not well understood. Several studies and reviews on the costs of cancers in adult populations have been conducted [13][14][15][16][17][18][19][20] and highlight the high direct costs in adult cancer populations compared to those without cancer. However, parallel evidence is lacking for those diagnosed with cancer as children and AYA.…”

Section: Introductionmentioning

confidence: 99%

Healthcare costs of cancer among children, adolescents, and young adults: A scoping review

Nabukalu,

Gordon,

Lowe

et al. 2024

Cancer Medicine

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ObjectiveTo collate and critically review international evidence on the direct health system costs of children and adolescents and young adults (AYA) with cancer.MethodsWe conducted searches in PubMed, MEDLINE, CINAHL, and Scopus. Articles were limited to studies involving people aged 0–39 years at cancer diagnosis and published from 2012 to 2022. Two reviewers screened the articles and evaluated the studies using the Consolidated Health Economic Evaluation Reporting Standards checklist. The reviewers synthesized the findings using a narrative approach and presented the costs in 2022 US dollars for comparability.ResultsOverall, the mean healthcare costs for all cancers in the 5 years post diagnosis ranged from US$36,670 among children in Korea to US$127,946 among AYA in the USA.During the first year, the mean costs among children 0–14 years ranged from US$34,953 in Chile to over US$130,000 in Canada. These were higher than the costs for AYA, estimated at US$61,855 in Canada. At the end of life, the mean costs were estimated at over US$300,000 among children and US$235,265 among adolescents in Canada.Leukemia was the most expensive cancer type, estimated at US$50,133 in Chile, to US$152,533 among children in Canada. Overall, more than a third of the total cost is related to hospitalizations. All the included studies were of good quality.ConclusionsHealthcare costs associated with cancer are substantial among children, and AYA. More research is needed on the cost of cancer in low‐ and middle‐income countries and harmonization of costs across countries.

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Factors impacting hospitalisation and related health service costs in cancer survivors in Australia: Results from a population data linkage study in Queensland (COS‐Q)

Merollini,

Collins,

Jones

et al. 2024

Cancer Medicine

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BackgroundThe global economic cost of cancer and the costs of ongoing care for survivors are increasing. Little is known about factors affecting hospitalisations and related costs for the growing number of cancer survivors. Our aim was to identify associated factors of cancer survivors admitted to hospital in the public system and their costs from a health services perspective.MethodsA population‐based, retrospective, data linkage study was conducted in Queensland (COS‐Q), Australia, including individuals diagnosed with a first primary cancer who incurred healthcare costs between 2013 and 2016. Generalised linear models were fitted to explore associations between socio‐demographic (age, sex, country of birth, marital status, occupation, geographic remoteness category and socio‐economic index) and clinical (cancer type, year of/time since diagnosis, vital status and care type) factors with mean annual hospital costs and mean episode costs.ResultsOf the cohort (N = 230,380) 48.5% (n = 111,820) incurred hospitalisations in the public system (n = 682,483 admissions). Hospital costs were highest for individuals who died during the costing period (cost ratio ‘CR’: 1.79, p < 0.001) or living in very remote or remote location (CR: 1.71 and CR: 1.36, p < 0.001) or aged 0–24 years (CR: 1.63, p < 0.001). Episode costs were highest for individuals in rehabilitation or palliative care (CR: 2.94 and CR: 2.34, p < 0.001), or very remote location (CR: 2.10, p < 0.001). Higher contributors to overall hospital costs were ‘diseases and disorders of the digestive system’ (AU$661 m, 21% of admissions) and ‘neoplastic disorders’ (AU$554 m, 20% of admissions).ConclusionsWe identified a range of factors associated with hospitalisation and higher hospital costs for cancer survivors, and our results clearly demonstrate very high public health costs of hospitalisation. There is a lack of obvious means to reduce these costs in the short or medium term which emphasises an increasing economic imperative to improving cancer prevention and investments in home‐ or community‐based patient support services.

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Lifetime direct healthcare costs of treating colorectal cancer: a systematic review

Cited by 8 publications

References 32 publications

A prognostic nomogram integrating carcinoembryonic antigen levels for predicting overall survival in elderly patients with stage II–III colorectal cancer

A prognostic nomogram integrating carcinoembryonic antigen levels for predicting overall survival in elderly patients with stage II–III colorectal cancer

Healthcare costs of cancer among children, adolescents, and young adults: A scoping review

Factors impacting hospitalisation and related health service costs in cancer survivors in Australia: Results from a population data linkage study in Queensland (COS‐Q)

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