Healthy life expectancy of oral squamous cell carcinoma patients aged 75years and older

Yamada, Shin‐ichi; Kitamura, Hiroshi; Tomioka, Takahiro; Ohta, Ryosuke; Yoshimura, Nobuhiko; Nishimaki, Fumihiro; Koyama, Yoshihito; Kondo, Eiji; Kamata, Toshihide

doi:10.1016/j.oraloncology.2016.11.014

Cited by 14 publications

(5 citation statements)

References 19 publications

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“…In addition, our comparison of different age groups shows that the loss of life years due to cancer-related deaths decreases gradually with increasing age, with greater changes in men’s LE than in women’s, with an increase of 3.15 years for men and 2.07 years for women, compared with 3.60 years for Canada. This was consistent with other studies [ 20 , 21 , 22 ], which also found greater changes in urban LE than in rural LE and greater changes in the east than in the central and west. Liu [ 23 ] conducted research on the impact of leading causes of death on LE in China.…”

Section: Discussionsupporting

confidence: 93%

Association of Major Chronic Noncommunicable Diseases and Life Expectancy in China, 2019

et al. 2022

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This study aimed to illustrate the association of four major chronic noncommunicable diseases (cardiovascular diseases, cancer, respiratory diseases, and diabetes) with life expectancy (LE) of Chinese residents in 2019 and to provide an evidence base for the scientific prevention and treatment of chronic diseases in China. The abbreviated life and cause-eliminated life tables were compiled according to the Jiang Qing Lang method recommended by WHO (World Health Organization) to calculate LE and cause-eliminated life expectancy (CELE) in 2019. The disease that had the greatest association with the LE of Chinese residents was cardiovascular disease (CVD), with the LE increasing by 8.13 years after removing CVD deaths. This was followed by cancer (2.68 years), respiratory diseases (0.88 years), and diabetes (0.24 years). The four major chronic noncommunicable diseases (NCDs) were the main diseases affecting the health of Chinese residents. CVD should be prevented and treated as the key disease among the chronic diseases, while women and rural people should be the major focus of health knowledge promotion. All residents should be encouraged to develop a good understanding of self-protection and of how to achieve a healthy lifestyle in order to reduce the occurrence of death and to improve their quality of life and health in general.

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Section: Discussionsupporting

confidence: 93%

Association of Major Chronic Noncommunicable Diseases and Life Expectancy in China, 2019

et al. 2022

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“…Ho, et al reported that old age was associated with tumor recurrence and metastasis [], and Yang, et al also reported that patient’s age was one of the risk factors that affect prognosis []. Additionally, in our previous report, health expectancy was poor (less than 1 year), in patients aged 75 years and older with advanced oral SCC, except among patients aged 75–79 years who underwent standard treatments []. These results suggested that the age of the patient might have a negative effect on the treatment of oral SCC.…”

Section: Discussionmentioning

confidence: 86%

Risk factors in securing successful surgical resection of oral squamous cell carcinoma

Nakanishi

Yamada

Nishizawa

et al. 2018

Oral Science International

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The purpose of this retrospective study was to analyze the factors that had a significant effect on securing a successful surgical resection (surgical margin) in oral cancer surgery. One hundred forty‐eight consecutive patients who underwent planned radical resection of oral squamous cell carcinoma (SCC) were analyzed. Successful resection was judged if pathological examination of the surgical specimen revealed a clear surgical margin (no SCC within 5 mm, n = 116), while an unsuccessful resection was judged if there was a close and involved surgical margin (SCC within 5 mm, n = 21; and SCC at margin, n = 11). Univariate analyses showed that gender, age, and T‐classification had significant influence on successful surgical resection. The results of multivariate logistic regression analysis showed that age (odds ratio [OR] = 1.042, 95% CI = 1.001‐1.084), T‐classification (OR = 1.656, 95% CI = 1.060‐2.587), and the presence of preoperative treatment (OR = 2.868, 95% CI = 1.047‐7.85) had significant effects on successful surgical resection. The results of this study suggested that successful resection of oral SCC was difficult in patients with either older age or advanced (T4) tumor. It is also suggested that preoperative therapy had a positive effect on securing a pathologically clear surgical margin.

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“…There have been many works done in the prediction of LE within the context of specific diseases such as predicting LE in men diagnosed with prostate cancer [24], schizophrenia [25], lung cancer [26,27], breast cancer [28], diabetes [29], limb ischemia [30], IgA nephropathy [31], oral Technologies 2018, 6, 74 6 of 18 squamous cell carcinoma [32], acute myeloid leukemia [33], and psychiatric disease [34]. These models have also been researched with consideration of geographical and regional areas [35][36][37], income [38], relationship with economic growth [39], and globalization [40].…”

Section: Date Of Birthmentioning

confidence: 99%

“…Cancer [24], schizophrenia [25], lung cancer [26,27], breast cancer [28], diabetes [29], limb ischemia [30], IgA nephropathy [31], oral squamous cell carcinoma [32], acute myeloid leukemia [33] and psychiatric disease [34] America, Europe, and Asia [35][36][37] Income related [38], relationship with economic growth [39] or globalization [40] Sullivan [41], Lee and Carter [22], Cairns et al [23], Jafelice [16], Agawal et al [17] and Pascaliu et al [21] As a result, for the purpose of this article it is concurred that Agrawal et al [17] provides the most accurate and useful methodology to calculate individual LE despite it only showing five years of LE. This has so far been the only tool that has been proposed to calculate a PLE for an individual utilizing personalized attributes entered in to questionnaires provided by a web application, whilst others are based on predictions of LE for a group based on larger demographic classifications.…”

Section: Diseases Based Geographic Areas Relationships Modelling Techmentioning

confidence: 99%

Systematic Predictive Analysis of Personalized Life Expectancy Using Smart Devices

Kang¹,

Adibi²

2018

Technologies

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With the emergence of technologies such as electronic health and mobile health (eHealth/mHealth), cloud computing, big data, and the Internet of Things (IoT), health related data are increasing and many applications such as smartphone apps and wearable devices that provide wellness and fitness tracking are entering the market. Some apps provide health related data such as sleep monitoring, heart rate measuring, and calorie expenditure collected and processed by the devices and servers in the cloud. These requirements can be extended to provide a personalized life expectancy (PLE) for the purpose of wellbeing and encouraging lifestyle improvement. No existing works provide this PLE information that is developed and customized for the individual. This article is based on the concurrent models and methodologies to calculate and predict life expectancy (LE) and proposes an idea of using multi-phased approaches to the solution as the project requires an immense and broad range of work to accomplish. As a result, the current prediction of LE, which was found to be up to a maximum of five years could potentially be extended to a lifetime prediction by utilizing generic health data. In this article, the novel idea of the solution proposing a PLE on an individual basis, which can be extended to lifetime is presented in addition to the existing works.

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Healthy life expectancy of oral squamous cell carcinoma patients aged 75years and older

Cited by 14 publications

References 19 publications

Association of Major Chronic Noncommunicable Diseases and Life Expectancy in China, 2019

Association of Major Chronic Noncommunicable Diseases and Life Expectancy in China, 2019

Risk factors in securing successful surgical resection of oral squamous cell carcinoma

Systematic Predictive Analysis of Personalized Life Expectancy Using Smart Devices

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