Elsevier

Computers in Human Behavior

Volume 68, March 2017, Pages 228-231
Computers in Human Behavior

Full length article
Investigation of the depression in breast cancer patients by computational intelligence technique

https://doi.org/10.1016/j.chb.2016.11.042Get rights and content

Highlights

  • Breast cancer is the most commonly occurring cancers in females globally.

  • Depression is a common psychiatric problem in patients with breast cancer.

  • It is known that symptoms of depression impair quality of life.

  • Depression prediction in breast cancer patients based on the different factors.

Abstract

Breast cancer is one of the most common cancers in females. Depression could be occurred in patients with breast cancer. The psychiatric problem could influence on the quality of life. Treatment could be used in order to eliminate the suffering. By the way a patient could show different complaints therefore the depression could remain undetected and not treated as well. In this investigation the depression was analyzed according the different input factors. These factors are: age range, occupation status, education level, marriage status, therapy level and economic status. Computational intelligence technique was used to estimate the influence of the each factor for the depression in the breast cancer patients. Based on the results the age range and occupation status is the most dominant combination of the factors for the depression in breast cancer patients.

Introduction

The breast cancer diagnosis is one of the major problems in the medical field. The correct patterns classification of breast cancer is an important real-world medical problem. Breast cancer has become one of the major causes of mortality around the world and research into cancer diagnosis and treatment has become an important issue for the scientific community. Among patients with cancer, the management of depression is very important to improve quality of life. Depression, fatigue, and sleep disturbances have been identified as a symptom cluster among breast cancer patients. However, few studies have examined the temporal relations between these symptoms surrounding diagnosis and treatment.

These distressing symptoms not only affect patients at diagnosis and during cancer treatment but also persist years beyond the end of treatment. Given the growing number of breast cancer survivors and the impact of receiving a cancer diagnosis and undergoing treatment on mood and quality of life, it is important to understand cancer-related mental health symptoms to inform treatment and prevention efforts.

Chemotherapy is one of the most common treatment modalities, as it aims to reduce the tumor burden. However, patients suffer extensively from the side effects of chemotherapy, which is believed to reduce their self-efficacy to fight against the disease and hence, compromises their quality of life. In the studies (Ho et al., 2013, Sajjad et al., 2016, So et al., 2010) the effect of individualized patient education was aimed to be determined along with emotional support on the quality of life (of breast cancer patients undergoing chemotherapy. The purpose of paper (Zhou et al., 2015) was to examine effects of music therapy and progressive muscle relaxation training on depression, anxiety and length of hospital stay in Chinese female breast cancer patients after radical mastectomy where results showed that he music therapy and progressive muscle relaxation training can reduce depression, anxiety and length of hospital stay in female breast cancer patients after radical mastectomy. In article (Saboonchi et al., 2014) the transiency of distress response in breast cancer patients was examined by investigating the changes in clinical caseness of depression and anxiety during one year following surgery where the findings emphasize the importance of screening and follow up monitoring of distress. The aim of the study (Yagli & Ulger, 2015) was to investigate the effects of yoga on the quality of life in patients with Cancer where it was concluded that yoga is valuable in helping to diminish depression, pain, fatigue and helps cancer patients to perform daily and routine activities, and increases the quality of life in elderly patients with breast cancer. It is unclear whether breast cancer survivors have a higher risk of long-term symptoms of depression or anxiety. The aim of the study (Maass, Roorda, Berendsen, Verhaak, & de Bock, 2015) was to systematically review the evidence about long-term symptoms of depression and anxiety in breast cancer survivors where it was suggested a higher prevalence of symptoms of depression among breast cancer survivors than among the general female population, persistent over more than 5 years after diagnosis. The study (Ho, Rohan, Parent, Tager, & McKinley, 2015) investigated the co-occurrence of and interrelations between nonsomatic depressive symptoms, fatigue, and sleep disturbances in breast cancer patients at three time points: before, after, and six to eight months following adjuvant chemotherapy treatment where findings supported the notion that depression, fatigue, and sleep disturbances manifest as a symptom cluster where it was found that the fatigue may precede nonsomatic symptoms of depression among premenopausal breast cancer patients and represents a potential intervention target. The study (Park, Lee, Kim, Bae, & Hahm, 2012) was shown that escitalopram may improve both quality of life and depression in breast cancer patients.

Although there were many investigations of the depression in breast cancer patients, in this study the main aim is to apply a computational intelligence technique for the depression analyzing (Jang, 1993). These factors are: age range, occupation status, education level, marriage status, therapy level and economic status. Computational intelligence technique was used to estimate the influence of the each factor for the depression in the breast cancer patients.

Section snippets

Depression data

The research included 87 interviewees, ages 30 to 78. From the total number of interviewees, three of them did not fill out the form properly, and were therefore excluded from further analysis, so the final statistical analysis of the sample was performed on 84 interviewees. The research was performed in the oncology outpatient ward in the Clinical Center of Niš. Patients filled out questionnaires which contained two parts: a part for filling out the socio-demographic characteristics of the

Results

Computational intelligence technique was trained for the given set of input/output samples and results were observed. According the results presented in Fig. 1 one can note the smallest RMSE for the input “age”. In other word the input “age” has the highest relevance or influence on the depression in the breast cancer patients. On the other hand the input “therapy level” has the highest RMSE therefore the smallest relevance or influence on the depression in breast cancer patients.

Furthermore

Conclusion

Breast cancer is the most common malignant tumor in the female population. Due to the negative consequences of a cancer diagnosis and the sequel of cancer-related treatments, many patients suffer from depression. The importance of detecting depression in good time and of its management during the treatment and survivorship phases of the disease trajectory. More research is necessary to study the psychological health, the role of illness adjustment, social support and adaptation among breast

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