Quality of life and occurrence  of depression under chemotherapy in patients suffering from lung carcinoma

Baczewska, Bożena; Kamińska, Marzena; Ciszewski, Tomasz; Kubiatowski, Tomasz; Makara‐Studzińska, Marta; Sygit, Katarzyna; Sygit, Marian; Zubilewicz, Jadwiga; Pietrzak, Karolina

doi:10.5604/12321966.1129933

Cited by 3 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our study found that 130 of 297 patients with lung cancer had depression with a prevalence of 43.77%, similar to previous studies (Gu et al, 2017) but lower than the study carried out by Baczewska et al (2014). The reason might be that the evaluation tools used were different, and the diagnostic gold standard was lacking, which led to the different prevalence rates in an existing study.…”

Section: Discussionsupporting

confidence: 90%

“…These patients also report unpleasant physical and emotional stresses, such as decreased physical function, fatigue, pain and depression (Medysky et al, 2021). Depression is pervasive and popular in patients with lung cancer (Wang et al, 2022), with an incidence ranging from 19% to 73.9% (Baczewska et al, 2014; Liu et al, 2018; Park et al, 2016). Depression caused by lung cancer is characterised by refractory, high recurrence rate, and multi‐factorial pathogenesis, which has become an essential reason for reducing patients' clinical therapeutic efficacy and quality of life and even leading to adverse health outcomes such as increasing the risk of suicide (Gu et al, 2017; Liu et al, 2022; Santos, 2017).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Developing a visual model for predicting depression in patients with lung cancer

Xing

Zhao

Duan

et al. 2022

Journal of Clinical Nursing

View full text Add to dashboard Cite

Aims and objectives: To investigate and analyse the prevalence of depression among patients with lung cancer, identify risk factors of depression, and develop a visual, non-invasive, and straightforward clinical prediction model that can be used to predict the risk probability of depression in patients with lung cancer quantitatively.Background: Depression is one of the common concomitant symptoms of patients with lung cancer, which can increase the risk of suicide. However, the current assessment tools cannot combine multiple risk factors to predict the risk probability of depression in patients. Design:A cross-sectional study. Methods:The clinical data from 297 patients with lung cancer in China were collected and analysed in this cross-sectional study. The clinical prediction model was constructed according to the results of the Chi-square test and the logistic regression analysis, evaluated by discrimination, calibration, and decision curve analysis, and visualised by a nomogram. This study was reported using the TRIPOD checklist.Results: 130 patients with lung cancer had depressive symptoms with a prevalence of 43.77%. A visual prediction model was constructed based on age, disease duration, exercise, stigma, and resilience. This model showed good discrimination at an AUC of 0.842. Calibration curve analysis indicated a good agreement between experimental and predicted values, and the decision curve analysis showed a high clinical utility. Conclusions:The visual prediction model developed in this study has excellent performance, which can accurately predict the occurrence of depression in patients with lung cancer at an early stage and assist the medical staff in taking targeted preventative measures. Relevance to clinical practice:The visual, non-invasive, and simple nomogram can help clinical medical staff to calculate the risk probability of depression among patients with lung cancer, formulate personalised preventive care measures for high-risk groups as soon as possible, and improve the quality of life of patients.

show abstract

Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Developing a visual model for predicting depression in patients with lung cancer

Xing

Zhao

Duan

et al. 2022

Journal of Clinical Nursing

View full text Add to dashboard Cite

show abstract

“… 12 In the questions regarding QOL, the answers are graded on the scale of 1-7, with the ascending values indicating increasing QOL. 6 To facilitate the analysis, the points were standardized on the scale of 1 to 100 and assessed according to a 4-degree Likert scale, namely, 0–25 points indicated “very low QOL,” 26–50 points indicated “low QOL,” 51–75 points indicated “high QOL,” and 76–100 points indicated “very high QOL. 6 …”

Section: Methodsmentioning

confidence: 99%

“… 3 The severity of cancer-related symptoms has been strongly related to the psychological symptoms in the patients, 4 and the unhealthy psychological status has been shown to be associated with a significantly increased frequency of cancer-related mortality. 5 Of 102 lung cancer patients treated by chemotherapy, Baczewska found 6 that 51.5% showed symptoms of severe depression, suggesting that depression occurs more frequently and with greater intensity in lung cancer patients as compared with that in healthy individuals. In another study of 1334 consecutively recruited lung cancer patients, Shimizu 7 reported 440 with significant anxiety issues.…”

mentioning

confidence: 99%

Factors influencing the psychology and quality of life in lung cancer patients

Wang

Hao

Zhang

2017

SMJ

View full text Add to dashboard Cite

Objectives:To determine the factors closely correlated with the unhealthy psychological status of patients with lung cancer and to ascertain whether the unhealthy psychology adversely affects their quality-of-life (QOL).Methods:Patients newly diagnosed with lung cancer between May 2013 and December 2015 in the Department of Thoracic Surgery, Tianjin 4th Centre Hospital, Tianjin, China were enrolled in this cross-sectional study. Patients were asked to complete the Symptom Checklist 90 (SCL-90) and Quality of Life Questionnaire (QLQ-C30) survey. From the responses, the correlation between the patient’s psychological status and QOL were analyzed with respect to several variables.Results:From the total of 258 patients subjected to the test, 168 belonged to the unhealthy psychology group and 90 to the healthy psychology group. Multiple regression analysis revealed that significant factors related to poor QOL among the 2 groups are gender (p=0.02), younger age (p=0.001), surgical history (p=0.04), employment status (p=0.03), and medical insurance (p=0.01) significantly predicted the severity of unhealthy psychology in lung cancer patients. A significantly negative correlation was noted between the points of SCL-90 and the general QOL in all included patients (p=0.03).Conclusion:Gender, younger age, surgical history, employment status, and medical insurance significantly predicted the severity of unhealthy psychology in lung cancer patients.

show abstract

“…As can be seen from the literature review, quality of life is an issue investigated by many researchers, some of whom have done so during chemotherapy [6], radiotherapy and other treatments, such bone marrow transplants [7]. Others referred to quality of life in specific types of cancer (breast, lung, prostate) [8].…”

mentioning

confidence: 99%

Quality of Life in Cancer Patients- A Nursing Perspective

Lavdaniti¹

2015

J Nurs Care

View full text Add to dashboard Cite

Quality of life and occurrence of depression under chemotherapy in patients suffering from lung carcinoma

Cited by 3 publications

References 10 publications

Developing a visual model for predicting depression in patients with lung cancer

Developing a visual model for predicting depression in patients with lung cancer

Factors influencing the psychology and quality of life in lung cancer patients

Quality of Life in Cancer Patients- A Nursing Perspective

Contact Info

Product

Resources

About