Effect of mindfulness therapy on the intervention of cancer-related fatigue in patients with lung cancer:a meta-analysis

Lyu Cheng,Han Wang,Wen-Jiao Li,Yun Ning,Chang-De Jin

1Graduate College, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China. 2School of Nursing, Tianjin University of Traditional Chinese Medicine,Tianjin 301617,China.

Abstract

Keywords:Mindfulness therapy,Cancer-related fatigue,Lung cancer,Meta-analysis

Background

The GLOBOCAN 2018 report [1] released by the international agency for research on cancer of the world health organization shows that lung cancer ranks first among 18.1 million new cancer cases worldwide in 2018. Lung cancer also ranks first among the 9.6 million cancer deaths worldwide [1]. Lung cancer is the leading cause of morbidity and mortality among Chinese men. The onset of lung cancer is insidious,and once diagnosed, it is usually in the late stage, with poor treatment effect and prognosis [2]. The latest National Comprehensive Cancer Network Guidelines define cancer-related fatigue as a painful, persistent,subjective,physical,emotional,or cognitive fatigue[3].Cancer-related fatigue is one of the most common symptoms in the course of chemotherapy for lung cancer patients,and its incidence is significantly higher than that of other tumor patients [4]. Cancer-related fatigue is characterized by high incidence, long duration, severity, and unpredictability [5].Cancer-related fatigue reduces patients' ability to participate in cancer treatment and to participate in important and valuable life activities, and may reduce the overall survival rate of cancer patients[6].

Mindfulness therapy is one of the non-drug therapies.The concept of “mindfulness” originally originated from Buddhist meditation, that is, it developed from meditation, and enlightenment [7]. Brown defines it as a purposeful and conscious focus on the present, but does not judge all ideas of the moment [8].At present,mindfulness therapy mainly includes mindfulness-based stress reduction (MBSR),mindfulness-based cognitive therapy (MBCT),acceptance and commitment therapy(ACT),dialectical behavioral therapy (DBT) and so on. Among them,MBSR is the most widely used one[9].

In recent years, mindfulness therapy has been increasingly applied to cancer patients,and its effect in breast cancer patients has been proved[10].At present,there has been an article analyzing the effect of MBSR on cancer-related fatigue in cancer patients, but the randomized controlled trials (RCTs) included in the study were inadequate as the retrieval time only ended in December 2014 [11], and also without cancer patients classification. Therefore, the purpose of this study was to use the Cochrane systematic review to conduct a meta-analysis of the included literature, to further scientifically evaluate the effect of mindfulness therapy on cancer-related fatigue in lung cancer patients, and to provide references for subsequent studies.

Methods

Inclusion criteria

(1) Study types: randomized controlled studies or clinical trials. The adequacy of allocation hiding and blind method is not considered. (2) Research object:the subjects met the WHO classification and were pathologically and/or cytologically diagnosed with lung cancer. Patients with lung cancer receive chemotherapy with cancer-related fatigue [12].According to the international classification of diseases tenth edition for cancer-related fatigue [13]. (3)Interventions: patients in intervention group were treated with routine care and mindfulness therapy;patients in control group were treated with routine care.(4) Outcome: the revised piper fatigue scale or the cancer fatigue scale was used to evaluate the cancer-related fatigue in lung cancer patients.

Exclusion criteria

(1) Repeated reports. (2) The outcome of this study is not evaluated or data loss cannot be analyzed. (3)Non-Chinese and English documents. (4) Conference papers,academic reports etc.

Search strategy

Chinese and English databases: Cochrane Library,PubMed, Embase, WanFang, VIP and CNKI. The retrieval time is limited to December 1, 2019. The retrieval method of combining subject words and free words is adopted, and the search strategy is adjusted according to different databases. Search terms include:lung cancer, lung carcinoma, cancer du poumon,MBSR, MBCT, cancer related fatigue and so on.Mainly by computer retrieval, supplemented by manual retrieval, to avoid the omission of literature, to ensure the recall rate. The retrieval strategy takes PubMed as an example, and the search strategy is shown in Table1.

Literature screening and data extraction

Two researchers trained in an evidence-based course screened the literature, extracted the data and cross-checked them. If the two disagree, a third researcher confirms. The extracted data table mainly includes the author, year, country, age, sample size,intervention group measures, control group measures,cancer-related fatigue scores and other contents.

Quality assessment

Quality assessment method recommended according to the Cochrane Handbook 5.1.0 for RCTs.The following domains were assessed: random sequence generation(selection bias),allocation concealment(selection bias),blinding of participants and personnel (performance bias), blinding of outcome assessment (detection bias),incomplete outcome data (attrition bias), and selective reporting (reporting bias). Two reviewers independently assessed each study and made evidence-based judgements on the attempts of study authors to minimize bias in their trials. Any disagreements were discussed and resolved by a third reviewer. Each study was methodically judged in all domains and placed into a category-low, high or unclear risk of bias.

Data synthesis

RevMan 5.3 software was applied to synthesize data as recommended by the Cochrane Handbook of systematic reviews of interventions. Continuous data were analyzed using the inverse variance approach by combining the mean difference of individual studies when the outcome was reported using the same measurement scale, or the standardized mean difference (SMD) of individual studies, when the outcome was reported using different measurement scales.Heterogeneity analysis was performed using theX2test. A X2test withP-value ＜0.10 (significance level of 0.1)indicates that a study is heterogenous.The I2statistic was used to assess the extent of heterogeneity (I2= 0%-30%, low; I2= 30%-60%,moderate;I2=50%-90%,substantial,I2=75%-100%,considerable). If heterogeneity was not significant(P-value ＞0.10 and I2＜50%), the fixed-effects model was adopted. If heterogeneity was significant (P-value＜0.10 and I2＞50%), a random-effects model was used. All effect sizes were expressed as 95%confidence interval(CI)and test level was taken as α=0.05.

Results

Search process

The systematic search yielded 297 records. 60 duplicates were removed, leaving 237 records for screening. 220 records based on title and 7 records based on abstract were excluded after screening against the eligibility criteria. The full-text of remaining 10 records were retried. Through sifting layer upon layer strictly, 6 articles were finally included [14-19]. The PRISMA flowchart (Figure 1) illustrates the search process.

Description of included studies

The six studies [14-19] included were RCTs involving a total of 448 patients, 223 patients in the intervention group, and 225 patients in the control group. All participants were above 50 years old, mean ages ranging from 54.26 ± 10.63 to 58.43 ± 6.57 years in the intervention group and 51.80 ± 10.20 to 59.11 ±8.45 years. Wang P [14] did not report mean age of participants included in their study. The duration of interventions ranged from 4 weeks to 3 months, with session varying from 10 minutes to 120 minutes. The basic characteristics of the included studies are shown in Table 2.

Risk of bias

Risk bias item presented as percentages across all included studies is shown in Figure 2. The results showed that 4 of the 6 studies reported the use of random number table method. Others were grouped according to admission time and enrollment time. All the 6 studies did not mention the allocation sequence method and the blind method. Two studies [14, 19]reported missed cases but none of them use the intention-to-treat (ITT) analysis. The data in the 6 studies is complete and is rated as low risk. Other biases could not be determined in the absence of enough evidence.

Results of meta-analysis

Cancer-related fatigue. The six studies [14-19]included were RCTs involving a total of 448 patients,223 patients in the intervention group,and 225 patients in the control group. Different studies assess cancer-related fatigue using different tools, and thus the SMD was used. Heterogeneity test: df = 5 (P=0.003), I2= 76%, indicating that the homogeneity of the included literature was poor, and the random effects model was used for meta-analysis. (SMD =-1.67, 95% CI (-2.09, -1.24),P＜0.001), the results showed that the intervention group was superior to the control group, as shown in Figure 3. Due to I2= 73%,so sensitivity analysis was used to explore heterogeneous sources by removing the selected RCTs one by one to recalculate the overall correlation results and I2.After analysis, the source of heterogeneity may be related to the intervention plan. The result of sensitivity analysis showed that:df=4(P=0.90),I2=0%, the heterogeneity was significantly smaller, and the difference was still statistically significant (SMD =-1.46,95%CI(-1.68,-1.23),P ＜0.001),as shown in Figure 4. In the study of Gao Rong [18], the intervention group was given both mindfulness therapy,progressive muscle relaxation exercises and so on.This study differs from other studies in progressive muscle relaxation exercise. Of course, the sources of heterogeneity may be also including intervention time,study object and other factors. This meta-analysis included only six studies.Because of the small number,the funnel plot was not used to quantify the publication bias.

Anxiety.Three studies[16,18,19]evaluated the effect of mindfulness therapy on anxiety in patients with lung cancer. The results showed that mindfulness therapy could alleviate the anxiety of lung cancer patients, and the combined effect was statistically significant (SMD= -1.33, 95% CI (-2.53, -0.13),P= 0.03), as shown in Figure 5.The combined results showed that the heterogeneity between studies was high (P＜0.001, I2= 94%), so sensitivity analysis was used to find the source of heterogeneity. The results showed that heterogeneity might be related to the intervening time.The intervening time of 2 studies was 6 or 8 weeks,while the intervening time of another study was 3 months. The trials passed the heterogeneity test after we removed RCTs by Ge Y [16] (I2= 0%,P= 0.61).The result showed that the difference in anxiety was significant(SMD =-0.73,95%CI(-1.10,-0.37),P＜0.001).

Depression. Three studies [16, 18, 19] evaluated the effect of mindfulness therapy on depression in patients with lung cancer. The results showed that mindfulness therapy could alleviate the depression of lung cancer patients, and the combined effect was statistically significant(SMD =-1.43,95%CI(-2.13,-0.73),P＜0.001), as shown in Figure 6. The combined results showed that the heterogeneity between studies was high (P ＜0.001, I2= 82%), so sensitivity analysis was used to find the source of heterogeneity. The trials passed the heterogeneity test after we removed RCTs by Gao R[18](I2=57%,P=0.13).The heterogeneity decreased but substantial heterogeneity remained. The result showed that the difference in anxiety was significant(SMD =-1.10,95%CI(-1.60,-0.61),P＜0.001). The heterogeneity might be related to the intervening plan,age of patients and so on.

Figure 1 PRISMA flow diagram

Other outcomes. The included literature also reported indicators such as quality of life, quality of sleep and self-efficiency. Due to the small number of literature reports, meta-analysis is not appropriate. Therefore,this paper only makes descriptive reports on these outcomes.In Wang YH's study,the quality of life score of the intervention group was higher than that of the control group (P＜0.001). In Gao R's study, the score of sleep quality in the intervention group after intervention was lower than that before intervention and lower than that in the control group (P＜0.05). In Guan XY's study, the self-efficacy score of the intervention group was higher than that of the control group (P＜0.05). In Ge Y's study, the survival quality score of the intervention group was higher than that of the control group (P＜0.05). In summary, due to the small number of studies, the impact of mindfulness therapy on the quality of life, sleep quality, and self-efficacy of patients with lung cancer still needs a long time to verify.

Table 1 Search strategy

Figure 3 Forest plot shows the effect of mindfulness therapy on the cancer-related fatigue in lung cancer patients.

Figure 4 Sensitivity analysis

Figure 5 Forest plot shows the effect of mindfulness therapy on the anxiety in lung cancer patients

Figure 6 Forest plot shows the effect of mindfulness therapy on the depression in lung cancer patients

Discussion

Originally derived from Buddhist meditation,mindfulness is a way of awakening the inner ability to focus through eastern Zen meditation, and a method of self-regulating psychological training [20]. The results of a study by Tian L in 2015 [11] showed the effectiveness of mindfulness therapy for cancer-related fatigue in cancer patients. The Cochran Handbook recommends that systematic reviews be updated every two years. So, Tian L's research is not time-sensitive.At the same time, her research included all kinds of cancer patients, while it was not completely universal for lung cancer patients who received more cycles of chemotherapy. Current research shows that mindfulness therapy can help reduce cancer-related fatigue in patients with lung cancer, but no meta-analysis was performed to check the effectiveness of the effects. At present, there are no studies discussing intervention plans to reduce cancer-related fatigue in patients with lung cancer.Therefore,this study conducts meta-analysis to discuss this.

The results of this meta-analysis showed that the intervention group with mindfulness therapy was better than the control group in alleviating cancer-related fatigue, which was statistically significant. In the included literatures, the main interventions involved mindfulness cognition, body scanning, breathing training and other mindfulness therapies,which are all guided by trained therapists. Formal meditation training mainly includes sitting meditation, walking meditation, body scanning, Gental Hatha yoga [21].The intervention time was mainly 8 weeks.Differences in intervention plans will prevent the application of mindfulness to clinical norms. At the same time, the mechanism of mindfulness therapy to alleviate the fatigue caused by cancer also needs to be further explored.

In this study, mindfulness therapy is beneficial for reducing anxiety and depression symptoms in patients with lung cancer. However, the number of included studies and sample size is small, and there is some heterogeneity, so the results need more multi-center,large-sample randomized controlled experiments. Due to the number of studies included, the effectiveness of mindfulness therapy for other outcome measures requires long-term test.

Among the six studies [14-19] included, there were 4 studies on random number table method.Two studies used time of enrollment and time of admission, which is a high-risk random method. None of the included studies reported the content assigned to the selection,blind method. In this study, the patients with cancer-related fatigue lung cancer may be treated with mindfulness therapy, so the blind method cannot be implemented on the patient. But researchers should focus on assigning selection and blind reports.Baseline data from the six studies were not statistically significant,and ITT analysis was not used in two of the studies with loss of follow-up. It illustrated that future research on mindfulness therapy should increase ITT analysis in order to clarify the bias caused by withdrawal.

This meta-analysis demonstrated the effectiveness of mindfulness therapy in reducing cancer-related fatigue in patients with lung cancer. The included literature also reported indicators such as quality of life, quality of sleep and self-efficiency. Due to a small number of indicators and insufficient evidence for meta-analysis,the impact of mindfulness therapy on these indicators in lung cancer patients is still uncertain. The included literature didn't adopt correct random allocation and concealment methods may cause selective bias. There may be publication bias, because of the meta analysis only has Chinese documents. Due to the different intervention plans,intervention time and other contents,the effect of mindfulness therapy on lung cancer patients needs to be further explored. Therefore, more large-scale and high-quality studies are needed for further validation and sequential analyses should be performed to determine the stability of the integration results.