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International Journal of General Medicine
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Open Access Full Text Article
REVIEW
Analysis of Outcome Indicators of Cancer-Related
Fatigue Treated with Chinese Herbal
Compounding
Zhong-Hui Li, Xin-Wei Zhang, Yue-Yan Weng, Lei Zhou, Fang Wang
Department of Oncology, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China
Correspondence: Fang Wang, Department of Oncology, Wangjing Hospital, China Academy of Chinese Medical Sciences, Huajiadi Road, Beijing,
100102, People’s Republic of China, Email wf074500@163.com
Objective: In the direction of evaluating the current status of outcome indicators and control group selection in randomized controlled
studies of Chinese herbal compounding (such as Sini plus Renshen Decoction, Jianpifuzhengfang, Bufei Jianzhong Decoction, etc) for
cancer-caused fatigue and to provide a reference for clinical studies of Chinese herbal compounding for cancer-caused fatigue.
Methods: Randomized controlled studies of Chinese herbal medicine for cancer-caused fatigue in the midst of 2012 and 2022 were
searched in CNKI, PubMed, and EMBASE databases on the China Knowledge Network, and the literature was screened using
NoteExpress. Two researchers independently conducted the literature review, and then the studies that met the criteria were grouped
and analyzed adopting qualitative analysis of outcome indicators and control groups.
Results: A total of 70 randomized controlled studies that met the requirements were included, and after doing statistical analysis, it
can draw to the conclusion that the risk of bias in the included studies was high; at the same time, the TCM evidence score scale,
objective indicators, and safety indicators were underutilized; additionally, there were no uniform standards for the fatigue scale, and
the selection of control groups lacked balance and consistency.
Conclusion: The outcome indicators of TCM compound treatment of cancer-caused fatigue should be on the basis of the principle of
“diagnosis and treatment” in TCM, the proportion of objective indicators should be exaggerated, as well as the interventions in the
control group should be unified.
Keywords: Chinese herbal compound, cancer-related fatigue, randomized controlled trial, outcome indicators, control group
Introduction
Cancer-related fatigue (CRF) is defined as a distressing, persistent, subjective feeling of somatic, emotional, or cognitive
fatigue or exhaustion that is characterized by rapid onset, duration, severity, and unpredictability.1 CRF is associated with
the tumor itself and treatment, but its specific pathogenesis is still unclear. In recent years, the incidence of cancer-caused
fatigue has shown a significant increase, and the current clinical treatment is mainly based on non-pharmacological
interventions, supplemented by pharmacological treatments.2 Chinese medicine compounding is the leading therapeutic
tool in traditional Chinese medicine (TCM), and it has achieved a better efficacy in the treatment of CRF.3 TCM has been
applied in the treatment of more than 70% of cancer patients in China. Data have shown that TCM can significantly
enhance the sensitivity to chemotherapeutic drugs, enhance tumor-suppressing effects, and significantly improve cancerrelated fatigue, bone marrow suppression, and other adverse reactions.4 Although there exist more clinical studies on the
treatment of CRF with herbal compounding, the evaluation of efficacy and outcome indicators alter, and there is no fixed
standard for the selection of control groups. Hence, in clinical studies, the selection of outcome indicators and control
groups are more critical aspects, and it has been proved that the outcome indicators and control groups adopted in similar
clinical studies differed greatly from each other.5 Therefore, we qualitatively analyzed the current status of the selection
of outcome indicators and control groups in randomized controlled studies approaching the treatment of cancer-caused
International Journal of General Medicine 2022:15 8603–8615
Received: 5 September 2022
Accepted: 10 November 2022
Published: 15 December 2022
8603
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Li et al
fatigue with Chinese herbal compound prescriptions over the past few decades to provide more accurate criteria for the
assessment of the efficacy of Chinese herbal compound prescriptions in the treatment of cancer-caused fatigue, and to
provide an over and above accurate assessment of the effectiveness of Chinese herbal compound prescriptions in the
treatment of cancer-caused fatigue. Baseline indicators and control group selection from the randomized controlled study
of the Chinese herbal formulation for the treatment of cancer fatigue are provided as references.
Materials and Methods
The data of this study were obtained from the randomized controlled trials (RCTs) papers on Chinese herbal compounds
for cancer-caused fatigue in CNKI, PubMed, and EMBASE databases, searched from 2012 to 2022, and the language
types included limited in Chinese and English.
Inclusion criteria: (1) The subjects in this study were cancer fatigue patients (race, nationality, cancer type); (2) The
study criteria were in accordance with the RCT trial design; (3) The interventions in the study were simple herbal
compounds for the treatment group and conventional treatment, chemotherapy, and placebo for the control group; and (4)
Outcome indicators were multi-fatigue scales, TCM evidentiary scales, quality of life scales, mood scales, biochemical
indicators, safety indicators, etc.
Exclusion criteria: (1) Duplicate literature; (2) Observation group was a combined Chinese herbal medicine protocol,
single herbal medicine, or Chinese medicine cream; (3) No complete observation index or single-arm pilot study; (4)
Relevant review type, observation type, and incomplete information articles; and (5) Non-Chinese and English literature.
Literature Research Strategy
The search databases included CNKI, PubMed, and EMBASE, and the search dates were between 2012 and 2022. The
search was conducted by a combination of subject terms and free words, and the Chinese search terms included: Chinese
medicine, cancer-caused fatigue, cancer fatigue, cancer, tumor, fatigue, fatigue, randomized, and control. English search
terms included: Chinese medicine, cancer-related fatigue, cancer, fatigue, chance, clinic, etc. Use “or (or)”, “and (and)”
to connect the disease names of cancer-caused fatigue; use the search in results with “or (or)”, “and (and)” to associate
with the name of the Chinese herbal compound; use “or (or)” and “and (and)” to connect random and control, and again
search in the results. The research methods in Chinese and English were similar, and the specific research strategy was as
follows, taking the CNKI research as an example.
CNKI: SU=(“Chinese medicine” + “Chinese medicine compound”) AND AB=(“random” + “control”) AND SU=
(“fatigue” + “fatigue” + “tiredness” + “exertion” + “fatigue”) AND SU=(“cancer” + “tumor”)
Literature Processing
The titles and abstracts of all literature were independently assessed and screened by two investigators applying
NoteExpress software in accordance with the same inclusion and exclusion criteria, and if one of the investigators
thought that the title and abstract of a particular article met the inclusion requirements, the full text was read by both of
them to make a decision on whether to include it, and any disagreement during the screening process should be arrived at
conclusion by discussion or a third party. The main information extracted included the first author of the literature,
the year of publication, interventions (observation and monitoring groups), outcome assessment indicators, and risk of
bias assessment.
Evaluation of the Risk of Study Bias
The risk of bias in the included studies was assessed by two reviewers using the risk of a bias assessment tool for
randomized controlled studies in the Cochrane Handbook.
Statistical Analysis
Qualitative descriptive analysis was used to analyze the classification and frequency of the interventions in the control
group in the study of herbal compounding for cancer-caused fatigue; to analyze the classification and frequency of
outcome indicators, and to analyze the types of fatigue scales selected in the study.
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Results
Literature Screening Results
Seventy randomized controlled studies were ultimately included, and the document selection process is presented in
Figure 1.
General Characteristics of the Included Studies
Out of 70 documents included, 65 were in Chinese, and 5 were in English. Among them, 42 were journal papers and 28
were dissertations, published between 2012 and 2022, and the literature in the last 3 years accounted for over 50% of the
total literature, indicating that the treatment of cancer-caused fatigue with herbal compounding has received with
acceleration attention in recent years. The interventions in the treatment group were limited to simple herbal compound
ing excluding combined application, and the control group mostly adopted western symptomatic treatment with
chemotherapy, as detailed in Table 1.
Results of Risk of Bias Evaluation
The findings of the bias risk assessment of the included studies are presented in Table 2.
Classification of the Control Group
The interventions in the 70 RCT treatment groups included in this research were limited to herbal compounding alone,
and the interventions in the control group included studies with symptomatic treatment at most as the control
Figure 1 Study search flow chart.
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Table 1 Characteristics of Included Studies
Ref.
Number
Intervention Measures
(T/C)
Cao et al,6 2022
Gao et al,7 2022
T
C
Treatment
Outcome
Cycle
Indicators
34/34
Symptomatic treatment + sini plus
Symptomatic treatment
21 d
1, 2, 3, 5
30/30
renshen decoction
Symptomatic treatment + xiaqi
Symptomatic treatment
21 d
1, 2, 3, 4, 6
decoction
Zuo et al, 20228
29/30
Symptomatic treatment +
jianpifuzhengfang
Symptomatic treatment + guipiwan
56 d
1, 2, 5
Dao, 20219
36/36
Self-made bufei jianzhong decoction
Buzhongyiqiwan
14 d
1, 2, 3, 6
Gao et al, 202110
34/34
Symptomatic treatment +
buzhongyiqiguben decoction
Symptomatic treatment
30 d
1, 2, 3, 4
Du et al, 202111
30/30
Chemotherapy + feifukangfang
Chemotherapy
84 d
1, 2, 4, 6
Zhao et al, 202112
Xu, 202113
50/50
26/26
Chemotherapy + feiliu xiaoji fang
Chemotherapy + fuzheng jiedu
Chemotherapy
Chemotherapy + jiedu decoction
84 d
56 d
1, 2, 3
1, 2, 3, 4, 5
Huang, 202114
35/35
Symptomatic treatment +
guiluerxianjiao tang
Symptomatic treatment
28 d
1, 2, 3, 5, 6
Zheng et al,
120/120
Modafinil + huoxue fuxing decoction
Modafinil
21 d
1, 3, 5, 6
202115
Du, 202116
25/25
Symptomatic treatment + jianpi
Symptomatic treatment
28 d
1, 2, 3
decoction
bushen fang
Xin, 202117
40/40
Symptomatic treatment +
jianpixiaoji tang
Symptomatic treatment
30 d
1, 3
Li et al, 202118
62/61
Symptomatic treatment + jianpiyiqi
Symptomatic treatment
28 d
1, 2, 3, 5
40/40
tang
Non drug treatment + neibu
Non drug treatment
28 d
1, 2, 3, 5, 6
Guo, 202119
huangqi decoction
Cao, 202120
30/30
Symptomatic treatment + qiyuliujun
tang
Symptomatic treatment
28 d
1, 2, 3, 5, 6
Gao, 202121
30/30
Symptomatic treatment +
Symptomatic treatment
14 d
1, 2, 3, 4, 6
30/30
shengyangyiweisanxian tang
Symptomatic treatment + sini
Symptomatic treatment
56 d
1, 2, 5
48 d
28 d
1, 2, 3, 5, 6
1, 2, 6
Cao et al, 202122
decoction
Xu, 202123
Chen et al, 202124
32/32
40/40
Chemotherapy + weining fang
Symptomatic treatment +
Chemotherapy
Symptomatic treatment
Hu et al, 202125
60/60
yangzhengjiefa tang
Buzhongyiqi tang
Placebo
21 d
1, 4, 5
Lee et al, 202126
24/24
Sini tang
Placebo
21 d
1, 4
Li et al, 202127
Jiang, 202028
55/55
45/45
Fuzhengjiedu fang
Chemotherapy + yiqiyangyin fang
Zhenqi fuzheng capsule
Chemotherapy
28 d
56 d
1, 5
1, 4, 5
Qin, 202029
30/30
Symptomatic treatment + bazhen
Symptomatic treatment
30 d
1, 2, 3, 4, 5, 6
32/32
decoction
Symptomatic treatment + shenling
Symptomatic treatment
30 d
1, 2
Zhang et al, 202030
baizhu powder
Zhang, 202031
30/30
Symptomatic treatment +
shengqidihuang tang
Symptomatic treatment
14 d
1, 2, 3, 5
Jiang et al, 202032
30/30
Symptomatic treatment + chaihu
Symptomatic treatment
7d
1, 3, 4, 5, 6
Sun, 202033
30/30
pingwei powder
Bufeihuaji tang + aidi injection
Aidi injection
34 d
1, 2
Wang, 202034
35/35
Symptomatic treatment + tiaogan
Symptomatic treatment
28 d
1, 2, 3, 5, 6
yangxue fang
(Continued)
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Table 1 (Continued).
Ref.
Number
(T/C)
35
Lin, 2020
Gan et al, 202036
Intervention Measures
T
C
Treatment
Cycle
Outcome
Indicators
30/30
Symptomatic treatment +
Symptomatic treatment
30 d
1, 2, 3, 4, 5, 6
48/48
fuzhengkangai tang
Symptomatic treatment +
Symptomatic treatment
56 d
1, 4, 5
fuzhengxiaoliu tang
Zhao, 202037
38/37
Symptomatic treatment +
fuzhengyangrong fang
Symptomatic treatment
56 d
1, 2, 3, 4, 5, 6
Liu, 202038
30/30
Symptomatic treatment +
Symptomatic treatment
56 d
1, 2, 3, 4, 6
Dai, 202039
30/30
gancaoxiexin tang
Chemotherapy + jianpiyangwei fang
Chemotherapy
14 d
1, 2, 3, 4, 5, 6
Ning, 202040
40/40
Symptomatic treatment +
Symptomatic treatment
21 d
1, 2, 3, 4 6
Xu, 202041
40/38
buzhongyiqi tang
Chemotherapy + buyixusun fang
Chemotherapy
42 d
1, 4, 5
He et al, 202042
34/34
Symptomatic treatment +
Symptomatic treatment
14 d
1, 3, 6
Xie et al, 202043
46/46
jianpibushen fang
Chemotherapy + buzhongyiqi tang
Chemotherapy
42 d
1, 4, 6
Han, 202044
36/36
Symptomatic treatment + shuyuwan
Symptomatic treatment
21 d
1, 2, 3, 6
Yich et al, 202045
Xiao et al, 202046
42/41
30/30
Renshenyangrong tang
Jianpishengsui fang
Huangqi
Placebo
42 d
42 d
4
1, 2, 4
Liu et al, 201947
66/66
Feiyanning fang + kangliuzengxiao
Kangliuzengxiao fang
90 d
1, 5
45/45
fang
Symptomatic treatment +
Symptomatic treatment + compound
90 d
1, 5
compound shougong powder
cantharidin capsule
Lu et al, 201948
Bao, 201949
25/25
Symptomatic treatment +
zhenqifuzheng fang
Symptomatic treatment
56 d
1, 2, 4
Zhan et al, 201950
42/38
Chemotherapy + jianpishengsui fang
Chemotherapy
21 d
1, 5
Li, 201951
44/43
Chemotherapy+jianpiyishenbuqi
tang
Chemotherapy + buzhongyiqi
mixture
90 d
1, 5, 6
Tao, 201952
30/30
Symptomatic treatment +
Symptomatic treatment
42 d
1, 2, 3, 5, 6
Cai, 201953
41/41
jianpiyishenyangxue fang
Chemotherapy + jusan decoction
Chemotherapy
84 d
1, 5, 6
Li, 201954
30/30
Symptomatic treatment +
Symptomatic treatment
14 d
1, 2, 3
30/30
shashenmaidong tang
Symptomatic treatment +
Symptomatic treatment
14 d
1, 2, 3, 5
Chemotherapy
Symptomatic treatment
42 d
14 d
1, 2, 3, 5, 6
1, 2, 3
Chemotherapy
Chemotherapy
84 d
168 d
1, 4, 5
1, 3, 4, 5
Health education
Symptomatic treatment
56 d
21 d
1, 2, 4, 6
1, 3
Han et al, 201955
shiquandabu tang
He, 201956
Lin et al, 201857
25/25
32/32
Shi et al, 201858
Ning et al, 201859
55/55
68/68
Liu, 201860
Liu, 201862
35/35
32/32
Li et al, 201863
42/42
Symptomatic treatment +
shiquandabu tang
Symptomatic treatment
14 d
1, 4, 5
Jia et al, 201864
54/54
Bozhi glycopeptide +
Bozhi glycopeptide
84 d
1, 5
15/15
jianpiyishenjiedu tang
Guipi decoction
Placebo
14 d
1, 4
Chemotherapy + wenbupishen fang
Symptomatic treatment +
buzhongyiqi tang
Chemotherapy + changyi decoction
Chemotherapy + fuzhengsanjiejiedu
tang
Health education + guipi decoction
Symptomatic treatment + guipi
decoction
Jee et al, 201865
(Continued)
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Table 1 (Continued).
Ref.
Number
(T/C)
66
Zhang et al, 2017
Nian, 201767
Intervention Measures
T
C
Treatment
Cycle
Outcome
Indicators
80/80
Symptomatic treatment + bazhen
Symptomatic treatment +
90 d
1, 2, 4, 5
19/19
tang
Symptomatic treatment +
buzhongyiqi mixture
Symptomatic treatment
56 d
1, 2, 3, 4, 5, 6
shuganjianpi granule
Li et al, 201668
Liu et al, 201669
45/45
41/41
Chemotherapy + jianpixiaoji tang
Chemotherapy + buzhongyiqi tang
Chemotherapy
Chemotherapy
40 d
21 d
1, 3
1, 6
Li 201670
75/75
Symptomatic treatment +
Symptomatic treatment
63 d
1, 2, 3, 5, 6
30/30
jianpiyishen fang
Symptomatic treatment +
Symptomatic treatment
28 d
1, 2, 4
Xu, 201671
yiqijianpibushen fang
Zhao, 201672
33/33
Symptomatic treatment +
jinshuifuyuan fang
Symptomatic treatment
14 d
1, 2, 3, 6
Li, 201573
30/30
Chemotherapy + jianpiyishen fang
Chemotherapy
42 d
1, 2, 3
Ji, 201574
30/30
Symptomatic treatment +
shiquandabu tang
Symptomatic treatment
14 d
1, 3, 4, 5, 6
Ma et al, 201575
23/22
Chemotherapy + xingjian tang
Chemotherapy
60 d
1, 2, 3
Tan et al, 201276
32/31
Chemotherapy + jianpiyishenhuatan
fang
Chemotherapy
14 d
1
Notes: T, treatment; C, control; 1, fatigue scale; 2, traditional Chinese medical syndrome scale; 3, quality of life scale; 4, other scales; 5, biochemical indicators; 6, safety
indicators.
Table 2 Results of Risk of Bias Evaluation of Included Studies [Articles (%)]
Projects
Random sequence generation
High Bias Risk
Low Bias Risk
Risk of Bias Unknown
4 (5.71)
48 (68.6)
18 (25.7)
Using blind method
Integrity of result data
0
0
10 (14.3)
51 (72.9)
60 (85.7)
19 (27.1)
Assign Hide
0
21 (30.00)
49 (70.00)
Selective Ending Report
Other sources of bias
0
0
11 (15.7)
0
59 (84.3)
70 (100.00)
group6,8,12,14–16,18–20,22,27,29,30,32–36,38,40,42,47,50,52,53,55,59,60,64,67–69,71,74 in 35 studies, chemotherapy alone as a control
group9,10,21,26,37,39,41,48,51,54,56,57,65,66,70,72,73 in 17 studies, placebo as a control group23,24,44,62 in 4 studies, and the rest
adopting symptomatic treatment + buzhongyiqi compound,63 symptomatic treatment + compound zebrano capsules,46
symptomatic treatment + guipiwan,6 chemotherapy + detox tang,11 chemotherapy + buzhongyiqi compound,49 addy
injection,31 buzhongyiqi wan,7 anti-tumor and potent formula,45 modafinil capsule,13 zhenqifuzheng capsule,25 bozhi
glycopeptide,61 huangqi,61 health education58 as the control group, and the results are shown in Table 3.
Classification of Outcome Indicators
The outcome indicators used ranged significantly across the 70 included studies. The largest number of studies used the
fatigue scale (68) among the outcome indicators, followed that the TCM symptom rating scale (44), quality of life scale
(40), biochemical indicators (39), safety indicators (29), other functional evaluation scales (29), with the quality of life
measurement scale for cancer patients (QLQ-C30) being adopted more frequently (17), mood-based scales (7), the
Pittsburgh sleep quality index scale (3), and the rest of the scales were handled only in individual studies, and the results
are demonstrated in Table 4.
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Table 3 Selection Classification of Chinese Medicine Compound for Cancer-Caused Fatigue Control Group
Control Group Classification
Control Group Interventions
Symptomatic treatment
Symptomatic treatment
alone4,5,8,12,14–16,18–20,22,27,29,30,32–36,38,40,42,47,50,52,53,55,59,60,64,67–69,71,74
35
Symptomatic treatment + guipiwan6
1
Symptomatic treatment + compound zebrano capsules6
Symptomatic treatment + buzhongyiqi compound63
1
1
Chemotherapy alone63
17
Chemotherapy + detox tang11
Chemotherapy +buzhongyiqi compound49
1
1
Buzhongyiqi wan7
Modafinil capsule13
1
1
Zhenqifuzheng capsule25
1
Addy injection31
Huangqi31
1
1
Anti-tumor and potent formula45
1
Bozhi glycopeptide45
Placebo23,24,44,62
1
4
Health education58
1
Chemotherapy
Other drugs
Non-drug
Number of Studies
Classification of Fatigue Scales
From the 70 included studies, six fatigue scales were used in the herbal preparation for cancer fatigue of which 25
studies6,14,16,18,20,26,29,32–34,37–40,44,46,50,51,54,55,57,64,65,71,72 used the piper fatigue scale (PFS) and 18
studies6,14,16,18,20,26,29,32–34,37–40,44,46,50,51,54,55,57,64,65,71,72 took advantage of the PFS revised (PFS-R), 11
studies4,9,13,17,23,31,42,45,49,61,73 using the cancer fatigue scale, and 8 studies5,10,24,25,45,60,62,68 using the brief fatigue
inventory, 3 studies47,48,66 using the fatigue symptom inventory, and 2 studies8,47 using the multidimensional fatigue
inventory.
Discussion
A statistical review of 70 studies revealed that approximately 97% of the studies applied the fatigue scale as an outcome
indicator, about 63% used the Chinese medicine evidence rating scale as an outcome indicator, about 57% used the
quality of life scale as an outcome indicator, and around 56% used biochemical indicators as an outcome indicator,
followed by the functional assessment scale (41%), safety indicators (41%), and others. For the selection of the control
group, all over 50% used symptomatic treatment as an intervention in the control group and about 24% used
chemotherapy as an intervention in the control group. After compiling the 70 studies, the following issues were identified
in the selection of outcome indicators and control groups in the plant-based composition studies for cancer fatigue.
There is still not enough use of the TCM syndrome scale. Chinese medicine treatment for CRF is mostly guided by
the “holistic concept” of Chinese medicine and is administered according to the patient’s condition, hence, the Chinese
medicine symptoms are the premise and basis of prescription. In modern Chinese medicine, it is considered part of the
category of “insufficient work” in Chinese medicine. Deficiency labor also acknowledged as deficiency loss is a general
term for a variety of chronic debilitating symptoms on the basis of deficiency of internal organs and deficiency of qi,
blood, yin, and yang as the basic pathology. Cancer-caused fatigue originates from cancer itself, and different cancer
types invade different internal organs, and different patients have a different physical constitution, so a clear standard
TCM symptom score is of vital importance. Although most researchers have recognized the importance of TCM
symptoms, there is a need to further increase the application of this index and standardize the TCM symptoms scale
to improve the clinical effectiveness of evidence-based treatment.
No uniform standard exists for fatigue ladders. The fatigue scale is the primary indicator of the results of the cancer
fatigue assessment, and six fatigue scales were used in the study. Even if the same treatment measures were applied,
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Table 4 Six Categories of Outcome Indicators for Cancer-Caused Fatigue Treated with Chinese Herbal Compounding
Classification of
Name
Number of
Outcome Indicators
Fatigue scale
Quality of life scale
Emotion scale
Other functional scales
Biochemical indicators
Studies
Cancer fatigue scale4,9,13,17,23,31,42,45,49,61,73
11
Piper fatigue revised scale7,11,12,21,22,27,30,36,41,53,56,58,59,63,67–70
18
Piper fatigue scale6,14,16,18,20,26,29,32–34,37–40,44,46,50,51,54,55,57,64,65,71,72
Brief fatigue inventory5,10,24,25,45,60,62,68
25
8
Multidimensional fatigue inventory8,47
2
Fatigue symptom inventory8,47
Karnofsky4,5,7,8,10–14,16,18,19,21,27,29,30,32,33,35–38,40,42,50,52,55,57,59,67,69–72,74
3
35
Comprehensive quality of life assessment inventory15
Eastern cooperative oncology group64
1
1
Quality of life inventory: European Organization for Research and Treatment of Cancer-quality of
1
life questionnaire-short form 3665
Hospital anxiety and depression scale24,27,58,64
4
Depression inventory60
1
Self-rated anxiety and depression scales60
Beck depression inventory62
1
1
Chinese medicine evidence scoring scale4–12,14,16–22,27,29,31–33,35–38,42,44,47,50,52–55,58,63,64,67–70,72,74
43
European Organization for Research and Treatment of
Cancer9,11,19,24,26,33,34,36,37,39,41,44,47,56,57,63,68
17
Functional assessment of cancer therapy8
1
Insomniaseverityindex62
Scored patient-generated subjective global assessment62
1
1
Functional assessment of breast cancer treatment scale35
1
Pittsburgh sleep quality index35
Numerical rating scale71
3
1
Sleep quality point scale71
1
Weight score71
Lung cancer specificity scale60
1
1
Adult dispositional hope scale60
1
Montreal cognitive assessment62
Appetite loss score5
1
1
MD Anderson symptom inventory43
1
T lymphocyte subpopulation4,11,12,16–18,23,25,26,30,33–35,37,45,46,49,51,53,54,56,57,60,61,63,71
Natural killer cell12,16,26,34,56,63
26
6
Albumin6,27,39
Hemoglobin6,11,16,26,27,29,32,39,48,53,71,73
3
12
Platelet16,29,32
3
White blood cell11,16,26,29,32,53,71,73
Lymphocyte29
8
1
Neutrophil32,48,53,71,73
5
C-reactive protein13,27,34,50,54,64
Tumor necrosis factor-α16,34,63
6
3
Interleukin-1β,63 interleukin-2,26,64,67 interleukin-4,64,67 interleukin-5,67 interleukin-6,13,16,34,54,64
8
interleukin-8,54 interferon-γ,63,64,67 interleukin-10,64 interleukin-17a64
Immunoglobulin G, immunoglobulin A, immunoglobulin M21,51,56,57
4
CD56+, CD19+45
1
Cortisol level45
Adrenocorticotrop(h)ic hormone13
2
1
CEA,13 Cyfra21-1,20 CA125,20 CA199,25,37 CA72425
3
Thyroid stimulating hormone, free triiodothyronine25
1
(Continued)
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Table 4 (Continued).
Classification of
Outcome Indicators
Name
Number of
Studies
Safety indicators
Hypertension, body temperature, pulse, breathing7,27,36,50,58,67
Hematology,5,7,9,12,13,17,18,21,27,33,35–38,42,50,54,58,64,67,69 urine routine,7,12,21,35–37,50,64,67 convenient
6
20
routine7,12,36,37,50,64,67
Liver and kidney function9,12,13,17–19,27,32,33,35–38,40,42,50,54,58,64,67,69
Electrocardiogram7,12,17,18,21,27,35–37,42,50,64,67,69
20
14
Gastrointestinal reactions7,12,17,18,21,27,35–37,42,50,64,67,69
5
Myelosuppression30,49,66
Toxic reaction51
3
1
different evaluation criteria would result in different outcomes and conclusions. Therefore, to ensure the reliability of the
study results, the fatigue scales should be standardized and unified.
The proportion of quality-of-life scales is low and there is no consistent standard. The assessment of the quality-oflife is an essential step for cancer patients and is also crucial for the determination of clinical efficacy, while the current
quality of life scale accounts for about 57%, and its proportion should be further escalated. There are four types of quality
of life scales used in the study, and although it can be clearly recognized that most of the studies designated to adopt the
Karlsberg score (KPS) there are still studies that use other types of scales to evaluate patients’ quality-of-life, so there is
a need for uniform standardization.
The proportion of objective indicators for assessment was not sufficient. Objective indicators were used in 56% of the
70 included studies, and the usage of objective indicators is expected to be further enhanced. Subjective scales such as
fatigue scale and quality of life score can reflect patients’ fatigue and other physical status, so most researchers made use
of them as the main evaluation indexes. While fatigue is the primary symptom of cancer-related fatigue, objective
indicators are always required to support the reliability of subjective indicators. Among the objective indices selected in
the study, including blood, immune, inflammatory, and hormone levels, the proportion of immune and blood indices is
relatively high, notwithstanding, there is still a problem of confusing indices and lack of specificity. The quality of life of
cancer fatigue patients has been found to be closely linked to hemoglobin and albumin levels,77 and also to immunity
such as T-lymphocyte subsets and natural killer cells,78 and traditional Chinese medicine is constructive in anti-tumor and
regulating human immunity to relieve fatigue. However, because there is no clear pathogenesis of cancer-caused fatigue,
the objective indexes are not standardized enough, so further research on the pathogenesis of cancer-caused fatigue is in
need of improving the objective biochemical indexes.
Inadequate utilization of safety indicators, of the 70 included studies, only 41% used safety indicators as indicators of
results. This study did not include the literature on the combination of herbal compounding with other external treatments
limited to herbal treatment solely, and it was found that most of the studies that used safety indicators were dissertations,
which proves that researchers did not pay enough attention to the safety of oral administration of herbal medicine. We
should improve the use of security indicators and deal with them accordingly.
The selection criteria for control groups vary. The choice of a control group for a study protocol is a more important
aspect and should follow the principle of equilibrium. On the other hand, cancer fatigue is different from ordinary
illnesses, and any treatment has a big impact on the progression of cancer and the patient’s condition. This study mainly
aimed to take the advantage of allopathic treatment and chemotherapy as a control group, while other studies used nonpharmacological treatment or other beneficial and supportive medications as a control group. Although interventions are
coherent within the treatment group, different control groups may lead to different study findings. Therefore, in order to
ensure the effects of patient treatment and study balance, control groups in cancer fatigue studies should be standardized
to come up with more reliable study results.
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There is a high potential for bias in study results. About 6% of the 70 included studies reported the use of blinding, about 16%
used concealing allowances, and only 10% of the studies documented the method of calculating the sample size. In addition,
about 32% of the studies were grouped mostly by subjective decision of the investigator without specifying the randomization
method of the study, all of which would lead to a high risk of selective bias. Therefore, the high risk of bias suggests that the test
presents issues such as reporting positive results only and a lack of discussion and analysis of negative results.
Conclusion
In conclusion, there exist many outcome indicators categorized in the studies of cancer-caused fatigue in Chinese
medicine, but it is uncomplicated to find that few of them are directly related to cancer-caused fatigue. Because fatigue is
a subjective feeling in patients, most studies use fatigue, quality of life, and mood scales to more fully assess the overall
fatigue state of patients. The objective indicators are very important to improve the reliability of the study, and the
biochemical indicators currently used in clinical practice lack specificity and have reason to be standardized and unified,
and insufficient attention is paid to safety indicators for cancer patients with poor overall physical status. The choice of
control groups in the study was also unbalanced and inconsistent.
Through the results of the above statistical analysis, in the selection of fatigue scales, although the PFS was used most
frequently in the included studies the PFS-R was more recommended by comparing the reliability of the fatigue scales and
other aspects;79 the KPS scale is widely used in cancer patients, and this scale can better reflect the patient’s health status and
is mostly used to judge cancer patients before chemotherapy,80 without regard to the reliability, validity, and responsiveness
of the QLQ-C30 are better and more frequently used, so the above two scales are recommended and support the selection of
more relevant indicators in accordance with different cancer types and states. As for the selection of objective indicators,
T-lymphocyte subsets, hemoglobin, leukocytes, and C-reactive protein are recommended for testing and assessment based on
the frequency of use in the included studies. The effectiveness of Chinese medicine in the treatment of cancer-related fatigue
must rest on an “evidence-based treatment”, thus, a uniform Chinese medicine evidence scale should be adopted more often
in the study, to analyze the patient’s situation specifically and choose a more effective and reasonable treatment plan. In
accordance with the risk of bias assessment, the risk of bias is a high-rise in most studies, so we should make an improvement
on the design of the study protocols to provide more rigorous and reliable evidence-based clinical evidence.
Ethical Approval
This article does not contain any studies with human participants or animals performed by any of the authors.
Author Contributions
All authors contributed to data analysis, drafting or revising the article, have agreed on the journal to which the article
will be submitted, gave final approval of the version to be published, and agree to be accountable for all aspects of the
work.
Funding
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Disclosure
The authors report no conflicts of interest in this work.
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