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 [email protected]

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 cancer-related 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 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.

Results

Literature Screening Results

Seventy randomized controlled studies were ultimately included, and the document selection process is presented in Figure 1.

Figure 1 Study search flow chart.

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 compounding excluding combined application, and the control group mostly adopted western symptomatic treatment with chemotherapy, as detailed in Table 1.

Table 1 Characteristics of Included Studies

Results of Risk of Bias Evaluation

The findings of the bias risk assessment of the included studies are presented in Table 2.

Table 2 Results of Risk of Bias Evaluation of Included Studies [Articles (%)]

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 group^{6,8,12,14–16,18–20,22,27,29,30,32–36,38,40,42,47,50,52,53,55,59,60,64,67–69,71,74} in 35 studies, chemotherapy alone as a control group^{9,10,21,26,37,39,41,48,51,54,56,57,65,66,70,72,73} in 17 studies, placebo as a control group^23,24,44,62 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.

Table 3 Selection Classification of Chinese Medicine Compound for Cancer-Caused Fatigue Control Group

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.

Table 4 Six Categories of Outcome Indicators for Cancer-Caused Fatigue Treated with Chinese Herbal Compounding

Classification of Fatigue Scales

From the 70 included studies, six fatigue scales were used in the herbal preparation for cancer fatigue of which 25 studies^{6,14,16,18,20,26,29,32–34,37–40,44,46,50,51,54,55,57,64,65,71,72} used the piper fatigue scale (PFS) and 18 studies^{6,14,16,18,20,26,29,32–34,37–40,44,46,50,51,54,55,57,64,65,71,72} took advantage of the PFS revised (PFS-R), 11 studies^{4,9,13,17,23,31,42,45,49,61,73} using the cancer fatigue scale, and 8 studies^{5,10,24,25,45,60,62,68} using the brief fatigue inventory, 3 studies^47,48,66 using the fatigue symptom inventory, and 2 studies^8,47 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, 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-of-life 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 non-pharmacological 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.

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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