Meta-Analysis Open Access
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Jul 26, 2021; 9(21): 5932-5942
Published online Jul 26, 2021. doi: 10.12998/wjcc.v9.i21.5932
Fatigue prevalence in men treated for prostate cancer: A systematic review and meta-analysis
Yu-Hong Luo, Yan-Wei Yang, Chang-Fu Wu, Chao Wang, Wen-Juan Li, Hong-Chen Zhang
Yu-Hong Luo, Hong-Chen Zhang, School of Nursing, Lanzhou University, Lanzhou 730000, Gansu Province, China
Yan-Wei Yang, Department of Stomatology, The 940th Hospital of Joint Logistic Support Force of the Chinese People’s Liberation Army, Lanzhou 730050, Gansu Province, China
Chang-Fu Wu, The First Clinical Medical College, Lanzhou University, Lanzhou 730000, Gansu Province, China
Chao Wang, School of Clinical Medicine, Gansu University of Chinese Medicine, Lanzhou 730000, Gansu Province, China
Wen-Juan Li, Department of Respiratory and Critical Care, Henan Provincial Hospital, Zhengzhou 450003, Henan Province, China
ORCID number: Yu-Hong Luo (0000-0002-1923-2755); Yan-Wei Yang (0000-0002-5457-1023); Chang-Fu Wu (0000-0003-1443-921X); Chao Wang (0000-0002-1473-2988); Wen-Juan Li (0000-0002-3113-5536); Hong-Chen Zhang (0000-0002-6434-705X).
Author contributions: Luo YH and Yang YW contributed equally to this work; Luo YH and Zhang HC contributed to the design; Wang C and Wu CF completed the data collection; Yang YW and Li WJ provided statistical support; Yang YW and Luo YH provided the analysis; Zhang HC, Luo YH and Yang YW contributed to the manuscript preparation.
Supported by National Natural Science Foundation of China, No. 81701029.
Conflict-of-interest statement: The authors declared no conflicts of interest.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Hong-Chen Zhang, MD, Lecturer, School of Nursing, Lanzhou University, No. 28 Yanxi Road, Chengguan District, Lanzhou 730000, Gansu Province, China. hczhang@lzu.edu.cn
Received: January 22, 2021
Peer-review started: January 22, 2021
First decision: April 29, 2021
Revised: May 8, 2021
Accepted: May 27, 2021
Article in press: May 27, 2021
Published online: July 26, 2021

Abstract
BACKGROUND

The side effects of prostate cancer (PCa) treatment are very prominent, with cancer-related fatigue (CRF) being the most common. Fatigue is a distressing symptom that interferes with daily functioning and seriously affects patient quality of life during, and for many years after, treatment. However, compared with other types of cancer, such as breast cancer, little is known about the prevalence of PCa-related fatigue.

AIM

To determine the prevalence of CRF in patients with PCa.

METHODS

A systematic search of EMBASE, PubMed, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure, WANFANG DATA, Technology Journal Database and the Chinese Biological Medical Database was conducted up to July 28, 2020. Included studies measured the incidence of PCa-related fatigue and differentiated fatigue outcomes (incidence) between treatment modalities and fatigue assessment times. In our meta-analysis, both fixed and random-effects models were used to estimate the pooled prevalence of PCa-related fatigue. Subgroup analyses were performed using treatment modalities and fatigue assessment times. Publication and sensitivity bias analyses were performed to test the robustness of the associations.

RESULTS

Fourteen studies, involving 4736 patients, were eligible for the review. The pooled CRF prevalence was 40% in a total sample of 4736 PCa patients [95% confidence interval (CI): 29-52; P < 0.01; I2 = 98%]. The results of the subgroup analyses showed the prevalence of CRF after androgen deprivation therapy treatment, radical prostatectomy and radiotherapy to be 42% (95%CI: 20-67, P < 0.01, I2 = 91%), 21% (95%CI: 16-26, P = 0.87, I2 = 0%) and 40% (95%CI: 22-58, P < 0.01, I2 = 90%), respectively. The prevalence of acute and persistent fatigue was 44% (95%CI: 25-64; P < 0.01; I2 = 93%) and 29% (95%CI: 25-32; P = 0.30; I2 = 17%), respectively.

CONCLUSION

Our meta-analysis showed that fatigue is a common symptom in men with PCa, especially those using hormone therapy.

Key Words: Prostate cancer, Fatigue, Prevalence, Meta-analysis, Systematic review

Core Tip: This study was a systematic review conducted to determine the prevalence of cancer-related fatigue in patients with prostate cancer. Compared with other types of cancer, little is known about the prevalence of prostate cancer treatment-related fatigue. In this study, we reviewed the data in 14 papers (4736 patients) and found that the pooled prevalence of cancer treatment-related fatigue was 40%. Interestingly, the prevalence of cancer-related fatigue was associated with the type of treatment that the patients received; those undergoing radical prostatectomy had the lowest prevalence of fatigue.



INTRODUCTION

Prostate cancer (PCa) is the second most common cancer in men after lung cancer, with an estimated 1.28 million newly diagnosed cases worldwide in 2018[1]. Treatment advances have improved PCa-specific survival, with 5-10-year disease-free survival rates in Western countries reported to be 75%-94%[2-5]. Androgen deprivation therapy (ADT), radiotherapy (RT), chemotherapy and surgery [radical prostatectomy (RP)] are the current mainstream treatment options due to their efficacy in reducing prostate-specific disease progression[6]. However, the side effects of PCa treatment are very prominent, and the clinical focus has shifted to controlling or reducing treatment-related side effects[7-10]. Fatigue is the most common treatment-related side effect of PCa, which seriously affects patient quality of life during treatment and for many years later[11-13].

Cancer-related fatigue (CRF) is defined as a sense of tiredness that persists over time, interferes with activities of daily living and is not relieved by adequate rest[14]. The prevalence of CRF is as high as 59%-100%[15]. Cancer patients who have partially completed treatment still feel tired for one or more years after treatment, and this symptom is listed by patients as the one with the longest duration and the most impact on daily life[16,17]. However, the exact statistics on the prevalence of CRF in patients with prostate cancer remain unknown.

Recently, there has been an increased interest in investigating the impacts of fatigue in men with PCa. Although these studies provide useful information, they are characterized by a number of methodologic limitations, such as small sample sizes and limited follow-up periods. Hence, they do not adequately reflect the current prevalence of fatigue in PCa patients. Therefore, we performed a meta-analysis with two main aims. The first aim was to compute a robust estimate of the prevalence of PCa-related fatigue based on high-quality studies with sufficiently large sample sizes. The second aim was to evaluate the effects of different treatment methods and the fatigue assessment times on the prevalence of CRF in patients.

MATERIALS AND METHODS
Literature search

The PRISMA statement guidelines were followed for the calculation and reporting of meta-analysis data[18]. Literature searches were conducted using EMBASE, PubMed, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure, WANFANG DATA, Technology Journal Database and the Chinese Biological Medical Database; the search period was from database inception through July 2020. The following search terms were used: “prostatic neoplasms,” “prostat* neoplasms,” “prostate cancer,” “prostat* cancer,” “prostat* tumor*,” “prostat* tumour*,” “prostat* carcino*,” “fatigue,” “tired*,” “cancer-related fatigue” and “CRF”. The references identified in the relevant publications were also reviewed to identify additional studies.

Inclusion and exclusion criteria

Studies that met the following criteria were included: investigated fatigue in men with prostate cancer, measured the prevalence of prostate CRF using structured questionnaires with established psychometric properties, differentiated fatigue outcomes (incidence) between treatment options or fatigue assessment time; there were no limitations on the language of publication, year of publication or publication status. Reviews, lectures, case reports and articles in which the data were obviously abnormal or missing (and the author could not be contacted) were excluded from the analysis.

Study selection and data extraction

The identified studies were stored in reference management software (EndNote, Clarivate, Philadelphia, PA, United States). Literature screening and data extraction were independently performed by two reviewers. Any disagreements between the reviewers were resolved by discussion with a third reviewer. We extracted the first author’s name, year of publication, study name, country in which the study was conducted, sample size, follow-up period, fatigue assessment scale, study design, fatigue assessment time (clinical fatigue diagnosed during treatment was defined as acute fatigue; fatigue continuing for ≥ 1 year after treatment was defined as persistent fatigue), treatment method and primary outcomes.

Quality assessment and publication bias

Papers that had small sample sizes, did not appropriately justify the questionnaires used, failed to properly control for confounding variables and did not fully explain the statistical methods of analysis were considered to be of low quality; fair- to high-quality papers met some or all of these criteria[19,20]. Publication bias was tested using Egger’s Funnel plots.

Statistical analysis

We used R software (version 4.0.2, R Foundation for Statistical Computing, Vienna, Austria) for all statistical analyses. The combined prevalence and 95% confidence interval (95%CI) of CRF in patients with PCa was calculated. Heterogeneity among the studies was assessed using Q and I2 statistic indices. A significant Q value (P < 0.1) indicated a lack of finding homogeneity among the studies; I2 = 0 indicated that an inconsistency among the results makes no statistical difference (I2 < 50% indicated low inconsistency, I2≥ 50% indicated high inconsistency). If the heterogeneity test results are P > 0.1 and I2 < 50%, the homogeneity of the study was considered to be good, and a fixed-effects model was adopted; otherwise, the random-effects model was adopted. Subgroup analyses were performed based on the treatment modalities used and the fatigue assessment times.

RESULTS
Characteristics of the included studies

A flow chart of the study selection process and exclusion criteria is shown in Figure 1. According to the search criteria, a total of 2594 studies were identified; the total number of patients was 4736. We filtered the results by title, abstract and full text. In the end, 14 studies met the inclusion and exclusion criteria. Among them, three studies were about the incidence of CRF after ADT treatment for prostate cancer, six reported the incidence of CRF after RT treatment, and three reported the incidence of CRF after RP. Six studies reported the incidence of acute fatigue, and five reported the incidence of persistent fatigue. The characteristics of the included studies are shown in Table 1.

Figure 1
Figure 1 Study selection flow diagram (up to July 2020). CBM: Chinese Biological Medical database; CNKI: China National Knowledge Infrastructure; VIP: China Science and Technology Journal database; WF: WANFANG DATA database.
Table 1 Characteristics of included studies.
Ref.
Country
Time of case inclusion
Study design
Sample size
Number of CRF cases
The incidence of CRF, %
Scale
Assessment time
Treatment
Yu and Chen[21]China2015.4-2017.9Cross-sectional17410962.64BFINAADT
Wang et al[22], 2017China2006.12-2016.12Longitudinal1478960.54BFINANA
Ashton et al[11], 2019United Kingdom2016.10-2017.3Cross-sectional621524.19BFIT1RARP/ADT
Baden et al[28], 2020Ireland1995.1-2011.3Cross-sectional287955619.31EORTC QLQ-C30NANA
Feng et al[23], 2017United States2009.9-2013.11Longitudinal341441.17FACT-FT2EBRT
Feng et al[8], 2019United States2009.9-2015.2Longitudinal471634.04FACT-FT2EBRT
Gonzalez et al[10], 2018Spain2014.7-2014.9Longitudinal26519.23FACT-FT1EBRT
Feng et al[7], 2020United States2009.9-2015.11Longitudinal643656.25FACT-FT1/T2ADT + RT/EBRT
Maliski et al[24], 2005United StatesNALongitudinal1472819.04SF-36NANA
Nelson et al[12], 2016United States2008.9-2013.10Case control study1453524.13BFIT1/T2ADT/RP
Saligan et al[25], 2016United States2009.4-2013.12Longitudinal473982.97FACT-FT1EBRT
Storey et al[13], 2012United Kingdom2005.8-2005.11Cross-sectional37721657.29BFIT2RT/ RP
Jones et al[27], 2016CanadaNALongitudinal5299017.01FACT-FNANA
Ozdemir et al[26], 2019Turkey2014.3-2018.9Cross-sectional583153.44FACT-FT1NA
Study quality evaluation

Most studies were of fair[8,10,21-26] or high[7,11-13,27,28] quality. Only three of these studies had an adequate sample size[13,27,28].

Fatigue prevalence

Fourteen studies reported the incidence of fatigue in patients with PCa, with mean ages ranging from 60.0 to 75.3. The pooled CRF prevalence was 40% (95%CI: 29-52), in a total sample of 4736 patients, with a high level of heterogeneity (P < 0.01, I2 = 98%). Therefore, we used a random-effects model (Figure 2).

Figure 2
Figure 2 Forest plot of cancer-related fatigue prevalence in prostate cancer patients. CI: Confidence interval.
Fatigue prevalence by treatment

Three of the included studies reported on CRF after ADT treatment, with mean ages ranging from 67.3 to 73.3. The pooled CRF prevalence was 42% (95%CI: 20-67), in a total sample of 254 patients, with a high level of heterogeneity (P < 0.01, I2 = 91%). Therefore, we used a random-effects model (Figure 3).

Figure 3
Figure 3 Forest plot of the prevalence of cancer-related fatigue in prostate cancer patients treated with androgen deprivation therapy. CI: Confidence interval.

Another three included studies reported on CRF after RP treatment, with mean ages ranging from 63.8 to 67.9. The pooled CRF prevalence was 21% (95%CI: 16–26), in a total sample of 260 patients, with a low level of heterogeneity (P = 0.87, I2 = 0%). Therefore, we used a fixed-effects model (Figure 4).

Figure 4
Figure 4 Forest plot of the prevalence of cancer-related fatigue in prostate cancer patients treated with radical prostatectomy. CI: Confidence interval.

Six studies reported on CRF after RT therapy, with mean ages ranging from 64.1 to 66.0. The pooled CRF prevalence was 40% (95%CI: 22-58) in a total sample of 411 patients, with a high level of heterogeneity (P < 0.01, I2 = 90%). Therefore, we used a random-effects model (Figure 5).

Figure 5
Figure 5 Forest plot of the prevalence of cancer-related fatigue in prostate cancer patients treated with radiation therapy. CI: Confidence interval.
Fatigue prevalence by fatigue assessment time

A total of six included studies reported on acute fatigue. The pooled CRF prevalence was 44% (95%CI: 25-64) in a total sample of 402 patients, with a high level of heterogeneity (P < 0.01, I2 = 93%). Therefore, we used a random-effects model (Figure 6).

Figure 6
Figure 6 Forest plot of acute fatigue prevalence in prostate cancer patients. CI: Confidence interval.

Five included studies reported on persistent fatigue. The pooled CRF prevalence was 29% (95%CI: 25-32), in a total sample of 667 patients, with a high level of heterogeneity (P = 0.30, I2 = 17%). Therefore, a fixed-effects model was used (Figure 7).

Figure 7
Figure 7 Forest plot of persistent fatigue prevalence in prostate cancer patients. CI: Confidence interval.
Publication bias

A funnel plot was created to represent the total prevalence of CRF; the plot showed an asymmetric distribution of the study points. Egger’s test result (P = 0.02617) also suggested the possibility of publication bias. A nonparametric shear complement method was used to estimate the number of missing studies and evaluate the influence of publication bias on the results. The results showed significant differences in the results before and after splicing. The prevalence of CRF, calculated before and after trimming, was 40% (95%CI: 29-52) and 20% (95%CI: 11-31), respectively, suggesting that publication bias had a great influence on the stability of the results (Figure 8).

Figure 8
Figure 8  Egger’s funnel plots for testing publication bias.
Sensitivity analysis

To assess the stability of the results, we performed a sensitivity analysis on the 14 included studies by sequentially excluding individual studies. After arbitrarily excluding one study, the combined conversion rate based on the random-effects model was 40% (95%CI: 29-52), indicating that it had little influence on the combined effect size. Therefore, the results of our meta-analysis are stable and reliable (Figure 9).

Figure 9
Figure 9 Sensitivity analysis of cancer-related fatigue prevalence in prostate cancer patients in all studies. CI: Confidence interval.
DISCUSSION

CRF is a common side effect of PCa treatment that can negatively affect a patient’s daily life, physiology and psychology[29,30]. Previous studies on the fatigue status of PCa patients have shown that the prevalence of CRF is between 17% and 82%, varying broadly due to various associated factors[25,27]. The present meta-analysis estimated the CRF prevalence to be 40% in a sample of 4736 patients, indicating that a sizeable proportion of men with PCa experience severe fatigue.

This review found that fatigue is associated with all common PCa treatment types. Specifically, our results showed that the prevalence of CRF in patients receiving RP (21%) was lower than that in those receiving ADT (42%) or RT (40%), similar to other published results[11,12], suggesting that RP has little impact on fatigue prevalence. This finding is likely due to the fact that patients receiving ADT and RT are older, have more underlying diseases and are in advanced stages of disease. Conversely, RP is mainly suited to patients with localized, significant disease and having > 10 years of life expectancy and those with the ability to perform activities of daily living. The rate of clinical fatigue associated with ADT treatment was similar to that with RT treatment, as both primarily cause fatigue via their hematologic toxicity.

Only one study[7] included in this meta-analysis reported the incidence of CRF in patients treated with a combination of RT and ADT; thus, only a descriptive analysis was performed. The highest incidence of fatigue (68%) occurred in patients receiving a combination of RT and ADT, which may be associated with the combination treatment aggravating the resultant hemotoxicity and peripheral and central nervous system mitochondrial dysfunction caused by either treatment alone.

Men with PCa are more likely than other cancer patients to report persistent fatigue for more than 6 mo after treatment, with a high incidence of functional impairment due to the fatigue[31]. The subgroup analysis results of this study showed that the prevalence of acute and persistent fatigue was 44% and 29%, respectively. After the initiation of RT or ADT, the fatigue severity increases and continues to increase over time[20]. Although there is evidence that fatigue severity returns to baseline levels 6–8 wk after completing treatment[32,33], this was not the case in the study by Feng et al[34]. Rather, they found a subset of patients in their cohort who continued to experience fatigue for a year after RT, long after the treatment-associated hematologic toxicities had resolved. These findings suggest that acute and persistent fatigue may be independent phenomena that are mechanistically different; each may be driven by distinct underlying pathogenic processes[8]. Storey et al[13] suggested that the presence of post-treatment CRF may be more influenced by the patient’s current medical and psychological comorbidities than by the initial type of treatment received. Most evidence suggests that persistent fatigue is associated with depression, anxiety, urinary symptoms, pain and insomnia[8,23]. Furthermore, while effective treatments for persistent fatigue do not currently exist, targeting each of the fatigue-related symptoms may provide relief for patients suffering from this debilitating condition.

The present meta-analysis is characterized by some limitations. First, there was considerable heterogeneity among the primary studies. This might be attributable to differences in the cultures of the patients, the study settings and the variety of tools used to measure the prevalence of fatigue. Second, only one article analyzed the incidence of CRF associated with a combination therapy, precluding a meaningful analysis of the impacts of combination therapy. Third, the distribution of the funnel plot results was asymmetric, indicating possible publication bias, which might affect the accuracy of the results.

In conclusion, our meta-analysis revealed that patients with PCa have a high prevalence of CRF and that significant treatment-related differences in CRF incidence exist; further, there is a high prevalence of persistent fatigue. Similarly, high levels of symptoms have been reported in patients with breast cancer, and many interventions have been developed and tested to treat these symptoms[35,36]. Unfortunately, limited fatigue management research has been conducted in patients with PCa. Reported PCa research indicates that physical activity interventions, such as aerobic exercise and resistance exercise, are beneficial for reducing fatigue[37,38]. Additional behavioral interventions that have been shown to mitigate fatigue in cancer patients, including energy conservation[39], cognitive-behavioral therapy[40] and nutritional therapy[41], deserve further study to determine effective fatigue management strategies for patients with PCa.

CONCLUSION

Fatigue is a common symptom in men with prostate cancer, especially those using hormone therapy.

ARTICLE HIGHLIGHTS
Research background

The side effects of prostate cancer (PCa) treatment are very prominent, with cancer-related fatigue (CRF) being the most common. Fatigue is a distressing symptom that interferes with daily functioning and seriously affects patient quality of life during, and for many years after, treatment. However, the exact statistics on the prevalence of CRF in patients with PCa remain unknown.

Research motivation

Recently, there has been an increased interest in investigating the impacts of fatigue in men with PCa. However, they do not adequately reflect the current prevalence of fatigue in PCa patients.

Research objectives

We performed a meta-analysis with two main aims. The first aim was to compute a robust estimate of the prevalence of PCa-related fatigue based on high-quality studies with sufficiently large sample sizes. The second aim was to evaluate the effects of different treatment methods and the fatigue assessment times on the prevalence of CRF in patients.

Research methods

A systematic search of EMBASE, PubMed, OVID, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure, WANFANG DATA, Technology Journal Database and the Chinese Biological Medical Database was conducted up to July 28, 2020. Included studies measured the incidence of prostate CRF and differentiated fatigue outcomes (incidence) between treatment modalities and fatigue assessment times. In our meta-analysis, both fixed and random-effects models were used to estimate the pooled prevalence of prostate CRF. Publication and sensitivity bias analyses were performed to test the robustness of the associations.

Research results

Fourteen studies, involving 4736 patients, were eligible for the review. The results showed that the pooled prevalence of cancer treatment-related fatigue was 40%. Interestingly, the prevalence of CRF was associated with the type of treatment that the patients received; those undergoing radical prostatectomy had the lowest prevalence of fatigue. Further, there is a high prevalence of persistent fatigue.

Research conclusions

Fatigue is a common symptom in men with prostate cancer, especially those using hormone therapy.

Research perspectives

Our meta-analysis revealed that patients with PCa have a high prevalence of CRF. Unfortunately, limited fatigue management research has been conducted in patients with PCa. Many interventions deserve further study to determine effective fatigue management strategies for patients with PCa.

ACKNOWLEDGEMENTS

We would like to thank Shen XP from the Department of Epidemiology and Biostatistics of School of Public Health of Lanzhou University for providing the help of biostatistics service.

Footnotes

Manuscript source: Unsolicited manuscript

Specialty type: Medicine, research and experimental

Country/Territory of origin: China

Peer-review report’s scientific quality classification

Grade A (Excellent): 0

Grade B (Very good): B

Grade C (Good): 0

Grade D (Fair): 0

Grade E (Poor): 0

P-Reviewer: Scaggiante B S-Editor: Gao CC L-Editor: Filipodia P-Editor: Liu JH

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