Published online Jul 26, 2021. doi: 10.12998/wjcc.v9.i21.5932
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
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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.
To determine the prevalence of CRF in patients with PCa.
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.
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.
Our meta-analysis showed that fatigue is a common symptom in men with PCa, especially those using hormone therapy.
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.
- Citation: Luo YH, Yang YW, Wu CF, Wang C, Li WJ, Zhang HC. Fatigue prevalence in men treated for prostate cancer: A systematic review and meta-analysis. World J Clin Cases 2021; 9(21): 5932-5942
- URL: https://www.wjgnet.com/2307-8960/full/v9/i21/5932.htm
- DOI: https://dx.doi.org/10.12998/wjcc.v9.i21.5932
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.
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.
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.
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.
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.
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.
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.
| 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] | China | 2015.4-2017.9 | Cross-sectional | 174 | 109 | 62.64 | BFI | NA | ADT |
| Wang et al[22], 2017 | China | 2006.12-2016.12 | Longitudinal | 147 | 89 | 60.54 | BFI | NA | NA |
| Ashton et al[11], 2019 | United Kingdom | 2016.10-2017.3 | Cross-sectional | 62 | 15 | 24.19 | BFI | T1 | RARP/ADT |
| Baden et al[28], 2020 | Ireland | 1995.1-2011.3 | Cross-sectional | 2879 | 556 | 19.31 | EORTC QLQ-C30 | NA | NA |
| Feng et al[23], 2017 | United States | 2009.9-2013.11 | Longitudinal | 34 | 14 | 41.17 | FACT-F | T2 | EBRT |
| Feng et al[8], 2019 | United States | 2009.9-2015.2 | Longitudinal | 47 | 16 | 34.04 | FACT-F | T2 | EBRT |
| Gonzalez et al[10], 2018 | Spain | 2014.7-2014.9 | Longitudinal | 26 | 5 | 19.23 | FACT-F | T1 | EBRT |
| Feng et al[7], 2020 | United States | 2009.9-2015.11 | Longitudinal | 64 | 36 | 56.25 | FACT-F | T1/T2 | ADT + RT/EBRT |
| Maliski et al[24], 2005 | United States | NA | Longitudinal | 147 | 28 | 19.04 | SF-36 | NA | NA |
| Nelson et al[12], 2016 | United States | 2008.9-2013.10 | Case control study | 145 | 35 | 24.13 | BFI | T1/T2 | ADT/RP |
| Saligan et al[25], 2016 | United States | 2009.4-2013.12 | Longitudinal | 47 | 39 | 82.97 | FACT-F | T1 | EBRT |
| Storey et al[13], 2012 | United Kingdom | 2005.8-2005.11 | Cross-sectional | 377 | 216 | 57.29 | BFI | T2 | RT/ RP |
| Jones et al[27], 2016 | Canada | NA | Longitudinal | 529 | 90 | 17.01 | FACT-F | NA | NA |
| Ozdemir et al[26], 2019 | Turkey | 2014.3-2018.9 | Cross-sectional | 58 | 31 | 53.44 | FACT-F | T1 | NA |
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].
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).
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).
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).
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).
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).
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).
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).
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).
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.
Fatigue is a common symptom in men with prostate cancer, especially those using hormone therapy.
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.
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.
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.
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.
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.
Fatigue is a common symptom in men with prostate cancer, especially those using hormone therapy.
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.
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.
Manuscript source: Unsolicited manuscript
Specialty type: Medicine, research and experimental
Country/Territory of origin: China
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P-Reviewer: Scaggiante B S-Editor: Gao CC L-Editor: Filipodia P-Editor: Liu JH
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