Exergaming Improves Cardiac Risk Factors in Prostate Cancer Patients: A Single-Blinded Randomized Controlled Trial

Abstract

Purpose:

Androgen deprivation therapy (ADT) may induce unfavorable changes in metabolic outcomes, insulin sensitivity, insulin-like growth factors (IGFs), and in serum levels of adipocyte-derived hormones. In this preplanned randomized ancillary study, we aimed to investigate the ability of exercise to counteract alterations in triglyceride, cholesterol, waist circumference, and insulin caused by ADT in men with locally advanced and metastatic prostate cancer (PCa).

Materials and Methods:

Forty-six PCa patients undergoing treatment were randomized to 12 weeks of 180 minutes of weekly unsupervised home-based exergaming or usual care. Blood glucose, lipids, cholesterol, adiponectin, leptin, insulin sensitivity, and the insulin growth factor axis were measured at baseline, and after 12 and 24 weeks. Biomarkers were analyzed using a linear mixed-effect model of the difference between the groups from baseline to week 24. In addition, blood pressure, body mass index, body weight, and waist circumference were measured at baseline and after 12 weeks/end of intervention and analyzed using adjusted linear regression analysis.

Results:

After 24 weeks, a significant difference was seen between the intervention and usual care groups in plasma triglyceride (diff: 0.5 mmol/L, P = 0.02) and high-density lipoprotein (HDL; diff: 0.2 mmol/L, P = 0.01) favoring the intervention group, whereas IGF-binding protein-3 (diff: 148 μg/L, P = 0.01) favored the usual care group. The remaining outcomes were unaffected.

Conclusion:

Improvement in HDL cholesterol could be used as a primary biomarker in future randomized controlled trials investigating the cardiovascular protecting properties of exergaming.

Introduction

Androgen deprivation therapy (ADT) serves as primary treatment for metastatic prostate cancer (PCa) and as neoadjuvant/adjuvant treatment in intermediate- or high-risk localized disease. The metabolic syndrome (MetS) is a well-known side effect to ADT and is characterized by increased waist circumference along with unfavorable changes in serum cholesterol and triglyceride and increased blood glucose and blood pressure.¹ ADT-related gain in fat mass expressed as increased waist circumference is associated with insulin resistance (IR).² Hyperinsulinemia may increase the hepatic sensitivity to growth hormone, and thereby stimulate insulin-like growth factor-I (IGF-I) generation in the liver.³ Adiponectin is considered to prevent the development of MetS and is associated with a reduced PCa risk and progression.⁴ However, the ADT-induced suppression of testosterone appears to lower plasma adiponectin.⁵ Another adipocyte-derived peptide hormone, leptin, correlates positively with obesity and the presence of MetS,⁶ whereas diet and exercise lead to decreased leptin levels.^7,8

Exercise intervention studies have been conducted to improve metabolic outcomes, adipocyte-derived hormones, and the IGF system in PCa patients on ADT.⁹ However, these studies have reported inconsistent results.¹⁰

The “healthy gaming” exercise concept, known as exergaming, was developed in the 2000s. Exergaming is a low-cost, technology-driven, and easy-to-perform at-home exercise modality offering increased physical activity level, instructions on how to exercise, and goal setting, which are considered cornerstones in helping people to do beneficial exercise.¹¹ To the best of our knowledge, the effect of home-based exergaming on MetS, adipocyte-derived peptide hormones, IR, and the IGF system has not been investigated previously in PCa patients. Thus, to evaluate the metabolic effect of exergaming, we performed a randomized controlled trial investigating the effectiveness of 12 weeks of home-based exercise using the Xbox^® 360 Kinect interactive videogaming system in (1) long-term improvement in blood glucose, lipids, cholesterol, adiponectin, leptin, insulin sensitivity, and the IGF system and (2) blood pressure, body mass index (BMI), body weight, and waist circumference at the end of the 12-week exercise intervention period.

Materials and Methods

Study design and patients

This study was part of a randomized clinical trial investigating the effect of 12 weeks of unsupervised home-based exergaming on ADT-related side effects. Additional study results and study details have been published previously.¹²

The study was performed as a two-arm, randomized controlled trial with an intervention group (n = 23) and a matched usual care group (n = 23). The research team was blinded to the allocation of participants. Eligible participants were PCa patients receiving continuous ADT (GNRH-analogs). Between February 2015 and January 2017, 46 patients were recruited from the urological outpatient clinics at Regional Hospital Holstebro and Regional Hospital Viborg, Denmark. All study procedures were conducted at Regional Hospital Holstebro. The study was registered at Clinical trial.gov, ID: NCT01762241. Approval had been obtained from the Regional Ethical Committee at Central Denmark Region (protocol no. 1-10-72-195-14) and the Danish Data Protection Agency (protocol no. 1-16-02-536-14).

Written informed consent was obtained from all individual participants before inclusion in the study.

Block randomization with 8–10 participants in each block was done on a 1:1 basis to either the intervention group or the usual care group. Under supervision, each participant picked a sealed opaque envelope containing information about the group allocation.

Intervention

After receiving 90 minutes of individual instruction by a physiotherapist, participants exercised unsupervised for 1 hour three times a week for 3 months using the Xbox 360 Kinect system (Microsoft, Redmond, WA). Participants could use the Your Shape Fitness Evolved 2012, the Sport and Adventure games at their own choice. The Fitness game offered combined aerobic and resistances exercises, and thus free weights of 0.5, 1.0, and 2.0 kg were supplied to the participants, who were instructed to use games requiring increased heartbeat. A chief physician reviewed safety issues and bone scans before inclusion. There were no adaptations or restrictions in the exercise protocol with regard to bone metastases. Participants who needed adaptations for other reasons than metastases received exercise advice accordingly.

During the intervention period, participants were contacted by the research assistant every second week to check on adverse events, changes in medication intake, and ensure compliance. There was no contact between the post-intervention tests at week 12 and follow-up blood samples at week 24.

Usual care group

The usual care group continued normal daily activities throughout the study.

During the study, all participants in each group kept a diary of his self-reported exercise.

Outcome measures

The harmonized classification of MetS was used to classify participants as suffering from MetS if three of the following five criteria were present: serum triglyceride ≥1.7 mmol/L, serum high-density lipoprotein (HDL) <1.0 mmol/L, fasting plasma glucose ≥5.6 mmol/L, blood pressure >130/85, and waist circumference ≥94 cm⁻¹.

Data on waist circumference, BMI, body weight, and blood pressure were collected at baseline and week 12 only.

Sixteen milliliters of whole blood was collected in a BD Vacutainer from the antecubital vein after an overnight fast at baseline and week 12 and 24 follow-up to analyze long-term improvement in blood glucose, lipids, cholesterol, adiponectin, leptin, insulin sensitivity, IGF, and IGF binding protein (IGFBP). Triglycerides, HDL cholesterol, low-density lipoprotein (LDL) cholesterol, total cholesterol, and glucose were analyzed at the accredited (ISO 15 189) laboratory of clinical biochemistry at Regional Hospital West, Denmark following standard laboratory procedures.

Adiponectin and leptin were analyzed using validated immunoassays.^13,14 For both assays, the intra- and inter-assay coefficient of variation (CV) averaged 5% and 10%, respectively. Care was taken to analyze all samples from the same individual within the same assay run.

Serum concentrations of IGF-I and IGFBP-3 were measured by a commercial chemiluminescence immunoassay on the IDS-iSYS multidiscipline automated analyzer (Immunodiagnostic Systems Nordic SA, Denmark) as previously described.^15,16 Serum concentrations of IGF-II were determined by an in-house assay after acid-ethanol extraction of IGFBPs as previously described with modifications.¹⁷ IGFBP-1 and IGFBP-2 were determined by in-house assays as previously described,¹⁸ with some modifications.¹⁹ IGF-bioactivity was determined as the ability of serum IGF-I and IGF-II to activate the IGF-I receptor in vitro, using an in-house, cell-based, kinase-receptor activation (KIRA) assay. The KIRA assay was performed as previously described²⁰ with some modifications. The intra- and inter-assay CVs for the in-house immunoassays averaged ∼5% and 10%, respectively. The only exception was the KIRA assays, where the corresponding CVs averaged 12% and 20%. The assays were analyzed at Medical Research Laboratory, Department of Clinical Medicine, Faculty of Health Science, Aarhus University, Denmark.

Insulin was determined using a solid-phase, two-site enzyme immunoassay (Insulin Elisa kit 10/1113/01; Mercodia AB, Uppsala, Sweden).

Insulin sensitivity was assessed using the homeostasis model assessment (HOMA)-IR described by Matthews et al.,²¹ using the validated equation: Fasting Plasma Insulin pmol/L × Fasting Plasma Glucose (mmol/L)/135.²² High HOMA scores denote low insulin sensitivity expressed as IR. A cutoff value of 2.8 was applied in considering subjects having IR.²³

Sample size calculation

In this preplanned randomized ancillary study, the sample size was based on improvement in the primary outcome, the 6-minute walk test. A sample size of 46 participants was based on 30% drop out in each group when showing a 100-m increase after 3 months with a standard deviation (SD) of 84.5 m at the alpha level of 0.05 and 90% power.¹²

Statistical analyses

Statistical analyses were performed using the STATA software (V13; StataCorp LP, College Station, TX). We used the modified intention-to-treat population, consisting of those individuals who completed all measurements at all time points.

The analyses included standard descriptive statistics, using unpaired Student's t-test for normal distributed continuous data, Mann–Whitney for non-normal distributed continuous data, and Fisher's exact test for categorical data.

For waist circumference, BMI, body weight, and blood pressure assessed at baseline and week 12 only, a linear regression analysis was conducted to evaluate differences in effects between the two groups adjusting for the associated baseline value as well as baseline ADT duration (below or above 365 days), BMI, and level of physical activity.

Blood samples were collected at three timepoints (baseline, week 12, and week 24). For these data, we used a linear mixed-effect regression analysis, where the effects represent change from baseline to week 24 for the treatment group compared with change from baseline to week 24 for the usual care group. Samples were collected at week 12 to investigate any trends from end of the exercise intervention to week 24. This analysis was adjusted for the abovementioned covariates as well as cardiovascular disease and diabetes at baseline.

Values are shown as the mean ± SD and 95% confidence interval. A P-value of <0.05 was considered statistically significant.

Results

Adherence to exercise and adverse effects

There was no significant difference between the groups at baseline (Table 1). The CONSORT diagram of recruitment and loss to follow-up through the study has been published previously,¹² showing that in total 91% of the intervention group and 87% of the usual care group completed the study. In the same publication, data from exercise diaries show that the intervention group began exercising according to the protocol, however, the group exercised 153.3 minutes per week and thus did not adhere to the protocolled 180 minutes per week.¹² Only one participant in the exercise group was excluded because of severe nonheart-related chest pain due to surgical clips in thorax. No other study-related adverse events occurred.

Table 1.

Baseline Characteristics of Study Participants

	Intervention group (n = 23)	Usual care group (n = 23)	P
	Mean (SD) n (%) Median (IQR)	Mean (SD) n (%) Median (IQR)	P
Age	67.6 (4.6)	69.8 (4.4)	0.09
Gleason score
Gleason 6	1 (4.35)	3 (13.04)	0.06
Gleason 7	11 (47.83)	5 (21.74)
Gleason 8–10	11 (47.83)	14 (60.87)
Not available	0 (0)	1 (4.35)
T stage
T1c–T2a	6 (26.08)	1 (4.35)	0.12
T2b	5 (21.74)	2 (8.70)
T2c–T3c	12 (52.17)	19 (82.61)
Tx	0 (0)	1 (4.35)
Metastases
Bone metastases	10 (43.48)	6 (26.09)	0.4
Lymph node metastases	2 (8.70)	1 (4.35)
M0, prior radiation therapy+ADT	11 (47.83)	16 (69.57)
ADT <365 days	7 (30.43)	8 (34.78)	1.00
ADT >365 days	16 (69.57)	15 (65.22)	1.00
Cardiovascular disease	16 (69.57)	17 (73.91)	1.00
Diabetes	2 (8.69)	5 (21.74)	0.22
PSA, μg/L	0.1 (0.1–0.3)	0.1 (0.1–0.2)	0.33
Weight, kg	93.2 (11.4)	88.3 (12.1)	0.16
BMI	29.8 (0.6)	29.1 (0.7)	0.43
Alcohol consumption, units/week	8.8 (7.7)	6.9 (5.5)	0.33
Cigarettes/cigars/pipe bowls, number per week	0 (0–70)	3 (0–80)	0.37
Godin questionnaire score	29.3 (29.2)	27.3 (21.8)	0.80

Data for continuous variables are assessed as mean (SD) using independent sample t-test. Non-normal distributed continuous data are assessed as median (IQR) using Mann–Whitney test. Data for categorical variables are presented as frequency (%) using Fisher's exact test. There were no statistically significant differences between groups at baseline (P > 0.05 for all variables). T stage was determined at time of PCa diagnosis. The presence of metastases was determined when ADT was initiated.

ADT, androgen deprivation therapy; IQR, interquartile range; PCa, prostate cancer; SD, standard deviation.

The MetS

During the study, triglyceride increased constantly in the usual care group and discreetly decreased in the intervention group leading to a significant and long-term change in favor of the intervention group (P = 0.02) in the adjusted analysis (Table 2). HDL cholesterol showed a significant change between groups at week 24 in favor of the intervention group (P = 0.01), whereas the adjusted analysis showed no between-group difference in fasting blood glucose (P = 0.84), total cholesterol (P = 0.87), and LDL cholesterol and (P = 0.97) (Table 2).

Table 2.

Biomarkers Throughout the Study Using the Linear Mixed-Effects Regression Analysis

	Baseline		Week 12		Week 24		P
	Intervention group (n = 23), mean (SD)	Usual care group (n = 23), mean (SD)	Intervention group (n = 21), mean (SD)	Usual care group (n = 20), mean (SD)	Intervention group (n = 21), mean (SD)	Usual care group (n = 20), mean (SD)	P
Plasma triglyceride, mmol/L	1.6 (0.87)	1.4 (0.61)	1.4 (0.68)	1.5 (0.74)	1.5 (0.90)	1.8 (1.15)	0.02
Plasma cholesterol, mmol/L	5.1 (1.20)	4.9 (1.02)	5.1 (1.13)	4.8 (1.01)	5.2 (1.22)	5.1 (1.19)	0.87
Plasma HDL, mmol/L	1.3 (0.40)	1.4 (0.35)	1.4 (0.43)	1.3 (0.34)	1.4 (0.47)	1.3 (0.36)	0.01
Plasma LDL cholesterol, mmol/L	3.1 (1.11)	2.9 (0.93)	3.1 (0.97)	2.9 (0.96)	3.2 (1.04)	2.94 (1.10)	0.96
Fasting plasma glucose,^a mmol/L	6.3 (0.96)	6.9 (2.10)	6.3 (0.88)	7.2 (2.67)	6.3 (0.88)	7.2 (2.62)	0.84
Leptin,^b μg/L	26.9 (18.64)	29.0 (17.36)	21.5 (11.6)	22.5 (12.7)	20.4 (11.2)	22.7 (12.38)	0.80
Adiponectin,^b mg/L	10.2 (10.15)	12.2 (7.21)	24.1 (13.51)	19.8 (10.0)	22.0 (12.68)	19.2 (9.95)	0.71
Leptin:adiponectin ratio	3.1 (1.81)	3.2 (2.57)	2.9 (1.90)	2.8 (2.01)	2.8 (1.73)	2.9 (1.89)	0.87

Linear mixed-effects regression analysis controlling for cardiovascular disease, baseline physical activity level, BMI, and ADT >365 days.

Baseline data were missing for one subject in the intervention group.

Week-24 data were missing for one subject in the usual care group.

BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein.

After 12 weeks, waist circumference, body weight, and BMI blood pressure remained unchanged in the intervention group compared with the usual care group (Table 3) and unaffected by the intensification of antihypertensive treatment in three patients during the study. In addition, no statistically improvements were seen in MetS in any of the groups at week 12 (data not shown).

Table 3.

Between-Group Changes in Additional Outcomes Related to the Metabolic Syndrome

	Baseline		Week 12		Adjusted group differences in mean change over 12 weeks
	Intervention group (n = 23), mean (SD)	Usual care group (n = 23), mean (SD)	Intervention group (n = 21), mean (SD)	Usual care group (n = 20), mean (SD)	Mean diff	95% CI	P
Systolic blood pressure, mmHg	160 (21.2)	160.5 (20.7)	160.1 (17.5)	158.1 (19.9)	−1.2	−9.0 to 6.7	0.77
Diastolic blood pressure, mmHg	90.2 (9.1)	92.4 (11.5)	92.7 (10.3)	91.0 (9.3)	1.8	−1.4 to 5.1	0.26
Waist circumference, cm	110 (8.4)	110 (9.6)	109 (9.0)	109 (10.6)	−0.6	−2.4 to 1.1	0.47
Body weight, kg	93.2 (11.4)	88.3 (12.1)	93.4 (11.9)	87.6 (13.0)	0.7	−0.4 to 1.8	0.23
BMI, kg/m²	29.8 (2.9)	29.1 (3.4)	29.8 (3.0)	28.8 (3.7)	0.2	−0.2 to 0.6	0.30

Adjusted for baseline value, physical activity level, BMI, and ADT less than or more than 365 days.

CI, confidence interval.

Tobacco use decreased significantly in the usual care group, from 52 to 5 cigarettes/cigars/pipe bowls per week, when comparing baseline and week 12 (P = 0.00) (Table 1).

Adiponectin and leptin

Leptin, adiponectin, and the leptin-to-adiponectin ratio remained unchanged at week 24 when comparing the groups (Table 2).

The IGF system

IGF-I, bioactive IGF, and IGF-II remained unchanged at week 24 when comparing the groups (P = 0.94, P = 0.38, and P = 0.10) (Table 4). A borderline between-group difference was seen in IGFBP-1 favoring the intervention group (P = 0.07) (Table 4), whereas IGFBP-2 did not show any difference (P = 0.46). IGFBP-3 increased in the usual care group and decreased in the intervention group producing a statistically significant difference in the adjusted analysis (P = 0.01) at week 24.

Table 4.

The Insulin-Like Growth Factor-Axis and Diabetes-Related Outcomes According to the Linear Mixed-Effects Regression Analysis

	Baseline		Week 12		Week 24		P
	Intervention group (n = 23), mean (SD)	Usual care group (n = 23), mean (SD)	Intervention group (n = 21), mean (SD)	Usual care group (n = 20), mean (SD)	Intervention group (n = 21), mean (SD)	Usual care group (n = 20), mean (SD)	P
IGF-I,^a μg/L	134 (44)	156 (62)	138 (43)	153 (61)	136 (37)	153 (37)	0.94
Bioactive IGF,^b μg/L	1.2 (0.8)	1.5 (0.8)	1.3 (0.9)	1.5 (0.6)	1.4 (0.8)	1.4 (0.6)	0.38
IGF-II,^a μg/L	545 (151)	525 (135)	549 (163)	542 (147)	554 (162)	556 (175)	0.10
IGFBP-1,^a μg/L	27 (16)	30 (28)	30 (19)	30 (29)	33 (19)	32 (31)	0.07
IGFBP-2,^a μg/L	233 (147)	179 (91)	234 (143)	181 (109)	240 (161)	166 (113)	0.45
IGFBP-3,^a μg/L	3649 (1028)	3640 (965)	3720 (917)	3674 (893)	3695 (827)	3837 (1016)	0.01
Insulin,^a pmol/L	76.0 (49.0)	73.2 (47.8)	60.8 (35.8)	62.8 (30.3)	57.4 (38.0)	66.7 (46.2)	0.38
HOMA-IR^a,c	3.6 (2.5)	3.9 (2.7)	2.9 (1.8)	3.5 (2.3)	2.7 (1.9)	3.6 (3.0)	0.62

Data were controlled for baseline physical activity level, BMI, ADT duration </> 365 days, and diabetes at time of inclusion.

Data available for 19 subjects in the usual care group at week 24.

Data available for 18 subjects in the usual care group at week 24.

Data available for 22 subjects in the intervention group at baseline.

HOMA-IR, homeostasis model assessment insulin resistance; IGF, insulin-like growth factor; IGFBP, insulin-like growth factor binding protein.

Insulin and insulin sensitivity

In the intervention group, insulin decreased numerically, and insulin sensitivity increased throughout the study. However, these changes were not statistically significant when comparing the two groups in the adjusted analysis at week 24 (P = 0.34 and P = 0.62, respectively) (Table 4).

Discussion

To the best of our knowledge, this is the first study to examine the effect of 12 weeks of unsupervised home-based “off-the-shelf” exergaming on metabolic parameters, adipocyte-derived peptide hormones, IR, insulin growth factors, and their binding proteins in PCa patients. Our main finding was that the exergaming intervention significantly increased HDL cholesterol and improved triglyceride when comparing the groups after 24 weeks. In a small study, exergaming was shown to significantly decrease triglyceride, cholesterol, and LDL in women with no sports experience. Furthermore, these women were not cancer patients in antihormonal treatment, which could explain the positive effect of exergaming.²⁴

Studies investigating the effect of exercise on the IGF axis demonstrate a significant heterogeneity and inconsistency,^25,26 and the significant increase in IGFBP-3 in the usual care group could be associated with a significant decrease in tobacco use as smoking has shown to reduce IGFBP-3 levels in men.²⁷

The unchanged findings in the adipocyte-derived peptide hormones, the MetS, and IR could be related to unchanged waist circumference and body weight as these variables have been associated with fat mass.^28,29 Finally, unsupervised home-based exergaming proved safe in this study population, of which some suffered from bone metastatic and cardiovascular disease.

Previous exercise studies in PCa patients receiving ADT have failed to demonstrate any effect of exercise on triglyceride,^9,30,31 which calls for studies with a combined exercise and dietary intervention. Data on dietary patterns were not collected in the present study, and there was no dietary intervention, which might have produced more significant results.

Based on earlier studies, the exergaming-induced improvement in HDL cholesterol observed in the present study corresponds to what can be obtained by a weekly energy expenditure of between 1200 and 2200 kilo calories or by performing 15–20 miles per week of brisk walking or jogging.³² Thus, our findings may be biologically and clinically relevant based on previous findings as it has been shown that a 2%–3% decrease in coronary disease risk appears for each 0.03 mmol/L increase in HDL cholesterol.³³ In the current study, HDL cholesterol increased by 0.1 mmol/L, implying that the intervention group obtained a decrease in coronary disease risk, ranging from 7% to 11% when compared with the usual care group. Thus, HDL cholesterol is a particularly interesting target in the rehabilitation of cancer patients.

In this study, we only enrolled PCa patients on GNRH-analogs. Thus, future studies could benefit from investigating the effect of unsupervised home-based exergaming in patients undergoing medical castration or orchiectomy due to the potentially different risk of cardiovascular disease induced by these two treatment modalities.

This study had several limitations. Being a preplanned randomized ancillary study, the sample size was not based on the specific outcomes investigated here, and thus, there is a risk that the findings could represent a type II error. Furthermore, the use of the three different games Fitness, Sport, and Adventure was left to the participants, thus producing a heterogeneous exercise intervention with a diverse effect on the outcome measures. In future studies, a more stringent use of games must be applied to secure a similar effect on different muscle groups.

Sleep duration and disturbance were not monitored although linked to ADT, and therefore, these factors could have influenced the components of MetS. Similar to other exercise-based studies,⁹ glycated hemoglobin (HbA1c) was not measured. For future trials, this outcome could be relevant to investigate as combined aerobic and resistance exercises are reported to improve HbA1c in patients with type 2 diabetes.⁷

Data on blood pressure, BMI, body weight, and waist circumference were not collected at week 24, which might have provided additional information regarding the long-term effect of the 12-week exercise intervention on MetS.

Conclusion

To the best of our knowledge, this is the first randomized controlled trial investigating effects of unsupervised home-based exergaming on metabolic parameters, IR, adipocyte-derived proteins, and the IGF system in PCa patients undergoing ADT. The intervention group showed a significant and clinically relevant improvement in HDL cholesterol. This increase is of special interest as this type of cholesterol is a major risk factor for the development of coronary heart disease as well as disease relapse in cancer patients. Being an easily accessible and beneficial exercise modality, home-based exergaming can be an alternative rehabilitation modality in a large variety of patient groups at risk of developing coronary heart disease as well as relapse of cancer.

Body fat has been associated with more of the outcomes in this study, and as we did not see any changes in these outcomes and body weight, more studies are warranted to investigate the dosage and intensity of exergaming.

Exergaming is a new technology-driven exercise concept in rehabilitation, equaling the energy expenditure of brisk walking or jogging. In this study, we proved exergaming to be safe in PCa patients with bone metastatic and cardiovascular disease. The effectiveness of this intervention is now ready to be investigated in larger patient populations at an increased risk of cardiovascular disease and cancer relapse.

Footnotes

Acknowledgments

The authors would like to thank the managers at Regional Hospital Holstebro, the staff at Regional Hospital Holstebro and Regional Hospital Viborg as well as biostatistician René dePont Christensen for their extensive support. The authors would also like to thank Sportsmaster, Elgiganten, and Gamestop Holstebro, for delivering equipment at a reduced price, and The Lundbeck Foundation Centre for Fast-track Hip and Knee Replacement for lending us the leg extensor power rig. Mölnlycke Health Care ApS for sponsor of visual analog scales.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

The authors would like to thank managers at Regional Hospital Holstebro, Fru Agnes Niebuhr Andersons Cancer Research Foundation, Family Hede-Nielsen foundation, European Association of Urology Nurses in cooperation with Ferring Pharmaceuticals and The Family Kjærsgaard, Sunds Foundation for financial support.

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