Skip to main content
Journal of Cachexia, Sarcopenia and Muscle logoLink to Journal of Cachexia, Sarcopenia and Muscle
. 2021 Oct 5;12(6):2034–2044. doi: 10.1002/jcsm.12806

A randomized, feasibility trial of an exercise and nutrition‐based rehabilitation programme (ENeRgy) in people with cancer

Charlie C Hall 1,2, Richard JE Skipworth 3, Honor Blackwood 1, Duncan Brown 1, Jane Cook 1, Katharina Diernberger 2,4, Elizabeth Dixon 5, Valerie Gibson 1, Catriona Graham 6, Peter Hall 2,4, Erna Haraldsdottir 1,7, Jane Hopkinson 8, Anna Lloyd 1, Matthew Maddocks 9, Lucy Norris 2, Sharon Tuck 4, Marie T Fallon 2, † , Barry JA Laird 1,2, † ,✉
PMCID: PMC8718057  PMID: 34612012

Abstract

Background

Despite rehabilitation being increasingly advocated for people living with incurable cancer, there is limited evidence supporting efficacy or component parts. The progressive decline in function and nutritional in this population would support an approach that targets these factors. This trial aimed to assess the feasibility of an exercise and nutrition based rehabilitation programme in people with incurable cancer.

Methods

We randomized community dwelling adults with incurable cancer to either a personalized exercise and nutrition based programme (experimental arm) or standard care (control arm) for 8 weeks. Endpoints included feasibility, quality of life, physical activity (step count), and body weight. Qualitative and health economic analyses were also included.

Results

Forty‐five patients were recruited (23 experimental arm, 22 control arm). There were 26 men (58%), and the median age was 78 years (IQR 69–84). At baseline, the median BMI was 26 kg/m2 (IQR: 22–29), and median weight loss in the previous 6 months was 5% (IQR: −12% to 0%). Adherence to the experimental arm was >80% in 16/21 (76%) patients. There was no statistically significant difference in the following between trial arms: step count − median % change from baseline to endpoint, per trial arm (experimental −18.5% [IQR: −61 to 65], control 5% [IQR: −32 to 50], P = 0.548); weight − median % change from baseline to endpoint, per trial arm (experimental 1%[IQR: −3 to 3], control −0.5% [IQR: −3 to 1], P = 0.184); overall quality of life − median % change from baseline to endpoint, per trial arm (experimental 0% [IQR: −20 to 19], control 0% [IQR: −23 to 33], P = 0.846). Qualitative findings observed themes of capability, opportunity, and motivation amongst patients in the experimental arm. The mean incremental cost of the experimental arm versus control was £‐319.51 [CI −7593.53 to 6581.91], suggesting the experimental arm was less costly.

Conclusions

An exercise and nutritional rehabilitation intervention is feasible and has potential benefits for people with incurable cancer. A larger trial is now warranted to test the efficacy of this approach.

Keywords: Exercise, Nutrition, Cancer, Rehabilitation

Introduction

Cancer is becoming more common, yet advances in treatment mean that more people are living longer with incurable disease than ever before. 1 Indeed the number of people living with cancer is increasing by approximately 3% every year with life expectancies of several months to years. 2 Further, with population aging, people with incurable cancer are increasingly older, living longer, and have more co‐morbidities.

Langbaum and Smith argue that ‘many people with cancer function fully for years, and it is commonplace for patients with chronic cancer to face the challenge of determining how to optimize their remaining time’. 1 This view is being increasingly acknowledged by learned societies with the European Society of Medical Oncology (ESMO) 3 and American Society of Clinical Oncology (ASCO), 4 supporting rehabilitation as a key component of cancer care. Optimizing overall function has been purported to improve quality of life, tolerability of cancer therapies and reduce patient and caregiver distress. Furthermore, this may have positive benefits on health care resource allocation and use. Although these are laudable achievements there remains a paucity of evidence to directly support the benefits of rehabilitation in patients with incurable cancer and to guide the constituent parts of programmes.

It would seem logical that targeting physical and nutritional deficits should be the cornerstones of any rehabilitation intervention. Together, deterioration in physical function combined with loss of muscle and fat termed ‘cancer cachexia’, result in approximately 50% of cancer deaths, and becomes more prevalent as disease progresses. It has been advocated that to optimally address cachexia, any interventions should be multimodal and comprise nutritional support and exercise advice. 5 , 6 , 7 , 8 However, to date, there is limited evidence to support this.

Therefore, a trial was undertaken to assess the feasibility of an exercise and nutritional rehabilitation programme in people with incurable cancer. Termed the ENeRgy trial, this was a randomized, feasibility trial of an Exercise and Nutrition‐based Rehabilitation programme (ENeRgy) versus standard care in people with cancer.

Methods

Study design and patients

We undertook a randomized, open label, feasibility trial at a specialist palliative care unit in the UK, serving a geographically defined population of approximately one million. Eligible patients met the following criteria: outpatients; age ≥18 years; Karnofsky performance status (KPS) ≥ 60; diagnosis of incurable cancer (defined as metastatic or locally advanced cancer not amenable to curative treatment); not undergoing anti‐cancer therapy (hormonal treatment and/or bisphosphonates were permitted); a clinician predicted survival of >3 months.

Patients undergoing anti‐cancer therapy (hormonal, bisphosphonates permitted), receiving parenteral nutritional support, who had dysphagia or who were co‐enrolled in a clinical trial were excluded. Those who had received any systemic anti‐cancer therapy in the preceding 4 weeks were not eligible.

The trial was conducted as per Good Clinical Practice and the Declaration of Helsinki. The protocol was approved by an ethics committee for human research (ethics reference: 17/WS/0226). All patients provided written informed consent. The authors certify that they comply with the ethical guidelines for authorship and publishing of the Journal of Cachexia, Sarcopenia and Muscle. 9 The trial was registered at ClinicalTrials.gov: NCT03316157. The rationale and trial design have been previously described. 10

Randomization

Patients were randomized centrally in a 1:1 ratio of experimental to control, using a block randomization with random block sizes and stratified for baseline KPS (60–80% or 90–100%).

Procedures

The experimental arm was an exercise and nutrition‐based rehabilitation programme. Following baseline assessments and randomization, patients had an interview with the trial physiotherapist and dietitian. Based on this interview, they were given personalized advice on nutrition and exercise.

The exercise component, developed by the physiotherapist, was a home‐based programme consisting of aerobic and resistance training in divided intervals as per patient choice and capability. The aerobic component totalled 60 min of exercise per week (e.g. walking) at moderate intensity (warm and slightly out of breath—modified Borg scale 3–4 rating). The resistance component focussed on major muscle groups in the upper and lower body, predominantly using body weight exercises including standing press ups, half squats and shoulder thrusts, with sets advised three times per week.

The nutrition component aimed to ensure optimal nutritional intake and consisted of dietitian‐led counselling (personalized for each patient) taking into account dietary preferences. Patients were also supplied with an Oral Nutritional Supplement (ONS—ProSure®—Abbott Laboratories, ILL, USA) and advised to take two per day. Each 220 mL supplement contained 1 g of eicosapentaenoic acid (EPA) and 1.5 kcal/mL. Patients who did not tolerate the ONS due to preference were offered an alternative ONS and oral capsules containing 2 g EPA.

Written information supporting the exercise and nutrition interventions were provided (Supporting Information, Data S3). The dietitian and physiotherapist reviewed adherence to the relevant interventions during weekly clinic attendances by patients. At this time, progress was reviewed and the intervention modified if needed, to support adherence. A patient diary (paper) was used to record the number of minutes of aerobic exercise per day, the number of strength exercises performed per day, and the number of nutritional supplements taken per day, and this was discussed with the patient at their weekly visits.

Patients randomized to the control arm received their usual care which may have included ongoing specialist palliative care follow‐up as per individual patient need. They were entitled to any additional support from allied health professionals if needed. Those in the control arm received weekly telephone calls from the research team to ensure adherence to trial‐related data collection and record any nutritional interventions (dietitian and/or prescribed ONS) and exercise undertaken. These data were collected to assess any contamination of the control group (mimicking any aspect of the trial‐related intervention). Patients in the control arm were offered the trial intervention at the end of their involvement in the trial.

Endpoints

The primary endpoint of the trial was to assess feasibility of the experimental arm (rehabilitation programme). Feasibility was assessed primarily by adherence to the intervention using the prescribed number of exercises/ONS prescribed versus actual undertaken. We recorded adherence by using the prescribed versus actual amounts of exercise and nutritional supplements performed/taken. These data were obtained from patient recorded diaries (of which completion was supported by weekly telephone calls by research staff).

Secondary endpoints assessed other aspects of feasibility using recruitment rate (could we recruit our target sample within an acceptable time frame [18 months]), attrition rate (compared with similar studies in patients with advanced cancer), and contamination of the control arm (use of ONS outside the trial and exercise uptake). The acceptable attrition rate was defined as <44%, and this was informed by previous work in palliative and supportive care trials. 11

The exploratory endpoints examined the following.

Physical function was assessed using a physical activity monitor (Fitbit®, San Francisco, USA). Patients wore this pre‐randomization for 7 days then at the end of the trial for 7 days. We assessed mean daily step count at these time points. We also assessed physical function assessed using the timed up and go (TUG) test, 12 2 min walk test (TMWT), 13 and the Life Space Assessment (LSA) questionnaire. 14 All of these were carried out at baseline (pre‐randomization) and at the trial endpoint.

Performance status was assessed at baseline using Karnofsky performance status criteria. 15 Nutritional status was assessed using the abridged Patient Generated Subjective Global Assessment (abPG‐SGA), 16 body weight, and assessment of nutritional intake using a 10‐point scale (AveS). 17

Quality of life was assessed using the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire – C15PAL (EORTC QLQ‐C15PAL), 18 the EQ‐5DL, and the EQ‐VAS questionnaires. 19

Quality of sleep was assessed using sleep data recorded by the physical activity monitor. Adverse events were also assessed and reported.

Health economic endpoints examined the potential impact on patient‐reported health utility, healthcare‐related resource use and costs. Health utility was assessed by the EQ‐5D‐5L 20 and EQ‐VAS patient completed questionnaire, healthcare utilization, and out of pocket expenses. 19 Questionnaires were designed to measure health‐related utility healthcare‐related resource use and costs, administered at baseline and follow‐up assessment time‐points. Patient health‐related quality of life was captured using a patient reported outcome measure; the EQ‐5D‐5L and EQ‐VAS questionnaires. Utility values were assigned to responses using the standard UK value set. 21 Healthcare utilization and costs were collected using a bespoke patient completed questionnaire, adapted from the UK Cancer Costs Questionnaire [citation: https://blogs.ed.ac.uk/ukcc/].

Unit costs were assigned to resource use items using standard national costing sources such as PSSRU 22 and NHS reference costs, 23 or through consultation with relevant service business managers. Costs were summarized from the perspectives of the NHS, the charitable and 3rd sector and the patient and their carers. Cost‐effectiveness was calculated as the Incremental Cost‐effectiveness Ratio (ICER), expressed as cost per QALY gained.

A within‐trial cost effectiveness analysis was performed in accordance with the methodological specification of the NICE Guide to the Methods for Health Technology Assessment. 24 Uncertainty was evaluated using probabilistic sensitivity analysis (PSA) and value of information (VoI) analysis, implemented using the bootstrap method (1000 replications). For the PSA and for the VoI Analysis, the SAVI Tool from the University of Sheffield was used. 25

Statistical considerations

As the primary endpoint of this study was to assess the feasibility of the trial, rather than superiority of the experimental arm over the control arm, a formal sample size calculation was not necessary. 26 Our justification for the sample size of 40 patients was supported by our previous work, 6 our potential pool of eligible patients (estimated at 1300 per year), consensus in the sample size of feasibility trials, 27 and based on this, we estimated we would be able to express the percentage completing the study protocol to within ±9% assuming a two‐sided 95% confidence interval (CI) around an expected percentage of 90% completion. Findings are presented descriptively split by trial arm and endpoints (e.g. change in daily step count and change in weight) are compared between trial arms using appropriate non‐parametric tests (Mann–Whitney U test). No interim analysis was planned or undertaken. The analysis was performed using data from on all patients recruited. SPSS v23 (Chicago, IL, USA) was used.

Embedded qualitative study

Interviews with a purposive sample of experimental arm patients were audio‐recorded and transcribed verbatim. Coding of all transcribed data, conducted by two researchers blind to the trial results (A. L. and J. H.), was inductive and focused on the questions: ‘What is the experience of ENeRgy?’ and ‘What are the barriers to and facilitators of the physical activity and nutritional components of ENeRgy?’

The analysis used the framework technique, 28 which involves systematic and interconnected stages of sifting and charting coded qualitative data, then mapping patterns in a search for understanding and explanation. The pre‐existing framework, Capability, Opportunity, and Motivation together result in Behaviour (COM‐B) was applied to the coded data. Coded data extracts were categorized (J. H.) as capability, opportunity, or motivation for physical activity or for nutritional intake. Data relevant to understanding the experience of and engagement with ENeRgy but falling outside the COM‐B framework were also captured in a visual representation of the whole data set. Overarching patterns were identified that revealed factors influencing adherence/non‐adherence to ENeRgy.

The trial was sponsored jointly by the University of Edinburgh and NHS Lothian.

Role of the funding source

This trial was funded by a grant from Marie Curie and the Chief Scientist Office (Scotland, UK). The oral nutritional supplement was provided free of charge by Abbott Laboratories. The funders and Abbott Laboratories had no involvement in the design, conduct or analysis of the trial. B. L., C. H., M. F., P. H., K. D., E. W., A. L., J. H., and C. G. had access to raw data. The corresponding author had final responsibility for the decision to submit the manuscript for publication.

Results

From 30 January 2018 to 24 April 2019 (15 months), 45 patients were recruited (23 experimental arm, 22 control arm) (Figure 1). Baseline characteristics are shown in Table 1. The median age was 78 years (IQR: 69–84) and 26 (58%) were male. The most common primary cancer site was gastrointestinal (18 [40%]), and patients had either metastatic (29 [64%]) or loco‐regionally advanced disease (16 [36%]). Twenty‐nine (65%) of patients had a Karnofsky performance score of 60–80. The median BMI at baseline was 26 kg/m2 (IQR: 22–29), and the median weight loss in the previous 6 months was 5% (IQR: 12%–0%) (Figure 2).

Figure 1.

Figure 1

Trial profile.

Table 1.

Patient characteristics

Experimental arm (n = 23) Control arm (n = 22)
n % n %
Age <55 6 26 2 9
/55–65/ /3 /13/ /4 /18/
>65 /14 61 /16 73
Male gender 14 61 12 55
Primary cancer
Gastrointestinal 12 52 6 27
Thoracic 1 4 2 9
Breast 2 9 4 18
Urological/Gyn 4 17 6 27
Myeloma 2 9 3 14
Head and neck 1 4 0 0
Other: (Endocrine) 1 4 1 5
Cancer stage
Loco‐regionally 8 35 8 36
Metastatic 15 65 14 64
Current cancer treatment
Hormonal 5 22 7 32
Bisphosphonate 2 9 2 9
Steroids 6 26 7 32
Performance status
60–80% 15 65 14 64
90–100% 8 35 8 36
Body mass index
<18.5 4 17 2 9
18.5–25 9 39 6 27
25.1–30 7 30 9 41
>30.1 3 13 5 23
Weight change at baseline(<1 month)
Weight gained 4 17 3 14
Loss 0–5% 18 78 14 64
Loss >5% 0 0 5 23
Unknown 1 4 0 0
Weight change at baseline (<6 months)
Weight gained 2 9 2 9
Loss 0–5% 10 43 5 23
Loss >5% 7 30 9 41
Unknown 4 17 6 27

Figure 2.

Figure 2

Trial schematic.

Table 2 details the primary endpoints of feasibility of the experimental arm (rehabilitation programme) assessed by adherence to the prescribed exercises/ONS versus actual undertaken. For the experimental arm, adherence was defined as excellent if this was ≥80%, good if this was 50–79% and poor if this was below 50%. For individual components of the experimental arm, excellent adherence was achieved by at least 16/21 (76%) of patients, and for adherence to all components, this was either good (8 [38%]) or excellent (12 [57%]) patients. Therefore, feasibility in terms of compliance to the experimental interventions was acceptable, and the trial was positive in this regard.

Table 2.

Primary endpoint: adherence to the experimental arm

Adherence to individual intervention components (n = 21) a <50% ≥50–79% ≥80%
n (%) n (%) n (%)
Oral nutritional supplement (n = 21) 1 (5) 4 (19) 16 (76)
Resistance (n = 21) 1 (5) 3 (14) 17 (81)
Aerobic (n = 21) 1 (5) 2 (10) 18 (86)
Adherence to combined intervention components <50% ≥50% ≥80%
Aerobic Resistance 1 (5) 4 (19) 16 (76)
Aerobic ONS 1 (5) 6 (29) 14 (67)
Resistance ONS 1 (5) 7 (33) 13 (62)
Aerobic Resistance ONS 1 (5) 8 (38) 12 (57)
a

Two patients withdrew from the trial post randomization.

Secondary endpoints assessed other aspects of feasibility. The recruitment target was 40 patients over 18 months; however, accrual was better than expected, and 45 patients were recruited over 15 months, and then, recruitment was stopped. Of the 121 people screened, 29 were not eligible and were not assessed further. Of the remaining 92 who were further assessed for participation, 45 (49%) were recruited, 9 (10%) were ineligible, 32 (35%) declined, 1 (1%) was not recruited due to an investigator decision, and 5 (5%) for other reasons. The recruitment rate was 37% (45/121) which was similar to other trials in this patient population. 29 , 30 The main reason for patients not participating was that they declined (32 [35%]).

Of the 45 patients recruited, 29 (64%) completed the trial resulting in an attrition rate of 36% (16/45). The attrition rate was 30% (7/23) and 41% (9/22) in the experimental and control arms respectively. The most common reason for attrition was deteriorating health (four patients—experimental; seven patients—control arm).

Contamination in the control arm was low; one patient in the control arm started an ONS and another increased their pre‐trial ONS use. Patients in the control arm did not have increased exercise based on self‐reported measures and activity data.

Table 3 details the exploratory endpoints examining physical function, weight, and nutrition, assessed as part of the trial. There was no evidence of statistically significant differences in the % difference in daily step count (P = 0.548), timed up and go test (P = 0.767), 2‐min walk test (P = 0.484), and life space assessment (P = 1.00) between the trial arms. Patients in the experimental arm gained a median of 1% (IQR: −3% to 3%) of weight versus those in the control arm who lost a median of 0.48% (IQR: −2.6% to 0.64%), P = 0.184.

Table 3.

Exploratory endpoints examining physical function, weight, and nutrition

Experimental arm Control arm P
N Median (IQR) n Median (IQR)

Daily step count a

Baseline 22 2954 (2168–4143) 22 2294 (591–3821)
Endpoint 16 2898 (1055–5005) 12 2478 (727–3645)
Difference 15 −476 (−1592–1882) 12 6 (−860–335)
Difference % 15 −19 (−61 to 65) 12 5 (−32 to 50) 0.548*
Timed up‐and go test (s) Baseline 23 13 (11–17) 22 16 (11–24)
Midpoint 17 15 (12–18) 15 14 (11–27)
Endpoint 16 14 (12–21.8) 12 15 (12–23)
Difference 16 −0.5 (−3–4) 12 0.5 (−1–2)
Difference % 16 −5 (−18–20) 12 4.5 (−3–12) 0.767*
2 min walk test (m) Baseline 23 114 (76–144) 21 104 (66–122)
Midpoint 17 115 (77–136) 13 107 (52–137)
Endpoint 16 116 (75–138) 10 106 (68–122)
Difference 16 9 (−5–18) 10 2 (−10–12)
Difference % 16 6 (−4–27) 10 2 (−10–15) 0.484*
Life space assessment (max score 120) Baseline 21 53 (32–81) 22 37(31–52)
Midpoint 18 38 (34–60) 16 52 (32–66)
Endpoint 16 50 (35–64) 13 48 (34–58)
Difference 16 0 (−16–11) 13 −2 (−10–5)
Difference % 16 0 (−21–41) 13 −5 (−19–17) 1.00*
Weight Baseline 23 71 (60–79) 22 70.8 (62–86)
Midpoint 17 76 (63–85) 15 68 (61–89)
Endpoint 16 80 (62–88) 13 67(57–87)
Difference 16 1 (−2–2) 13 −3 (−2–0)
Difference % 16 1 (−3–3) 13 −0.5 (−3–1) 0.184*
aPG‐SGA score (0–36) Baseline 23 4 (1–9) 22 6 (2–11)
Midpoint 18 5 (1–16) 15 6 (1–14)
Endpoint 16 8 (1–13) 13 6 (1–10)
Difference 16 1 (−2–5) 13 1 (−3–3)
Difference % 16 27 (−18–300) 13 −42 (−73–117) 0.249*
AveS score (0–10) Baseline 23 8 (5–8) 22 7 (5–8)
Midpoint 18 7 (5–9) 16 8 (6–10)
Endpoint 16 7 (4–10) 13 8 (7–10)
Difference 16 0 (−1–1) 13 0 (−2–2)
Difference % 16 0 (−25–22) 13 0 (−16–31) 0.398*
*

Mann–Whitney U‐test.

a

Full 24 h periods.

Table 4 details the exploratory endpoints examining patient reported outcomes of quality of life measured using the EORTC QLQ‐C15 PAL. With the exception of emotional functioning (P = 0.006), there were no statistically significant differences between the trial arms. There was no difference in carer‐related quality of life (P = 0.5) or any sleep parameters between the trial arms—data not presented).

Table 4.

Exploratory endpoints examining patient reported outcomes of quality of life

Experimental arm Control arm P Experimental arm Control arm P
n Median (IQR) n Median (IQR) n Median (IQR) n Median (IQR)
Overall QoL Baseline 23 66.7 (50–83.3) 22 50 (45.8–70.8) Dyspnoea 23 50 (16.7–66.7) 22 33.3 (16.7–70.8)
Midpoint 18 75.0 (50–83.3) 16 50 (50–66.7) 18 33.3 (29.2–54.2) 16 33.3 (16.7–62.5)
Endpoint 16 66.7 (50–83.3) 13 66.7 (50–66.7) 16 50 (33.3–66.7) 13 33.3 (16.7–41.7)
Difference 16 0.0 (−16.7–12.5) 13 0.0 (−16.7–16.7) 16 8.3 (−16.7–16.7) 13 0.0 (−16.7–16.7)
Difference % 16 0.0 (−20–18.8) 13 0.0 (−22.5–33.3) 0.846 16 10 (−33–100) 13 0.0 (−50–75) 0.589
Physical Baseline 23 88.9 (66.7–100) 22 83.3 (66.7–100) Insomnia 23 33 (0.0–66.7) 22 33.3 (0.0–33.3)
Midpoint 18 88.9 (77.8–100) 16 88.9 (77.8–100) 18 33.3 (0.0–41.7) 16 0 (0.0–33.3)
Endpoint 16 83.3 (66.7–100) 13 88.9 (83.3–100) 16 16.7 (0.0–66.7) 13 0 (0–0)
Difference 16 0.0 (0.0–8.3) 13 0.0 (0.0–11.1) 16 0 (0–0) 13 0 (−16.7–16.7)
Difference % 16 0.0 (0.0–9.4 13 0.0 (0.0–18.3) 0.268 8 0 (−37.5–75) 13 −100 (−100 to‐75) 0.92
Emotional Baseline 23 100 (83.3–100) 22 100 (83.3–100) Appetite 23 0 (0.0–33.3) 22 33.3 (0.0–66.7)
Midpoint 18 100 (95.8–100) 16 100 (66.7–100) 18 16.7 (0.0–66.7) 16 33.3 (0.0–58.3)
Endpoint 16 100 (100–100) 13 83.3 (83.3–100) 16 16.7 (0.0–33.3) 13 0 (0.0–33.3)
Difference 16 0.0 (0.0–16.7) 13 −16.7 (−16.7–0.0) 16 0 (0.0–25) 13 0 (−33–0.0)
Difference % 16 0.0 (0.0–20) 13 −16.7 (−16.7‐)_ 0.006 16 0 (−50–25) 13 −50 (−100–0.0) 0.268
Pain Baseline 23 33.3 (16.7–66.7) 22 33.3 (16.7–54.2) Nausea 23 0 (0.0–33.3) 22 0 (0.0–33.3)
Midpoint 18 33.3 (16.7–70.8) 16 16.7 (0.0–33.3) 18 0 (0.0–66.7) 16 0 (0.0–25)
Endpoint 16 33.3 (16.7–66.7) 13 16.7 (0.0–41.7) 16 0 (0.0–33.3) 13 0 (0.0–33.3)
Difference 16 0.0 (−16.7–0.0) 13 0.0 (−16.7–16.7) 16 0 (0.0–0.0) 13 0 (0.0–0.0)
Difference % 13 0.0 (−58.3–0.0) 13 0.0 (−100–50) 0.714 16 −66 (−100–0.0) 13 0 (−100–0.0) 0.812
Fatigue Baseline 23 50 (16.7–66.7) 22 33.3 (16.7–70.8) Constipation 23 0 (0.0–33.3) 22 33.3 (0.0–66.7)
Midpoint 18 33.3 (29.2–54.2) 16 33.3 (16.7–62.5) 18 16.7 (0.0–33.3) 16 0 (0.0–33.3)
Endpoint 16 50 (33.3–66.7) 13 33.3 (16.7–41.7) 16 0 (0.0–0.0) 13 33.3 (0.0–33.3)
Difference 16 8.3 (−16.7–16.7) 13 0.0 (−16.7–16.7) 16 0 (−25–0.0) 13 0 (−16.7–16.7)
Difference % 16 10 (−33–100) 13 0.0 (−50–75) 0.449 16 −100 (−100–16.7) 13 0.0 (−100–0.0) 0.714

Table 5 details adverse events. There were no SAEs for patients in the trial. There were 39 AEs recorded in total, 20 in the experimental arm (51%), and 19 in the control arm (49%). Of AEs in the experimental arm, nine (45%) were related to the ONS, nine (45%) related to the underlying cancer diagnosis, and two (10%) were due to non‐cancer‐related issues.

Table 5.

Adverse events

AE type Experimental arm (n = 23) Control arm (n = 22)

AE relating to ONS

Description

9

‐ Flatus/gurgling from stoma

‐ Flatulence/stool frequency

‐ Flatulence/gurgling from bowel

‐ Flatulence and abdominal cramps

‐ Flatulence

‐ Nausea ×2

‐ Diarrhoea

‐ Overactive stoma

N/A

AE related to cancer

Description

9

‐ Pressure sore

‐ Chest infection ×2

‐ Sub‐hepatic haematoma

‐ Intrahepatic bleed

‐ Oesophageal bolus obstruction (tablet)

‐ Falls (recurrent)

‐ Admission to hospice‐reduced mobility

‐ Duodenal obstruction

12

‐ Deep vein thrombosis

‐ Hypercalcaemia

‐ Fall ×3

‐ Chest infection ×2

‐ Delirium

‐ Rectal bleeding

‐ Pathological femur fracture

‐ Pressure sore

‐ Dysphagia

AE unrelated to cancer

Description

2

‐ Urinary tract infection

‐ Diarrhoea and vomiting

7

‐ Tooth abscess

‐ Atrial fibrillation ×2

‐ Cardiovascular complication

‐ Diarrhoea

‐ Oral antibiotics for skin wound

‐ Diarrhoea and vomiting

In the control arm, there were 12 cancer‐related AEs (63%) and seven unrelated AEs (37%), relating to pre‐existing medical conditions or not serious enough to constitute an SAE.

Health economic results

Supporting Information, Data S1 contains the full health economic analysis results. In summary, the main drivers of costs were hospital inpatient stays and unscheduled hospice stays followed by community care, outpatient appointments, out of hours (OOH) services, and travel costs. The mean incremental cost of the experimental arm versus control is £‐319.51 [CI −7593.53 to 6581.91], suggesting the experimental arm is less costly. The mean incremental benefit of the experimental arm versus control was 0.00018 QALYs [CI −0.021, 0.023]. Probabilities of the intervention being cost saving and more beneficial compared with the control group were 0.544 and 0.517, respectively.

Qualitative analysis

Fourteen patients in the experimental arm had an end of trial interview. The factors influencing capability, opportunity, and motivation to adhere to ENeRgy with supporting evidence (patient quotes) are reported in the Supporting Information, Data S2.

In summary, to engage with ENeRgy patients had to perceive benefit; improvement in energy levels, increased physical or social activity, improved food intake, weight gain or, for one patient, an expectation of improved survival. For 10 of the patients, ENeRgy was enjoyable and restorative. However, only some of these patients reported improvement in activity, physical strength, oral intake, or weight. Perception of benefit, such as a sense of achievement, knowing what to do, a sense of control, or hope of improvement, could motivate adherence. Family members and carers also influenced ability to and willingness to adhere to ENeRgy. The four patients who did not report benefit ranged from mildly resistant to non‐adherent. These patients revealed that ENeRgy can have an unintended consequence of raising awareness of progressing disease and impending death.

Discussion

Our findings demonstrate that delivering and testing a rehabilitation programme incorporating exercise and nutritional advice/supplementation, delivered in an outpatient setting to people with incurable cancer, is feasible. This trial recruited ahead of schedule and target, with an acceptable attrition rate in the setting of advanced cancer. The trial was not powered to assess the effects on nutritional, functional or quality of life outcomes, but encouraging changes in emotional functioning were observed, echoed by our qualitative findings. Our health economic analyses were also encouraging. There is a strong belief that rehabilitation should be an optional therapy for the management of people living with incurable cancer, yet trials supporting this viewpoint are scarce. The present trial provides a foundation for larger trials to assess the efficacy of such an approach.

There is limited similar research for comparison; however, two studies are notable. Naito and co‐workers completed a single arm trial examining a multimodal intervention (exercise and nutrition) in 30 elderly patients with lung or pancreatic cancer (NEXTAC‐ONE). 30 They demonstrated feasibility, and a randomized phase two trial is underway to further assess this approach. 31 Edbrooke and co‐workers undertook a randomized trial assessing exercise and behavioural change strategies in 92 patients with inoperable lung cancer. 32 No improvement in exercise capacity was observed (primary outcome), but quality of life improved. These trials, along with the present trial, are well aligned with recommendations by ESMO, 3 ASCO, 4 and the UK National Institute for Clinical Excellence (NICE) for the care of people with incurable cancer. However, a rehabilitative approach, integrated into routine care, remains the exception rather than the norm. In the present study, the paradigm and design were informed by our previous work in cancer cachexia where the importance of a multimodal approach including exercise and optimal nutrition is advocated. Cancer cachexia remains the cause of death in approximately half of patients with cancer, and the combination of nutritional and functional deficits acts synergistically with devastating consequences. Previous work has focussed on uni‐modal exercise approaches to rehabilitation with scarce attention to nutritional care scarce. Optimizing nutritional care alongside physical function may serve to optimize rehabilitative potential but also address cachexia as exercise itself has an anti‐inflammatory effect. It is hoped that future work will elucidate this.

A key strength of our trial is the embedded qualitative analysis. Feasibility trials often do not progress to efficacy trials due to a lack of encouraging effects on exploratory endpoints, and as such, interventions may seem ineffective. However, we would argue that in feasibility trials, with modest sample sizes, it is unrealistic to expect a plethora of encouraging exploratory endpoint results. Richards and colleagues argue that ‘Applying mixed methods integration techniques to data or findings from studies involving both RCTs and qualitative research can yield insights that might be useful for understanding variation in outcomes, the mechanism by which interventions have an impact, and identifying ways of tailoring therapy to patient preference and type’, and we agree. 33 The qualitative findings demonstrated the positive impact of the intervention and suggest continuation to a larger trial is worthwhile and will help refine aspects of the trial design. There are limited qualitative studies conducted as part of quantitative clinical trials in cancer rehabilitation; however, Edbrooke and co‐workers are to be commended for assessing the patient experience of their exercise intervention, 34 as part of their clinical trial. 32

The Health Economic Analysis undertaken suggested that the rehabilitation intervention was cost‐saving compared with the control group. We focussed on the costs to the NHS, and community care with some indication of costs to the patients such as travel costs. One potential reason for the cost saving was that the care provided replaced or prevented community healthcare needs. It may have been due to patients having additional attention to their wider symptom control needs (e.g. pain management) or indirect psychological support from the trial team. The Health Economic Analysis is an important part as even if a rehabilitation intervention proves to be efficacious, excess costs may prohibit wide spread integration into health care. Cost‐effectiveness analyses may therefore support widespread integration.

The trial had several limitations including the sample size. This was small however in terms of a feasibility trial it was reasonable; however, any definitive conclusions on efficacy cannot be drawn. Further the sample size was also underpowered for health economic analysis, particularly for estimation of costs and this will need further evaluated in any larger trial. We also acknowledge that the heterogeneous sample (age, tumour type, etc.) is a limitation. It was also difficult to standardize background care to ensure both arms received similar care with the exception of the rehabilitation intervention. This latter point is key, and we cannot rule out that improvements in emotional functioning seen in the intervention arm were as result of contact with trial staff rather than the intervention per se. Such aspects are difficult to disentangle yet represent key considerations in future trial design. We also acknowledge that while the intervention targeted physical function and nutrition, we did not quantify degree of cancer cachexia or incorporate specific measures of body composition (lean mass assessment) or measures of muscle function (e.g. hand grip strength). Rather, we focussed on generic measures of function (physical activity) and quality of life but accept that the former parameters would be of interest. Further, characterizing cachexia stage of participants at enrolment, in future trials, would be of interest.

Conclusion

A rehabilitation intervention targeting exercise and nutrition, in people with incurable cancer, is feasible and has potential benefits in terms of emotional function, motivation, capability attitudes, and costs. The trial was feasible and provides sufficient support for progression to a larger trial to assess efficacy. Such a trial, ENeRgise, is in development and, along with similar trials, will serve to inform rehabilitation interventions in people living with incurable cancer.

Conflict of interest

B.L. has received honoraria and consultancy fees from Helsinn, Artelo and XBiotech. R.S. has received honoraria and consultancy fees from Helsinn and Novartis. M.F. has received honoraria and consultancy fees from Pfizer. C.H., H.B., D.B., J.C., K.D., E.D., V.G., C.G., P.H., E.H., J.H., A.L., M.M., L.W., and S.T. have no conflicts of interest.

Supporting information

Data S1. Cost effectiveness plane.

Table S1: Mean cumulative costs per patient at study end point for NHS, community care and travel.

Table S2: Expected Value of Perfect Information (EVPI) per person.

Table S3: Expected value of perfect parameter information (EVPPI).

Table S4: CRFs Start point‐, Midpoint‐, Endpoint Assessment.

Data S2. Supporting information.

Data S3. Supporting information.

Acknowledgements

The authors would like to thank the following: Southampton Clinical Trials Unit who provided trial oversight, Patient and Public Involvement Representatives—Pamela MacKay and Susan Siegell (Marie Curie Expert Voices); all staff at St Columba's Hospice particularly Tommy Dalgliesh and Gillian Reid (trial volunteers), the Community Palliative Care Team, and Julie Young; Emma Carduff and Anne Finucane (Marie Curie); staff at Marie Curie Hospice Edinburgh. We would like to make a special acknowledgement to Dr Anne C Voss who is a nutritional scientist and provided valuable support throughout the trial. This trial was funded by a grant from Marie Curie and the Chief Scientists Office (Scotland, UK)—MCRGS‐07‐16‐73. Abbott Laboratories provided the oral nutritional supplement (Prosure) used in the trial, free of charge.

Hall C. C., Skipworth R. J. E., Blackwood H., Brown D., Cook J., Diernberger K., Dixon E., Gibson V., Graham C., Hall P., Haraldsdottir E., Hopkinson J., Lloyd A., Maddocks M., Norris L., Tuck S., Fallon M. T., and Laird B. J. A. (2021) A randomized, feasibility trial of an exercise and nutrition‐based rehabilitation programme (ENeRgy) in people with cancer, Journal of Cachexia, Sarcopenia and Muscle, 12, 2034–2044, 10.1002/jcsm.12806

References

  • 1. Langbaum T, Smith TJ. Time to study metastatic‐cancer survivorship. N Engl J Med 2019;380:1300–1302. [DOI] [PubMed] [Google Scholar]
  • 2. Society AC . Cancer treatment and survivorship facts and figures. Atlanta 2019.
  • 3. Jordan K, Aapro M, Kaasa S, Ripamonti CI, Scotte F, Strasser F, et al. European Society for Medical Oncology (ESMO) position paper on supportive and palliative care. Ann Oncol 2018;29:36–43. [DOI] [PubMed] [Google Scholar]
  • 4. Ferrell BR, Temel JS, Temin S, Alesi ER, Balboni TA, Basch EM, et al. Integration of palliative care into standard oncology care: American Society of Clinical Oncology Clinical Practice Guideline update. J Clin Oncol 2017;35:96–112. [DOI] [PubMed] [Google Scholar]
  • 5. Fearon KC. Cancer cachexia: developing multimodal therapy for a multidimensional problem. Eur J Cancer 2008;44:1124–1132. [DOI] [PubMed] [Google Scholar]
  • 6. Solheim TS, Laird BJ, Balstad T, Stene G, Bye A, Johns N, et al. A randomized phase II feasibility trial of a multimodal intervention for the management of cachexia in lung and pancreatic cancer. J Cachexia Sarcopenia Muscle 2017;In Press;8:778–788. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Solheim TS, Laird BJA, Balstad TR, Bye A, Stene G, Baracos V, et al. Cancer cachexia: rationale for the MENAC (Multimodal‐Exercise, Nutrition and Anti‐inflammatory medication for Cachexia) trial. BMJ Support Palliat Care 2018;8:258–265. [DOI] [PubMed] [Google Scholar]
  • 8. Hall CC, Cook J, Maddocks M, Skipworth RJE, Fallon M, Laird BJ. Combined exercise and nutritional rehabilitation in outpatients with incurable cancer: a systematic review. Support Care Cancer 2019;27:2371–2384. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. von Haehling S, Morley JE, Coats AJ, Anker SD. Ethical guidelines for publishing in the Journal of Cachexia, Sarcopenia and Muscle: update 2015. J Cachexia Sarcopenia Muscle 2015;6:315–316. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Hall CC, Norris L, Dixon L, Cook J, Maddocks M, Graham C, et al. A randomised, phase II, unblinded trial of an Exercise and Nutrition‐based Rehabilitation programme (ENeRgy) versus standard care in patients with cancer: feasibility trial protocol. Pilot Feasibility Stud 2018;4:192. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Hui D, Glitza I, Chisholm G, Yennu S, Bruera E. Attrition rates, reasons, and predictive factors in supportive care and palliative oncology clinical trials. Cancer 2013;119:1098–1105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Podsiadlo D, Richardson S. The timed “Up & Go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 1991;39:142–148. [DOI] [PubMed] [Google Scholar]
  • 13. Butland RJ, Pang J, Gross ER, Woodcock AA, Geddes DM. Two‐, six‐, and 12‐minute walking tests in respiratory disease. Br Med J (Clin Res Ed) 1982;284:1607–1608. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Phillips JL, Lam L, Luckett T, Agar M, Currow D. Is the Life Space Assessment applicable to a palliative care population? Its relationship to measures of performance and quality of life. J Pain Symptom Manage 2014;47:1121–1127. [DOI] [PubMed] [Google Scholar]
  • 15. Karnofsky DA, Abelmann WH, Craver LF, Burchendal JH. The use of the nitrogen mustards in the palliative treatment of carcinoma. With particular reference to bronchogenic carcinoma. Cancer 1948;1:634–656. [Google Scholar]
  • 16. Vigano AL, di Tomasso J, Kilgour RD, Trutschnigg B, Lucar E, Morais JA, et al. The abridged patient‐generated subjective global assessment is a useful tool for early detection and characterization of cancer cachexia. J Acad Nutr Diet 2014;114:1088–1098. [DOI] [PubMed] [Google Scholar]
  • 17. Thibault R, Goujon N, Le Gallic E, Clairand R, Sebille V, Vibert J, et al. Use of 10‐point analogue scales to estimate dietary intake: a prospective study in patients nutritionally at‐risk. Clin Nutr 2009;28:134–140. [DOI] [PubMed] [Google Scholar]
  • 18. Groenvold M, Petersen MA, Aaronson NK, Arraras JI, Blazeby JM, Bottomley A, et al. The development of the EORTC QLQ‐C15‐PAL: a shortened questionnaire for cancer patients in palliative care. Eur J Cancer 2006;42:55–64. [DOI] [PubMed] [Google Scholar]
  • 19. Pickard AS, Wilke CT, Lin HW, Lloyd A. Health utilities using the EQ‐5D in studies of cancer. Pharmacoeconomics 2007;25:365–384. [DOI] [PubMed] [Google Scholar]
  • 20. Foundtaion ER . EQ‐5D‐5L User guide. 2019.
  • 21. Bansback N, Brazier J, Tsuchiya A, Anis A. Using a discrete choice experiment to estimate health state utility values. J Health Econ 2012;31:306–318. [DOI] [PubMed] [Google Scholar]
  • 22. Curtis L, Burns A. Unit Costs of Health and Social Care 2019. 2018.
  • 23. NHS . NHS Reference Costs.
  • 24. (NICE) NIfHaCE.
  • 25. Strong M, Oakley JE, Brennan A. Estimating multiparameter partial expected value of perfect information from a probabilistic sensitivity analysis sample: a nonparametric regression approach. Med Decis Making 2014;34:311–326. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Whitehead AL, Julious SA, Cooper CL, Campbell MJ. Estimating the sample size for a pilot randomised trial to minimise the overall trial sample size for the external pilot and main trial for a continuous outcome variable. Stat Methods Med Res 2016;25:1057–1073. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Lancaster GA, Dodd S, Williamson PR. Design and analysis of pilot studies: recommendations for good practice. J Eval Clin Pract 2004;10:307–312. [DOI] [PubMed] [Google Scholar]
  • 28. Gale NK, Heath G, Cameron E, Rashid S, Redwood S. Using the framework method for the analysis of qualitative data in multi‐disciplinary health research. BMC Med Res Methodol 2013;13:117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Fallon M, Hoskin PJ, Colvin LA, Fleetwood‐Walker SM, Adamson D, Byrne A, et al. Randomized double‐blind trial of pregabalin versus placebo in conjunction with palliative radiotherapy for cancer‐induced bone pain. J Clin Oncol 2016;34:550–556. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Naito T, Mitsunaga S, Miura S, Tatematsu N, Inano T, Mouri T, et al. Feasibility of early multimodal interventions for elderly patients with advanced pancreatic and non‐small‐cell lung cancer. J Cachexia Sarcopenia Muscle 2019;10:73–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Miura S, Naito T, Mitsunaga S, Omae K, Mori K, Inano T, et al. A randomized phase II study of nutritional and exercise treatment for elderly patients with advanced non‐small cell lung or pancreatic cancer: the NEXTAC‐TWO study protocol. BMC Cancer 2019;19:528. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Edbrooke L, Aranda S, Granger CL, McDonald CF, Krishnasamy M, Mileshkin L, et al. Multidisciplinary home‐based rehabilitation in inoperable lung cancer: a randomised controlled trial. Thorax 2019;74:787–796. [DOI] [PubMed] [Google Scholar]
  • 33. Richards DA, Bazeley P, Borglin G, Craig P, Emsley R, Frost J, et al. Integrating quantitative and qualitative data and findings when undertaking randomised controlled trials. BMJ Open 2019;9:e032081. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34. Edbrooke L, Denehy L, Granger CL, Kapp S, Aranda S. Home‐based rehabilitation in inoperable non‐small cell lung cancer‐the patient experience. Support Care Cancer 2020;28:99–112. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Data S1. Cost effectiveness plane.

Table S1: Mean cumulative costs per patient at study end point for NHS, community care and travel.

Table S2: Expected Value of Perfect Information (EVPI) per person.

Table S3: Expected value of perfect parameter information (EVPPI).

Table S4: CRFs Start point‐, Midpoint‐, Endpoint Assessment.

Data S2. Supporting information.

Data S3. Supporting information.


Articles from Journal of Cachexia, Sarcopenia and Muscle are provided here courtesy of Wiley

RESOURCES