Long-term effectiveness and cost-effectiveness of high versus low-to-moderate intensity resistance and endurance exercise interventions among cancer survivors

Detailed methods, including sample size calculations, of the REACT study have been reported previously [9, 10]. Briefly, REACT is a multicenter randomized controlled trial (RCT) in cancer patients recruited from nine Dutch hospitals between 2011 and 2013. The Medical Ethics Committee of the VU University Medical Centre approved the study. Patients aged ≥ 18 years with histologically confirmed breast, colon, ovarian, cervix or testis cancer, or lymphomas with no indication of recurrent or progressive disease who had completed (neo-)adjuvant chemotherapy with curative intent were eligible and invited to participate. Exclusion criteria were the following: being unable to perform daily activities; presence of cognitive disorders, severe emotional instability, and diseases that hamper patients’ capacity of carrying out HI exercise; and being unable to read and write Dutch. Written informed consent was obtained from all participants prior to participation.

Following baseline assessments, participants were stratified by cancer type and hospital and randomly assigned to HI exercise, LMI exercise, or WLC using random numbers tables [9]. Shortly after randomization, HI and LMI participants commenced their 12-week exercise program. WLC participants were also randomly allocated to HI or LMI exercise, but started exercising after the 12-week follow-up assessment. Allocation sequence was concealed from the clinical and research staff. Due to the interventions’ nature, participants and physiotherapists were not blinded.

HI and LMI exercise interventions had similar exercise types, durations, and frequencies, but differed in intensity (Table 1). Exercise sessions were given twice per week during 12 weeks and supervised by a trained physiotherapist. Both exercise programs included six resistance exercises targeting large muscle groups (i.e., vertical row, leg press, bench press, pull over, abdominal crunch, and lunge), with a training volume of two sets of ten repetitions [10]. Workload per exercise was defined by an indirect one-repetition maximum (1-RM) measurement. Following a warm-up, the physiotherapist estimated a workload at which the patient was expected to perform four to eight repetitions, taking into consideration age, gender, and height [10]. Furthermore, both programs included two types of endurance interval exercises. During weeks 1–4, patients cycled 2 × 8 min with alternating workloads (defined by the maximum short exercise capacity (MSEC) estimated by the steep ramp test [11]). Patients in the HI exercise group alternated 30 s at 65% of MSEC with 60 s at 30% of MSEC. From the fifth week onwards, the 30 s at 65% of MSEC was alternated with 30 s at 30% of MSEC. The workload for the LMI exercise group alternated between 45 and 30% of MSEC in a similar way. During weeks 5–12, one additional endurance interval session was added substituting one 8-min interval of cycling. This interval session consisted of 3 × 5 min of aerobic exercise at constant workload (defined by the heart rate reserve using the Karvonen formula) [12]. The use of the Karvonen formula allowed patients to perform these aerobic exercises using different ergometers (e.g., cycle ergometer, treadmill). Physiotherapists applied behavioral motivational counseling techniques to overcome possible exercise barriers and to encourage participants to obtain and maintain a physically active lifestyle. At 4, 10, and 18 weeks after intervention completion, three booster sessions (i.e., supervised workout sessions) were provided to motivate participants to maintain their exercise engagements.

Socio-demographic data were collected by self-report. Clinical information was obtained from medical records. Physiotherapists documented session attendance in exercise logs. Outcomes were assessed at baseline, and after 12 and 64 weeks, except for dual energy X-ray absorptiometry (DXA), which was only performed at baseline and 64 weeks. Detailed descriptions of the assessments and their measurement properties are provided elsewhere [10, 13]. Physical tests were performed by an independent assessor.

Cardiorespiratory fitness was measured during a maximal cyclometer exercise test aiming to achieve peak oxygen uptake (peakVO₂, in mL/kg/min) within 8–12 min [14] following a ramp protocol, in which breath-by-breath gas exchange was measured continuously. After each test, peakVO₂ (i.e., highest oxygen consumption values averaged over a 15-s interval within the last 60 s), peak power output (peakW, in watt), and the ventilatory threshold (determined by the oxygen equivalent method [14]) were recorded. Hand-grip strength was assessed using a JAMAR hand-grip dynamometer [15] and the mean score (in kg) of three attempts with the participants’ dominant hand was used for further analyses. Lower body function was assessed using the 30-s chair-stand test [16]. The total number of times participants raised to a full stand in 30 s was reported. Fatigue was assessed using the Multidimensional Fatigue Inventory (MFI) [17], including five subscales: general fatigue, physical fatigue, reduced physical activity, reduced motivation, and mental fatigue.

HRQoL was measured using the European Organisation Research and Treatment of Cancer-Quality of Life questionnaire-Core 30 (EORTC-QLQ-C30) [18] and anxiety and depression by the Hospital Anxiety and Depression Scale (HADS) [19]. Physical activity (PA) was objectively assessed by accelerometers (Actigraph) using vertical accelerations converted into counts/minute. Body mass index (BMI) was calculated from measured body height and weight. Body composition was determined using percentage of total body fat mass (%FM), lean mass (%LM), and lumbar spine (L1–L4) bone mineral density (BMD), measured by DXA with a Hologic Discovery DXA scanner. Quality-adjusted life years (QALYs) were estimated using the EQ-5D-3L [20]. EQ-5D-3L health states were converted into utilities using the Dutch tariff [21]. QALYs were calculated using linear interpolation between measurement points.

Intervention costs were micro-costed [22, 23]. Attendance of exercise and booster sessions were registered, intervention providers’ time investments were valued using their gross hourly salaries (including overhead), and material costs were estimated using invoices. All other cost categories were assessed using 3-monthly questionnaires, with 3-month recall periods. Healthcare costs included costs due to primary and secondary healthcare use, and medication. Dutch standard costs were used to value healthcare use [23]. Medication use was valued using unit prices of the Royal Dutch Society of Pharmacy [24]. Informal care (i.e., care by family/friends) was valued using a shadow price [23]. Absenteeism was assessed using participants’ reports of their number of absence days and, in case of partial absence, their percentage of normal working hours worked. Using the friction cost approach (FCA), absenteeism costs were valued with age- and gender-specific price weights [23, 25]. The FCA assumes that costs are limited to the friction period (i.e., period needed to replace a sick-listed worker = 23 weeks) [23, 25]. Unpaid productivity (e.g., volunteer work) losses were valued using the aforementioned shadow price [23]. Sports costs included expenses on memberships and equipment. All costs were converted to 2012 euros (€) [26].

Differences in outcomes between HI and LMI exercise interventions at longer-term follow-up were assessed using linear mixed model analyses with a two-level structure (i.e., participants were clustered within hospitals). Both interventions were simultaneously regressed on the longer-term value of the outcome, adjusted for the baseline value, age, gender, and timing of intervention (i.e., direct start or WLC). To check whether missing data affected the results, sensitivity analyses were conducted on an imputed dataset for peakVO₂, hand-grip strength, and fatigue (SA1). Missing data were multiple imputed using predictive mean matching, stratified by group allocation [27]. The imputation model was specified according to White et al. [27]. Twenty different datasets were created. Pooled estimates were calculated using Rubin’s rules [27].

To evaluate within-group changes in HI and LMI exercise interventions from short-term to longer-term follow-up, we conducted linear mixed models for repeated measurements (i.e., repeated measurements were clustered within patients, which were clustered within hospitals). This model simultaneously regressed the intervention effect on short term and longer term and included time and the interaction between time and exercise group as determinants and age, gender, and the outcome’s baseline value as covariates.

Cost-effectiveness analyses were performed from the societal perspective using the multiple imputed datasets [27]. Between-group differences were estimated for total and disaggregated costs. Total cost and effect differences were estimated using linear mixed model analyses, adjusted for baseline, age, gender, and intervention timing. Incremental cost-effectiveness ratios (ICERs) were calculated by dividing the adjusted total cost differences by those in effects [6]. Uncertainty around cost differences and ICERs was estimated using bias-corrected (BC) bootstrap intervals (5000 replications, stratified by hospital) [28]. Cost-effectiveness planes [29] and cost-effectiveness acceptability (CEA) curves were constructed [30]. A post hoc analysis was performed applying a healthcare perspective and a sensitivity analysis (SA2) was conducted assuming that all scheduled exercise sessions needed to be paid for, rather than only those attended.

All primary analyses were performed according to intention-to-treat. Costs and effects beyond 1 year were discounted at a rate of 4 and 1.5%, respectively [23]. Effectiveness analyses were performed in SPSS (v22.0) and multiple imputation and cost-effectiveness analyses in STATA (v12.0). P < 0.05 was considered significant.