Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

Factors influencing participation in a randomized controlled resistance exercise intervention study in breast cancer patients during radiotherapy

BMC Cancer volume 15, Article number: 186 (2015) Cite this article

Abstract

Background

Over the past years knowledge about benefits of physical activity after cancer is evolving from randomized exercise intervention trials. However, it has been argued that results may be biased by selective participation. Therefore, we investigated factors influencing participation in a randomized exercise intervention trial for breast cancer patients.

Methods

Non-metastatic breast cancer patients were systematically screened for a randomized exercise intervention trial on cancer-related fatigue. Participants and nonparticipants were compared concerning sociodemographic characteristics (age, marital status, living status, travel time to the training facility), clinical data (body-mass-index, tumor stage, tumor size and lymph node status, comorbidities, chemotherapy), fatigue, and physical activity. Reasons for participation or declination were recorded.

Results

117 patients (52 participants, 65 nonparticipants) were evaluable for analysis. Multiple regression analyses revealed significantly higher odds to decline participation among patients with longer travel time (p = 0.0012), living alone (p = 0.039), with more comorbidities (0.031), previous chemotherapy (p = 0.0066), of age ≥ 70 years (p = 0.025), or being free of fatigue (p = 0.0007). No associations were found with BMI or physical activity. By far the most frequently reported reason for declination of participation was too long commuting time to the training facility.

Conclusions

Willingness of breast cancer patients to participate in a randomized exercise intervention study differed by sociodemographic factors and health status. Neither current physical activity level nor BMI appeared to be selective for participation. Reduction of personal inconveniences and time effort, e.g. by decentralized training facilities or flexible training schedules, seem most promising for enhancing participation in exercise intervention trials.

Trial registration

Registered at ClinicalTrials.gov: NCT01468766 (October 2011).

Background

In recent years an increasing number of studies have been published, evaluating the role of physical activity during or after cancer treatment. It has been shown that structured exercise training can reduce adverse effects in cancer patients like cancer-related fatigue (CRF) [1-3], improve quality of life [4] and positively impact cardiorespiratory fitness [5]. Most of the findings are based on clinical studies with small numbers of subjects or patients, and there is an ongoing debate whether those patients willing to be randomized to a demanding exercise program might be highly selective [6,7]. Clinical trials are essential for research and randomized controlled studies are considered the gold standard to evaluate new therapies and determine efficacy or effectiveness of interventions [8]. However, only 3-5% of all cancer patients in Great Britain and the US are included in randomized controlled studies [9]. These low rates result from strict study protocols together with patient- and physician related factors, e.g. time constraints or influence on the relationship between physician and patient. Moreover, it has been shown that the process of recruitment itself is very selective and often threatens the generalizability [10]. Data from clinical cancer trials (mostly drug studies) suggest that age [11,12], tumor stage [13,14], lymph node involvement [12], comorbidities [12], and travel distance [15,16] play an important role in the acceptance or non-acceptance in study participation. De Jong et al. [17] determined differences between participants and nonparticipants of an exercise trial for patients with rheumatoid arthritis. They concluded that nonparticipants were older, mainly males, suffered for a longer duration from their disease and had a lower level of education. To our knowledge, the determinants of participation of cancer patients in exercise intervention trials have not yet been systematically investigated in this extent. It is important to explore these determinants to improve participation rates in further trials.

Therefore aim of the present study was to investigate factors that explain participation and nonparticipation in an exercise intervention trial for breast cancer patients undergoing adjuvant radiotherapy. This study focuses on demographic, personal and clinical factors associated with participation, as well as patient motivation.

Methods

Study design

The present BEST-Participation-study was carried out from July 2011 to December 2011 during the patient screening for the BEST-study. The BEST-study (in German: Bewegung und Entspannung für Brustkrebspatientinnen unter Strahlentherapie, translation: exercise and relaxation for breast cancer patients during radiotherapy) is a prospective, randomized, controlled intervention trial for non-metastatic breast cancer patients undergoing adjuvant radiotherapy. The BEST-study compared a 12-week resistance intervention program during and after radiotherapy with relaxation training in regard to cancer-related fatigue perception [18,19]. The BEST-Participation-study was an observational study embedded in the BEST-study, collecting information on factors potentially influencing willingness to participate in a randomized exercise-intervention trial. The aims of the present analysis were (1) to determine clinical and sociodemographic characteristics of participants and nonparticipants, and (2) to identify reasons for participation or declination. Patients, who signed informed consent for the BEST trial automatically took part in the BEST-Participation-study and are referred to as participants throughout this manuscript. Patients, who refused participation in the BEST-study but agreed to fill out the short questionnaire for the BEST-Participation-study, are referred to as nonparticipants.

Protocols of the BEST- and of the BEST-Participation-study were approved by the Ethic Committee of the University of Heidelberg and have been performed in accordance with the ethical standards of the Declaration of Helsinki. The BEST-study is registered at ClinicalTrials.gov (NCT01468766).

Study population

All participants were treated at the National Center for Tumor Diseases Heidelberg (NCT) in cooperation with the Department of Radiooncology of the University Medical Centre in Heidelberg. Inclusion criteria were: female breast cancer patients with UICC stage I-III, indication for adjuvant radiotherapy, age ≥ 18 years, BMI ≥ 18 kg/m2, written informed consent, ability to follow instructions. Exclusion criteria were: acute infection, problems with walking or standing, severe neurological dysfunction, severe cardiovascular disease, severe pulmonary insufficiency, severe renal insufficiency, other malignancies (except carcinoma in situ of skin or cervix), abuse of alcohol or drugs, regular participation in resistance or endurance training. Breast cancer patients were recruited by a physician who was responsible for the assessment of inclusion and exclusion criteria. Both nonparticipants and participants had to fulfill these BEST-inclusion criteria.

Study recruitment

Eligible patients were briefly informed about the exercise trial at their first consultation for radiotherapy at the outpatient clinic of the Department of Radiooncology of the NCT. Interested patients were handed out an information sheet. They were called a few days later to get more comprehensive information.

Upon informed consent women were included in the BEST-study as well as in the BEST-Participation-study. As participants they had to fill out relevant questionnaires (see below) at their baseline visit for the study entry.

Patients refusing participation were asked whether they would be willing to provide some reasons for their declination and to complete a brief questionnaire either immediately in the outpatient clinic or at home, returned by mail. Written informed consent was obtained from both, BEST participants and nonparticipants. For the recruitment flow see Figure 1.

Figure 1
figure 1

Recruitment flow.

Full size image

Data collection

Clinical data, including tumor size, lymph node status, tumor stage, comorbidities, chemotherapy (yes/no), age, BMI, were collected from the clinical information system. Additional information, such as sociodemographic data, fatigue, physical activity and motivational aspects for exercise, was assessed by self-administered questionnaires. Patients were asked to specify marital status (married/living with partner, separated, divorced, widowed, single, not specified), living status (alone, with others) and travel distance (up to 30 min, between 30 min and 1 h, more than 1 h) to the training center. For a baseline assessment of physical activity reflecting the last week prior to inclusion we used the short version of the Freiburg questionnaire of physical activity (FFKA) [20], a standardized and validated instrument. FFKA focuses on everyday activity with low to medium exertion in addition to exercise activities. With 8 questions basal, recreational and sportive activities are assessed. Cancer-related fatigue, the primary endpoint of the BEST-study, was measured by the multidimensional, 20-item Fatigue Assessment Questionnaire (FAQ) [21]. FAQ is a standardized and validated questionnaire for self-assessment of the physical, cognitive and affective dimensions of fatigue. In addition, using a visual analogue scale (0 = not tired at all, 10 = totally exhausted), patients were asked to rate the intensity of current fatigue. Besides the continuous fatigue scores (total physical, cognitive and affective fatigue) we also investigated a dichotomous variable using as cutpoint the mean fatigue score of women age ≥ 60 years from the general German population (FAQ point value for women aged 14–39 years: 11,2; aged 40–59 years: 12,1; aged ≥ 60 years) [22].To assess the motivation of patients to participate in the BEST-study they could choose among 7 answers, in addition to provide their own free text. Nonparticipants had the choice between 15 answers and free text to explain why they decided against study participation. Multiple answers were allowed.

If the questionnaires were not returned, patients were reminded at least three times by phone. All questionnaires and clinical information had to be completed prior to the first radiotherapy.

Statistical analysis

Characteristics of participants and nonparticipants were compared using Student’s t-test (metric data), Mann–Whitney-U-test (ordinal data), or Chi2-test (categorical data). To assess the associations between the characteristics and nonparticipation, we performed multiple logistic regression analyses assessing following covariates simultaneously in the model: age group, number of comorbidities, marital status, living status, travel distance, BMI, previous chemotherapy, and fatigue. Due to high collinearity tumor characteristics were investigated in separate models without chemotherapy. The different physical activity variables were also included in the models, but none showed a significant association with nonparticipation. Additional sensitivity analyses were performed using smaller sets of covariates to check for overfitting or spurious effects by related variables, but there were no substantial changes in the results. Reasons for participation or declination were analyzed descriptively. P-values below 0.05 were considered as statistically significant. All analyses were performed using PASW Statistics 19.0 or SAS 9.2 [SAS Institute Inc., Cary, USA].

Results

From July to December 2011 a total of 398 patients with non-metastatic breast cancer were irradiated at the study clinic. In this period 52 participants and 69 nonparticipants were recruited (Figure 1). Due to missing data from 4 nonparticipants the sample was restricted to 65 evaluable nonparticipants. The remaining 277 patients were either not eligible, received no information from the recruiting physicians or were not interested in any study participation. Thus, information for this BEST-Participation-study was available for 30.4% of all breast cancer patients with adjuvant radiotherapy during the study period.

Characteristics of participants and non-participants

Sociodemographic characteristics are presented in Table 1. The mean age did not differ statistically significantly between participants and nonparticipants (p = 0.64). However, participants were more likely to be middle aged (age 40–70 years) whereas nonparticipants were more likely to be younger or older (<40 years, ≥ 70 years) (p = 0.02). Significant differences were also noted for living status (p = 0.009) and travel distance (p = 0.02). Here, the nonparticipants more commonly reported living alone and had to spend more time to travel from their home to the treatment center. There were no significant differences with respect to marital status (p = 0.18).

Table 1 Sociodemographic and clinical characteristics of participants and nonparticipants
Full size table

Tumor size (p = 0.047), nodal status (p = 0.036) and tumor stage (p = 0.043) were indicative for a locally more advanced disease among nonparticipants. The number of comorbidities tended to be higher in nonparticipants (p = 0.066). Prior treatment with chemotherapy was somewhat more frequently reported by nonparticipants (p = 0.09). No difference between both groups was observed for BMI (p = 0.14).

Participants and nonparticipants had comparable current physical activity levels (p > .99) (see Table 2). Only 34.6% of the participants and 33.8% of the nonparticipants were classified as “sufficiently active” according to the criteria of Frey and Berg [23] (total score in the FFKA of 30 or a score of 14 in sportive activities) prior to starting radiotherapy. Compared to a healthy reference group [20] our entire study population was comparably active in day-to-day and recreational activities, but less so with respect to exercise activities.

Table 2 Physical activity levels of participants and nonparticipants (BEST-study) according to the short version of the FFKA
Full size table

Neither total fatigue levels (p = 0.25) nor levels for the subcategories physical, cognitive, and affective fatigue or sleep problems differed significantly between the groups (see Table 3). There was also no significant difference between participants and nonparticipants with regard to their fatigue levels the year before diagnosis, at the days after surgery, or during chemotherapy (if applicable). However, among nonparticipants significantly (p = 0.01) more women were currently free of fatigue (i.e. with levels below the mean fatigue level of the general reference population) than among participants.

Table 3 Fatigue levels of participants and nonparticipants (BEST-study) according to FAQ
Full size table

Multiple logistic regression analyses (see Table 4) showed significantly higher odds for nonparticipation among patients with higher age, higher number of comorbidities, those living alone, having longer travel distances, having received a chemotherapy, or those not feeling fatigued. Divorced or separated women had lower odds to refuse participation. BMI and physical activity were not associated with participation.

Table 4 Multiple logistic regression model assessing the odds for nonparticipation
Full size table

Due to high collinearity, the variables tumor stage, tumor size, and chemotherapy were not included jointly in a model. Similar results were observed in the models with either tumor stage or tumor size instead of chemotherapy, with OR = 3.3 (1.2 – 9.3) for higher stage vs. lower stage, and OR = 4.6 (1.4 – 15.1) for tumor sizes T2/3 vs. T1/Tis (data not shown).

Reasons for participation or non-participation

When asked for their reasons for acceptance or declination of the study the five most frequently stated motivational aspects of BEST participants were: “I hope to reduce fatigue and improve quality of life” (65.4%), “I want to contribute to scientific progress” (65.4%), “I hope for positive effects on my cancer prognosis” (59.6%), “I want to cope with cancer” (59.6%), “I hope for better fitness and health” (57.7%) (see Table 5). Nonparticipants most often named “Journey too far/difficulties to reach training center” (70.8%) as reason for their declination. “Time conflicts” (23.1%) and “Twice a week training is too much” (13.8%) were followed by “Health problems” and “I do not want to participate in relaxation” (both 12.3%) (see Table 6).

Table 5 Motivations for study participation reported by participants of the BEST-study
Full size table
Table 6 Reasons for declination of study participation given by nonparticipants of the BEST-study
Full size table

Discussion

The present study showed that willingness of breast cancer patients to participate in a randomized exercise intervention study was significantly influenced by age distribution, comorbidities, living status, travel time to the training center, cancer characteristics or treatment, and fatigue. No associations were observed with BMI and extent of current physical activity.

Patient’s well-being often is negatively influenced by cancer itself as well as by common cancer therapies. Intervention studies have revealed the importance of physical activity as an effective method in supportive therapy [1,2,4,5].

In literature, generalizability of results from clinical trials to the overall patient population has been questioned [12,14,24]. Discrepancies between willingness in general expressed by healthy persons to participate in a clinical cancer trial versus actual participation rates in patient populations have been addressed in the study from Comis et al. 2003: In a survey healthy Americans were asked about their willingness to participate in a clinical cancer trial if they were faced with cancer diagnosis. 31% indicated to be “very willing”, 51% “somewhat willing”, 9% “not very willing” and 6% “not willing at all” [25]. This is in clear contrast to the finding that only 3 to 5% of all cancer patients in Great Britain and the US participate in clinical trials [9]. Reasons may be that no appropriate study was open, patients were not informed about ongoing studies or were ineligible, or patients were not willing to participate. In the BEST-study 13.1% of the target population could be enrolled during the recruitment period (from July to December 2011). In consequence it is assumed that participation in intervention studies is highly selective.

In the present study, travel distance was a major factor reducing study participation: Participation in the intervention trial required the acceptance to travel twice a week to the treatment center and to spend extra time for the training. The present study shows that patients who needed significantly less time to reach the training centre were more likely to agree. Furthermore, 70.8% of the nonparticipants named “journey too far/difficulties to reach training centre” as an important reason for refusing to participate. Long travel distances and limited transportation capabilities are held responsible for less utilization of cancer treatment [26]. In line, studies from gynecological cancer types reported that travel distance and study participation are reciprocally related to each other [15].

Participants of the BEST-study represented the age group between 40 to 69 years very well. However, patients aged younger than 40 years or older than 69 years only accounted for 7.7% of the trial participants whereas 32.2% of the nonparticipants were classified in these groups. Higher age was even significantly associated with nonparticipation when adjusting for other factors such as comorbidities. Our results strengthen previous studies observing that especially older patients are underrepresented in clinical trials, although they comprise about one third of newly diagnosed breast cancer patients [12,27,28]. A detailed explanation for the selected representation of younger patients cannot be determined due to the small size of this age group.

In the BEST-Participation-study among nonparticipants a larger proportion reported living alone. Participants tended to be more often married, while widowed or single women were more frequent among nonparticipants, but differences were not statistically significant. Our data suggest that social and perhaps logistical support is an important component when considering participation in a rather time-consuming clinical exercise trial. These data are in line with Elting et al. [12] who compared social factors of participants and nonparticipants with different cancer types. However, two other studies could not find such associations [17,29].

Comparable to Elting et al. who observed higher percentages of comorbidities in nonparticipants [12], the present study revealed a statistical association between more comorbidities and nonparticipation when adjusting for other characteristics. Participants had smaller tumor sizes, lower tumor stages and less frequently positive lymph nodes than nonparticipants. Potentially, physical activity intervention trials are selective for patients with less advanced and rather local disease.

Importantly, nonparticipants and participants did not differ in their physical activity level and both groups showed a predominantly sedentary lifestyle. Thus, the present study suggests that exercise intervention studies are not selectively addressing more active patients. Likewise the BEST-Participation-study found no influence of BMI on participation in an exercise trial. As the BEST-study focuses on interventions against fatigue, it is not surprising that patients who did not feel fatigued at all were more likely to refuse study participation.

In the literature two main theories are discussed to explain motivation of participants to participate in clinical trials: Altruistic motives as well as self-interested arguments. Jenkins and Fallowfield [30] found that a major argument for participation in clinical trials is the desire to help future patients who are confronted with cancer diagnosis. In contrast to these results Truong et al. [31] showed that altruism is not the primary reason for accepting participation. Catt et al. [32] also discussed personal benefits to be responsible for acceptance or non-acceptance of trial inclusion. In the Best-Participation-study we observed both of these motivations. “I hope to reduce fatigue and improve quality of life” and “I want to contribute to scientific progress, that future patients benefit thereof” were the two most frequent statements. Thus, the feeling to influence cancer prognosis and to positively impact the own health status seems both to be important to patients.

Declination of study participation in the BEST-study was largely attributable to the distance to get to the training centre or to difficulties related to commuting. Previous studies also showed that distance and limited transportation possibilities can be barriers for study participation [33,34]. In a review Ross et al. [35] concluded that long travel distances associated with higher costs led to a declination of study participation and higher dropout rates. “Date difficulties”, “Twice a week training is too much” and “Additional time for questionnaires and measurements is too much” can be summarized as additional logistical constraints that may be important in line with findings from other studies [34,36].

Our study had several strengths: By including only patients who were classified to be eligible through the BEST-study protocol and were offered participation from physicians we were able to investigate patient-related factors in relation to participation and nonparticipation. In contrast, most of the previous studies investigating these differences used retrospective designs where recruitment procedures and criteria were not fully comparable between participants and nonparticipants. Furthermore we collected additional information like fatigue status or physical activity level which are important variables in the emerging field of exercise interventions among cancer patients. A limitation of our BEST-Participation-study is, that as most of the clinical studies, we also cannot report on the exact percentage of contacted patients with respect to the entire target population. Due to organizational difficulties in the recruitment process, such as short-term alterations of the medical staff or time constraints of the physicians, not all patients were informed about the BEST-study, and among patients not willing to participate in BEST, not all were asked to complete the questionnaires of the BEST-Participation-study. Beyond that a certain proportion of the target population decided against any study participation, so that only 30.4% of all patients with breast cancer stage I-III responded to the BEST-Participation-study, either with participation or non-participation in the BEST-study. Further research is necessary to verify these aspects in detail.

Conclusions

Our study suggest that breast cancer patients are less willing or able to participate in a randomized resistance exercise trial if they live alone, have a long travel distance, a worse cancer prognosis, had a recent chemotherapy, are affected by fatigue, are above age 70 or have more comorbidities. However, there seemed to be no selection by current physical activity level or BMI. By far the most frequently reported reason for declination of participation was too long commuting time to the training facility. Our results might help to improve participation by adapting recruitment procedures in future exercise intervention studies appropriately.

References

  1. Velthuis MJ, Agasi-Idenburg SC, Aufdemkampe G, Wittink HM. The effect of physical exercise on cancer-related fatigue during cancer treatment: a meta-analysis of randomised controlled trials. Clin Oncol (R Coll Radiol). 2010;22(3):208–21.

    Article  CAS  Google Scholar 

  2. Berger AM, Gerber LH, Mayer DK. Cancer-related fatigue: implications for breast cancer survivors. Cancer. 2012;118(8 Suppl):2261–9.

    Article  PubMed  Google Scholar 

  3. Jones LW, Alfano CM. Exercise-oncology research: Past, present, and future. Acta Oncol. 2013;52(2):195–215.

    Article  PubMed  Google Scholar 

  4. Cramp F, James A, Lambert J. The effects of resistance training on quality of life in cancer: a systematic literature review and meta-analysis. Support Care Cancer. 2010;18(11):1367–76.

    Article  PubMed  Google Scholar 

  5. Lakoski SG, Eves ND, Douglas PS, Jones LW. Exercise rehabilitation in patients with cancer. Nat Rev Clin Oncol. 2012;9(5):288–96.

    Article  PubMed Central  PubMed  Google Scholar 

  6. van Dijk-Lokkart EM, Braam KI, Huisman J, Kaspers GJ, Takken T, Veening MA, et al. Factors influencing childhood cancer patients to participate in a combined physical and psychosocial intervention program: Quality of Life in Motion. Psychooncology. 2014; doi: 10.1002/pon.3677. [Epub ahead of print]

  7. Adams RN, Mosher CE, Blair CK, Snyder DC, Sloane R, Demark-Wahnefried W. Cancer survivors' uptake and adherence in diet and exercise intervention trials: An integrative data analysis. Cancer. 2015;121(1):77–83.

    Article  PubMed  Google Scholar 

  8. Dwan K, Gamble C, Williamson PR, Altman DG. Reporting of clinical trials: a review of research funders' guidelines. Trials. 2008;9:66.

    Article  PubMed Central  PubMed  Google Scholar 

  9. Harrison JD, Solomon MJ, Young JM, Meagher A, Hruby G, Salkeld G, et al. Surgical and oncology trials for rectal cancer: who will participate? Surgery. 2007;142(1):94–101.

    Article  PubMed  Google Scholar 

  10. Gross CP, Mallory R, Heiat A, Krumholz HM. Reporting the recruitment process in clinical trials: who are these patients and how did they get there? Ann Intern Med. 2002;137(1):10–6.

    Article  PubMed  Google Scholar 

  11. Kemeny MM, Peterson BL, Kornblith AB, Muss HB, Wheeler J, Levine E, et al. Barriers to clinical trial participation by older women with breast cancer. J Clin Oncol. 2003;21(12):2268–75.

    Article  PubMed  Google Scholar 

  12. Elting LS, Cooksley C, Bekele BN, Frumovitz M, Avritscher EB, Sun C, et al. Generalizability of cancer clinical trial results: prognostic differences between participants and nonparticipants. Cancer. 2006;106(11):2452–8.

    Article  PubMed  Google Scholar 

  13. Simon MS, Du W, Flaherty L, Philip PA, Lorusso P, Miree C, et al. Factors associated with breast cancer clinical trials participation and enrollment at a large academic medical center. J Clin Oncol. 2004;22(11):2046–52.

    Article  PubMed  Google Scholar 

  14. Al-Refaie WB, Vickers SM, Zhong W, Parsons H, Rothenberger D, Habermann EB. Cancer trials versus the real world in the United States. Ann Surg. 2011;254(3):438–42. discussion 442–433.

    Article  PubMed  Google Scholar 

  15. Legge F, Eaton D, Molife R, Ferrandina G, Judson I, de Bono J, et al. Participation of patients with gynecological cancer in phase I clinical trials: two years experience in a major cancer center. Gynecol Oncol. 2007;104(3):551–6.

    Article  CAS  PubMed  Google Scholar 

  16. Courneya KS, Segal RJ, Mackey JR, Gelmon K, Reid RD, Friedenreich CM, et al. Effects of aerobic and resistance exercise in breast cancer patients receiving adjuvant chemotherapy: a multicenter randomized controlled trial. J Clin Oncol. 2007;25(28):4396–404.

    Article  PubMed  Google Scholar 

  17. de Jong Z, Munneke M, Jansen LM, Ronday K, van Schaardenburg DJ, Brand R, et al. Differences between participants and nonparticipants in an exercise trial for adults with rheumatoid arthritis. Arthritis Rheum. 2004;51(4):593–600.

    Article  PubMed  Google Scholar 

  18. Potthoff K, Schmidt ME, Wiskemann J, Hof H, Klassen O, Habermann N, et al. Randomized controlled trial to evaluate the effects of progressive resistance training compared to progressive muscle relaxation in breast cancer patients undergoing adjuvant radiotherapy: the BEST study. BMC Cancer. 2013;13:162.

    Article  PubMed Central  PubMed  Google Scholar 

  19. Steindorf K, Schmidt ME, Klassen O, Ulrich CM, Oelmann J, Habermann N, et al. Randomized, controlled trial of resistance training in breast cancer patients receiving adjuvant radiotherapy: results on cancer-related fatigue and quality of life. Ann Oncol. 2014;25(11):2237–43.

    Article  CAS  PubMed  Google Scholar 

  20. Frey I, Berg A, Grathwohl D, Keul J. Freiburg Questionnaire of physical activity–development, evaluation and application. Soz Praventivmed. 1999;44(2):55–64.

    Article  CAS  PubMed  Google Scholar 

  21. Glaus A, Muller S. Measuring fatigue of cancer patients in the German-speaking region: development of the Fatigue Assessment Questionnaire. Pflege. 2001;14(3):161–70.

    Article  CAS  PubMed  Google Scholar 

  22. Beutel ME, Hinz A, Albani C, Brahler E. Fatigue assessment questionnaire: standardization of a cancer-specific instrument based on the general population. Oncology. 2006;70(5):351–7.

    Article  CAS  PubMed  Google Scholar 

  23. Frey I, Berg A. Körperliche Aktivität in Prävention und Therapie Evidenzbasierter Leitfaden für Klinik und Praxis. Hand Marseille Verlag GmbH, München: Samitz G., Mensink G.B.M; 2002.

    Google Scholar 

  24. Cottin V, Arpin D, Lasset C, Cordier JF, Brune J, Chauvin F, et al. Small-cell lung cancer: patients included in clinical trials are not representative of the patient population as a whole. Ann Oncol. 1999;10(7):809–15.

    Article  CAS  PubMed  Google Scholar 

  25. Comis RL, Miller JD, Aldige CR, Krebs L, Stoval E. Public attitudes toward participation in cancer clinical trials. J Clin Oncol. 2003;21(5):830–5.

    Article  PubMed  Google Scholar 

  26. Guidry JJ, Aday LA, Zhang D, Winn RJ. Transportation as a barrier to cancer treatment. Cancer Pract. 1997;5(6):361–6.

    CAS  PubMed  Google Scholar 

  27. Murthy VH, Krumholz HM, Gross CP. Participation in cancer clinical trials: race-, sex-, and age-based disparities. JAMA. 2004;291(22):2720–6.

    Article  CAS  PubMed  Google Scholar 

  28. Hurria A. Clinical trials in older adults with cancer: past and future. Oncology (Williston Park). 2007;21(3):351–8. discussion 363–354, 367.

    Google Scholar 

  29. Mancini J, Geneve J, Dalenc F, Genre D, Monnier A, Kerbrat P, et al. Decision-making and breast cancer clinical trials: how experience challenges attitudes. Contemp Clin Trials. 2007;28(6):684–94.

    Article  PubMed  Google Scholar 

  30. Jenkins V, Fallowfield L. Reasons for accepting or declining to participate in randomized clinical trials for cancer therapy. Br J Cancer. 2000;82(11):1783–8.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  31. Truong TH, Weeks JC, Cook EF, Joffe S. Altruism among participants in cancer clinical trials. Clin Trials. 2011;8(5):616–23.

    Article  PubMed  Google Scholar 

  32. Catt S, Langridge C, Fallowfield L, Talbot DC, Jenkins V. Reasons given by patients for participating, or not, in Phase 1 cancer trials. Eur J Cancer. 2011;47(10):1490–7.

    Article  CAS  PubMed  Google Scholar 

  33. Baggstrom MQ, Waqar SN, Sezhiyan AK, Gilstrap E, Gao F, Morgensztern D, et al. Barriers to enrollment in non-small cell lung cancer therapeutic clinical trials. J Thorac Oncol. 2011;6(1):98–102.

    Article  PubMed  Google Scholar 

  34. Lara Jr PN, Higdon R, Lim N, Kwan K, Tanaka M, Lau DH, et al. Prospective evaluation of cancer clinical trial accrual patterns: identifying potential barriers to enrollment. J Clin Oncol. 2001;19(6):1728–33.

    PubMed  Google Scholar 

  35. Ross S, Grant A, Counsell C, Gillespie W, Russell I, Prescott R. Barriers to participation in randomised controlled trials: a systematic review. J Clin Epidemiol. 1999;52(12):1143–56.

    Article  CAS  PubMed  Google Scholar 

  36. Locock L, Smith L. Personal benefit, or benefiting others? Deciding whether to take part in clinical trials. Clin Trials. 2011;8(1):85–93.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements and Funding

The BEST trial is funded by the Interdisciplinary Research Funding Program (intramural) of the National Center for Tumor Diseases (NCT), Heidelberg. The authors thank Werner Diehl for Data Management.

Author information

Author notes

    Authors and Affiliations

    1. Unit of Physical Activity and Cancer, Department of Preventive Oncology, German Cancer Research Center and National Center for Tumor Diseases, Im Neuenheimer Feld 460, 69120, Heidelberg, Germany

      Sandra M Gollhofer, Joachim Wiskemann, Martina E Schmidt, Oliver Klassen & Karen Steindorf

    2. Unit of Environmental Epidemiology, German Cancer Research Center, Im Neuenheimer Feld 280, 69120, Heidelberg, Germany

      Martina E Schmidt & Karen Steindorf

    3. Department of Medical Oncology, National Center for Tumor Diseases, Im Neuenheimer Feld 460, 69120, Heidelberg, Germany

      Joachim Wiskemann & Karin Potthoff

    4. Department of Radiation Oncology, University of Heidelberg Medical Center, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany

      Jan Oelmann, Holger Hof & Karin Potthoff

    5. Department of Preventive Oncology, National Center for Tumor Diseases, Im Neuenheimer Feld 460, 69120, Heidelberg, Germany

      Cornelia M Ulrich

    6. National Center for Tumor Diseases (NCT), Divisions of Medical Oncology and Preventive Oncology, Im Neuenheimer Feld 460, 69120, Heidelberg, Germany

      Joachim Wiskemann

    Authors
    1. Sandra M Gollhofer
      View author publications

      You can also search for this author in PubMed Google Scholar

    2. Joachim Wiskemann
      View author publications

      You can also search for this author in PubMed Google Scholar

    3. Martina E Schmidt
      View author publications

      You can also search for this author in PubMed Google Scholar

    4. Oliver Klassen
      View author publications

      You can also search for this author in PubMed Google Scholar

    5. Cornelia M Ulrich
      View author publications

      You can also search for this author in PubMed Google Scholar

    6. Jan Oelmann
      View author publications

      You can also search for this author in PubMed Google Scholar

    7. Holger Hof
      View author publications

      You can also search for this author in PubMed Google Scholar

    8. Karin Potthoff
      View author publications

      You can also search for this author in PubMed Google Scholar

    9. Karen Steindorf
      View author publications

      You can also search for this author in PubMed Google Scholar

    Corresponding author

    Correspondence to Joachim Wiskemann.

    Additional information

    Competing interests

    The authors declare that they have no competing interests.

    Authors’ contributions

    SG performed the data collection and study coordination and drafted the manuscript. JW developed the research question and supervised the data collection. MS participated in the design of the study and performed the statistical analysis. OK was responsible for the study organization and coordination. CU helped to draft the manuscript. JO, HH and KP recruited the patients and performed the medical check-up with regard to the study inclusion criteria. KS conceived and supervised the whole study process and helped to draft the manuscript. All authors read and approved the final manuscript.

    Karin Potthoff and Karen Steindorf contributed equally to this work.

    Rights and permissions

    Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

    The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

    To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/.

    The Creative Commons Public Domain Dedication waiver (https://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

    Reprints and permissions

    About this article

    Check for updates. Verify currency and authenticity via CrossMark

    Cite this article

    Gollhofer, S.M., Wiskemann, J., Schmidt, M.E. et al. Factors influencing participation in a randomized controlled resistance exercise intervention study in breast cancer patients during radiotherapy. BMC Cancer 15, 186 (2015). https://0-doi-org.brum.beds.ac.uk/10.1186/s12885-015-1213-1

    Download citation

    • Received:

    • Accepted:

    • Published:

    • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s12885-015-1213-1

    Keywords

    BMC Cancer

    ISSN: 1471-2407

    Contact us