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In this study, we provide consensus guidelines for the use of bisphosphonates in men with prostate cancer. To this end, an expert panel composed of urologists, medical oncologists, radiation oncologists, and endocrinologists met to review current clinical evidence for the use of bisphosphonates in patients with different stages of prostate cancer to derive consensus recommendations. Physicians should be proactive in monitoring bone loss in patients receiving long-term androgen-deprivation therapy for prostate cancer. Further study is needed before recommending the routine use of bisphosphonates in men with nonmetastatic prostate cancer. However, if a patient has clinically significant bone loss, use of a bisphosphonate to prevent further compromise of bone integrity should be strongly considered, regardless of hormonal and metastatic status. Bone scans are the preferred method for the identification of bone metastases. In patients with hormone-refractory prostate cancer and bone metastases, zoledronic acid is the only bisphosphonate indicated for the prevention of skeletal complications. In conclusion, patients with prostate cancer are at high risk for skeletal morbidity. Bisphosphonates have been shown to prevent cancer treatment-induced bone loss in men receiving androgen-deprivation therapy as well as skeletal complications in men with bone metastases. However, further study of the use of bisphosphonates across the clinical spectrum of prostate cancer is needed., SCOPUS: re.j, info:eu-repo/semantics/published

Background Fatigue is the most commonly reported acute effect of breast radiotherapy with approximately 40% of patients experiencing this debilitating symptom. Amelioration of radiation induced fatigue has been hindered by a multifactorial aetiology and an imprecise understanding of the biological pathways whereby a localised treatment causes a systemic effect. Evidence suggests the involvement of an inappropriate neuroimmunological response, mediated via the release of proinflammtory cytokines, like interleukin-6 (1). The agonistic soluble interleukin-6 receptor (sIL6R) is of interest as neural cells only respond to IL-6 in complex with sIL-6R. Therefore, many of the behavioural effects of IL-6 depend on concentrations of sIL-6R. Evidence also identifies Body Mass Index as a risk factor for fatigue, though it is unclear whether this is due to associations between adiposity and, IL-6, increased volumes of radiation or depression and reduced activity. In this study relationships will be sought between both irradiated normal tissue volumes and BMI and inflammatory cytokines at the biochemical level and fatigue at the behavioural level. Methods 100 ‘early’ breast cancer patients receiving no prior systemic therapies and prescribed 45Gy/15#/3 weeks, were consecutively recruited. Fatigue was measured by the Functional Assessment of Cancer Therapy Fatigue Subscale. The volumes of normal tissue within the 10%, 50% and 90% isodose levels were determined via dose-volume histogram analysis. ELISA kits determined circulating levels of sIL-6R. Multiple regression analysis will be utilised. Results The first 50 patients have been recruited and preliminary results will be available by October 2008. References 1. Collado-Hidalgo, A. et al. 2006. Inflammatory biomarkers for persistent fatigue in breast cancer survivors. Clinical Cancer Research 12(9), pp. 2759-2766.

Introduction: As part of a move towards reflexivity, whereby practice can influence research and vice-versa, more longitudinal study designs are being utilised within radiotherapy research. Questions regarding change over time of an outcome and the assessment of predictive factors associated with the outcome can be answered by this approach. As subjects are measured repeatedly over time their responses are correlated, and failure to incorporate this fact into the data analysis may lead to erroneous conclusions and loss of statistical power (1). Conventional approaches to analyse correlated observations have been, to transform multiple observations into a single summary measure or to use a form of repeated-measures analysis of variance (rANOVA) (2). Both approaches have recognised strengths but also inherent weaknesses regarding inflexibility of the number, timing and variability of observations, an inability to estimate the way individual subjects change over time and difficulties when dealing with incomplete datasets (3). More sophisticated statistical methods, mixed-effects models and generalised estimating equations, overcome most of these issues but until recently have been too complex for most researchers to utilise. Novel software, such as SPSS version15, has now made them accessible without requiring statistical programming. Method: Archives of six journals - Radiotherapy & Oncology, International Journal of Radiation Oncology Biology Physics, Journal of Clinical Oncology, Radiography, Journal of Pain & Symptom Management and Journal of Radiotherapy in Practice - were searched for radiotherapy related repeated measure designs, published between 1999 and 2006. The level of statistical analysis was noted. Results: In 1999 12% of studies used sophisticated models, 75% used rANOVA and 13% summary measures. By 2006 the use of sophisticated models was 39%, with 59% rANOVA and only 2% summary measures. Discussion: Radiotherapy research has increasingly utilised mixe

Introduction: As part of a move towards reflexivity, whereby practice can influence research and vice-versa, more longitudinal study designs are being utilised within radiotherapy research. Questions regarding change over time of an outcome and the assessment of predictive factors associated with the outcome can be answered by this approach. As subjects are measured repeatedly over time their responses are correlated, and failure to incorporate this fact into the data analysis may lead to erroneous conclusions and loss of statistical power (1). Conventional approaches to analyse correlated observations have been, to transform multiple observations into a single summary measure or to use a form of repeated-measures analysis of variance (rANOVA) (2). Both approaches have recognised strengths but also inherent weaknesses regarding inflexibility of the number, timing and variability of observations, an inability to estimate the way individual subjects change over time and difficulties when dealing with incomplete datasets (3). More sophisticated statistical methods, mixed-effects models and generalised estimating equations, overcome most of these issues but until recently have been too complex for most researchers to utilise. Novel software, such as SPSS version15, has now made them accessible without requiring statistical programming. Method: Archives of six journals - Radiotherapy & Oncology, International Journal of Radiation Oncology Biology Physics, Journal of Clinical Oncology, Radiography, Journal of Pain & Symptom Management and Journal of Radiotherapy in Practice - were searched for radiotherapy related repeated measure designs, published between 1999 and 2006. The level of statistical analysis was noted. Results: In 1999 12% of studies used sophisticated models, 75% used rANOVA and 13% summary measures. By 2006 the use of sophisticated models was 39%, with 59% rANOVA and only 2% summary measures. Discussion: Radiotherapy research has increasingly utilised mixe

Background Fatigue is the most commonly reported acute effect of breast radiotherapy with approximately 40% of patients experiencing this debilitating symptom. Amelioration of radiation induced fatigue has been hindered by a multifactorial aetiology and an imprecise understanding of the biological pathways whereby a localised treatment causes a systemic effect. Evidence suggests the involvement of an inappropriate neuroimmunological response, mediated via the release of proinflammtory cytokines, like interleukin-6 (1). The agonistic soluble interleukin-6 receptor (sIL6R) is of interest as neural cells only respond to IL-6 in complex with sIL-6R. Therefore, many of the behavioural effects of IL-6 depend on concentrations of sIL-6R. Evidence also identifies Body Mass Index as a risk factor for fatigue, though it is unclear whether this is due to associations between adiposity and, IL-6, increased volumes of radiation or depression and reduced activity. In this study relationships will be sought between both irradiated normal tissue volumes and BMI and inflammatory cytokines at the biochemical level and fatigue at the behavioural level. Methods 100 ‘early’ breast cancer patients receiving no prior systemic therapies and prescribed 45Gy/15#/3 weeks, were consecutively recruited. Fatigue was measured by the Functional Assessment of Cancer Therapy Fatigue Subscale. The volumes of normal tissue within the 10%, 50% and 90% isodose levels were determined via dose-volume histogram analysis. ELISA kits determined circulating levels of sIL-6R. Multiple regression analysis will be utilised. Results The first 50 patients have been recruited and preliminary results will be available by October 2008. References 1. Collado-Hidalgo, A. et al. 2006. Inflammatory biomarkers for persistent fatigue in breast cancer survivors. Clinical Cancer Research 12(9), pp. 2759-2766.