Randomised controlled trial of a home-based physical activity intervention in breast cancer survivors

Background: To improve adherence to physical activity (PA), behavioural support in the form of behavioural change counselling may be necessary. However, limited evidence of the effectiveness of home-based PA combined with counselling in breast cancer patients exists. The aim of this current randomised controlled trial with a parallel group design was to evaluate the effectiveness of a home-based PA intervention on PA levels, anthropometric measures, health-related quality of life (HRQoL), and blood biomarkers in breast cancer survivors. Methods: Eighty post-adjuvant therapy invasive breast cancer patients (age = 53.6 ± 9.4 years; height = 161.2 ± 6.8 cm; mass = 68.7 ± 10.5 kg) were randomly allocated to a 6-month home-based PA intervention or usual care. The intervention group received face-to-face and telephone PA counselling aimed at encouraging the achievement of current recommended PA guidelines. All patients were evaluated for our primary outcome, PA (International PA Questionnaire) and secondary outcomes, mass, BMI, body fat %, HRQoL (Functional assessment of Cancer Therapy-Breast), insulin resistance, triglycerides (TG) and total (TC), high-density lipoprotein (HDL-C) and low-density lipoprotein (LDL-C) cholesterol were assessed at baseline and at 6-months. Results: On the basis of linear mixed-model analyses adjusted for baseline values performed on 40 patients in each group, total, leisure and vigorous PA significantly increased from baseline to post-intervention in the intervention compared to usual care (between-group differences, 578.5 MET-min∙wk−1, p = .024, 382.2 MET-min∙wk−1, p = .010, and 264.1 MET-min∙wk−1, p = .007, respectively). Both body mass and BMI decreased significantly in the intervention compared to usual care (between-group differences, −1.6 kg, p = .040, and −.6 kg/m2, p = .020, respectively). Of the HRQoL variables, FACT-Breast, Trial Outcome Index, functional wellbeing, and breast cancer subscale improved significantly in the PA group compared to the usual care group (between-group differences, 5.1, p= .024; 5.6, p = .001; 1.9 p = .025; and 2.8, p=.007, respectively). Finally, TC and LDL-C was significantly reduced in the PA group compared to the usual care group (between-group differences, −.38 mmol∙L−1, p=.001; and −.3 mmol∙L−1, p=.023, respectively). Conclusions: We found that home-based PA resulted in significant albeit small to moderate improvements in selfreported PA, mass, BMI, breast cancer specific HRQoL, and TC and LDL-C compared with usual care

Improving the Prognostic Ability through Better Use of Standard Clinical Data - The Nottingham Prognostic Index as an Example

Background Prognostic factors and prognostic models play a key role in medical research and patient management. The Nottingham Prognostic Index (NPI) is a well-established prognostic classification scheme for patients with breast cancer. In a very simple way, it combines the information from tumor size, lymph node stage and tumor grade. For the resulting index cutpoints are proposed to classify it into three to six groups with different prognosis. As not all prognostic information from the three and other standard factors is used, we will consider improvement of the prognostic ability using suitable analysis approaches. Methods and Findings Reanalyzing overall survival data of 1560 patients from a clinical database by using multivariable fractional polynomials and further modern statistical methods we illustrate suitable multivariable modelling and methods to derive and assess the prognostic ability of an index. Using a REMARK type profile we summarize relevant steps of the analysis. Adding the information from hormonal receptor status and using the full information from the three NPI components, specifically concerning the number of positive lymph nodes, an extended NPI with improved prognostic ability is derived. Conclusions The prognostic ability of even one of the best established prognostic index in medicine can be improved by using suitable statistical methodology to extract the full information from standard clinical data. This extended version of the NPI can serve as a benchmark to assess the added value of new information, ranging from a new single clinical marker to a derived index from omics data. An established benchmark would also help to harmonize the statistical analyses of such studies and protect against the propagation of many false promises concerning the prognostic value of new measurements. Statistical methods used are generally available and can be used for similar analyses in other diseases

Trastuzumab in the Adjuvant Treatment of HER2-Positive Early Breast Cancer Patients: A Meta-Analysis of Published Randomized Controlled Trials

BACKGROUND: Adjuvant trastuzumab therapy has yielded conflicting results for overall survival, concerns about central nervous system (CNS) metastasis, and questions about optimal schedule. Therefore, we carried out a meta-analysis to assess the benefits of concurrent or sequential trastuzumab with adjuvant chemotherapy for early breast cancer patients with HER2-positive tumors. METHODS: Computerized and manual searches were performed to identify randomized clinical trials comparing adjuvant chemotherapy with or without trastuzumab in HER2-positive early breast cancer patients. Odds ratios were used to estimate the association between the addition of trastuzumab to adjuvant chemotherapy and various survival outcomes. The fixed-effects or random-effects model was used to combine data. FINDINGS: With six eligible studies identified, this analysis demonstrated that patients with HER2-positive breast cancer derived benefit in disease-free survival, overall survival, locoregional recurrence and distant recurrence (all P<0.001) from the addition of trastuzumab to adjuvant chemotherapy, whereas trastuzumab did worse in CNS recurrence as compared to the control group (P = 0.018). Furthermore, concomitant use of trastuzumab significantly lowered the hazard of death (P<0.001) but bore a higher incidence of CNS recurrence (P = 0.010), while statistical significance failed to be discerned for either overall survival (P = 0.069) or CNS metastasis (P = 0.374) between the sequential and observation arms. CONCLUSION: This analysis verifies the efficacy of trastuzumab in the adjuvant setting. Additionally, our findings indirectly corroborate the superiority of concurrent trastuzumab to sequential use and also illuminate that prolonged survival is the possible reason for the higher incidence of CNS with trastuzumab versus observation

Joint sequencing of human and pathogen genomes reveals the genetics of pneumococcal meningitis.

Streptococcus pneumoniae is a common nasopharyngeal colonizer, but can also cause life-threatening invasive diseases such as empyema, bacteremia and meningitis. Genetic variation of host and pathogen is known to play a role in invasive pneumococcal disease, though to what extent is unknown. In a genome-wide association study of human and pathogen we show that human variation explains almost half of variation in susceptibility to pneumococcal meningitis and one-third of variation in severity, identifying variants in CCDC33 associated with susceptibility. Pneumococcal genetic variation explains a large amount of invasive potential (70%), but has no effect on severity. Serotype alone is insufficient to explain invasiveness, suggesting other pneumococcal factors are involved in progression to invasive disease. We identify pneumococcal genes involved in invasiveness including pspC and zmpD, and perform a human-bacteria interaction analysis. These genes are potential candidates for the development of more broadly-acting pneumococcal vaccines