Impact of the EndoPredict genomic assay on treatment decisions for oestrogen receptor-positive early breast cancer patients: benefits of physician selective testing.

PURPOSE: Genomic tests improve accuracy of risk prediction for early breast cancers but these are expensive. This study evaluated the clinical utility of EndoPredict®, in terms of impact on adjuvant therapy recommendations and identification of parameters to guide selective application. METHODS: Patients with ER-positive, HER2-negative, and early-stage invasive breast cancer were tested with EndoPredict®. Two cohorts were recruited: one consecutively and another at clinical team discretion. Systemic treatment recommendations were recorded before and after EndoPredict® results were revealed to the multidisciplinary team. RESULTS: 233 patients were recruited across five sites: 123 consecutive and 110 at clinical team discretion. In the consecutive cohort 50.6% (62/123) cases were classified high risk of recurrence by EndoPredict®, compared with 62.7% (69/110) in the selective cohort. A change in treatment recommendation was significantly more likely (p < 0.0001) in the selective cohort (43/110, 39.1%) compared to the consecutive group (11/123, 8.9%). The strongest driver of selective recruitment was intermediate grade histology, whilst logistic regression modelling demonstrated that nodal status (p < 0.001), proliferative rate (p = 0.001), and progesterone receptor positivity (p < 0.001) were the strongest discriminators of risk. CONCLUSION: Whilst molecular risk can be predicted by traditional variables in a high proportion of cases, EndoPredict® had a greater impact on treatment decisions in those cases selected for testing at team discretion. This is indicative of the robust ability of the clinical team to identify cases most likely to benefit from testing, underscoring the value of genomic tests in the oncologists' tool kit.

Third generation cephalosporins and piperacillin/tazobactam have distinct impacts on the microbiota of critically ill patients.

Effective implementation of antibiotic stewardship, especially in critical care, is limited by a lack of direct comparative investigations on how different antibiotics impact the microbiota and antibiotic resistance rates. We investigated the impact of two commonly used antibiotics, third-generation cephalosporins (3GC) and piperacillin/tazobactam (TZP) on the endotracheal, perineal and faecal microbiota of intensive care patients in Australia. Patients exposed to either 3GC, TZP, or no ß-lactams (control group) were sampled over time and 16S rRNA amplicon sequencing was performed to examine microbiota diversity and composition. While neither treatment significantly affected diversity, numerous changes to microbiota composition were associated with each treatment. The shifts in microbiota composition associated with 3GC exposure differed from those observed with TZP, consistent with previous reports in animal models. This included a significant increase in Enterobacteriaceae and Enterococcaceae abundance in endotracheal and perineal microbiota for those administered 3GC compared to the control group. Culture-based analyses did not identify any significant changes in the prevalence of specific pathogenic or antibiotic-resistant bacteria. Exposure to clinical antibiotics has previously been linked to reduced microbiota diversity and increased antimicrobial resistance, but our results indicate that these effects may not be immediately apparent after short-term real-world exposures.

Interobserver concordance in visual assessment of Ki67 immunohistochemistry in surgical excision specimens from patients with lymph node-negative breast cancer.

PURPOSE: This study aimed to determine the interobserver concordance of two methods for proliferation assessment in breast cancer using Ki67 immunohistochemistry. METHODS: Ki67 was independently assessed in randomly selected tumour samples from patients with lymph node-negative breast cancer using two different methods: either cell counting or visual estimation of hot spot areas. For hot spot cell counting, positive and negative cell numbers were recorded for total cell counts of 300-500, 500-800 and 800-1000 cells. Visual estimation involved allocation of a score from 1 to 5 using a visual scale to estimate percentage positivity. Interobserver agreement for hot spot counting was calculated using a two-way fixed effects intraclass correlation model, and by using Cohen's kappa measure for visual assessment. Prognostic concordance between the two methods was also calculated using Cohen's kappa. RESULTS: Samples from 96 patients were included in this analysis. Interobserver agreement for hot spot cell counting was excellent (> 0.75) across all three cell count ranges, with correlation coefficients of 0.88 (95% CI 0.84-0.92), 0.87 (95% CI 0.82-0.91) and 0.89 (95% CI 0.85-0.92), respectively. Interobserver agreement with visual estimation was greatest for hot spots compared with areas of intermediate or low proliferation, with kappa scores of 0.49, 0.42 and 0.40, respectively. Both assessment methods demonstrated excellent prognostic agreement. CONCLUSIONS: Interobserver and prognostic concordance in Ki67 immunohistochemistry assessments was high using either hot spot cell counting or visual estimation, further supporting the utility and reproducibility of these cost-efficient methods to assess proliferation.

Developing an Intranet-Based Lymphedema Dashboard for Breast Cancer Multidisciplinary Teams: Design Research Study.

BACKGROUND: A large quantity of data is collected during the delivery of cancer care. However, once collected, these data are difficult for health professionals to access to support clinical decision making and performance review. There is a need for innovative tools that make clinical data more accessible to support health professionals in these activities. One approach for providing health professionals with access to clinical data is to create the infrastructure and interface for a clinical dashboard to make data accessible in a timely and relevant manner. OBJECTIVE: This study aimed to develop and evaluate 2 prototype dashboards for displaying data on the identification and management of lymphedema. METHODS: The study used a co-design framework to develop 2 prototype dashboards for use by health professionals delivering breast cancer care. The key feature of these dashboards was an approach for visualizing lymphedema patient cohort and individual patient data. This project began with 2 focus group sessions conducted with members of a breast cancer multidisciplinary team (n=33) and a breast cancer consumer (n=1) to establish clinically relevant and appropriate data for presentation and the visualization requirements for a dashboard. A series of fortnightly meetings over 6 months with an Advisory Committee (n=10) occurred to inform and refine the development of a static mock-up dashboard. This mock-up was then presented to representatives of the multidisciplinary team (n=3) to get preliminary feedback about the design and use of such dashboards. Feedback from these presentations was reviewed and used to inform the development of the interactive prototypes. A structured evaluation was conducted on the prototypes, using Think Aloud Protocol and semistructured interviews with representatives of the multidisciplinary team (n=5). RESULTS: Lymphedema was selected as a clinically relevant area for the prototype dashboards. A qualitative evaluation is reported for 5 health professionals. These participants were selected from 3 specialties: surgery (n=1), radiation oncology (n=2), and occupational therapy (n=2). Participants were able to complete the majority of tasks on the dashboard. Semistructured interview themes were categorized into engagement or enthusiasm for the dashboard, user experience, and data quality and completeness. CONCLUSIONS: Findings from this study constitute the first report of a co-design process for creating a lymphedema dashboard for breast cancer health professionals. Health professionals are interested in the use of data visualization tools to make routinely collected clinical data more accessible. To be used effectively, dashboards need to be reliable and sourced from accurate and comprehensive data sets. While the co-design process used to develop the visualization tool proved effective for designing an individual patient dashboard, the complexity and accessibility of the data required for a cohort dashboard remained a challenge.

Epidemiology of complementary and alternative medicine therapy use in allogeneic hematopoietic stem cell transplant survivorship patients in Australia.

In addition to prescribed conventional medicines, many allogeneic hematopoietic stem cell transplant (HSCT) survivors also use complementary and alternative medical therapies (CAM), however, the frequency and types of CAMs used by allogeneic HSCT survivors remain unclear. Study participants were adults who had undergone an allogeneic HSCT between 1st January 2000 and 31st December 2012. Participants completed a 402-item questionnaire regarding the use of CAM, medical complications, specialist referrals, medications and therapies, infections, vaccinations, cancer screening, lifestyle, and occupational issues and relationship status following stem cell transplantation. A total of 1475 allogeneic HSCT were performed in the study period. Of the 669 recipients known to be alive at study sampling, 583 were contactable and were sent study packs. Of 432 participants who returned the completed survey (66% of total eligible, 76% of those contacted), 239 (54.1%) HSCT survivors used at least one form of CAM. These included dietary modification (13.6%), vitamin therapy (30%), spiritual or mind-body therapy (17.2%), herbal supplements (13.5%), manipulative and body-based therapies (26%), Chinese medicine (3.5%), reiki (3%), and homeopathy (3%). These results definitively demonstrate that a large proportion of HSCT survivors are using one or more form of CAM therapy. Given the potential benefits demonstrated by small studies of specific CAM therapies in this patient group, as well as clearly documented therapies with no benefit or even toxicity, this result shows there is a large unmet need for additional studies to ascertain efficacy and safety of CAM therapies in this growing population.

Problematic Dichotomization of Risk for Intensive Care Unit (ICU)-Acquired Invasive Candidiasis: Results Using a Risk-Predictive Model to Categorize 3 Levels of Risk From a Multicenter Prospective Cohort of Australian ICU Patients.

BACKGROUND: Delayed antifungal therapy for invasive candidiasis (IC) contributes to poor outcomes. Predictive risk models may allow targeted antifungal prophylaxis to those at greatest risk. METHODS: A prospective cohort study of 6685 consecutive nonneutropenic patients admitted to 7 Australian intensive care units (ICUs) for ≥72 hours was performed. Clinical risk factors for IC occurring prior to and following ICU admission, colonization with Candida species on surveillance cultures from 3 sites assessed twice weekly, and the occurrence of IC ≥72 hours following ICU admission or ≤72 hours following ICU discharge were measured. From these parameters, a risk-predictive model for the development of ICU-acquired IC was then derived. RESULTS: Ninety-six patients (1.43%) developed ICU-acquired IC. A simple summation risk-predictive model using the 10 independently significant variables associated with IC demonstrated overall moderate accuracy (area under the receiver operating characteristic curve = 0.82). No single threshold score could categorize patients into clinically useful high- and low-risk groups. However, using 2 threshold scores, 3 patient cohorts could be identified: those at high risk (score ≥6, 4.8% of total cohort, positive predictive value [PPV] 11.7%), those at low risk (score ≤2, 43.1% of total cohort, PPV 0.24%), and those at intermediate risk (score 3-5, 52.1% of total cohort, PPV 1.46%). CONCLUSIONS: Dichotomization of ICU patients into high- and low-risk groups for IC risk is problematic. Categorizing patients into high-, intermediate-, and low-risk groups may more efficiently target early antifungal strategies and utilization of newer diagnostic tests.

Candida colonization as a risk marker for invasive candidiasis in mixed medical-surgical intensive care units: development and evaluation of a simple, standard protocol.

Colonization with Candida species is an independent risk factor for invasive candidiasis (IC), but the minimum and most practicable parameters for prediction of IC have not been optimized. We evaluated Candida colonization in a prospective cohort of 6,015 nonneutropenic, critically ill patients. Throat, perineum, and urine were sampled 72 h post-intensive care unit (ICU) admission and twice weekly until discharge or death. Specimens were cultured onto chromogenic agar, and a subset underwent molecular characterization. Sixty-three (86%) patients who developed IC were colonized prior to infection; 61 (97%) tested positive within the first two time points. The median time from colonization to IC was 7 days (range, 0 to 35). Colonization at any site was predictive of IC, with the risk of infection highest for urine colonization (relative risk [RR]=2.25) but with the sensitivity highest (98%) for throat and/or perineum colonization. Colonization of ≥2 sites and heavy colonization of ≥1 site were significant independent risk factors for IC (RR=2.25 and RR=3.7, respectively), increasing specificity to 71% to 74% but decreasing sensitivity to 48% to 58%. Molecular testing would have prompted a resistance-driven decision to switch from fluconazole treatment in only 11% of patients infected with C. glabrata, based upon species-level identification alone. Positive predictive values (PPVs) were low (2% to 4%) and negative predictive values (NPVs) high (99% to 100%) regardless of which parameters were applied. In the Australian ICU setting, culture of throat and perineum within the first two time points after ICU admission captures 84% (61/73 patients) of subsequent IC cases. These optimized parameters, in combination with clinical risk factors, should strengthen development of a setting-specific risk-predictive model for IC.

Assessment of clinical risk predictive rules for invasive candidiasis in a prospective multicentre cohort of ICU patients.

PURPOSE: To assess the generalisability of published clinical risk predictive models for invasive candidiasis in ICU patients. METHODS: The performance characteristics of published clinical risk factor-only and Candida colonisation-only predictive models for invasive candidiasis were assessed in a multicentre cohort of Australian ICU patients. Clinical risk factors and Candida colonisation parameters were collected prospectively from patients. RESULTS: The two clinical risk factor-only predictive models applied to an Australian patient cohort (n = 615) performed less well than in published studies involving derivation populations. Model performance characteristics improved when Candida colonisation parameters were added post-hoc. CONCLUSIONS: Risk predictive models should factor in both clinical risk factors and Candida colonisation parameters. Integrating these models into therapeutic algorithms first requires external validation in different patient populations and settings.