Associations between body mass index and the surgical phenotype and location of endometriotic lesions.

RESEARCH QUESTION: Is there a relationship between body mass index (BMI) and endometriotic lesions, specifically surgical phenotype and lesion location? DESIGN: An observational retrospective cohort study at the Royal Women's Hospital, Melbourne, Australia, including 471 histologically confirmed endometriosis patients. Statistical analyses included multivariate logistic regression and multivariate modelling, correcting for multiple testing. Outcomes were the presence or absence of surgically classified lesion phenotypes, as per revised American Society for Reproductive Medicine criteria including superficial or deep, peritoneal or ovarian, and adhesions (Study I); and lesions at specific anatomical locations (including pelvic side wall, uterosacral ligament, pouch of Douglas, ovarian, uterovesical fold, bladder, and pararectal endometriosis) (Study II). RESULTS: In Study I, patients with higher BMI were more likely to have superficial peritoneal lesions (odds ratio [OR] 1.070, 95% confidence interval [CI] 1.004-1.144; P = 0.044), and less likely to have deep ovarian lesions (OR 0.928, 95% CI 0.864-0.993; P = 0.034). In Study II, patients with higher BMI were less likely to have uterovesical fold lesions (OR 0.927, 95% CI 0.867-0.985; P = 0.021) or anterior compartment lesions (OR 0.940, 95% CI 0.888-0.989; P = 0.023). After correcting for multiple testing, the relationship between BMI and lesion phenotypes did not persist (P > 0.01). CONCLUSIONS: This analysis does not conclusively support an influence of BMI on endometriotic lesion phenotype based on surgical classification or location. Further investigation of the physiological disturbances underlying BMI and the promotion of endometriotic lesion phenotypes and their location is warranted, but any effect is likely to be small.

Ambulatory Toxicity Management (AToM) in patients receiving adjuvant or neo-adjuvant chemotherapy for early stage breast cancer - a pragmatic cluster randomized trial protocol.

BACKGROUND: Population-based studies suggest that emergency department visits and hospitalizations are common among patients receiving chemotherapy and that rates in routine practice are higher than expected from clinical trials. Chemotherapy-related toxicities are often predictable and, consequently, acute care visits may be preventable with adequate treatment planning and support between visits to the cancer centre. We will evaluate the impact of proactive telephone-based toxicity management on emergency department visits and hospitalizations in women with early stage breast cancer receiving chemotherapy. METHODS: In this pragmatic covariate constraint-based cluster randomized trial, 20 centres in Ontario, Canada are randomly allocated to either proactive telephone toxicity management (intervention) or routine care (control). The primary outcome is the cluster-level mean number of ED + H visits per patient evaluated using Ontario administrative healthcare data. Participants are all patients with early stage (I-III) breast cancer commencing adjuvant or neo-adjuvant chemotherapy at participating institutions during the intervention period. At least 25 patients at each centre participate in a patient reported outcomes sub-study involving the collection of standardized questionnaires to measure: severity of treatment toxicities, self-care, self-efficacy, quality of life, and coordination of care. Patients participating in the patient reported outcomes (PRO) sub-study are asked to provide written consent to link their PRO data to administrative data. Unit costs will be applied to each per person resource utilized, and a total cost per population and patient will be generated. An incremental cost-effectiveness analysis will be undertaken to compare the incremental costs and outcomes between the intervention and control groups from the health system perspective. DISCUSSION: This study evaluates the effectiveness of a proactive toxicity management intervention in a routine care setting. The use of administrative healthcare data to evaluate the primary outcome enables an evaluation in a real world setting and at a much larger scale than previous studies. TRIAL REGISTRATION: Clinicaltrials.gov , NCT02485678. Registered 30 June 2015.

User-Centered Design of a Web-Based Tool to Support Management of Chemotherapy-Related Toxicities in Cancer Patients.

BACKGROUND: Cancer patients receiving chemotherapy have high symptom needs that can negatively impact quality of life and result in high rates of unplanned acute care visits. Remote monitoring tools may improve symptom management in this patient population. OBJECTIVE: This study aimed to design a prototype tool to facilitate remote management of chemotherapy-related toxicities. METHODS: User needs were assessed using a participatory, user-centered design methodology that included field observation, interviews, and focus groups, and then analyzed using affinity diagramming. Participants included oncology patients, caregivers, and health care providers (HCPs) including medical oncologists, oncology nurses, primary care physicians, and pharmacists in Ontario, Canada. Overarching themes informed development of a Web-based prototype, which was further refined over 2 rounds of usability testing with end users. RESULTS: Overarching themes were derived from needs assessments, which included 14 patients, 1 caregiver, and 12 HCPs. Themes common to both patients and HCPs included gaps and barriers in current systems, need for decision aids, improved communication and options in care delivery, secure access to credible and timely information, and integration into existing systems. In addition, patients identified missed opportunities, care not meeting their needs, feeling overwhelmed and anxious, and wanting to be more empowered. HCPs identified accountability for patient management as an issue. These themes informed development of a Web-based prototype (bridges), which included toxicity tracking, self-management advice, and HCP communication functionalities. Usability testing with 11 patients and 11 HCPs was generally positive; however, identified challenges included tool integration into existing workflows, need for standardized toxicity self-management advice, issues of privacy and consent, and patient-tailored information. CONCLUSIONS: Web-based tools integrating just-in-time self-management advice and HCP support into routine care may address gaps in systems for managing chemotherapy-related toxicities. Attention to the integration of new electronic tools into self-care by patients and practice was a strong theme for both patients and HCP participants and is a key issue that needs to be addressed for wide-scale adoption.

Establishing achievable benchmarks for quality improvement in systemic therapy for early-stage breast cancer.

BACKGROUND: Setting realistic targets for performance is a consistent challenge in quality improvement. In the current study, the authors used administrative data to define achievable targets for a panel of 15 previously developed quality indicators (QIs) focusing on systemic therapy in patients with early-stage breast cancer. METHODS: Deterministically linked administrative databases were used to identify patients with TNM stage I to stage III breast cancer who were diagnosed between 2006 and 2010 in Ontario, Canada. For each individual indicator, data-driven empirical benchmarks were calculated using the pared-mean benchmark approach. Variation in institution-level performance for each indicator was examined through the construction of funnel plots. RESULTS: A total of 28,303 patients with early-stage breast cancer were identified, 43% of whom received adjuvant chemotherapy. For the 9 QIs for which receiving the service or outcome was desirable (ie, consultation with a medical oncologist), the benchmark varied from 40.9% to 100%. For the 6 indicators for which not receiving the service or outcome was desirable (ie, incidence of febrile neutropenia), the benchmark varied from 0% to 49.0%. There was substantial variation noted with regard to the number of institutions meeting the target and the amount of interinstitution variation between the QIs. Top performing institutions varied by indicator, with no individual institution meeting the benchmark for all indicators. For the majority of indicators, institution size was not found to be correlated with performance. CONCLUSIONS: Data-derived benchmarking can be used to facilitate quality improvement by identifying areas of both good as well as suboptimal performance while defining an achievable target for which to strive. Cancer 2017;123:3772-3780. © 2017 American Cancer Society.

Setting Quality Improvement Priorities for Women Receiving Systemic Therapy for Early-Stage Breast Cancer by Using Population-Level Administrative Data.

Purpose Routine evaluation of quality measures (QMs) can drive improvement in cancer systems by highlighting gaps in care. Targeting quality improvement at QMs that demonstrate substantial variation has the potential to make the largest impact at the population level. We developed an approach that uses both variation in performance and number of patients affected by the QM to set priorities for improving the quality of systemic therapy for women with early-stage breast cancer (EBC). Patients and Methods Patients with EBC diagnosed from 2006 to 2010 in Ontario, Canada, were identified in the Ontario Cancer Registry and linked deterministically to multiple health care databases. Individual QMs within a panel of 15 QMs previously developed to assess the quality of systemic therapy across four domains (access, treatment delivery, toxicity, and safety) were ranked on interinstitutional variation in performance (using interquartile range) and the number of patients who were affected; then the two rankings were averaged for a summative priority ranking. Results We identified 28,427 patients with EBC who were treated at 84 institutions. The use of computerized physician electronic order entry for chemotherapy, emergency room visits or hospitalizations during chemotherapy, and timely receipt of chemotherapy were identified as the QMs that had the largest potential to improve quality of care at a system level within this cohort. Conclusion A simple ranking system based on interinstitutional variation in performance and patient volume can be used to identify high-priority areas for quality improvement from a population perspective. This approach is generalizable to other health care systems that use QMs to drive improvement.