PurposeUnmanaged distress has been shown to adversely affect survival and quality of life in breast cancer survivors. Fortunately, distress can be managed and even prevented with appropriate evidence-based interventions. Therefore, the objective of this systematic review was to synthesize the published literature around predictors of distress in female breast cancer survivors to help guide targeted intervention to prevent distress.MethodsRelevant studies were located by searching MEDLINE, Embase, PsycINFO, and CINAHL databases. Significance and directionality of associations for commonly assessed candidate predictors (n ≥ 5) and predictors shown to be significant (p ≤ 0.05) by at least two studies were summarized descriptively. Predictors were evaluated based on the proportion of studies that showed a significant and positive association with the presence of distress.ResultsForty-two studies met the target criteria and were included in the review. Breast cancer and treatment-related predictors were more advanced cancer at diagnosis, treatment with chemotherapy, longer primary treatment duration, more recent transition into survivorship, and breast cancer recurrence. Manageable treatment-related symptoms associated with distress included menopausal/vasomotor symptoms, pain, fatigue, and sleep disturbance. Sociodemographic characteristics that increased the risk of distress were younger age, non-Caucasian ethnicity, being unmarried, and lower socioeconomic status. Comorbidities, history of mental health problems, and perceived functioning limitations were also associated. Modifiable predictors of distress were lower physical activity, lower social support, and cigarette smoking.ConclusionsThis review established a set of evidence-based predictors that can be used to help identify women at higher risk of experiencing distress following completion of primary breast cancer treatment.Electronic supplementary materialThe online version of this article (doi:10.1007/s10549-017-4290-9) contains supplementary material, which is available to authorized users.

Objective To examine off-label indications for antidepressants in primary care and determine the level of scientific support for off-label prescribing.Design Descriptive study of antidepressant prescriptions written by primary care physicians using an indication based electronic prescribing system.Setting Primary care practices in and around two major urban centres in Quebec, Canada.Participants Patients aged 18 years or older who visited a study physician between 1 January 2003 and 30 September 2015 and were prescribed an antidepressant through the electronic prescribing system.Main outcome measures Prevalence of off-label indications for antidepressant prescriptions by class and by individual drug. Among off-label antidepressant prescriptions, the proportion of prescriptions in each of the following categories was measured: strong evidence supporting use of the prescribed drug for the respective indication; no strong evidence for the prescribed drug but strong evidence supporting use of another drug in the same class for the indication; or no strong evidence supporting use of the prescribed drug and all other drugs in the same class for the indication. Results 106 850 antidepressant prescriptions were written by 174 physicians for 20 920 adults. By class, tricyclic antidepressants had the highest prevalence of off-label indications (81.4%, 95% confidence interval, 77.3% to 85.5%), largely due to a high off-label prescribing rate for amitriptyline (93%, 89.6% to 95.7%). Trazodone use for insomnia was the most common off-label use for antidepressants, accounting for 26.2% (21.9% to 30.4%) of all off-label prescriptions. For only 15.9% (13.0% to 19.3%) of all off-label prescriptions, the prescribed drug had strong scientific evidence for the respective indication. For 39.6% (35.7% to 43.2%) of off-label prescriptions, the prescribed drug did not have strong evidence but another antidepressant in the same class had strong evidence for the respective indication. For the remaining 44.6% (40.2% to 49.0%) of off-label prescriptions, neither the prescribed drug nor any other drugs in the class had strong evidence for the indication.Conclusions When primary care physicians prescribed antidepressants for off-label indications, these indications were usually not supported by strong scientific evidence, yet often another antidepressant in the same class existed that had strong evidence for the respective indication. There is an important need to generate and provide physicians with evidence on off-label antidepressant use to optimise prescribing decisions.

Antidepressant use in the United States has increased over the last 2 decades. 1 A suspected reason for this trend is that primary care physicians are increasingly prescribing antidepressants for nondepressive indications, including unapproved (off-label) indications that have not been evaluated by regulatory agencies. 2 However, the frequency with which physicians prescribe antidepressants for nondepressive indications is unknown because treatment indications are rarely documented. We analyzed the prevalence of treatment indications for antidepressants and assessed temporal trends in antidepressant prescribing for depression.

BACKGROUND Admission to hospital provides the opportunity to review patient medications; however, the extent to which the safety of drug regimens changes after hospitalization is unclear. OBJECTIVE To estimate the number of potentially inappropriate medications (PIMs) prescribed to patients at hospital discharge and their association with the risk of adverse events 30 days after discharge. DESIGN Prospective cohort study. SETTING Tertiary care hospitals within the McGill University Health Centre Network in Montreal, Quebec, Canada. PARTICIPANTS Patients from internal medicine, cardiac, and thoracic surgery, aged 65 years and older, admitted between October 2014 and November 2016. MEASURES Abstracted chart data were linked to provincial health databases. PIMs were identified using AGS (American Geriatrics Society) Beers Criteria®, STOPP, and Choosing Wisely statements. Multivariable logistic regression and Cox models were used to assess the association between PIMs and adverse events. RESULTS Of 2,402 included patients, 1,381 (57%) were male; median age was 76 years (interquartile range [IQR] = 70‐82 years); and eight discharge medications were prescribed (IQR = 2‐8). A total of 1,576 (66%) patients were prescribed at least one PIM at discharge; 1,176 (49%) continued a PIM from prior to admission, and 755 (31%) were prescribed at least one new PIM. In the 30 days after discharge, 218 (9%) experienced an adverse drug event (ADE) and 862 (36%) visited the emergency department (ED), were rehospitalized, or died. After adjustment, each additional new PIM and continued community PIM were respectively associated with a 21% (odds ratio [OR] = 1.21; 95% confidence interval [CI] = 1.01‐1.45) and a 10% (OR = 1.10; 95% CI = 1.01‐1.21) increased odds of ADEs. They were also respectively associated with a 13% (hazard ratio [HR] = 1.13; 95% CI = 1.03‐1.26) and a 5% (HR = 1.05; 95% CI = 1.00‐1.10) increased risk of ED visits, rehospitalization, and death. CONCLUSIONS Two in three hospitalized patients were prescribed a PIM at discharge, and increasing numbers of PIMs were associated with an increased risk of ADEs and all‐cause adverse events. Improving hospital prescribing practices may reduce the frequency of PIMs and associated adverse events. J Am Geriatr Soc 68:1184–1192, 2020.

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Key PointsQuestionDoes an electronic medication reconciliation tool reduce the occurrence of adverse drug events and other adverse outcomes in the 30 days after discharge?FindingsIn this cluster randomized trial that included 3491 patients discharged from 2 medical units and 2 surgical units of 1 academic hospital, electronic medication reconciliation reduced medication discrepancies but had no effect on adverse drug events (primary outcome), emergency department visits, or readmission in the 30 days after discharge.MeaningHospital accreditation requirements for medication reconciliation should be revised to focus on interventions that will reduce the risk of adverse events for patients with multiple changes to their community medication.

Organogels can be prepared by immobilizing an organic phase into a three-dimensional network coming from the self-assembly of a low molecular weight gelator molecule. In this work, an injectable subcutaneous organogel system based on safflower oil and a modified-tyrosine organogelator was evaluated in vivo for the delivery of rivastigmine, an acetylcholinesterase (AChE) inhibitor used in the treatment of Alzheimer's disease. Different implant formulations were injected and the plasmatic drug concentration was assayed for up to 35 days. In parallel, the inhibition of AChE in different brain sections and the biocompatibility of the implants were monitored. The pharmacokinetic profiles were found to be influenced by the gel composition, injected dose and volume of the implant. The sustained delivery of rivastigmine was accompanied by a significant prolonged inhibition of AChE in the hippocampus, a brain structure involved in memory. The implant induced only a minimal to mild chronic inflammation and fibrosis, which was comparable to poly(D,L-lactide-co-glycolide) in situ-forming implants. These findings suggest that tyrosine-based organogels could represent an alternative approach to current formulations for the sustained delivery of cholinesterase inhibitors.

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