Reducing inappropriate prescribing is key to mitigating antibiotic resistance, particularly in acute care settings. Clinicians' prescribing decisions are influenced by their judgments and actual or perceived patient expectations. Fuzzy trace theory predicts that patients and clinicians base such decisions on categorical gist representations that reflect the bottom-line understanding of information about antibiotics. However, due to clinicians' specialized training, the categorical gists driving clinicians' and patients' decisions might differ, which could result in mismatched expectations and inefficiencies in targeting interventions. We surveyed clinicians and patients from 2 large urban academic hospital emergency departments (EDs) and a sample of nonpatient subjects regarding their gist representations of antibiotic decisions, as well as relevant knowledge and expectations. Results were analyzed using exploratory factor analysis (EFA) and multifactor regression. In total, 149 clinicians (47% female; 74% white), 519 online subjects (45% female; 78% white), and 225 ED patients (61% female; 56% black) completed the survey. While clinicians demonstrated greater knowledge of antibiotics and concern about side effects than patients, the predominant categorical gist for both patients and clinicians was "why not take a risk," which compares the status quo of remaining sick to the possibility of benefit from antibiotics. This gist also predicted expectations and prior prescribing in the nonpatient sample. Other representations reflected the gist that "germs are germs" conflating bacteria and viruses, as well as perceptions of side effects and efficacy. Although individually rational, reliance on the "why not take a risk" representation can lead to socially suboptimal results, including antibiotic resistance and individual patient harm due to adverse events. Changing this representation could alter clinicians' and patients' expectations, suggesting opportunities to reduce overprescribing.

Background

Adherence to evidence-based antibiotic therapy guidelines for treatment of upper respiratory tract infections (URIs) varies widely among clinicians. Understanding this variability is key for reducing inappropriate prescribing.

Objective

To measure how emergency department (ED) clinicians' perceptions of antibiotic prescribing risks affect their decision-making.

Design

Clinician survey based on fuzzy-trace theory, a theory of medical decision-making, combined with retrospective data on prescribing outcomes for URI/pneumonia visits in two EDs. The survey predicts the categorical meanings, or gists, that individuals derive from given information.

Participants

ED physicians, residents, and physician assistants (PAs) who completed surveys and treated patients with URI/pneumonia diagnoses between August 2014 and December 2015.

Main measures

Gists derived from survey responses and their association with rates of antibiotic prescribing per visit.

Key results

Of 4474 URI/pneumonia visits, 2874 (64.2%) had an antibiotic prescription. However, prescribing rates varied from 7% to 91% for the 69 clinicians surveyed (65.2% response rate). Clinicians who framed therapy-prescribing decisions as a categorical choice between continued illness and possibly beneficial treatment ("why not take a risk?" gist, which assumes antibiotic therapy is essentially harmless) had higher rates of prescribing (OR 1.28 [95% CI, 1.06-1.54]). Greater agreement with the "antibiotics may be harmful" gist was associated with lower prescribing rates (OR 0.81 [95% CI, 0.67-0.98]).

Conclusions

Our results indicate that clinicians who perceive prescribing as a categorical choice between patients remaining ill or possibly improving from therapy are more likely to prescribe antibiotics. However, this strategy assumes that antibiotics are essentially harmless. Clinicians who framed decision-making as a choice between potential harms from therapy and continued patient illness (e.g., increased appreciation of potential harms) had lower prescribing rates. These results suggest that interventions to reduce inappropriate prescribing should emphasize the non-negligible possibility of serious side effects.

Background

There is growing evidence that exposure to low-grade inflammation may be associated with adverse health outcomes.

Methods

We conducted a cross-sectional study within the California Teachers Study prospective cohort, among female participants who had completed a questionnaire that asked about their health behaviors (e.g., diabetes, physical activity, body mass index, medication use) and who had donated blood within a year of their questionnaire. 822 women with stored serum were evaluated for 16 immune biomarkers. In addition, four immune pathways were constructed: Th1, pro-inflammatory/macrophage activation, B-cell activation, and T-cell activation. Odds ratios (ORs) and 95% confidence intervals (CI) for the association between host characteristics and immune biomarkers were assessed using logistic regression models.

Result

Compared to women of a normal BMI, obese women (>30 kg/m²) were positively associated with sTNFR2, CD27, IL6, CXCL13, sIL-2Rα, and IL6Ra levels above the median, with odds ratios ranging from 1.5 to 6.0. The pro-inflammatory/macrophage activation pathway was positively associated with diabetes (OR = 2.12, 95% CI = 1.14-3.95), fueled by individual associations between diabetes and sTNF-R2, TNFα and sCD27. Physical activity was inversely associated with sTNF-R2, TNFα, CXCL13, IL6, IL10, and IFN-γ levels, particularly for the highest category of activity (5.88+ hours/week) (ORs = 0.32-0.69). In pathway-based analyses, the Th1 pathway which includes decreased levels of IL4 and IL10 was positively associated with elevated physical activity (OR = 1.5). In contrast, the pro-inflammatory, B- and T-cell activation pathways were positively associated with higher BMI (OR ranging from 1.6 to 3) and inversely associated with increasing levels of physical activity.

Conclusions

Several host characteristics were associated with circulating levels of immune biomarkers, including markers of inflammation. Further understanding of associations between immune marker profiles with human disease are warranted.

Background

Physical inactivity and unhealthy diet are modifiable behaviors that lead to several cancers. Biologically, these behaviors are linked to cancer through obesity-related insulin resistance, inflammation, and oxidative stress. Individual strategies to change physical activity and diet are often short lived with limited effects. Interventions are expected to be more successful when guided by multi-level frameworks that include environmental components for supporting lifestyle changes. Understanding the role of environment in the pathways between behavior and cancer can help identify what environmental conditions are needed for individual behavioral change approaches to be successful, and better recognize how environments may be fueling underlying racial and ethnic cancer disparities.

Methods

This cross-sectional study was designed to select participants (n = 602 adults, 40% Hispanic, in San Diego County) from a range of neighborhoods ensuring environmental variability in walkability and food access. Biomarkers measuring cancer risk were measured with fasting blood draw including insulin resistance (fasting plasma insulin and glucose levels), systemic inflammation (levels of CRP), and oxidative stress measured from urine samples. Objective physical activity, sedentary behavior, and sleep were measured by participants wearing a GT3X+ ActiGraph on the hip and wrist. Objective measures of locations were obtained through participants wearing a Qstarz Global Positioning System (GPS) device on the waist. Dietary measures were based on a 24-h food recall collected on two days (weekday and weekend). Environmental exposure will be calculated using static measures around the home and work, and dynamic measures of mobility derived from GPS traces. Associations of environment with physical activity, obesity, diet, and biomarkers will be measured using generalized estimating equation models.

Discussion

Our study is the largest study of objectively measured physical activity, dietary behaviors, environmental context/exposure, and cancer-related biomarkers in a Hispanic population. It is the first to perform high quality measures of physical activity, sedentary behavior, sleep, diet and locations in which these behaviors occur in relation to cancer-associated biomarkers including insulin resistance, inflammation, impaired lipid metabolism, and oxidative stress. Results will add to the evidence-base of how behaviors and the built environment interact to influence biomarkers that increase cancer risk.

Trial registration

ClinicalTrials.gov NCT02094170 , 03/21/2014.

PURPOSE: To estimate the risk of contralateral breast cancer (CBC) among women with germline pathogenic variants (PVs) in ATM, BRCA1, BRCA2, CHEK2, and PALB2. METHODS: The study population included 15,104 prospectively followed women within the CARRIERS study treated with ipsilateral surgery for invasive breast cancer. The risk of CBC was estimated for PV carriers in each gene compared with women without PVs in a multivariate proportional hazard regression analysis accounting for the competing risk of death and adjusting for patient and tumor characteristics. The primary analyses focused on the overall cohort and on women from the general population. Secondary analyses examined associations by race/ethnicity, age at primary breast cancer diagnosis, menopausal status, and tumor estrogen receptor (ER) status. RESULTS: Germline BRCA1, BRCA2, and CHEK2 PV carriers with breast cancer were at significantly elevated risk (hazard ratio > 1.9) of CBC, whereas only the PALB2 PV carriers with ER-negative breast cancer had elevated risks (hazard ratio, 2.9). By contrast, ATM PV carriers did not have significantly increased CBC risks. African American PV carriers had similarly elevated risks of CBC as non-Hispanic White PV carriers. Among premenopausal women, the 10-year cumulative incidence of CBC was estimated to be 33% for BRCA1, 27% for BRCA2, and 13% for CHEK2 PV carriers with breast cancer and 35% for PALB2 PV carriers with ER-negative breast cancer. The 10-year cumulative incidence of CBC among postmenopausal PV carriers was 12% for BRCA1, 9% for BRCA2, and 4% for CHEK2. CONCLUSION: Women diagnosed with breast cancer and known to carry germline PVs in BRCA1, BRCA2, CHEK2, or PALB2 are at substantially increased risk of CBC and may benefit from enhanced surveillance and risk reduction strategies.

Purpose

To determine the contribution of germline pathogenic variants (PVs) in hereditary cancer testing panel genes to invasive lobular carcinoma (ILC) of the breast.

Materials and methods

The study included 2,999 women with ILC from a population-based cohort and 3,796 women with ILC undergoing clinical multigene panel testing (clinical cohort). Frequencies of germline PVs in breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, PALB2, PTEN, RAD51C, RAD51D, and TP53) were compared between women with ILC and unaffected female controls and between women with ILC and infiltrating ductal carcinoma (IDC).

Results

The frequency of PVs in breast cancer predisposition genes among women with ILC was 6.5% in the clinical cohort and 5.2% in the population-based cohort. In case-control analysis, CDH1 and BRCA2 PVs were associated with high risks of ILC (odds ratio [OR] > 4) and CHEK2, ATM, and PALB2 PVs were associated with moderate (OR = 2-4) risks. BRCA1 PVs and CHEK2 p.Ile157Thr were not associated with clinically relevant risks (OR < 2) of ILC. Compared with IDC, CDH1 PVs were > 10-fold enriched, whereas PVs in BRCA1 were substantially reduced in ILC.

Conclusion

The study establishes that PVs in ATM, BRCA2, CDH1, CHEK2, and PALB2 are associated with an increased risk of ILC, whereas BRCA1 PVs are not. The similar overall PV frequencies for ILC and IDC suggest that cancer histology should not influence the decision to proceed with genetic testing. Similar to IDC, multigene panel testing may be appropriate for women with ILC, but CDH1 should be specifically discussed because of low prevalence and gastric cancer risk.

Background

The World Health Organization recommends drug-susceptibility testing of Mycobacterium tuberculosis complex for all patients with tuberculosis to guide treatment decisions and improve outcomes. Whether DNA sequencing can be used to accurately predict profiles of susceptibility to first-line antituberculosis drugs has not been clear.

Methods

We obtained whole-genome sequences and associated phenotypes of resistance or susceptibility to the first-line antituberculosis drugs isoniazid, rifampin, ethambutol, and pyrazinamide for isolates from 16 countries across six continents. For each isolate, mutations associated with drug resistance and drug susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These profiles were predicted to be susceptible to all four drugs (i.e., pansusceptible) if they were predicted to be susceptible to isoniazid and to the other drugs or if they contained mutations of unknown association in genes that affect susceptibility to the other drugs. We simulated the way in which the negative predictive value changed with the prevalence of drug resistance.

Results

A total of 10,209 isolates were analyzed. The largest proportion of phenotypes was predicted for rifampin (9660 [95.4%] of 10,130) and the smallest was predicted for ethambutol (8794 [89.8%] of 9794). Resistance to isoniazid, rifampin, ethambutol, and pyrazinamide was correctly predicted with 97.1%, 97.5%, 94.6%, and 91.3% sensitivity, respectively, and susceptibility to these drugs was correctly predicted with 99.0%, 98.8%, 93.6%, and 96.8% specificity. Of the 7516 isolates with complete phenotypic drug-susceptibility profiles, 5865 (78.0%) had complete genotypic predictions, among which 5250 profiles (89.5%) were correctly predicted. Among the 4037 phenotypic profiles that were predicted to be pansusceptible, 3952 (97.9%) were correctly predicted.

Conclusions

Genotypic predictions of the susceptibility of M. tuberculosis to first-line drugs were found to be correlated with phenotypic susceptibility to these drugs. (Funded by the Bill and Melinda Gates Foundation and others.).

Inappropriately high breakpoints have resulted in systematic false-susceptible AST results to anti-TB drugs. MIC, PK/PD and clinical outcome data should be combined when setting breakpoints to minimise the emergence and spread of antimicrobial resistance. https://bit.ly/3i43wb6

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.