Parents' Desire to Change Phone Use: Associations with Objective Smartphone Use and Feelings About Problematic Use and Distraction

We examined objective smartphone use (via a mobile sensing application) and self-reported desire to change phone use among a sample of 268 U.S. parents of infants. Using the Transtheoretical Stages of Change model as a conceptual foundation, we contextualized their attitudes and behaviors and explored how phone use and desire to change relate to perceptions of distraction and problematic phone use around their child. Latent profile analysis of parents' precontemplation, contemplation, and action scores revealed two classes-precontemplators (15%) and contemplators (85%). Contemplators-those considering or desiring change-showed more bedtime phone use and general social networking than precontemplors; however, there were no significant differences between groups on other objective use measures (e.g., total daily duration of phone use, phone use around child, etc.). Contemplators also showed greater perceptions of problematic use around their child and parenting distraction. Moreover, parents' problematic use and distraction were predictive of higher contemplation scores, even after controlling for demographic and objective phone use variables. Taken together, these results suggest that perceptions of phone use as problematic may be more important than actual phone habits, especially total phone use duration, for desire to change. Suggestions for future research and intervention are provided.

A CRISPR-enhanced metagenomic NGS test to improve pandemic preparedness

The lack of preparedness for detecting and responding to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen (i.e., COVID-19) has caused enormous harm to public health and the economy. Testing strategies deployed on a population scale at day zero, i.e., the time of the first reported case, would be of significant value. Next-generation sequencing (NGS) has such capabilities; however, it has limited detection sensitivity for low-copy-number pathogens. Here, we leverage the CRISPR-Cas9 system to effectively remove abundant sequences not contributing to pathogen detection and show that NGS detection sensitivity of SARS-CoV-2 approaches that of RT-qPCR. The resulting sequence data can also be used for variant strain typing, co-infection detection, and individual human host response assessment, all in a single molecular and analysis workflow. This NGS work flow is pathogen agnostic and, therefore, has the potential to transform how large-scale pandemic response and focused clinical infectious disease testing are pursued in the future.

Analysis of Gut Microbiome Using Explainable Machine Learning Predicts Risk of Diarrhea Associated With Tyrosine Kinase Inhibitor Neratinib: A Pilot Study

Neratinib has great efficacy in treating HER2+ breast cancer but is associated with significant gastrointestinal toxicity. The objective of this pilot study was to understand the association of gut microbiome and neratinib-induced diarrhea. Twenty-five patients (age ≥ 60) were enrolled in a phase II trial evaluating safety and tolerability of neratinib in older adults with HER2+ breast cancer (NCT02673398). Fifty stool samples were collected from 11 patients at baseline and during treatment. 16S rRNA analysis was performed and relative abundance data were generated. Shannon's diversity was calculated to examine gut microbiome dysbiosis. An explainable tree-based approach was utilized to classify patients who might experience neratinib-related diarrhea (grade ≥ 1) based on pre-treatment baseline microbial relative abundance data. The hold-out Area Under Receiver Operating Characteristic and Area Under Precision-Recall Curves of the model were 0.88 and 0.95, respectively. Model explanations showed that patients with a larger relative abundance of Ruminiclostridium 9 and Bacteroides sp. HPS0048 may have reduced risk of neratinib-related diarrhea and was confirmed by Kruskal-Wallis test (p ≤ 0.05, uncorrected). Our machine learning model identified microbiota associated with reduced risk of neratinib-induced diarrhea and the result from this pilot study will be further verified in a larger study.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, identifier NCT02673398.

Abstract PS5-41: Machine learning model of gut microbiota predicts neratinib induced diarrhea in patients with breast cancer

Background: Neratinib is a potent small molecule tyrosine kinase inhibitor (TKI) of human epidermal growth factor receptors (HER1,2,4). One of the major side effects of neratinib is diarrhea. The human gut contains a dense microbiome ecosystem that is essential in maintaining a healthy host physiology, and its disruption may lead to increased risk of toxicities from cancer therapy. In this study, we aimed to develop a machine learning model based on analysis of gut microbiota data to predict neratinib-induced diarrhea.

Methods: Patients were enrolled in a phase II trial evaluating safety and tolerability of neratinib in older adults with HER2+ breast cancer (NCT02673398). Neratinib was administered as single agent, 240 mg oral daily in a 28-day cycle. Stool samples were collected at baseline and during treatment for 16S rRNA gene sequencing. Using microbial relative abundance data, we developed gradient-boosted tree models with two nested loops of cross validations to classify whether diarrhea would occur or not after treatment onset. For the inner validation loop, we used ten-fold cross validation to determine the optimal model from hyper-parameters including regularization. For the outer validation loop, we utilized a leave-one-patient-out cross validation to test this model on the hold-out patient’s baseline data and the predictions were used for model assessment.

Results: A total of 11 patients and 50 longitudinal stool samples were collected. The median age was 66 years. 73% developed grade ≥ 1 diarrhea attributed to neratinib. Shannon diversity index of gut microbiome was not associated with diarrhea. For predictive modeling, the outer validation loop Area Under the Receiver Operating Characteristic Curve (AUROC) and Area Under the Precision Recall Curve (AUPRC) were 0.92 and 0.97, respectively. The two most important taxa predictive of protection from diarrhea were Ruminiclostridium 9, and Bacteroides sp. HPS0048. We found that patients with a larger relative abundance of Ruminiclostridium 9 and Bacteroides sp. HPS0048 have reduced risk of neratinib-related diarrhea.

Conclusions: The machine learning model can identify breast cancer patients at risk of diarrhea prior to neratinib use. Future studies are required to validate this finding.

Citation Format: Chi Wah Wong, Susan E. Yost, Jin Sun Lee, John D. Gillece, Megan Folkerts, Lauren Reining, Sarah K. Highlander, Zahra Eftekhari, Joanne Mortimer, Yuan Yuan. Machine learning model of gut microbiota predicts neratinib induced diarrhea in patients with breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS5-41.

A Phase II Clinical Trial of Pembrolizumab and Enobosarm in Patients with Androgen Receptor-Positive Metastatic Triple-Negative Breast Cancer

LESSONS LEARNED

The combination of enobosarm and pembrolizumab was well tolerated and showed a modest clinical benefit rate of 25% at 16 weeks. Future trials investigating androgen receptor-targeted therapy in combination with immune checkpoint inhibitors are warranted.

BACKGROUND

Luminal androgen receptor is a distinct molecular subtype of triple-negative breast cancer (TNBC) defined by overexpression of androgen receptor (AR). AR-targeted therapy has shown modest activity in AR-positive (AR+) TNBC. Enobosarm (GTx-024) is a nonsteroidal selective androgen receptor modulator (SARM) that demonstrates preclinical and clinical activity in AR+ breast cancer. The current study was designed to explore the safety and efficacy of the combination of enobosarm and pembrolizumab in patients with AR+ metastatic TNBC (mTNBC).

METHODS

This study was an open-label phase II study for AR+ (≥10%, 1+ by immunohistochemistry [IHC]) mTNBC. Eligible patients received pembrolizumab 200 mg intravenous (IV) every 3 weeks and enobosarm 18 mg oral daily. The primary objective was to evaluate the safety of enobosarm plus pembrolizumab and determine the response rate. Peripheral blood, tumor biopsies, and stool samples were collected for correlative analysis.

RESULTS

The trial was stopped early because of the withdrawal of GTx-024 drug supply. Eighteen patients were enrolled, and 16 were evaluable for responses. Median age was 64 (range 36-81) years. The combination was well tolerated, with only a few grade 3 adverse events: one dry skin, one diarrhea, and one musculoskeletal ache. The responses were 1 of 16 (6%) complete response (CR), 1 of 16 (6%) partial response (PR), 2 of 16 (13%) stable disease (SD), and 12 of 16 (75%) progressive disease (PD). Response rate (RR) was 2 of 16 (13%). Clinical benefit rate (CBR) at 16 weeks was 4 of 16 (25%). Median follow-up was 24.9 months (95% confidence interval [CI], 17.5-30.9). Progression-free survival (PFS) was 2.6 months (95% CI, 1.9-3.1) and overall survival (OS) was 25.5 months (95% CI, 10.4-not reached [NR]).

CONCLUSION

The combination of enobosarm and pembrolizumab was well tolerated, with a modest clinical benefit rate of 25% at 16 weeks in heavily pretreated AR+ TNBC without preselected programmed death ligand-1 (PD-L1). Future clinical trials combining AR-targeted therapy with immune checkpoint inhibitor (ICI) for AR+ TNBC warrant investigation.

Randomized trial assessing impact of probiotic supplementation on gut microbiome and clinical outcome from targeted therapy in metastatic renal cell carcinoma

Studies suggest a link between the gut microbiome and metastatic renal cell carcinoma (mRCC) outcomes, including evidence that mRCC patients possess a lower abundance of Bifidobacterium spp. compared to healthy adults. We sought to assess if a Bifidobacterium‐containing yogurt product could modulate the gut microbiome and clinical outcome from vascular endothelial growth factor‐tyrosine kinase inhibitors (VEGF‐TKIs). mRCC patients initiating VEGF‐TKIs, regardless of the line of therapy, were randomized to probiotic‐supplemented (two 4 oz. servings of the probiotic yogurt product daily) or probiotic‐restricted arms. Stool samples were collected prior to therapy and at weeks 2, 3, 4, and 12. Microbiome composition was assessed using whole‐metagenome sequencing. A total of 20 patients were randomized. Bifidobacterium animalis, the active ingredient of the probiotic supplement, reached detectable levels in all patients in the probiotic‐supplemented arm versus two patients in the probiotic‐restricted arm. Clinical benefit rate was similar in probiotic‐supplemented versus probiotic‐restricted arms (70% vs. 80%, p = 0.606). Linear discriminant analysis (LDA) effect size analysis of MetaPhIAn2 abundance data predicted 25 enriched species demonstrating an LDA score >3 in either clinical benefit or no clinical benefit. In patients with clinical benefit (vs. no clinical benefit), Barnesiella intestinihominis and Akkermansia muciniphila were significantly more abundant (p = 7.4 × 10⁻⁶ and p = 5.6 × 10⁻³, respectively). This is the first prospective randomized study demonstrating modulation of the gut microbiome with a probiotic in mRCC. Probiotic supplementation successfully increased the Bifidobacterium spp. levels. Analysis of longitudinal stool specimens identified an association between B. intestinihominis, A. muciniphila, and clinical benefit with therapy.

Trial Registration: NCT02944617

Stool Microbiome Profiling of Patients with Metastatic Renal Cell Carcinoma Receiving Anti-PD-1 Immune Checkpoint Inhibitors

Preclinical models and early clinical data suggest an interplay between the gut microbiome and response to immunotherapy in solid tumors including metastatic renal cell carcinoma (mRCC). We sought to characterize the stool microbiome of mRCC patients receiving a checkpoint inhibitor (CPI) and to assess treatment-related changes in microbiome composition over the course of CPI therapy. Stool was collected from 31 patients before initiation of nivolumab (77%) or nivolumab plus ipilimumab (23%) therapy, of whom 58% experienced clinical benefit. Greater microbial diversity was associated with clinical benefit from CPI therapy (p =  0.001), and multiple species were associated with clinical benefit or lack thereof. Temporal profiling of the microbiome indicated that the relative abundance of Akkermansia muciniphila increased in patients deriving clinical benefit from CPIs. This study substantiates results from previous CPI-related microbiome profiling studies in mRCC. Temporal changes in microbiome composition suggest potential utility in modulating the microbiome for more successful CPI outcomes. PATIENT SUMMARY: We compared the composition and diversity of the gut microbiome in patients receiving immunotherapy for renal cell carcinoma. We found that higher microbial diversity is associated with better treatment outcomes. Treatment response is characterized by changes in microbial species over the course of treatment.

Involving patients as key stakeholders in the design of cardiovascular implantable electronic device data dashboards: Implications for patient care

Background

Data from remote monitoring (RM) of cardiovascular implantable electronic devices (CIEDs) currently are not accessible to patients despite demand. The typical RM report contains multiple pages of data for trained technicians to read and interpret and requires a patient-centered approach to be curated to meet individual user needs.

Objective

The purpose of this study was to understand which RM data elements are important to patients and to gain design insights for displaying meaningful data in a digital dashboard.

Methods

Adults with implantable cardioverter–defibrillators (ICDs) and pacemakers (PMs) participated in this 2-phase, user-centered design study. Phase 1 included a card-sorting activity to prioritize device data elements. Phase 2 included one-on-one design sessions to gather insights and feedback about a visual display (labels and icons).

Results

Twenty-nine adults (mean age 71.8 ± 11.6 years; 51.7% female; 89.7% white) participated. Priority data elements for both ICD and PM groups in phase 1 (n = 19) were related to cardiac episodes, device activity, and impedance values. Recommended replacement time for battery was high priority for the PM group but not the ICD group. Phase 2 (n = 10) revealed that patients would like descriptive, nontechnical terms to depict the data and icons that are intuitive and informative.

Conclusion

This user-centered design study demonstrated that patients with ICDs and PMs were able to prioritize specific data from a comprehensive list of data elements that they had never seen before. This work contributes to the goal of sharing RM data with patients in a way that optimizes the RM feature of CIEDs for improving patient outcomes and clinical care.

Abstract P5-06-26: Gut microbiome profiling of patients with metastatic breast cancer undergoing immune checkpoint inhibitor therapy

Background: Collection of fecal samples is non-invasive, and DNA sequencing of microorganisms can provide a profile of the gut microbiome which may be an indicator of general health and disease, including inflammation, digestive inefficiencies, and the presence of pathogens. The gut microbiome has been associated with response to immune checkpoint inhibitors (ICI) in patients with solid tumors. We aim to study the association of gut microbiome and response to therapy in patients with metastatic breast cancer (BC) undergoing ICI therapies.

Methods: 50 fecal samples from two ICI clinical trials (NCT02971761, N=22; NCT02778685, N=28) were collected at baseline, on treatment and at the end of treatment. DNA was extracted, and 16S rRNA gene libraries were generated targeting the variable region 4 (V4) region of the bacterial and archaeal rRNA gene. Libraries were sequenced on the Illumina MiSeq and sequence reads were analyzed using QIIME2.

Results: A total of 22 dominant taxa (present ≥5% in any one sample) were identified in samples from 12 triple negative BC patients treated with pembrolizumab + GTx-024 (Enobosarm) and 17 dominant taxa were identified taxa 10 ER+ BC patients treated with pembrolizumab, letrozole, and palbociclib. As is true for most microbiome studies, inter-subject variation was much greater than intra-subject variation. However, in some patients there was a significant change in the composition of the microbial communities over time. In the first study, two patients had partial response (PR) to treatment and both had relatively “healthy” gut microbiota dominated by Bacteroides, Faecalibacterium prausnitzii, and other short chain fatty acid producers like Ruminococcus bromii or Roseburia faecis. Most of the patients who progressed had dysbiotic gut microbiomes and four had very high (≥20%) relative abundance of Prevotella copri, an organism associated with inflammation. In the second study, four patients had PR, and as before, these patients had “healthy” gut signatures dominated by Bacteroides and short chain fatty acid-producing Firmicutes. In one of these patients, a high level of Prevotella stercorea (57%)at baseline was replaced by Bacteroides and Lachnospira as treatment proceeded. Three additional patients had very high levels of P. copri (≥34%); one resolved during treatment, the others did not. Shannon’s diversity index was used to measure abundance and evenness in the fecal communities. Several samples in both studies had very low diversity at baseline. In most cases, the diversity increased following treatment.

Conclusion: Most patients who progressed on ICI had dysbiotic gut microbiomes present at baseline and later time points, such as a high relative abundance of Prevotella (implicated in inflammatory processes); this often resolved during therapy. Our observations provide promise for future use of the gut microbiome as a predictor of response to immunotherapy for BC and the potential for modulating the gut microbiome to improve responses in patients with dysbiosis.

Citation Format: Yuan Yuan, Sarah Highlander, Susan E Yost, Kim Robinson, Simran Padam, Aileen Tang, Norma Martinez, John Gillece, Lauren Reining, Mina Sedrak, Joanne Mortimer, James Waisman. Gut microbiome profiling of patients with metastatic breast cancer undergoing immune checkpoint inhibitor therapy [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-06-26.

Teens Using Screens for Help: Impact of Suicidal Ideation, Anxiety, and Depression Levels on Youth Preferences for Telemental Health Resources

BACKGROUND

High rates of mental illness, stress, and suicidality among teens constitute a major public health concern in the United States. However, treatment rates remain low, partially because of barriers that could be mitigated with tech-based telemental health (TMH) resources, separate from or in addition to traditional care.

OBJECTIVE

This study aimed to analyze TMH resource usage by high school students to establish current user characteristics and provide a framework for future development.

METHODS

A total of 2789 students were surveyed regarding demographics, recent anxiety and depression symptoms, suicidality, and stress; people with whom they could openly and honestly discuss stress or problems, and prior TMH use. Logistic regression models and a general linear model were used to test relationships between variables.

RESULTS

Overall, 30.58% (853/2789) and 22.91% (639/2789) of students reported moderate to severe anxiety and depression symptoms, respectively, in the past 2 weeks; 16.24% (414/2550) had seriously considered suicide in the past year, consistent with national averages. Meanwhile, 16.03% (447/2789) of students had previously used at least 1 of 4 types of TMH resources (ie, self-help, anonymous chat, online counselor, or crisis text line). Teens reporting depression symptoms, higher stress, or suicidality were less likely to talk to a parent about stress or problems and more likely to tell no one. Suicidality was related to the use of all 4 types of TMH resources. Depression symptoms were related to the use of anonymous chat and crisis text line, and those with higher stress were more likely to have used an online counselor. Those reporting anxiety symptoms were less likely to have no one to talk to and more likely to have used a self-help resource.

CONCLUSIONS

Youth struggling with mental health symptoms, some of whom lack real-life confidants, are using existing TMH support, with resource preferences related to symptoms. Future research should consider these preferences and assist in the creation of specialized, evidence-based TMH resources.

Ab initio calculation of optical spectra of liquids: many-body effects in the electronic excitations of water

We present ab initio calculations of the excited state properties of liquid water in the framework of many-body Green's function formalism. Snapshots taken from molecular dynamics simulations are used as input geometries to calculate electronic and optical spectra, and the results are averaged over the different configurations. The optical absorption spectra with the inclusion of excitonic effects are calculated by solving the Bethe-Salpeter equation. The insensitivity of screening effects to a particular configuration make these calculations feasible. The resulting spectra, which are strongly modified by many-body effects, are in good agreement with experiments.

Excitonic effects on the silicon plasmon resonance

We present an ab initio calculation of the electron energy loss spectrum of silicon including local-field, self-energy, and excitonic effects. When self-energy corrections are added to the standard random phase approximation (RPA) the line shape of the plasmon resonance worsens. The electron-hole interaction cancels this correction and improves the result both compared to the RPA and to the self-energy one, yielding very good agreement between theory and experiment provided that the mixing of interband transitions of both positive and negative frequencies is included.