Predicting health outcomes with intensive longitudinal data collected by mobile health devices: a functional principal component regression approach.

BACKGROUND: Intensive longitudinal data (ILD) collected in near real time by mobile health devices provide a new opportunity for monitoring chronic diseases, early disease risk prediction, and disease prevention in health research. Functional data analysis, specifically functional principal component analysis, has great potential to abstract trends in ILD but has not been used extensively in mobile health research. OBJECTIVE: To introduce functional principal component analysis (fPCA) and demonstrate its potential applicability in estimating trends in ILD collected by mobile heath devices, assessing longitudinal association between ILD and health outcomes, and predicting health outcomes. METHODS: fPCA and scalar-to-function regression models were reviewed. A case study was used to illustrate the process of abstracting trends in intensively self-measured blood glucose using functional principal component analysis and then predicting future HbA1c values in patients with type 2 diabetes using a scalar-to-function regression model. RESULTS: Based on the scalar-to-function regression model results, there was a slightly increasing trend between daily blood glucose measures and HbA1c. 61% of variation in HbA1c could be predicted by the three preceding months' blood glucose values measured before breakfast (P < 0.0001, [Formula: see text]). CONCLUSIONS: Functional data analysis, specifically fPCA, offers a unique tool to capture patterns in ILD collected by mobile health devices. It is particularly useful in assessing longitudinal dynamic association between repeated measures and outcomes, and can be easily integrated in prediction models to improve prediction precision.

A novel causal mediation analysis approach for zero-inflated mediators.

Mediation analyses play important roles in making causal inference in biomedical research to examine causal pathways that may be mediated by one or more intermediate variables (ie, mediators). Although mediation frameworks have been well established such as counterfactual-outcomes (ie, potential-outcomes) models and traditional linear mediation models, little effort has been devoted to dealing with mediators with zero-inflated structures due to challenges associated with excessive zeros. We develop a novel mediation modeling approach to address zero-inflated mediators containing true zeros and false zeros. The new approach can decompose the total mediation effect into two components induced by zero-inflated structures: the first component is attributable to the change in the mediator on its numerical scale which is a sum of two causal pathways and the second component is attributable only to its binary change from zero to a non-zero status. An extensive simulation study is conducted to assess the performance and it shows that the proposed approach outperforms existing standard causal mediation analysis approaches. We also showcase the application of the proposed approach to a real study in comparison with a standard causal mediation analysis approach.

Computed tomography-based radiomics quantification predicts epidermal growth factor receptor mutation status and efficacy of first-line targeted therapy in lung adenocarcinoma.

Background: Biomarkers that predict the efficacy of first-line tyrosine kinase inhibitors (TKIs) are pivotal in epidermal growth factor receptor (EGFR) mutant advanced lung adenocarcinoma. Imaging-based biomarkers have attracted much attention in anticancer therapy. This study aims to use the machine learning method to distinguish EGFR mutation status and further explores the predictive role of EGFR mutation-related radiomics features in response to first-line TKIs. Methods: We retrospectively analyzed pretreatment CT images and clinical information from a cohort of lung adenocarcinomas. We entered the top-ranked features into a support vector machine (SVM) classifier to establish a radiomics signature that predicted EGFR mutation status. Furthermore, we identified the best response-related features based on EGFR mutant-related features in first-line TKI therapy patients. Then we test and validate the predictive effect of the best response-related features for progression-free survival (PFS). Results: Six hundred ninety-two patients were enrolled in building radiomics signatures. The 13 top-ranked features were input into an SVM classifier to establish the radiomics signature of the training cohort (n = 514), and the predictive score of the radiomics signature was assessed on an independent validation group with 178 patients and obtained an area under the curve (AUC) of 74.13%, an F1 score of 68.29%, a specificity of 79.55%, an accuracy of 70.79%, and a sensitivity of 62.22%. More importantly, the skewness-Low (≤0.882) or 10th percentile-Low group (≤21.132) had a superior partial response (PR) rate than the skewness-High or 10th percentile-High group (p < 0.01). Higher skewness (hazard ratio (HR) = 1.722, p = 0.001) was also found to be significantly associated with worse PFS. Conclusions: The radiomics signature can be used to predict EGFR mutation status. Skewness may contribute to the stratification of disease progression in lung cancer patients treated with first-line TKIs.

Comprehensive Characterization of the Genomic Landscape in Chinese Pulmonary Neuroendocrine Tumors Reveals Prognostic and Therapeutic Markers (CSWOG-1901).

BACKGROUND: Pulmonary neuroendocrine tumors (pNETs) include typical carcinoid (TC), atypical carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC), and small cell lung carcinoma (SCLC). The optimal treatment strategy for each subtype remains elusive, partly due to the lack of comprehensive understanding of their molecular features. We aimed to explore differential genomic signatures in pNET subtypes and identify potential prognostic and therapeutic biomarkers. METHODS: We investigated genomic profiles of 57 LCNECs, 49 SCLCs, 18 TCs, and 24 ACs by sequencing tumor tissues with a 520-gene panel and explored the associations between genomic features and prognosis. RESULTS: Both LCNEC and SCLC displayed higher mutation rates for TP53, PRKDC, SPTA1, NOTCH1, NOTCH2, and PTPRD than TC and AC. Small cell lung carcinoma harbored more frequent co-alterations in TP53-RB1, alterations in PIK3CA and SOX2, and mutations in HIF-1, VEGF and Notch pathways. Large cell neuroendocrine carcinoma (12.7 mutations/Mb) and SCLC (11.9 mutations/Mb) showed higher tumor mutational burdens than TC (2.4 mutations/Mb) and AC (7.1 mutations/Mb). 26.3% of LCNECs and 20.8% of ACs harbored alterations in classical non-small cell lung cancer driver genes. The presence of alterations in the homologous recombination pathway predicted longer progression-free survival in advanced LCNEC patients with systemic therapy (P = .005) and longer overall survival (OS) in SCLC patients with resection (P = .011). The presence of alterations in VEGF (P = .048) and estrogen (P = .018) signaling pathways both correlated with better OS in patients with resected SCLC. CONCLUSION: We performed a comprehensive genomic investigation on 4 pNET subtypes in the Chinese population. Our data revealed distinctive genomic signatures in subtypes and provided new insights into the prognostic and therapeutic stratification of pNETs.

Clinical and genomic features of Chinese lung cancer patients with germline mutations.

The germline mutation landscape in Chinese lung cancer patients has not been well defined. In this study, sequencing data of 1,021 cancer genes of 1,794 Chinese lung cancer patients was analyzed. A total of 111 pathogenic or likely pathogenic germline mutations were identified, significantly higher than non-cancer individuals (111/1794 vs. 84/10,588, p < 2.2e-16). BRCA1/2 germline mutations are associated with earlier onset age (median 52.5 vs 60 years-old, p = 0.008). Among 29 cancer disposition genes with germline mutations detected in Chinese cohort and/or TCGA lung cancer cohort, Only 11 from 29 genes are identified in both cohorts and BRCA2 mutations are significantly more common in Chinese cohort (p = 0.015). Chinese patients with germline mutations have different prevalence of somatic KRAS, MET exon 14 skipping and TP53 mutations compared to those without. Our findings suggest potential ethnic and etiologic differences between Western and Asian lung cancer patients.

Getting Creative: Pilot Study of a Coached Writing Intervention in Patients with Advanced Cancer at a Rural Academic Medical Center.

Background: Unfacilitated writing activities, such as expressive writing, have not shown benefit in people with advanced cancer, but facilitated writing activities have yet to be fully explored. Objectives: To assess the feasibility and acceptability of facilitated writing activities determined by a writing coach in people with advanced incurable cancer. Design: This is a single-arm pilot study. Settings/Subjects: Adult patients with advanced incurable solid malignancies from a U.S. rural comprehensive cancer program met with a writing coach monthly for at least three months for facilitated writing activities. Measurements: Feasibility was assessed by enrollment and postinclusion attrition rate. Acceptability was assessed by (1) <15% drop out rate due to the intervention, (2) <15% elevated anxiety or depression due to the intervention, and (3) patient qualitative comments. Results: In total, 22 out of 63 patients consented (35%). Postinclusion attrition rate was 18% (n = 4) at three months with 82% completing at least three months of the writing coach intervention. No participants dropped out or had elevated anxiety/depression due to the intervention. The majority of patients wanted the whole intervention continued. Conclusions: A writing coach using facilitated writing activities was feasible and acceptable in patients with advanced incurable cancer, but further studies are needed to assess impact. Clinical Trial Registration Number NCT 025 75898.

Severe Pain Profiles and Associated Sociodemographic and Clinical Characteristics in Individuals With Sickle Cell Disease.

OBJECTIVE: The aim of this study was to identify classes of individuals with sickle cell disease (SCD) who share distinct severe pain profiles and evaluate differences in demographic, clinical, and psychosocial characteristics between classes. METHODS: This exploratory, cross-sectional study used data collected for the SCD Implementation Consortium Research Registry at Duke University. Using Adult Sickle Cell Quality of Life-Measurement System pain-item data from 291 adults with SCD, latent class analysis was used to determine classes of individuals sharing distinct severe pain profiles. Bivariate analyses and logistic regression models were used to assess the relationships between pain profile classes and demographic, clinical, and psychosocial characteristics. RESULTS: Three classes sharing distinct severe pain profiles were identified: Low Frequency and Impact class (n=73), Moderate Frequency and Impact class (n=94), and High Frequency and Impact class (n=124). When compared with the Low Frequency and Impact class and controlling for age and sex, individuals in the Moderate Frequency and Impact class were more likely to: be female (P=0.031) and unemployed (P=0.013); report worse sleep (P=0.005) and social functioning (P=0.005); have less emotional distress (P=0.004); describe pain as "sore" (P=0.002); and have previous SCD-related lung complications (P=0.016). When compared with the Low Frequency and Impact class, individuals in the High Frequency and Impact class: had worse social functioning (P<0.001) and previous SCD-related lung complications (P=0.006); described pain as "sore" (P<0.001); and were taking pain medication daily for SCD (P=0.001). DISCUSSION: Severe pain experiences in SCD are complex; however, there are subgroups of people who report similar experiences of severe pain.

[Research Progress of Anti-angiogenic Agents Combined with Immunotherapy 
in Patients with Advanced Non-small Cell Lung Cancer].

Lung cancer has the highest incidence rate and mortality in China, even in the world, and non-small cell lung cancer (NSCLC) accounts for about 85%. The growth and metastasis of tumor depend on the generation of blood vessels, and anti-angiogenic therapy is playing an increasingly important role, however, no significant improvement was observed in the underwent anti-angiogenic agents used for patients alone. In recent years, the application of immune checkpoint inhibitor (ICI) has significantly improved the prognosis of some lung cancer patients, however, the objective response rate of patients receiving ICI alone is low. While anti-angiogenic agents and ICI both regulate the tumor immune microenvironment and have a potential synergistic mechanism, showing a bright prospect in the combined application of anti-tumor therapy. In this review, we focused on the research and application of anti-angiogenic agents in combination with ICI in advanced non-small cell lung cancer.

Perceptions of Using Multiple Mobile Health Devices to Support Self-Management Among Adults With Type 2 Diabetes: A Qualitative Descriptive Study.

PURPOSE: This study identified facilitators and barriers pertaining to the use of multiple mobile health (mHealth) devices (Fitbit Alta® fitness tracker, iHealth® glucometer, BodyTrace® scale) that support self-management behaviors in individuals with type 2 diabetes mellitus (T2DM). DESIGN: This qualitative descriptive study presents study participants' perceptions of using multiple mobile devices to support T2DM self-management. Additionally, this study assessed whether participants found visualizations, generated from each participant's health data as obtained from the three separate devices, useful and easy to interpret. METHODS: Semistructured interviews were completed with a convenience sample of participants (n = 20) from a larger randomized control trial on T2DM self-management. Interview questions focused on participants' use of three devices to support T2DM self-management. A study team member created data visualizations of each interview participant's health data using RStudio. RESULTS: We identified two themes from descriptions of study participants: feasibility and usability. We identified one theme about visualizations created from data obtained from the mobile devices. Despite some challenges, individuals with T2DM found it feasible to use multiple mobile devices to facilitate engagement in T2DM self-management behaviors. DISCUSSION: As mHealth devices become increasingly popular for diabetes self-management and are integrated into care delivery, we must address issues associated with the use of multiple mHealth devices and the use of aggregate data to support T2DM self-management. CLINICAL RELEVANCE: Real-time patient-generated health data that are easily accessible and readily available can assist T2DM self-management and catalyze conversations, leading to better self-management. Our findings lay an important groundwork for understanding how individuals with T2DM can use multiple mHealth devices simultaneously to support self-management.

Dacomitinib induces objective responses in metastatic brain lesions of patients with EGFR-mutant non-small-cell lung cancer: A brief report.

OBJECTIVE: Dacomitinib is a potent, irreversible and pan-HER tyrosine kinase inhibitor (TKI) of epidermal growth factor receptor (EGFR) mutant non-small cell lung cancer (NSCLC). Currently, evidence of its activity on brain metastasis is lacking. MATERIALS AND METHODS: NSCLC patients diagnosed at Hunan Cancer Hospital between July, 2019 and July, 2020 with enhanced MRI-detected brain metastasis prior to treatment and laboratory-confirmed EGFR mutations were reviewed. In total, 14 EGFR-mutant NSCLC patients with brain metastasis were treated with first-line dacomitinib. The first radiographic review of chest CT and brain MRI was after one month and thereafter every 2 months. The objective response rate (ORR) and the depth of the brain metastasis response were determined via RECIST 1.1 and RANO-LM criteria. RESULTS: In total, 14 of 59 EGFR-mutant advanced NSCLC patients who received first-line dacomitinib therapy had brain metastasis before treatment. Among these patients, 5 were given a dacomitinib starting dose of 45 mg once daily, while 9 received 30 mg daily until disease progression or unbearable toxicity. Eight patients harbored EGFR 19del, 5 had EGFR L858R, and one patient had EGFR G719A and I706 T co-mutations. The median duration of follow-up was 4.5 months. All patients received at least one review. The ORR was 92.9 % (13/14) and the disease control rate (DCR) was 100 %. A measurable response of the intracranial metastases was observed in 12 of 14 patients (85.7 %), including 12 of 13 (92.3 %) with brain parenchymal metastasis, but the one patient with meningeal metastasis did not respond well. All patients (100 %) had grade 1-2 adverse effects, but none discontinued treatment or required a dosage adjustment. CONCLUSIONS: This case series study of 14 patients has shown that dacomitinib has potent efficacy for central nervous system (CNS) metastasis in EGFR-positive NSCLC. More data are required to confirm its advantages and optimize its clinical application.

Co-delivery of paclitaxel and anti-VEGF siRNA by tripeptide lipid nanoparticle to enhance the anti-tumor activity for lung cancer therapy.

The combination of chemotherapeutic drug paclitaxel (PTX) and VEGF siRNA could inhibit cancer development with synergistic efficacy. However, efficient and safe delivery systems with high encapsulation efficiency of PTX and a long-time release of drugs are urgently needed. In this study, novel nanoparticles (PTX/siRNA/FALS) were constructed by using tripeptide lipid (L), sucrose laurate (S), and folate-PEG2000-DSPE (FA) to co-deliver PTX and siRNA. The cancer cell targeting nanoparticle carrier (PTX/siRNA/FALS) showed anticipated PTX encapsulation efficiency, siRNA retardation ability, improved cell uptake and sustained and controlled drug release. It led to significant anti-tumor activity in vitro and in vivo by efficient inhibition of VEGF expression and induction of cancer cell apoptosis. Importantly, the biocompatibility of the carriers and low dosage of PTX required for effective therapy greatly reduced the toxicity to mice. The targeting nanoparticles show potential as an effective co-delivery platform for RNAi and chemotherapy drugs, aiming to improve the efficacy of cancer therapy.

Peripheral Blood Biomarkers Associated With Outcome in Non-small Cell Lung Cancer Patients Treated With Nivolumab and Durvalumab Monotherapy.

Background: Selecting patients who potentially benefit from immune checkpoint inhibitors (ICIs) is critical. Programmed death ligand-1 (PD-L1) protein immunohistochemical expression on cancer cells or immune cells and next-generation sequencing-based tumor mutational burden (TMB) are hot spots in studies on ICIs, but there is still confusion in the testing methods. Because blood samples are much easier for clinical application, many potential peripheral biomarkers have been proposed. This study identified blood parameters associated with the outcome of non-small cell lung cancer (NSCLC) patients with ICI monotherapy. Materials and Methods: Data from 76 NSCLC patients were analyzed retrospectively. To assess the connection between survival and peripheral blood markers measured before the first and fifth doses of ICI treatment, we utilized Cox regression model survival analysis and receiver operating characteristic (ROC) curve analysis to assess the markers. Results: In the nivolumab cohort, the optimal cutoffs for predicting 11-month overall survival (OS) were 168.13 and 43 g/L for platelet-to-lymphocyte ratio (PLR) and albumin, respectively. When patients were grouped with PLR and albumin, a significant difference in SD-PR vs. PD rate was found between the high and low groups, which was not found when the patients were grouped by PD-L1 expression. Patients with high PLR (>168.13) or low albumin ( ≤ 43 g/L) before ICI had a significantly increased hazard of progression, separately (for PLR, P = 0.006; for albumin, P = 0.033), and of death (for PLR, P = 0.014; for albumin, P = 0.009) compared with those patients who had low PLR or albumin levels. More importantly, we found that a higher PLR (>168.13) before the fifth dose of ICIs was also a prognostic biomarker, which significantly correlated with shorter OS in both the nivolumab (P = 0.046) and durvalumab cohorts (P = 0.028). Conclusions: PLR and albumin may help in the stratification of high progression and death risk groups in advanced NSCLC patients treated with nivolumab and durvalumab monotherapy.

Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis.

BACKGROUND: Sustained self-monitoring and self-management behaviors are crucial to maintain optimal health for individuals with type 2 diabetes mellitus (T2DM). As smartphones and mobile health (mHealth) devices become widely available, self-monitoring using mHealth devices is an appealing strategy in support of successful self-management of T2DM. However, research indicates that engagement with mHealth devices decreases over time. Thus, it is important to understand engagement trajectories to provide varying levels of support that can improve self-monitoring and self-management behaviors. OBJECTIVE: The aims of this study were to develop (1) digital phenotypes of the self-monitoring behaviors of patients with T2DM based on their engagement trajectory of using multiple mHealth devices, and (2) assess the association of individual digital phenotypes of self-monitoring behaviors with baseline demographic and clinical characteristics. METHODS: This longitudinal observational feasibility study included 60 participants with T2DM who were instructed to monitor their weight, blood glucose, and physical activity using a wireless weight scale, phone-tethered glucometer, and accelerometer, respectively, over 6 months. We used latent class growth analysis (LCGA) with multitrajectory modeling to associate the digital phenotypes of participants' self-monitoring behaviors based on their engagement trajectories with multiple mHealth devices. Associations between individual characteristics and digital phenotypes on participants' self-monitoring behavior were assessed by analysis of variance or the Chi square test. RESULTS: The engagement with accelerometers to monitor daily physical activities was consistently high for all participants over time. Three distinct digital phenotypes were identified based on participants' engagement with the wireless weight scale and glucometer: (1) low and waning engagement group (24/60, 40%), (2) medium engagement group (20/60, 33%), and (3) consistently high engagement group (16/60, 27%). Participants that were younger, female, nonwhite, had a low income, and with a higher baseline hemoglobin A1c level were more likely to be in the low and waning engagement group. CONCLUSIONS: We demonstrated how to digitally phenotype individuals' self-monitoring behavior based on their engagement trajectory with multiple mHealth devices. Distinct self-monitoring behavior groups were identified. Individual demographic and clinical characteristics were associated with different self-monitoring behavior groups. Future research should identify methods to provide tailored support for people with T2DM to help them better monitor and manage their condition. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/13517.

[Research Progress of Immunotherapy and Prognostic Markers in Small Cell Lung Cancer].

The efficacy of non-small cell lung cancer (NSCLC) has been obviously improved recent years, while the survival of small cell lung cancer (SCLC) patients remains inferior for limit treatment options. The incidence of SCLC accounts for 15% of the overall incidence of lung cancer, and it is characterized with high malignancy, rapid growth, early widespread metastasis, making it very difficult to treat. With the approval of immunotherapy for a variety of solid tumors including NSCLC, as a relatively immunogenic cancer species, relevant clinical researchs on SCLC are also underway and have made certain progress. More importantly, due to the existence of tumor heterogeneity, exploring relevant markers that can predict the efficacy of SCLC is essential for accurate therapy. This review describes the latest advances in SCLC immunotherapy and biomarkers related to the efficacy of immunotherapy.

Enhancing Diabetes Self-Management Through Collection and Visualization of Data From Multiple Mobile Health Technologies: Protocol for a Development and Feasibility Trial.

BACKGROUND: Self-management is integral for control of type 2 diabetes mellitus (T2DM). Patient self-management is improved when they receive real-time information on their health status and behaviors and ongoing facilitation from health professionals. However, timely information for these behaviors is notably absent in the health care system. Providing real-time data could help improve patient understanding of the dynamics of their illness and assist clinicians in developing targeted approaches to improve health outcomes and in delivering personalized care when and where it is most needed. Mobile technologies (eg, wearables, apps, and connected scales) have the potential to make these patient-provider interactions a reality. What strategies might best help patients overcome self-management challenges using self-generated diabetes-related data? How might clinicians effectively guide patient self-management with the advantage of real-time data? OBJECTIVE: This study aims to describe the protocol for an ongoing study (June 2016-May 2019) that examines trajectories of symptoms, health behaviors, and associated challenges among individuals with T2DM utilizing multiple mobile technologies, including a wireless body scale, wireless glucometer, and a wrist-worn accelerometer over a 6-month period. METHODS: We are conducting an explanatory sequential mixed methods study of 60 patients with T2DM recruited from a primary care clinic. Patients were asked to track relevant clinical data for 6 months using a wireless body scale, wireless glucometer, a wrist-worn accelerometer, and a medication adherence text message (short message service, SMS) survey. Data generated from the devices were then analyzed and visualized. A subset of patients is currently being interviewed to discuss their challenges and successes in diabetes self-management, and they are being shown visualizations of their own data. Following the data collection period, we will conduct interviews with study clinicians to explore ways in which they might collaborate with patients. RESULTS: This study has received regulatory approval. Patient enrollment ongoing with a sample size of 60 patients is complete, and up to 20 clinicians will be enrolled. At the patient level, data collection is complete, but data analysis is pending. At the clinician level, data collection is currently ongoing. CONCLUSIONS: This study seeks to expand the use of mobile technologies to generate real-time data to enhance self-management strategies. It also seeks to obtain both patient and provider perspectives on using real-time data to develop algorithms for software that will facilitate real-time self-management strategies. We expect that the findings of this study will offer important insight into how to support patients and providers using real-time data to manage a complex chronic illness. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13517.

Effect of enrofloxacin and roxarsone on CYP450s in pig.

Enrofloxacin (ENR) and roxarsone (ROX) have been widely used in animal breeding. In this study, the daily clinical dosage of ENR and daily additive amount of ROX were administrated to Bama pigs. After 5days, the activity and protein expression of three important enzymes in the cytochrome P450 family were measured in the porcine liver. CYP1A2 was induced by both ENR and ROX independently. CYP2E1 and CYP3A4 were inhibited by ENR, but not affected by ROX. The combined administration of ENR and ROX were antagonistic to CYP1A2 and CYP2E1, but not to CYP3A4. Drug-drug interactions should be considered during the administration of ENR, ROX and for their co-administration with other drugs to minimize adverse reactions.