User Preferences and Needs for Health Data Collection Using Research Electronic Data Capture: Survey Study.

BACKGROUND: Self-administered web-based questionnaires are widely used to collect health data from patients and clinical research participants. REDCap (Research Electronic Data Capture; Vanderbilt University) is a global, secure web application for building and managing electronic data capture. Unfortunately, stakeholder needs and preferences of electronic data collection via REDCap have rarely been studied. OBJECTIVE: This study aims to survey REDCap researchers and administrators to assess their experience with REDCap, especially their perspectives on the advantages, challenges, and suggestions for the enhancement of REDCap as a data collection tool. METHODS: We conducted a web-based survey with representatives of REDCap member organizations in the United States. The survey captured information on respondent demographics, quality of patient-reported data collected via REDCap, patient experience of data collection with REDCap, and open-ended questions focusing on the advantages, challenges, and suggestions to enhance REDCap's data collection experience. Descriptive and inferential analysis measures were used to analyze quantitative data. Thematic analysis was used to analyze open-ended responses focusing on the advantages, disadvantages, and enhancements in data collection experience. RESULTS: A total of 207 respondents completed the survey. Respondents strongly agreed or agreed that the data collected via REDCap are accurate (188/207, 90.8%), reliable (182/207, 87.9%), and complete (166/207, 80.2%). More than half of respondents strongly agreed or agreed that patients find REDCap easy to use (165/207, 79.7%), could successfully complete tasks without help (151/207, 72.9%), and could do so in a timely manner (163/207, 78.7%). Thematic analysis of open-ended responses yielded 8 major themes: survey development, user experience, survey distribution, survey results, training and support, technology, security, and platform features. The user experience category included more than half of the advantage codes (307/594, 51.7% of codes); meanwhile, respondents reported higher challenges in survey development (169/516, 32.8% of codes), also suggesting the highest enhancement suggestions for the category (162/439, 36.9% of codes). CONCLUSIONS: Respondents indicated that REDCap is a valued, low-cost, secure resource for clinical research data collection. REDCap's data collection experience was generally positive among clinical research and care staff members and patients. However, with the advancements in data collection technologies and the availability of modern, intuitive, and mobile-friendly data collection interfaces, there is a critical opportunity to enhance the REDCap experience to meet the needs of researchers and patients.

Care Fragmentation, Faulty Communication, and Documentation Lapses Derail a Treatment Plan.

This is the second Cancer Morbidity, Mortality, and Improvement Rounds, a series of articles intended to explore the unique safety risks experienced by oncology patients through the lens of quality improvement, systems and human factors engineering, and cognitive psychology. This case describes the care of a patient who was diagnosed with locally advanced lung cancer during the COVID-19 pandemic; it highlights how gaps in communication and care coordination caused the patient to receive care that did not reflect the consensus of his multidisciplinary team. The discussion highlights the importance of multidisciplinary care, particularly for patients with stage III non-small-cell lung cancer, discusses factors that led to communication gaps, and examines how we should assign accountability across dispersed health care systems.Cancer Morbidity, Mortality, and Improvement Rounds is a series of articles intended to explore the unique safety risks experienced by oncology patients through the lens of quality improvement, systems and human factors engineering, and cognitive psychology. For purposes of clarity, each case focuses on a single theme, although, as is true for all medical incidents, there are almost always multiple, overlapping, contributing factors. The quality improvement paradigm used here, which focuses on root cause analyses and opportunities to improve care delivery systems, was previously outlined in this journal.

Virtual conversational agents versus online forms: Patient experience and preferences for health data collection.

Objective: Virtual conversational agents, or chatbots, have emerged as a novel approach to health data collection. However, research on patient perceptions of chatbots in comparison to traditional online forms is sparse. This study aimed to compare and assess the experience of completing a health assessment using a chatbot vs. an online form. Methods: A counterbalanced, within-subject experimental design was used with participants recruited via Amazon Mechanical Turk (mTurk). Participants completed a standardized health assessment using a chatbot (i.e., Dokbot) and an online form (i.e., REDCap), each followed by usability and experience questionnaires. To address poor data quality and preserve integrity of mTurk responses, we employed a thorough data cleaning process informed by previous literature. Quantitative (descriptive and inferential statistics) and qualitative (thematic analysis and complex coding query) approaches were used for analysis. Results: A total of 391 participants were recruited, 185 of whom were excluded, resulting in a final sample size of 206 individuals. Most participants (69.9%) preferred the chatbot over the online form. Average Net Promoter Score was higher for the chatbot (NPS = 24) than the online form (NPS = 13) at a statistically significant level. System Usability Scale scores were also higher for the chatbot (i.e. 69.7 vs. 67.7), but this difference was not statistically significant. The chatbot took longer to complete but was perceived as conversational, interactive, and intuitive. The online form received favorable comments for its familiar survey-like interface. Conclusion: Our findings demonstrate that a chatbot provided superior engagement, intuitiveness, and interactivity despite increased completion time compared to online forms. Knowledge of patient preferences and barriers will inform future design and development of recommendations and best practice for chatbots for healthcare data collection.

An Evaluation of a Community-Based Psycho-Educational Program for Users of Child Sexual Exploitation Material.

Online sexual offenders represent an increasingly large proportion of all sexual offenders. Many of these offenders receive noncustodial sentences, and there is a growing need for community-based interventions. The aim of this study was to evaluate a psycho-educational program for community dwelling users of child sexual exploitation material (CSEM). A total of 92 adult male participants completed self-report measures at pre and post. A subset of participants also completed measures after a follow-up period. Results suggested benefits across depression, anxiety, and stress; social competency, including locus of control and self-esteem; and distorted attitudes. Furthermore, these effects remained 8 to 12 weeks following program completion. Our results suggest that CSEM users are amenable to treatment in the community and that there are beneficial outcomes in affective and interpersonal functioning following psycho-education. These factors represent treatment targets for sexual offenders and are recognized risk factors for contact sexual offense recidivism.

Algorithms in the First-Line Treatment of Metastatic Clear Cell Renal Cell Carcinoma--Analysis Using Diagnostic Nodes.

BACKGROUND: With the advent of targeted therapies, many treatment options in the first-line setting of metastatic clear cell renal cell carcinoma (mccRCC) have emerged. Guidelines and randomized trial reports usually do not elucidate the decision criteria for the different treatment options. In order to extract the decision criteria for the optimal therapy for patients, we performed an analysis of treatment algorithms from experts in the field. MATERIALS AND METHODS: Treatment algorithms for the treatment of mccRCC from experts of 11 institutions were obtained, and decision trees were deduced. Treatment options were identified and a list of unified decision criteria determined. The final decision trees were analyzed with a methodology based on diagnostic nodes, which allows for an automated cross-comparison of decision trees. The most common treatment recommendations were determined, and areas of discordance were identified. RESULTS: The analysis revealed heterogeneity in most clinical scenarios. The recommendations selected for first-line treatment of mccRCC included sunitinib, pazopanib, temsirolimus, interferon-α combined with bevacizumab, high-dose interleukin-2, sorafenib, axitinib, everolimus, and best supportive care. The criteria relevant for treatment decisions were performance status, Memorial Sloan Kettering Cancer Center risk group, only or mainly lung metastases, cardiac insufficiency, hepatic insufficiency, age, and "zugzwang" (composite of multiple, related criteria). CONCLUSION: In the present study, we used diagnostic nodes to compare treatment algorithms in the first-line treatment of mccRCC. The results illustrate the heterogeneity of the decision criteria and treatment strategies for mccRCC and how available data are interpreted and implemented differently among experts. IMPLICATIONS FOR PRACTICE: The data provided in the present report should not be considered to serve as treatment recommendations for the management of treatment-naïve patients with multiple metastases from metastatic clear cell renal cell carcinoma outside a clinical trial; however, the data highlight the different treatment options and the criteria used to select them. The diversity in decision making and how results from phase III trials can be interpreted and implemented differently in daily practice are demonstrated.

The high-dose aldesleukin "select" trial: a trial to prospectively validate predictive models of response to treatment in patients with metastatic renal cell carcinoma.

PURPOSE: High-dose aldesleukin (HD IL2) received FDA approval for the treatment of metastatic renal cell carcinoma (MRCC) in 1992, producing a 14% objective response rate (ORR) and durable remissions. Retrospective studies suggested that clinical and pathologic features could predict for benefit. The Cytokine Working Group conducted this prospective trial to validate proposed predictive markers of response to HD IL2. EXPERIMENTAL DESIGN: Standard HD IL2 was administered to prospectively evaluate whether the ORR of patients with mRCC with "good" predictive pathologic features based on an "integrated selection" model [ISM (e.g., clear-cell histology subclassification and carbonic anhydrase-9 (CA-9) IHC staining] was significantly higher than the ORR of a historical, unselected population. Archived tumor was collected for pathologic analysis including tumor programmed death-ligand 1 (PD-L1) expression. RESULTS: One hundred and twenty eligible patients were enrolled between June 11 and September 7; 70% were Memorial Sloan Kettering Cancer Center (New York, NY) intermediate risk, 96% had clear cell RCC, and 99% had prior nephrectomy. The independently assessed ORR was 25% (30/120, 95% CI, 17.5%-33.7%, P = 0.0014; 3 complete responses, 27 partial responses) and was higher than a historical ORR. Thirteen patients (11%) remained progression free at 3 years and the median overall survival was 42.8 months. ORR was not statistically different by ISM classification ("good-risk" 23% vs. "poor-risk" 30%; P = 0.39). ORR was positively associated with tumor PD-L1 expression (P = 0.01) by IHC. CONCLUSIONS: In this prospective, biomarker validation study, HD IL2 produced durable remissions and prolonged survival in both "good" and "poor-risk" patients. The proposed ISM was unable to improve the selection criteria. Novel markers (e.g., tumor PD L1 expression) appeared useful, but require independent validation.

Immune checkpoint inhibitors as novel targets for renal cell carcinoma therapeutics.

Monoclonal antibodies targeting programmed death 1, programmed death ligand 1, and cytotoxic T-lymphocyte antigen 4 pathways are currently in development for metastatic renal cell carcinoma. By inhibiting these immune regulatory pathways, these agents improve the immune response to cancer with the goal of creating durable responses. Although still early in development, several agents have been studied in phases I and II setting for metastatic renal cell carcinoma, with 1 drug in phase III testing (nivolumab). The unique toxicity profile of this class of therapy presents challenges to the treating clinician. Ongoing clinical trials hope to define patients who will benefit based on predictive biomarkers. Immune checkpoint inhibitors may play a key role in the future of management of solid tumors including kidney cancer.

Compound EGFR mutations and response to EGFR tyrosine kinase inhibitors.

BACKGROUND: Non-small-cell lung cancers (NSCLCs) containing EGFR mutations are exquisitely sensitive to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs). This is the case of the most common EGFR mutations affecting exon 18 (G719X), 19 (inframe deletions), and 21 (L858R and L861Q). However, the frequency of compound (i.e., double or complex) EGFR mutations-where an EGFR TKI sensitizing or other mutation is identified together with a mutation of unknown clinical significance-and their pattern of response/resistance to EGFR TKIs are less well described. METHODS: We analyzed the EGFR mutation pattern of 79 cases of NSCLC harboring EGFR mutations and compiled the genotype-response data for patients with NSCLCs with compound EGFR mutations treated with EGFR TKIs. RESULTS: Of the 79 EGFR-mutated tumors identified, 11 (14%) had compound mutations. Most involved the EGFR TKI-sensitizing G719X (n = 3, plus S768I or E709A), L858R (n = 4, plus L747V, R776H, T790M, or A871G), L861Q (n = 1, plus E709V), and delL747_T751 (n = 1, plus R776H). Eight patients received an EGFR TKI: three cases with G719X plus another mutation had partial responses (PRs) to erlotinib; of three cases with L858R plus another mutation, two displayed PRs and one (with EGFR-L858R+A871G) progressive disease (PD) to erlotinib; one NSCLC with EGFR-L861Q+E709A and one with delL747_T751+R776S had PRs to EGFR TKIs. CONCLUSION: Compound EGFR mutations comprised 14% of all mutations identified during routine sequencing of exons 18-21 of EGFR in our cohort. Most patients with an EGFR TKI-sensitizing mutation (G719X, exon 19 deletion, L858R, and L861Q) in addition to an atypical mutation responded to EGFR TKIs. Reporting of the genotype-response pattern of NSCLCs with EGFR compound and other rare mutations, and the addition of this information to searchable databases, will be helpful to select the appropriate therapy for EGFR-mutated NSCLC.

Functional survey for heterologous sugar transport proteins, using Saccharomyces cerevisiae as a host.

Molecular transport is a key process in cellular metabolism. This step is often limiting when using a nonnative carbon source, as exemplified by xylose catabolism in Saccharomyces cerevisiae. As a step toward addressing this limitation, this study seeks to characterize monosaccharide transport preference and efficiency. A group of 26 known and putative monosaccharide transport proteins was expressed in a recombinant Saccharomyces cerevisiae host unable to transport several monosaccharides. A growth-based assay was used to detect transport capacity across six different carbon sources (glucose, xylose, galactose, fructose, mannose, and ribose). A mixed glucose-and-xylose cofermentation was performed to determine substrate preference. These experiments identified 10 transporter proteins that function as transporters of one or more of these sugars. Most of these proteins exhibited broad substrate ranges, and glucose was preferred in all cases. The broadest transporters confer the highest growth rates and strongly prefer glucose. This study reports the first molecular characterization of the annotated XUT genes of Scheffersomyces stipitis and open reading frames from the yeasts Yarrowia lipolytica and Debaryomyces hansenii. Finally, a phylogenetic analysis demonstrates that transporter function clusters into three distinct groups. One particular group comprised of D. hansenii XylHP and S. stipitis XUT1 and XUT3 demonstrated moderate transport efficiency and higher xylose preferences.