Sensitivity of US Preventive Services Task Force and PLCOm2012 lung cancer screening eligibility criteria in individuals with lung cancer in South Dakota self-reporting as Indigenous and non-Indigenous.

BACKGROUND: Lung cancer is the leading cause of cancer deaths. Screening individuals who are at elevated risk using low-dose computed tomography reduces lung cancer mortality by ≥20%. Individuals who have community-based factors that contribute to an increased risk of developing lung cancer have high lung cancer rates and are diagnosed at younger ages. In this study of lung cancer in South Dakota, the authors compared the sensitivity of screening eligibility criteria for self-reported Indigenous race and evaluated the need for screening at younger ages. METHODS: US Preventive Services Task Force (USPSTF) 2013 and 2021 (USPSTF2013 and USPSTF2021) criteria and two versions of the PLCOm2012 risk-prediction model (based on the 2012 Prostate, Lung, Colorectal, and Ovarian [PLCO] Cancer Screening Trial), one with a predictor for race and one without, were applied at USPSTF-equivalent thresholds of ≥1.7% in 6 years and ≥1.0% in 6 years to 1565 individuals who were sequentially diagnosed with lung cancer (of whom 12.7% self-reported as Indigenous) at the Monument Health Cancer Care Institute in South Dakota (2010-2019). RESULTS: Eligibility sensitivities of USPSTF criteria did not differ significantly between individuals who self-reported their race as Indigenous and those who did not (p > .05). Sensitivities of both PLCOm2012 models were significantly higher than comparable USPSTF criteria. The sensitivity of USPSTF2021 criteria was 66.1% and, for comparable PLCOm2012 models with and without race, sensitivity was 90.7% and 89.6%, respectively (both p < .001); 1.4% of individuals were younger than 50 years, and proportions did not differ by Indigenous classification (p = .518). CONCLUSIONS: Disparities in screening eligibility were not observed for individuals who self-reported their race as Indigenous. USPSTF criteria had lower sensitivities for lung cancer eligibility. Both PLCOm2012 models had high sensitivities, with higher sensitivity for the model that included race. The PLCOm2012noRace model selected effectively in this population, and screening individuals younger than 50 years did not appear to be justified. PLAIN LANGUAGE SUMMARY: Lung cancer is the leading cause of cancer deaths. Studies show that using low-dose computed tomography scans to screen people who smoke or who used to smoke and are at elevated risk for lung cancer reduces lung cancer deaths. This study of 1565 individuals with lung cancer in South Dakota compared screening eligibility using US Preventive Services Task Force (USPSTF) criteria and a lung cancer risk-prediction model (PLCOm2012; from the 2012 Prostate, Lung, Colorectal, and Ovarian [PLCO] Cancer Screening Trial). The model had higher sensitivity and picked more people with lung cancer to screen compared with USPSTF criteria. Eligibility sensitivities were similar for individuals who self-reported as Indigenous versus those who did not between USPSTF criteria and the model.

Towards Systematic Design Considerations for Visualizing Cross-View Data Relationships.

Due to the scale of data and the complexity of analysis tasks, insight discovery often requires coordinating multiple visualizations (views), with each view displaying different parts of data or the same data from different perspectives. For example, to analyze car sales records, a marketing analyst uses a line chart to visualize the trend of car sales, a scatterplot to inspect the price and horsepower of different cars, and a matrix to compare the transaction amounts in types of deals. To explore related information across multiple views, current visual analysis tools heavily rely on brushing and linking techniques, which may require a significant amount of user effort (e.g., many trial-and-error attempts). There may be other efficient and effective ways of displaying cross-view data relationships to support data analysis with multiple views, but currently there are no guidelines to address this design challenge. In this article, we present systematic design considerations for visualizing cross-view data relationships, which leverages descriptive aspects of relationships and usable visual context of multi-view visualizations. We discuss pros and cons of different designs for showing cross-view data relationships, and provide a set of recommendations for helping practitioners make design decisions.

Toxicological analysis of serious drug-related harm among electronic dance music festival attendees in New South Wales, Australia: A consecutive case series.

BACKGROUND: A substantial increase in drug-related harm was observed during the 2018-2019 music festival season in New South Wales, Australia, including the deaths of five young people. As part of a rapid public health response, the New South Wales Ministry of Health referred samples from patients with suspected severe drug-related illness for forensic toxicological testing to identify the type and concentration of substances associated with the presentations. METHODS: Cases were identified through a variety of active and passive surveillance systems, and selected consecutively based on indicators of clinical severity. Comprehensive toxicology testing of blood and urine samples was expedited for all cases. Demographic and clinical characteristics were collated, together with quantitative toxicology results. Results were analysed using descriptive statistics. RESULTS: Forty cases from eleven different music festivals were included. The majority of cases (80.0%) were aged 25 years and under. There were five fatalities, and 62.5% of cases were admitted to intensive care units. MDMA was the most frequent substance, detected in 87.5% of cases. In 82.9% of cases with MDMA, blood concentrations were above thresholds that have been associated with toxicity. Multiple substances were detected in 60.0% of cases. Novel psychoactive substances were not detected. CONCLUSIONS: Our findings strongly suggest that MDMA-related toxicity was a major factor in the severity of the clinical presentations among these cases. Other substances may have enhanced MDMA toxicity but appear unlikely to have caused severe toxicity in isolation. These findings have important implications for harm reduction strategies targeted to music festival settings.

Enhancing Web-based Analytics Applications through Provenance.

Visual analytics systems continue to integrate new technologies and leverage modern environments for exploration and collaboration, making tools and techniques available to a wide audience through web browsers. Many of these systems have been developed with rich interactions, offering users the opportunity to examine details and explore hypotheses that have not been directly encoded by a designer. Understanding is enhanced when users can replay and revisit the steps in the sensemaking process, and in collaborative settings, it is especially important to be able to review not only the current state but also what decisions were made along the way. Unfortunately, many web-based systems lack the ability to capture such reasoning, and the path to a result is transient, forgotten when a user moves to a new view. This paper explores the requirements to augment existing client-side web applications with support for capturing, reviewing, sharing, and reusing steps in the reasoning process. Furthermore, it considers situations where decisions are made with streaming data, and the insights gained from revisiting those choices when more data is available. It presents a proof of concept, the Shareable Interactive Manipulation Provenance framework (SIMProv.js), that addresses these requirements in a modern, client-side JavaScript library, and describes how it can be integrated with existing frameworks.

A pre-post survey analysis of satisfaction with health care and medical mistrust after patient navigation for American Indian cancer patients.

PURPOSE: To assess the impact of patient navigation (PN) on satisfaction with health care and medical mistrust among American Indians (AI) undergoing cancer treatment. METHODS: This was a pre-post cohort survey study of 52 AI cancer patients who participated in a culturally-tailored PN program during their cancer treatment. Surveys were administered prior to and after cancer treatment assessing medical mistrust and satisfaction with health care using two Likert-type scales. RESULTS: Participation refusal rate was 7%. Mean scale scores for satisfaction with health care were significantly improved after PN compared with pre-navigation (p<.0001; Wilcoxon signed-rank test). There was no significant difference in the mean scale scores for medical mistrust after PN compared with those observed prior to treatment (p=.13). CONCLUSIONS: American Indian cancer patients who received PN services during their cancer treatment showed improvement in levels of satisfaction with health. However, no improvements were observed in levels of medical mistrust.

Patient navigation for American Indians undergoing cancer treatment: utilization and impact on care delivery in a regional healthcare center.

BACKGROUND: A study was undertaken to assess patient navigation utilization and its impact on treatment interruptions and clinical trial enrollment among American Indian cancer patients. METHODS: Between February 2004 and September 2009, 332 American Indian cancer patients received patient navigation services throughout cancer treatment. The patient navigation program provided culturally competent navigators to assist patients with navigating cancer therapy, obtaining medications, insurance issues, communicating with medical providers, and travel and lodging logistics. Data on utilization and trial enrollment were prospectively collected. Data for a historical control group of 70 American Indian patients who did not receive patient navigation services were used to compare treatment interruptions among those undergoing patient navigation during curative radiation therapy (subgroup of 123 patients). RESULTS: The median number of contacts with a navigator was 12 (range, 1-119). The median time spent with the navigator at first contact was 40 minutes (range, 10-250 minutes), and it was 15 minutes for subsequent contacts. Patients treated with radiation therapy with curative intent who underwent patient navigation had fewer days of treatment interruption (mean, 1.7 days; 95% confidence interval [CI], 1.1-2.2 days) than historical controls who did not receive patient navigation services (mean, 4.9 days; 95% CI, 2.9-6.9 days). Of the 332 patients, 72 (22%; 95% CI, 17%-26%) were enrolled on a clinical treatment trial or cancer control protocol. CONCLUSIONS: Patient navigation was associated with fewer treatment interruptions and relatively high rates of clinical trial enrollment among American Indian cancer patients compared with national reports.

Involving American Indians and medically underserved rural populations in cancer clinical trials.

PURPOSE: To assess cancer clinical trial recruitment and reasons for nonaccrual among a rural, medically underserved population served by a community-based cancer care center. METHODS: We prospectively tracked clinical trial enrollment incidence among all new patients presenting at the Rapid City Regional Cancer Care Institute. Evaluating physicians completed questionnaires for each patient regarding clinical trial enrollment status and primary reasons for nonenrollment. Patients who identified as American Indian were referred to a program where patients were assisted in navigating the medical system by trained, culturally competent staff. RESULTS: Between September 2006 and January 2008, 891 new cancer patients were evaluated. Seventy-eight patients (9%; 95% confidence intervals, 7-11%) were enrolled on a clinical treatment trial. For 73% (95% confidence intervals, 69-75%) of patients (646 of 891) lack of relevant protocol availability or protocol inclusion criteria restrictiveness was the reason for nonenrollment. Only 45 (5%; 95% confidence intervals, 4-7%) patients refused enrollment on a trial. Of the 78 enrolled on a trial, 6 (8%; 95% confidence intervals, 3-16%) were American Indian. Three additional American Indian patients were enrolled under a nontreatment cancer control trial, bringing the total percentage enrolled of the 94 American Indians who presented to the clinic to 10% (95% confidence intervals, 5-17%). LIMITATIONS: Eligibility rates were unable to be calculated and cross validation of the number in the cohort via registries or ICD-9 codes was not performed. CONCLUSION: Clinical trial participation in this medically underserved population was low overall, but approximately 3-fold higher than reported national accrual rates. Lack of availability of protocols for common cancer sites as well as stringent protocol inclusion criteria were the primary obstacles to clinical trial enrollment. Targeted interventions using a Patient Navigation program were used to engage AI patients and may have resulted in higher clinical trial enrollment among this racial/ethnic group.

VisComplete: automating suggestions for visualization pipelines.

Building visualization and analysis pipelines is a large hurdle in the adoption of visualization and workflow systems by domain scientists. In this paper, we propose techniques to help users construct pipelines by consensus--automatically suggesting completions based on a database of previously created pipelines. In particular, we compute correspondences between existing pipeline subgraphs from the database, and use these to predict sets of likely pipeline additions to a given partial pipeline. By presenting these predictions in a carefully designed interface, users can create visualizations and other data products more efficiently because they can augment their normal work patterns with the suggested completions. We present an implementation of our technique in a publicly-available, open-source scientific workflow system and demonstrate efficiency gains in real-world situations.

Querying and creating visualizations by analogy.

While there have been advances in visualization systems, particularly in multi-view visualizations and visual exploration, the process of building visualizations remains a major bottleneck in data exploration. We show that provenance metadata collected during the creation of pipelines can be reused to suggest similar content in related visualizations and guide semi-automated changes. We introduce the idea of query-by-example in the context of an ensemble of visualizations, and the use of analogies as first-class operations in a system to guide scalable interactions. We describe an implementation of these techniques in VisTrails, a publicly-available, open-source system.