10 research outputs found

    Experiences along the diagnostic pathway for patients with advanced lung cancer in the USA: a qualitative study.

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    BACKGROUND: Most patients with lung cancer are diagnosed at advanced stages. However, the advent of oral targeted therapies has improved the prognosis of many patients with lung cancer. PURPOSE: We aimed to understand the diagnostic experiences of patients with advanced lung cancer with oncogenic mutations. METHODS: Qualitative interviews were conducted with patients with advanced or metastatic non-small cell lung cancer with oncogenic alterations. Patients were recruited from online support groups within the USA. Interviews were conducted remotely or in person. Analysis used an iterative inductive and deductive process. Themes were mapped to the Model for Pathways to Treatment. RESULTS: 40 patients (12 male and 28 female) with a median age of 48 were included. We identified nine distinct themes. During the 'patient interval', individuals became concerned about symptoms, but often attributed them to other causes. Prolonged or more severe symptoms prompted care-seeking. During the 'primary care interval', doctors initially treated for illnesses other than cancer. Discovery of an imaging abnormality was a turning point in diagnostic pathways. Occasionally, severity of symptoms prompted patients to seek emergency care. During the 'secondary care interval', obtaining tissue samples was pivotal in confirming diagnosis. Delays in accessing oncology care sometimes led to patient distress. Obtaining genetic testing was crucial in directing patients to receive targeted treatments. CONCLUSIONS: Patients experienced multiple different routes to their diagnosis. Some patients perceived delays, inefficiencies and lack of coordination, which could be distressing. Shifting the stage of diagnosis of lung cancer to optimise the impact of targeted therapies will require concerted efforts in early detection

    Patient-Centered Outcomes Related to Imaging Testing in US Primary Care

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    Background: Imaging tests are one of the most sophisticated types of diagnostic tools used in health care, yet there are concerns that imaging is overused. Currently, tests are typically evaluated and implemented based on their accuracy, and there is limited knowledge about the range of patient-centered outcomes (PCOs) that imaging tests may lead to. This study explores patients’ experiences and subsequent outcomes of imaging tests most notable to patients. Methods: Adult patients from four primary care clinics who had an x-ray, CT, MRI, or ultrasound in the 12 months before recruitment participated in a single semistructured interview to recount their imaging experience. Interview transcripts were analyzed thematically. Results: Four themes related to PCOs were identified from 45 interviews. Participants’ mean age was 53 years (25-83 years), 30 had undergone a diagnostic imaging test, and 15 underwent imaging for screening or monitoring. Themes included knowledge gained from the imaging test, its contribution to their overall health care journey, physical experiences during the test procedure, and impacts of the testing process on emotions. Conclusions: Patients identified various imaging test outcomes that were important to them. Measurement and reporting these outcomes should be considered more often in diagnostic research. Tools for providers and patients to discuss and utilize these outcomes may help promote shared decision making around the use and impact of imaging tests

    Evaluating an app-guided self-test for influenza: lessons learned for improving the feasibility of study designs to evaluate self-tests for respiratory viruses

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    Abstract Background Seasonal influenza leads to significant morbidity and mortality. Rapid self-tests could improve access to influenza testing in community settings. We aimed to evaluate the diagnostic accuracy of a mobile app-guided influenza rapid self-test for adults with influenza like illness (ILI), and identify optimal methods for conducting accuracy studies for home-based assays for influenza and other respiratory viruses. Methods This cross-sectional study recruited adults who self-reported ILI online. Participants downloaded a mobile app, which guided them through two low nasal swab self-samples. Participants tested the index swab using a lateral flow assay. Test accuracy results were compared to the reference swab tested in a research laboratory for influenza A/B using a molecular assay. Results Analysis included 739 participants, 80% were 25–64 years of age, 79% female, and 73% white. Influenza positivity was 5.9% based on the laboratory reference test. Of those who started their test, 92% reported a self-test result. The sensitivity and specificity of participants’ interpretation of the test result compared to the laboratory reference standard were 14% (95%CI 5–28%) and 90% (95%CI 87–92%), respectively. Conclusions A mobile app facilitated study procedures to determine the accuracy of a home based test for influenza, however, test sensitivity was low. Recruiting individuals outside clinical settings who self-report ILI symptoms may lead to lower rates of influenza and/or less severe disease. Earlier identification of study subjects within 48 h of symptom onset through inclusion criteria and rapid shipping of tests or pre-positioning tests is needed to allow self-testing earlier in the course of illness, when viral load is higher

    How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States.

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    The diagnosis of lung cancer in ambulatory settings is often challenging due to non-specific clinical presentation, but there are currently no clinical quality measures (CQMs) in the United States used to identify areas for practice improvement in diagnosis. We describe the pre-diagnostic time intervals among a retrospective cohort of 711 patients identified with primary lung cancer from 2012-2019 from ambulatory care clinics in Seattle, Washington USA. Electronic health record data were extracted for two years prior to diagnosis, and Natural Language Processing (NLP) applied to identify symptoms/signs from free text clinical fields. Time points were defined for initial symptomatic presentation, chest imaging, specialist consultation, diagnostic confirmation, and treatment initiation. Median and interquartile ranges (IQR) were calculated for intervals spanning these time points. The mean age of the cohort was 67.3 years, 54.1% had Stage III or IV disease and the majority were diagnosed after clinical presentation (94.5%) rather than screening (5.5%). Median intervals from first recorded symptoms/signs to diagnosis was 570 days (IQR 273-691), from chest CT or chest X-ray imaging to diagnosis 43 days (IQR 11-240), specialist consultation to diagnosis 72 days (IQR 13-456), and from diagnosis to treatment initiation 7 days (IQR 0-36). Symptoms/signs associated with lung cancer can be identified over a year prior to diagnosis using NLP, highlighting the need for CQMs to improve timeliness of diagnosis
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