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1.
Transl Behav Med ; 13(10): 804-808, 2023 Sep 28.
Article in English | MEDLINE | ID: mdl-37579304

ABSTRACT

Building upon prior work developing and pilot testing a provider-focused Empathic Communication Skills (ECS) training intervention, this study sought feedback from key invested partners who work with individuals with lung cancer (i.e. stakeholders including scientific and clinical advisors and patient advocates) on the ECS training intervention. The findings will be used to launch a national virtually-delivered multi-center clinical trial that will examine the effectiveness and implementation of the evidence-based ECS training intervention to reduce patients' experience of lung cancer stigma. A 1-day, hybrid, key invested partners meeting was held in New York City in Fall 2021. We presented the ECS training intervention to all conference attendees (N = 25) to seek constructive feedback on modifications of the training content and platform for intervention delivery to maximize its impact. After participating in the immersive training, all participants engaged in a group discussion guided by semi-structured probes. A deductive thematic content analysis was conducted to code focus group responses into 12 distinct a priori content modification recommendations. Content refinement was suggested in 8 of the 12 content modification themes: tailoring/tweaking/refining, adding elements, removing elements, shortening/condensing content, lengthening/extending content, substituting elements, re-ordering elements, and repeating elements. Engagement and feedback from key invested multi-sector partner is a valuable resource for intervention content modifications. Using a structured format for refining evidence-based interventions can facilitate efforts to understand the nature of modifications required for scaling up interventions and the impact of these modifications on outcomes of interest. ClinicalTrials.gov Identifier: NCT05456841.


This study was done to get feedback from people who are involved with patients with lung cancer (PwLCs) including scientists, clinicians, and patient advocates on training in Empathic Communication Skills (ECS). The training is intended to reduce PwLCs experience of lung cancer stigma. The feedback is being used to help prepare for launching the training program in multiple cancer centers across the USA to test how well the training will work to reduce the stigma felt by PwLCs. A one-day, hybrid (in-person and virtual attendees) meeting was held in New York City in October 2021. We presented the original version of the ECS training program to all conference attendees (N = 25) to get feedback on modifications to improve the training program for the larger study planned at many cancer centers. After the training, all meeting attendees participated in a semi-structured group discussion. The content of the discussion was analyzed and sorted into 12 distinct categories that were defined before the meeting. Changes to the content were suggested in 8 of the 12 categories. These changes included tailoring/tweaking/refining, adding elements, removing elements, shortening/condensing content, lengthening/extending content, substituting elements, re-ordering elements, and repeating elements. Engaging and getting feedback from people involved in a topic is a good way to improve content and delivery of training materials.

2.
J Am Coll Radiol ; 20(9): 863-867, 2023 09.
Article in English | MEDLINE | ID: mdl-37453601

ABSTRACT

There are two major areas for patient engagement in radiology artificial intelligence (AI). One is in the sharing of data for AI development; the second is the use of AI in patient care. In general, individuals support sharing deidentified data if used for the common good, to help others with similar health conditions, or for research. However, there is concern with risk to privacy including reidentification and use for other than intended purposes. Lack of trust is mentioned as a barrier for data sharing. Individuals want to be involved in the data-sharing process. In the use of AI in medical care, patients generally support AI as an assist to the radiologist but lack trust in unsupervised AI. Patients worry about liability in case of bad outcomes. Patients are concerned about loss of the human connection and the loss of empathy during a vulnerable time in their lives. Patients expressed concern about risk of discrimination due to bias in AI algorithms. Building trust in AI requires transparency, explainability, security, and privacy protection. Radiologists can take action to prepare their patients to become more trusting of AI. Developing and implementing data-sharing agreements allows patients to voluntarily help in the algorithm development process. Developing AI disclosure guidelines and having AI use disclosure discussions with patients will help them understand the use of AI in their care. As the use of AI increases, there is an opportunity for radiologists to develop and maintain close relationships with their patients and to become more involved in their care.


Subject(s)
Artificial Intelligence , Radiology , Humans , Radiologists , Algorithms , Privacy
3.
Eur Respir J ; 2023 May 18.
Article in English | MEDLINE | ID: mdl-37202154

ABSTRACT

Screening for lung cancer with low radiation dose computed tomography (LDCT) has a strong evidence base. The European Council adopted a recommendation in November 2022 that lung cancer screening be implemented using a stepwise approach. The imperative now is to ensure that implementation follows an evidence-based process that delivers clinical and cost effectiveness. This ERS Taskforce was formed to provide a technical standard for a high-quality lung cancer screening program. METHOD: A collaborative group was convened to include members of multiple European societies (see below). Topics were identified during a scoping review and a systematic review of the literature was conducted. Full text was provided to members of the group for each topic. The final document was approved by all members and the ERS Scientific Advisory Committee. RESULTS: Ten topics were identified representing key components of a screening program. The action on findings from the LDCT were not included as they are addressed by separate international guidelines (nodule management and clinical management of lung cancer) and by a linked taskforce (incidental findings). Other than smoking cessation, other interventions that are not part of the core screening process were not included (e.g. pulmonary function measurement). Fifty-three statements were produced and areas for further research identified. CONCLUSION: This European collaborative group has produced a technical standard that is a timely contribution to implementation of LCS. It will serve as a standard that can be used, as recommended by the European Council, to ensure a high quality and effective program.

4.
Contemp Clin Trials ; 124: 107005, 2023 01.
Article in English | MEDLINE | ID: mdl-36396069

ABSTRACT

Low dose computed tomography (LDCT) is an effective screening test to decrease lung cancer deaths. Lung cancer screening may be a teachable moment helping people who smoke to quit, which may result in increased benefit of screening. Innovative strategies are needed to engage high-risk individuals in learning about LDCT screening. More precise methods such as polygenic risk scores quantify genetic predisposition to tobacco use, and optimize lung health interventions. We present the ESCAPE (Enhanced Smoking Cessation Approach to Promote Empowerment) protocol. This study will test a smoking cessation intervention using personal stories and a lung cancer screening decision-aide compared to standard care (brief advice, referral to a quit line, and a lung cancer screening decision-aide), examine the relationship between a polygenic risk score and smoking abstinence, and describe perceptions about integration of genomic information into smoking cessation treatment. A randomized controlled trial followed by a sequential explanatory mixed methods approach will compare the efficacy of the interventions. Interviews will add insight into the use of genomic information and risk perceptions to tailor smoking cessation treatment. Two-hundred and fifty individuals will be recruited from primary care, community-based organizations, mailing lists and through social media. Data will be collected at baseline, 1, 3 and 6-months. The primary outcomes are 7-day point prevalence smoking abstinence and stage of lung cancer screening at 6-months. The results from this study will provide information to refine the ESCAPE intervention and facilitate integration of precision health into future lung health interventions. Clinical trial registration number: NCT0469129T.


Subject(s)
Lung Neoplasms , Smoking Cessation , Humans , Smoking Cessation/methods , Early Detection of Cancer/methods , Lung Neoplasms/diagnosis , Lung Neoplasms/epidemiology , Lung , Smoking/epidemiology , Smoking/therapy , Randomized Controlled Trials as Topic
5.
Ann Am Thorac Soc ; 19(8): 1371-1378, 2022 08.
Article in English | MEDLINE | ID: mdl-34818144

ABSTRACT

Rationale: Future optimization of computed tomography (CT) lung cancer screening (CTLS) algorithms will depend on clinical outcomes data. Objectives: To report the outcomes of positive and suspicious findings in a clinical CTLS program. Methods: We retrospectively reviewed results for patients from our institution undergoing lung cancer screening from January 2012 through December 2018, with follow-up through December 2019. All exams were retrospectively rescored using Lung-RADS v1.1 (LR). Metrics assessed included positive, probably benign, and suspicious exam rates, frequency/nature of care escalation, and lung cancer detection rates after a positive, probably benign, and suspicious exam result and overall. We calculated time required to resolve suspicious exams as malignant or benign. Results were broken down by subcategories, reason for positive/suspicious designation, and screening round. Results: During the study period 4,301 individuals underwent a total of 10,897 exams. The number of positive (13.9%), suspicious (5.5%), and significant incidental (6.4%) findings was significantly higher at baseline screening. Cancer detection and false-positive rates were 2.0% and 12.3% at baseline versus 1.3% and 5.1% across subsequent screening rounds, respectively. Baseline solid nodule(s) 6 to <8 mm were the only probably benign findings resulting in lung cancer detection within 12 months. New solid nodules 6 to <8 mm were the only LR category 4A (LR4A) findings falling within the LR predicted cancer detection range of 5-15% (12.8%). 38.5% of LR4A cancers were detected within 3 months. Conclusions: Modification of the definition and suggested workup of positive and suspicious lung cancer screening findings appears warranted.


Subject(s)
Early Detection of Cancer , Lung Neoplasms , Early Detection of Cancer/methods , Humans , Lung Neoplasms/diagnostic imaging , Lung Neoplasms/pathology , Mass Screening/methods , Radiation Dosage , Retrospective Studies , Tomography, X-Ray Computed/methods
7.
J Thorac Oncol ; 16(1): 37-53, 2021 01.
Article in English | MEDLINE | ID: mdl-33188913

ABSTRACT

Lung cancer is the leading cause of cancer-related deaths worldwide, accounting for almost a fifth of all cancer-related deaths. Annual computed tomographic lung cancer screening (CTLS) detects lung cancer at earlier stages and reduces lung cancer-related mortality among high-risk individuals. Many medical organizations, including the U.S. Preventive Services Task Force, recommend annual CTLS in high-risk populations. However, fewer than 5% of individuals worldwide at high risk for lung cancer have undergone screening. In large part, this is owing to delayed implementation of CTLS in many countries throughout the world. Factors contributing to low uptake in countries with longstanding CTLS endorsement, such as the United States, include lack of patient and clinician awareness of current recommendations in favor of CTLS and clinician concerns about CTLS-related radiation exposure, false-positive results, overdiagnosis, and cost. This review of the literature serves to address these concerns by evaluating the potential risks and benefits of CTLS. Review of key components of a lung screening program, along with an updated shared decision aid, provides guidance for program development and optimization. Review of studies evaluating the population considered "high-risk" is included as this may affect future guidelines within the United States and other countries considering lung screening implementation.


Subject(s)
Early Detection of Cancer , Lung Neoplasms , Humans , Lung , Lung Neoplasms/diagnosis , Mass Screening , Tomography, X-Ray Computed , United States/epidemiology
8.
Radiology ; 293(2): 436-440, 2019 11.
Article in English | MEDLINE | ID: mdl-31573399

ABSTRACT

This is a condensed summary of an international multisociety statement on ethics of artificial intelligence (AI) in radiology produced by the ACR, European Society of Radiology, RSNA, Society for Imaging Informatics in Medicine, European Society of Medical Imaging Informatics, Canadian Association of Radiologists, and American Association of Physicists in Medicine. AI has great potential to increase efficiency and accuracy throughout radiology, but it also carries inherent pitfalls and biases. Widespread use of AI-based intelligent and autonomous systems in radiology can increase the risk of systemic errors with high consequence and highlights complex ethical and societal issues. Currently, there is little experience using AI for patient care in diverse clinical settings. Extensive research is needed to understand how to best deploy AI in clinical practice. This statement highlights our consensus that ethical use of AI in radiology should promote well-being, minimize harm, and ensure that the benefits and harms are distributed among stakeholders in a just manner. We believe AI should respect human rights and freedoms, including dignity and privacy. It should be designed for maximum transparency and dependability. Ultimate responsibility and accountability for AI remains with its human designers and operators for the foreseeable future. The radiology community should start now to develop codes of ethics and practice for AI that promote any use that helps patients and the common good and should block use of radiology data and algorithms for financial gain without those two attributes. This article is a simultaneous joint publication in Radiology, Journal of the American College of Radiology, Canadian Association of Radiologists Journal, and Insights into Imaging. Published under a CC BY-NC-ND 4.0 license. Online supplemental material is available for this article.


Subject(s)
Artificial Intelligence/ethics , Radiology/ethics , Canada , Consensus , Europe , Humans , Radiologists/ethics , Societies, Medical , United States
9.
J Am Coll Radiol ; 16(4 Pt B): 601-606, 2019 Apr.
Article in English | MEDLINE | ID: mdl-30947894

ABSTRACT

Lung cancer screening is just starting to be implemented across the United States. Challenges to screening include access to care, awareness of the option for screening, stigma and implicit bias that are due to stigmatization of smoking, stigma of race, nihilism with lung cancer diagnosis viewed as a "death sentence," shared decision making, and underestimation of lung cancer risk. African Americans (AA) have the highest lung cancer mortality rate in the United States despite similar smoking rates as whites. AAs are diagnosed at a later stage, and there is a greater likelihood they will refuse treatment options when diagnosed. Additionally, fewer AAs were found to meet lung cancer screening eligibility criteria compared with whites because of lower tobacco exposure and younger age at time of diagnosis. Outreach and access for lung cancer screening in the AA community and other subpopulations at risk are critical to avoid further increasing disparities in lung cancer morbidity and mortality as lung cancer screening is implemented across the United States. The path forward requires implementing outreach programs and providing lung cancer screening in underserved communities at high risk for lung cancer; consideration of using National Comprehensive Cancer Network guidelines for screening selection criteria, including risk model screening selection; and developing interventions to address stigma, clinician implicit bias, and nihilism.


Subject(s)
Early Detection of Cancer/statistics & numerical data , Health Status Disparities , Healthcare Disparities/economics , Lung Neoplasms/diagnosis , Lung Neoplasms/mortality , Patient Acceptance of Health Care/statistics & numerical data , Adult , Black or African American/statistics & numerical data , Aged , Female , Healthcare Disparities/ethnology , Humans , Male , Middle Aged , Needs Assessment , Risk Assessment , Socioeconomic Factors , Survival Analysis , United States , White People/statistics & numerical data
11.
J Natl Compr Canc Netw ; 16(4): 444-449, 2018 Apr.
Article in English | MEDLINE | ID: mdl-29632062

ABSTRACT

Background: This review assessed the performance of patients in NCCN high-risk group 2 in a clinical CT lung screening (CTLS) program. Methods: We retrospectively reviewed screening results for all patients from our institution undergoing clinical CTLS from January 2012 through December 2016, with follow-up through June 2017. To qualify for screening, patients had to meet the NCCN Guidelines high-risk criteria for CTLS, have a physician order for screening, be asymptomatic, be lung cancer-free for 5 years, and have no known metastatic disease. We compared demographics and screening performance of NCCN high-risk groups 1 and 2 across >4 rounds of screening. Screening metrics assessed included rates of positive and suspicious examinations, significant incidental and infectious/inflammatory findings, false negatives, and cancer detection. We also compared cancer stage and histology detected in each NCCN high-risk group. Results: A total of 2,927 individuals underwent baseline screening, of which 698 (24%) were in NCCN group 2. On average, group 2 patients were younger (60.6 vs 63.1 years), smoked less (38.8 vs 50.8 pack-years), had quit longer (18.1 vs 6.3 years), and were more often former smokers (61.4% vs 44.2%). Positive and suspicious examination rates, false negatives, and rates of infectious/inflammatory findings were equivalent in groups 1 and 2 across all rounds of screening. An increased rate of cancer detection was observed in group 2 during the second annual (T2) screening round (2.7% vs 0.5%; P=.005), with no difference in the other screening rounds: baseline (T0; 2% vs 2.3%; P=.61), first annual (T1; 1.2% vs 1.7%; P=.41), and third annual and beyond (≥T3; 1.2% vs 1.1%; P=1.00). Conclusions: CTLS appears to be equally effective in both NCCN high-risk groups.


Subject(s)
Lung Neoplasms/diagnosis , Lung Neoplasms/epidemiology , Mass Screening , Early Detection of Cancer/methods , Humans , Lung Neoplasms/etiology , Mass Screening/methods , Neoplasm Staging , Practice Guidelines as Topic , Radiography/methods , Retrospective Studies , Risk Factors
13.
J Am Coll Radiol ; 15(2): 282-286, 2018 02.
Article in English | MEDLINE | ID: mdl-29289507

ABSTRACT

BACKGROUND: Assess patient adherence to radiologist recommendations in a clinical CT lung cancer screening program. METHODS: Patients undergoing CT lung cancer screening between January 12, 2012, and June 12, 2013, were included in this institutional review board-approved retrospective review. Patients referred from outside our institution were excluded. All patients met National Comprehensive Cancer Network Guidelines Lung Cancer Screening high-risk criteria. Full-time program navigators used a CT lung screening program management system to schedule patient appointments, generate patient result notification letters detailing the radiologist follow-up recommendation, and track patient and referring physician notification of missed appointments at 30, 60, and 90 days. To be considered adherent, patients could be no more than 90 days past due for their next recommended examination as of September 12, 2014. Patients who died, were diagnosed with cancer, or otherwise became ineligible for screening were considered adherent. Adherence rates were assessed across multiple variables. RESULTS: During the study interval, 1,162 high-risk patients were screened, and 261 of 1,162 (22.5%) outside referrals were excluded. Of the remaining 901 patients, 503 (55.8%) were male, 414 (45.9%) were active smokers, 377 (41.8%) were aged 65 to 73, and >95% were white. Of the 901 patients, 772 (85.7%) were adherent. Most common reasons for nonadherence were patient refusal of follow-up exam (66.7%), inability to successfully contact the patient (20.9%), and inability to obtain the follow-up order from the referring provider (7.8%); 23 of 901 (2.6%) were discharged for other reasons. CONCLUSIONS: High rates of adherence to radiologist recommendations are achievable for in-network patients enrolled in a clinical CT lung screening program.


Subject(s)
Lung Neoplasms/diagnostic imaging , Patient Compliance , Tomography, X-Ray Computed , Aged , Early Detection of Cancer , Female , Humans , Male , Mass Screening , Middle Aged , Retrospective Studies , Risk Factors
17.
J Thorac Dis ; 8(Suppl 6): S481-7, 2016 Jul.
Article in English | MEDLINE | ID: mdl-27606076

ABSTRACT

BACKGROUND: Lung cancer screening may provide a "teachable moment" for promoting smoking cessation. This study assessed smoking cessation and relapse rates among individuals undergoing follow-up low-dose chest computed tomography (CT) in a clinical CT lung screening program and assessed the influence of initial screening results on smoking behavior. METHODS: Self-reported smoking status for individuals enrolled in a clinical CT lung screening program undergoing a follow-up CT lung screening exam between 1st February, 2014 and 31st March, 2015 was retrospectively reviewed and compared to self-reported smoking status using a standardized questionnaire at program entry. Point prevalence smoking cessation and relapse rates were calculated across the entire population and compared with exam results. All individuals undergoing screening fulfilled the National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology: Lung Cancer Screening v1.2012(®) high-risk criteria and had an order for CT lung screening. RESULTS: A total of 1,483 individuals underwent a follow-up CT lung screening exam during the study interval. Smoking status at time of follow-up exam was available for 1,461/1,483 (98.5%). A total of 46% (678/1,461) were active smokers at program entry. The overall point prevalence smoking cessation and relapse rates were 20.8% and 9.3%, respectively. Prior positive screening exam results were not predictive of smoking cessation (OR 1.092; 95% CI, 0.715-1.693) but were predictive of reduced relapse among former smokers who had stopped smoking for 2 years or less (OR 0.330; 95% CI, 0.143-0.710). Duration of program enrollment was predictive of smoking cessation (OR 0.647; 95% CI, 0.477-0.877). CONCLUSIONS: Smoking cessation and relapse rates in a clinical CT lung screening program rates are more favorable than those observed in the general population. Duration of participation in the screening program correlated with increased smoking cessation rates. A positive exam result correlated with reduced relapse rates among smokers recently quit smoking.

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