Lung; NodeNCT05738031
Investigating Incidental Pulmonary Nodules in Underserved Communities
An observational study of Lung; Node, run by Montefiore Medical Center at 1 site in United States.
Trial summary
The study team hypothesizes that incidentally discovered pulmonary nodules are often under captured and/or not surveilled in accordance with published guidelines in the Montefiore Health System, which cares for a large proportion of Black and Hispanic patients. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Lung; Node
- How many people
- 0 participants
- Where
- 1 siteUnited States
- Study dates
- Oct 2023to May 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The target population for the study consists of patients with an identified incidental pulmonary nodule seen at the Montefiore Medical Center after Feburary 1, 2023.
Who may be able to join
- Part A of the study seeks to capture IPNs and standardize mechanism for management will employ the following inclusion criteria:
- Above the age of 18
- Underwent an imaging study for any purpose other than lung cancer screening at a Montefiore Medical Center facility that identifies a pulmonary nodule
- Imaging results captured into the Epic electronic medical record
- Referred to the lung nodule clinic
- Underwent an in-person or telephone/telehealth encounter at a Montefiore Medical Center facility during the study period
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- Lung cancers diagnosed at a Montefiore Medical Center facility between April 1, 2021 and March 31 2022 will also be included for retrospective review and comparison to the cohort of lung cancers diagnosed following the instillation of the IPN program herein described
- Part B of the study will seek to develop an algorithm for incidental lung nodule risk stratification utilizing data from the electronic medical record. Inclusion criteria are:
- Above the age of 18
- Underwent an imaging study for any purpose other than lung cancer screening at a Montefiore Medical Center facility that identifies a pulmonary nodule
- Imaging results captured into the Epic electronic medical record
- Referred to the lung nodule clinic
- Underwent an in-person or telephone/telehealth encounter at a Montefiore Medical Center facility during the study period
- The third part (Part C) of the study is a substudy examining plasma-based expression of markers associated with lung cancer in patients with lung nodules, and will include the following patients:
- Above the age of 18
- Underwent an imaging study, including imaging performed for lung cancer screening, at a Montefiore Medical Center facility that identifies a pulmonary nodule
- Imaging results captured into the Epic electronic medical record
- Referred to the lung nodule clinic
- Underwent an in-person or telephone/telehealth encounter at a Montefiore Medical Center facility during the study period
- Recommended follow-up by means of either continued imaging surveillance of nodule or procedure for diagnosis, including percutaneous transthoracic needle biopsy, endobronchial transbronchial needle aspiration, surgical biopsy or resection of pulmonary nodule
Who cannot join
- <18 years of age
- No evidence of a lung nodule through imaging
Trial locations and contacts
1 site in 1 country.
United States1 site
Montefiore Medical Center-Albert Einstein College of Medicine
The Bronx, New York, 10461
About this study
The study team hypothesizes that incidentally discovered pulmonary nodules are often under captured and/or not surveilled in accordance with published guidelines in the Montefiore Health System, which cares for a large proportion of Black and Hispanic patients. Incidental Pulmonary Nodules (IPNs) require a pragmatic approach to follow-up and management, especially in racially disparate populations who have greater potential for lung cancer morbidity and mortality.
Read the detailed description
An estimated 235,760 people will be newly diagnosed with lung cancer in 2021 and over 130,000 people will die as a result. Computed tomography (CT) screening has demonstrated reduced lung cancer mortality, and is now recommended for adults aged 50 to 80 years with a 20-pack-year smoking history who are current smoker or have quit within 15 years. Along with the early identification of at-risk pulmonary nodules, screening programs also have the ability to direct patients into pathways for protocolized follow-up. Despite defined eligibility requirements, lung cancer screening (LCS) is underutilized, with less than 10% of eligible patients undergoing screening. Screening is particularly challenging in minority and socioeconomically disadvantaged populations, who face an increased risk of death due to lung cancer. Of over 50,000 patients enrolled in the National Lung Screening Trial, for example, only 4.5% of participants identified as Black and 1.7% identified as Hispanic.
Outside of screening programs, lung nodules are commonly detected incidentally on imaging done for other reasons. Each year, more than 1.5 million patients are diagnosed with an incidental pulmonary nodule. Of these, 5-9% are estimated to represent cancers, higher than the malignancy rate noted in lung cancer screening programs. Guidelines exist for the follow-up of IPNs, however compliance is often poor. IPNs may be overlooked in the context of the other illnesses for which imaging is obtained. Tests may also be ordered by providers without continuity of care, as occurs in the emergency department (ED). Patients may thus be unaware of incidental findings or receive inadequate direction for follow-up when there is no clear chain of responsibility. Racially disparate populations are specifically at risk and often face barriers to accessing primary care providers (PCPs), leading to increased use of the ED. In one study, a higher proportion of Black and Hispanic patients (38.3% and 28.1%, respectively) had initial imaging identifying an IPN performed in the ED compared to White patients (10.7%), who were more likely to have outpatient scans.
Previous studies indicate that only 38% of patients receive guideline concordant care once diagnosed with an IPN. Lung cancer was diagnosed in 8% of these patients undergoing such care compared to only 1% in those who received less intensive evaluation. Similarly, the median time to diagnosis of a lung cancer was 1.3 months in the guideline concordant care group versus 12 months in the less intensive evaluation patients, again underscoring the importance of appropriate mechanisms of follow-up. The consequences of a missed nodule are clear.
Data suggest that racial and ethnic disparities exist in the follow-up of IPNs. In a study of 1,562 patients with an IPN requiring follow-up at a tertiary care center, only 49.1% of Hispanic patients and 55.1% of Black patients were notified of IPNs compared to 79.5% of White patients. Similarly, non-White patients had significantly lower rates of ordering and adherence to follow-up imaging and had an increased odds of delaying follow-up. While this discrepancy in care has been identified, few solutions exist to bridge the gap and underrepresented patients remain at higher risk of delayed diagnosis until advanced stages of disease.
Further compounding the difficulty in managing underserved patients with IPNs is the lack of programs for formalized follow-up, specifically in urban areas. In an advisory board meeting of major medical centers within New York City, only one formal nodule evaluation program associated with a center's ED was identified. New York Presbyterian Hospital Weill Cornell identified 539 patients with IPNs over a two-year period. After radiologic review, chest radiologists referred 289 patients for further consultation and of these 142 (26.3% of original population) were referred for evaluation by a pulmonologist or oncologist. While the results of this investigation and rates of cancer diagnoses are currently being tabulated, the large proportion of patients referred for concerning findings is quite notable.
Within New York City, the Montefiore Health System is uniquely positioned to conduct clinical research and bridge health care disparities by engaging underserved and underrepresented communities. The health system is comprised of 11 hospitals in the Bronx, Westchester, and the Hudson Valley in New York. The main campuses include two high volume EDs, including one of the five busiest in the country, and serve a diverse population of nearly 1.5 million residents in the Bronx. Previous data from Montefiore have demonstrated that of 855 primary lung cancers diagnosed between 2013 and 2016, only 417 (55%) were found in patients with an in-network PCP, illustrating the need for a better support system and for a systematic approach to identify and guide these patients. Furthermore, of the 175 of these patients who were eligible for LCS, only 33 had completed screening. Among screened patients, 64% were diagnosed with stage I/II non-small cell lung cancer, compared to only 29% of the lung cancers found outside of screening. In this latter group, 46% were diagnosed with metastatic disease. This demonstrates not only the value of screening in this at-risk population, but also emphasizes the need for prompt follow-up of incidentally detected lung abnormalities. A large proportion of this population in whom lung cancers were identified outside of screening was comprised of Black (46%) and Hispanic (34%) patients with a median per capita income of only approximately $20,000.12. The evaluation and implementation of a nodule detection program may thus extend care and improve the potential for survival in patients with reduced access to health care, where the ED may function as the primary care hub.
- Conditions
- Lung; Node
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Group A | Aim 1 (Part A). To utilize natural language processing (NLP) to identify all ED patients with incidentally detected lung nodules found on chest radiographs or chest or abdominal CT scans, and to develop a standardized referral and notification process Aim 1.1) Utilization of NLP to screen radiologic reports and identify nodules meeting criteria for follow-up per Fleischner Society Guidelines Aim 1.2) Creation of an electronic medical record-based notification system to alert patients and providers of the identification of an IPN that requires follow-up, tracked by a dedicated patient navigator Aim 1.3) Establishment of a multidisciplinary lung nodule management team, hereafter referred to as the lung nodule clinic, to ensure guideline-directed management of nodules with emphasis on high risk nodules as identified in subsequent aims | |
| Group B | Aim 2 (Part B). To clinically risk stratify patients with IPNs utilizing artificial intelligence (AI) processing of known clinical risks factors for pulmonary malignancy, such as age, smoking history, and history of malignancy, along with radiographic risk classifiers including nodule location, size, and imaging features. Aim 2.1) Development of an integrated classifier based on automated scanning and data retrieval from the electronic medical record (EMR) to stratify patients with IPNs as low, intermediate or high risk for malignancy, with factor analysis to assess contributions of individual factors to the model Aim 2.2) Prospective evaluation of the integrated classifier and comparison of automated integrated classifier to established manual risk calculators | |
| Group C | Aim 3 (Part C). To investigate biologic risk classifiers that may aid in the risk stratification of pulmonary nodules Aim 3.1) Evaluation of a blood-based gene expression assay for risk stratification of pulmonary nodules using biobanked specimens Aim 3.2) Prospective collection of plasma from patients enrolled in lung nodule clinic and evaluation of gene expression to assess malignancy risk |
What is being measured
The primary outcome is the main question the study is designed to answer.
Capture of incidentally identified lung nodules utilizing the electronic medical record
To capture all incidentally identified lung nodules and create a multidisciplinary team for lung nodule management. Radiology and pulmonary providers will identify and report IPNs >=6mm denoted as positive imaging result at Montefiore. NLP will be used to identify IPNs using the Lung Orchestrator and IPNs will be captured by automated assessment of radiology. Cardiothoracic Imaging will assist in nodule identification using NLP. Following confirmation of a nodule requiring follow-up, the Lung Orchestrator will place the patient in a work queue. Patients diagnosed with lung cancer the year prior to the program will be reviewed retrospectively with NLP for determination on whether the approach increases adherence to IPN follow-up guidelines.
Measured: Through completion of chart review, up to 1 year
Performance comparison of EMR-based algorithm to establish risk
Patients will be followed to develop a multi-component integrated risk classifier for stratification into low or intermediate malignancy risk. Risk calculators (Brock University; Mayo Clinic) will be used for assessment and evaluations designed to automatically populate in the EMR. Stratification will be based upon demographic factors, such as age, gender, race, smoking, and cancer history. Imaging characteristics such as emphysema, nodule location, size, and concerning features will be used. The aim is to develop an automated risk calculating algorithm based upon AI-mediated processing of clinical data and radiomics. These assessments will allow for real-time risk identification and the investigation of a novel model will incorporate data from a more diverse population.
Measured: Through development of algorithm, up to 1 year
Evaluation of LiquidLung plasma-based gene expression assay for biomarker subset selection using biobanked specimens
This assay is applicable for all concerning pulmonary nodules, represented by those patients referred to the lung nodule clinic. The lung nodule clinic manages both incidental and screen-detected lesions. Montefiore Health System has an established lung cancer screening program with over 1,000 screenings completed in the last year. Patients with suspicious nodules are recommended follow-up and also have potential to benefit from testing via non-invasive means.
Measured: Through evaluation of assay, up to 1.5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Feb 2023
- Study startOct 2023 (estimated)
- Primary completionMay 2025 (estimated)
- Study completionMay 2025 (estimated)
Why it stopped: Withdrawn by IRB on 10-16-2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (16)Papers the sponsor has linked to this study.
- Other trials for Lung; NodeStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 0 participants (actual)
Sponsor and investigators
- Lead sponsor
- Montefiore Medical Center
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Neel Chudgar, MD, Principal investigator, Montefiore Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05738031
- Sponsor's protocol ID
- 2021-13475
- Status last verified
- Nov 2023
- First submitted
- 3 Feb 2023
- Last updated
- 18 Nov 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: Once the trial data collection is completed the potential for sharing data to expand the trial may occur.
Publications
Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer Statistics, 2021. CA Cancer J Clin. 2021 Jan;71(1):7-33. doi: 10.3322/caac.21654. Epub 2021 Jan 12.
PubMed 33433946National Lung Screening Trial Research Team; Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, Gareen IF, Gatsonis C, Marcus PM, Sicks JD. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011 Aug 4;365(5):395-409. doi: 10.1056/NEJMoa1102873. Epub 2011 Jun 29.
PubMed 21714641US Preventive Services Task Force; Krist AH, Davidson KW, Mangione CM, Barry MJ, Cabana M, Caughey AB, Davis EM, Donahue KE, Doubeni CA, Kubik M, Landefeld CS, Li L, Ogedegbe G, Owens DK, Pbert L, Silverstein M, Stevermer J, Tseng CW, Wong JB. Screening for Lung Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2021 Mar 9;325(10):962-970. doi: 10.1001/jama.2021.1117.
PubMed 33687470Jemal A, Fedewa SA. Lung Cancer Screening With Low-Dose Computed Tomography in the United States-2010 to 2015. JAMA Oncol. 2017 Sep 1;3(9):1278-1281. doi: 10.1001/jamaoncol.2016.6416.
PubMed 28152136Lake M, Shusted CS, Juon HS, McIntire RK, Zeigler-Johnson C, Evans NR, Kane GC, Barta JA. Black patients referred to a lung cancer screening program experience lower rates of screening and longer time to follow-up. BMC Cancer. 2020 Jun 16;20(1):561. doi: 10.1186/s12885-020-06923-0.
PubMed 32546140Wiener RS, Gould MK, Slatore CG, Fincke BG, Schwartz LM, Woloshin S. Resource use and guideline concordance in evaluation of pulmonary nodules for cancer: too much and too little care. JAMA Intern Med. 2014 Jun;174(6):871-80. doi: 10.1001/jamainternmed.2014.561.
PubMed 24710850Hanchate AD, Dyer KS, Paasche-Orlow MK, Banerjee S, Baker WE, Lin M, Xue WD, Feldman J. Disparities in Emergency Department Visits Among Collocated Racial/Ethnic Medicare Enrollees. Ann Emerg Med. 2019 Mar;73(3):225-235. doi: 10.1016/j.annemergmed.2018.09.007. Epub 2018 Oct 26.
PubMed 30798793Schut RA, Mortani Barbosa EJ Jr. Racial/Ethnic Disparities in Follow-Up Adherence for Incidental Pulmonary Nodules: An Application of a Cascade-of-Care Framework. J Am Coll Radiol. 2020 Nov;17(11):1410-1419. doi: 10.1016/j.jacr.2020.07.018. Epub 2020 Aug 7.
PubMed 32771492Su CT, Bhargava A, Shah CD, Halmos B, Gucalp RA, Packer SH, Ohri N, Haramati LB, Perez-Soler R, Cheng H. Screening Patterns and Mortality Differences in Patients With Lung Cancer at an Urban Underserved Community. Clin Lung Cancer. 2018 Sep;19(5):e767-e773. doi: 10.1016/j.cllc.2018.05.019. Epub 2018 Jun 5.
PubMed 29937386Dziadzko MA, Novotny PJ, Sloan J, Gajic O, Herasevich V, Mirhaji P, Wu Y, Gong MN. Multicenter derivation and validation of an early warning score for acute respiratory failure or death in the hospital. Crit Care. 2018 Oct 30;22(1):286. doi: 10.1186/s13054-018-2194-7.
PubMed 30373653Kammer MN, Massion PP. Noninvasive biomarkers for lung cancer diagnosis, where do we stand? J Thorac Dis. 2020 Jun;12(6):3317-3330. doi: 10.21037/jtd-2019-ndt-10.
PubMed 32642255Gould MK, Tang T, Liu IL, Lee J, Zheng C, Danforth KN, Kosco AE, Di Fiore JL, Suh DE. Recent Trends in the Identification of Incidental Pulmonary Nodules. Am J Respir Crit Care Med. 2015 Nov 15;192(10):1208-14. doi: 10.1164/rccm.201505-0990OC.
PubMed 26214244MacMahon H, Naidich DP, Goo JM, Lee KS, Leung ANC, Mayo JR, Mehta AC, Ohno Y, Powell CA, Prokop M, Rubin GD, Schaefer-Prokop CM, Travis WD, Van Schil PE, Bankier AA. Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017. Radiology. 2017 Jul;284(1):228-243. doi: 10.1148/radiol.2017161659. Epub 2017 Feb 23.
PubMed 28240562Kang SK, Garry K, Chung R, Moore WH, Iturrate E, Swartz JL, Kim DC, Horwitz LI, Blecker S. Natural Language Processing for Identification of Incidental Pulmonary Nodules in Radiology Reports. J Am Coll Radiol. 2019 Nov;16(11):1587-1594. doi: 10.1016/j.jacr.2019.04.026. Epub 2019 May 24.
PubMed 31132331Mobiny A, Yuan P, Cicalese PA, Moulik SK, Garg N, Wu CC, Wong K, Wong ST, He TC, Nguyen HV. Memory-Augmented Capsule Network for Adaptable Lung Nodule Classification. IEEE Trans Med Imaging. 2021 Oct;40(10):2869-2879. doi: 10.1109/TMI.2021.3051089. Epub 2021 Sep 30.
PubMed 33434126
Study at a glance
From the registry record, last updated by the sponsor on 18 Nov 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Investigating Incidental Pulmonary Nodules in Underserved Communities
- ClinicalTrials.gov ID
- NCT05738031
- Acronym / sponsor ID
- 2021-13475
- Conditions
- Lung; Node
- Study type
- Observational
- Recruitment status
- WithdrawnReason stopped: Withdrawn by IRB on 10-16-2023
- Enrolment
- 0 participants (actual)
- Lead sponsor
- Montefiore Medical CenterUniversity, hospital or other
- Study start
- Oct 2023 (estimated)
- Primary completion
- May 2025 (estimated)
- Study completion
- May 2025 (estimated)
- First posted
- 21 Feb 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The study team hypothesizes that incidentally discovered pulmonary nodules are often under captured and/or not surveilled in accordance with published guidelines in the Montefiore Health System, which cares for a large proportion of Black and Hispanic patients. Incidental Pulmonary Nodules (IPNs) require a pragmatic approach to follow-up and management, especially in racially disparate populations who have greater potential for lung cancer morbidity and mortality.
Detailed description
An estimated 235,760 people will be newly diagnosed with lung cancer in 2021 and over 130,000 people will die as a result. Computed tomography (CT) screening has demonstrated reduced lung cancer mortality, and is now recommended for adults aged 50 to 80 years with a 20-pack-year smoking history who are current smoker or have quit within 15 years. Along with the early identification of at-risk pulmonary nodules, screening programs also have the ability to direct patients into pathways for protocolized follow-up. Despite defined eligibility requirements, lung cancer screening (LCS) is underutilized, with less than 10% of eligible patients undergoing screening. Screening is particularly challenging in minority and socioeconomically disadvantaged populations, who face an increased risk of death due to lung cancer. Of over 50,000 patients enrolled in the National Lung Screening Trial, for example, only 4.5% of participants identified as Black and 1.7% identified as Hispanic.
Outside of screening programs, lung nodules are commonly detected incidentally on imaging done for other reasons. Each year, more than 1.5 million patients are diagnosed with an incidental pulmonary nodule. Of these, 5-9% are estimated to represent cancers, higher than the malignancy rate noted in lung cancer screening programs. Guidelines exist for the follow-up of IPNs, however compliance is often poor. IPNs may be overlooked in the context of the other illnesses for which imaging is obtained. Tests may also be ordered by providers without continuity of care, as occurs in the emergency department (ED). Patients may thus be unaware of incidental findings or receive inadequate direction for follow-up when there is no clear chain of responsibility. Racially disparate populations are specifically at risk and often face barriers to accessing primary care providers (PCPs), leading to increased use of the ED. In one study, a higher proportion of Black and Hispanic patients (38.3% and 28.1%, respectively) had initial imaging identifying an IPN performed in the ED compared to White patients (10.7%), who were more likely to have outpatient scans.
Previous studies indicate that only 38% of patients receive guideline concordant care once diagnosed with an IPN. Lung cancer was diagnosed in 8% of these patients undergoing such care compared to only 1% in those who received less intensive evaluation. Similarly, the median time to diagnosis of a lung cancer was 1.3 months in the guideline concordant care group versus 12 months in the less intensive evaluation patients, again underscoring the importance of appropriate mechanisms of follow-up. The consequences of a missed nodule are clear.
Data suggest that racial and ethnic disparities exist in the follow-up of IPNs. In a study of 1,562 patients with an IPN requiring follow-up at a tertiary care center, only 49.1% of Hispanic patients and 55.1% of Black patients were notified of IPNs compared to 79.5% of White patients. Similarly, non-White patients had significantly lower rates of ordering and adherence to follow-up imaging and had an increased odds of delaying follow-up. While this discrepancy in care has been identified, few solutions exist to bridge the gap and underrepresented patients remain at higher risk of delayed diagnosis until advanced stages of disease.
Further compounding the difficulty in managing underserved patients with IPNs is the lack of programs for formalized follow-up, specifically in urban areas. In an advisory board meeting of major medical centers within New York City, only one formal nodule evaluation program associated with a center's ED was identified. New York Presbyterian Hospital Weill Cornell identified 539 patients with IPNs over a two-year period. After radiologic review, chest radiologists referred 289 patients for further consultation and of these 142 (26.3% of original population) were referred for evaluation by a pulmonologist or oncologist. While the results of this investigation and rates of cancer diagnoses are currently being tabulated, the large proportion of patients referred for concerning findings is quite notable.
Within New York City, the Montefiore Health System is uniquely positioned to conduct clinical research and bridge health care disparities by engaging underserved and underrepresented communities. The health system is comprised of 11 hospitals in the Bronx, Westchester, and the Hudson Valley in New York. The main campuses include two high volume EDs, including one of the five busiest in the country, and serve a diverse population of nearly 1.5 million residents in the Bronx. Previous data from Montefiore have demonstrated that of 855 primary lung cancers diagnosed between 2013 and 2016, only 417 (55%) were found in patients with an in-network PCP, illustrating the need for a better support system and for a systematic approach to identify and guide these patients. Furthermore, of the 175 of these patients who were eligible for LCS, only 33 had completed screening. Among screened patients, 64% were diagnosed with stage I/II non-small cell lung cancer, compared to only 29% of the lung cancers found outside of screening. In this latter group, 46% were diagnosed with metastatic disease. This demonstrates not only the value of screening in this at-risk population, but also emphasizes the need for prompt follow-up of incidentally detected lung abnormalities. A large proportion of this population in whom lung cancers were identified outside of screening was comprised of Black (46%) and Hispanic (34%) patients with a median per capita income of only approximately $20,000.12. The evaluation and implementation of a nodule detection program may thus extend care and improve the potential for survival in patients with reduced access to health care, where the ED may function as the primary care hub.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Group A | – | –Aim 1 (Part A). To utilize natural language processing (NLP) to identify all ED patients with incidentally detected lung nodules found on chest radiographs or chest or abdominal CT scans, and to develop a standardized referral and notification process Aim 1.1) Utilization of NLP to screen radiologic reports and identify nodules meeting criteria for follow-up per Fleischner Society Guidelines Aim 1.2) Creation of an electronic medical record-based notification system to alert patients and providers of the identification of an IPN that requires follow-up, tracked by a dedicated patient navigator Aim 1.3) Establishment of a multidisciplinary lung nodule management team, hereafter referred to as the lung nodule clinic, to ensure guideline-directed management of nodules with emphasis on high risk nodules as identified in subsequent aims |
| Group B | – | –Aim 2 (Part B). To clinically risk stratify patients with IPNs utilizing artificial intelligence (AI) processing of known clinical risks factors for pulmonary malignancy, such as age, smoking history, and history of malignancy, along with radiographic risk classifiers including nodule location, size, and imaging features. Aim 2.1) Development of an integrated classifier based on automated scanning and data retrieval from the electronic medical record (EMR) to stratify patients with IPNs as low, intermediate or high risk for malignancy, with factor analysis to assess contributions of individual factors to the model Aim 2.2) Prospective evaluation of the integrated classifier and comparison of automated integrated classifier to established manual risk calculators |
| Group C | – | –Aim 3 (Part C). To investigate biologic risk classifiers that may aid in the risk stratification of pulmonary nodules Aim 3.1) Evaluation of a blood-based gene expression assay for risk stratification of pulmonary nodules using biobanked specimens Aim 3.2) Prospective collection of plasma from patients enrolled in lung nodule clinic and evaluation of gene expression to assess malignancy risk |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The target population for the study consists of patients with an identified incidental pulmonary nodule seen at the Montefiore Medical Center after Feburary 1, 2023.
Key inclusion criteria (20 listed)
- Part A of the study seeks to capture IPNs and standardize mechanism for management will employ the following inclusion criteria:
- Above the age of 18
- Underwent an imaging study for any purpose other than lung cancer screening at a Montefiore Medical Center facility that identifies a pulmonary nodule
- Imaging results captured into the Epic electronic medical record
- Referred to the lung nodule clinic
Key exclusion criteria (2 listed)
- <18 years of age
- No evidence of a lung nodule through imaging
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Capture of incidentally identified lung nodules utilizing the electronic medical record
Time frame: Through completion of chart review, up to 1 year
To capture all incidentally identified lung nodules and create a multidisciplinary team for lung nodule management. Radiology and pulmonary providers will identify and report IPNs >=6mm denoted as positive imaging result at Montefiore. NLP will be used to identify IPNs using the Lung Orchestrator and IPNs will be captured by automated assessment of radiology. Cardiothoracic Imaging will assist in nodule identification using NLP. Following confirmation of a nodule requiring follow-up, the Lung Orchestrator will place the patient in a work queue. Patients diagnosed with lung cancer the year prior to the program will be reviewed retrospectively with NLP for determination on whether the approach increases adherence to IPN follow-up guidelines.
Performance comparison of EMR-based algorithm to establish risk
Time frame: Through development of algorithm, up to 1 year
Patients will be followed to develop a multi-component integrated risk classifier for stratification into low or intermediate malignancy risk. Risk calculators (Brock University; Mayo Clinic) will be used for assessment and evaluations designed to automatically populate in the EMR. Stratification will be based upon demographic factors, such as age, gender, race, smoking, and cancer history. Imaging characteristics such as emphysema, nodule location, size, and concerning features will be used. The aim is to develop an automated risk calculating algorithm based upon AI-mediated processing of clinical data and radiomics. These assessments will allow for real-time risk identification and the investigation of a novel model will incorporate data from a more diverse population.
Evaluation of LiquidLung plasma-based gene expression assay for biomarker subset selection using biobanked specimens
Time frame: Through evaluation of assay, up to 1.5 years
This assay is applicable for all concerning pulmonary nodules, represented by those patients referred to the lung nodule clinic. The lung nodule clinic manages both incidental and screen-detected lesions. Montefiore Health System has an established lung cancer screening program with over 1,000 screenings completed in the last year. Patients with suspicious nodules are recommended follow-up and also have potential to benefit from testing via non-invasive means.
Results and safety
The study was withdrawn before enrolling participants, so there are no results.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 Nov 2023.
- Background: PubMed 33433946Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer Statistics, 2021. CA Cancer J Clin. 2021 Jan;71(1):7-33. doi: 10.3322/caac.21654. Epub 2021 Jan 12.
- Background: PubMed 21714641National Lung Screening Trial Research Team; Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, Gareen IF, Gatsonis C, Marcus PM, Sicks JD. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011 Aug 4;365(5):395-409. doi: 10.1056/NEJMoa1102873. Epub 2011 Jun 29.
- Background: PubMed 33687470US Preventive Services Task Force; Krist AH, Davidson KW, Mangione CM, Barry MJ, Cabana M, Caughey AB, Davis EM, Donahue KE, Doubeni CA, Kubik M, Landefeld CS, Li L, Ogedegbe G, Owens DK, Pbert L, Silverstein M, Stevermer J, Tseng CW, Wong JB. Screening for Lung Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2021 Mar 9;325(10):962-970. doi: 10.1001/jama.2021.1117.
- Background: PubMed 28152136Jemal A, Fedewa SA. Lung Cancer Screening With Low-Dose Computed Tomography in the United States-2010 to 2015. JAMA Oncol. 2017 Sep 1;3(9):1278-1281. doi: 10.1001/jamaoncol.2016.6416.
- Background: PubMed 32546140Lake M, Shusted CS, Juon HS, McIntire RK, Zeigler-Johnson C, Evans NR, Kane GC, Barta JA. Black patients referred to a lung cancer screening program experience lower rates of screening and longer time to follow-up. BMC Cancer. 2020 Jun 16;20(1):561. doi: 10.1186/s12885-020-06923-0.
- Background: PubMed 24710850Wiener RS, Gould MK, Slatore CG, Fincke BG, Schwartz LM, Woloshin S. Resource use and guideline concordance in evaluation of pulmonary nodules for cancer: too much and too little care. JAMA Intern Med. 2014 Jun;174(6):871-80. doi: 10.1001/jamainternmed.2014.561.
- Background: PubMed 30798793Hanchate AD, Dyer KS, Paasche-Orlow MK, Banerjee S, Baker WE, Lin M, Xue WD, Feldman J. Disparities in Emergency Department Visits Among Collocated Racial/Ethnic Medicare Enrollees. Ann Emerg Med. 2019 Mar;73(3):225-235. doi: 10.1016/j.annemergmed.2018.09.007. Epub 2018 Oct 26.
- Background: PubMed 32771492Schut RA, Mortani Barbosa EJ Jr. Racial/Ethnic Disparities in Follow-Up Adherence for Incidental Pulmonary Nodules: An Application of a Cascade-of-Care Framework. J Am Coll Radiol. 2020 Nov;17(11):1410-1419. doi: 10.1016/j.jacr.2020.07.018. Epub 2020 Aug 7.
- Background: PubMed 29937386Su CT, Bhargava A, Shah CD, Halmos B, Gucalp RA, Packer SH, Ohri N, Haramati LB, Perez-Soler R, Cheng H. Screening Patterns and Mortality Differences in Patients With Lung Cancer at an Urban Underserved Community. Clin Lung Cancer. 2018 Sep;19(5):e767-e773. doi: 10.1016/j.cllc.2018.05.019. Epub 2018 Jun 5.
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- Results publication: PubMed 26214244Gould MK, Tang T, Liu IL, Lee J, Zheng C, Danforth KN, Kosco AE, Di Fiore JL, Suh DE. Recent Trends in the Identification of Incidental Pulmonary Nodules. Am J Respir Crit Care Med. 2015 Nov 15;192(10):1208-14. doi: 10.1164/rccm.201505-0990OC.
- Individual participant dataSharing planned: Undecided. Once the trial data collection is completed the potential for sharing data to expand the trial may occur.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Neel Chudgar, MD principal investigator
Montefiore Medical Center
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Lung; Node, run by Montefiore Medical Center at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 20 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: withdrawn, as of the sponsor's last update on 18 Nov 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study was withdrawn before enrolling participants, so there are no results.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Capture of incidentally identified lung nodules utilizing the electronic medical record (time frame: Through completion of chart review, up to 1 year). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05738031, which also lists 16 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 18 Nov 2023.