ILAs in CT Lung Cancer Screening Population

Interstitial Lung Disease Clinical Trial

Official title:

Interstitial Lung Abnormalities--Qualitative Imaging Cohort Study in CT Lung Cancer Screening Population

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04503044
• Other study ID #: 1628689
• Status: Completed
• Start date: January 30, 2021
• Est. completion date: June 30, 2021

Study information

• Verified date: August 2021
• Source: Lahey Clinic
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Interstitial Lung Abnormalities (ILA) have been previously defined as nondependent changes affecting more than 5% of any lung zone on computed tomography (CT) scans of the lung. Several studies suggest that the prevalence of ILA in participants in non-pulmonary research studies ranges anywhere from 7-9%. Work over the last decade has shown that, despite previous characterization as an asymptomatic research finding, ILA has significant clinical and biological consequences. These include reduced exercise capacity, functional limitations, decreased lung volumes, increased mortality, and in some cases histopathology similar to Idiopathic Pulmonary Fibrosis (IPF). ILA have been detected in lung cancer screening cohorts, where the prevalence of ILA is estimated to be between (10%-20%) to those noted in other research cohorts. Given that a significant proportion of those will have progression, CT lung cancer screening (CTLS) cohorts represent an ideal catchment population for future research and clinical trials. Lahey Hospital and Medical Center was one of the earliest clinical centers to develop a CTLS program in the country. Investigators propose to qualitatively characterize ILA in a large clinical CTLS population.

Description:

Investigators propose a retrospective, single-center study with following aims: 1. Characterize the prevalence and incidence of ILA at baseline and 5 year follow-up, respectively, and associated imaging phenotypes in CTLS cohort. 2. Baseline qualitative ILA features associated with clinical outcomes: Lung Cancer, Hospitalization, and Mortality. 3. Baseline qualitative ILA features associated with progressive ILA and fibrotic lung disease. 4. Clinical opportunity: to determine the % of CTLS patients with ILA who are at risk for progressive and development of fibrotic lung disease and who would benefit from specialized care referral and potential enrollment in clinical trials utilizing proven antifibrotic therapies Patient Selection: All clinical CT Lung Cancer Screening (CTLS) patients at Lahey Hospital and Medical Center (LHMC), Burlington, MA from January 1st, 2012 through September 30th, 2014 who had an in network primary care physician (n=1703). Patients with T4 screening scans will be scored for progression (n=653). To qualify for our study, patients had to satisfy the National Comprehensive Cancer Network (NCCN) Guidelines® Lung Cancer Screening Version 1.2012 high-risk criteria for lung cancer. Based on the NCCN Guidelines®, individuals eligible for lung cancer screening can be classified into NCCN group 1 and 2 as previously described. Patients in both groups were asymptomatic and had a physician order for CTLS, were free of lung cancer for ≥ 5 years, and had no known metastatic disease. Clinical Variables: Clinical variables were collected prospectively as part of the CTLS program and stored in a centralized data repository. Additional clinical variables not already available in this data repository will be collected retrospectively by manual review of the electronic medical record or pulled directly from the EMR and stored utilizing a custom-designed database (FileMaker ProVersion 11; Filemaker Inc, Santa Clara, California). Data was obtained through September 30th, 2019, patient demographics, past medical history, PFTs, immunization records, whether the patient was managed by a pulmonologist, and for hospital admissions with principal admission diagnoses. Hospital admissions will be collected using Lahey administrative coding data. Principal admission diagnoses of COPD, PNA, and CHF will be characterized based on diagnosis codes per 2018 Center for Medicare and Medicaid Services (CMS) condition-specific measures. CT Imaging: Clinically acquired, CTLS examinations which were performed on ≥64-row multidetector CT scanners (LightSpeed VCT and Discovery VCT [GE Medical Systems, Milwaukee, Wisconsin]; Somatom Definition [Siemens AG, Erlangen, Germany]; iCT [Philips Medical Systems, Andover, Massachusetts]) at 100 kV and 30 to 100 mA, depending on the scanner and the availability of iterative reconstruction software. Axial images were obtained at 1.25- to 1.5-mm thickness with 50% overlap and reconstructed with both soft tissue and lung kernels. Qualitative ILA Scoring: CT images will be scored utilizing Philips Intellispace PACS version 4.4 with clinical grade monitors. Scoring will be performed independently by two thoracic radiologists as described previously. Scores that are discordant between the two radiologists will be scored by a third by a pulmonologist with expertise in ILD. ILA: The presence of ILA features will be scores as (Yes/No/Indeterminate). Indeterminate will be defined as features identified unilaterally/focal involvement. ILA features that will be scored include: A) non dependent ground glass, B) reticular abnormalities, C) traction bronchiectasis and D) honeycombing. A) Non Dependent ground glass: (Yes/No/Indeterminate) defined as hazy increased attenuation of the lung with preservation of bronchial and vascular margins. B) Reticular abnormalities: (Yes/No/Indeterminate) defined as a collection of innumerable small linear opacities that, by summation, produce an appearance resembling a net. C) Traction Bronchiectasis: (Yes/No/Indeterminate) defined Traction bronchiectasis and traction bronchiolectasis respectively represents irregular bronchial and bronchiolar dilatation caused by surrounding retractile pulmonary fibrosis. D) Honeycombing: (Yes/No/Indeterminate) defined on CT as clustered cystic air spaces, typically of comparable diameters on the ordered of 3-10 mm but occasionally as large as 2.5 cm. Pattern: The overall pattern/Type of ILA findings will also be scored as the following: Subpleural, centrilobular, mixed or consistent with ILD (see UIP below). Subpleural: Defined as less than 1 cm from the pleural surface. Centrilobular: Defined as region of the bronchiolovascular core of the secondary pulmonary lobule. Location: Overall location ILA will then be scored as Upper lobe, lower lobe or diffuse. Extent: Overall extent of disease will be scored as Mild, Moderate and Marked. Usual Interstitial Pneumonia: Finally, the subset of scans that have evidence of fibrotic disease defined as traction bronchiectasis/honeycombing will then be classified as consistent with usual interstitial pneumonia (UIP) (Yes/Probable/No) based on Fleischner Criteria. UIP defined as Honey-combing with basal and subpleural distribution. Progression: The subset of patients who have had their T4 (5 year post baseline) screening scanned will be independently scored as above and in addition will be compared to their baseline scans and scored for progression: Stable, improved, and progressed.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 1703
• Est. completion date: June 30, 2021
• Est. primary completion date: June 30, 2021
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 80 Years

Eligibility

Inclusion Criteria: Patient who have undergone low-dose screening CT scan for lung cancer as part of the LHMC CTLS program from January 1, 2012 through September 30, 2014, with an in-network PCP. Exclusion Criteria: Any patient that does not meet inclusion criteria.

Related Conditions & MeSH terms

• Interstitial Lung Disease
• IPF
• Lung Diseases
• Lung Diseases, Interstitial

Intervention

Other:
• Retrospective observational study
No intervention to occur

Locations

Country	Name	City	State
United States	Lahey Hospital and Medical Center	Burlington	Massachusetts

Sponsors (2)

Lead Sponsor	Collaborator
Lahey Clinic	Genentech, Inc.

Country where clinical trial is conducted

United States, 

References & Publications (20)

Araki T, Putman RK, Hatabu H, Gao W, Dupuis J, Latourelle JC, Nishino M, Zazueta OE, Kurugol S, Ross JC, San José Estépar R, Schwartz DA, Rosas IO, Washko GR, O'Connor GT, Hunninghake GM. Development and Progression of Interstitial Lung Abnormalities in the Framingham Heart Study. Am J Respir Crit Care Med. 2016 Dec 15;194(12):1514-1522. — View Citation

Ash SY, Harmouche R, Putman RK, Ross JC, Diaz AA, Hunninghake GM, Onieva Onieva J, Martinez FJ, Choi AM, Lynch DA, Hatabu H, Rosas IO, San Jose Estepar R, Washko GR; COPDGene Investigators. Clinical and Genetic Associations of Objectively Identified Interstitial Changes in Smokers. Chest. 2017 Oct;152(4):780-791. doi: 10.1016/j.chest.2017.04.185. Epub 2017 May 12. — View Citation

Ash SY, Harmouche R, Ross JC, Diaz AA, Hunninghake GM, Putman RK, Onieva J, Martinez FJ, Choi AM, Lynch DA, Hatabu H, Rosas IO, Estepar RSJ, Washko GR. The Objective Identification and Quantification of Interstitial Lung Abnormalities in Smokers. Acad Radiol. 2017 Aug;24(8):941-946. doi: 10.1016/j.acra.2016.08.023. Epub 2016 Dec 15. — View Citation

Doyle TJ, Hunninghake GM, Rosas IO. Subclinical interstitial lung disease: why you should care. Am J Respir Crit Care Med. 2012 Jun 1;185(11):1147-53. doi: 10.1164/rccm.201108-1420PP. Epub 2012 Feb 23. Review. — View Citation

Doyle TJ, Washko GR, Fernandez IE, Nishino M, Okajima Y, Yamashiro T, Divo MJ, Celli BR, Sciurba FC, Silverman EK, Hatabu H, Rosas IO, Hunninghake GM; COPDGene Investigators. Interstitial lung abnormalities and reduced exercise capacity. Am J Respir Crit Care Med. 2012 Apr 1;185(7):756-62. doi: 10.1164/rccm.201109-1618OC. Epub 2012 Jan 20. — View Citation

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Horeweg N, van Rosmalen J, Heuvelmans MA, van der Aalst CM, Vliegenthart R, Scholten ET, ten Haaf K, Nackaerts K, Lammers JW, Weenink C, Groen HJ, van Ooijen P, de Jong PA, de Bock GH, Mali W, de Koning HJ, Oudkerk M. Lung cancer probability in patients with CT-detected pulmonary nodules: a prespecified analysis of data from the NELSON trial of low-dose CT screening. Lancet Oncol. 2014 Nov;15(12):1332-41. doi: 10.1016/S1470-2045(14)70389-4. Epub 2014 Oct 1. — View Citation

Hunninghake GM, Hatabu H, Okajima Y, Gao W, Dupuis J, Latourelle JC, Nishino M, Araki T, Zazueta OE, Kurugol S, Ross JC, San José Estépar R, Murphy E, Steele MP, Loyd JE, Schwarz MI, Fingerlin TE, Rosas IO, Washko GR, O'Connor GT, Schwartz DA. MUC5B promoter polymorphism and interstitial lung abnormalities. N Engl J Med. 2013 Jun 6;368(23):2192-200. doi: 10.1056/NEJMoa1216076. Epub 2013 May 21. — View Citation

Jin GY, Lynch D, Chawla A, Garg K, Tammemagi MC, Sahin H, Misumi S, Kwon KS. Interstitial lung abnormalities in a CT lung cancer screening population: prevalence and progression rate. Radiology. 2013 Aug;268(2):563-71. doi: 10.1148/radiol.13120816. Epub 2013 Mar 19. — View Citation

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Miller ER, Putman RK, Vivero M, Hung Y, Araki T, Nishino M, Washko GR, Rosas IO, Hatabu H, Sholl LM, Hunninghake GM. Histopathology of Interstitial Lung Abnormalities in the Context of Lung Nodule Resections. Am J Respir Crit Care Med. 2018 Apr 1;197(7):955-958. doi: 10.1164/rccm.201708-1679LE. — View Citation

Moyer VA; U.S. Preventive Services Task Force. Screening for lung cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2014 Mar 4;160(5):330-8. doi: 10.7326/M13-2771. — View Citation

National 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. — View Citation

Pastorino U, Silva M, Sestini S, Sabia F, Boeri M, Cantarutti A, Sverzellati N, Sozzi G, Corrao G, Marchianò A. Prolonged lung cancer screening reduced 10-year mortality in the MILD trial: new confirmation of lung cancer screening efficacy. Ann Oncol. 2019 Jul 1;30(7):1162-1169. doi: 10.1093/annonc/mdz117. Erratum in: Ann Oncol. 2019 Oct 1;30(10):1672. — View Citation

Putman RK, Gudmundsson G, Axelsson GT, Hida T, Honda O, Araki T, Yanagawa M, Nishino M, Miller ER, Eiriksdottir G, Gudmundsson EF, Tomiyama N, Honda H, Rosas IO, Washko GR, Cho MH, Schwartz DA, Gudnason V, Hatabu H, Hunninghake GM. Imaging Patterns Are Associated with Interstitial Lung Abnormality Progression and Mortality. Am J Respir Crit Care Med. 2019 Jul 15;200(2):175-183. doi: 10.1164/rccm.201809-1652OC. — View Citation

Putman RK, Hatabu H, Araki T, Gudmundsson G, Gao W, Nishino M, Okajima Y, Dupuis J, Latourelle JC, Cho MH, El-Chemaly S, Coxson HO, Celli BR, Fernandez IE, Zazueta OE, Ross JC, Harmouche R, Estépar RS, Diaz AA, Sigurdsson S, Gudmundsson EF, Eiríksdottír G, Aspelund T, Budoff MJ, Kinney GL, Hokanson JE, Williams MC, Murchison JT, MacNee W, Hoffmann U, O'Donnell CJ, Launer LJ, Harrris TB, Gudnason V, Silverman EK, O'Connor GT, Washko GR, Rosas IO, Hunninghake GM; Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) Investigators; COPDGene Investigators. Association Between Interstitial Lung Abnormalities and All-Cause Mortality. JAMA. 2016 Feb 16;315(7):672-81. doi: 10.1001/jama.2016.0518. — View Citation

Washko GR, Hunninghake GM, Fernandez IE, Nishino M, Okajima Y, Yamashiro T, Ross JC, Estépar RS, Lynch DA, Brehm JM, Andriole KP, Diaz AA, Khorasani R, D'Aco K, Sciurba FC, Silverman EK, Hatabu H, Rosas IO; COPDGene Investigators. Lung volumes and emphysema in smokers with interstitial lung abnormalities. N Engl J Med. 2011 Mar 10;364(10):897-906. doi: 10.1056/NEJMoa1007285. — View Citation

Whittaker Brown SA, Padilla M, Mhango G, Powell C, Salvatore M, Henschke C, Yankelevitz D, Sigel K, de-Torres JP, Wisnivesky J. Interstitial Lung Abnormalities and Lung Cancer Risk in the National Lung Screening Trial. Chest. 2019 Dec;156(6):1195-1203. doi: 10.1016/j.chest.2019.06.041. Epub 2019 Aug 9. — View Citation

* Note: There are 20 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Prevalence of ILA at baseline	Both presence and absence of ILA, as well as phenotypes, will be described for the entire cohort.	6 months
Primary	Association between baseline ILA (presence/absence) and time to mortality, time to first hospitalization, and time to development of cancer in the full cohort	Kaplan-Meier plots will be generated to visualize the associations between ILA variables and cancer, hospital admission and mortality. The log-rank test will be used to evaluate for a significant association. Cox regression proportional hazards models will be used to test for this association in both univariate and multivariable models. The multivariable model will be adjusted for age, sex, smoking status and pack years exposure.	6 months
Primary	Progression of ILA	Progression of ILA, defined as worsening of existing ILA or incidence of ILA over 5 years, will be described for the subset of patients with T4 imaging at 5 years. Univariate and multivariable analyses using logistic regression will be performed to test for associations between qualitative ILA characteristics (presence and absence, as well as individual phenotypes in separate models) and progression (yes/no). Stable and improved will be considered no progression, while incident ILA and worsening of existing ILA will be considered progression. Models will be checked for influential points. Multivariable models will be adjusted for sex, age, currently smoking, and pack years exposure.	6 months
Secondary	Association between phenotypes of ILA and outcomes	Using Kaplan-Meier plots and Cox regression analysis to examine association between phenotypes of ILA with time to first hospitalization, cancer, and mortality. The proportional hazards assumption will be checked for all Cox regression models.	6 months
Secondary	Association between ILA and time to cause-specific mortality, hospitalization.	Investigators will investigate the association between ILA (presence/absence) and time to cause-specific mortality (pulmonary, cardiac, cancer, other), as well as cause-specific hospitalization based on primary diagnosis (COPD, PNA, and CHF). The proportional hazards assumption will be checked for all Cox regression models.	6 months