David E Gerber1, Heidi A Hamann2, Claudia Chavez3, Olivia Dorsey3, Noel O Santini4, Travis Browning5, Cristhiaan D Ochoa6, Joyce Adesina4, Vijaya Subbu Natchimuthu4, Eric Steen7, Hong Zhu8, Simon J Craddock Lee8. 1. Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX; Division of Hematology-Oncology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX; Division of Hematology-Oncology, Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX. Electronic address: david.gerber@utsouthwestern.edu. 2. Department of Psychology, University of Arizona, Tucson, AZ; Department of Family and Community Medicine, University of Arizona, Tucson, AZ. 3. Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX. 4. Parkland Health and Hospital System, Dallas, TX. 5. Parkland Health and Hospital System, Dallas, TX; Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX. 6. Parkland Health and Hospital System, Dallas, TX; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX. 7. Parkland Health and Hospital System, Dallas, TX; Division of General Internal Medicine, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX. 8. Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX; Division of Hematology-Oncology, Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX.
Abstract
INTRODUCTION: For lung cancer screening, the available data are often derived from patients enrolled prospectively in clinical trials. We, therefore, investigated lung cancer screening patterns among individuals eligible for, but not enrolled in, a screening trial. PATIENTS AND METHODS: From February 2017 through February 2019, we enrolled subjects in a trial examining telephone-based navigation during low-dose computed tomography (LDCT) for lung cancer screening. We identified patients for whom LDCT was ordered and who were approached, but not enrolled, in the trial. We categorized nonenrollment as the patient had declined or could not be reached. We compared the characteristics and LDCT completion rates among these groups and the enrolled population using the 2-sample t test and χ2 test. RESULTS: Of 900 individuals approached for participation (mean age, 62 years; 45% women, 53% black), 447 were enrolled in the screening clinical trial. No significant demographic differences were found between the enrolled and nonenrolled cohorts. Of the 453 individuals not enrolled, 251 (55%) had declined participation and 202 (45%) could not be reached, despite up to 6 attempts. LDCT completion was significantly associated with enrollment status: 81% of enrolled individuals, 73% of individuals who declined participation, and 49% of those who could not be reached (P < .001). CONCLUSIONS: In the present single-center study, demographic factors did not predict for participation in a lung cancer screening trial. Lung cancer screening adherence rates were substantially lower for those not enrolled in a screening trial, especially for those who could not be contacted. These findings may inform the broader implementation of screening programs.
INTRODUCTION: For lung cancer screening, the available data are often derived from patients enrolled prospectively in clinical trials. We, therefore, investigated lung cancer screening patterns among individuals eligible for, but not enrolled in, a screening trial. PATIENTS AND METHODS: From February 2017 through February 2019, we enrolled subjects in a trial examining telephone-based navigation during low-dose computed tomography (LDCT) for lung cancer screening. We identified patients for whom LDCT was ordered and who were approached, but not enrolled, in the trial. We categorized nonenrollment as the patient had declined or could not be reached. We compared the characteristics and LDCT completion rates among these groups and the enrolled population using the 2-sample t test and χ2 test. RESULTS: Of 900 individuals approached for participation (mean age, 62 years; 45% women, 53% black), 447 were enrolled in the screening clinical trial. No significant demographic differences were found between the enrolled and nonenrolled cohorts. Of the 453 individuals not enrolled, 251 (55%) had declined participation and 202 (45%) could not be reached, despite up to 6 attempts. LDCT completion was significantly associated with enrollment status: 81% of enrolled individuals, 73% of individuals who declined participation, and 49% of those who could not be reached (P < .001). CONCLUSIONS: In the present single-center study, demographic factors did not predict for participation in a lung cancer screening trial. Lung cancer screening adherence rates were substantially lower for those not enrolled in a screening trial, especially for those who could not be contacted. These findings may inform the broader implementation of screening programs.
Authors: Ethan B Ludmir; Walker Mainwaring; Timothy A Lin; Austin B Miller; Amit Jethanandani; Andres F Espinoza; Jacob J Mandel; Steven H Lin; Benjamin D Smith; Grace L Smith; Noam A VanderWalde; Bruce D Minsky; Albert C Koong; Thomas E Stinchcombe; Reshma Jagsi; Daniel R Gomez; Charles R Thomas; C David Fuller Journal: JAMA Oncol Date: 2019-12-01 Impact factor: 31.777
Authors: Sandra Garcia; Ajit Bisen; Jingsheng Yan; Xian-Jin Xie; Suresh Ramalingam; Joan H Schiller; David H Johnson; David E Gerber Journal: J Thorac Oncol Date: 2017-08-09 Impact factor: 15.609
Authors: David E Gerber; Heidi A Hamann; Noel O Santini; Suhny Abbara; Hsienchang Chiu; Molly McGuire; Lisa Quirk; Hong Zhu; Simon J Craddock Lee Journal: Contemp Clin Trials Date: 2017-07-05 Impact factor: 2.226
Authors: Drew W Rasco; Yang Xie; Jingsheng Yan; Jennifer R Sayne; Celette Sugg Skinner; Jonathan E Dowell; David E Gerber Journal: Oncologist Date: 2009-04-28
Authors: Tracy Onega; Eric J Duell; Xun Shi; Eugene Demidenko; Daniel Gottlieb; David C Goodman Journal: Med Care Res Rev Date: 2009-05-19 Impact factor: 3.929
Authors: Ayal A Aizer; Ming-Hui Chen; Ellen P McCarthy; Mallika L Mendu; Sophia Koo; Tyler J Wilhite; Powell L Graham; Toni K Choueiri; Karen E Hoffman; Neil E Martin; Jim C Hu; Paul L Nguyen Journal: J Clin Oncol Date: 2013-09-23 Impact factor: 44.544
Authors: Tri Le; Stacie Miller; Emily Berry; Sarah Zamarripa; Aurelio Rodriguez; Benjamin Barkley; Asha Kandathil; Cecelia Brewington; Keith E Argenbright; David E Gerber Journal: J Am Coll Radiol Date: 2022-02-07 Impact factor: 5.532
Authors: Yukiko Kunitomo; Brett Bade; Craig G Gunderson; Kathleen M Akgün; Alexandria Brackett; Lynn Tanoue; Lori A Bastian Journal: J Gen Intern Med Date: 2022-07-15 Impact factor: 6.473
Authors: Harris Majeed; Hong Zhu; Sarah A Williams; Heidi A Hamann; Vijaya Subbu Natchimuthu; Jessica Lee; Noel O Santini; Travis Browning; Tanushree Prasad; Joyce O Adesina; Minh Do; David Balis; Juana Gamarra de Willams; Ellen Kitchell; David H Johnson; Simon J Craddock Lee; David E Gerber Journal: Clin Lung Cancer Date: 2022-04-29 Impact factor: 4.840
Authors: David E Gerber; Heidi A Hamann; Olivia Dorsey; Chul Ahn; Jessica L Phillips; Noel O Santini; Travis Browning; Cristhiaan D Ochoa; Joyce Adesina; Vijaya Subbu Natchimuthu; Eric Steen; Harris Majeed; Amrit Gonugunta; Simon J Craddock Lee Journal: Clin Lung Cancer Date: 2020-12-11 Impact factor: 4.840