Each year 1.5 million people are diagnosed with an incidentally (not screen) detected lung nodule. The diagnosis is important because it may represent an early-stage lung cancer, but 90% of incidentally detected lung nodules are benign. Accordingly, the intensity of a lung nodule evaluation must weigh the benefits of early-detection and treatment (e.g. cure) against the risks of diagnostic tests (e.g. radiation exposure, procedure-related adverse events). Practice guideline recommendations are intended to optimize risks and benefits but adherence rates are only 55%. One reason for this poor adherence is the low level of evidence supporting guidelines leading to legitimate uncertainty about their effectiveness, safety, and impact on health care resources. This uncertainty is significant because it is unclear whether interventions should be developed to increase guideline adherence or if new approaches to varying the intensity of a nodule evaluation are needed. Until recently, an important barrier to generating a higher level of evidence has been an inability to identify and longitudinally follow a cohort of individuals with an incidentally detected lung nodule. Investigators from the Cancer Research Network (CRN) have determined that individuals with an incidentally detected lung nodule can be efficiently and accurately identified using a combination of administrative data, electronic radiology reports, natural language processing, and some chart abstraction. Additionally, investigators found that providers routinely document lung cancer risk factors (e.g. age and smoking status) that allow for a study of adherence to Fleischner Society guidelines, and this information is readily available in a structured format within the electronic medical record. Furthermore, other CRN investigators have developed methods that allow for estimation of radiation exposure from imaging studies and the costs of care delivery within integrated healthcare systems. This work allows us to propose the first-ever multi-site comparative-effectiveness study of individuals with an incidentally detected lung nodule diagnosed between 2005 and 2015. The study aims to compare the: 1) effectiveness (e.g. incidence of early-stage lung cancer), 2) potential harms (e.g. radiation exposure, procedure-related adverse events), and 3) two-year total costs of care of varying intensities of lung nodule evaluation (e.g. guideline concordant versus more intense versus less intense evaluations). We hypothesize that less intense nodule evaluations are associated with a lower incidence of early-stage lung cancer compared to guideline concordant care, and more intense nodule evaluations are associated with greater radiation exposure, more procedure-related adverse events, and higher costs. Findings from this study will determine whether limited resources should be invested in developing system-level interventions designed to increase guideline adherence or studying alternative approaches to lung nodule evaluation (e.g. risk- prediction models, biomarkers). This line of investigation is expected to ultimately improve the care and outcomes of individuals with an incidentally detected lung nodule.

Public Health Relevance

This investigation will ultimately lead to better care and outcomes for over 1.5 million people per year with an incidentally (not screen) detected lung nodule. The study compares the effectiveness (early-detection of lung cancer), safety (radiation exposure, procedure related adverse-events), and costs of varying intensities of lung nodule evaluation (e.g. a guideline-concordant, more intense, or less intense work-up). Knowledge gained from this investigation will direct limited resources towards development of system-level interventions designed to increase guideline adherence (e.g. standardized radiology reports, centralized nodule care) or investigating alternative approaches to lung nodule evaluation (e.g. risk-prediction, biomarkers).

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA207375-04
Application #
9830022
Study Section
Health Services Organization and Delivery Study Section (HSOD)
Program Officer
Doria-Rose, Paul P
Project Start
2017-12-01
Project End
2020-11-30
Budget Start
2019-12-01
Budget End
2020-11-30
Support Year
4
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Washington
Department
Surgery
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195