Grant Number:	5R01CA258352-03 Interpret this number
Primary Investigator:	Farjah, Farhood
Organization:	University Of Washington
Project Title:	Comparative-Effectiveness of Pretreatment Lung Cancer Nodal Staging
Fiscal Year:	2024

ABSTRACT Our goal is to reduce diagnostic and treatment errors, improve survival, and increase the value of care for lung cancer patients by improving our ability to select patients who benefit from a pretreatment lymph node biopsy. Accurately determining whether cancer has spread to lymph nodes and the extent of spread (a process called nodal staging) is critical for appropriate treatment selection. Understaging can lead to omission of chemotherapy or unnecessary surgery. Overstaging can lead to unnecessary chemotherapy and omission of surgery. Diagnostic and treatment errors negatively impact survival. These errors commonly occur when using imaging alone for nodal staging. A biopsy can reduce the chances of error, but it can also result in rare, life- threatening adverse events. Each biopsy costs ~$5,000. Practice guidelines recommend selectively performing a biopsy when imaging findings suggest nodal disease. However, national biopsy rates are less than half of what they should be. Moreover, there is 25-fold facility-level variability not explained by access to care, case- mix, or clinician or facility characteristics. These findings, along with the low levels of evidence underlying guideline recommendations, suggest true clinical and scientific uncertainty over the indications for lymph node biopsy. We conducted a pilot study to better understand how well guideline recommendations select patients for biopsy and learned that guideline-concordant nodal staging selects all patients with true nodal disease for biopsy and two-thirds of patients without true nodal disease for biopsy. Additionally, we developed and validated an alternative risk-based nodal staging strategy that uses a prediction model to stratify and select patients for lymph node biopsy. Preliminary data show that it identifies nearly all patients with true nodal disease for biopsy but selects fewer patients without nodal true nodal disease for biopsy. However, the relationship between selection strategies for lymph node biopsy and patient outcomes remains unknown. We hypothesize that guideline-concordant nodal staging is associated with higher 5-year survival rates compared with guideline-discordant nodal staging (Aim I) and that risk-based nodal staging is equivalent to guideline- concordant nodal staging in terms of survival but superior in terms of lower biopsy-related adverse events and healthcare expenditures (Aim II). Testing these hypotheses will require ~4,000 patients; therefore, a trial is not feasible at this time. We will create a novel cohort of lung cancer patients using the Cancer Research Network infrastructure to conduct Aim I using an observational, comparative-effectiveness study design with advanced regression techniques and machine learning to minimize confounding. Additionally, we will use patient-level data from this cohort as model inputs in a comparative-effectiveness simulation model that we will develop to conduct Aim II. Findings from this study will lead to: 1) developing and testing implementation strategies designed to increase guideline-concordant nodal staging, 2) alternative guideline recommendations for nodal staging, and/or 3) justifying trials comparing outcomes between different nodal staging strategies.





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