Validation of Self-Reported Lung Cancer Diagnoses in the National Lung Screening Trial (NLST): A Retrospective Analysis of Participant Annual Surveys
Principal Investigator
Name
Peter Bach
Degrees
M.D., M.A.P.P.
Institution
Delfi Diagnostics, Inc.
Position Title
Chief Medical Officer
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-1479
Initial CDAS Request Approval
Nov 13, 2025
Title
Validation of Self-Reported Lung Cancer Diagnoses in the National Lung Screening Trial (NLST): A Retrospective Analysis of Participant Annual Surveys
Summary
Large-scale clinical trials and longitudinal cohort studies, such as the National Lung Screening Trial (NLST), are foundational to evidence-based medicine. These studies often supplement rigorous medical record abstraction with participant self-reported outcomes via questionnaires for long-term follow-up and efficiency. The accuracy of this self-reported data is critical for the validity of secondary analyses and for designing future trials, yet it is not always well-characterized.
This project will conduct a retrospective analysis of data from the NLST to determine the accuracy of self-reported lung cancer diagnoses. We will compare participant responses on the Annual Study Update (ASU) forms, including the question regarding a self-reported lung cancer diagnosis, against the gold standard of information captured from medically-confirmed lung cancer diagnoses that is captured through the NLST’s comprehensive medical record abstraction protocol conducted after the individuals’ self-report date.
The primary analysis will involve calculating the sensitivity and specificity of the self-reported data. We will compare the date of the survey response to the date of the confirmed diagnosis to evaluate concordance, where the confirmed diagnosis will constitute the gold standard. As the events occur over time we will pay particular attention to the timing of the diagnosis relative to the time of the survey response. Subgroup analyses may be conducted within important demographic variables such as age, sex, race, and smoking status. We will also examine reports of other key diagnoses, including the occurrence of other cancer types.
The findings from this study will provide crucial evidence on the reliability of participant self-reporting in a major cancer screening trial. This will directly inform the design of future clinical trials and long-term follow-up protocols, potentially identifying more efficient methods for outcome ascertainment. Furthermore, it will provide essential context for researchers conducting ancillary studies using the valuable NLST public-use dataset.
Aims
Primary Goal: To assess the validity of participant self-reported cancer diagnoses within the National Lung Screening Trial.
To determine the sensitivity and specificity for self-reported cancer diagnoses on the Annual Study Update (ASU) forms, using the NLST's medically-confirmed cancer diagnosis as the gold standard. The primary measure is for lung cancer self report.
Subgroup analyses may be completed within demographic variables of interest to determine differences across NLST participant groups (e.g., age, sex, race, etc.).
To observe the accuracy and concordance of self-reported cancer in the annual study update forms (ASU), with confirmed lung cancer as per NLST criteria for medical record abstraction, and to analyze demographic and clinical factors associated with discordant self-reports.
To quantify the concordance in timing between the date of the ASU survey response reporting a lung cancer diagnosis and the date of the confirmed diagnosis from medical record abstraction to characterize reporting delays.
Collaborators
Peter Bach Delfi Diagnostics, Inc.
Niti Trivedi Delfi Diagnostics, Inc.
Dave Morgenstern Delfi Diagnostics, Inc.
Benjamin Wilson Delfi Diagnostics, Inc.
Yuhua Zong Delfi Diagnostics, Inc.
Niti Trivedi Delfi Diagnostics, Inc.
Niti Trivedi Delfi Diagnostics, Inc.
Daniel Civello Delfi Diagnostics, Inc.