# Natural Language Processing-Assisted Incidental Pulmonary Nodule Evaluation Program: Impact on Lung Cancer Outcomes

**Authors:** Noa Tamam Shenholz, Keren Hod, Liat Toderis, Noam Fink, Arnon Makori, Michael Peer, Evgeni Gershman, Merav A. Ben-David, Elizabeth Dudnik

PMC · DOI: 10.3390/medsci14010104 · 2026-02-21

## TL;DR

This study shows that using natural language processing to evaluate lung nodules in CT reports helps detect lung cancer earlier and improves treatment timelines.

## Contribution

The study introduces an NLP-assisted program for incidental pulmonary nodule evaluation that improves lung cancer diagnostic outcomes.

## Key findings

- NLP-assisted evaluation led to a significant stage shift toward earlier-stage lung cancer detection.
- Time to systemic treatment and radiotherapy was significantly shorter in the NLP-assisted group.
- The program improved diagnostic efficiency and expedited time-critical interventions.

## Abstract

Introduction: Early detection and timely treatment (Tx) initiation are critical to improving lung cancer (LC) outcomes. This study assessed the natural language processing (NLP)-assisted incidental pulmonary nodule (IPN) evaluation program, which employs chest computer tomography (CT) report analysis as an LC diagnostic screening (LCS) tool to identify suspicious lung findings (SLF) necessitating further investigation, and evaluated its impact on prognosis and diagnostic work-up and Tx timelines for patients with LC. Materials and Methods: Consecutive LC patients (n = 200) diagnosed at Assuta Medical Centers (AMC) between January 2019 and December 2022 were retrieved from the AMC electronic database using the MDClone big data platform, and divided into two groups: group A (NLP-assisted IPN evaluation, n = 100) and group B (traditional referral for evaluation of SLF by the community physician, n = 100). Stage at diagnosis, different diagnostic work-up and Tx timelines, and overall survival (OS) were assessed. Results: The NLP-assisted IPN evaluation program led to a significant stage shift (stage I disease: 48% vs. 27% in groups A and B, respectively, p = 0.013). Although the time from imaging to Tx initiation was similar (2.1 ± 5.3 months vs. 2.6 ± 5.9 months in groups A and B, respectively, p = 0.654), the time to systemic Tx (p = 0.035) and the time to radiotherapy (p = 0.044) were significantly shorter in group A. Conclusions: Implementing an NLP-assisted IPN evaluation program may enable earlier LC detection, driving a stage shift towards earlier diagnosis, improved diagnostic efficiency, and expedited time-critical interventions.

## Linked entities

- **Diseases:** lung cancer (MONDO:0005138)

## Full-text entities

- **Genes:** EGFR (epidermal growth factor receptor) [NCBI Gene 1956] {aka ERBB, ERBB1, ERRP, HER1, NISBD2, NNCIS}, CD274 (CD274 molecule) [NCBI Gene 29126] {aka ADMIO5, B7-H, B7H1, PD-L1, PDCD1L1, PDCD1LG1}, Braf (B-Raf proto-oncogene, serine/threonine kinase) [NCBI Gene 109880] {aka 9930012E13Rik, B-raf, Braf-2, Braf2, C230098H17, D6Ertd631e}, Egfr (epidermal growth factor receptor) [NCBI Gene 13649] {aka 9030024J15Rik, Erbb, Errb1, Errp, Wa5, wa-2}, Met (met proto-oncogene, receptor tyrosine kinase) [NCBI Gene 17295] {aka HGF, HGFR, Par4, c-Met}, Cd274 (CD274 antigen) [NCBI Gene 60533] {aka A530045L16Rik, B7h1, Pdcd1l1, Pdcd1lg1, Pdl1}, Alk (anaplastic lymphoma kinase) [NCBI Gene 11682] {aka CD246, Tcrz}, Kras (Kras proto-oncogene, GTPase) [NCBI Gene 16653] {aka K-Ras, K-Ras 2, K-ras, Ki-ras, Kras-2, Kras2}, Ret (ret proto-oncogene) [NCBI Gene 19713] {aka PTC, RET51, RET9, c-Ret}, Ros1 (Ros1 proto-oncogene, receptor tyrosine kinase) [NCBI Gene 19886] {aka Ros-1, c-ros}
- **Diseases:** NSCLC (MESH:D002289), IPN (MESH:D055613), stage I-II disease (MESH:D058625), LC (MESH:D008175), death (MESH:D003643), I (MESH:D006969), Adenocarcinoma (MESH:D000230), LDCT (MESH:C000719218), injury to (MESH:D014947), COVID-19 (MESH:D000086382), stage I (MESH:D062706), SLF (MESH:D009461), ACS (MESH:D009369), weight loss (MESH:D015431), thoracic tumor (MESH:D013899)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13027686/full.md

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Source: https://tomesphere.com/paper/PMC13027686