# Serum markers for prognostic value of EGFR-TKI in lung adenocarcinoma with bone metastases: a retrospective study

## TL;DR

This study identifies blood markers that help predict how well lung cancer patients with bone metastases will respond to a specific drug treatment.

## Contribution

A new nomogram based on serum markers improves prediction of treatment outcomes for EGFR-TKI therapy in lung adenocarcinoma with bone metastases.

## Key findings

- Age, NLR, CEA, and Cyfra21-1 were significant predictors in the Cox model.
- The model had a c-index of 0.644 and good calibration for survival prediction.
- A nomogram was created to guide personalized treatment decisions.

## Abstract

Lung adenocarcinoma is a prevalent malignancy. Mutations in the epidermal growth factor receptor (EGFR) have introduced novel prospects for targeted therapies. However, the status of EGFR mutations alone may be insufficient to fully predict treatment outcomes. To this end, the present research was performed to evaluate the serum markers associated with epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) treatment in patients with lung adenocarcinoma and bone metastases, specifically focusing on the prognostic value of EGFR-TKI therapy.

A retrospective analysis was conducted on 164 patients diagnosed with lung adenocarcinoma and bone metastases at Yunnan Cancer Hospital between January 2019 and December 2020. Clinical and follow-up data were collected, and a Cox regression model was employed to evaluate the combined predictive value of serum markers for survival outcomes.

The findings revealed that variables identified through Cox regression analysis included age, the neutrophil-to-lymphocyte ratio (NLR), carcinoembryonic antigen (CEA), and Cytokeratin 19 fragment (Cyfra21-1), all exhibiting significance levels of P < 0.05. The Cox model exhibited a c-index of 0.644, and the calibration curve demonstrated satisfactory performance, indicating the moderate predictive capacity of the model. A nomogram was subsequently constructed to visualize these results.

This research successfully developed a nomogram based on the Cox regression model to predict prognosis and treatment outcomes in patients with lung adenocarcinoma and bone metastases undergoing EGFR-TKI therapy. This facilitates the avoidance of poor treatment outcomes by enabling individualized therapeutic approaches, thereby simplifying the development of the most appropriate treatment plans and ultimately improving patient prognosis.