# Medical expenses and influencing factors in lung cancer patients: a comparative analysis between surgical and non-surgical cases from Xiamen, China

## TL;DR

This study compares medical costs and factors affecting surgical decisions for lung cancer patients in Xiamen, China, finding that surgery is much more expensive and influenced by age, gender, and hospital stay length.

## Contribution

The study identifies novel demographic and clinical predictors of surgical intervention and quantifies significant cost differences between surgical and non-surgical lung cancer treatments.

## Key findings

- Surgical patients incurred 8.5-fold higher median costs compared to non-surgical patients.
- Female gender, younger age, and prolonged hospitalization were key predictors of surgical intervention.
- Medical consumables showed a >2,000-fold cost disparity between surgical and non-surgical cases.

## Abstract

To investigate medical expenses and factors influencing surgical choices among lung cancer patients in a tertiary hospital in Xiamen, China, and to identify key cost differences between surgical and non-surgical approaches.

In this retrospective cross-sectional study, we analyzed 3,806 lung cancer patients treated in 2023. Data analysis was performed using SPSS 27.0, with independent-sample t-tests for cost comparisons and binary logistic regression to identify factors influencing surgical intervention.

The study analyzed 3,806 lung cancer patients (60.7% male, 51.1% aged 61–80 years), revealing significant demographic and clinical predictors of surgical intervention. Multivariate analysis identified female gender (adjusted OR = 1.989, 95%CI:1.624–2.436, p < 0.001), younger age (61–80 years: adjusted OR = 0.454, 95% CI:0.305–0.676, p = 0.001; >80 years: adjusted OR = 0.353, 95%CI: 0.161–0.774, p = 0.009), and prolonged hospitalization (adjusted OR = 106.729, 95%CI: 79.485–143.312, p < 0.001) as key determinants, while insurance type showed no association. Surgical patients incurred 8.5-fold higher median costs (¥48,610 vs. ¥5,676), with medical consumables exhibiting the most pronounced disparity (>2,000-fold difference). The predictive model demonstrated excellent discrimination (AUC = 0.904), calibration (Hosmer-Lemeshow p = 0.402), and specificity (81.6%) at a 46.75% probability threshold, with length of stay being the strongest individual predictor (univariate AIC = 2,874 vs. full model AIC = 2,802). Insurance type showed no significant association with surgical treatment in either univariate or multivariate analyses.

Gender, age, and hospital stay length were major factors associated with surgical decisions in lung cancer patients, with surgery significantly increasing total medical costs. Policy improvements in the management of high-value medical consumables and insurance reimbursement are needed to reduce financial burdens and enhance surgical accessibility.