关键词: 非小细胞肺癌, 治疗质量, 首次住院天数, 多项式回归

Abstract: Objective Based on polynomial logistic regression model,this study aimed to analyze the optimal length of hospital stay for patients with non-small cell lung cancer(NSCLC)at different stages to achieve the best treatment quality,providing reference for improving treatment quality and formulating relevant policies. Methods The data of NSCLC cases were collected and 16 diagnosis and treatment process indicators were selected.Patients were stratified according to the stage of lung cancer.A polynomial logistic regression model was constructed,including patient characteristics to analyze the impact of first hospitalization days on the quality of comprehensive treatment. Results A total of 10,053 patients with NSCLC were collected in this study,with a median comprehensive treatment quality score of 0.60.According to the staging of lung cancer,patients were divided into the early stage group(stage Ⅰ-Ⅱ),locally advanced stage group(stage Ⅲ),and advanced stage group(stage Ⅳ).The first hospitalization days and treatment quality of each subgroup showed a non-linear relationship.The polynomial model results showed that after adjusting the characteristics of patients,the length of hospitalization day and the quadratic term of hospital stay had a statistically significant impact on treatment quality in each subgroup:early patients had a first hospital stay of 18 days,and locally advanced and advanced patients had a first hospital stay of 22 days,with the highest probability of achieving high treatment quality. Conclusion Patients in different stages have varying degrees of illness and treatment plans,resulting in different first hospitalization days corresponding to the highest probability of obtaining high-quality treatment.Hospitals can improve the treatment quality and medical efficiency by implementing standardized diagnosis and treatment guidelines,strengthening the management of the diagnosis and treatment process,and reasonably controlling the first hospitalization time of patients in different stages.

Key words: Non-small cell lung cancer, Quality of treatment, First hospitalization days, Polynomial regression