Exploring clinical pathways to a metastatic lung cancer diagnosis: A latent class analysis using North Carolina multi-payer claims data

探索转移性肺癌诊断的临床路径:基于北卡罗来纳州多方支付索赔数据的潜在类别分析

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Abstract

BACKGROUND: Non-small cell lung cancer (NSCLC) is the leading cause of cancer mortality in the U.S. and North Carolina, accounting for more than 5,600 deaths annually in NC. Nearly half of patients are diagnosed with metastatic disease, and the five-year survival rate is 12%. This study identified clinical pathways preceding the diagnosis of metastatic NSCLC using the North Carolina Central Cancer Registry (NCCR) linked with multi-payer utilization data. METHODS: We identified individuals diagnosed with de novo metastatic NSCLC between 2015 and 2019 in the NCCR and linked them to claims-based enrollment and utilization files. Latent class analysis examined pre-diagnostic healthcare encounters, including ambulatory visits, hospitalizations, emergency/urgent department visits, lung cancer screening, and specialist visits, using ICD-9/ICD-10 codes. We evaluated demographic and clinical predictors of pathway membership and examined associations between groups and receipt of tumor molecular testing. RESULTS: Among 11,613 individuals, four diagnostic pathways emerged: comprehensive healthcare users (12%), emergency care users (24%), primary care-only users (n27%), and low healthcare users (37%). Pathway membership was significantly associated with molecular testing. Primary care-oriented users had the highest adoption of comprehensive or individual biomarker testing, whereas emergency-dominant and low-utilization groups had substantially lower rates. CONCLUSIONS: Although nearly two-thirds of patients engaged with the healthcare system before a metastatic NSCLC diagnosis, over one-third had minimal pre-diagnostic contact. Differences in molecular testing across pathways indicate disparities in access to precision oncology. IMPACT: Interventions tailored to utilization patterns-particularly for low-contact and emergency-based care users-may improve diagnostic equity, biomarker testing, and outcomes.

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