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Patterns of Comorbidities in Lung Cancer Patients and Survival
Alessandra Buja1, Marcello Di Pumpo2,3, Massimo Rugge4
1Department of Cardiologic, Vascular and Thoracic Sciences, and Public Health, University of Padova, 35128 Padova, Italy.
Introduction:
Comorbidities affect diagnosis and treatments in cancer patients. This study explores the prevalence and patterns of comorbidities in non-small cell lung cancer (NSCLC) patients and their association with survival.
Materials And Methods:
This retrospective population-based cohort study included 1674 incident NSCLC patients. Comorbidities were classified based on the ICD-9-CM system, with 13 disease categories analyzed. Patients with more than two comorbidities were classified into three mutually exclusive and exhaustive latent classes (Latent Class Analysis [LCA]). The optimal number of latent classes was determined by applying the Akaike Information Criterion. Cox regression models were run to assess overall and cancer-specific mortality, adjusting for the comorbidity groups, sex, age, and stage at diagnosis.
Results:
In 1674 NSCLC patients, the most prevalent medical conditions were respiratory (35.8%) and cardiovascular (33.5%). The Cox regression showed that even one comorbidity is associated with an increased hazard of overall mortality (HR = 1.33, 95%CI: 1.11-1.59, p = 0.002). LCA-derived Class-1 (cardiovascular-respiratory and endocrine) reported HR = 1.74 (95%CI: 1.39-2.17, p < 0.001), Class-2 (multi-organ) HR = 1.44 (95%CI: 1.18-1.77, p < 0.001), and Class-3 (socio-multifactorial-neuro) HR = 1.62 (95%CI: 1.36-1.93, p < 0.001). Instead, in patients with one comorbidity, NSCLC-specific mortality showed no significant trend towards increased risk (HR = 1.17, 95%CI: 1.00-1.43, p = 0.114). Significant associations emerged between NSCLC-specific mortality and LCA-classes: Class-1: HR = 1.49 (95%CI: 1.20-1.91, p = 0.001); Class-2 HR = 1.25 (95%CI: 1.0-1.57 p = 0.048); and Class-3: HR = 1.23 (95%CI: 1.00-1.48, p = 0.035).
Conclusions:
The adverse impact of comorbidities on NSCLC-specific mortality requires their inclusion as risk factors in cancer treatment and prognosis.
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