Heliyon (Jan 2024)

Research of correlation between personality traits and hormones with the nature of pulmonary nodules

  • Yonggang Teng,
  • Chaoli Wang,
  • Yabo Zhao,
  • Yongyu Teng,
  • Chaoren Yan,
  • Yongkai Lu,
  • Shijun Duan,
  • Jian Wang,
  • Xiaofei Li

Journal volume & issue
Vol. 10, no. 1
p. e22888

Abstract

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Background: Rising rates of lung cancer screening have contributed to an increase in pulmonary nodule diagnosis rates. Studies have shown that psychosocial factors and hormones have an impact on the development of the oncological diseases. Therefore, we conducted this study to explore the potential relationship between pulmonary nodules pathology and patient personality traits and hormone levels. Methods: This study enrolled 245 individuals who had first been diagnosed with pulmonary nodules in Tangdu Hospital and admitted for surgery. The personality profile of these patients was analyzed on admission using the C-Type Behavioral Scale and hormone levels were measured in preoperative serum samples. Associations between nodule pathology, personality scores, and hormone levels, were then assessed through Statistical methods analysis. Results: Behavioral scale analyses revealed significant differences four items, including depression, anger outward, optimism, and social support (P< 0.05). Specifically, patients with higher depression scores were more likely to harbor malignant pulmonary nodules, as were patients with lower levels of anger outward, social support, and optimism. Univariate analyses indicated that nodule pathology was associated with significant differences in nodule imaging density, CT value, testosterone levels, and T4 levels(P< 0.05), and logistic regression analyses revealed pulmonary nodule imaging density and T4 levels to be significant differences of nodule pathology. Conclusion: The results showed a significant association between nodules pathology and the personality characteristics of the patients (depression, anger outward, optimism, social support), the patients' T4 levels and the imaging density of the nodules.

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