Anxiety and Depression as Potential Predictors for Shorter Time to Undergo Initial Surgical Treatment for Papillary Thyroid Cancer.
Dragan VujovicMathilda AlsenVikram VasanEric GendenMaaike A G van GerwenPublished in: Cancers (2024)
(1) Background: A pre-existing psychiatric condition may impact decision making by patients and/or physicians following a thyroid cancer diagnosis, such as potentially electing surgery over active surveillance, thus shortening the time to cancer removal. This is the first study to investigate the association between pre-existing anxiety and/or depression and time to receive surgical treatment for thyroid cancer. (2) Methods: Retrospective data were collected from 652 surgical thyroid cancer patients at our institution from 2018 to 2020. We investigated the time between thyroid cancer diagnosis and surgery, comparing patients with pre-existing anxiety and/or depression to those without. (3) Results: Patients with anxiety, depression, and both anxiety and depression had a significantly shorter time between diagnosis and surgery (51.6, 57, and 57.4 days, respectively) compared to patients without (111.9 days) ( p = 0.002, p = 0.004, p = 0.003, respectively). (4) Conclusions: Although little is known about the impact of pre-existing psychiatric conditions in the decision-making process for thyroid cancer surgery, this present study showed that anxiety and/or depression may lead to more immediate surgical interventions. Thus, psychiatric history may be an important factor for physicians to consider when counseling patients with thyroid cancer.
Keyphrases
- sleep quality
- minimally invasive
- coronary artery bypass
- decision making
- depressive symptoms
- end stage renal disease
- ejection fraction
- newly diagnosed
- primary care
- prognostic factors
- surgical site infection
- physical activity
- squamous cell carcinoma
- machine learning
- percutaneous coronary intervention
- papillary thyroid
- high resolution
- acute coronary syndrome
- coronary artery disease
- young adults
- cross sectional
- big data
- lymph node metastasis
- high speed