Computational prediction of State anxiety in Asian patients with cancer susceptible to chemotherapy-induced nausea and vomiting
Yap, Kevin Yi-Lwern, Low, Xiu Hui, Chui, Wai Keung and Chan, Alexandre. (2012) Computational prediction of State anxiety in Asian patients with cancer susceptible to chemotherapy-induced nausea and vomiting. Journal of Clinical Psychopharmacology, Vol.32 (No.2). pp. 207-217. ISSN 0271-0749Full text not available from this repository.
Official URL: http://dx.doi.org/10.1097/JCP.0b013e31824888a1
State anxiety, a risk factor for chemotherapy-induced nausea and vomiting (CINV), is a subjective symptom and difficult to quantify. Clinicians need appropriate anxiety measures to assess patients' risks of CINV. This study aimed to determine the anxiety characteristics that can predict CINV based on computational analysis of an objective assessment tool. A single-center, prospective, observational study was carried out between January 2007 and July 2010. Patients with breast, head and neck, and gastrointestinal cancers were recruited and treated with a variety of chemotherapy protocols and appropriate antiemetics. Chemotherapy-induced nausea and vomiting characteristics and antiemetic use were recorded using a standardized diary, whereas patients' anxiety characteristics were evaluated using the Beck Anxiety Inventory. Principal component (PC) analysis was performed to analyze the anxiety characteristics. A subset known as principal variables, which had the highest PC weightings, was identified for patients with and without complete response, complete protection, and complete control. Chemotherapy-induced nausea and vomiting events and anxiety characteristics of 710 patients were collated; 51%, 30%, and 20% were on anthracycline-, oxaliplatin-, and cisplatin-based therapies, respectively. Most patients suffered from delayed CINV, with decreasing proportions achieving complete response (58%), complete protection (42%), and complete control (27%). Seven symptoms (fear of dying, fear of the worst, unable to relax, hot/cold sweats, nervousness, faintness, numbness) were identified as potential CINV predictors. This study demonstrates the usefulness of PC analysis, an unsupervised machine learning technique, to identify 7 anxiety characteristics that are useful as clinical CINV predictors. Clinicians should be aware of these characteristics when assessing CINV in patients on emetogenic chemotherapies.
|Item Type:||Journal Article|
|Subjects:||R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)|
|Divisions:||Faculty of Science > WMG (Formerly the Warwick Manufacturing Group)|
|Journal or Publication Title:||Journal of Clinical Psychopharmacology|
|Publisher:||Lippincott Williams & Wilkins|
|Page Range:||pp. 207-217|
|Access rights to Published version:||Restricted or Subscription Access|
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