A dynamic prediction engine to prevent chemotherapy-induced nausea and vomiting

A Randomized Clinical Trial Investigating an Integrated Nursing Educational Program to Mitigate Chemotherapy-Induced Nausea and Vomiting in Cancer Patients: The NIV-EC Trial

BACKGROUND

In addition to pharmacological prevention, chemotherapy-induced nausea and vomiting (CINV) can be mitigated through patient education; written supporting materials can be beneficial.

METHODS

This is a randomized, controlled trial which randomly assigned patients undergoing first chemotherapy cycle to receive oral information regarding CINV prevention and management (control arm) or oral information plus an informative booklet (experimental arm). Overall, 384 cancer patients fulfilling the following inclusion criteria were enrolled: age ≥18 years; life expectancy ≥6 months; no cognitive impairment; written informed consent. After the first cycle, CINV occurrence and its impact on daily activities were assessed using the Functional Living Index Emesis (FLIE).

RESULTS

Severe nausea was self-reported by 3.0% and 10.8% of patients in the experimental and control group, respectively (difference: 7.8%; 95% confidence interval: 2.3% to 13.1%). Moderate/high impact of nausea on daily activities was lower in patients also receiving the booklet than in the control group (4.2% and 10.1%, respectively; difference: 5.9%; 95% confidence interval: 0.3% to 11.5%). Vomiting was not statistically different between study arms.

CONCLUSIONS

This integrated nursing approach was effective in aiding cancer patients in CINV self-management. Although the beneficial effect was moderate, this intervention demands minimal resources in terms of costs and time.

External Application of Traditional Chinese Medicine in the Prevention and Treatment of Nausea and Vomiting Caused by Chemotherapy of Non-Small-Cell Lung Cancer: A RCT Study

Objective. To investigate the external application of traditional Chinese medicine in the prevention and treatment of nausea and vomiting caused by chemotherapy of non-small-cell lung cancer. Methods. This is a prospective trial. A total of 114 patients with non-small-cell lung cancer who were hospitalized in our hospital from October 2020 to March 2022 were selected and randomly divided into the research group and the control group at the ratio of 1 : 1. The control group received chemotherapy + tropisetron 4 mg intravenous drip 30 minutes before chemotherapy./day × 3 days. The research group received chemotherapy + intravenous infusion of tropisetron 4 mg 30 minutes before chemotherapy, once a day for 3 days + external application of traditional Chinese medicine for 5 days. The therapeutic effects of the two groups of patients were compared. Results. After treatment, the serum creatinine, urea nitrogen, and endogenous creatinine in the research group were better than those in the control group (t = 15.943, 12.005, and 13.325; $P=0.001$ , 0.005, and 0.005). After treatment, ALT and TBIL in the research group were superior to those in the control group (t = 11.583, 10.012, and 9.426; $P=0.001$ , 0.002, and 0.001). After treatment, the physiological status, social/family status, emotional status, and family status of the research group were significantly better than those in the control group (t = 16.274, 5.379, 5.142, and 8.153; $P=0.005$ , 0.000, 0.002, and 0.001). After treatment, the ECOG score and KPS score (82.46 ± 4.61) of the research group were significantly different from those of the control group (t = 11.913 and 9.357; $P=0.035$ and 0.001). The effective rate (χ2 = 11.724; $P=0.000$ ) of the research group was higher but the incidence of adverse reaction (χ2 = 4.294; $P=0.001$ ) was lower than that of the control group. Conclusion. External application of traditional Chinese medicine can significantly reduce nausea and vomiting caused by chemotherapy of non-small-cell lung cancer and can improve the patient’s body and quality of life, which is worthy of clinical research and promotion.

Artificial intelligence empowered Digital Health Technologies in Cancer Survivorship Care: a scoping review

Objective

The objectives of this systematic review are to describe features and specific application scenarios for current cancer survivorship care services of Artificial intelligence (AI)-driven digital health technologies (DHTs) and to explore the acceptance and briefly evaluate its feasibility in the application process.

Methods

Search for literatures published from 2010 to 2022 on sites MEDLINE, IEEE-Xplor, PubMed, Embase, Cochrane Central Register of Controlled Trials and Scopus systematically. The types of literatures include original research, descriptive study, randomized controlled trial, pilot study, and feasible or acceptable study. The literatures above described current status and effectiveness of digital medical technologies based on AI and used in cancer survivorship care services. Additionally, we use QuADS quality assessment tool to evaluate the quality of literatures included in this review.

Results

43 studies that met the inclusion criteria were analyzed and qualitatively synthesized. The current status and results related to the application of AI-driven DHTs in cancer survivorship care were reviewed. Most of these studies were designed specifically for breast cancer survivors’ care and focused on the areas of recurrence or secondary cancer prediction, clinical decision support, cancer survivability prediction, population or treatment stratified, anti-cancer treatment-induced adverse reaction prediction, and so on. Applying AI-based DHTs to cancer survivors actually has shown some positive outcomes, including increased motivation of patient-reported outcomes (PROs), reduce fatigue and pain levels, improved quality of life, and physical function. However, current research mostly explored the technology development and formation (testing) phases, with limited-scale population, and single-center trial. Therefore, it is not suitable to draw conclusions that the effectiveness of AI-based DHTs in supportive cancer care, as most of applications are still in the early stage of development and feasibility testing.

Conclusions

While digital therapies are promising in the care of cancer patients, more high-quality studies are still needed in the future to demonstrate the effectiveness of digital therapies in cancer care. Studies should explore how to develop uniform standards for measuring patient-related outcomes, ensure the scientific validity of research methods, and emphasize patient and health practitioner involvement in the development and use of technology.