Advancements in Treatment Protocols and Technologies
Cancer is a complex and multifaceted disease that requires a variety of treatments, medications, and technologies to be effectively treated. These treatments and technologies can potentially help treat patients and reduce medical errors. However, there are also potential risks and negative aspects that should be considered. There are many different types of cancer, each with its own unique set of symptoms and treatments. To effectively treat cancer, medical professionals must stay up to date on the latest treatments and innovations in technology.
Benefits and Potential Risks of Innovative Medical Interventions
CAR-T Therapy
The new treatment protocol for cancer is known as CAR-T therapy. CAR-T therapy is a form of immunotherapy that involves taking immune cells from the patient, engineering them to recognize and attack cancer cells, and then infusing them back into the patient (Mohanty et al., 2019). This treatment is very effective in treating certain types of cancer and can potentially be a significant advancement in cancer treatment. Nevertheless, it is also associated with a high risk of potentially serious side effects, such as cytokine release syndrome and neurological toxicity, which can be life-threatening.
Machine Learning
Another innovative technology that is beginning to gain recognition as a valuable tool in detecting and treating cancer is machine learning algorithms. Researchers use machine learning to mine vast amounts of genetic data and medical records to identify patterns that can predict cancer outcomes and develop more targeted therapies (Rafique et al., 2021). Such algorithms have been used to predict the risk of breast cancer recurrence and pancreatic cancer survival rates (Sharma et al., 2018). Incorrect data retrieval, algorithms that are not unbiased, and relying too heavily on technology can be hazardous to patient safety.
Targeted Therapy
Innovations in cancer medication include targeted therapies, which involve using drugs to specifically target and inhibit the growth of cancer cells. This medication has been found to provide some relief to those afflicted with certain types of cancer, with fewer side effects than chemotherapy (Mohanty et al., 2019). Though it can be pricey, the results are not always guaranteed.
Liquid Biopsy
Liquid biopsies are a new technology being developed for diagnosing cancer. They involve examining a patient’s blood or other body fluids for biomarkers associated with cancer. This technology has the potential to provide more accurate and faster diagnosis of cancer, potentially leading to earlier and more successful treatment (De Rubis et al., 2019). Although still in the early stages of development, liquid biopsies are not yet widely available.
The RN’s Role in Protecting Patient Safety
The role of the registered nurse (RN) in protecting the safety and well-being of patients receiving these treatments, medications, and tests is critical. The RN must monitor the patient closely for any signs of side effects or complications and any changes in the patient’s condition. The RN should also be aware of any potential risks associated with the treatment or medication and be prepared to report any changes or issues to other healthcare team members.
In machine learning, the nurse activates the care plan by placing patients at higher risk for cancer or recurrence on the appropriate testing protocol (Rafique et al., 2021). They ensure that labs and scans are completed on schedule and that the results are communicated to the patient and the provider team. Lastly, the RN should be prepared to educate and support the patient, their family, and caregivers.
References
De Rubis, G., Krishnan, S. R., & Bebawy, M. (2019). Liquid biopsies in cancer diagnosis, monitoring, and prognosis. Trends in Pharmacological Sciences, 40(3), 172-186. Web.
Mohanty, R., Chowdhury, C.R., Arega, S., Sen, P., Ganguly, P., & Ganguly, N. (2019). CAR T cell therapy: A new era for cancer treatment (Review). Oncology Reports, 42, 2183-2195. Web.
Rafique, R., Islam, S. M., & Kazi, J. U. (2021). Machine learning in the prediction of cancer therapy. Computational and Structural Biotechnology Journal, 19, 4003-4017, Web.
Sharma, S., A. Aggarwal, A., & Choudhury, T. (2018). Breast cancer detection using machine learning algorithms. International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS), 114-118.