Trending News: New Machine-Learning Model Can Predict Response in Patients with Myelodysplastic Syndrome

Top news of the day from across the health care landscape.

A new machine-learning model can predict the response rate to hypomethylating agents in patients with myelodysplastic syndrome, according to MD Magazine. Investigators from the Cleveland Clinic developed a clinical artificial intelligence model to predict response and resistance to hypomethylating agents after 90 days of initiating therapy. After promising trial results, investigators believe that the model can be used to develop novel trial design as well as to decide whether a patient who was predicted to respond should continue hypomethylating agent therapy.

The Typhoid Vaccine Acceleration Consortium is conducting a phase 3 study on the efficacy of a typhoid conjugate vaccine with children in Nepal, according to Contagion Live. The children have been randomly assigned 1 of 2 vaccines: typhoid conjugate vaccine or the Group A meningococcal vaccine. Preliminary results gathered via blood tests have shown that typhoid occurred in 38 children who received the Group A meningococcal vaccine and in 7 children who had received typhoid conjugate vaccine. According to the investigators, the typhoid conjugate vaccine has several advantages compared to previous vaccines, such as fewer necessary doses.

A new study has found that a quarter of patients with cancer in the United Kingdom experience avoidable delays in diagnosis due to staffing shortages within the National Health Service, according to The American Journal of Managed Care. The study included 14,259 patients diagnosed with cancer in 2014 whose diagnosis had unnecessary delays. Physicians reported nearly 3400 patients, or nearly 24%, who had their diagnoses avoidably delayed. According to the article, a major contributing factor to the findings is the shortage of medical staff necessary to expedite the diagnosis process.