Spotlight On Software Racial Bias Amid Concerns Over Lung Cancer Diagnoses
A new study suggests as many as 40% more Black male patients might have been diagnosed with breathing problems if software didn't have a built-in racial bias. Also: underuse of lung cancer CT scans; genetics in testing for prostate cancer; AI identifying heart failure; and more.
AP:
Black Men Were Likely Underdiagnosed With Lung Problems Because Of Bias In Software, Study Suggests
Racial bias built into a common medical test for lung function is likely leading to fewer Black patients getting care for breathing problems, a study published Thursday suggests. As many as 40% more Black male patients in the study might have been diagnosed with breathing problems if current diagnosis-assisting computer software was changed, the study said. (Stobbe, 6/1)
In other testing updates —
The Wall Street Journal:
The CT Scan Test For Lung Cancer That More People Should Get
There is a test that could diminish the toll of the nation’s top cancer killer—if people would use it. Doctors are pushing harder to make that happen. Lung cancer kills upward of 127,000 people in the U.S. each year. The toll has waned in recent years thanks to declining smoking rates and new treatments, but it remains the deadliest cancer for Americans by far. A CT scan can catch the disease early to help save lives. (Abbott, 6/1)
USA Today:
Are You Truly At Risk For Prostate Cancer? Adding Genetics May Give More Accurate PSA Tests
For decades, it has been known that prostate specific antigen ‒ or PSA ‒ tests are a flawed way to diagnose prostate cancer. Many men have a high PSA without having cancer. Others have low PSA that might lead to aggressive tumors being missed in screenings. This has led to overtreatment of men who didn't need biopsies or whose cancers would never have become dangerous and undertreatment of those whose tumors were missed. (Weintraub, 6/1)
Fox News:
AI Identified These 5 Types Of Heart Failure In New Study: 'Interesting To Differentiate'
Researchers from the University College London (UCL) recently used machine learning — a type of artificial intelligence — to pinpoint five distinct types of heart failure, with the goal of predicting the prognosis for the different kinds. "We sought to improve how we classify heart failure, with the aim of better understanding the likely course of disease and communicating this to patients," said lead author Professor Amitava Banerjee from UCL in a press release announcing the study. (Rudy, 6/2)
Also —
Stat:
Tempus Launches An AI ‘Assistant’ For Thousands Of Oncologists
Tempus, a company that combines DNA sequencing for cancer with artificial intelligence, said Thursday that it is launching a voice-and-text assistant called Tempus One that will give physicians much easier access to patient data. The AI assistant is being launched ahead of the annual meeting of the American Society of Clinical Oncology in Chicago. (Herper, 6/1)
KFF Health News:
'What The Health?' Podcast: Our 300th Episode!
This week, KFF Health News’ weekly policy news podcast — “What the Health?” — celebrates its 300th episode with a wide-ranging discussion of what’s happened in health policy since it launched in 2017 and what may happen in the next decade. (6/1)
