‘Winners’ and ‘Losers’; Mandated Sick Leave and Cancer Screening; More AI Advances

The verbiage surrounding a person’s experience with cancer or some other serious illness, particularly references to “battle,” has the unintended effect of portraying survivors as “winners” and those who die as “losers.” (NPR)

The annual cost of newly diagnosed cancer in adolescents and young adults is nearing $25 billion. (Teen Cancer America, Journal of Clinical Oncology)

A California couple has sued a fertility clinic for allegedly transferring an embryo with a rare stomach cancer gene and then falsifying records to cover up the mistake, which the parents believe puts their young son at risk of the cancer. (CNN)

Patients living in metropolitan areas with mandated sick-leave policies had significantly higher rates of cancer screening. (New England Journal of Medicine)

Merck announced the discontinuation of a phase III trial in castration-resistant prostate cancer after an interim analysis showed that the addition of pembrolizumab (Keytruda) to enzalutamide (Xtandi) and androgen deprivation therapy did not improve radiographic progression-free survival or overall survival (OS). In the same statement, Merck said a phase III trial of pembrolizumab plus chemotherapy did not improve OS in patients with progressive EGFR-mutant non-small cell lung cancer (NSCLC).

Merck got some good news for another phase III study that showed neoadjuvant pembrolizumab chemotherapy followed by adjuvant pembrolizumab improved event-free survival in resectable stage II, IIIA, or IIIB NSCLC versus neoadjuvant chemotherapy.

Sobi and Sanofi announced that a phase III trial of efanesoctocog alfa (recombinant Factor VIII) in children with hemophilia A met the primary endpoint of undetectable factor VIII inhibitors.

The largest-ever study of prostate cancer genetics in Black individuals identified new variants that could provide insight into the increased risk and poorer outcomes. (Keck School of Medicine at USC, European Urology)

Using doctors’ notes, an experimental artificial intelligence (AI) system accurately predicted the survival odds for patients with cancer. (University of British Columbia, JAMA Network Open)

In another advance for AI, machine learning showed promise for identifying cancer type-specific driver mutations that could guide development of new drugs and treatment strategies. (Pohang University of Science and Technology, Briefings in Bioinformatics)