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  • Tumor mutation burden is an imperfect predictor of response to immunotherapies. Mutations in regions of the genome unlikely to undergo loss during tumor evolution constitute a persistent tumor mutation burden that may drive sustained immunological tumor control in the context of cancer immunotherapy.

    Research Briefing
  • Six supplements widely marketed as cholesterol-lowering agents performed poorly compared with a low-dose statin — with a similar safety profile.

    • Karen O’Leary
    Research Highlight
  • Despite concerns that bariatric surgery may increase patients’ risk of esophageal or gastric cancers, a large retrospective study offers reassurance that this is not the case.

    • Karen O’Leary
    Research Highlight
  • A large study finds that offering cash for vaccination does not have unintended negative consequences — providing much-needed data and alleviating some longstanding concerns.

    • Karen O’Leary
    Research Highlight
  • Patients with BRAFV600E-mutated colorectal cancer have encouraging overall response rates to inhibition of PD-1, BRAF and MEK, with translational analyses suggesting that induction of tumor-intrinsic programs and immune programs contributes to improved outcomes via MAPK inhibition.

    • Jun Tian
    • Jonathan H. Chen
    • Ryan B. Corcoran
    Article Open Access
  • Genomic analyses in large cohorts of patients with cancer identify a new measure of tumor mutational burden, based on genomic regions that are unlikely to undergo loss, that is associated with therapeutic response to immunotherapy.

    • Noushin Niknafs
    • Archana Balan
    • Valsamo Anagnostou
    Article Open Access
  • The US Food and Drug Administration should address health misinformation through existing and new regulatory approaches, including modernizing product labeling, investing in infodemic surveillance and addressing the roles of the internet and social media.

    • Kushal T. Kadakia
    • Adam L. Beckman
    • Harlan M. Krumholz
    Comment
  • We are launching a series on evidence in medicine, to discuss new approaches to assessing the safety and efficacy of cutting-edge health technologies and treatments.

    Editorial
  • Artificial intelligence algorithms have had mixed success in health, in part because regulation prevents them from evolving at the necessary rate.

    • David W. Bates
    World View
  • A study showing feasibility and preliminary efficacy of off-the-shelf CAR T cells represents steady progress on the long road to clinical use.

    • Jennifer N. Brudno
    • James N. Kochenderfer
    News & Views
  • A gene-therapy treatment applied to the skin resulted in dramatic wound healing in patients with epidermolysis bullosa, a painful and debilitating skin condition.

    • Karen O’Leary
    Research Highlight
  • We demonstrate the power of a data-informed medicines-based approach in discovering the indirect effect of the COVID-19 pandemic on cardiovascular events using 1.32 billion records of dispensed medications in England, Scotland and Wales. We estimate that interruption of preventive care could result in more than 13,000 extra cardiovascular events.

    Research Briefing
  • By performing a large-scale biobank-based genome-wide association study, we identified a strong link between the underlying risk of cardiometabolic disease and patterns of lifelong medication use in hyperlipidemia, hypertension and type 2 diabetes. We discover hundreds of genetic predictors of medication use behavior and show medication-use-enhanced applications for polygenic prediction in cardiometabolic diseases.

    Research Briefing
  • The cause of pregnancy loss or perinatal death often remains unexplained, even following a standard autopsy. Comprehensive genomic investigation of pregnancy loss or perinatal death identifies a cause in over 50% of cases, particularly where congenital abnormalities are present. Causes of stillbirths without congenital abnormalities remain difficult to identify.

    Research Briefing
  • Clinical trials in neurological diseases often involve subjective, qualitative endpoints, such ‘by eye’ observations of movement. We developed an artificial intelligence–based method to analyze natural daily behavior data from people with Duchenne muscular dystrophy, using machine-learning algorithms to accurately predict their personal disease trajectories better than conventional clinical assessments.

    Research Briefing